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1 Semester - 2019 - Batch | Course Code |
Course |
Type |
Hours Per Week |
Credits |
Marks |
MTH111 | TEACHING TECHNOLOGY AND RESEARCH METHODOLOGY IN MATHEMATICS AND SERVICE LEARNING | Add On Courses | 3 | 2 | 100 |
MTH131 | REAL ANALYSIS | - | 4 | 4 | 100 |
MTH132 | ORDINARY AND PARTIAL DIFFERENTIAL EQUATIONS | - | 4 | 4 | 100 |
MTH133 | FLUID MECHANICS | - | 4 | 4 | 100 |
MTH141A | ELEMENTARY GRAPH THEORY | - | 4 | 4 | 100 |
MTH141B | DISCRETE MATHEMATICS | - | 4 | 4 | 100 |
MTH142A | NUMBER THEORY | - | 4 | 4 | 100 |
MTH142B | CRYPTOGRAPHY | - | 4 | 4 | 100 |
MTH151 | INTRODUCTION TO LATEX AND FOSS TOOLS | - | 3 | 3 | 50 |
2 Semester - 2019 - Batch | Course Code |
Course |
Type |
Hours Per Week |
Credits |
Marks |
MTH211 | STATISTICS | - | 3 | 2 | 100 |
MTH231 | GENERAL TOPOLOGY | - | 4 | 4 | 100 |
MTH232 | COMPLEX ANALYSIS | - | 4 | 4 | 100 |
MTH233 | ADVANCED ALGEBRA | - | 4 | 4 | 100 |
MTH234 | ADVANCED FLUID MECHANICS | - | 4 | 4 | 100 |
MTH235 | ALGORITHMIC GRAPH THEORY | - | 4 | 4 | 100 |
MTH251 | MATHEMATICS LAB USING PYTHON | - | 3 | 3 | 50 |
3 Semester - 2018 - Batch | Course Code |
Course |
Type |
Hours Per Week |
Credits |
Marks |
MTH311 | INTRODUCTION TO FREE AND OPEN-SOURCE SOFTWARE (FOSS) TOOLS : (GNU OCTAVE) | Add On Courses | 3 | 2 | 50 |
MTH331 | MEASURE THEORY AND LEBESGUE INTEGRATION | - | 4 | 4 | 100 |
MTH332 | NUMERICAL ANALYSIS | - | 4 | 4 | 100 |
MTH333 | CLASSICAL MECHANICS | - | 4 | 4 | 100 |
MTH334 | LINEAR ALGEBRA | - | 4 | 4 | 100 |
MTH335 | ADVANCED GRAPH THEORY | - | 4 | 4 | 100 |
MTH351 | NUMERICAL METHODS USING PYTHON | - | 3 | 3 | 50 |
MTH381 | INTERNSHIP IN PG COURSE | - | 0 | 2 | 0 |
4 Semester - 2018 - Batch | Course Code |
Course |
Type |
Hours Per Week |
Credits |
Marks |
MTH431 | DIFFERENTIAL GEOMETRY | - | 4 | 4 | 100 |
MTH432 | COMPUTATIONAL FLUID DYNAMICS | - | 4 | 4 | 100 |
MTH433 | FUNCTIONAL ANALYSIS | - | 4 | 4 | 100 |
MTH446 | ADVANCED LINEAR PROGRAMMING | - | 4 | 4 | 100 |
MTH448 | COMBINATORIAL MATHEMATICS | - | 4 | 4 | 100 |
MTH451 | NUMERICAL METHODS FOR BOUNDARY VALUE PROBLEM USING PYTHON | - | 3 | 3 | 50 |
MTH481 | PROJECT | - | 2 | 2 | 100 |
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Introduction to Program: | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
The M.Sc. course in Mathematics aims at developing mathematical ability in students with acute and abstract reasoning. The course will enable students to cultivate a mathematician?s habit of thought and reasoning and will enlighten students with mathematical ideas relevant for oneself and for the course itself.
COURSE DESIGN: Masters in Mathematics is a two year programme spreading over four semesters. In the first two semesters focus is on the basic courses in mathematics such as Algebra, Topology, Analysis, Discrete Mathematics and Number Theory/Cryptography along with the basic applied course ordinary and partial differential equations. In the third and fourth semester focus is on the special courses, elective courses and skill-based courses including Measure Theory and Lebesgue Integration, Functional Analysis, Computational Fluid Dynamics, Advanced Graph Theory. Classical Mechanics, Linear Algebra and Numerical Analysis. Important feature of the curriculum is that one course on the topic Fluid Mechanics and Graph Theory is offered in each semester with a project on these topics in the fourth semester, which will help the students to pursue the higher studies in these topics. To gain proficiency in software skills, Mathematics Lab papers are introduced in each semester. Special importance is given to the skill enhancement courses Teaching Technology and Research Methodology in Mathematics and service learning, Introduction to Free and Open-Source Software (FOSS) Tools: (GNU Octave) and Statistics. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Assesment Pattern | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Assessment Pattern
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Examination And Assesments | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
EXAMINATION AND ASSESSMENTS (Theory)
EXAMINATION AND ASSESSMENTS (Practicals) The course is evaluated based on continuous internal assessment (CIA). The parameters for evaluation under each component and the mode of assessment are given below:
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MTH111 - TEACHING TECHNOLOGY AND RESEARCH METHODOLOGY IN MATHEMATICS AND SERVICE LEARNING (2019 Batch) | |
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
Max Marks:100 |
Credits:2 |
Course Objectives/Course Description |
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Course Description: This course is intended to assist the students in acquiring necessary skills on the use of modern technology in teaching. Also, the students are exposed to the principles, procedures and techniques of planning and implementing the research project.Through service learning they will apply the knowledge in real-world situations and benefit the community.
Course Objective: This course will help the learner to: COBJ1. acquire skills in using technology effectively for teaching COBJ2. know the general research method and methods of research that can be employed for research in Mathematics COBJ3. experience service learning |
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Course Outcome |
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After completing this course, the student will be able to: CO1. gain necessary skills on the use of modern technology in teaching. CO2. foster a clear understanding about research design that enables students in analyzing and evaluating the published research. CO3. understand the components and techniques of effective report writing. CO4. obtain necessary skills in understanding the mathematics research articles CO5. acquire skills in preparing scientific documents using MS Word, Mathtype, Open Office Math editor, yEd Graph Editor and LaTeX. CO6. strengthen personal character and sense of social responsibility through service learning module. |
Unit-1 |
Teaching Hours:10 |
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Teaching Technology
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Development of concept of teaching, Teaching skills, Chalk board skills, Teaching practices, Effective teaching, Models of teaching, Teaching aids(Audio-Visual), Teaching aids(projected and non-projected), Communication skills, Feed back in teaching, Teacher’s role and responsibilities, Information technology for teaching. | |||||||||||||||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:10 |
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Research Methodology
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Introduction to research and research methodology, Scientific methods, Choice of research problem, Literature survey and statement of research problem, Reporting of results, Roles and responsibilities of research student and guide. | |||||||||||||||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:10 |
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Mathematical research methodology
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Introducing mathematics Journals, Reading a Journal article, Mathematics writing skills. -Standard Notations and Symbols, Using Symbols and Words, Organizing a paper, Defining variables, Symbols and notations, Different Citation Styles, IEEE Referencing Style in detail. Package for Mathematics Typing, MS Word, Math Type, Open Office Math Editor, Tex, yEd Graph Editor, Tex in detail, Installation and Set up, Text, Formula, Pictures and Graphs, Producing various types of documents using TeX. | |||||||||||||||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:15 |
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Service Learning
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Guidelines for service learning: One among the following can be considered as a service learning module:
After deciding, get approval from your respective mentors.
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Text Books And Reference Books: . | |||||||||||||||||||||||||||||||||||||||||
Essential Reading / Recommended Reading
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Evaluation Pattern Evaluation and Assessment ( Service Learning ) You will be graded on the quality of your work rather than on the quantity of hours. You need to provide with the following items:
Perform the service. Make sure you answer each of the following questions every time you perform the service. Write your diary based on the following:
Service-Learning Student Diary Format
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MTH131 - REAL ANALYSIS (2019 Batch) | |||||||||||||||||||||||||||||||||||||||||
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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Course Description: This course will help students to understand the concepts of functions of single and several variables. This course includes such concepts as Riemann-Stieltjes integral, sequences and series of functions, Special Functions, and the Implicit Function Theorem.
