5257 papers
Hep-Ph explores the fundamental forces that govern how particles interact and behave at the smallest scales imaginable. This field bridges the gap between theoretical predictions and experimental reality, helping scientists understand the building blocks of our universe without getting lost in complex mathematics. Whether investigating the Higgs boson or searching for new physics beyond current models, these studies push the boundaries of human knowledge about matter and energy.
At Gist.Science, we process every new preprint in this category as soon as it appears on arXiv. We strip away the dense jargon to offer both accessible plain-language explanations and detailed technical summaries, ensuring that groundbreaking research is understandable to everyone from students to seasoned experts. Below are the latest papers in this dynamic field, ready for you to explore with clarity and depth.
This paper proposes utilizing large-volume neutrino telescopes as "Large Neutrino Colliders" to probe TeV-scale physics beyond the Standard Model by leveraging ultra-high-energy cosmic neutrinos that achieve center-of-mass energies exceeding the Large Hadron Collider's 14 TeV limit.
This paper proposes a testable two-component self-interacting dark matter framework where a dominant species resolves small-scale structure issues while a tiny ultra-strongly interacting subcomponent seeds early halo collapse for high-redshift quasars, all consistent with current astrophysical observations and Lyman- constraints.
This paper investigates the discovery potential of heavy neutral leptons at the proposed TRISTAN same-sign muon collider, demonstrating that its high-energy lepton-number-violating and lepton-flavor-violating signatures could significantly surpass current electroweak precision bounds on HNL mixing, particularly for masses in the 5–10 TeV range.
This paper presents a precise theoretical calculation of the total and differential cross sections for radiative inverse beta decay using heavy baryon chiral perturbation theory, providing sub-permille accuracy essential for interpreting data from current and future reactor antineutrino experiments like JUNO.
This paper presents a complete, high-precision calculation of radiative corrections to the inverse beta decay reaction using heavy-baryon chiral perturbation theory, incorporating quantum electrodynamics, chromodynamics, and electroweak contributions to provide updated cross-section predictions essential for reactor neutrino flux normalization, oscillation parameter determination, and new physics searches.
This paper establishes a systematic, all-orders perturbative map that explicitly reorganizes diagrammatic expansions of the Wavefunction of the Universe into Schwinger-Keldysh in-in correlators, thereby providing a concrete bridge between these two central frameworks for analyzing primordial cosmological observables.
This paper proposes a theoretical framework where a fundamental scale GeV, potentially arising from composite Higgs models, explains small neutrino masses and accidental baryon/lepton number symmetries while predicting a proton lifetime consistent with a potential Super-Kamiokande observation of decay, which Hyper-Kamiokande is expected to confirm.
Inspired by recent LHCb measurements, this paper utilizes the final-state rescattering framework to predict that the decays exhibit branching fractions around with direct CP asymmetries near 1%, whereas the channel shows negligible CP violation and branching ratios highly sensitive to the spin assignments of the states.
This study incorporates the Breit interaction into all-orders correlation potential calculations for Cs and Fr isoelectronic sequences, revealing that while these corrections significantly improve fine-structure intervals and highlight large effects in f-states, they do not fully resolve existing discrepancies between theoretical energy levels and experimental data.
This paper demonstrates how heteroscedastic and Bayesian normalizing flows can learn and propagate calibrated systematic and statistical uncertainties for generative neural networks in LHC physics, using both toy models with explicit likelihoods and classifier-reweighted approaches for top pair events.