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We compute the potential-graviton contribution to the scattering amplitude, the radial action, and the scattering angle of two extremal black holes in N = 8 supergravity at the fifth post-Minkowskian order to next-to-leading order in a large mass expansion (first self-force order). Properties of classical unitarity cuts allow us to focus on the integration-by-parts reduction of planar integrals, while nonplanar integrals at this order are obtained from the planar ones by straightforward manipulations. We present all master integrals and solve their associated differential equations necessary to evaluate the classical scattering amplitudes of massive scalar particles at this order in all gravitational theories, in particular in N = 8 supergravity, and in general relativity. Despite the appearance of higher-weight generalized polylogarithms and elliptic functions in the solution to the differential equation for master integrals, the final supergravity answer is remarkably simple and contains only (harmonic) polylogarithmic functions up to weight 2. The systematic analysis of elliptic integrals discussed here, as well as the particular organization of boundary integrals in N = 8 observables are independent of supersymmetry and may have wider applications, including to aspects of collider physics., Comment: 50 pages, 6 figures

We derive bounds for the Gaussian volume of the Minkowski sum \(\Omega + K_a\), where \(\Omega\) is any Borel set and \(K_a\) represents the vertices of a hypercube with edge length \(2a\). For \(a = c/\sqrt{\ln n}\), we show that if \(c < \pi/\sqrt{2}\), then the volume remains close to that of \(\Omega\). Conversely, if \(c > \pi\), we construct a domain \(\Omega\) for which the volume of the sum is significantly less than that of \(\Omega\). These results extend to generalized hypercubes, providing precise volume bounds based on the sparsity ratio of the vertices used in the translations. The findings have implications for adversarial hypothesis testing, particularly in scenarios where an adversary, after observing a Gaussian random vector, perturbs a subset of its components by a fixed magnitude., Comment: 7 pages

Broadband impedance-matched Josephson parametric amplifiers are key components for high-fidelity single-shot multi-qubit readout. Nowadays, several types of impedance matched parametric amplifiers have been proposed: the first is an impedance-matched parametric amplifier based on a Klopfenstein taper, and the second is an impedance-matched parametric amplifier based on auxiliary resonators. Here, we present the quantum-limited 3-wave-mixing lumped-element SNAIL parametric amplifier with two-units impedance matching transformer. A two-pole Chebyshev matching network with shunted resonators based on parallel-plate capacitors and superconducting planar coil. Operating in a flux-pumped mode, we experimentally demonstrate an average gain of $15dB$ across a $600MHz$ bandwidth, along with an average saturation power of $-107dBm$ and quantum-limited noise temperature., Comment: 7 pages, 3 figures

Assume $X$ is a variety for which the elliptic stable envelope exists. In this note we construct natural $q$-difference equations from the elliptic stable envelope of $X$. In examples, these equations coincide with the quantum difference equations, which give a natural $q$-deformation of the Dubrovin connection of $X$. Solutions of the quantum difference equations provide generating functions counting curves in $X$. In this way, our construction connects curve counting and equivariant elliptic cohomology. This is an overview paper based on the author's talk at the workshop The 16th MSJ-SI: Elliptic Integrable Systems, Representation Theory and Hypergeometric Functions, Tokyo 2023., Comment: 16 pages, 5 figures

We establish a version of the Landen's transformation for Weierstrass functions and invariants that is applicable to general lattices in complex plane. Using it we present an effective method for computing Weierstrass functions, their periods, and elliptic integral in Weierstrass form given Weierstrass invariants $g_2$ and $g_3$ of an elliptic curve. Similarly to the classical Landen's method our algorithm has quadratic rate of convergence.

The bounds on parameters of the eV and higher scale sterile neutrinos from the $0\nu \beta \beta$ decay have been refined and updated. We present a simple and compact analytic expression for the bound in the $\Delta m^2_{41} - \sin^2 2\theta_{14}$ plane, which includes all relevant parameters. Dependencies of the bound on unknown CP-phases and the type of mass spectrum of light neutrinos (mass ordering and level of degeneracy) are studied in detail. We have computed the bounds using the latest and most stringent data from KamLAND-Zen. The projected constraints from future experiments are estimated. The obtained bounds are confronted with positive indications of the presence of sterile neutrinos as well as with the other existing bounds. The $0\nu \beta \beta$ decay results exclude the regions of parameters implied by BEST and Neutrino-4, and the regions indicated by LSND and MiniBooNE are in conflict with $0\nu \beta \beta$ results combined with $\nu_\mu-$ disappearance bounds., Comment: 6 pages + references, 4 figures

We investigate the effects of dark matter annihilation on objects with masses close to the sub-stellar limit, finding that the minimum mass for stable hydrogen burning is larger than the $\sim0.075 M_\odot $ value predicted in the Standard Model. Below this limit, cooling brown dwarfs evolve into stable dark matter-powered objects that we name dark dwarfs. The timescale of this transition depends on the ambient dark matter density $\rho_{\rm DM}$ and circular velocity $v_{\rm DM}$ but is independent of the dark matter mass. We predict a population of dark dwarfs close to the galactic center, where the dark matter density is expected to be $\rho_{\rm DM}\gtrsim 10^{3}$ GeV/cm$^3$. At larger galactic radii the dark matter density is too low for these objects to have yet formed within the age of the universe. Dark dwarfs retain their initial lithium-7 in mass ranges where brown/red dwarfs would destroy it, providing a method for detecting them., Comment: DC+3JS. 5 pages, 5 figures, results can be reproduced using code provided at https://zenodo.org/records/13141908

