James D. Neuhaus, Nathan Nichols, Debshikha Banerjee et al. · SciPost Physics Codebases · 2024
We introduce the SmoQyDEAC.jl package, a Julia implementation of the Differential Evolution Analytic Continuation (DEAC) algorithm [N. S. Nichols et al., Phys. Rev. E 106, 025312 (2022)] for analytically continuing noisy imaginary time correlation functions to the real frequency axis. Our implementation supports fermionic and bosonic correlation functions on either the imaginary time or Matsubara frequency axes, and treatment of the covariance error in the input data. This paper presents an overview of the DEAC algorithm and the features implemented in the SmoQyDEAC.jl package. It also provides detailed benchmarks of the package’s output against the popular maximum entropy and stochastic analytic continuation methods. The code for this package can be downloaded from our GitHub repository at https://github.com/SmoQySuite/SmoQyDEAC.jl or installed using the Julia package manager. The online documentation, including examples, can be accessed at https://smoqysuite.github.io/SmoQyDEAC.jl/stable/.
Cited by 1Open access
S. Gardiner, Joshua Isaacson, L. Pickering · SciPost Physics Codebases · 2025
Simulations of neutrino interactions are playing an increasingly important role in the pursuit of high-priority measurements for the field of particle physics. A significant technical barrier for efficient development of these simulations is the lack of a standard data format for representing individual neutrino scattering events. We propose and define such a universal format, named NuHepMC, as a common standard for the output of neutrino event generators. The NuHepMC format uses data structures and concepts from the HepMC3 event record library adopted by other subfields of high-energy physics. These are supplemented with an original set of conventions for generically representing neutrino interaction physics within the HepMC3 infrastructure.
Cited by 1Open access
Lukas Rammelmüller, David Huber, Artem G. Volosniev · SciPost Physics Codebases · 2023
We introduce a generic and accessible implementation of an exact diagonalization method for studying few-fermion models. Our aim is to provide a testbed for the newcomers to the field as well as a stepping stone for trying out novel optimizations and approximations. This userguide consists of a description of the algorithm, and several examples in varying orders of sophistication. In particular, we exemplify our routine using an effective-interaction approach that fixes the low-energy physics. We benchmark this approach against the existing data, and show that it is able to deliver state-of-the-art numerical results at a significantly reduced computational cost.
Cited by 1Open access
Jan Košata, Javier del Pino, Toni L. Heugel et al. · SciPost Physics Codebases · 2022
HarmonicBalance.jl is a publicly available Julia package designed to simplify and solve systems of periodic time-dependent nonlinear ordinary differential equations. Time dependence of the system parameters is treated with the harmonic balance method, which approximates the system’s behaviour as a set of harmonic terms with slowly-varying amplitudes. Under this approximation, the set of all possible steady-state responses follows from the solution of a polynomial system. In HarmonicBalance.jl, we combine harmonic balance with contemporary implementations of symbolic algebra and the homotopy continuation method to numerically determine all steady-state solutions and their associated fluctuation dynamics. For the exploration of involved steady-state topologies, we provide a simple graphical user interface, allowing for arbitrary solution observables and phase diagrams. HarmonicBalance.jl is a free software available at https://github.com/NonlinearOscillations/HarmonicBalance.jl.
Cited by 2Open access
Simon Kiesewetter, Ria Rushin Joseph, P. D. Drummond · SciPost Physics Codebases · 2023
The xSPDE toolbox treats stochastic partial and ordinary differential equations, with applications in biology, chemistry, engineering, medicine, physics and quantum technologies. It computes statistical averages, including time-step and/or sampling error estimation. xSPDE can provide higher order convergence, Fourier spectra and probability densities. The toolbox has graphical output and \chi^{2} <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:msup><mml:mi>χ</mml:mi><mml:mn>2</mml:mn></mml:msup></mml:math> statistics, as well as weighted, projected, or forward-backward equations. It can generate input-output quantum spectra. All equations may have independent periodic, Dirichlet, and Neumann or Robin boundary conditions in any dimension, for any vector field component, and at either end of any interval.
Cited by 1Open access
Kosuke Nogaki, Jiani Fei, Emanuel Gull et al. · SciPost Physics Codebases · 2023
We introduce a Julia implementation of the recently proposed Nevanlinna analytic continuation method. The method is based on Nevanlinna interpolants and inherently preserves the causality of a response function due to its construction. For theoretical calculations without statistical noise, this continuation method is a powerful tool to extract real-frequency information from numerical input data on the Matsubara axis. This method has been applied to first-principles calculations of correlated materials. This paper presents its efficient and full-featured open-source implementation of the method including the Hamburger moment problem and smoothing.
