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PREFACE: A Search for Long-Lived Particles at the Large Hadron Collider

The Standard Model (SM) fails to explain many problems (neutrino masses, dark matter, and matter–antimatter asymmetry, among others) that may be resolved with new particles beyond the SM. No observation of such new particles may be explained either by their exceptionally high mass or by considerably small coupling to SM particles. The latter case implies relatively long lifetimes. Such long-lived particles (LLPs) then to have signatures different from those of SM particles. Searches in the “central region” are covered by the LHC general purpose experiments. The forward small angle region far from the interaction point (IP) is unexplored. Such particles are expected to have the energy as large as E = O(1 TeV) and Lorentz time dilation factor γ = E/m ≈ 10 2 –10 3 (with m the particle mass) hence long enough decay distances. A new class of specialized LHC detectors dedicated to LLP searches has been proposed for the forward regions. Among these experiments, FASER is already operational, and FACET is under consideration at a location 100 m from the LHC IP5 (the CMS detector intersection). However, some features of FACET require a specially enlarged beam pipe, which cannot be implemented for LHC Run 4. In this study, we explore a simplified version of the proposed detector PREFACE compatible with the standard LHC beam pipe in the HL-LHC Run 4. Realistic G EANT 4 simulations are performed and the background is evaluated. An initial analysis of the physics potential with the PREFACE geometry indicates that several significant channels could be accessible with sensitivities comparable to FACET and other LLP searches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

Exploring the holographic entropy cone via reinforcement learning

We develop a reinforcement learning algorithm to study the holographic entropy cone. Given a target entropy vector, our algorithm searches for a graph realization whose min-cut entropies match the target vector. If the target vector does not admit such a graph realization, it must lie outside the cone, in which case the algorithm finds a graph whose corresponding entropy vector most nearly approximates the target and allows us to probe the location of the facets. For the N = 3 cone, we confirm that our algorithm successfully rediscovers monogamy of mutual information beginning with a target vector outside the holographic entropy cone. We then apply the algorithm to the N = 6 cone, analyzing the 6 mystery extreme rays of the subadditivity cone from [1] that satisfy all known holographic entropy inequalities yet lacked graph realizations. We found realizations for 3 of them, proving they are genuine extreme rays of the holographic entropy cone, while providing evidence that the remaining 3 are not realizable, implying unknown holographic inequalities exist for N = 6.

AdS-CFT correspondence

Charge accumulation and solvation in $β$-NiOOH: Surface chemistry of an OER catalyst from ML-aided simulations

Electrochemical water splitting is a key technology for a sustainable energy transition, providing a route to store surplus electricity from renewable sources. A central bottleneck is the sluggish oxygen evolution reaction (OER), which drives the search for catalysts that are active, stable, and inexpensive enough for large-scale deployment. Within this context, pure and doped NiO x H y combine high activity with low cost, making them prime candidates for alkaline OER. Yet, despite extensive study, the atomistic structure of NiOOH under operando conditions and the associated reaction mechanisms remain debated. Here, we investigate the structural complexity of pure β-NiOOH, the scaffold for its doped derivatives. We systematically investigate the oxidation of the surface adsorbates via proton-coupled electron transfer steps across relevant facets and sites, identifying the most probable sequence of deprotonation events. Our results reveal asymmetric charge accumulation on Wulff-relevant surfaces and show how applied potential can promote morphological restructuring. Explicit solvation is included through machine-learning interatomic potential molecular dynamics of the NiOOH/water interface, which allows us to resolve the hydrophobic and hydrophilic character of different surfaces and the associated interfacial water structure. Together, these insights demonstrate how surface chemistry and solvation jointly govern the stability of NiOOH and the accumulation of surface charge, with possible implications for catalytic performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH