{"categories":[{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/4"}],"enrichment":{"capability":"Computes stransverse mass (MT2) for particle physics calculations, supporting both symmetric and asymmetric cases with vectorized numpy array operations.","skillfed_tags":["particle-physics","high-energy-physics","numpy-ufunc"],"use_cases":["Compute MT2 for individual particle collision events in high-energy physics data analysis.","Scan parameter grids of invisible particle masses using vectorized numpy arrays for efficiency.","Cross-check results against the legacy arXiv implementation using mt2_arxiv for validation.","Integrate MT2 calculations into Monte Carlo simulations for physics phenomenology studies.","Use as a numpy ufunc with advanced features like conditional computation via the where argument."],"what_it_does":"mt2 is a specialized physics library that computes the stransverse mass (MT2), a kinematic variable used in high-energy particle physics to infer properties of invisible particles in collision events. It wraps an optimized C++ implementation of the Lester-Nachman bisection algorithm, providing both a standard function and a raw numpy ufunc for flexibility.\n\nThe package is designed for high-throughput calculations in particle physics analyses. It supports vectorization over numpy arrays, allowing efficient batch computation across grids of parameters\u2014useful for Monte Carlo simulations and parameter scans. The implementation is scale-invariant and reportedly 3x to 4x faster than the original arXiv reference code, with a fallback to the legacy arxiv implementation available for independent verification.","worth_installing":"Yes, if you work in particle physics and need MT2 calculations. The package is actively maintained, has no known vulnerabilities, supports modern Python versions (3.9\u20133.14), and offers significant performance gains over reference implementations. Install friction is moderate due to C++ compilation, but precompiled wheels mitigate this for most platforms. MIT licensing poses no restrictions."},"id":"mt2","links":{"html":"https://skillfed.io/packages/mt2","md":"https://skillfed.io/packages/mt2.md","pypi":"https://pypi.org/project/mt2/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2025-10-09","license_spdx":"MIT","license_treatment":"permissive","name":"mt2","python_support":"supports_current","summary":"Stransverse mass computation as a numpy ufunc."},"popularity":{"monthly_downloads":430029,"position":6732,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.3.1"}