Cited by 3Open access
Michael N. Evans · 2025
<strong class="journal-contentHeaderColor">Abstract.</strong> We present a database of curated databases (DoD2k version 1) developed for Common Era (1–2000 A.D.) paleoclimate research. The DoD2k leverages existing community efforts, many of which arise from the PAGES (Past Global Changes) 2k working group, and the codebase developed by the paleoclimate data informatics communities over the past decade. Using a common, compact set of terms for metadata and data management, we merge five existing curated databases. These individual curated databases represent a range of approaches, from single archive-single observation to multiarchive-multiobservation collections, and span a total of 14 archives, 49 data types, and 4613 records within the Common Era. We then use a multistage algorithm to remove duplicates, checking against a common set of metadata and comparison metrics. We illustrate the value of the DoD2k with two applications. In the first, we extract the moisture and temperature subset of records and perform an empirical orthogonal function (EOF) analysis on the resulting multi-archive, multi-observation dataset. In the second, we show that calcite speleothem oxygen isotopic composition is consistent with proxy system simulations. DoD2k may also be useful for paleoclimatic detection and attribution analysis using proxy system modeling, data assimilation, and deep learning for the development and testing of improved proxy system models.
Cited by 0Open access
Alex Towell · Zenodo (CERN European Organization for Nuclear Research) · 2026
Remove ~1,300 lines of dead code, redundant comments, unused concepts, and duplicated logic across all layers while preserving full API compatibility and test coverage (486 tests pass). Highlights Dead code removal Removed 12 unused C++20 concepts across algorithms/concepts and methods/concepts Removed unused type traits, forward declarations, and speculative abstractions Removed unused includes (<functional>, <span>, <ranges>, <vector>, etc.) Duplication elimination Extracted detail::tag_name<Tag>() — maps function tags to string names (replaced 34-line if-constexpr chain) Extracted detail::make_integrand_fn<Dim>() — consolidates triplicated integrand lambda construction Extracted detail::mc_box_sampler<T, Dims> — shared Monte Carlo RNG and sampling logic Extracted detail::make_extended_args() — shared argument tuple construction for sum/product Extracted combine_results() — deduplicated product integral error propagation Bug fixes Fixed incorrect #include in conditional.hpp and sum_product.hpp Replaced unimplementable gauss_legendre primary template with static_assert listing supported N values Fixed MSVC AVX2 flag to respect ENABLE_AVX2 option (was unconditional) Removed redundant global CMAKE_CXX_STANDARD (already set via target_compile_features) Test improvements Extracted limes_add_test() CMake function (108 → 54 LOC) Made test RNG deterministic with fixed seed Modernized: std::numbers::pi instead of M_PI Removed dead test assertions and redundant concept tests Documentation Rewrote ARCHITECTURE.md to match actual v3.x codebase (was outdated from v1.x) Fixed README.md CMake version requirement (3.16 → 3.20) Updated CLAUDE.md with current concept inventory and detail namespace Stats 38 files changed, 698 insertions, 1,965 deletions (net −1,267 lines) 486 tests pass — zero functionality changes
Cited by 0Open access
Konstantin A. Maslov · Zenodo (CERN European Organization for Nuclear Research) · 2026
This repository contains all the codebase underlying the dissertation titled "AI's Eyes on Ice: Large-Scale Glacier Mapping and Surface Mass Balance Modelling with Earth Observation and Deep Learning." The contents correspond to the state of each repository as of 20 Feb 2026. Each project is included as a direct copy of the corresponding GitHub repository at the referenced date (without commit history). Included repositories:- https://github.com/konstantin-a-maslov/scalable_glacier_mapping- https://github.com/konstantin-a-maslov/icemapper- https://github.com/konstantin-a-maslov/glacier_facies_classification- https://github.com/konstantin-a-maslov/glaunti- https://github.com/konstantin-a-maslov/massive_ice_divides- https://github.com/konstantin-a-maslov/demimputation Each subproject retains its original license (GNU General Public License v2) as specified in its respective repository. For the most up-to-date versions, including issue tracking and full git histories, please consult the original GitHub repositories.
Cited by 0Open access
Konstantin A. Maslov · Zenodo (CERN European Organization for Nuclear Research) · 2026
This repository contains all the codebase underlying the dissertation titled "AI's Eyes on Ice: Large-Scale Glacier Mapping and Surface Mass Balance Modelling with Earth Observation and Deep Learning." The contents correspond to the state of each repository as of 20 Feb 2026. Each project is included as a direct copy of the corresponding GitHub repository at the referenced date (without commit history). Included repositories:- https://github.com/konstantin-a-maslov/scalable_glacier_mapping- https://github.com/konstantin-a-maslov/icemapper- https://github.com/konstantin-a-maslov/glacier_facies_classification- https://github.com/konstantin-a-maslov/glaunti- https://github.com/konstantin-a-maslov/massive_ice_divides- https://github.com/konstantin-a-maslov/demimputation Each subproject retains its original license (GNU General Public License v2) as specified in its respective repository. For the most up-to-date versions, including issue tracking and full git histories, please consult the original GitHub repositories.
