Computational modelling of ray propagation through optical elements using the principles of geometric optics (Ray Tracer)

Overview

Computational modelling of ray propagation through optical elements using the principles of geometric optics (Ray Tracer)

Introduction

By applying the principles of geometric optics, imaging performances of lenses were investigated via examining the propagation of optical rays through various optical systems. The optical system and its elements were modelled with an object-oriented approach using the Python programming language. Through utilising a ray bundle with specific parameters, the performances of a planoconvex lens with different orientations were analysed. The orientation with the convex surface facing the incident beam was found to be more effective at minimising the spherical aberration. This was evident from the value of the geometric RMS spot radius of 1.85 x 10^-5} m at the paraxial focus compared to 7.04 x 10^-5 m for the plano-convex orientation. This was further supported by the relatively slow rate of increase in the RMS spot radius with the beam size for the convex-plano orientation. Furthermore, by optimising the curvatures of a singlet lens with a image distance of 100 mm, the best form curvatures were approximated as 0.01417 mm^-1 and -0.00532 mm^-1 with the RMS spot radius of 6.07 x 10^-8 m, leading to a conclusion that the system was diffraction limited and the effect of diffraction was substantial when using a beam radius smaller than 13.60 mm.

Requirements

Python 2.x is required to run the scripts (except for those with name beginning with 'ODE_').

Create an environment using conda as follows:

  conda create -n python2 python=2.x

Then activate the new environment by:

  conda activate python2

Results

In an ideal case, optical rays refracting through a spherical lens can be made to converge at a single point known as the focal point. However, in practice, rays fail to converge at a single point and a blurring effect occurs. This optical effect, known as the spherical aberration, is a result of the rays propagating parallel to the optical axis through a spherical lens at different distances from the axis.$^{1, 3}$ The rays further away from the optical axis experience greater refraction and thus they intersect the optical axis slightly behind the paraxial focus before diverging (FIG. 1).

For a single lens, spherical aberration can be minimised either by changing the orientation of the lens or by carefully choosing the curvatures of the spherical surfaces into the best form. In this investigation, both cases are examined using collimated ray bundles with uniformly distributed rays of various diameters with the aim to minimise this effect.

SA Figure 1: A lens displaying spherical aberration - the marginal and paraxial rays focus at the points F_1 and F_2 respectively.


single

Figure 2: A ray bundle of radius 5 mm propagating through a single spherical surface with a curvature of 0.03 mm^-1 and refracting towards the optical axis.


spotplot2

Figure 3: The non-uniform ring pattern that is shown in the figure is symbolic of the spherical aberration effect. The aberration is significantly reduced using the convex-plano orientation.


RMSPC

Figure 4: A graph depicting the change in the RMS spot radius at the paraxial focus with increasing beam size.


RMSDL

Figure 5: A graph showing the relationships of the diffraction limit and the RMS spot radius with increasing beam size.

🔗 Links

linkedin

License

MIT License

Owner
Son Gyo Jung
Son Gyo Jung
Objax Apache-2Objax (🥉19 · ⭐ 580) - Objax is a machine learning framework that provides an Object.. Apache-2 jax

Objax Tutorials | Install | Documentation | Philosophy This is not an officially supported Google product. Objax is an open source machine learning fr

Google 729 Jan 02, 2023
Inverse Rendering for Complex Indoor Scenes: Shape, Spatially-Varying Lighting and SVBRDF From a Single Image

Inverse Rendering for Complex Indoor Scenes: Shape, Spatially-Varying Lighting and SVBRDF From a Single Image (Project page) Zhengqin Li, Mohammad Sha

209 Jan 05, 2023
Generative Exploration and Exploitation - This is an improved version of GENE.

GENE This is an improved version of GENE. In the original version, the states are generated from the decoder of VAE. We have to check whether the gere

33 Mar 23, 2022
《Truly shift-invariant convolutional neural networks》(2021)

Truly shift-invariant convolutional neural networks [Paper] Authors: Anadi Chaman and Ivan Dokmanić Convolutional neural networks were always assumed

Anadi Chaman 46 Dec 19, 2022
DilatedNet in Keras for image segmentation

Keras implementation of DilatedNet for semantic segmentation A native Keras implementation of semantic segmentation according to Multi-Scale Context A

