Tootfinder

XPPLORE: Import, visualize, and analyze XPPAUT data in MATLAB
Matteo Martin, Anna Kishida Thomas, George Bard Ermentrout
https://arxiv.org/abs/2507.02709 h…

XPPLORE: Import, visualize, and analyze XPPAUT data in MATLAB
The analysis of ordinary differential equation (ODE) dynamical systems, particularly in applied disciplines such as mathematical biology and neuroscience, often requires flexible computational workflows tailored to model-specific questions. XPPAUT is a widely used tool combining numerical integration and continuation methods. Various XPPAUT toolboxes have emerged to customize analyses, however, they typically rely on summary '.dat' files and cannot parse the more informative '.auto' files, whic…

REAP-T: A MATLAB Toolbox for Implementing Robust-to-Early Termination Model Predictive Control
Mohsen Amiri, Mehdi Hosseinzadeh
https://arxiv.org/abs/2507.00863

REAP-T: A MATLAB Toolbox for Implementing Robust-to-Early Termination Model Predictive Control
This paper presents a MATLAB toolbox for implementing robust-to-early termination model predictive control, abbreviated as REAP, which is designed to ensure a sub-optimal yet feasible solution when MPC computations are prematurely terminated due to limited computational resources. Named REAP-T, this toolbox is a comprehensive, user-friendly, and modular platform that enables users to explore, analyze, and customize various components of REAP for their specific applications. Notable attributes o…

MATLAB developer bringing systems back online following ransomware attack https://therecord.media/matlab-developer-bringing-systems-online-ransomware

Modeling and Simulation of Coupled Biochemical and Two-Phase Compositional Flow in Underground Hydrogen Storage
Elyes Ahmed, Brahim Amaziane, Salaheddine Chabab, St\'ephanie Delage Santacreu, Guillaume Galli\'ero, Olav M{\o}yner, Xavier Raynaud
https://arxiv.org/abs/2506.02582

Modeling and Simulation of Coupled Biochemical and Two-Phase Compositional Flow in Underground Hydrogen Storage
Integrating microbial activity into underground hydrogen storage models is crucial for simulating long-term reservoir behavior. In this work, we present a coupled framework that incorporates bio-geochemical reactions and compositional flow models within the Matlab Reservoir Simulation Toolbox (MRST). Microbial growth and decay are modeled using a double Monod formulation, with populations influenced by hydrogen and carbon dioxide availability. First, a refined Equation of State (EoS) is employe…

A Matlab-based Toolbox for Automatic EMT Modeling and Small-Signal Stability Analysis of Modern Power Systems
Josep Arevalo-Soler, Dionysios Moutevelis, Elia Mateu-Barriendos, Onur Alican, Carlos Collados-Rodriguez, Marc Cheah-Ma\~ne, Eduardo Prieto-Araujo, Oriol Gomis-Bellmunt
https://arxiv.org/abs/2506.22201

A Matlab-based Toolbox for Automatic EMT Modeling and Small-Signal Stability Analysis of Modern Power Systems
The intensive integration of power converters is changing the way that power systems operate, leading to the emergence of new types of dynamic phenomena and instabilities. At the same time, converters act as an interface between traditional AC grids and their more recent DC counterparts, giving rise to hybrid AC/DC networks. These conditions increase the necessity for stability analysis tools that can simultaneously account for the newly-introduced dynamic phenomena and can also be applied for …

Faddeev-Jackiw Quantization of Classical Constrained Systems
Shaza Abdul Majid, Ansha S Nair, Saurabh Gupta
https://arxiv.org/abs/2507.22505 https://arxiv.…

Faddeev-Jackiw Quantization of Classical Constrained Systems
We accomplish the quantization of a few classical constrained systems à la (modified) Faddeev-Jackiw formalism. We analyze the constraint structure and obtain basic brackets of the theory. In addition, we disclose the gauge symmetries within the symplectic framework. We also provide new interpretation for Lagrange multipliers and outline a MATLAB implementation algorithm for symplectic formulation.