Cited by 0Open access
Ippocratis D. Saltas, Roberto Oliveri · SciPost Physics Codebases · 2025
We describe a simple and efficient Python code to perform Bayesian forecasting for gravitational waves (GW) produced by Extreme-Mass-Ratio-Inspiral systems (EMRIs). The code runs on GPUs for an efficient parallelised computation of thousands of waveforms and sampling of the posterior through a Markov-Chain-Monte-Carlo (MCMC) algorithm. EMRI_MC generates EMRI waveforms based on the so-called kludge scheme, and propagates it to the observer accounting for cosmological effects in the observed waveform due to modified gravity/dark energy. The code provides a helpful resource for forecasts for interferometry missions in the milli-Hz scale, e.g the satellite-mission LISA.
Cited by 1Open access
Thomas Biekötter · SciPost Physics Codebases · 2026
evortran is a modern Fortran library designed for high-performance genetic algorithms and evolutionary optimization. evortran can be used to tackle a wide range of problems in high-energy physics and beyond, such as derivative-free parameter optimization, complex search taks, parameter scans and fitting experimental data under the presence of instrumental noise. The library is built as an fpm package with flexibility and efficiency in mind, while also offering a simple installation process, user interface and integration into existing Fortran (or Python) programs. evortran offers a variety of selection, crossover, mutation and elitism strategies, with which users can tailor an evolutionary algorithm to their specific needs. evortran supports different abstraction levels: from operating directly on individuals and populations, to running full evolutionary cycles, and even enabling migration between independently evolving populations to enhance convergence and maintain diversity. In this paper, we present the functionality of the evortran library, demonstrate its capabilities with example benchmark applications, and compare its performance with existing genetic algorithm frameworks. As physics-motivated applications, we use evortran to confront extended Higgs sectors with LHC data and to reconstruct gravitational wave spectra and the underlying physical parameters from LISA mock data, demonstrating its effectiveness in realistic, data-driven scenarios.
Cited by 1Open access
Enrico Bothmann, Walter T. Giele, Stefan Höche et al. · SciPost Physics Codebases · 2022
The compute efficiency of Monte-Carlo event generators for the Large Hadron Collider is expected to become a major bottleneck for simulations in the high-luminosity phase. Aiming at the development of a full-fledged generator for modern GPUs, we study the performance of various recursive strategies to compute multi-gluon tree-level amplitudes. We investigate the scaling of the algorithms on both CPU and GPU hardware. Finally, we provide practical recommendations as well as baseline implementations for the development of future simulation programs. The GPU implementations can be found at: https://www.gitlab.com/ebothmann/blockgen-archive.
Cited by 4Open access
Dominik Kiese, Anxiang Ge, Nepomuk Ritz et al. · SciPost Physics Codebases · 2024
The Matsubara Green’s function formalism stands as a powerful technique for computing the thermodynamic characteristics of interacting quantum many-particle systems at finite temperatures. In this manuscript, our focus centers on introducing MatsubaraFunctions.jl, a Julia library that implements data structures for generalized n-point Green’s functions on Matsubara frequency grids. The package’s architecture prioritizes user-friendliness without compromising the development of efficient solvers for quantum field theories in equilibrium. Following a comprehensive introduction of the fundamental types, we delve into a thorough examination of key facets of the interface. This encompasses avenues for accessing Green’s functions, techniques for extrapolation and interpolation, as well as the incorporation of symmetries and a variety of parallelization strategies. Examples of increasing complexity serve to demonstrate the practical utility of the library, supplemented by discussions on strategies for sidestepping impediments to optimal performance.
Cited by 2Open access
Benjamin Cohen-Stead, Sohan Malkaruge Costa, James D. Neuhaus et al. · SciPost Physics Codebases · 2024
We introduce the SmoQyDQMC.jl package, a Julia implementation of the determinant quantum Monte Carlo algorithm. SmoQyDQMC.jl supports generalized tight-binding Hamiltonians with on-site Hubbard and generalized electron-phonon ( e <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mi>e</mml:mi></mml:math> -ph) interactions, including non-linear e <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mi>e</mml:mi></mml:math> -ph coupling and anharmonic lattice potentials. Our implementation uses hybrid Monte Carlo methods with exact forces for sampling the phonon fields, enabling efficient simulation of low-energy phonon branches, including acoustic phonons. The SmoQyDQMC.jl package also uses a flexible scripting interface, allowing users to adapt it to different workflows and interface with other software packages in the Julia ecosystem. The code for this package can be downloaded from our GitHub repository at https://github.com/SmoQySuite/SmoQyDQMC.jl or installed using the Julia package manager. The online documentation, including examples, can be obtained from our document page at https://smoqysuite.github.io/SmoQyDQMC.jl/stable/.
