IceCube data analysis yields a 3.1 sigma excess consistent with dark matter annihilation into neutrinos from the dwarf galaxy Bootes III at 26.5 TeV mass.
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Bauer, Nicholas L
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Future global 21-cm observations could beat CMB limits on TeV-scale decaying dark matter for lifetimes ≳10^15 s, especially for decays into neutrinos.
Gamma-ray upper limits from five high-energy observatories constrain the annihilation cross sections of composite dark matter in the mass range 10^5--10^12 GeV.
Calculations indicate AMEGO-X could detect PBH transits within 0.1 AU while HAWC and LHAASO could observe explosions out to 0.1-0.5 pc, with future events at ~1000 AU potentially producing measurable electromagnetic signals unlike the 2023 KM3NeT neutrino candidate.
The KM3NeT neutrino event may be a primordial neutrino from relic particle decay or annihilation near recombination, yielding a narrow spectral peak that evades broad power-law constraints from other telescopes.
PUEO will constrain the proton fraction of ultrahigh-energy cosmic rays under strong source evolution and set leading neutrino constraints on ultraheavy dark matter decays and some cosmic string models above 10^19 eV.
This work sets new upper limits on decay lifetimes and couplings for axion-like particles, dark photons, scalars, and B-L or L_i-L_j vector bosons using 511 keV line, X-ray continuum, and cosmic-ray flux observations.
Super-Kamiokande data constrains the DM-electron scattering cross-section for leptophilic dark matter to ~4e-41 cm2 below 100 GeV, exceeding direct detection by over an order of magnitude.
Assuming the KM3-230213A event comes from heavy dark matter decay, the preferred mass exceeds 100 PeV at 95% CL with lifetimes of 10^26-10^27 s, but these regions conflict with bounds from other neutrino telescopes and gamma-ray observations.
Absence of detectable pre-burst gamma-ray, cosmic-ray, and lower-energy neutrino signals strongly disfavors a primordial black hole origin for the KM3-230213A event under standard 4D Schwarzschild evaporation.
Jarvis-HEP introduces a YAML-based Python framework for composing workflows and performing parameter scans in high-energy physics.
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Jarvis-HEP: A lightweight Python framework for workflow composition and parameter scans in high-energy physics
Jarvis-HEP introduces a YAML-based Python framework for composing workflows and performing parameter scans in high-energy physics.