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We introduce Dionysos.jl, a modular package for solving optimal control problems for complex dynamical systems using state-of-the-art and experimental techniques from symbolic control, optimization, and learning. More often than not with…

Systems and Control · Electrical Eng. & Systems 2025-02-14 Julien Calbert , Adrien Banse , Benoît Legat , Raphaël M. Jungers

Sunny is a Julia package designed to serve the needs of the quantum magnetism community. It supports the specification of a very broad class of spin models and a diverse suite of numerical solvers. These include powerful methods for…

In this paper we present \texttt{SymOrb.jl}, a software which combines group representation theory and variational methods to provide numerical solutions of singular dynamical systems of paramount relevance in Celestial Mechanics and other…

This paper introduces the algorithmic design and implementation of Tulip, an open-source interior-point solver for linear optimization. It implements a regularized homogeneous interior-point algorithm with multiple centrality corrections,…

Optimization and Control · Mathematics 2022-04-04 Miguel F. Anjos , Andrea Lodi , Mathieu Tanneau

Hamilton's equations are fundamental for modeling complex physical systems, where preserving key properties such as energy and momentum is crucial for reliable long-term simulations. Geometric integrators are widely used for this purpose,…

Machine Learning · Computer Science 2026-03-17 Priscilla Canizares , Davide Murari , Carola-Bibiane Schönlieb , Ferdia Sherry , Zakhar Shumaylov

We introduce $\texttt{RandomMeas$.$jl}$, a modular and high-performance open-source software package written in Julia for implementing and analyzing randomized measurement protocols in quantum computing. Randomized measurements provide a…

Quantum Physics · Physics 2026-04-29 Andreas Elben , Benoît Vermersch

Symbolic Regression (SR) holds great potential for uncovering underlying mathematical and physical relationships from observed data. However, the vast combinatorial space of possible expressions poses significant challenges for both online…

Machine Learning · Computer Science 2025-02-12 Yuan Tian , Wenqi Zhou , Michele Viscione , Hao Dong , David Kammer , Olga Fink

Symbolic Regression (SR) holds great potential for uncovering underlying mathematical and physical relationships from observed data. However, the vast combinatorial space of possible expressions poses significant challenges for both online…

Machine Learning · Computer Science 2025-02-14 Yuan Tian , Wenqi Zhou , Michele Viscione , Hao Dong , David Kammer , Olga Fink

Understanding astrophysical and cosmological processes can be challenging due to their complexity and lack of intuitive analogies. To address this, we present \texttt{AstronomyCalc}, a Python package specifically designed to aid…

Physics Education · Physics 2025-11-26 Sambit K. Giri

MomentClosure.jl is a Julia package providing automated derivation of the time-evolution equations of the moments of molecule numbers for virtually any chemical reaction network using a wide range of moment closure approximations. It…

Molecular Networks · Quantitative Biology 2021-05-13 Augustinas Sukys , Ramon Grima

Computing the matter power spectrum, $P(k)$, as a function of cosmological parameters can be prohibitively slow in cosmological analyses, hence emulating this calculation is desirable. Previous analytic approximations are insufficiently…

This work develops a new open source API and software package called \textit{SymPhas} for simulations of phase-field, phase-field crystal and reaction-diffusion models, supporting up to three dimensions and an arbitrary number of fields.…

Computational Physics · Physics 2021-09-07 Steven A. Silber , Mikko Karttunen

This paper presents solutions to Einstein's equation -- and the numerical methods used to construct them -- that describe simple cosmological models on manifolds with compact non-orientable spatial slices. These solutions have been…

General Relativity and Quantum Cosmology · Physics 2026-04-28 Fan Zhang , Lee Lindblom

Analytical solutions to differential equations offer exact, interpretable insight but are rarely available because discovering them requires expert intuition or exhaustive search of combinatorial spaces. We introduce SIGS, a neuro-symbolic…

Machine Learning · Computer Science 2026-05-22 Orestis Oikonomou , Levi Lingsch , Dana Grund , Siddhartha Mishra , Georgios Kissas

Large Language Models (LLMs) have emerged as a promising alternative to traditional static program analysis methods, such as symbolic execution, offering the ability to reason over code directly without relying on theorem provers or SMT…

Programming Languages · Computer Science 2025-09-22 Yihe Li , Ruijie Meng , Gregory J. Duck

Current and upcoming cosmological experiments open a new era of precision cosmology, thus demanding accurate theoretical predictions for cosmological observables. Because of the complexity of the codes delivering such predictions, reaching…

Cosmology and Nongalactic Astrophysics · Physics 2020-05-05 F. Tarsitano , U. Schmitt , A. Refregier , J. Fluri , R. Sgier , A. Nicola , J. Herbel , A. Amara , T. Kacprzak , L. Heisenberg

TopologicalNumbers.jl is an open-source Julia package designed to calculate topological invariants, mathematical quantities that characterize the properties of materials in condensed matter physics. These invariants, such as the Chern…

Mesoscale and Nanoscale Physics · Physics 2025-04-29 Keisuke Adachi , Minoru Kanega

Quantum computing has made tremendous progress in recent years, providing potentialities for breaking the bottleneck of computing power in the field of scientific computing, like computational fluid dynamics. To reduce computational costs…

Quantum Physics · Physics 2025-05-05 Li Xu , Ming Li , Lei Zhang , Hai Sun , Jun Yao

TensorKit.jl is a Julia-based software package for tensor computations, especially focusing on tensors with internal symmetries. This paper introduces the design philosophy, core functionalities, and distinctive features, including how to…

Mathematical Software · Computer Science 2025-08-15 Lukas Devos , Jutho Haegeman

Approximating partial differential equations for extensive industrial and scientific applications requires leveraging the power of modern high-performance computing. In large-scale parallel computations, the geometrical discretisation…

Numerical Analysis · Mathematics 2024-12-30 Pere A. Martorell , Santiago Badia
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