Course objectives: This course will help the learner to COBJ1. Develop in a rigorous and self-contained manner the elements of real variable functions COBJ2. Integrate functions of a real variable in the sense of Riemann – Stieltjes COBJ3. Classify sequences and series of functions which are pointwise convergent and uniform Convergent COBJ4. Demonstrate the ability to manipulate and use of special functions COBJ5. Use and operate functions of several variables. |
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Course Outcome |
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On successful completion of the course, the students should be able to CO1. determine the Riemann-Stieltjes integrability of a bounded function. CO2. recognize the difference between pointwise and uniform convergence of sequence/series of functions. CO3. illustrate the effect of uniform convergence on the limit function with respect to continuity, differentiability, and integrability. CO4. analyze and interpret the special functions such as exponential, logarithmic, trigonometric and Gamma functions. CO5. gain in depth knowledge on functions of several variables and the use of Implicit Function Theorem. |
UNIT 1 |
Teaching Hours:15 |
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The Riemann-Stieltjes Integration
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Definition and Existence of Riemann-Stieltjes Integral, Linearity Properties of Riemann-Stieltjes Integral, The Riemann-Stieltjes Integral as the Limit of Sums, Integration, and Differentiation, Integration of Vector-valued Functions, Rectifiable Curves. | |||||||||||||||||||||||||||||
UNIT 2 |
Teaching Hours:15 |
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Sequences and Series of Functions
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Pointwise and uniform convergence, Uniform Convergence: Continuity, Integration and Differentiation, Equicontinuous Families of Functions, The Stone-Weierstrass Theorem | |||||||||||||||||||||||||||||
UNIT 3 |
Teaching Hours:15 |
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Some Special Functions
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Power Series, The Exponential and Logarithmic Functions, The Trigonometric Functions, The Algebraic Completeness of the Complex Field, Fourier Series, The Gamma Function. | |||||||||||||||||||||||||||||
UNIT 4 |
Teaching Hours:15 |
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Functions of Several Variables
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Linear Transformations, Differentiation, The Contraction Principle, The Inverse Function Theorem, The Implicit Function Theorem, The Rank Theorem, Determinants, Derivatives of Higher Order, Differentiation of Integrals. | |||||||||||||||||||||||||||||
Text Books And Reference Books: W. Rudin, Principles of Mathematical Analysis, 3rd ed., New Delhi: McGraw-Hill (India), 2016. | |||||||||||||||||||||||||||||
Essential Reading / Recommended Reading
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Evaluation Pattern
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MTH132 - ORDINARY AND PARTIAL DIFFERENTIAL EQUATIONS (2019 Batch) | |||||||||||||||||||||||||||||
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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Course description : This helps students understand the beauty of the important branch of mathematics, namely, differential equations. This course includes a study of second order linear differential equations, adjoint and self-adjoint equations, Eigen values and Eigen vectors of the equations, power series method for solving differential equations, second order partial differential equations like wave equation, heat equation, Laplace equations and their solutions by Eigen function method. Course objectives : This course will help the learner to COBJ1. Solve adjoint differential equations, hypergeometric differential equation and power series. COBJ2. Solve partial differential equation of the type heat equation, wave equation and Laplace equations. COBJ3. Also solving initial boundary value problems. |
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Course Outcome |
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On successful completion of the course, the students should be able to CO1. Understand concept of Linear differential equation, Fundamental set Wronskian. CO2. Understand the concept of Liouvilles theorem, Adjoint and Self Adjoint equation, Lagrange's Identity, Green’s formula, Eigen value and Eigen functions. CO3. Identify ordinary and singular point by Frobenius Method, Hyper geometric differential equation and its polynomial. CO4. Understand the basic concepts and definition of PDE and also mathematical models representing stretched string, vibrating membrane, heat conduction in rod. CO5. Demonstrate on the canonical form of second order PDE. CO6. Demonstrate initial value boundary problem for homogeneous and non-homogeneous PDE. CO7. Demonstrate on boundary value problem by Dirichlet and Neumann problem. |
UNIT 1 |
Teaching Hours:20 |
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Linear Differential Equations
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Linear differential equations, fundamental sets of solutions, Wronskian, Liouville’s theorem, adjoint and self-adjoint equations, Lagrange identity, Green’s formula, zeros of solutions, comparison and separation theorems. Legendre, Bessel's, Chebeshev's, Eigen values and Eigen functions, related examples. | |||||||||||||||||||||||||||||
UNIT 2 |
Teaching Hours:10 |
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Power series solutions
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Solution near an ordinary point and a regular singular point by Frobenius method, solution near irregular singular point, hypergeometric differential equation and its polynomial solutions, standard properties. | |||||||||||||||||||||||||||||
UNIT 3 |
Teaching Hours:15 |
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Partial Differential Equations
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Formation of PDE, solutions of first and second order PDE, mathematical models representing stretched string, vibrating membrane, heat conduction in solids and the gravitational potentials, second-order equations in two independent variables, canonical forms and general solution. | |||||||||||||||||||||||||||||
UNIT 4 |
Teaching Hours:15 |
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Solutions of PDE
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The Cauchy problem for homogeneous wave equation, D’Alembert’s solution, domain of influence and domain of dependence, the Cauchy problem for non-homogeneous wave equation, the method of separation of variables for the one-dimensional wave equation and heat equation. Boundary value problems, Dirichlet and Neumann problems in Cartesian coordinates, solution by the method of separation of variables. Solution by the method of eigenfunctions. | |||||||||||||||||||||||||||||
Text Books And Reference Books:
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Essential Reading / Recommended Reading
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Evaluation Pattern
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MTH133 - FLUID MECHANICS (2019 Batch) | |||||||||||||||||||||||||||||
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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Course Description: This course aims at introducing the fundamentals of fluid mechanics. This course aims at imparting the knowledge on tensors, kinematics of fluid, incompressible flow, boundary layer flows and classification of non-Newtonian fluids.
Course objectives: This course will help the learner to COBJ1. understand the basic concept of tensors and their representative COBJ2. physics and mathematics behind the basics of fluid mechanics COBJ3. familiar with two or three dimensional incompressible flows COBJ4. classifications of non-Newtonian fluids COBJ5. familiar with standard two or three dimensional viscous flows |
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Course Outcome |
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On successful completion of the course, the students should be able to CO1. confidently manipulate tensor expressions using index notation, and use the divergence theorem and the transport theorem. CO2. able to understand the basics laws of Fluid mechanics and their physical interpretations. CO3. able to understand two or three dimension flows incompressible flows. CO4. able to understand the viscous flows, their mathematical modelling and physical interpretations. |
Unit-1 |
Teaching Hours:15 |
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Cartesian tensors and continuum hypothesis
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Cartesian tensors: Cartesian tensors, basic properties, transpose, symmetric and skew symmetric tensors, gradient, divergence and curl in tensor calculus, integral theorems. Continuum hypothesis: deformation gradient, strain tensors, infinitesimal strain, compatibility relations, principal strains, material and local time derivatives, transport formulas, stream lines, path lines. | |||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:20 |
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Stress, Strain and basic physical laws
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Stress and Strain: stress components and stress tensor, normal and shear stresses, principal stresses, transformation of the rate of strain and stress, relation between stress and rate of strain. Fundamental basic physical laws: The equation of continuity, conservation of mass, equation of motion (Navier-Stokes equations), conservation of momentum, the energy equation, conservation of energy. | |||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:15 |
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One, Two and Three Dimensional Invisid Incompressible Flow
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Bernoulli equation, applications of Bernoulli equation, circulation theorems, circulation concept, Kelvin’s theorem, constancy of circulation, Laplace equations, stream functions in two and three dimensional motion. Two dimensional flow: Rectilinear flow, source and sink, the theorem of Blasius. | |||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:10 |
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Two Dimensional Flows of Viscous Fluid
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Flow between parallel flat plates, Couette flow, plane Poiseuille flow, the Hagen-Poiseuille flow, flow between two concentric rotating cylinders. | |||||||||||||||||||||||||||||
Text Books And Reference Books:
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Essential Reading / Recommended Reading
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Evaluation Pattern Examination and Assessments
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MTH141A - ELEMENTARY GRAPH THEORY (2019 Batch) | |||||||||||||||||||||||||||||
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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Course Description: This course is an introductory course to the basic concepts of Graph Theory. This includes definition of graphs, vertex degrees, directed graphs, trees, distances, connectivity and paths. Course objectives:This course will help the learner to COBJ1. know the history and development of graph theory COBJ2. understand all the elementary concepts and proof techniques in Graph Theory |
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Course Outcome |
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Course outcomes: The successful completion of this course the students will be able to: CO1. write precise and accurate mathematical definitions of basics concepts in graph theory CO3. provide appropriate examples and counterexamples to illustrate the basic concepts CO3. demonstrate and apply various proof techniques in proving theorems in graph theory CO4. showcase mastery in using graph drawing tools |
Unit-1 |
Teaching Hours:15 |
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Introduction to Graphs
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Definition and introductory concepts, Graphs as Models, Matrices and Isomorphism, Decomposition and Special Graphs, Connection in Graphs, Bipartite Graphs, Eulerian Circuits. | |||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:15 |
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Vertex Degrees and Directed Graphs
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Counting and Bijections, Extremal Problems, Graphic Sequences, Directed Graphs, Vertex Degrees, Eulerian Digraphs, Orientations and Tournaments. | |||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:15 |
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Trees and Distance
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Properties of Trees, Distance in Trees and Graphs, Enumeration of Trees, Spanning Trees in Graphs, Decomposition and Graceful Labellings, Minimum Spanning Tree, Shortest Paths. | |||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:15 |
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Connectivity and Paths
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Connectivity, Edge - Connectivity, Blocks, 2 - connected Graphs, Connectivity in Digraphs, k - connected and k-edge-connected Graphs, Maximum Network Flow, Integral Flows. | |||||||||||||||||||||||||||||
Text Books And Reference Books: D.B. West, Introduction to Graph Theory, New Delhi: Prentice-Hall of India, 2011. | |||||||||||||||||||||||||||||
Essential Reading / Recommended Reading
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Evaluation Pattern
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MTH141B - DISCRETE MATHEMATICS (2019 Batch) | |||||||||||||||||||||||||||||
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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Course Description: This course aims at providing the necessary background for the students to gain proficiency in abstraction, notation, and critical thinking in the Discrete Mathematics.
