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 189 tok/s
Gemini 2.5 Pro 53 tok/s Pro
GPT-5 Medium 36 tok/s Pro
GPT-5 High 36 tok/s Pro
GPT-4o 75 tok/s Pro
Kimi K2 160 tok/s Pro
GPT OSS 120B 443 tok/s Pro
Claude Sonnet 4.5 37 tok/s Pro
2000 character limit reached

Searches for long-lived dark photons at proton accelerator experiments (2409.11096v3)

Published 17 Sep 2024 in hep-ph

Abstract: A systematic and unified analysis of the capability of lifetime frontier experiments to probe the parameter space of hypothetical long-lived particles is crucial for defining the targets of future searches. However, such a comprehensive study has not yet been conducted for dark photons - hypothetical massive particles that kinetically mix with Standard Model photons. Existing studies often rely on outdated assumptions about dark photon phenomenology, leading to inaccurate calculations of the parameter space, including regions already excluded or relevant for future experiments. In this paper, we present a comprehensive calculation of the parameter space for GeV-scale dark photons and light dark matter accessible to lifetime frontier experiments. Our analysis highlights how theoretical uncertainties in dark photon phenomenology can significantly impact experimental sensitivity across coupling and mass parameters. To facilitate further investigation, we provide these results in a publicly accessible form, incorporating updated dark photon phenomenology into the event generator \texttt{SensCalc}.

Citations (2)

Summary

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

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

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

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 1 like.

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