Codebase release 0.3 for VSDM

Key findings from this study

This research indicates that:

• The VSDM software computes scattering rates for anisotropic materials in dark matter detection experiments through partial rate matrix calculations.
• Both Julia and Python implementations handle three-dimensional response functions that vary with material orientation.
• The computational framework separates contributions from velocity distributions, material properties, and particle characteristics into distinct matrix elements.

Overview

This codebase release describes version 0.3 of Vector Spaces for Dark Matter (VSDM), a software package implemented in Julia and Python for computing scattering rates in dark matter direct detection experiments using anisotropic target materials. The software addresses computational challenges associated with three-dimensional response functions in materials that exhibit directional sensitivity. The implementation calculates partial rate matrices across combinations of dark matter velocity distributions, material response functions, and particle properties. Anisotropic materials offer advantages in distinguishing potential dark matter signals from Standard Model backgrounds through their directional characteristics.

Methods and approach

The VSDM software handles scattering rate computations by constructing partial rate matrices for each combination of input parameters. The implementation accounts for rotating, three-dimensional response functions characteristic of anisotropic target materials. Both Julia and Python versions provide the computational infrastructure for these calculations. The approach separates the contributions from dark matter velocity distributions, material response functions, and particle dark matter properties into discrete matrix elements.

Results

The release provides functional Julia and Python implementations of the VSDM computational framework. The software successfully performs scattering rate calculations for anisotropic target materials in dark matter direct detection contexts. The partial rate matrix method enables systematic evaluation across parameter spaces defined by velocity distributions, material responses, and particle properties. The implementation addresses the computational complexity inherent in three-dimensional, orientation-dependent response functions.

Implications

The availability of VSDM in two widely-used scientific programming languages expands accessibility for researchers conducting dark matter direct detection analyses with anisotropic materials. The matrix-based computational approach may facilitate more comprehensive parameter space exploration than previous methods. The software infrastructure supports investigation of directional detection strategies that could improve discrimination between dark matter signals and backgrounds. This computational tool enables more detailed theoretical predictions for experiments employing anisotropic target materials, potentially informing detector design choices and data analysis frameworks for next-generation direct detection efforts.

Scope and limitations

This summary is based on the study abstract and available metadata. It does not include a full analysis of the complete paper, supplementary materials, or underlying datasets unless explicitly stated. Findings should be interpreted in the context of the original publication.