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Characterizing the energy resolution of the MicroBooNE LArTPC at the MeV scale using monoenergetic features of $^{208}$Tl decays
arXiv:2605.30709v1 Announce Type: new Abstract: A detailed understanding of the capabilities and fidelity of low-energy reconstruction is crucial for taking advantage of MeV-scale neutrino physics opportunities in liquid argon time projection chambers (LArTPCs). This study presents a measurement of the resolution of reconstructed energy in the MicroBooNE LArTPC at $\approx 1.5$ MeV. The characterization is performed using monoenergetic signals generated by $2.614$ MeV $\gamma$-rays from...
Thermal Decoherence and Population Transfer of MeV Channeling Electrons in Diamond
arXiv:2602.16529v2 Announce Type: replace-cross Abstract: Channeling radiation from MeV-regime electrons is governed by transitions between quantized transverse bound states, but experimental spectra are strongly modified by thermal diffuse scattering. To capture these open-system dynamics, a frozen-phonon multislice framework is combined with bound-state projection analysis to construct depth-dependent reduced density matrices in selected transverse manifolds. Beyond reproducing...
Performance of an LYSO-Based Active Converter for a Conversion Spectrometer aiming for 52.8 MeV photon detection in Future $\mu^+ \to e^+ \gamma$ Search Experiments
arXiv:2512.24209v3 Announce Type: replace Abstract: To facilitate future $\mu^+ \to e^+ \gamma$ search experiments with a branching-ratio sensitivity of $10^{-15}$, we are developing a conversion spectrometer that incorporates an active LYSO converter. The converter generates $e^+e^-$ pairs from incident photons while simultaneously measuring their energy deposition and timing, thereby enabling precise reconstruction of 52.8 MeV photons. The design goals include a time resolution of 30 ps...
Signals and Spoils: Speculative Oracle Extractable Value in the Era of Cross-Chain Interoperability
Announce Type: new Abstract: A new form of Maximal Extractable Value (MEV), termed speculative MEV, has emerged across Layer-2 blockchains. Unlike Ethereum mainnet, many Layer-2 systems lack a public mempool, forcing extraction strategies to become probabilistic: searchers emit multiple identical transactions hoping to capture an opportunity first. This generates substantial transaction spam, increasing fees and wasting block space.
Perspective on a challenge: predicting the photochemistry of cyclobutanone
Announce Type: replace Abstract: This Perspective is part of a Special Topic that explored the maturity of nonadiabatic molecular dynamics for predicting photochemical processes. In 2023, a prediction challenge was issued to the community of computational photochemists to simulate the photochemistry of cyclobutanone, photoexcited at 200 nm, and the resulting time-resolved MeV-UED signal.
A formal framework for the economic security of DeFi compositions
arXiv:2606.05418v1 Announce Type: new Abstract: Decentralized Finance (DeFi) services are usually constructed by composing a variety of smart contracts. While composability is a key driver of the success of DeFi, it also creates security risks: adversaries may exploit interactions between newly deployed contracts and the pre-existing ones to inflict economic losses. We introduce MEV non-interference, a formal security notion for DeFi composability requiring that the maximal extractable value...
Deep-learning-based low-energy trigger algorithms for the Hyper-Kamiokande experiment
arXiv:2605.31391v1 Announce Type: cross Abstract: Modern machine learning techniques have become increasingly important in particle physics because of their powerful pattern-recognition capabilities, including in real-time data acquisition where stringent runtime constraints apply. This paper details the performance of deep-learning-based trigger algorithms for a large water Cherenkov detector such as Hyper-Kamiokande aimed at low-energy neutrino events (below 7 MeV). The performance of...
Deep-learning-based low-energy trigger algorithms for the Hyper-Kamiokande experiment
arXiv:2605.31391v1 Announce Type: new Abstract: Modern machine learning techniques have become increasingly important in particle physics because of their powerful pattern-recognition capabilities, including in real-time data acquisition where stringent runtime constraints apply. This paper details the performance of deep-learning-based trigger algorithms for a large water Cherenkov detector such as Hyper-Kamiokande aimed at low-energy neutrino events (below 7 MeV). The performance of custom...
Attosecond Compression of Relativistic Electron Pulses via Continuous Harmonic Undulator Resonance
arXiv:2605.31083v1 Announce Type: new Abstract: Extending megaelectronvolt ultrafast electron diffraction (MeV UED) into the attosecond regime is essential for resolving intrinsic structural dynamics, yet requires simultaneously controlling electron-pulse duration and arrival-time stability. Here, we propose a generalized harmonic laser-electron interaction that extends beam modulation into a continuous harmonic regime. We demonstrate that highly detuned, non-integer harmonic modulation via...
Beam-Plasma Collective Oscillations in Intense Charged-Particle Beams: Dielectric Response Theory, Langmuir Wave Dispersion, and Unsupervised Detection via Prometheus
arXiv:2603.10457v4 Announce Type: replace-cross Abstract: We develop a theoretical and computational framework for beam-plasma collective oscillations in intense charged-particle beams at intermediate energies (10-100 MeV). In Part I, we formulate a kinetic field theory governed by the Vlasov-Poisson system, deriving the Lindhard dielectric function and random phase approximation (RPA) polarization tensor for three beam distribution functions. We prove via the dielectric function...