We study the radio continuum emission of four galaxies experiencing ram-pressure stripping in four clusters of the Shapley supercluster at redshift z~0.05. Multi-band (235-1367 MHz) radio data, complemented by integral-field spectroscopy, allow us to detect and analyse in detail the non-thermal component both in the galaxy discs and the radio continuum tails. Three galaxies present radio continuum tails which are tens of kiloparsecs long. By deriving the radio spectral index in the inner and outer tails and comparing our findings with the distribution of the extraplanar ionised gas and the results of N-body/hydrodynamical simulations, we demonstrate that these tails are caused by the ram pressure which, together with the ionised gas, sweeps the magnetic field from the galaxy discs. We suggest that the radio continuum emission in these tails can be differently powered by (i) in situ star formation; (ii) relativistic electrons stripped from the disc; (iii) shock excitation or a combination of them. All the ram-pressure stripped galaxies are found in environments where cluster-cluster interactions occurred and/or are ongoing thus strongly supporting the thesis that cluster and group collisions and mergers may locally increase the ram pressure and trigger hydrodynamical interactions between the intracluster medium and the interstellar medium of galaxies., Comment: 18 pages, 14 figures, accepted for publication in MNRAS

The 21 cm transition from neutral Hydrogen promises to be the best observational probe of the Epoch of Reionisation (EoR). This has led to the construction of low-frequency radio interferometric arrays, such as the Hydrogen Epoch of Reionization Array (HERA), aimed at systematically mapping this emission for the first time. Precision calibration, however, is a requirement in 21 cm radio observations. Due to the spatial compactness of HERA, the array is prone to the effects of mutual coupling, which inevitably lead to non-smooth calibration errors that contaminate the data. When unsmooth gains are used in calibration, intrinsically spectrally-smooth foreground emission begins to contaminate the data in a way that can prohibit a clean detection of the cosmological EoR signal. In this paper, we show that the effects of mutual coupling on calibration quality can be reduced by applying custom time-domain filters to the data prior to calibration. We find that more robust calibration solutions are derived when filtering in this way, which reduces the observed foreground power leakage. Specifically, we find a reduction of foreground power leakage by 2 orders of magnitude at k=0.5.

The labor market is undergoing rapid changes, with increasing demands on job seekers and a surge in job openings. Identifying essential skills and competencies from job descriptions is challenging due to varying employer requirements and the omission of key skills. This study addresses these challenges by comparing traditional Named Entity Recognition (NER) methods based on encoders with Large Language Models (LLMs) for extracting skills from Russian job vacancies. Using a labeled dataset of 4,000 job vacancies for training and 1,472 for testing, the performance of both approaches is evaluated. Results indicate that traditional NER models, especially DeepPavlov RuBERT NER tuned, outperform LLMs across various metrics including accuracy, precision, recall, and inference time. The findings suggest that traditional NER models provide more effective and efficient solutions for skill extraction, enhancing job requirement clarity and aiding job seekers in aligning their qualifications with employer expectations. This research contributes to the field of natural language processing (NLP) and its application in the labor market, particularly in non-English contexts.

We propose selective debiasing -- an inference-time safety mechanism that aims to increase the overall quality of models in terms of prediction performance and fairness in the situation when re-training a model is prohibitive. The method is inspired by selective prediction, where some predictions that are considered low quality are discarded at inference time. In our approach, we identify the potentially biased model predictions and, instead of discarding them, we debias them using LEACE -- a post-processing debiasing method. To select problematic predictions, we propose a bias quantification approach based on KL divergence, which achieves better results than standard UQ methods. Experiments with text classification datasets demonstrate that selective debiasing helps to close the performance gap between post-processing methods and at-training and pre-processing debiasing techniques.

We propose an experimental study of adaptive time-stepping methods for efficient modeling of the aggregation-fragmentation kinetics. Precise modeling of this phenomena usually requires utilization of the large systems of nonlinear ordinary differential equations and intensive computations. We concentrate on performance of three explicit Runge-Kutta time-integration methods and provide simulations for two types of problems: finding of equilibrium solutions and simulations for kinetics with periodic solutions. The first class of problems may be analyzed through the relaxation of the solution to the stationary state after large time. In this case, the adaptive time-stepping may help to reach it using big steps reducing cost of the calculations without loss of accuracy. In the second case, the problem becomes numerically unstable at certain points of the phase space and may require tiny steps making the simulations very time-consuming. Adaptive criteria allows to increase the steps for most of points and speedup simulations significantly., Comment: 9 pages, 3 figures, 3 tables

Over the last decade, there has been increasing interest in autonomous driving systems. Reinforcement Learning (RL) shows great promise for training autonomous driving controllers, being able to directly optimize a combination of criteria such as efficiency comfort, and stability. However, RL- based controllers typically offer no safety guarantees, making their readiness for real deployment questionable. In this paper, we propose SECRM-2D (the Safe, Efficient and Comfortable RL- based driving Model with Lane-Changing), an RL autonomous driving controller (both longitudinal and lateral) that balances optimization of efficiency and comfort and follows a fixed route, while being subject to hard analytic safety constraints. The aforementioned safety constraints are derived from the criterion that the follower vehicle must have sufficient headway to be able to avoid a crash if the leader vehicle brakes suddenly. We evaluate SECRM-2D against several learning and non-learning baselines in simulated test scenarios, including freeway driving, exiting, merging, and emergency braking. Our results confirm that representative previously-published RL AV controllers may crash in both training and testing, even if they are optimizing a safety objective. By contrast, our controller SECRM-2D is successful in avoiding crashes during both training and testing, improves over the baselines in measures of efficiency and comfort, and is more faithful in following the prescribed route. In addition, we achieve a good theoretical understanding of the longitudinal steady-state of a collection of SECRM-2D vehicles.

