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2022 Fall

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Qiang Zhu edited this page Dec 1, 2022 · 14 revisions

List of Students

  1. James Taber, https://github.com/Jtaber1/ComputationalPhysics300
  2. Tabris Loveless, https://github.com/Azegon/ComputationalPhysics300
  3. Kory Schlax, https://github.com/schlak1/ComputationalPhysics300
  4. Sterling Vivier, https://github.com/sterlingvivier/ComputationalPhysics300
  5. Emily Huerta, https://github.com/emilyh1701/ComputationalPhysics300
  6. Junhao Liu, https://github.com/kongyue233/ComputationalPhysics300
  7. Nick Pereira, https://github.com/nickpereira1242

Feedback:

  1. Improve the instruction on the open problem homework (maybe show some examples regarding the input/output)

Presentation 1 (2022/11/03):

We will split the class into two groups

  • Tabris Loveless, Willing to lead MC or Optimization projects
  • Kory Schlax, Willing to lead the RNG projects,
  • Emily Huerta, Willing to lead, (linear regression/finite difference)
  • Junhao Liu, Prefers RNG (doesn't want to be the leader)
  • Sterling Vivier (linear regression/finite difference), same team with Emily.

Group 1 (Linear regression)

  • Emily Huerta
  • Sterling Vivier
  • Nich Pereria

Group 2 (RNG)

  • Kory Schlax
  • Junhao Liu
  • Tabris Loveless

Rules:

  • 1, upload your presentation to the GitHub repo before the class
  • 2, do some practice, control your presentation within 25 minutes.
  • 3, Each presentation should have through, background/objective, code and results analysis
  • 4, We also expect a 5-minutes Q/A session after each presentation

Lectures will be over by 11/29/2022.

Presentation 2 (Final, 12/01/2022):

  • Kory Schlax (Mandelbrot set)
  • Emily Huerta (Mandelbrot set)
  • James Taber (ML)
  • Tabris Loveless (NN-ML)
  • Junhao Liu (Machine Learning)
  • Nich Pereria (Machinę learning)
  • Sterling Vivier (Numerical derivatives)

Rules:

  • 1, upload your presentation to the GitHub repo before the class
  • 2, do some practise, control your presentation within 5 minutes.
  • 3, In the 5 minutes, you need to go through, background/objective, code and results analysis
  • 4, we also expect a 3-minutes Q/A session after each presentation
  • 5, do it by yourself (no team work!)

Schedule:

12/06/2022

12/08/2022

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