Tootfinder

The Mixed-Sparse-Smooth-Model Toolbox (MSSM): Efficient Estimation and Selection of Large Multi-Level Statistical Models
Joshua Krause, Jelmer P. Borst, Jacolien van Rij
https://arxiv.org/abs/2506.13132

The Mixed-Sparse-Smooth-Model Toolbox (MSSM): Efficient Estimation and Selection of Large Multi-Level Statistical Models
Additive smooth models, such as Generalized additive models (GAMs) of location, scale, and shape (GAMLSS), are a popular choice for modeling experimental data. However, software available to fit such models is usually not tailored specifically to the estimation of mixed models. As a result, estimation can slow down as the number of random effects increases. Additionally, users often have to provide a substantial amount of problem-specific information in case they are interested in more general …

Quantum Algorithm Software for Condensed Matter Physics
T. Farajollahpour
https://arxiv.org/abs/2506.09308 https://arxiv.org/pdf/2506…

Quantum Algorithm Software for Condensed Matter Physics
This report offers a comprehensive analysis of the evolving landscape of quantum algorithm software specifically tailored for condensed matter physics. It examines fundamental quantum algorithms such as Variational Quantum Eigensolver (VQE), Quantum Phase Estimation (QPE), Quantum Annealing (QA), Quantum Approximate Optimization Algorithm (QAOA), and Quantum Machine Learning (QML) as applied to key condensed matter problems including strongly correlated systems, topological phases, and quantum …

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…

iRonCub 3: The Jet-Powered Flying Humanoid Robot
Davide Gorbani, Hosameldin Awadalla Omer Mohamed, Giuseppe L'Erario, Gabriele Nava, Punith Reddy Vanteddu, Shabarish Purushothaman Pillai, Antonello Paolino, Fabio Bergonti, Saverio Taliani, Alessandro Croci, Nicholas James Tremaroli, Silvio Traversaro, Bruno Vittorio Trombetta, Daniele Pucci
https…

iRonCub 3: The Jet-Powered Flying Humanoid Robot
This article presents iRonCub 3, a jet-powered humanoid robot, and its first flight experiments. Unlike traditional aerial vehicles, iRonCub 3 aims to achieve flight using a full-body humanoid form, which poses unique challenges in control, estimation, and system integration. We highlight the robot's current mechanical and software architecture, including its propulsion system, control framework, and experimental infrastructure. The control and estimation framework is first validated in simulat…

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/2407.02764 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csOS_…

Data-driven Software-based Power Estimation for Embedded Devices
Energy measurement of computer devices, which are widely used in the Internet of Things (IoT), is an important yet challenging task. Most of these IoT devices lack ready-to-use hardware or software for power measurement. In this paper, we propose an easy-to-use approach to derive a software-based energy estimation model with external low-end power meters based on data-driven analysis. Our solution is demonstrated with a Jetson Nano board and Ruideng UM25C USB power meter. Various machine learni…

Apax: A Flexible and Performant Framework For The Development of Machine-Learned Interatomic Potentials
Moritz Ren\'e Sch\"afer, Nico Segreto, Fabian Zills, Christian Holm, Johannes K\"astner
https://arxiv.org/abs/2505.22168

Apax: A Flexible and Performant Framework For The Development of Machine-Learned Interatomic Potentials
We introduce Atomistic learned potentials in JAX (apax), a flexible and efficient open source software package for training and inference of machine-learned interatomic potentials. Built on the JAX framework, apax supports GPU acceleration and implements flexible model abstractions for fast development. With features such as kernel-based data selection, well-calibrated uncertainty estimation, and enhanced sampling, it is tailored to active learning applications and ease of use. The features and…