Computer Physics Communications

We introduce WimPyC, a Python code for the calculation of the capture rate of Weakly Interacting Massive Particles (WIMPs) by celestial bodies through nuclear scattering in the optically thin regime. WimPyC is an extension of the WimPyDD code, that calculates WIMP–nucleus scattering signals in direct detection (DD) experiments, and allows to combine DD and capture in celestial bodies in virtually any scenario within the framework of Galilean–invariant non–relativistic effective theory (NREFT), including inelastic scattering, an arbitrary WIMP spin and a generic WIMP velocity distribution in the Galactic halo. WimPyDD and WimPyC are suitable for both top–down approaches, where the interaction operators of a high–energy physics model are matched to those of the NREFT, and for bottom–up studies, where the Wilson coefficients of the NREFT are explored in a model–independent way and/or where the velocity distribution is written in terms of a superposition of streams taken as free parameters. As in the case of WimPyDD WimPyC exploits the factorization of the three main components that enter in the calculation of the capture rate: i) the Wilson coefficients that encode the dependence of the signals on the ultraviolet completion of the effective theory; ii) a response function that depends on the nuclear physics; iii) the halo function that depends on the WIMP velocity distribution. In WimPyC these three components are calculated and stored separately for later interpolation and combined together only as the last step of the signal evaluation procedure. This makes the phenomenological study of the capture rate with WimPyC transparent and improves computational speed.

PACme is a C++ computer code developed and optimized for the simulation, data analysis, and visualization of experimental (Time Differential) Perturbed Angular Correlations (PAC) observables resulting from both static and dynamic (time-dependent) magnetic and electric quadrupole hyperfine fields. The program is fully generalized to simultaneously handle fractions of probe atoms in different environments, each subject to static or multiple transient states. The code works for an arbitrary probe nuclear spin embedded in single-crystal or polycrystalline materials. A distinctive feature of PACme is the analytical treatment of static hyperfine field distributions, which are incorporated directly into the Hamiltonian formulation, even in the study of dynamic interactions. This approach is motivated by the fact that distributions of electric field gradients or magnetic fields around probe atoms-often caused by uncorrelated defects-are common and have a significant impact on the resulting PAC spectra. This article presents the implementation, structure, and usage of the PACme code as a general-purpose tool for the simulation and analysis of TDPAC spectra.

Pulgon-tools is an open-source software package providing building blocks for the analysis and modeling of quasi-one-dimensional (quasi-1D) periodic systems based on line-group theory. While mature libraries exist for space-group detection in three-dimensional crystals, an automated and structure-based identification of line groups has so far been lacking. We present software that integrates four complementary components within a consistent line-group framework: (i) structure generation, (ii) symmetry detection, (iii) irreducible representations (irreps) and character tables and (iv) harmonic interatomic force constants (IFCs) correction. This paper introduces the general code structure and several examples that illustrate some relevant applications of the program.

Evolutionary algorithms provide a powerful route to exploring the structural complexity of molecules and materials, enabling efficient exploration of the system's energy landscape to identify the minima related to stable and metastable configurations. Yet, existing frameworks often trade flexibility for chemical fidelity or scalability, leading to unphysical structures or overly restricted search spaces. The here presented framework {is designed to address several of these limitations} through a modular evolutionary architecture that preserves chemical consistency while enabling scalable exploration. combines an interchangeable evolutionary pipeline with chemically grounded molecular and crystalline encodings, {ensuring physically meaningful sampling across different atomistic problem classes}. A hierarchical Supercell Escalation (HiSE) protocol propagates low-energy motifs from minimal cells to larger supercells, improving sampling efficiency in extended systems. The execution model integrates synchronous parallelism for physical evaluations with an asynchronous multi-agent island strategy, while a hybrid SQL–HDF5 archive ensures efficient, reproducible, and fault-tolerant data management. Across benchmarks spanning peptide conformations, Lennard–Jones nanoclusters, binary-oxide convex-hull reconstruction, and CuO/Cu2O surface phase diagrams, {recovers the targeted low-energy basins and thermodynamic envelopes across the tested benchmarks}, resolves complex phase boundaries, and d{shows low orchestration overhead and efficient strong-scaling behavior for the tested benchmark configuration}. High-level YAML workflows enable autonomous discovery campaigns {with reduced manual intervention in the tested workflows, positioning as a flexible framework for scalable, chemically consistent atomistic exploration.}

GHWC is a GPU-accelerated gyrofluid code for simulating quasi-two-dimensional turbulence with consistent finite Larmor radius (FLR) effects in magnetized plasmas. The simulation setup allows for fundamental studies of FLR effects on isothermal resistive drift waves, turbulence, and zonal flows. It includes the standard Hasegawa-Wakatani model in the limit of cold ions. It is a GPU-accelerated update of GHW, rewritten in CUDA. This version has already been used in a recent publication on zonal-flow merging.

