Skip to content

cpuyyp/prelims

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Preliminary Exams and Solutions

Question topics

✓ - Information Gathered, ✓✓ - Final Notebook

2017

Spring

  1. Matrix (Dr. Quaife) ✓
  2. Partial Differential Equations (Dr. Quaife) ✓
  3. Linear Algebra (Dr. Peterson) ✓
  4. Ordinary Differential Equations (Dr. Meyer-Baese) ✓
  5. Interpolation (Dr. Shanbhag) ✓
  6. Numerical Differentiation (Dr. Shanbhag) ✓
  7. Quadrature (Dr. Shanbhag) ✓
  8. Optimization (Dr. Navon) ✓
  9. Parallel Computing (Dr. Huang) ✓
  10. Data Structure (Dr. Beerli) ✓
  11. Statistics (Dr. Beerli) ✓

Summer (May)

  1. Linear Algebra (Dr. Peterson) ✓
  2. Integration and Fourier Series (Dr. Shanbhag) ✓
  3. Approximation (Dr. Shanbhag) ✓
  4. Probability and Statistics (Dr. Shanbhag) ✓
  5. Finite Difference (Dr. Quaife) ✓
  6. Optimization/Linear Programming (Dr. Quaife) ✓
  7. Partial Differential Equations (Dr. Quaife) ✓
  8. Parallel Programming (Dr. Huang) ✓
  9. Fast Fourier Transform (Dr. Meyer-Baese) ✓
  10. Data Structure (Dr. Meyer-Baese) ✓
  11. Stability and Convergence of Numerical PDEs (Dr. Plewa) ✓

2016

Spring

  1. Numerical Linear Algebra (Dr. Peterson) ✓
  2. Numerical Quadrature (Dr. Peterson) ✓
  3. Numerical Integration (Dr. Shanbhag) ✓
  4. Ordinary Differential Equations (Dr. Quaife) ✓✓
  5. Statistics (Dr. Ye) ✓
  6. PDE Problem (Dr. Ye) ✓
  7. Linear Algebra (Dr. Burkardt) ✓✓
  8. Optimization (Dr. Navon)
  9. Fast Fourier Transform (Dr. Meyer-Baese) ✓
  10. Data Structure (Dr. Erlebacher) ✓
  11. Parallelization and Molecular Dynamics (Dr. Plewa)

Summer

  1. Numerical Linear Algebra (Dr. Peterson) ✓
  2. Approximation (Dr. Shanbhag)
  3. ODEs and Linear Algebra (Dr. Shanbhag)
  4. Monte Carlo (Dr. Shanbhag) ✓
  5. ODE and Integral (Dr. Quaife)
  6. Numerical Integration (Dr. Burkardt) ✓
  7. PDE and Finite Difference (Dr. Burkardt) ✓
  8. Parallel Computing (Dr. Huang) ✓
  9. Fast Fourier Transform (Dr. Meyer-Baese) ✓
  10. Data Structure (Dr. Meyer-Baese) ✓
  11. Q11. Optimization (Dr. Navon) ✓

2015

Spring

  1. Numerical Linear Algebra (Peterson)
  2. Numerical Linear Algebra (Peterson) ✓
  3. Approximation Theory (Gunzburger)
  4. Numerical ODEs (Erlebacher) ✓
  5. Numerical Quadrature (Shanbahg) ✓✓
  6. Statistics (Beerli) ✓
  7. Fourier Analysis (Meyer-Baese) ✓
  8. Optimization (Wang) ✓
  9. Finite Element Mathod (Burkardt)
  10. Stability and convergence of numerical PDEs (Plewa)
  11. Parallelization and performance of molecular dynamics code (Dr. Plewa) ✓

Summer

  1. Fast Fourier Transforms (Meyer-Baese)
  2. Linear Algebra (Wang) ✓
  3. Finite Elements (Burkardt) ✓
  4. Numerical Linear Algebra/Eigenproblems (Peterson) ✓✓
  5. Interpolation/Numerical Quadratures (Peterson) ✓
  6. Numerical Differentiation (Shanbhag) ✓
  7. Statistical Analysis (Ye) ✓
  8. Numerical Optimization (Navon) ✓
  9. Parallel Programming (Huang) ✓
  10. Monte Carlo Integration (Shanbhag) ✓
  11. Numerical Partial Differential Equations (Erlebacher)