Course objectives:This course will help the learner to be familiar with: COBJ1. mathematical logic and the rules of inference COBJ2. concepts of sets, relation and functions COBJ3. the combinatorial techniques of enumeration COBJ4. generating functions, recurrence relations and their applications |
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Course Outcome |
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The successful completion of this course will enable the students to: CO1. construct mathematical arguments using logical connectives and quantifiers. CO2. verify the correctness of an argument using propositional and predicate logic and truth tables. CO3. construct proofs using direct proof, proof by contraposition, proof by contradiction, proof by cases, and mathematical induction. CO4. understand the counting techniques and apply CO5. gain proficiency in handling the properties connected to the relations. |
Unit-1 |
Teaching Hours:15 |
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Foundations
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Propositional Logic, Propositional Equivalences, Predicates and Quantifiers, Nested Quantifiers, Rules of Inference, Introduction to Proofs, Proof Methods and Strategy. | |||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:15 |
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Counting
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The Basics of Counting, The Pigeonhole Principle, Permutations and Combinations, Binomial Coefficients, Generalized Permutations and Combinations, Generating Permutations and Combinations. | |||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:15 |
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Advanced Counting Techniques
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Recurrence Relations, Solving Linear Recurrence Relations, Divide-and-Conquer Algorithms, Generating Functions, Inclusion-Exclusion, Applications of Inclusion-Exclusion | |||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:15 |
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Relations
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Relations and Their Properties, n-ary Relations and Their Applications, Representing Relations, Closures of Relations, Equivalence Relations, Partial Orderings | |||||||||||||||||||||||||||||
Text Books And Reference Books: Kenneth H. Rosen, “Discrete mathematics and its applications”, 6th Edition, WCB/McGraw- Hill, 2007. | |||||||||||||||||||||||||||||
Essential Reading / Recommended Reading
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Evaluation Pattern
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MTH142A - NUMBER THEORY (2019 Batch) | |||||||||||||||||||||||||||||
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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Course Description: This course is concerned with the basics of analytical number theory. Topics such as divisibility, congruence’s, quadratic residues and functions of number theory are covered in this course. Some of the applications of the said concepts are also included. Course objectives:This course will help the learner to be familiar with: COBJ1. all the elementary concepts and proof techniques in Number Theory |
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Course Outcome |
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On successful completion of this course, students will be able to CO1. Define and interpret the concepts of divisibility, congruence, greatest common divisor, prime, and prime-factorization, CO2. Solve linear Diophantine equations and congruences of various types, and use the theory of congruences in applications. CO3. Prove and apply properties of multiplicative functions such as the Euler phi-function and of quadratic residues. CO4. Apply the Law of Quadratic Reciprocity and other methods to classify numbers as primitive roots, quadratic residues, and quadratic non-residues, CO5. Produce rigorous arguments (proofs) centered on the material of number theory, most notably in the use of Mathematical Induction and/or the Well Ordering Principle in the proof of theorems. |
UNIT 1 |
Teaching Hours:10 |
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Divisibility
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The division algorithm, the Euclidean algorithm, the unique factorization theorem, Euclid’s theorem, linear Diophantine equations. | |||||||||||||||||||||||||||||
UNIT 2 |
Teaching Hours:20 |
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Congruences
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Definitions and properties, complete residue system modulo m, reduced residue system modulo m, Euler’s φ function, Fermat’s theorem, Euler’s generalization of Fermat’s theorem, Wilson’s theorem, solutions of linear congruences, the Chinese remainder theorem, solutions of polynomial congruences, prime power moduli, power residues, number theory from algebraic point of view, groups, rings and fields. | |||||||||||||||||||||||||||||
UNIT 3 |
Teaching Hours:18 |
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Quadratic residues
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Legendre symbol, Gauss’s lemma, quadratic reciprocity, the Jacobi symbol, binary quadratic forms, equivalence and reduction of binary quadratic forms, sums of two squares, positive definite binary quadratic forms | |||||||||||||||||||||||||||||
UNIT 4 |
Teaching Hours:12 |
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Some functions of number theory
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Greatest integer function, arithmetic functions, the Mobius inversion formula. | |||||||||||||||||||||||||||||
Text Books And Reference Books: Ivan Niven, Herbert S. Zuckerman and Hugh L. Montgomery, An introduction to the theory of numbers, John Wiley, 2004. | |||||||||||||||||||||||||||||
Essential Reading / Recommended Reading
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Evaluation Pattern
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MTH142B - CRYPTOGRAPHY (2019 Batch) | |||||||||||||||||||||||||||||
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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Course Description: Cryptography is the science of encrypting and decrypting any information. This is one of the finest applications of Number Theory. In this course, the fundamentals of cryptography are dealt with. As a piece of information is expressed through symbols, representing it in a way that only the intended party would know it is the best part of encryption and decryption. As the world is flooded with information, generation, transfer and acquisition of it is very important. Students with basic background in Number Theory can take up this course. Course objectives:This course will help the learner to be familiar with: COBJ1. the fundamental notions in cryptography COBJ2. the foundational Number Theory required for handling encryption and decryption techniques in Cryptography |
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Course Outcome |
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Course outcomes: The successful completion of this course, will enable the students to: CO1. use Number Theory for encryption and decryption CO2. encrypt and Decrypt message CO3. know the difference between private key and public key cryptographies CO4. understand a number of privacy mechanisms |
Unit-1 |
Teaching Hours:15 |
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Some Topics in Elementary Number Theory
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Elementary concepts of number theory, time estimates for doing arithmetic, divisibility and the Euclidian algorithm, congruences, some applications to factoring. Finite fields and quadratic residues: Finite fields, quadratic residues and reciprocity. | |||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:15 |
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Cryptography
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Some simple cryptosystems, enciphering matrices. | |||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:15 |
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Public Key
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The idea of public key cryptography, RSA, discrete log., knapsack, zero-knowledge protocols and oblivious transfer.. | |||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:15 |
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Elliptic Curves
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Basic facts, elliptic curve cryptosystems, elliptic curve primality test, elliptic curve factorization. | |||||||||||||||||||||||||||||
Text Books And Reference Books: N. Koblitz, A course in number theory and cryptography, Graduate Texts in Mathematics, No.114, Springer-Verlag, 1987 | |||||||||||||||||||||||||||||
Essential Reading / Recommended Reading
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Evaluation Pattern
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MTH151 - INTRODUCTION TO LATEX AND FOSS TOOLS (2019 Batch) | |||||||||||||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:50 |
Credits:3 |
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Course Objectives/Course Description |
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Course Description: This course aims as introducing LaTeX and the mathematical software packages “WxMaxima” and “Scilab”, for learning basic operation on matrix manipulation, plotting graphs etc.,. These software packages will also help students to solve problems / applied problems on Mathematics. Course objectives: This course will help the learner to: COBJ1. understand the basics of LaTeX and its implementation COBJ2. use the FOSS tools WxMaxima and Scilab effectively |
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Course Outcome |
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On successful completion of the course, the students should be able to CO1. use LaTeX effectively CO2. Use the basic commands in WxMaxima including the 2D and 3D plots CO3. Have a strong command on the inbuilt commands required for the learning and analyzing mathematics CO4. Solve problems / applied problems on mathematics by using Scilab. |
Unit-1 |
Teaching Hours:10 |
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Introduction to LaTeX
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Document Markup - The absolute basics of LaTeX - The TeX conceptual model of typesetting - Text elements - Tables and Figures - Math - References. | |||||||||||||||||||||||||
Unit-2 |
Teaching Hours:20 |
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Introduction to WxMaxima and Scilab
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Introduction to WxMaxima Interface - Maxima expressions, numbers, operators, constants and reserved words - input and output in WxMaxima - 2D and 3D plots in WxMaxima - symbolic computations in WxMaxima - Solving Ordinary differential equations in WxMaxima - Introduction to Scilab and commands connected with Matrices - Computations with Matrices - 2D and 3D Plots - Script Files and Function Files | |||||||||||||||||||||||||
Unit-3 |
Teaching Hours:15 |
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Solving problems using Scilab / WxMaxima
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Solving systems of equation and explain consistence - Find the values of some standard trigonometric functions in radians as well as in degree - Create polynomials of different degrees and find its real roots - Display Fibonacci series using Scilab program - Display non-Fibonacci series using Scilab program. | |||||||||||||||||||||||||
Text Books And Reference Books:
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Essential Reading / Recommended Reading
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Evaluation Pattern The course is evaluated based on continuous internal assessment (CIA). The parameters for evaluation under each component and the mode of assessment are given below:
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MTH211 - STATISTICS (2019 Batch) | |||||||||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:100 |
Credits:2 |
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Course Objectives/Course Description |
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Course Description: This course aims at teach the students the idea of discrete and continuous random variables, Probability theory, in-depth treatment of discrete random variables and distributions, with some introduction to continuous random variables and introduction to estimation and hypothesis testing. Course Objective: This course will help the learner to: COBJ1. be proficient in understanding and solving problems on random variables COBJ2. efficiently solve problems involving probability distributions |
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Course Outcome |
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Course outcomes: After completing this course, the student will be able to: CO1. Understand random variables and probability distributions. CO2. Distinguish discrete and continuous random variables. CO3. Obtain ability compute Expected value and Variance of discrete random variable. CO4. Acquire knowledge in using Binomial distribution, Poisson distribution etc., CO5. Define inferential statistics. CO6. Effectively use sampling distributions in inferential statistics. |
