chenzhu-xie / nlast

NLAST-scalar model (Outdated) —— NLAST: Nonlinear Angular Spectrum Theory

This repo contains the official implementation of the paper (If one uses the code, please cite this paper. :)):

Nonlinear Angular Spectrum Theory for Sum Frequency Generation

About

• This model 👉 NLAST-scalar model
  1. Contains paper ⊋ 👉 NLAST-scalar paper (Private)
  2. Subseteq model ⊂ 👉 NLAST-vector model (Private)
     • Contains paper ⊋ 👉 Berry-Mcleod paper (Private)
  3. Foundations are ≺ 👉 undergraduate courses
     • Contains science ⊷ 👉 Bachelor Thesis 1st_draft; Mathematical Methods in the Physical Sciences; Information Optics; Electrodynamics; Linear Algebra; Advanced Mathematics
     • Contains tech ⊷ 👉 Python
  4. Derived tool ⊷ 👉 generate.cif
• 中文「自述文档」㊥ 👉 NLAST-scalar 模型

Description

The Nonlinear Angular Spectrum Theory (NLAST) is the ultimate solution to calculate various nonlinear process with unprecedented both accuracy and efficiency.

In this paper, the NLAST solves the generation and linear diffraction of $\omega_3$ in SFG process simultaneously in just one step, by transforming the nonlinear convolution of fundamental waves in the spatial frequency domain down to the FFT-2D form.

Running the code

Run any .py file, and one shall see the bloody truth.

History

• This model 👉 NLAST-scalar model
  1. The NLAST project launched on 2022.02. (23 years old and 9 months old)
     • Winter vacation in the second year of graduate school. (1.5 / 5.0 years)
  2. The model basically completed around 2022.06. (24 years old and 2 months old)
     • Summer vacation in the second year of graduate school. (2.0 / 5.0 years)
  3. details can be found in repo 👉 postgraduate academia 1.5-2.0 year
• Contains paper ⊋ 👉 NLAST-scalar paper (Private)
  1. The paper initiated on 2024.06. (26 years old and 2 months old)
     • The second year of PhD Program. (3.8 / 5.0 years)
  2. The first draft was done around 2024.09. (26 years old and 5 months old)
     • The penultimate semester of PhD Program. (4.0 / 5.0 years)
  3. details can be found in repo 👉 PhD academia 1.5-2.0 year