2014

Spring

  1. Optimization (Dr. Navon) ✓
  2. Fourier Analysis (Dr. Meyer-Baese)
  3. Integration and Approximation: (Dr. Shanbhag) ✓
  4. Ordinary Differential Equations (Dr. Ye)
  5. Statistics (Dr. Ye) ✓
  6. Parallel Programming - MPI (Dr. Burkardt) ✓
  7. Finite Difference Methods (Dr. Peterson)
  8. Approximation: (Dr. Wang) ✓
  9. Data structures: (Dr. Beerli) ✓
  10. Numerical Integration (Dr. Beerli) ✓
  11. PDEs: (Dr. Plewa)

2013

Spring

  1. Optimization (Dr. Navon) ✓
  2. Fourier Analysis (Dr. Meyer-Baese) ✓
  3. Ordinary Differential Equations: (Dr. Shanbhag)
  4. Partial Differential Equations (Dr. Ye)
  5. Linear Algebra (Dr. Peterson) ✓
  6. Linear Algebra (Dr. Burkardt) ✓
  7. Parallel Programming - MPI (Dr. Burkardt) ✓
  8. Statistics: (Dr. Slice) ✓
  9. Approximation: (Dr. Wang) ✓
  10. Numerical Integration (Dr. Beerli) ✓
  11. Molecular Dynamics (Dr. Shanbhag)
  12. PDEs (Dr. Plewa)

2012

Spring

  1. Optimization (Dr. Navon)
  2. Ordinary Differential Equations/Molecular Dynamics (Dr. Shanbhag) ✓✓
  3. Interpolation (Dr. Shanbhag) ✓
  4. Finite Element (Dr. Burkardt)
  5. Linear Algebra (Dr. Burkardt)
  6. Datastructures (Dr. Beerli)
  7. Linear Algebra (Dr. Wang)
  8. Parallel Programming (Dr. Wang) ✓
  9. Fourier Analysis (Dr. Meyer-Baese)
  10. Partial Differential Equations (Dr. Ye)
  11. Statistics (Dr. Ye)
  12. Integration (Dr. Beerli) ✓

2011

Spring

  1. Ordinary Differential Equations
  2. Linear Algebra
  3. Optimization
  4. Partial Differential Equations
  5. Computational Fourier analysis
  6. Partial differential equations: finite element method
  7. Optimization
  8. Parallel programming
  9. Numerical ODE
  10. Data structure
  11. Numerical differentiation

Summer

  1. Linear Algebra (Dr. Peterson)
  2. Partial Differential Equations (Dr. Peterson)
  3. Constrained Optimization (Dr. Navon)
  4. Unconstrained Optimization (Dr. Navon)
  5. Parallel Programming
  6. Datastructures (Dr. Wang)
  7. Linear Algebra (Dr. Wang)
  8. Approximation (Dr. Shanbhag)
  9. Gaussian Quadrature (Dr. Shanbhag)
  10. Ordinary Differential Equations (Dr. Erlebacher)
  11. Statistics and Random Processes (Dr. Beerli)

2010

Spring

  1. Ordinary differential equations
  2. Monte Carlo and quadrature
  3. Orthogonal matrices and transformations
  4. Singular value decomposition
  5. Computational Fourier analysis
  6. Partial differential equations: finite element method
  7. Optimization
  8. Linear programming
  9. Parallel programming
  10. Numerical differentiation
  11. Data structure

Summer

  1. Ordinary differential equations
  2. Linear algebra
  3. Gaussian quadrature
  4. Monte Carlo
  5. Computational Fourier analysis
  6. Partial differential equations: finite element method
  7. Optimization
  8. Parallel programming
  9. Numerical ODE
  10. Data structure
  11. Numerical differentiation

2009

Spring

  1. Datastructures
  2. Integration
  3. Monte-Carlo
  4. Numerical Linear Algebra
  5. Numerical Linear Algebra
  6. Parallel computations
  7. Numerical PDEs
  8. Numerical PDEs
  9. Fourier Transform/Optimization
  10. Linear Programming
  11. Statistical Methods

2008

Spring

  1. Datastructures
  2. Interpolation
  3. Approximation
  4. Monte-Carlo
  5. Fourier Transform
  6. Maximum Likelihood
  7. Singular Value Decomposition
  8. PDEs
  9. PDEs
  10. Parallel Solution of Recurrences
  11. Numerical Linear Algebra
  12. Newton’s Method for Unconstrained Optimization
  13. Numerical Integration
  14. Numerical Differentiation

Hello!

About

Prelims and solutions

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 87.2%
  • TeX 6.8%
  • MATLAB 2.0%
  • C++ 1.7%
  • Python 1.6%
  • Fortran 0.6%
  • Other 0.1%