Retrieval-augmented generation (RAG) techniques are widely used today to retrieve and present information in a conversational format. This paper presents a set of enhancements to traditional RAG techniques, focusing on large language models (LLMs) fine-tuned and hosted on AWS Trainium and Inferentia2 AI chips via SageMaker. These chips are characterized by their elasticity, affordability, and efficient performance for AI compute tasks. Besides enabling deployment on these chips, this work aims to improve tool usage, add citation capabilities, and mitigate the risks of hallucinations and unsafe responses due to context bias. We benchmark our RAG system's performance on the Natural Questions and HotPotQA datasets, achieving an accuracy of 62% and 59% respectively, exceeding other models such as DBRX and Mixtral Instruct.

The dual-phase liquid argon time projection chamber is presently one of the leading technologies to search for dark matter particles with masses below 10 GeV/c$^2$. This was demonstrated by the DarkSide-50 experiment with approximately 50 kg of low-radioactivity liquid argon as target material. The next generation experiment DarkSide-20k, currently under construction, will use 1,000 times more argon and is expected to start operation in 2027. Based on the DarkSide-50 experience, here we assess the DarkSide-20k sensitivity to models predicting light dark matter particles, including Weakly Interacting Massive Particles (WIMPs) and sub-GeV/c$^2$ particles interacting with electrons in argon atoms. With one year of data, a sensitivity improvement to dark matter interaction cross-sections by at least one order of magnitude with respect to DarkSide-50 is expected for all these models. A sensitivity to WIMP--nucleon interaction cross-sections below $1\times10^{-42}$ cm$^2$ is achievable for WIMP masses above 800 MeV/c$^2$. With 10 years exposure, the neutrino fog can be reached for WIMP masses around 5 GeV/c$^2$., Comment: submitted to Nature Communications

This study explores the application of genetic algorithms in generating highly nonlinear substitution boxes (S-boxes) for symmetric key cryptography. We present a novel implementation that combines a genetic algorithm with the Walsh-Hadamard Spectrum (WHS) cost function to produce 8x8 S-boxes with a nonlinearity of 104. Our approach achieves performance parity with the best-known methods, requiring an average of 49,399 iterations with a 100% success rate. The study demonstrates significant improvements over earlier genetic algorithm implementations in this field, reducing iteration counts by orders of magnitude. By achieving equivalent performance through a different algorithmic approach, our work expands the toolkit available to cryptographers and highlights the potential of genetic methods in cryptographic primitive generation. The adaptability and parallelization potential of genetic algorithms suggest promising avenues for future research in S-box generation, potentially leading to more robust, efficient, and innovative cryptographic systems. Our findings contribute to the ongoing evolution of symmetric key cryptography, offering new perspectives on optimizing critical components of secure communication systems.

An ultra-light axion with CP violating interactions with a dark sector and CP preserving interactions with the visible sector can act as a novel portal between dark matter and the Standard Model. In such theories, dark matter sources an axion field extending over the entire galaxy, the gradient of which can be searched for with precise spin precession experiments. A reinterpretation of existing co-magnetometer data already constrains theories that are consistent with astrophysical bounds, and near-future experiments will begin probing well-motivated models. The required interactions can arise from a confining hidden sector without necessitating fine-tuning of the axion's mass., Comment: 6 pages, 1 figure; comments welcome!

Due to interactions with dark matter, neutrinos can acquire refractive masses which explain the data from oscillation experiments. We study the effects of relic neutrinos with refractive masses on structure formation in the Universe. In the model with a light fermionic mediator, above the resonance energy, $E_R$, associated with the mass of the mediator, refractive masses have all the properties identical to the usual vacuum masses. Below the resonance, refractive masses decrease with neutrino energy, however, they cannot be used in the same way as usual masses. We study the dispersion relations and group velocities of such neutrinos and their dependence on redshift. We show that in the epoch of structure formation, relic neutrinos were ultrarelativistic and essentially massless particles for $E_R = (10 - 10^5)\,$eV. This allows to reconcile the values of masses extracted from oscillation experiments with the stringent bounds on sum of neutrino masses from cosmological surveys., Comment: 6 pages, 3 figures

Identity is one of the most commonly studied constructs in social science. However, despite extensive theoretical work on identity, there remains a need for additional empirical data to validate and refine existing theories. This paper introduces a novel approach to studying identity by enhancing word embeddings with socio-demographic information. As a proof of concept, we demonstrate that our approach successfully reproduces and extends established findings regarding gendered self-views. Our methodology can be applied in a wide variety of settings, allowing researchers to tap into a vast pool of naturally occurring data, such as social media posts. Unlike similar methods already introduced in computer science, our approach allows for the study of differences between social groups. This could be particularly appealing to social scientists and may encourage the faster adoption of computational methods in the field.

We aim to constrain the gas density and temperature distributions as well as gas masses in several T Tauri protoplanetary disks located in Taurus. We use the 12CO, 13CO, and C18O (2-1) isotopologue emission observed at 0.9 with the IRAM NOrthern Extended Millimeter Array (NOEMA) as part of the MPG-IRAM Observatory Program PRODIGE (PROtostars and DIsks: Global Evolution PIs: P. Caselli & Th. Henning). Our sample consists of Class II disks with no evidence of strong radial substructures. We use thesedata to constrain the thermal and chemical structure of these disks through theoretical models for gas emission. To fit the combined optically thick and thin CO line data in Fourier space, we developed the DiskCheF code, which includes the parameterized disk physical structure, machine-learning (ML) accelerated chemistry, and the RADMC-3D line radiative transfer module. A key novelty of DiskCheF is the fast and feasible ML-based chemistry trained on the extended grid of the disk physical-chemical models precomputed with the ANDES2 code. This ML approach allows complex chemical kinetics models to be included in a time-consuming disk fitting without the need to run a chemical code. We present a novel approach to incorporate chemistry into disk modeling without the need to explicitly calculate a chemical network every time. Using this new disk modeling tool, we successfully fit the 12CO, 13CO, and C18O (2-1) data from the CI, CY, DL, DM, DN, and IQ Tau disks. The combination of optically thin and optically thick CO lines allows us to simultaneously constrain the disk temperature and mass distribution, and derive the CO-based gas masses. These values are in reasonable agreement with the disk dust masses rescaled by a factor of 100 as well as with other indirect gas measurements., Comment: 25 pages, 19 figures

We analyzed the regularity/chaoticity of the orbits of 45 globular clusters in the central region of the Galaxy with a radius of 3.5 kpc, which are subject to the greatest influence from an elongated rotating bar. Various analysis methods were used, namely, methods for calculating the Highest Lyapunov Exponents, the method of Poincar$\acute{e}$ sections, the frequency method based on the calculation of fundamental frequencies, as well as the visual assessment method. Bimodality was discovered in the histogram of the distribution of positive Lyapunov exponents, calculated in the classical version, without renormalization of the shadow orbit, which makes it possible to implement a probabilistic method of GC classification. To construct the orbits of globular clusters, we used a gravitational potential model with a bar in the form of a triaxial ellipsoid, described in detail in the work of Bajkova et al., Izvestiya Glavnoi astronomicheskoi observatorii v Pulkove, {\bf 228}, 1 (2023). The following bar parameters were adopted: mass $10^{10} M_\odot $, semimajor axis length 5 kpc, bar viewing angle 25$^o$, rotation velocity 40 km s$^{-1}$ kpc$^{-1}$. To form the 6D-phase space required for orbit integration, the most accurate astrometric data to date from the Gaia satellite (EDR3) (Vasiliev, Baumgardt, 2021), as well as new refined average distances to globular clusters (Baumgardt, Vasiliev, 2021) were used. A classification is made of globular clusters with regular and chaotic dynamics. As the analysis showed, globular clusters with small pericentric distances and large eccentricities are most susceptible to the influence of the bar and demonstrate the greatest chaos. It is shown that the results of classifying globular clusters by the nature of their orbital dynamics, obtained using the various methods of analysis considered in the work, correlate well with each other., Comment: 26 pages, 10 figures, 3 tables

A short review of expansion by regions is presented. It is a well-known strategy to obtain an expansion of a given multiloop Feynman integral in a given limit where some kinematic invariants and/or masses have certain scaling measured in powers of a given small parameter. Prescriptions of this strategy are formulated in a simple geometrical language and are illustrated through simple examples., Comment: 13 pages, 3 figures, published in "Anti-Differentiation and the Calculation of Feynman Amplitudes", ed. J. Bl\"umlein and C. Schneider, Springer 2021, doi:10.1007/978-3-030-80219-6. arXiv admin note: text overlap with arXiv:1809.04325

Here we present the results of benchmarking of a quantum processor based on trapped $^{171}$Yb$^{+}$ ions by performing basic quantum machine learning algorithms. Specifically, we carry out a supervised binary classification of small-scale digits images, which are intentionally chosen so that they can be classified with 100% accuracy, using a quantum-enhanced Support Vector Machine algorithm with up to four qubits. In our work, we specifically consider different types of quantum encodings of the dataset and different levels of transpilation optimizations for the corresponding quantum circuits. For each quantum encoding, we obtain a classifier that is of 100% accuracy on both training and test sets, which demonstrates that the quantum processor can correctly solve the basic classification task considered. As we expect, with the increase of the capabilities quantum processors, they can become a useful tool for machine learning., Comment: 8 pages, 1 figure

Context: Interferometric imaging is algorithmically and computationally challenging as there is no unique inversion from the measurement data back to the sky maps, and the datasets can be very large. Many imaging methods already exist, but most of them focus either on the accuracy or the computational aspect. Aims: This paper aims to reduce the computational complexity of the Bayesian imaging algorithm resolve, enabling the application of Bayesian imaging for larger datasets. Methods: By combining computational shortcuts of the CLEAN algorithm with the Bayesian imaging algorithm resolve we developed an accurate and fast imaging algorithm which we name fast-resolve. Results: We validate the accuracy of the presented fast-resolve algorithm by comparing it with results from resolve on VLA Cygnus A data. Furthermore, we demonstrate the computational advantages of fast-resolve on a large MeerKAT ESO 137-006 dataset which is computationally out of reach for resolve. Conclusions: The presented algorithm is significantly faster than previous Bayesian imaging algorithms, broadening the applicability of Bayesian interferometric imaging. Specifically for the single channel VLA Cygnus A datasets fast-resolve is about $144$ times faster than resolve. For the MeerKAT dataset with multiple channels the computational speedup of fast-resolve is even larger., Comment: 24 pages, 14 figures