One major shortcoming of classical and mixed quantum-classical approaches devoted to large helium nanodroplets (HNDs) is the lack of superfluidity. A method, recently published in Chemical Physics Letters, is implemented in DynHeMat to enable the user to take into account helium superfluidity on a phenomenological manner by imposing projectiles colliding with HNDs to maintain their velocity at the critical Landau velocity when they move within the HND. Projectiles can thus enter deeply inside the droplet and, for instance, the stability of weakly-bound complexes in helium can be investigated. Moreover, the database provided with DynHeMat, called ZPAD_DB, contains a new file with the positions and velocities of He_70000 equilibrated at T = 0.37 K for 1.5 ns with the mPL He-He pseudopotential. Output files collecting the HND center-of-mass position and linear momentum as well as the HND total angular momentum are supplied for each trajectory and output files gathering energetic data are somewhat changed. Finally, a few error messages displayed at DynHeMat execution are slightly modified.

Efficient simulation of photon propagation in highly scattering, fluorescent multi-layer media remains challenging due to the need to simultaneously model scattering, absorption, and emission. Existing open-source codes, developed primarily for biomedical and sensing applications, cannot handle multi-layer configurations with multiple fluorescent and non-fluorescent (e.g., white filler) inclusions. There is a need for user-friendly open-source tools capable of modeling such complex structures, with applications in radiative cooling, energy harvesting, and solid-state lighting. Additionally, accommodating uncertainty in optical properties is a valuable feature currently lacking in existing codes. In this paper, we present an open-source code utilizing a Python-based, parallelized Monte Carlo algorithm that handles photon propagation in multi-layer media with fluorescent and non-fluorescent inclusions, simulating the following spectral radiative properties: reflectance, spectral fluorescence, absolute and normalized radiosity, total and different types of absorptances, and transmittance. This work serves as a built function on FOS, a previous open-source code developed by our group for non-fluorescent media. The Fluor-FOS open-source code enables efficient simulation of spectral radiative properties for fluorescent media in radiative cooling applications, LED packages, and energy harvesting systems. The proposed software has been validated against an open-source code and two experimental cases with different configurations and light sources, ensuring the fidelity of the proposed modified Monte Carlo algorithm.

In recent years, the concept of kirigami has been used in creating deployable structures for various scientific and technological applications. While high-fidelity Finite Element Analysis (FEA) is the standard for analyzing stress distributions and material deformation, it is computationally intensive and often ill-suited for the rapid exploration of vast kinematic configuration spaces. In this work, we develop PyKirigami, a lightweight, open-source Python framework for the efficient deployment simulation of kirigami structures. Unlike continuum mechanics solvers, PyKirigami models tessellations as articulated rigid-body networks, allowing for the real-time simulation of global deployment trajectories and volumetric transformations. The tool incorporates collision detection and interactive actuation, enabling users to validate folding paths and identify geometric locking states in both 2D and 3D topologies. This framework serves as a fast kinematic prototyping tool for kirigami structures, allowing researchers to verify deployment mechanics and self-contacts prior to performing detailed mechanical analysis or physical fabrication.

We present HYMOR (Hypersonic Modal/non-modal, and Receptivity), an open-source computational framework for the linear stability analysis of high-enthalpy hypersonic flows. The toolkit includes MATLAB and Julia implementations and is released under the MIT license. HYMOR provides global modal, non-modal, and receptivity analyses capable of capturing interactions among spatially separated physical mechanisms that are inaccessible to traditional local methods. A shock-fitting formulation is employed to treat the bow shock as a sharp discontinuity, ensuring that the interaction of infinitesimal disturbances with the shock recovers the response predicted by linear interaction analysis. The code also solves the nonlinear equations for base-flow computation and automatically linearizes the resulting discrete operators for the stability analyses. Several thermochemical models are available for the treatment of real-gas effects in high-enthalpy regimes. The numerical implementation is verified against a collection of benchmark cases that demonstrate the accuracy and capabilities of the toolkit across its modal, non-modal, and receptivity analysis modes.

In this paper, we present HyperPrecision, a Mathematica package for high-precision numerical evaluation of general Horn-type multivariate hypergeometric functions and their Laurent expansions in a small parameter ϵ. Such functions appear widely in physics and mathematics, with applications ranging from quantum field theory and string theory to number theory and statistics. Their high-precision numerical evaluation, however, remains challenging, since their defining series converge only in restricted domains and analytic continuation beyond these domains is, in general, non-trivial. HyperPrecision addresses this problem by automatically constructing the Pfaffian system of partial differential equations for a given hypergeometric function and restricting it to a one-dimensional contour in the space of variables connecting the starting point to the target point. The resulting ordinary differential equation is then solved by the Frobenius method, with the boundary conditions analytically determined by the defining series. We illustrate the use of the package by evaluating commonly occurring multivariate hypergeometric functions, including the Appell F1, F2, F3, and F4 functions, the Horn G- and H-series, and the Lauricella FA, FB, FC, and FD functions, as well as by considering applications to angular integrals, Feynman integrals, and cosmological and holographic correlators.