Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 134 tok/s
Gemini 2.5 Pro 46 tok/s Pro
GPT-5 Medium 23 tok/s Pro
GPT-5 High 32 tok/s Pro
GPT-4o 101 tok/s Pro
Kimi K2 179 tok/s Pro
GPT OSS 120B 435 tok/s Pro
Claude Sonnet 4.5 36 tok/s Pro
2000 character limit reached

Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification (2507.18824v1)

Published 24 Jul 2025 in hep-ph, nucl-th, stat.AP, and stat.ML

Abstract: Simulation Based Inference (SBI) is shown to yield more accurate resonance parameter estimates than traditional chi-squared minimization in certain cases of model misspecification, demonstrated through a case study of pi-pi scattering and the rho(770) resonance. Models fit to some data sets using chi-squared minimization can predict inaccurate pole positions for the rho(770), while SBI provides more robust predictions across the same models and data. This result is significant both as a proof of concept that SBI can handle model misspecification, and because accurate modeling of pi-pi scattering is essential in the study of many contemporary physical systems (e.g., a1(1260), omega(782)).

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com
Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

X Twitter Logo Streamline Icon: https://streamlinehq.com

Tweets

This paper has been mentioned in 1 tweet and received 49 likes.

Upgrade to Pro to view all of the tweets about this paper: