arXiv subjects

A. Acar

Publications and source records attributed to A. Acar.

4 recordsLinked to original sources

arXiv2026

A new methodology for direct detection of heavy dark matter at intense particle beam facilities

We propose new concepts for experiments in which intense high energy photon or muon beams are employed parasitically to detect scattering by cosmic heavy weakly interacting dark matter (DM) particles. We show that the scattering cross-sections are sizeable enough to potentially observe beam scattering on heavy dark matter particles at high beam intensities for typically inferred near-Earth DM densities of $\rho_\chi\sim0.3~GeV/cm^3$. The predicted effect is particularly large in the case of a proposed muon collider Higgs factory, especially in the heavy (and poorly constrained) DM scenarios of WIMPZilla's. Current photon facilities such as at Jefferson Laboratory are predicted to require intensity and energy upgrades to reach detectable rates.

hep-ph↗

arXiv2025

First Study of the Nuclear Response to Fast Hadrons via Angular Correlations between Pions and Slow Protons in Electron-Nucleus Scattering

We report on the first measurement of angular correlations between high-energy pions and slow protons in electron-nucleus ($eA$) scattering, providing a new probe of how a nucleus responds to a fast-moving quark. The experiment employed the CLAS detector with a 5-GeV electron beam incident on deuterium, carbon, iron, and lead targets. For heavier nuclei, the pion-proton correlation function is more spread-out in azimuth than for lighter ones, and this effect is more pronounced in the $\pi p$ channel than in earlier $\pi\pi$ studies. The proton-to-pion yield ratio likewise rises with nuclear mass, although the increase appears to saturate for the heaviest targets. These trends are qualitatively reproduced by state-of-the-art $eA$ event generators, including BeAGLE, eHIJING, and GiBUU, indicating that current descriptions of target fragmentation rest on sound theoretical footing. At the same time, the precision of our data exposes model-dependent discrepancies, delineating a clear path for future improvements in the treatment of cold-nuclear matter effects in $eA$ scattering.

nucl-ex↗

arXiv2025

Dark matter: red or blue?

We report the first calculation of light scattering on heavy dark matter (DM) particles. We show that despite the fact that DM has no direct coupling to photons, the light-DM($\gamma\chi$) ($m_\chi \sim 1$ TeV) cross-section is non-vanishing, albeit small. The cross section, calculated within the Standard Model (SM) framework, is particularly large in the case of heavy Weakly Interacting Massive Particles (WIMP). Combined with astrophysical observation, these results can constrain existing WIMP DM models in favor of lighter DM, $M_\chi<<M_{\mathrm{Planck}}$, (axions, composite DM, etc..) or non-weakly interacting pure gravitational DM. We also show that the energy dependence of light scattering on dark matter should make the DM colored - red in the case of weak-DM and blue for the gravitational-DM, when a white background light is passing through. Gravitational scattering of light on DM particles also leads to non-trivial polarization effects, which might be easier to detect than the deflection of light from the scattering on DM particles, $\gamma\chi\rightarrow\gamma\chi$.

hep-ph↗

arXiv2004

An agent framework for dynamic agent retraining: Agent academy

Agent Academy (AA) aims to develop a multi-agent society that can train new agents for specific or general tasks, while constantly retraining existing agents in a recursive mode. The system is based on collecting information both from the environment and the behaviors of the acting agents and their related successes/failures to generate a body of data, stored in the Agent Use Repository, which is mined by the Data Miner module, in order to generate useful knowledge about the application domain. Knowledge extracted by the Data Miner is used by the Agent Training Module as to train new agents or to enhance the behavior of agents already running. In this paper the Agent Academy framework is introduced, and its overall architecture and functionality are presented. Training issues as well as agent ontologies are discussed. Finally, a scenario, which aims to provide environmental alerts to both individuals and public authorities, is described an AA-based use case.

cs.MA↗