The concept of nuclear spin temperature has been a cornerstone of the theory of dynamic nuclear spin polarization by electrons in various semiconductor structures for decades. Still, it is not always applicable to strongly localized electrons due to their long spin correlation times. This motivated the use of the oversimplified central spin model for the description of the nuclear spin dynamics in quantum dots. Here, we present a microscopic theory that bridges the gap between these two approaches by describing the nuclear spin thermodynamics for systems with long electron spin correlation times. Importantly, our theory predicts that efficient nuclear spin cooling by strongly localized electrons requires an external magnetic field by far exceeding the local field of nuclear spin-spin interaction, and that the time of the nuclear spin heating by unpolarized electrons may change by several orders of magnitude depending on the magnetic field., Comment: 5+5 pages, 3+1 figures

Quantitative estimates of the contributions of the anthropogenic forcing, characterized by changes in the radiative forcing of atmospheric greenhouse gases (CO2, in particular), and solar activity variations to the trends of the global surface temperature on secular temporal horizons are obtained with the aid of autoregressive models from simulations with climate models of the CMIP6 ensemble and from long-term observational data since the 19th century. The results for the simulations with climate models characterized by low, medium and high temperature sensitivity to changes in the CO2 content are compared. It is found, in particular, that the estimates from observation data revealing the determinative contribution of the CO2 content to the global surface temperature trends on half-century and century-long time intervals are most consistent with the estimates from simulations with the climate model with the lowest sensitivity of the global surface temperature to doubling the CO2 atmospheric content., Comment: 11 pages, 2 figures, 4 tables

In this paper, we introduce the Behavior Structformer, a method for modeling user behavior using structured tokenization within a Transformer-based architecture. By converting tracking events into dense tokens, this approach enhances model training efficiency and effectiveness. We demonstrate its superior performance through ablation studies and benchmarking against traditional tabular and semi-structured baselines. The results indicate that structured tokenization with sequential processing significantly improves behavior modeling.

We propose new vertex operators, both the type I and the type II dual, of the elliptic quantum toroidal algebra U_{t_1,t_2,p}(gl_{1,tor}) by combining representations of U_{t_1,t_2,p}(gl_{1,tor}) and the notions of the elliptic stable envelopes for the instanton moduli space M(n,r). The vertex operators reproduce the shuffle product formula of the elliptic stable envelopes by their composition. We also show that the vacuum expectation value of a composition of the vertex operators gives a correct formula of the K-theoretic vertex function for M(n,r). We then derive exchange relations among the vertex operators and construct a L-operator satisfying the RLL=LLR^* relation with R and R^* being elliptic dynamical instanton R-matrices defined as transition matrices of the elliptic stable envelopes. Assuming a universal form of L, we define a comultiplication \Delta in terms of it. It turns out that the new vertex operators are intertwining operators of the U_{t_1,t_2,p}(gl_{1,tor})-modules w.r.t \Delta., Comment: 42 pages

We obtain explicit formulas for capped descendent vertex functions of $\text{Hilb}^n(\mathbb{C}^2)$ for descendents given by chern classes of tautological bundles. The expression is the result of twisting a well known generating function for normalized Macdonald polynomials. This gives an explicit description of the rational function the capped vertex is an expansion of. Along the way we prove various limit expressions of the capping operator and the bare vertex function.

We explore the bound neutrons decay into invisible particles (e.g., $n\rightarrow 3 \nu$ or $nn \rightarrow 2 \nu$) in the JUNO liquid scintillator detector. The invisible decay includes two decay modes: $ n \rightarrow { inv} $ and $ nn \rightarrow { inv} $. The invisible decays of $s$-shell neutrons in $^{12}{\rm C}$ will leave a highly excited residual nucleus. Subsequently, some de-excitation modes of the excited residual nuclei can produce a time- and space-correlated triple coincidence signal in the JUNO detector. Based on a full Monte Carlo simulation informed with the latest available data, we estimate all backgrounds, including inverse beta decay events of the reactor antineutrino $\bar{\nu}_e$, natural radioactivity, cosmogenic isotopes and neutral current interactions of atmospheric neutrinos. Pulse shape discrimination and multivariate analysis techniques are employed to further suppress backgrounds. With two years of exposure, JUNO is expected to give an order of magnitude improvement compared to the current best limits. After 10 years of data taking, the JUNO expected sensitivities at a 90% confidence level are $\tau/B( n \rightarrow { inv} ) > 5.0 \times 10^{31} \, {\rm yr}$ and $\tau/B( nn \rightarrow { inv} ) > 1.4 \times 10^{32} \, {\rm yr}$., Comment: 28 pages, 7 figures, 4 tables

The Spin Physics Detector collaboration proposes to install a universal detector in the second interaction point of the NICA collider under construction (JINR, Dubna) to study the spin structure of the proton and deuteron and other spin-related phenomena using a unique possibility to operate with polarized proton and deuteron beams at a collision energy up to 27 GeV and a luminosity up to $10^{32}$ cm$^{-2}$ s$^{-1}$. As the main goal, the experiment aims to provide access to the gluon TMD PDFs in the proton and deuteron, as well as the gluon transversity distribution and tensor PDFs in the deuteron, via the measurement of specific single and double spin asymmetries using different complementary probes such as charmonia, open charm, and prompt photon production processes. Other polarized and unpolarized physics is possible, especially at the first stage of NICA operation with reduced luminosity and collision energy of the proton and ion beams. This document is dedicated exclusively to technical issues of the SPD setup construction.

