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Related papers: SPINAS: Spinor Amplitude Subroutines for Construct…

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The Spinsim python package simulates spin-half and spin-one quantum mechanical systems following a time dependent Shroedinger equation. It makes use of numba.cuda, which is an LLVM (Low Level Virtual Machine) compiler for Nvidia Cuda…

Quantum Physics · Physics 2023-03-22 Alex Tritt , Joshua Morris , Joel Hochstetter , R. P. Anderson , James Saunderson , L. D. Turner

A large part of modern research, especially in the broad field of complex systems, relies on the numerical integration of PDEs, with and without stochastic noise. This is usually done with eiher in-house made codes or external packages like…

Computational Physics · Physics 2024-10-03 Fernando Caballero

A FORM program which is used to efficiently expand in components pure spinor superfield expressions of kinematic factors is presented and comments on how it works are made. It is highly customizable using the standard features of FORM and…

High Energy Physics - Theory · Physics 2010-07-29 Carlos R. Mafra

The article presents and documents the Mathematica package SymBuild. This package implements the computation and manipulation of integrable symbols appearing in various calculations in high-energy scattering amplitudes. By using Gr\"obner…

High Energy Physics - Theory · Physics 2018-11-01 Vladimir Mitev , Yang Zhang

Numerical methods are a powerful tool for doing calculations in spinfoam theory. We review the major frameworks available, their definition, and various applications. We start from $\texttt{sl2cfoam-next}$, the state-of-the-art library to…

General Relativity and Quantum Cosmology · Physics 2023-09-12 Pietro Dona , Muxin Han , Hongguang Liu

This paper presents SPIROS (Streamlined, Precise, Intuitive, and Rapid Optical Simulator), a dedicated optical simulation tool developed for the design and analysis of particle physics detectors. Unlike general-purpose frameworks such as…

Instrumentation and Detectors · Physics 2026-04-10 Tatsuya Kikawa

Reasonable evaluation of composition amplitude in spinodal decomposition is a challenge to microanalysis of atom probe tomography, especially at early stages when phase separation is not prominent. This impedes quantitative analysis of…

Materials Science · Physics 2012-05-21 Wei Xiong , John Ågren , Jing Zhou

The "Spinors" software is a "Mathematica" package which implements 2-component spinor calculus as devised by Penrose for General Relativity in dimension 3+1. The "Spinors" software is part of the "xAct" system, which is a collection of…

General Relativity and Quantum Cosmology · Physics 2015-05-30 Alfonso García-Parrado Gómez-Lobo , José M. Martín-García

The Algebra of Physical Space (APS) is used to explore the Constructive Standard Model (CSM) of particle physics. Namely, this paper connects the spinor formalism of the APS to massive amplitudes in the CSM. A novel equivalency between…

High Energy Physics - Phenomenology · Physics 2026-01-26 Moab Croft , Neil Christensen

SPARC is an accurate, efficient, and scalable real-space electronic structure code for performing ab initio Kohn-Sham density functional theory calculations. Version 2.0.0 of the software provides increased efficiency, and includes…

The increasing availability of high-quality optical and near-infrared spectroscopic data, as well as advances in modelling techniques, have greatly expanded the scientific potential of spectroscopic studies. However, the software tools…

Instrumentation and Methods for Astrophysics · Physics 2025-12-23 Daniele Gasparri , Lorenzo Morelli , Umberto Battino , Jairo Méndez Abreu , Adriana de Lorenzo-Cáceres

A computational nanophotonic design library for gradient-based optimization called SPINS is presented. Borrowing the concept of computational graphs, SPINS is a design framework that emphasizes flexibility and reproducible results. The…

In this work, the library spinney is presented, which provides an implementation of helicity spinors and related algorithms for the symbolical manipulation program Form. The package is well suited for symbolic amplitude calculations both in…

High Energy Physics - Phenomenology · Physics 2011-08-04 Gavin Cullen , Maciej Koch-Janusz , Thomas Reiter

We discuss a high-performance and high-throughput hardware accelerator for probabilistic Spiking Neural Networks (SNNs) based on Generalized Linear Model (GLM) neurons, that uses binary STT-RAM devices as synapses and digital CMOS logic for…

Neural and Evolutionary Computing · Computer Science 2020-08-06 Anakha V Babu , Osvaldo Simeone , Bipin Rajendran

The rise of Physics-Informed Neural Networks (PINNs) has popularized the concept of solving differential equations via residual minimization. However, neural networks are often viewed as ``black boxes" requiring significant computational…

Numerical Analysis · Mathematics 2026-05-20 Ayman Mourad , Fatima Mroue

PINT is a pure-Python framework for high-precision pulsar timing developed on top of widely used and well-tested Python libraries, supporting both interactive and programmatic data analysis workflows. We present a new frequentist framework…

The Laura++ software package is designed for performing fits of amplitude models to data from decays of spin-0 particles into final states containing three spin-0 particles - so-called Dalitz-plot analysis. An overview of the amplitude…

Data Analysis, Statistics and Probability · Physics 2016-05-30 Thomas Latham

The concept of phase space amplitudes for systems with continuous degrees of freedom is generalized to finite-dimensional spin systems. Complex amplitudes are obtained on both a sphere and a finite lattice, in each case enabling a more…

Quantum Physics · Physics 2015-05-20 P Watson , A J Bracken

The discovery of pure spinor formalism makes the computation of superstring scattering amplitudes possible. In this paper, we will illustrate how computer algebra system Cadabra is used in computing the supersymmetric amplitude in pure…

High Energy Physics - Theory · Physics 2016-08-17 Ke-Sheng Sun , Xiang-Mao Ding , Fei Sun , Hai-Bin Zhang

Spiking neural networks (SNNs) offer energy efficiency over artificial neural networks (ANNs) but suffer from high latency and computational overhead due to their multi-timestep operational nature. While various dynamic computation methods…

Machine Learning · Computer Science 2025-08-21 Donghwa Kang , Doohyun Kim , Sang-Ki Ko , Jinkyu Lee , Brent ByungHoon Kang , Hyeongboo Baek
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