POPxf: An Exchange Format for Polynomial Observable Predictions
Ilaria Brivio (ed.), Ken Mimasu (ed.), Peter Stangl (ed.), Anke Biek\"otter, Ana R. Cueto G\'omez, Charlotte Knight, Luca Mantani, Eleonora Rossi, Alejo N. Rossia, Aleks Smolkovi\v{c}

TL;DR
POPxf is a new standardized data format designed to facilitate the publication, exchange, and reinterpretation of polynomial-based theoretical predictions in high energy physics, especially for Effective Field Theory analyses.
Contribution
It introduces a structured, machine-readable format that encodes polynomial observables with explicit assumptions and flexible uncertainty treatment, enhancing reproducibility and collaboration.
Findings
Enables consistent sharing of polynomial predictions
Supports detailed uncertainty and correlation encoding
Improves reproducibility and reinterpretation of theoretical results
Abstract
We introduce the Polynomial Observable Prediction Exchange Format, POPxf, a structured, machine-readable data format for the publication and exchange of semi-analytical theoretical predictions in high energy physics. The format is designed to encode observables that can be expressed in terms of polynomials in model parameters, with particular emphasis on Effective Field Theory applications. All relevant assumptions and metadata are recorded explicitly, and the treatment of uncertainties and correlations is flexible enough to capture parameter-dependent effects. The format aims to improve reproducibility, facilitate global fits and reinterpretations, and streamline the use of theoretical predictions across the particle physics community.
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Taxonomy
TopicsParticle physics theoretical and experimental studies · High-Energy Particle Collisions Research · Computational Physics and Python Applications