Cited by 6Open access
Valentina Gualtieri, Charles Renshaw-Whitman, Vinicius Hernandes et al. · SciPost Physics Codebases · 2025
We introduce QDsim, a Python package tailored for the rapid generation of charge stability diagrams in large-scale quantum dot devices, extending beyond traditional double or triple dots. QDsim is founded on the constant interaction model from which we rephrase the task of finding the lowest energy charge configuration as a convex optimization problem. Therefore, we can leverage the existing package CVXPY, in combination with an appropriate powerful solver, for the convex optimization which streamlines the creation of stability diagrams and polytopes. Through multiple examples, we demonstrate how QDsim enables the generation of large-scale dataset that can serve a basis for the training of machine-learning models for automated tuning algorithms. While the package currently does not support quantum effects beyond the constant interaction model, QDsim is a tool that directly addresses the critical need for cost-effective and expeditious data acquisition for better tuning algorithms in order to accelerate the development of semiconductor quantum devices.
Cited by 2Open access
Nicolas Loizeau, J. Clayton Peacock, Dries Sels · SciPost Physics Codebases · 2025
We present the Julia package PauliStrings.jl for quantum many-body simulations, which performs fast operations on the Pauli group by encoding Pauli strings in binary. All of the Pauli string algebra is encoded into low-level logic operations on integers, and is made efficient by various truncation methods which allow for systematic extrapolation of the results. We illustrate the effectiveness of our package by (i) performing Heisenberg time evolution through direct numerical integration and (ii) by constructing a Liouvillian Krylov space. We benchmark the results against tensor network methods, and we find our package performs favorably. In addition, we show that this representation allows for easy encoding of any geometry. We present results for chaotic and integrable spin systems in 1D as well as some examples in 2D. Currently, the main limitations are the inefficiency of representing non-trivial pure states (or other low-rank operators), as well as the need to introduce dissipation to probe long-time dynamics.
Cited by 4Open access
Sofia Ponomareva, Adelin Patoux, Clément Majorel et al. · SciPost Physics Codebases · 2025
We present “torchGDM”, a numerical framework for nano-optical simulations based on the Green’s Dyadic Method (GDM). This toolkit combines a hybrid approach, allowing for both fully discretized nano-structures and structures approximated by sets of effective electric and magnetic dipoles. It supports simulations in three dimensions and for infinitely long, two-dimensional structures. This capability is particularly suited for multi-scale modeling, enabling accurate near-field calculations within or around a discretized structure embedded in a complex environment of scatterers represented by effective models. Importantly, torchGDM is entirely implemented in PyTorch, a well-optimized and GPU-enabled automatic differentiation framework. This allows for the efficient calculation of exact derivatives of any simulated observable with respect to various inputs, including positions, wavelengths or permittivity, but also intermediate parameters like Green’s tensor components, which can be interesting for physics informed deep learning applications. We anticipate that this toolkit will be valuable for applications merging nano-photonics and machine learning, as well as for solving nano-photonic optimization and inverse problems, such as the global design and characterization of metasurfaces, where optical interactions between structures are critical.
Cited by 1Open access
Fitzgerald, Emily, Belton, Amanda, LEE, STUART et al. · Figshare · 2025
Code for maps shared as foundations for the participatory mapping workshops and maps resulting from the community workshops that were refined for publication in the Pursuit article for the theme. The code for creating maps for the Map of the Month project is organised into themes by the individual authors.
Cited by 0Open access
Lorenzo Crippa, Igor Krivenko, Samuele Giuli et al. · SciPost Physics Codebases · 2025
We present a next-generation version of EDIpack, a flexible, high-performance numerical library using Lanczos-based exact diagonalization to solve generic quantum impurity problems, such as those introduced in Dynamical Mean-Field Theory to describe extended strongly correlated materials. This new release efficiently solves impurity problems allowing for different broken-symmetry solutions, including superconductivity, featuring local spin-orbit coupling and/or electron-phonon coupling. It provides quick access to dynamical correlation functions on the entire complex frequency plane at zero and low-temperatures. The modular architecture of the software not only provides Fortran APIs but also includes bindings to C/C++, interfaces with Python and Julia or with TRIQS and w2dynamics research platforms, thus ensuring unprecedented level of inter-operability. The outlook includes further extensions to study quantum materials and cold atoms quantum simulators, as well as quantum information applications.
Cited by 1Open access