The new #Matlab version (2025a) doesn't keep my favorites pinned and that's very annoying
#JustComplaining

MatBYIB: A Matlab-based code for Bayesian inference of extreme mass-ratio inspiral binary with arbitrary eccentricity
Gen-Liang Li, Shu-Jie Zhao, Huai-Ke Guo, Jing-Yu Su, Zhen-Heng Lin
https://arxiv.org/abs/2506.05954

MatBYIB: A Matlab-based code for Bayesian inference of extreme mass-ratio inspiral binary with arbitrary eccentricity
Accurate parameter estimation(PE) of gravitational waves(GW) is essential for GW data analysis. In extreme mass-ratio inspiral binary(EMRI) systems, orbital eccentricity is a critical parameter for PE. However, current software for for PE of GW often neglects the direct estimation of orbital eccentricity. To fill this gap, we have developed the MatBYIB, a MATLAB-based software package for PE of GW with arbitrary eccentricity. The MatBYIB employs the Analytical Kludge (AK) waveform as a computat…

Replaced article(s) found for hep-th. https://arxiv.org/list/hep-th/new
[2/2]:
- MatBYIB: A Matlab-based code for Bayesian inference of extreme mass-ratio inspiral binary with ar...
Gen-Liang Li, Shu-Jie Zhao, Huai-Ke Guo, Jing-Yu Su, Zhen-Heng Lin

First experimental demonstration of plasma shape control in a tokamak through Model Predictive Control
Adriano Mele, Maria A. Topalova, Cristian Galperti, Stefano Coda, TCV team, Eurofusion Tokamak Exploitation Team
https://arxiv.org/abs/2506.20096

First experimental demonstration of plasma shape control in a tokamak through Model Predictive Control
In this work, a Model Predictive Controller (MPC) is proposed to control the plasma shape in the Tokamak à Configuration Variable (TCV). The proposed controller relies on models obtained by coupling linearized plasma response models, derived from the \texttt{fge} code of the Matlab EQuilibrium toolbox (MEQ) suite, with a state-space description of the core TCV magnetic control system. It optimizes the reference signals fed to this inner control loop in order to achieve the desired plasma shape…

Solution of Least Squares Problems with Randomized Preconditioned Normal Equations
Ilse C. F. Ipsen
https://arxiv.org/abs/2507.18466 https://arxiv.org/pdf/…

Solution of Least Squares Problems with Randomized Preconditioned Normal Equations
We consider the solution of full column-rank least squares problems by means of normal equations that are preconditioned, symmetrically or non-symmetrically, with a randomized preconditioner. With an effective preconditioner, the solutions from the preconditioned normal equations are almost as accurate as those from the QR-based Matlab backslash (mldivide) command -- even for highly illconditioned matrices. This means the accuracy of the preconditioned normal equations depends on the residual o…

Collaborative governance of cyber violence: A two-phase, multi-scenario four-party evolutionary game and SBI1I2R public opinion dissemination
Xiaoting Yang, Wei Lv, Ting Yang, Bart Baesens
https://arxiv.org/abs/2506.19704

Collaborative governance of cyber violence: A two-phase, multi-scenario four-party evolutionary game and SBI1I2R public opinion dissemination
Cyber violence severely disrupts public order in both cyberspace and the real world. Existing studies have gradually advocated collaborative governance but rely on macro-level theoretical analyses. This study integrates micro- and macro-level perspectives to propose a two-stage, multi-scenario governance mechanism for cyber violence. In the first phase, a multi-scenario evolutionary game model with four parties involved in cyber violence was developed based on evolutionary game theory. Matlab s…

DPLib: A Standard Benchmark Library for Distributed Power System Analysis and Optimization
Milad Hasanzadeh, Amin Kargarian
https://arxiv.org/abs/2506.20819

