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The brightest cosmic gamma-ray burst (GRB) ever detected, GRB 221009A, was accompanied by photons of very high energies. These gamma rays may be used to test both the astrophysical models of the burst and our understanding of long-distance propagation of energetic photons, including potential new-physics effects. Here we present the observation of a photon-like air shower with the estimated primary energy of $300^{+43}_{-38}$ TeV, coincident (with the chance probability of $\sim 9\cdot 10^{-3}$) with the GRB in its arrival direction and time. Making use of the upgraded Carpet-3 muon detector and new machine learning analysis, we estimate the probability that the primary was hadronic as $\sim 3 \cdot 10^{-4}$. This is the highest-energy event ever associated with any GRB., Comment: 11 pages, 9 figures

This letter presents a spatial filter based on saturated absorption in gas as a replacement for the solid pinhole in a lens-pinhole-lens filtering system. We show that an ultraviolet laser pulse focused through ozone will have its spatial profile cleaned if its peak fluence rises above the ozone saturation fluence. Specifically, we demonstrate that a 5 ns 266 nm beam with 4.2 mJ of initial energy can be effectively cleaned by focusing through a 1.4% ozone-oxygen mixture, with about 76% of the main beam energy transmitted and 89% of the side lobe energy absorbed. This process can be adapted to other gases and laser wavelengths, providing alignment-insensitive and damage-resistant pinholes for high-repetition-rate high-energy lasers.

The Radio Neutrino Observatory in Greenland (RNO-G) is the first in-ice radio array in the northern hemisphere for the detection of ultra-high energy neutrinos via the coherent radio emission from neutrino-induced particle cascades within the ice. The array is currently in phased construction near Summit Station on the Greenland ice sheet, with 7~stations deployed during the first two boreal summer field seasons of 2021 and 2022. In this paper, we describe the installation and system design of these initial RNO-G stations, and discuss the performance of the array as of summer 2024.

The Radio Neutrino Observatory - Greenland (RNO-G) seeks discovery of ultra-high energy neutrinos from the cosmos through their interactions in ice. The science program extends beyond particle astrophysics to include radioglaciology and, as we show herein, solar observations, as well. Currently seven of 35 planned radio-receiver stations (24 antennas/station) are operational. These stations are sensitive to impulsive radio signals with frequencies between 80 and 700 MHz and feature a neutrino trigger threshold for recording data close to the thermal floor. RNO-G can also trigger on elevated signals from the Sun, resulting in nanosecond resolution time-domain flare data; such temporal resolution is significantly shorter than from most dedicated solar observatories. In addition to possible RNO-G solar flare polarization measurements, the Sun also represents an extremely useful above-surface calibration source. Using RNO-G data recorded during the summers of 2022 and 2023, we find signal excesses during solar flares reported by the solar-observing Callisto network and also in coincidence with $\sim$2/3 of the brightest excesses recorded by the SWAVES satellite. These observed flares are characterized by significant time-domain impulsivity. Using the known position of the Sun, the flare sample is used to calibrate the RNO-G absolute pointing on the radio signal arrival direction to sub-degree resolution. We thus establish the Sun as a regularly observed astronomical calibration source to provide the accurate absolute pointing required for neutrino astronomy.

Here we demonstrate nanometer thick iron garnet films suitable for the magneto-optical applica-tions. Bismuth-substituted iron garnet films of compositions Bi{_1}Y{_2}Fe{_5}O{_{12}} and Bi{_1}Tm{_2}Fe{_5}O{_{12}} deposited on gadolinium gallium garnet substrate are fabricated and characterized. Their thicknesses range from 2 to 10 nm, which corresponds to just a few crystal lattice constants. Faraday rotation of the nanofilms reaches 29.7 deg/{\mu}m at 420 nm which is comparable and even a bit better than single crystal micrometer thick films of similar composition. The film surface morphology by atomic force microscopy gives root mean square (RMS) roughness of the nanofilms as small as 0.13 nm that is also similar to the RMS of single crystal micrometer thick films. The Bi{_1}Tm{_2}Fe{_5}O{_{12}} films demonstrate effective uniaxial anisotropy. These all make the fabricated nanofilms very promising for their po-tential applications in magneto-optical devices and quantum technologies.

