SPECTER: efficient evaluation of the spectral EMD

A bstract The Energy Mover’s Distance (EMD) has seen use in collider physics as a metric between events and as a geometric method of defining infrared and collinear safe observables. Recently, the Spectral Energy Mover’s Distance (SEMD) has been proposed as a more analytically tractable alternative to the EMD. In this work, we obtain a closed-form expression for the Riemannian-like p = 2 SEMD metric between events, eliminating the need to numerically solve an optimal transport problem. Additionally, we show how the SEMD can be used to define event and jet shape observables by minimizing the distance between events and parameterized energy flows (similar to the EMD), and we obtain closed-form expressions for several of these observables. We also present the Specter framework, an efficient and highly parallelized implementation of the SEMD metric and SEMD-derived shape observables as an analogue of the previously-introduced Shaper for EMD-based computations. We demonstrate that computing the SEMD with Specter can be up to a thousand times faster than computing the EMD with standard optimal transport libraries.

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Publication Details

Journal
Journal of High Energy Physics
Published
2024-12-30
DOI
https://doi.org/10.1007/jhep12(2024)219
Citations
3
Primary Topic
Particle physics theoretical and experimental studies
Type
article
Field-Weighted Citation Impact
1.98

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article

SPECTER: efficient evaluation of the spectral EMD

Rikab Gambhir, Andrew J. Larkoski, Jesse Thaler
3 citations
Journal of High Energy Physics
Particle physics theoretical and experimental studies
1.98
article

SPECTER: efficient evaluation of the spectral EMD

Rikab Gambhir, Andrew J. Larkoski, Jesse Thaler
article en
3 citations

Abstract

A bstract The Energy Mover’s Distance (EMD) has seen use in collider physics as a metric between events and as a geometric method of defining infrared and collinear safe observables. Recently, the Spectral Energy Mover’s Distance (SEMD) has been proposed as a more analytically tractable alternative to the EMD. In this work, we obtain a closed-form expression for the Riemannian-like p = 2 SEMD metric between events, eliminating the need to numerically solve an optimal transport problem. Additionally, we show how the SEMD can be used to define event and jet shape observables by minimizing the distance between events and parameterized energy flows (similar to the EMD), and we obtain closed-form expressions for several of these observables. We also present the Specter framework, an efficient and highly parallelized implementation of the SEMD metric and SEMD-derived shape observables as an analogue of the previously-introduced Shaper for EMD-based computations. We demonstrate that computing the SEMD with Specter can be up to a thousand times faster than computing the EMD with standard optimal transport libraries.

Journal of High Energy PhysicsVol. 2024(12)
University of California, Los Angeles (US), University of California System (US), Instituto de Física Teórica (ES), The NSF AI Institute for Artificial Intelligence and Fundamental Interactions (US), Massachusetts Institute of Technology (US)
National Science Foundation, U.S. Department of Energy, High Energy Physics
Affordable and clean energy
Openalex Percentile: Top 8%
Particle physics theoretical and experimental studies
1.98
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