In this note we consider a class of $q$-hypergeometric equations describing the quantum difference equation for the cotangent bundle over projective space $X=T^{*}\mathbb{P}^n$ . We show that over $\mathbb{Q}_p$ these equations are equipped with the Frobenius action $z\to z^p$. We obtain an explicit formula for the constant term of the Frobenius intertwiner in therms of $p$-adic $q$-gamma function of Koblitz. In the limit $q\to 1$ our formula degenerates to the Frobenius intertwiners for the hypergeometric differential equations discovered by B.Dwork., Comment: 17 pages, 1 picture

In this technical report, we present three novel datasets of Kotlin code: KStack, KStack-clean, and KExercises. We also describe the results of fine-tuning CodeLlama and DeepSeek models on this data. Additionally, we present a version of the HumanEval benchmark rewritten by human experts into Kotlin - both the solutions and the tests. Our results demonstrate that small, high-quality datasets (KStack-clean and KExercises) can significantly improve model performance on code generation tasks, achieving up to a 16-point increase in pass rate on the HumanEval benchmark. Lastly, we discuss potential future work in the field of improving language modeling for Kotlin, including the use of static analysis tools in the learning process and the introduction of more intricate and realistic benchmarks.

The optical orientation and alignment of excitons in semiconductor indirect gap quantum dots have been studied theoretically. A special regime is analyzed in which the energy of the hyperfine interaction of an electron with lattice nuclei is small compared to the exchange splitting between bright and dark excitonic levels, but is comparable to the anisotropic exchange splitting of the radiative doublet. The dependencies of degrees of circular and linear polarization on the external magnetic field under resonant excitation of excitons by polarized light are calculated., Comment: 11 pages, 1 figure. This is a translation of the original manuscript in Russian in memory of V. M. Agranovich, which is available in the supplementary files at arXiv and at https://www.dropbox.com/scl/fi/kyyyaaimh2bjtf1dycv11/Agranovich_memorium.pdf?rlkey=ix0t7gi0ytxu5et4yhw134ke8&st=yp7n4f3o&dl=1

In this paper the vacuum energy density and generation of topological mass are investigated for a system of a real and complex scalar fields interacting with each other. In addition to that, it is also included the quartic self-interaction for each one of the fields. The condition imposed on the real field is the periodic condition, while the complex field obey a quasi-periodic condition. The system is placed in a scenario where the CPT-even aether-type Lorentz symmetry violation takes place. We allow that the Lorentz violation affects the fields with different intensities. The vacuum energy density, its loop correction, and the topological mass are evaluated analytically. It is also discussed the possibility of different vacuum states and their corresponding stability requirements, which depends on the conditions imposed on the fields, the interaction coupling constants and also the Lorentz violation parameters. The formalism used here to perform this investigation is the effective potential one, which is written as a loop expansion via path integral in quantum field theory., Comment: 18 pages, 6 figures. arXiv admin note: text overlap with arXiv:2302.14540

We study the small-mass asymptotic behavior of so-called angular integrals, appearing in phase-space calculations in perturbative quantum field theory. For this purpose we utilize the strategy of expansion by regions, which is a universal method both for multiloop Feynman integrals and various parametric integrals. To apply the technique to angular integrals, we convert them into suitable parametric integral representations, which are accessible to existing automation tools. We use the the code \texttt{asy.m} to reveal regions contributing to the asymptotic expansion of angular integrals. To evaluate the contributions of these regions in an epsilon expansion we apply the method of Mellin-Barnes representation. Our approach is checked against existing results on angular integrals revealing a connection between contributing regions and angular integrals constructed from an algebraic decomposition. We explicitly calculate the previously unknown asymptotics for angular integrals with three and four denominators and formulate a conjecture for the leading asymptotics and the pole part for a general number of denominators and masses., Comment: 23 pages, no figures

As shown by A. Melnikov, the orbits of a Borel subgroup acting by conjugation on upper-triangular matrices with square zero are indexed by involutions in the symmetric group. The inclusion relation among the orbit closures defines a partial order on involutions. We observe that the same order on involutive permutations also arises while describing the inclusion order on B-orbit closures in the direct product of two Grassmannians. We establish a geometric relation between these two settings., Comment: 8 pages, 4 figures

Dark Matter (DM) can become captured, deposit annihilation energy, and hence increase the heat flow in exoplanets and brown dwarfs. Detecting such a DM-induced heating in a population of exoplanets in the inner kpc of the Milky Way thus provides potential sensitivity to the galactic DM halo parameters. We develop a Bayesian Hierarchical Model to investigate the feasibility of DM discovery with exoplanets and examine future prospects to recover the spatial distribution of DM in the Milky Way. We reconstruct from mock exoplanet datasets observable parameters such as exoplanet age, temperature, mass, and location, together with DM halo parameters, for representative choices of measurement uncertainty and the number of exoplanets detected. We find that detection of $\mathcal{O}(100)$ exoplanets in the inner Galaxy can yield quantitative information on the galactic DM density profile, under the assumption of 10% measurement uncertainty. Even as few as $\mathcal{O}(10)$ exoplanets can deliver meaningful sensitivities if the DM density and inner slope are sufficiently large., Comment: Comments are welcome. 14 pages, 11 figures, 2 tables

This paper studies strategic communication in the context of social learning. Product reviews are used by consumers to learn product quality, but in order to write a review, a consumer must be convinced to purchase the item first. When reviewers care about welfare of future consumers, this leads to a conflict: a reviewer today wants the future consumers to purchase the item even when this comes at a loss to them, so that more information is revealed for the consumers that come after. We show that due to this conflict, communication via reviews is inevitably noisy, regardless of whether reviewers can commit to a communication strategy or have to resort to cheap talk. The optimal communication mechanism involves truthful communication of extreme experiences and pools the moderate experiences together.

