20 skills found
rafael-fuente / Diffractsim✨🔬 A flexible diffraction simulator for exploring and visualizing physical optics.
brandondube / Prysmphysical optics: integrated modeling, phase retrieval, segmented systems, polynomials and fitting, sequential raytracing...
spacetelescope / PoppyPhysical Optics Propagation in Python
mperrin / PoppyPhysical Optics Propagation in Python
JuliaPhysics / PhysicalOptics.jlA package for simulation of physical optics. Physical optics is more general than ray optics but not as general as full electrodynamics.
srio / DiffractionPhysical Optics Diffraction experiments with Python
bjornsturmberg / EMUstackEMUstack is an open-source simulation package for calculating light propagation through multi-layered stacks of dispersive, lossy, nanostructured, optical media. It implements a generalised scattering matrix method, which extends the physical intuition of thin film optics to complex structures.
pingpongballz / PO SBR PythonA python implementation of shooting and bouncing rays (PO-SBR), accelerated using OptiX.
PyPO-dev / PyPO📡 Open-source physical optics simulation package.
andykee / LentilHeart-healthy physical optics
aeberspaecher / PyopticsPhysical optics in Python
jdaniel400 / Computational ElectromagneticsResearch project in computational electromagnetics. Software program simulates approximate physical optics currents on conductor meshes and calculates scattering E fields
arielmission-space / PAOSPAOS is a fast, modern, and reliable Python package for Physical Optics studies.
flechsig / Phasea physical optics package
Littlehhh / Physical OpticsPhysical Optics HomeWork
seghil / OpenCavityPython package for laser cavities design: 1D/2D eigenmodes solver plus physical optics propagation
brandondube / Praisereference implementation of contemporary "forward-reverse" or "iterative transform" phase retrieval algorithms
DebarghyaTapadar29 / PO MEC Multi Band RCS Radar Cross Section MATLAB tool for 3D Radar Cross Section (RCS) analysis. Implements Physical Optics (PO) with optional Method of Edge Currents (MEC) for efficient prediction from STL geometry across frequency bands and viewing angles.
Sagnac / Zernike.jlGenerates Zernike polynomials, models wavefront errors, and plots them using Makie.
Abhishek-chohan / WiFi Positioning And Analysis SystemIt is very difficult to think of an aspect of life that has not been affected by the Internet. It does more than just connecting computers. It connects people, lives, stories, and businesses. Wireless networks are present in all the large buildings or sites, and they are anticipated to provide high-speed Internet for the connected users. This can be attained by connecting wireless routers to the Internet backbone through fast connection cables (e.g. fiber optics), or as well finding the optimal position of the router along with the location, so that the targeted area is covered with Internet access as much as possible, provided that the cost constraints of routers and the cost of their mutual interconnection are satisfied. As the placement of WI-FI routers in the network is a very intensive problem concerning connectivity and coverage. It directly affects the transmission loss, installation cost, operational complexity, wi-fi network coverage, etc. However, optimizing the location of the routers can resolve these issues and increase network performance. Therefore, using major deep-learning models this problem can be resolved. The proposed model concentrates on the optimization of the objective function in terms of the empty spaces in the location, hindrances such as concrete walls, metallic objects, etc. in the area, client coverage in the location, and the network connectivity. It is an initial step to ensure the desired network performance such as throughput, connectivity, and coverage of the network. The model also additionally bifurcates the areas into divisions based on the network coverage in each region for particular chores like messaging, streaming, gaming, etc. Furthermore, an advanced Wi-Fi analyzing system for generating different results based on the observations of the Wi-Fi router and the network it is placed in is implemented. It gives an analysis report of the Wi-Fi router. It dictates the number of users presently connected to the system with their description like IP Address, Physical Address, etc and also determines the information regarding the devices in the network range of the router. It executes signal strength testing that demonstrates the strength of the signal in the network and also performs a speed testing module that determines the upload speed and the download speed of the system using real-time graph plotting. The computational experiment, performed over a dataset of sample house maps, to indicate the optimal position of the Wi-Fi proposes that the approach can obtain great results. Consequently, the results indicate that the approach can be easily adapted for application in practice for determining the network areas based on the signal strengths in the region, in terms of the Wi-Fi router placement and analyze the wireless network, devices in the network, and the connected users. The application can be extended to provide co-ordinates for a 3D map. The model can also be paired with some hardware to increase portability.
