Syllabus - SAU 2016
M.Sc. in Applied Mathematics
Format of the Entrance Test Paper
The duration of the Entrance Test will be 3 hours and the
question paper will consist of 100 multiple choice questions in two parts.
PART A: 40
questions on Basic Mathematics.
PART B: 60
questions on Undergraduate Level Mathematics.
.
The combined syllabus for both Part A and Part B is as follows:
Calculus and Analysis: Limit, continuity, uniform continuity and differentiability;
Bolzano Weierstrass theorem; mean value theorems; tangents and normal; maxima
and minima; theorems of integral calculus; sequences and series of functions;
uniform convergence; power series; Riemann sums; Riemann integration; definite
and improper integrals; partial derivatives and Leibnitz theorem; total
derivatives; Fourier series; functions of several variables; multiple
integrals; line; surface and volume integrals; theorems of Green; Stokes and
Gauss; curl; divergence and gradient of vectors.
Algebra: Basic
theory of matrices and determinants; groups and their elementary properties;
subgroups, normal subgroups, cyclic groups, permutation groups; Lagrange's
theorem; quotient groups; homomorphism of groups; isomorphism and
correspondence theorems; rings; integral domains and fields; ring homomorphism
and ideals; vector space, vector subspace, linear independence of vectors,
basis and dimension of a vector space.
Differential equations: General and particular solutions of ordinary differential
equations (ODEs); formation of ODE; order, degree and classification of ODEs;
integrating factor and linear equations; first order and higher degree linear
differential equations with constant coefficients; variation of parameter;
equation reducible to linear form; linear and quasi-linear first order partial
differential equations (PDEs); Lagrange and Charpits methods for first order
PDE; general solutions of higher order PDEs with constant coefficients.
Numerical Analysis: Computer arithmetic; machine computation; bisection,
secant; Newton-Raphson and fixed point iteration methods for algebraic and
transcendental equations; systems of linear equations: Gauss elimination, LU
decomposition, Gauss Jacobi and Gauss Siedal methods, condition number; Finite
difference operators; Newton and Lagrange interpolation; least square
approximation; numerical differentiation; Trapezoidal and Simpsons integration
methods.
Probability and Statistics: Mean, median, mode and standard deviation; conditional
probability; independent events; total probability and Baye’s theorem; random
variables; expectation, moments generating functions; density and distribution
functions, conditional expectation.
Linear Programming: Linear programming problem and its formulation; graphical method, simplex method, artificial starting solution, sensitivity analysis, duality and post-optimality analysis.
Note:
· If the answer given to
any of the Multiple Choice Questions is wrong, ¼ of the marks assigned to that
question will be deducted.
· Calculators will not
be allowed. However, Log Tables may be used
Syllabus - SAU 2016
M.Phil./ Ph.D. in
Applied Mathematics
Format of the Entrance
Test Paper
The duration of the Entrance Test will be 3 hours and the
question paper will consist of 70 multiple choice questions in two parts: Part
A and Part B.
PART A: 30 questions on undergraduate level Mathematics
PART B: 40 questions on Master’s level Mathematics
The areas from which questions may be asked will include the following:
Analysis: Real functions;
limit, continuity, differentiability; sequences; series; uniform convergence;
functions of complex variables; analytic functions, complex integration;
singularities, power and Laurent series; metric spaces; stereographic
projection; topology, compactness, connectedness; normed linear spaces, inner
product spaces; dual spaces, linear operators; Lebesgue measure and
integration; convergence theorems.
Algebra: Basic theory of matrices and determinants; eigen values and eigen vectors; Groups and their elementary properties; subgroups, normal subgroups, cyclic groups, permutation groups; Lagrange's theorem; quotient groups, homomorphism of groups; Cauchy Theorem and p-groups; the structure of groups; Sylow's theorems and their applications; rings, integral domains and fields; ring homomorphism and ideals; polynomial rings and irreducibility criteria; vector space, vector subspace, linear independence of vectors, basis and dimension of a vector space, inner product spaces, orthonormal basis; Gram-Schmidt process, linear transformations.
Differential Equations: First order
ordinary differential equations (ODEs); solution of first order initial value
problems; singular solution of first order ODEs; system of linear first order
ODEs; method of solution of dx/P=dy/Q=dz/R; orthogonal trajectory; solution of
Pfaffian differential equations in three variables; linear second order
ODEs. Sturm-Liouville problems; Laplace transformation of ODEs; series
solutions; Cauchy problem for first order partial differential equations (PDEs); method of characteristics; second order linear PDEs in two variables and their classification; separation of variables; solution of Laplace, wave and diffusion equations, Fourier transform and Laplace transform of PDEs.
solutions; Cauchy problem for first order partial differential equations (PDEs); method of characteristics; second order linear PDEs in two variables and their classification; separation of variables; solution of Laplace, wave and diffusion equations, Fourier transform and Laplace transform of PDEs.
Numerical Analysis: Numerical solution of algebraic and transcendental equations,
direct and iterative methods for system of linear equations; matrix eigenvalue
problems; interpolation and approximations; numerical differentiation and
integration; composite numerical integration; double numerical integration;
numerical solution for initial value problems; finite difference and finite
element methods for boundary value problems.
Probability and
Statistics: Axiomatic approach of
probability; random variables, expectation, moments generating functions,
density and distribution functions, conditional expectation.
Linear Programming: Linear programming
problem and its formulation; graphical method, simplex method; artificial
starting solution; sensitivity analysis; duality and post-optimality analysis.
Note:
·
If the answer given to any of the Multiple Choice Questions is
wrong, ¼ of the marks assigned to that question will be deducted.
·
Calculators will not be allowed. However, Log Tables may be
used.
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