303 Mar 15, 2022
Adjust Decision Boundary for Class Imbalanced Learning

Adjusting Decision Boundary for Class Imbalanced Learning This repository is the official PyTorch implementation of WVN-RS, introduced in Adjusting De

Peyton Byungju Kim 16 Jan 04, 2023
An implementation of quantum convolutional neural network with MindQuantum. Huawei, classifying MNIST dataset

关于实现的一点说明 山东大学 2020级 苏博南 www.subonan.com 文件说明 tools.py 这里面主要有两个函数: resize(a, lenb) 这其实是我找同学写的一个小算法hhh。给出一个$28\times 28$的方阵a,返回一个$lenb\times lenb$的方阵。因

ぼっけなす 2 Aug 29, 2022
Topic Modelling for Humans

gensim – Topic Modelling in Python Gensim is a Python library for topic modelling, document indexing and similarity retrieval with large corpora. Targ

RARE Technologies 13.8k Jan 03, 2023
Material del curso IIC2233 Programación Avanzada 📚

Contenidos Los contenidos se organizan según la semana del semestre en que nos encontremos, y según la semana que se destina para su estudio. Los cont

IIC2233 @ UC 72 Dec 23, 2022
Multiband spectro-radiometric satellite image analysis with K-means cluster algorithm

Multi-band Spectro Radiomertric Image Analysis with K-means Cluster Algorithm Overview Multi-band Spectro Radiomertric images are images comprising of

Chibueze Henry 6 Mar 16, 2022
Automatic number plate recognition using tech: Yolo, OCR, Scene text detection, scene text recognation, flask, torch

Automatic Number Plate Recognition Automatic Number Plate Recognition (ANPR) is the process of reading the characters on the plate with various optica

Meftun AKARSU 52 Dec 22, 2022
Anatomy of Matplotlib -- tutorial developed for the SciPy conference

Introduction This tutorial is a complete re-imagining of how one should teach users the matplotlib library. Hopefully, this tutorial may serve as insp

Matplotlib Developers 1.1k Dec 29, 2022
Machine learning, in numpy

numpy-ml Ever wish you had an inefficient but somewhat legible collection of machine learning algorithms implemented exclusively in NumPy? No? Install

David Bourgin 11.6k Dec 30, 2022
Dieser Scanner findet Websites, die nicht direkt in Suchmaschinen auftauchen, aber trotzdem erreichbar sind.

Deep Web Scanner Dieses Script findet Websites, die per IPv4-Adresse erreichbar sind und speichert deren Metadaten. Die Ausgabe im Terminal wird nach

Alex K. 30 Nov 18, 2022
An unofficial implementation of "Unpaired Image Super-Resolution using Pseudo-Supervision." CVPR2020

UnpairedSR An unofficial implementation of "Unpaired Image Super-Resolution using Pseudo-Supervision." CVPR2020 turn RCAN(modified) -- xmodel(xilinx

JiaKui Hu 10 Oct 28, 2022
GAN encoders in PyTorch that could match PGGAN, StyleGAN v1/v2, and BigGAN. Code also integrates the implementation of these GANs.

MTV-TSA: Adaptable GAN Encoders for Image Reconstruction via Multi-type Latent Vectors with Two-scale Attentions. This is the official code release fo

owl 37 Dec 24, 2022
NeurIPS 2021 Datasets and Benchmarks Track

AP-10K: A Benchmark for Animal Pose Estimation in the Wild Introduction | Updates | Overview | Download | Training Code | Key Questions | License Intr

AP-10K 82 Dec 11, 2022
An AFL implementation with UnTracer (our coverage-guided tracer)

UnTracer-AFL This repository contains an implementation of our prototype coverage-guided tracing framework UnTracer in the popular coverage-guided fuz

113 Dec 17, 2022
Explainability for Vision Transformers (in PyTorch)

Explainability for Vision Transformers (in PyTorch) This repository implements methods for explainability in Vision Transformers

Jacob Gildenblat 442 Jan 04, 2023
An implementation of Geoffrey Hinton's paper "How to represent part-whole hierarchies in a neural network" in Pytorch.

GLOM An implementation of Geoffrey Hinton's paper "How to represent part-whole hierarchies in a neural network" for MNIST Dataset. To understand this

50 Oct 19, 2022