Unit-1 |
Teaching Hours:15 |
Random Variables and Expectation
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Discrete and continuous random variables, distribution functions, probability mass and density functions, bivariate distributions, marginal and conditional distributions, expected value of a random variable, independence of random variables, conditional expectations, covariance matrix, correlation coefficients and regression, Chebyshev’s inequality, moments, moment generating functions, characteristic functions. | |
Unit-2 |
Teaching Hours:15 |
Probability Distributions
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Probability: Sample spaces, events, probability of an event, theorems on probability, conditional probability, independent events, Bayes theorem. Boole’s inequality. Discrete Probability Distribution: Introduction, uniform, Bernoulli, Binomial, negative Binomial, geometric, Hypergeometric and Poisson distribution. Continuous Probability Distributions: Introduction, uniform, gamma, exponential, beta and normal distributions. | |
Unit-3 |
Teaching Hours:15 |
Sampling distributions
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t, F and chi-square distributions, standard errors and large sample distributions. | |
Text Books And Reference Books:
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Essential Reading / Recommended Reading
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Evaluation Pattern . | |
MTH231 - GENERAL TOPOLOGY (2019 Batch) | |
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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Course Description: This course deals with the essentials of topological spaces and their properties in terms of continuity, connectedness, compactness etc.,. Course objectives: This course will help the learner to: COBJ1. provide precise definitions and appropriate examples and counter examples of fundamental concepts in general topology COBJ2. acquire knowledge about generalization of the concept of continuity and related properties COBJ3. appreciate the beauty of deep mathematical results such as Uryzohn’s lemma and understand and apply various proof techniques |
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Course Outcome |
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On successful completion of the course, the students should be able to CO1. define topological spaces, give examples and counterexamples on concepts like open sets, basis and subspaces CO2. establish equivalent definitions of continuity and apply the same in proving theorems CO3. understand the concepts of metrizability, connectedness, compactness and learn the related theorems |
Unit-1 |
Teaching Hours:15 |
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Topological Spaces
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Elements of topological spaces, basis for a topology, the order topology, the product topology on X x Y, the subspace topology, Closed sets and limit points. | |||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:15 |
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Continuous Functions
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Continuous functions, the product topology, metric topology. | |||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:15 |
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Connectedness and Compactness
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Connected spaces, connected subspaces of the Real Line, components and local connectedness, compact spaces, Compact Subspaces of the Real Line, limit point compactness, local compactness. | |||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:15 |
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Countability and Separation Axioms
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he countability axioms, the separation axioms, normal spaces, the Urysohn lemma, the Urysohn metrization theorem, Tietze extension theorem. | |||||||||||||||||||||||||||||
Text Books And Reference Books: J.R. Munkres,Topology, Second Edition, Prentice Hall of India, 2007. | |||||||||||||||||||||||||||||
Essential Reading / Recommended Reading
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Evaluation Pattern
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MTH232 - COMPLEX ANALYSIS (2019 Batch) | |||||||||||||||||||||||||||||
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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Course Description: This course will help students learn about the essentials of complex analysis. This course includes important concepts such as power series, analytic functions, linear transformations, Laurent’s series, Cauchy’s theorem, Cauchy’s integral formula, Cauchy’s residue theorem, argument principle, Schwarz lemma , Rouche’s theorem and Hadamard’s 3-circles theorem. Course objectives: This course will help the learner to COBJ1. enhance the understanding the advanced concepts in Complex Analysis COBJ2. Acquire problem solving skills in Complex Analysis. |
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Course Outcome |
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On successful completion of the course, the students should be able to CO1. apply the concept and consequences of analyticity and the Cauchy-Riemann equations and of results on harmonic and entire functions including the fundamental theorem of algebra CO2. compute complex contour integrals in several ways: directly using parameterization, using the Cauchy-Goursat theorem Evaluate complex contour integrals directly and by the fundamental theorem, apply the Cauchy integral theorem in its various versions, and the Cauchy integral formula CO3. represent functions as Taylor, power and Laurent series, classify singularities and poles, find residues and evaluate complex integrals using the residue theorem CO4. use conformal mappings and know about meromorphic functions |
Unit-1 |
Teaching Hours:18 |
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Power Series
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Power series, radius and circle of convergence, power series and analytic functions, Line and contour integration, Cauchy’s theorem, Cauchy integral formula, Cauchy integral formula for derivatives, Cauchy integral formula for multiply connected domains, Morera’s theorem, Gauss mean value theorem, Cauchy inequality for derivatives, Liouville’s theorem, fundamental theorem of algebra, maximum and minimum modulus principles. | |||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:15 |
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Singularities
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Taylor’s series, Laurent’s series, zeros of analytical functions, singularities, classification of singularities, characterization of removable singularities and poles. | |||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:15 |
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Mappings
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Rational functions, behavior of functions in the neighborhood of an essential singularity, Cauchy’s residue theorem, contour integration problems, Mobius transformation, conformal mappings | |||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:12 |
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Meromorphic functions
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Meromorphic functions and argument principle, Schwarz lemma, Rouche’s theorem, convex functions and their properties, Hadamard 3-circles theorem. | |||||||||||||||||||||||||||||
Text Books And Reference Books:
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Essential Reading / Recommended Reading
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Evaluation Pattern
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MTH233 - ADVANCED ALGEBRA (2019 Batch) | |||||||||||||||||||||||||||||
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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Course Description: This course enables students to understand the intricacies of advanced areas in algebra. This includes a study of advanced group theory, Euclidean rings, polynomial rings and Galois theory. Course objectives: This course will help the learner to COBJ1. enhance the knowledge on advanced level algebra COBJ2. understand the proof techniques for the theorems on advanced group theory, Rings and Galois Theory |
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Course Outcome |
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On successful completion of the course, the students should be able to CO1. Demonstrate knowledge of conjugates, the Class Equation and Sylow theorems CO2. Demonstrate knowledge of polynomial rings and associated properties CO3. Derive and apply Gauss Lemma, Eisenstein criterion for irreducibility of rationals CO4. Demonstrate the characteristic of a field and the prime subfield; CO5. Demonstrate Factorization and ideal theory in the polynomial ring; the structure of a primitive polynomials; Field extensions and characterization of finite normal extensions as splitting fields; The structure and construction of finite fields; Radical field extensions;Galois group and Galois theory |
Unit-1 |
Teaching Hours:15 |
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Advanced Group Theory
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Automorphisms, Cayley’s theorem, Cauchy’s theorem, permutation groups, symmetric groups, alternating groups, simple groups, conjugate elements and class equations of finite groups, Sylow theorems, direct products, finite abelian groups, solvable groups | |||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:15 |
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Rings
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Euclidean Ring, Polynomial rings, polynomials rings over the rational field, polynomial rings over commutative rings, | |||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:15 |
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Fields
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Extension fields, roots of polynomials, construction with straightedge and compass, more about roots. | |||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:15 |
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Galois theory
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The elements of Galois theory, solvability by radicals, Galois group over the rationals, finite fields. | |||||||||||||||||||||||||||||
Text Books And Reference Books: I. N. Herstein, Topics in algebra, Second Edition, John Wiley and Sons, 2007. | |||||||||||||||||||||||||||||
Essential Reading / Recommended Reading
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Evaluation Pattern
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MTH234 - ADVANCED FLUID MECHANICS (2019 Batch) | |||||||||||||||||||||||||||||
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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Course Description: This course helps the students to understand the basic concepts of heat transfer, types of convection shear and thermal instability of linear and non-linear problems. This course also includes the analysis Prandtlboundry layer, porous media and Non-Newtonian fluid. Course objectives: This course will help the learner to COBJ1. understand the different modes of heat transfer and their applications. COBJ2. understand the importance of doing the non-dimensionalization of basic equations. COBJ3. understand the boundary layer flows. COBJ4. familiarity with porous medium and non-Newtonian fluids |
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Course Outcome |
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On successful completion of the course, the students should be able to CO1. understand the basic laws of heat transfer and understand the fundamentals of convective heat transfer process. CO2. solve Rayleigh - Benard problem and their physical phenomenon. CO3. solve and understand different boundary layer problems CO4. give an introduction to the basic equations with porous medium and solution methods for mathematical modeling of viscous fluids and elastic matter |
UNIT 1 |
Teaching Hours:15 |
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Dimensional Analysis and Similarity
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Introduction to heat transfer, different modes of heat transfer- conduction, convection and radiation, steady and unsteady heat transfer, free and forced convection. Non-dimensional parameters determined from differential equations – Buckingham’s Pi Theorem – Non-dimensionalization of the Basic Equations - Non-dimensional parameters and dynamic similarity. | |||||||||||||||||||||||||||||
UNIT 2 |
Teaching Hours:20 |
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Heat Transfer and Thermal Instability
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Shear Instability: Stability of flow between parallel shear flows - Squire’s theorem for viscous and inviscid theory – Rayleigh stability equation – Derivation of Orr-Sommerfeld equation assuming that the basic flow is strictly parallel. Basic concepts of stability theory – Linear and Non-linear theories – Rayleigh Benard Problem – Analysis into normal modes – Principle of Exchange of stabilities – first variation principle – Different boundary conditions on velocity and temperature. | |||||||||||||||||||||||||||||