Experiments aimed at direct searches for WIMP dark matter require highly effective reduction of backgrounds and control of any residual radioactive contamination. In particular, neutrons interacting with atomic nuclei represent an important class of backgrounds due to the expected similarity of a WIMP-nucleon interaction, so that such experiments often feature a dedicated neutron detector surrounding the active target volume. In the context of the development of DarkSide-20k detector at INFN Gran Sasso National Laboratory (LNGS), several R&D projects were conceived and developed for the creation of a new hybrid material rich in both hydrogen and gadolinium nuclei to be employed as an essential element of the neutron detector. Thanks to its very high cross-section for neutron capture, gadolinium is one of the most widely used elements in neutron detectors, while the hydrogen-rich material is instrumental in efficiently moderating the neutrons. In this paper results from one of the R&Ds are presented. In this effort the new hybrid material was obtained as a poly(methyl methacrylate) (PMMA) matrix, loaded with gadolinium oxide in the form of nanoparticles. We describe its realization, including all phases of design, purification, construction, characterization, and determination of mechanical properties of the new material.

The origin of neutrino masses remains unknown. Both the vacuum mass and the dark mass generated by the neutrino interactions with DM particles or fields can fit the current oscillation data. The dark mass squared is proportional to the DM number density and therefore varies on the galactic scale with much larger values around the Galactic Center. This affects the group velocity and the arrival time delay of core-collapse supernovae neutrinos. This time delay, especially for the $\nu_e$ neutronization peak with a sharp time structure, can be used to distinguish the vacuum and dark neutrino masses. For illustration, we explore the potential of DUNE which is sensitive to $\nu_e$. Our simulations show that DUNE can distinguish the two neutrino mass origins at more than $5\sigma\,$C.L., depending on the observed local value of neutrino mass, the neutrino mass ordering, the DM density profile, and the SN location., Comment: 6 pages, 4 figures

This conceptual analysis examines the dynamics of data transmission in 5G networks. It addresses various aspects of sending data from cameras and LiDARs installed on a remote-controlled ferry to a land-based control center. The range of topics includes all stages of video and LiDAR data processing from acquisition and encoding to final decoding, all aspects of their transmission and reception via the WebRTC protocol, and all possible types of network problems such as handovers or congestion that could affect the quality of experience for end-users. A series of experiments were conducted to evaluate the key aspects of the data transmission. These include simulation-based reproducible runs and real-world experiments conducted using open-source solutions we developed: "Gymir5G" - an OMNeT++-based 5G simulation and "GstWebRTCApp" - a GStreamer-based application for adaptive control of media streams over the WebRTC protocol. One of the goals of this study is to formulate the bandwidth and latency requirements for reliable real-time communication and to estimate their approximate values. This goal was achieved through simulation-based experiments involving docking maneuvers in the Bay of Kiel, Germany. The final latency for the entire data processing pipeline was also estimated during the real tests. In addition, a series of simulation-based experiments showed the impact of key WebRTC features and demonstrated the effectiveness of the WebRTC protocol, while the conducted video codec comparison showed that the hardware-accelerated H.264 codec is the best. Finally, the research addresses the topic of adaptive communication, where the traditional congestion avoidance and deep reinforcement learning approaches were analyzed. The comparison in a sandbox scenario shows that the AI-based solution outperforms the WebRTC baseline GCC algorithm in terms of data rates, latency, and packet loss.

A spin-photon interface based on the luminescence of a singly charged quantum dot in a micropillar cavity allows for the creation of photonic entangled states. Current devices suffer from cavity birefringence, which limits the generation of spin-photon entanglement. In this paper, we theoretically study the light absorption and emission by the interface with an anisotropic cavity and derive the maximal excitation and spin-photon entanglement conditions. We show that the concurrence of the spin-photon state equal to one and complete quantum dot population inversion can be reached for a micropillar cavity with any degree of birefringence by tuning the quantum dot resonance strictly between the cavity modes. This sweet spot is also valid for generating a multiphoton cluster state, as we demonstrate by calculating the three-tangle and fidelity with the maximally entangled state., Comment: 10 pages, 4 figures

We fit various colour-magnitude diagrams (CMDs) of the high-latitude Galactic globular clusters NGC\,5024 (M53), NGC\,5053, NGC\,5272 (M3), NGC\,5466, and NGC\,7099 (M30) by isochrones from the Dartmouth Stellar Evolution Database and Bag of Stellar Tracks and Isochrones for $\alpha$-enrichment [$\alpha$/Fe]$=+0.4$. For the CMDs, we use data sets from {\it Hubble Space Telescope}, {\it Gaia}, and other sources utilizing, at least, 25 photometric filters for each cluster. We obtain the following characteristics with their statistic uncertainties for NGC\,5024, NGC\,5053, NGC\,5272, NGC\,5466, and NGC\,7099, respectively: metallicities [Fe/H]$=-1.93\pm0.02$, $-2.08\pm0.03$, $-1.60\pm0.02$, $-1.95\pm0.02$, and $-2.07\pm0.04$ dex with their systematic uncertainty 0.1 dex; ages $13.00\pm0.11$, $12.70\pm0.11$, $11.63\pm0.07$, $12.15\pm0.11$, and $12.80\pm0.17$ Gyr with their systematic uncertainty 0.8 Gyr; distances (systematic uncertainty added) $18.22\pm0.06\pm0.60$, $16.99\pm0.06\pm0.56$, $10.08\pm0.04\pm0.33$, $15.59\pm0.03\pm0.51$, and $8.29\pm0.03\pm0.27$ kpc; reddenings $E(B-V)=0.023\pm0.004$, $0.017\pm0.004$, $0.023\pm0.004$, $0.023\pm0.003$, and $0.045\pm0.002$ mag with their systematic uncertainty 0.01 mag; extinctions $A_\mathrm{V}=0.08\pm0.01$, $0.06\pm0.01$, $0.08\pm0.01$, $0.08\pm0.01$, and $0.16\pm0.01$ mag with their systematic uncertainty 0.03 mag, which suggest the total Galactic extinction $A_\mathrm{V}=0.08$ across the whole Galactic dust to extragalactic objects at the North Galactic pole. The horizontal branch morphology difference of these clusters is explained by their different metallicity, age, mass-loss efficiency, and loss of low-mass members in the evolution of the core-collapse cluster NGC\,7099 and loose clusters NGC\,5053 and NGC\,5466., Comment: 9 figures, published in Research in Astronomy and Astrophysics