Raman spectroscopy together with density functional calculations were used to study lattice dynamics in a layered honeycomb cobaltite Na$_3$Co$_2$SbO$_6$, which can host a field-induced phase related with the Kitaev physics. We show that there develops an additional mode well above Neel temperature (at $\approx 200$K) at 525 cm$^{-1}$, which origin can be related to an electronic excitation to one of $j_{3/2}$ doublets. Moreover, our theoretical calculations demonstrate that the highest frequency intensive mode related to the oxygen vibrations is very sensitive to type of the magnetic order. Thus, we propose to use the softening of this mode as a hallmark of the transition to a fully polarized regime, which is stabilized in Kitaev materials in strong magnetic fields., Comment: To be published in JETP Letters

High-intensity lasers require suppression of prepulses and other non-ideal temporal structure to avoid target disruption before the arrival of the main pulse. To address this, we demonstrate that ionization gratings act as a controllable optical switch for high-power light with a temporal contrast improvement of at least $3\times10^5$ and a switching time less than 500 fs. We also show that a grating system can run for hours at 10 Hz without degradation. The contrast improvement from an ionization grating compares favorably to that achievable with plasma mirrors., Comment: 6 pages, 4 figures

Over the past few years, one of the most notable advancements in AI research has been in foundation models (FMs), headlined by the rise of language models (LMs). As the models' size increases, LMs demonstrate enhancements in measurable aspects and the development of new qualitative features. However, despite researchers' attention and the rapid growth in LM application, the capabilities, limitations, and associated risks still need to be better understood. To address these issues, we introduce an open Multimodal Evaluation of Russian-language Architectures (MERA), a new instruction benchmark for evaluating foundation models oriented towards the Russian language. The benchmark encompasses 21 evaluation tasks for generative models in 11 skill domains and is designed as a black-box test to ensure the exclusion of data leakage. The paper introduces a methodology to evaluate FMs and LMs in zero- and few-shot fixed instruction settings that can be extended to other modalities. We propose an evaluation methodology, an open-source code base for the MERA assessment, and a leaderboard with a submission system. We evaluate open LMs as baselines and find that they are still far behind the human level. We publicly release MERA to guide forthcoming research, anticipate groundbreaking model features, standardize the evaluation procedure, and address potential societal drawbacks., Comment: The paper version comparable with the release code v.1.1.0 of the benchmark MERA. ACL-2024 main track camera ready version

We demonstrate optical nonthermal excitation of exchange dominated spin waves of different orders in a magnetophotonic crystal. The magnetophotonic structure consists of a thin magnetic film and a Bragg stack of nonmagnetic layers to provide a proper nonuniform interference pattern of the inverse Faraday effect induced by light in the magnetic layer. We found a phenomenon of the pronounced phase slippage of the inverse Faraday effect distribution when the pump wavelength is within the photonic band gap of the structure. It allows to tune the interference pattern by a slight variation of light wavelength which results in the modification of excitation efficiency of the different order spin waves. The approach can be applied for different magnetic dielectrics expanding their application horizons for spin-wave based devices.

The constantly increasing dimensionality of artificial quantum systems demands for highly efficient methods for their characterization and benchmarking. Conventional quantum tomography fails for larger systems due to the exponential growth of the required number of measurements. The conceptual solution for this dimensionality curse relies on a simple idea - a complete description of a quantum state is excessive and can be discarded in favor of experimentally accessible information about the system. The probably approximately correct (PAC) learning theory has been recently successfully applied to a problem of building accurate predictors for the measurement outcomes using a dataset which scales only linearly with the number of qubits. Here we present a constructive and numerically efficient protocol which learns a tensor network model of an unknown quantum system. We discuss the limitations and the scalability of the proposed method., Comment: 10 pages, 11 figures