UNIT 3 |
Teaching Hours:10 |
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Prandtl Boundry Layer
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Boundary layer concept, the boundary layer equations in two-dimensional flow, the boundary layer along a flat plate, the Blasius solution. Stagnation point flow. Falkner-Skan family of equations. | |||||||||||||||||||||||||||||
UNIT 4 |
Teaching Hours:15 |
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Porous Media and Non - Newtonian Fluids
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Introduction to porous medium, porosity, Darcy’s Law, Extension of Darcy Law – accelerations and inertial effects, Brinkman’s equation, effects of porosity variations, Bidisperse porous media. Constitutive equations of Maxwell, Oldroyd, Ostwald , Ostwald de waele, Reiner – Rivlin and Micropolar fluid. Weissenberg effect and Tom’s effect.Equation of continuity, Conservation of momentum for non-Newtonian fluids. | |||||||||||||||||||||||||||||
Text Books And Reference Books:
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Essential Reading / Recommended Reading
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Evaluation Pattern
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MTH235 - ALGORITHMIC GRAPH THEORY (2019 Batch) | |||||||||||||||||||||||||||||
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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Course description: This course helps the students to understand the colouring of graphs, Planar graphs, edges and cycles. Course objectives: This course will help the learner to COBJ1.Construct examples and proofs pertaining to the basic theorems COBJ2. Apply the theoretical knowledge and independent mathematical thinking in creative investigation of questions in graph theory COBJ3. Write graph theoretic ideas in a coherent and technically accurate manner. |
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Course Outcome |
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On successful completion of the course, the students should be able to CO1. understand the basic concepts and fundamental results in matching, domination, coloring and planarity. CO2. reason from definitions to construct mathematical proofs CO3. obtain a solid overview of the questions addressed by graph theory and will be exposed to emerging areas of research |
Unit-1 |
Teaching Hours:15 |
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Colouring of Graphs
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Definition and Examples of Graph Colouring, Upper Bounds, Brooks’ Theorem, Graph with Large Chromatic Number, Extremal Problems and Turan’s Theorem, Colour-Critical Graphs, Counting Proper Colourings. | |||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:15 |
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Matchings and Factors
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Maximum Matchings, Hall’s Matching Condition, Min-Max Theorem, Independent Sets and Covers, Maximum Bipartite Matching, Weighted Bipartite Matching, Tutte’s 1-factor Theorem, Domination. | |||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:15 |
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Planar Graphs
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Drawings in the Plane, Dual Graphs, Euler’s Formula, Kuratowski’s Theorem, Convex Embeddings, Coloring of Planar Graphs, Thickness and Crossing Number. | |||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:15 |
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Edges and Cycles Edge
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Colourings, Characterisation of Line Graphs, Necessary Conditions of Hamiltonian Cycles, Sufficient Conditions of Hamiltonian Cycles, Cycles in Directed Graphs, Tait’s Theorem, Grinberg’s Theorem, Flows and Cycle Covers. | |||||||||||||||||||||||||||||
Text Books And Reference Books: D.B. West, Introduction to Graph Theory, New Delhi: Prentice-Hall of India, 2011. | |||||||||||||||||||||||||||||
Essential Reading / Recommended Reading
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Evaluation Pattern
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MTH251 - MATHEMATICS LAB USING PYTHON (2019 Batch) | |||||||||||||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:50 |
Credits:3 |
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Course Objectives/Course Description |
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Course description: This course aims as introducing the programming language Python and its uses in solving problems on discrete mathematics and differential equations. Course objectives: This course will help the learner to COBJ1.Acquire skill in usage of suitable functions/packages of Python to solve mathematical problems COBJ2.Gain proficiency in using Python to solve problems on Differential equations COBJ3. The built in functions required to deal withcreating and visualizing Graphs, Digraphs, MultiGraph |
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Course Outcome |
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On successful completion, a student will be able to: CO1. Acquire proficiency in using different functions of Python to compute solutions of basic mathematical problems CO2. Demonstrate the use of Python to solve differential equations along with visualize the solutions CO3. Be familiar with the built-in functions to deal with Graphs and Digraphs |
Unit-1 |
Teaching Hours:15 |
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Introduction to Python Programming
|
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Python commands: Comments, Number and other data types, Expressions, Operators, Variables and assignments, Decisions, Loops, Lists, Strings - plotting using “matplotlib” - Basic operations , Simplification, Calculus, Solvers and Matrices using Sympy. | |||||||||||||||||||||||||
Unit-2 |
Teaching Hours:15 |
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Differential Equations using Python
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Solving ODE’s using Python - Libraries for Differential equations in Python, PDE’s using sympy user functions pde_seperate(), pde_seperate_add(). pde_seperate_mul(), pdsolve(), classify_pde(), checkpdesol(), pde_1st_linear_constant_coeff_homogeneous, pde_1st_linear_constant_coeff, pde_1st_linear_variable_coeff. | |||||||||||||||||||||||||
Unit-3 |
Teaching Hours:15 |
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Discrete Mathematics using Python
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Creating and visualizing Graphs, Digraphs, MultiGraphs and MultiDiGraph - Python methods for reporting nodes, edges and neighbours of the given graph / digraph - Python methods for counting nodes, edges and neighbours of the given graph / digraph. | |||||||||||||||||||||||||
Text Books And Reference Books:
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Essential Reading / Recommended Reading
| |||||||||||||||||||||||||
Evaluation Pattern The course is evaluated based on continuous internal assessment (CIA). The parameters for evaluation under each component and the mode of assessment are given below:
| |||||||||||||||||||||||||
MTH311 - INTRODUCTION TO FREE AND OPEN-SOURCE SOFTWARE (FOSS) TOOLS : (GNU OCTAVE) (2018 Batch) | |||||||||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:50 |
Credits:2 |
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Course Objectives/Course Description |
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Course Description: This course is a foundation for introducing to Free and Open-Source Software (FOSS) Tools (Octave). It enables the students to explore mathematical concepts and verify mathematical facts through the use of software and also enhance the skills in programming. Course Objective: This course will the learner to COBJ1. use FOSS tool GNU Octave to effectively calculate the solutions of problems on Mathematics |
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Course Outcome |
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On successful completion of this course student will be able to CO1. express proficiency in using Octave, CO2. understand the use of various techniques of the software for effectively doing Mathematics. CO3. obtain necessary skills in Octave programming. CO4. use octave for applications of Mathematics |
Unit-1 |
Teaching Hours:15 |
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Introduction to GNU Octave
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Getting started with GNU Octave - vector operations - Projections - Matrix operations - Plotting: plotting options - saving plots - Matrices and Linear systems: solution of linear system using Gaussian elimination, left division, LU decomposition - Polynomial curve fitting - Matrix transformations. | |||||||||||||||||||||||||
Unit-2 |
Teaching Hours:15 |
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Calculus using Octave
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Limits, sequences and series - Numerical integration using Quadrature - Numerical integration using approximate sums - parametric and polar plots - special functions. | |||||||||||||||||||||||||
Unit-3 |
Teaching Hours:15 |
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3D Graphs, Multiple Integrals, Vector fields and Differential Equations
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Three dimensional graphs: space curves - surfaces - solids of revolution - Multiple integrals - Vector fields - Differential Equations: slope fields - Euler’s method - The Livermore solver | |||||||||||||||||||||||||
Text Books And Reference Books: J. Lachniet, Introduction to GNU Octave: a brief tutorial for linear algebra and calculus students. Jason Lachniet, 2017. | |||||||||||||||||||||||||
Essential Reading / Recommended Reading
| |||||||||||||||||||||||||
Evaluation Pattern The course is evaluated based on continuous internal assessment (CIA). The parameters for evaluation under each component and the mode of assessment are given below:
| |||||||||||||||||||||||||
MTH331 - MEASURE THEORY AND LEBESGUE INTEGRATION (2018 Batch) | |||||||||||||||||||||||||
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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Course description: The Coursecovers the basic material that one needs to know in the theory of functions of a real variable and measure and integration theory as expounded by Henri Léon Lebesgue Course objectives: This course will help the learner to COBJ1. enhance the understanding of the advanced notions from Mathematical Analysis COBJ2. know more about the Measure theory and Lebesgue Integration |
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Course Outcome |
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On successful completion of the course, the students should be able to CO1. understand the fundamental concepts of Mathematical Analysis. CO2. tate some of the classical theorems in of Advanced Real Analysis. CO3. be familiar with measurable sets and functions. CO4. integrate a measurable function CO5. understand the properties of Lp Spaces |
Unit-1 |
Teaching Hours:20 |
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Lebesgue Measure
|
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Lebesgue Outer Measure, The s-Algebra of Lebesgue Measurable Sets, Outer and Inner Approximation of Lebesgue Measurable Sets, Countable Additivity, Continuity and the Borel-Cantelli Lemma, Nonmeasurable Sets, The Cantor Set and the Canton-Lebesgue Function, Sums, Products and Compositions of Lebesgue Measurable Functions, Sequential Pointwise Limits and Simple Approximation, Littlewood’s three principles, Egoroff’s Theorem and Lusin’s Theorem. | |||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:15 |
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The Lebesgue Integration
|
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The Lebesgue Integral of a Bounded Measurable Function over a Set of Finite Measure, The Lebesgue Integral of a Measurable Nonnegative Function; The General Lebesgue Integral; Countable Additivity and Continuity of Integration, Uniform Integrability, Uniform Integrability and Tightness, Convergence in measure, Characterizations of Riemann and Lebesgue Integrability. | |||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:15 |
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Differentiation and Lebesgue Integration
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Continuity of Monotone Functions, Differentiation of Monotone Functions, Functions of Bounded Variation, Absolutely Continuous Functions, Integrating Derivatives. | |||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:10 |
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The Lp Spaces
|
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Normed Linear Spaces, The Inequalities of Young, Hölder and Minkowski, The Lp spaces, Approximation and Separability, The Riesz Representation for the Dual of Lp, Weak Sequential Convergence in Lp, Weak Sequential Compactness, The Minimization of Convex Functionals. | |||||||||||||||||||||||||||||
Text Books And Reference Books: H.L. Royden and P.M. Fitzpatrick, Real Analysis, 4th ed. New Jersey: Pearson Education Inc., 2013. | |||||||||||||||||||||||||||||
Essential Reading / Recommended Reading
| |||||||||||||||||||||||||||||
Evaluation Pattern
| |||||||||||||||||||||||||||||