We introduce a novel time-division multiplexing differential saturated absorption spectroscopy (TDMDSAS) approach, providing superior accuracy and stability in Doppler-free spectroscopy. By distinguishing probe and reference fields in the temporal domain, TDMDSAS efficiently suppresses Doppler broadening and common-mode optical noise. We utilized this technology to determine the absolute frequency of diverse neutral Yb isotopes across its $6s^2\ ^{1}S_0\to 6s6p ^{1}P_1$ transitions. Furthermore, the first-ever observation of in-situ Doppler-free Zeeman sub-level spectra was accomplished, enabling the determination of magnetic field gradients. We stabilized a UV diode laser at 399 nm using an error signal derived from the spectral first-derivative demodulated signal of $^{174}\mathrm{Yb}$. This technique yielded a frequency stability of up to 15 kHz with a 40 s averaging time and a standard deviation of around 180 kHz over a half-hour period. Given its low cost, straightforward, and scalable nature, TDMDSAS holds excellent potential in metrology and quantum applications.

In this work we provide theoretical estimates for the ranks of the power functions $f(k) = k^{-\alpha}$, $\alpha>1$ in the quantized tensor train (QTT) format for $k = 1, 2, 3, \ldots, 2^{d}$. Such functions and their several generalizations (e.~g. $f(k) = k^{-\alpha} \cdot e^{-\lambda k}, \lambda > 0$) play an important role in studies of the asymptotic solutions of the aggregation-fragmentation kinetic equations. In order to support the constructed theory we verify the values of QTT-ranks of these functions in practice with the use of the TTSVD procedure and show an agreement between the numerical and analytical results., Comment: 6 pages, 1 figure, 20 references

Nonequilibrium quantum noise $S^>(\omega,V)$ measured at finite frequencies $\omega$ and bias voltages $V$ probes Majorana bound states in a host nanostructure via fluctuation fingerprints unavailable in average currents or static shot noise. When Majorana interference is brought into play, it enriches nonequilibrium states and makes their nature even more unique. Here we demonstrate that an interference of two Majorana modes via a nonequilibrium quantum dot gives rise to a remarkable finite frequency response of the differential quantum noise $\partial S^>(\omega,V,\Delta\phi)/\partial V$ driven by the Majorana phase difference $\Delta\phi$. Specifically, at low bias voltages there develops a narrow resonance of width $\hbar\Delta\omega\sim\sin^2\Delta\phi$ at a finite frequency determined by $V$, whereas for high bias voltages there arise two antiresonances at two finite frequencies controlled by both $V$ and $\Delta\phi$. We show that the maximum and minimum of these resonance and antiresonances have universal fractional values, $3e^3/4h$ and $-e^3/4h$. Moreover, detecting the frequencies of the antiresonances provides a potential tool to measure $\Delta\phi$ in nonequilibrium experiments on Majorana finite frequency quantum noise., Comment: 14 pages, 8 figures

Synthetic data is gaining increasing relevance for training machine learning models. This is mainly motivated due to several factors such as the lack of real data and intra-class variability, time and errors produced in manual labeling, and in some cases privacy concerns, among others. This paper presents an overview of the 2nd edition of the Face Recognition Challenge in the Era of Synthetic Data (FRCSyn) organized at CVPR 2024. FRCSyn aims to investigate the use of synthetic data in face recognition to address current technological limitations, including data privacy concerns, demographic biases, generalization to novel scenarios, and performance constraints in challenging situations such as aging, pose variations, and occlusions. Unlike the 1st edition, in which synthetic data from DCFace and GANDiffFace methods was only allowed to train face recognition systems, in this 2nd edition we propose new sub-tasks that allow participants to explore novel face generative methods. The outcomes of the 2nd FRCSyn Challenge, along with the proposed experimental protocol and benchmarking contribute significantly to the application of synthetic data to face recognition., Comment: arXiv admin note: text overlap with arXiv:2311.10476

Large Language Models (LLMs) are capable of transforming natural language domain descriptions into plausibly looking PDDL markup. However, ensuring that actions are consistent within domains still remains a challenging task. In this paper we present a novel concept to significantly improve the quality of LLM-generated PDDL models by performing automated consistency checking during the generation process. Although the proposed consistency checking strategies still can't guarantee absolute correctness of generated models, they can serve as valuable source of feedback reducing the amount of correction efforts expected from a human in the loop. We demonstrate the capabilities of our error detection approach on a number of classical and custom planning domains (logistics, gripper, tyreworld, household, pizza).