DPLib: A Standard Benchmark Library for Distributed Power System Analysis and Optimization
\textit{DPLib} is an open-source MATLAB-based benchmark library created to support research and development in distributed and decentralized power system analysis and optimization. Distributed and decentralized methods offer scalability, privacy preservation, and resilience to single points of failure, making them increasingly important for modern power systems. However, unlike centralized tools such as MATPOWER, no general-purpose, reproducible data library package currently exists for distrib…

MatBYIB: A Matlab-based code for Bayesian inference of extreme mass-ratio inspiral binary with arbitrary eccentricity
Gen-Liang Li, Shu-Jie Zhao, Huai-Ke Guo, Jing-Yu Su, Zhen-Heng Lin
https://arxiv.org/abs/2506.05954

MatBYIB: A Matlab-based code for Bayesian inference of extreme mass-ratio inspiral binary with arbitrary eccentricity
Accurate parameter estimation(PE) of gravitational waves(GW) is essential for GW data analysis. In extreme mass-ratio inspiral binary(EMRI) systems, orbital eccentricity is a critical parameter for PE. However, current software for for PE of GW often neglects the direct estimation of orbital eccentricity. To fill this gap, we have developed the MatBYIB, a MATLAB-based software package for PE of GW with arbitrary eccentricity. The MatBYIB employs the Analytical Kludge (AK) waveform as a computat…

This https://arxiv.org/abs/2403.16634 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csMS_…

Symbolic and User-friendly Geometric Algebra Routines (SUGAR) for Computations in Matlab
Geometric algebra (GA) is a mathematical tool for geometric computing, providing a framework that allows a unified and compact approach to geometric relations which in other mathematical systems are typically described using different more complicated elements. This fact has led to an increasing adoption of GA in applied mathematics and engineering problems. However, the scarcity of symbolic implementations of GA and its inherent complexity, requiring a specific mathematical background, make it…

Programming Geotechnical Reliability Algorithms using Generative AI
Atma Sharma, Jie Zhang, Meng Lu, Shuangyi Wu, Baoxiang Li
https://arxiv.org/abs/2506.19536

Programming Geotechnical Reliability Algorithms using Generative AI
Programming reliability algorithms is crucial for risk assessment in geotechnical engineering. This study explores the possibility of automating and accelerating this task using Generative AI based on Large Language Models (LLMs). Specifically, the most popular LLM, i.e., ChatGPT, is used to test the ability to generate MATLAB codes for four classical reliability algorithms. The four specific examples considered in this study are: (1) First Order Reliability Method (FORM); (2) Subset simulation…

Low-EFFourth: A computational framework for generating and studying multilevel model ensembles in low-dimensional systems
Francisco de Melo Vir\'issimo
https://arxiv.org/abs/2506.03313

Low-EFFourth: A computational framework for generating and studying multilevel model ensembles in low-dimensional systems
This paper introduces Low-EFFourth (LEF4), a MATLAB-based computational framework designed for generating and studying multilevel model ensembles in continuous dynamical systems. Initially developed to address questions in climate modelling, LEF4 can also be used in other disciplines such as epidemiology, economics, and engineering, with minimal modifications to the code. The framework provides an efficient and flexible approach for investigating uncertainties arising from initial conditions, m…

Matrix best approximation in the spectral norm
Vance Faber, J\"org Liesen, Petr Tich\'y
https://arxiv.org/abs/2506.09687 https://

Matrix best approximation in the spectral norm
We derive, similar to Lau and Riha, a matrix formulation of a general best approximation theorem of Singer for the special case of spectral approximations of a given matrix from a given subspace. Using our matrix formulation we describe the relation of the spectral approximation problem to semidefinite programming, and we present a simple MATLAB code to solve the problem numerically. We then obtain geometric characterizations of spectral approximations that are based on the $k$-dimensional fiel…