MTH332 - NUMERICAL ANALYSIS (2018 Batch) | |||||||||||||||||||||||||||||
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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Course description: This course deals with the theory and application of various advanced methods of numerical approximation. These methods or techniques help us to approximate the solutions of problems that arise in science and engineering. The emphasis of the course will be the thorough study of numerical algorithms to understand the guaranteed accuracy that various methods provide, the efficiency and scalability for large scale systems and issues of stability Course objectives: This course will help the learner to develop the basic understanding of the construction of numerical algorithms, and perhaps more importantly, the applicability and limits of their appropriate use. The learners will be familiar with the methods which will help to obtain solution of algebraic and transcendental equations, linear system of equations, finite differences, interpolation, numerical integration and differentiation, numerical solution of differential equations and boundary value problems |
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Course Outcome |
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On successful completion of the course, the students should be able to CO1. Derive numerical methods for approximating the solution of problems of algebraic and transcendental equations, ordinary differential equations and boundary value problems. CO2. Implement a variety of numerical algorithms appropriately in various situations CO3. interpret, analyse and evaluate results from numerical computations |
Unit-1 |
Teaching Hours:20 |
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Solution of algebraic and transcendental equations
|
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Fixed point iterative method, convergence criterion, Aitken’s -process, Sturm sequence method to identify the number of real roots, Newton-Raphson methods (includes the convergence criterion for simple roots), Bairstow’s method, Graeffe’s root squaring method, Birge-Vieta method, Muller’s method. Solution of Linear System of Algebraic Equations: LU-decomposition methods (Crout’s, Choleky and Delittle methods), consistency and ill-conditioned system of equations, Tri-diagonal system of equations, Thomas algorithm. | |||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:15 |
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Interpolation and Numerical Integration
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Lagrange, Hermite, Cubic-spline’s (Natural, Not a Knot and Clamped) - with uniqueness and error term, for polynomial interpolation. Chebychev and Rational function approximation. Gaussian quadrature, Gauss-Legendre, Gauss-Chebychev formulas | |||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:15 |
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Numerical solution of ordinary differential equations
|
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Initial value problems, Runge-Kutta methods of second and fourth order, multistep method, Adams-Moulton method, stability (convergence and truncation error for the above methods), boundary value problems, second order finite difference method. | |||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:10 |
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Boundary Value Problems
|
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Numerical solutions of second order boundary value problems (BVP) of first, second and third types by shooting method, Rayleigh-Ritz Method, Gelarkin Method. | |||||||||||||||||||||||||||||
Text Books And Reference Books:
| |||||||||||||||||||||||||||||
Essential Reading / Recommended Reading
| |||||||||||||||||||||||||||||
Evaluation Pattern
| |||||||||||||||||||||||||||||
MTH333 - CLASSICAL MECHANICS (2018 Batch) | |||||||||||||||||||||||||||||
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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This course deals with some of the key ideas of classical mechanics. The concepts covered in the course include generalized coordinates, Lagrange’s equations, Hamilton’s equations and Hamilton - Jacobi theory. |
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Course Outcome |
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On successful completion of the course, the students should be able to |
Unit-1 |
Teaching Hours:12 |
||||||||||||||||||||||||||||
Introductory concepts
|
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The mechanical system - Generalised Coordinates - constraints - virtual work - Energy and momentum. | |||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:20 |
||||||||||||||||||||||||||||
Lagrange's equation
|
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Derivation and examples - Integrals of the Motion - Small oscillations. Special Applications of Lagrange’s Equations: Rayleigh’s dissipation function - impulsive motion - velocity dependent potentials. | |||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:13 |
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Hamilton's equations
|
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Hamilton's principle - Hamilton’s equations - Other variational principles - phase space. | |||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:15 |
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Hamilton - Jacobi Theory
|
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Hamilton's Principal Function – The Hamilton - Jacobi equation - Separability. | |||||||||||||||||||||||||||||
Text Books And Reference Books: Donald T. Greenwood, Classical Dynamics, Reprint, USA: Dover Publications, 2012. | |||||||||||||||||||||||||||||
Essential Reading / Recommended Reading
| |||||||||||||||||||||||||||||
Evaluation Pattern
| |||||||||||||||||||||||||||||
MTH334 - LINEAR ALGEBRA (2018 Batch) | |||||||||||||||||||||||||||||
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
|||||||||||||||||||||||||||||
Course Description: This course aims at introducing elementary notions on linear transformations, canonical forms, rational forms, Jordan forms, inner product space and bilinear forms. Course Objective: This course will help learner to COBJ1. gain proficiency on the theories of Linear Algebra COBJ2. enhance problem solving skills in Linear Algebra |
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Course Outcome |
|||||||||||||||||||||||||||||
On successful completion of the course, the students should be able to CO1. Have thorough understanding of the Linear transformations CO2.Demonstrate the elementary canonical forms, rational and Jordan forms. CO3. Apply the inner product space CO4. Express familiarity in using bilinear forms |
Unit-1 |
Teaching Hours:15 |
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Linear Transformations and Determinants
|
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Vector Spaces: Recapitulation, Linear Transformations: Algebra of Linear Transformations - Isomorphism – Representation of Transformation by Matrices – Linear Functionals – The transpose of a Linear Transformation, Determinants: Commutative Rings – Determinant Functions – Permutation and the Uniqueness of Determinants – Additional Properties of Determinants | |||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:20 |
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Elementary Canonical Forms, Rational and Jordan Forms
|
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Elementary Canonical Forms : Characteristic Values – Annihilating Polynomials – Invariant Subspaces – Simultaneous Triangulation and Diagonalization – Direct sum Decomposition – Invariant Dual Sums - The Primary Decomposition Theorem. The Rational and Jordan Forms: Cyclic subspaces and Annihilators – Cyclic Decompositions and the Rational Form – The Jordan Form – Computation of Invariant Factors – Semi-Simple Operators. | |||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:15 |
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Inner Product Spaces
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Inner Products – Inner Product Spaces – Linear Functionals and Adjoints – Unitary Operators – Normal Operators – Forms on Inner Product Spaces – Positive Forms – Spectral Theory – Properties of Normal Operators. | |||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:10 |
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Bilinear Forms
|
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Bilinear Forms – Symmetric Bilinear Forms – Skew-Symmetric Bilinear Forms – Groups Preserving Bilinear Forms | |||||||||||||||||||||||||||||
Text Books And Reference Books: K. Hoffman and R. Kunze, Linear Algebra, 2nd ed. New Delhi, India: PHI Learning Private Limited, 2011. | |||||||||||||||||||||||||||||
Essential Reading / Recommended Reading
| |||||||||||||||||||||||||||||
Evaluation Pattern
| |||||||||||||||||||||||||||||
MTH335 - ADVANCED GRAPH THEORY (2018 Batch) | |||||||||||||||||||||||||||||
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
|||||||||||||||||||||||||||||
Course description:Domination of Graphs, perfect graphs, chromatic graph theory and Eigenvalues of Graphs are dealt with in the detail in this course. Course objectives: This course will help the learner to COBJ1. understand the advanced topics in Graph Theory COBJ2. enhance the understanding of techniques of writing proofs for advanced topics in Graph Theory |
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Course Outcome |
|||||||||||||||||||||||||||||
By the end of the course the learner will be able to: CO1. have thorough understanding of the concepts in domination and perfect graphs CO2. familiarity in implementing the acquired knowledge appropriately CO3. mastery in employing proof techniques |
Unit-1 |
Teaching Hours:15 |
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Domination in Graphs
|
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Domination in Graphs, Bounds in terms of Order, Bounds in terms of Order, Degree and Packing, Bounds in terms of Order and Size, Bounds in terms of Degree, Diameter and Girth, Bounds in terms of Independence and Covering. | |||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:15 |
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Chromatic Graph Theory
|
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T-Colourings, L(2,1)-colourings, Radio Colourings, Hamiltonian Colourings, Domination and Colourings. | |||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:15 |
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Perfect Graphs
|
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The Perfect Graph Theorem, Chordal Graphs Revisited, Other Classes of Perfect Graphs, Imperfect Graphs, The Strong Perfect Graph Conjecture. | |||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:15 |
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Eigenvalues of Graphs
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The Characteristic Polynomial, Eigenvalues and Graph Parameters, Eigenvalues of Regular Graphs, Eigenvalues and Expanders, Strongly Regular Graphs. | |||||||||||||||||||||||||||||
Text Books And Reference Books:
| |||||||||||||||||||||||||||||
Essential Reading / Recommended Reading
| |||||||||||||||||||||||||||||
Evaluation Pattern
| |||||||||||||||||||||||||||||
MTH351 - NUMERICAL METHODS USING PYTHON (2018 Batch) | |||||||||||||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:50 |
Credits:3 |
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Course Objectives/Course Description |
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Course description: In this course programming Numerical Methods in Python will be focused. How to program the numerical methods step by step to create the most basic lines of code that run on the computer efficiently and output the solution at the required degree of accuracy. Course objectives: This course will help the learner to COBJ1. Program the numerical methods to create simple and efficient Python codes that output the numerical solutions at the required degree of accuracy. COBJ2. Use the plotting functions of matplotlib to visualize the results graphically. COBJ3. Acquire skill in usage of suitable functions/packages of Python to solve initial value problems numerically. |
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Course Outcome |
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By the end of the course the learner will be able to: CO1. Acquire proficiency in using different functions of Python to compute solutions of system of equations. CO2. Demonstrate the use of Python to solve initial value problem numerically along with graphical visualization of the solutions . CO3. Be familiar with the built-in functions to deal with numerical methods. |
Unit-1 |
Teaching Hours:15 |
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Introduction to Python and Roots of High-Degree Equations
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Introduction and Simple Iterations Method, Finite Differences Method | |||||||||||||||||||||||||
Unit-2 |
Teaching Hours:15 |
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Systems of Linear Equations
|
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Introduction & Gauss Elimination Method: Algorithm, Gauss Elimination Method, Jacobi's Method, Gauss-Seidel's Method, Linear System Solution in NumPy and SciPy & Summary | |||||||||||||||||||||||||
