[Paper Review] Displaying dark matter constraints from colliders with varying simplified model parameters

A. Albert, A. Boveia+18 more|arXiv (Cornell University)|Mar 22, 2022

Particle physics theoretical and experimental studies4 citations

TL;DR

This paper presents analytical and semi-analytical methods to rescale dark matter collider limits across varying simplified model couplings without re-running Monte Carlo simulations, enabling efficient reinterpretation of ATLAS and CMS results for arbitrary coupling values. The key contribution is a computationally efficient framework—supported by a public Python package—that allows full limit visualization across coupling ranges, with application to Snowmass 2021 and future collider studies.

ABSTRACT

The search for dark matter is one of the main science drivers of the particle and astroparticle physics communities. Determining the nature of dark matter will require a broad approach, with a range of experiments pursuing different experimental hypotheses. Within this search program, collider experiments provide insights on dark matter which are complementary to direct/indirect detection experiments and to astrophysical evidence. To compare results from a wide variety of experiments, a common theoretical framework is required. The ATLAS and CMS experiments have adopted a set of simplified models which introduce two new particles, a dark matter particle and a mediator, and whose interaction strengths are set by the couplings of the mediator. So far, the presentation of LHC and future hadron collider results has focused on four benchmark scenarios with specific coupling values within these simplified models. In this work, we describe ways to extend those four benchmark scenarios to arbitrary couplings, and release the corresponding code for use in further studies. This will allow for more straightforward comparison of collider searches to accelerator experiments that are sensitive to smaller couplings, such as those for the US Community Study on the Future of Particle Physics (Snowmass 2021), and will give a more complete picture of the coupling dependence of dark matter collider searches when compared to direct and indirect detection searches. By using semi-analytical methods to rescale collider limits, we drastically reduce the computing resources needed relative to traditional approaches based on the generation of additional simulated signal samples.

Motivation & Objective

• Address the limitation of existing LHC dark matter benchmarks, which are restricted to only four fixed coupling scenarios, making cross-experiment and cross-collaboration comparisons difficult.
• Overcome the high computational cost of generating new Monte Carlo signal samples for each new coupling value in simplified dark matter models.
• Enable accurate reinterpretation of collider limits for arbitrary couplings—especially smaller ones relevant to future colliders and low-mass dark matter searches—using rescaling techniques.
• Provide a practical, community-ready toolset (including a Python package) to support the Snowmass 2021 process and future dark matter searches.
• Investigate the minimum coupling values required to satisfy dark matter relic density constraints across the four main simplified model types (scalar, pseudo-scalar, vector, axial-vector mediators).

Proposed method

• Use leading-order cross-section calculations for key final states in simplified dark matter models to derive analytical rescaling formulas between different coupling strengths.
• Apply semi-analytical rescaling to both resonant (e.g., dijet + missing transverse energy) and $E_T^{\text{miss}}+X$ final states, avoiding full event generation.
• Treat acceptances and $k$-factors as constant across rescaled scenarios, with caveats noted for accuracy limitations in cases where they vary significantly.
• Develop a Python package to automate the rescaling process, enabling users to generate full limit plots for any coupling value within the model framework.
• Validate the rescaling approach by comparing with existing LHC results and benchmarking against known limits, particularly for vector and axial-vector mediators.
• Compute minimum allowed couplings for relic density consistency by scanning over SM couplings and solving for the lowest coupling that avoids overproduction of dark matter.

Experimental results

Research questions

• RQ1 How can collider limits from ATLAS and CMS be efficiently reinterpretated across a wide range of coupling values in simplified dark matter models without re-running costly Monte Carlo simulations?
• RQ2 What are the analytical rescaling relations that allow accurate conversion of exclusion limits between different coupling strengths in vector and axial-vector mediator models?
• RQ3 What are the minimum coupling values required for each simplified model (scalar, pseudo-scalar, vector, axial-vector) to remain consistent with observed dark matter relic density?
• RQ4 How do the rescaling techniques perform across different final states, particularly in $E_T^{\text{miss}}+X$ and resonant search channels, and what are their limitations?
• RQ5 To what extent can the current framework be extended to include lepton colliders or scalar/pseudoscalar mediators in future versions?

Key findings

• The rescaling method enables accurate reinterpretation of collider limits across arbitrary coupling values with minimal computational cost, reducing reliance on expensive Monte Carlo simulations.
• The technique has been successfully applied to both resonant and $E_T^{\text{miss}}+X$ final states, with the $E_T^{\text{miss}}+X$ rescaling being a novel contribution not previously documented.
• For scalar and pseudo-scalar mediators, couplings of order $g_q \sim 1$ are required to satisfy the observed dark matter relic density, while vector and axial-vector mediators require $g_q \gtrsim 0.1$.
• In large regions of phase space—particularly for light dark matter and heavy mediators—no viable coupling exists that avoids dark matter overproduction, indicating strong theoretical constraints.
• The minimum coupling required to avoid overproduction is presented as a function of dark matter and mediator masses for all four simplified model types, providing a critical benchmark for experimental searches.
• A preliminary version of the open-source Python package for rescaling is already available on GitHub and has been shared with ATLAS and CMS collaborations for integration into future analyses.