Unit-3 |
Teaching Hours:15 |
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Numerical differentiation, Integration and Ordinary Differential Equations
|
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Introduction & Euler's Method, Second Order Runge-Kutta's Method, Fourth Order Runge-Kutta's Method, Fourth Order Runge-Kutta's Method: Plot Numerical and Exact Solutions. | |||||||||||||||||||||||||
Text Books And Reference Books: J. Kiusalaas, Numerical methods in engineering with Python 3. Cambridge University Press, 2013. | |||||||||||||||||||||||||
Essential Reading / Recommended Reading Hans Fangohr, Introduction to Python for Computational Science and Engineering (A beginner’s guide), University of Southampton, 2015. | |||||||||||||||||||||||||
Evaluation Pattern The course is evaluated based on continuous internal assessment (CIA). The parameters for evaluation under each component and the mode of assessment are given below:
| |||||||||||||||||||||||||
MTH381 - INTERNSHIP IN PG COURSE (2018 Batch) | |||||||||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:0 |
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Max Marks:0 |
Credits:2 |
||||||||||||||||||||||||
Course Objectives/Course Description |
|||||||||||||||||||||||||
The objective of this course is to provide the students an opportunity to gain work experience in the relevant institution, connected to their subject of study. The experienced gained in the workplace will give the students a competetive edge in their career. |
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Course Outcome |
|||||||||||||||||||||||||
On successful completion of the course, the students should be able to · Expose to the field of their professional interest · Explore an opportunity to get practical experience in the field of their interest · Strengthen the research culture |
Unit-1 |
Teaching Hours:45 |
Internship in PG Mathematics course
|
|
M.Sc. Mathematics students have to undertake a mandatory internship of not less than 45 working days at any of the following: reputed research centres, recognized educational institutions, summer research fellowships, programmes like M.T.T.S or any other approved by the P.G. coordinator and H.O.D. The internship is to be undertaken at the end of second semester (during first year vacation). The report submission and the presentation on the report will be held during the third semester and the credits will appear in the mark sheet of third semester. The students will have to give an internship proposal with the following details: Organization where the student proposes to do the internship, reasons for the choice, nature of internship, period on internship, relevant permission letters, if available, name of the mentor in the organization, email, telephone and mobile numbers of the person in the organization with whom Christ University could communicate matters related to internship. Typed proposals will have to be given at least one month before the end of the second semester. The coordinator of the programme in consultation with the HOD will assign faculty members from the department as guides at least two weeks before the end of second semester. The students will have to be in touch with the guides during the internship period either through personal meetings, over the phone or through email. At the place of internship, students are advised to be in constant touch with their mentors. At the end of the required period of internship, the candidates will submit a report as per the guidelines given by the department. The report should be submitted within first 10 days of the reopening of the University for the third semester. Within 20 days from the day of reopening, the department must hold a presentation by the students. During the presentation the guide or a nominee of the guide should be present and be one of the evaluators. Students should preferably be encouraged to make a power point presentation of their report. A minimum of 10 minutes should be given for each of the presenter. The maximum limit is left to the discretion of the evaluation committee. Students will get 2 credits on successful completion of internship. | |
Text Books And Reference Books: . | |
Essential Reading / Recommended Reading . | |
Evaluation Pattern . | |
MTH431 - DIFFERENTIAL GEOMETRY (2018 Batch) | |
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
Max Marks:100 |
Credits:4 |
Course Objectives/Course Description |
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Course description: Differential geometry is the study of geometric properties of curves, surfaces, and their higher dimensional analogues using the methods of calculus. On successful completion of this module students will have acquired an active knowledge and understanding of the basic concepts of the geometry of curves and surfaces in three-dimensional Euclidean space and will be acquainted with the ways of generalising these concepts to higher dimensions.
Course objectives: This course will help the learner to CO BJ1. write proofs for the theorems on Curves and Surfaces in R3. COBJ2. implement the properties of curves and surfaces in solving problems described in terms of tangent vectors / vector fields / forms etc., |
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Course Outcome |
|
On successful completion of the course, the students should be able to CO1. express sound knowledge on the basic concepts in geometry of curves and surfaces in Euclidean space, especially E3. CO2. demonstrate mastery in solving typical problems associated with the theory. CO3. extend the knowledge in generalizing the concepts learned to higher dimensions. |
UNIT 1 |
Teaching Hours:15 |
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Calculus on Euclidean Geometry
|
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Euclidean Space - Tangent Vectors - Directional derivatives - Curves in E3 - 1-Forms - Differential Forms - Mappings. | |||||||||||||||||||||||||||||
UNIT 2 |
Teaching Hours:15 |
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Frame Fields and Euclidean Geometry
|
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Dot product - Curves - vector field - The Frenet Formulas - Arbitrary speed curves - cylindrical helix - Covariant Derivatives - Frame fields - Connection Forms - The Structural equations. | |||||||||||||||||||||||||||||
UNIT 3 |
Teaching Hours:15 |
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Euclidean Geometry and Calculus on Surfaces
|
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Isometries of E3 - The derivative map of an Isometry - Surfaces in E3 - patch computations - Differential functions and Tangent vectors - Differential forms on a surface - Mappings of Surfaces. | |||||||||||||||||||||||||||||
UNIT 4 |
Teaching Hours:15 |
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Shape Operators
|
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The Shape operator of M in E3 - Normal Curvature - Gaussian Curvature - Computational Techniques - Special curves in a surface - Surfaces of revolution. | |||||||||||||||||||||||||||||
Text Books And Reference Books: B.O’Neill, Elementary Differential geometry, 2nd revised ed., New York: Academic Press, 2006. | |||||||||||||||||||||||||||||
Essential Reading / Recommended Reading
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Evaluation Pattern
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MTH432 - COMPUTATIONAL FLUID DYNAMICS (2018 Batch) | |||||||||||||||||||||||||||||
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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Course Description: This course helps the students to learn the solutions of partial differential equations using finite difference and finite element methods. This course also helps them to know how solve the Burger’s equations using finite difference equation, quasi-linearization of non-linear equations. Course objectives: This course will help the students to COBJ1.Familiar with solving PDE using finite difference method and finite element method COBJ2. Understand the non-linear equation Burger’s equation using finite difference method COBJ3.Understand the compressible fluid flow using ACM, PCM and SIMPLE methods COBJ4.Solve differential equations using finite element method usingdifferent shape functions |
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Course Outcome |
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On successful completion of the course, the students should be able to CO1. Solve both linear and non-linear PDE using finite difference methods CO2. Understand both physics and mathematical properties of governing Navier-Stokes equations and define proper boundary conditions for solution CO3. Understanding of physics of compressible and incompressible fluid flows CO4. Write the programming in MATLAB to solve PDE using finite difference method |
Unit-1 |
Teaching Hours:15 |
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Numerical solution of elliptic partial differential equations
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Review of classification of partial differential equations, classification of boundary conditions, numerical analysis, basic governing equations of fluid mechanics. Difference methods for elliptic partial differential equations, difference schemes for Laplace and Poisson’s equations, iterative methods of solution by Jacobi and Gauss-Siedel, solution techniques for rectangular and quadrilateral regions. | |||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:15 |
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Numerical solution of parabolic and hyperbolic partial differential equations
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Difference methods for parabolic equations in one-dimension, methods of Schmidt, Laasonen, Crank-Nicolson and Dufort-Frankel, stability and convergence analysis for Schmidt and Crank-Nicolson methods, ADI method for two-dimensional parabolic equation, explicit finite difference schemes for hyperbolic equations, wave equation in one dimension. | |||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:15 |
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Finite Difference Methods for non-linear equations
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Finite difference method to nonlinear equations, coordinate transformation for arbitrary geometry, Central schemes with combined space-time discretization-Lax-Friedrichs, Lax-Wendroff, MacCormack methods, Artificial compressibility method, pressure correction method – Lubrication model, onvection dominated flows – Euler equation – Quasilinearization of Euler equation, Compatibility relations, nonlinear Burger equation. | |||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:15 |
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Finite Element Methods
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Introduction to finite element methods, one-and two-dimensional bases functions – Lagrange and Hermite polynomials elements, triangular and rectangular elements, Finite element method for one-dimensional problem and two-dimensional problems: model equations, discretization, interpolation functions, evaluation of element matrices and vectors and their assemblage. | |||||||||||||||||||||||||||||
Text Books And Reference Books:
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Essential Reading / Recommended Reading
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Evaluation Pattern
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MTH433 - FUNCTIONAL ANALYSIS (2018 Batch) | |||||||||||||||||||||||||||||
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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Course Description: This abstract course imparts an in-depth analysis of Banach spaces, Hilbert spaces, conjugate spaces, etc. This course also includes a few important applications of functional analysis to other branches of both pure and applied mathematics. Course Objective. This course will help learner to COBJ1: know the notions behind Functional Analysis COBJ2. enhance the problem solving ability in Functional Analysis |
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Course Outcome |
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On successful completion of the course, the students should be able to CO1. Explain the fundamental concepts of functional analysis. |
Unit-1 |
Teaching Hours:15 |
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Banach spaces
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Normed linear spaces, Banach spaces, continuous linear transformations, isometric isomorphisms, functionals and the Hahn-Banach theorem, the natural embedding of a normed linear space in its second dual. | |||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:12 |
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Mapping theorems
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The open mapping theorem and the closed graph theorem, the uniform boundedness theorem, the conjugate of an operator. | |||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:15 |
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Inner products
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Inner products, Hilbert spaces, Schwarz inequality, parallelogram law, orthogonal complements, orthonormal sets, Bessel’s inequality, complete orthonormal sets.
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Unit-4 |
Teaching Hours:18 |
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Conjugate space
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The conjugate space, the adjoint of an operator, self-adjoint, normal and unitary operators, projections, finite dimensional spectral theory.
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Text Books And Reference Books: G.F. Simmons, Introduction to topology and modern Analysis, Reprint, Tata McGraw-Hill, 2004. | |||||||||||||||||||||||||||||
Essential Reading / Recommended Reading
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Evaluation Pattern
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MTH446 - ADVANCED LINEAR PROGRAMMING (2018 Batch) | |||||||||||||||||||||||||||||
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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Course Description: This course is about the analysis and applications of transportation and assignment models, game theory, CPM - PERT methods and dynamic programming. Course objectives: This course will help the students to COBJ1. acquire and demonstrate the implementation of the necessary algorithms for solving advanced level linear programming problems |
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Course Outcome |
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On successful completion of the course, the students should be able to CO1. Apply the notions of linear programming in solving transportation problems CO2. Understand the theory of games for solving simple games CO3. Acquire knowledge in formulating Tax planning problem and use goal programming algorithms CO4. Use linear programming in the formulation of shortest route problem and use algorithmic approach in solving various types of network problems CO5. Know the use of dynamic programming in various applications |
Unit-1 |
Teaching Hours:16 |
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Transportation Model
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Determination of the Starting Solution – Iterative computations of the transportation algorithm. Assignment Model: The Hungarian Method – Simplex explanation of the Hungarian Method – The trans-shipment Model. | |||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:16 |
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Game Theory
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Game Theory: Optimal solution of two person zero – sum games – Solution of Mixed strategy Games (both graphical and Linear programming solution) – Goal Programming: Formulation – Tax Planning Problem – Goal programming algorithms – The weights method – preemptive method. | |||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:16 |
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Network Models
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Linear programming formulation of the shortest-route Problem. Maximal Flow model: Enumeration of cuts – Maximal Flow Algorithm – Linear Programming Formulation of Maximal Flow Model. CPM and PERT: Network Representation – Critical path computations – Construction of the Time Schedule – Linear Programming formulation of CPM – PERT calculations. | |||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:12 |
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Dynamic Programming
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Dynamic Programming: Recursive nature of computations in DP – Forward and Backward Recursion – Knapsack / Fly Away / Cargo-Loading Model - Equipment Replacement Model. | |||||||||||||||||||||||||||||
Text Books And Reference Books: A.H. Taha, Operations research, 7th Ed, Pearson Education, 2003. | |||||||||||||||||||||||||||||
Essential Reading / Recommended Reading
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Evaluation Pattern
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MTH448 - COMBINATORIAL MATHEMATICS (2018 Batch) | |||||||||||||||||||||||||||||
Total Teaching Hours for Semester:60 |
No of Lecture Hours/Week:4 |
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Max Marks:100 |
Credits:4 |
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Course Objectives/Course Description |
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Course Description: Combinatorics deals with the existence of certain configurations in a structure and when it exists it counts the number of such configurations. In this course we deal with the basic concepts such as Permutations and Combinations, Generating Functions, Recurrence Relations, The Principle of Inclusion and Exclusion including Polya’s theory.
Course objectives:The student will be familiar with: COBJ1. the rules of Sum and Product of permutations and combinations. COBJ2. distributions of distinct objects into non-distinct cells and partitions of integers. COBJ3. the technique of generating functions and recurrence relations COBJ4. the concepts of permutations with restrictions on relative positions and the rook polynomials. enumeration using Polya’s Theory. |
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Course Outcome |
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After completing this course, the student will be able to CO1. be familiar with the combinatorial methods and techniques CO2. develop combinatorial models for different problems and hence find their solutions CO3. apply combinatorial techniques in enumeration problems problems. |
Unit-1 |
Teaching Hours:20 |
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Permutations, Combinations and Generating Functions
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Introduction - The rules of Sum and Product - Permuations - Combinations - Distributions of Distinct Objects - Distributions of Non distinct Objects. Generating Functions for Combinations - Enumerators for Permutations – Distributions of Distinct Objects into Non distinct Cells - Partitions of Integers - Elementary Relations. | |||||||||||||||||||||||||||||
Unit-2 |
Teaching Hours:12 |
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Recurrence Relations
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Introduction - Linear Recurrence relations with Constant Coefficients - Solution by the technique of Generating Functions - Recurrence Relations with Two Indices. | |||||||||||||||||||||||||||||
Unit-3 |
Teaching Hours:13 |
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The Principle of Inclusion and Exclusion
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Introduction - The Principle of Inclusion and Exclusion - The General Formula - Derangements - Permutations with Restrictions on Relative Positions - The Rook Polynomials. | |||||||||||||||||||||||||||||
Unit-4 |
Teaching Hours:15 |
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Polya's Theory of Counting
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Introduction - Equivalence Classes under a Permutation Group - Equivalence Classes of Functions -Weights and Inventories of Functions - Polya’s Fundamental Theorem - Generalization of Polya’s Theorem. | |||||||||||||||||||||||||||||
Text Books And Reference Books: C. L. Liu, Introduction to Combinatorial Mathematics, McGraw-Hill Inc., New york,1968. | |||||||||||||||||||||||||||||
Essential Reading / Recommended Reading
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Evaluation Pattern
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MTH451 - NUMERICAL METHODS FOR BOUNDARY VALUE PROBLEM USING PYTHON (2018 Batch) | |||||||||||||||||||||||||||||
Total Teaching Hours for Semester:45 |
No of Lecture Hours/Week:3 |
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Max Marks:50 |
Credits:3 |
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Course Objectives/Course Description |
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Course description: This course helps students to have an in-depth knowledge of Python in solving Boundary Value problems This includes solution of Two-point boundary value problems using core Python. This course also introduces students to FEniCS, an extension of Python for solving various PDE’s and boundary problems. Course objectives: This course will help the learner to COBJ1.Program Python codes to solve two-point boundary value problems at the required degree of accuracy. COBJ2.Use the plotting functions of matplotlib to visualize the solution of BVP’s. COBJ3.Acquire skill in usage of suitable functions/packages of Python to solve partial differential equations. |
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Course Outcome |
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By the end of the course the learner will be able to: CO1. acquire proficiency in using different functions of Python and writing user defined functions to compute solutions of two-point boundary value problems CO2. demonstrate the use of Python to solve ODEs numerically using shooting method with graphical visualization. CO3. be familiar with the built-in functions to deal with solution of PDE’s. |
Unit-1 |
Teaching Hours:15 |
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Two-Point Boundary Value Problems
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Introduction to two-point boundary value Problems - Shooting Method: second order differential equations - Higher order differential equations - solution of second order differential equation using Finite Difference Method, solution of fourth order differential equation using Finite Difference Method. | |||||||||||||||||||||||||
Unit-2 |
Teaching Hours:15 |
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FEniCS and Finite element Solvers
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Implementation of FEniCS - The heat equation - A nonlinear Poisson equation - Equation of linear elasticity - The Navier - Stokes equations - A system of advection-diffusion-reaction equations. | |||||||||||||||||||||||||
Unit-3 |
Teaching Hours:15 |
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Subdomains and Boundary conditions
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Combining Dirichlet and Neuman conditions - Setting multiple Dirichlet conditions - defining subdomains - setting up multiple Dirichlet, Neumann, and Robin conditions - Generating meshes with subdomains.
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Text Books And Reference Books:
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Essential Reading / Recommended Reading J. Crank, H. G. Martin, and D. M. Melluish, Non-Linear Ordinary Differential Equations. Oxford University Press. | |||||||||||||||||||||||||
Evaluation Pattern The course is evaluated based on continuous internal assessment (CIA). The parameters for evaluation under each component and the mode of assessment are given below:
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MTH481 - PROJECT (2018 Batch) | |||||||||||||||||||||||||
Total Teaching Hours for Semester:30 |
No of Lecture Hours/Week:2 |
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Max Marks:100 |
Credits:2 |
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Course Objectives/Course Description |
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The objective of this course is to develop positive attitude, knowledge and competence for the research in Mathematics. |
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Course Outcome |
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Through this project students will develop analytical and computational skills |
Unit-1 |
Teaching Hours:30 |
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PROJECT
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Students are exposed to the mathematical software packages like Scilab, Maxima, Octave, OpenFOAM, Mathematica and Matlab. Students are given a choice of topic either on Fluid Mechanics or Graph theory or any other topic from other fields with the approval of HOD / Coordinator. Each candidate will work under the supervision of the faculty. Coordinator will allot the supervisor for each candidate in consultation with the HOD at the end of third semester. Project need not be based on original research work. Project could be based on the review of advanced text book or advanced research papers. Each candidate has to submit a dissertation on the project topic followed by viva voce examination. The viva voce will be conducted by the committee constituted by the head of the department which will have an external and an internal examiner. The student must secure 50% of the marks to pass the project examination. The candidates who fail must redo the project as per the university regulation. Time line for Project:
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Text Books And Reference Books: . | |||||||||||||||||||
Essential Reading / Recommended Reading . | |||||||||||||||||||
Evaluation Pattern Assessment: Project is evaluated based on the parameters given below:
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