February 2024 arXiv papers — page 64

Werner U Boeglin, Misak M Sargsian

We demonstrate that at sufficiently high energies where the eikonal regime is established for hadronic interactions, the double scattering subprocess can be clearly identified and isolated in quasi-elastic deuteron electro-disintegration processes. Comparing theoretical calculations with the recent high precision experimental data we present a ``proof of pri

Dale R. Worley

This is a survey of characterizations and relationships between some properties of lattices, particularly the modular, Arguesian, linear, and distributive properties, but also some other related properties. The survey emphasizes finite and finitary lattices and deemphasizes complemented lattices.

Dylan Sam, Rattana Pukdee, Daniel P. Jeong, Yewon Byun

Bayesian neural networks (BNNs) have recently gained popularity due to their ability to quantify model uncertainty. However, specifying a prior for BNNs that captures relevant domain knowledge is often extremely challenging. In this work, we propose a framework for integrating general forms of domain knowledge (i.e., any knowledge that can be represented by

Shylaja G., Kesavulu Naidu V., Venkatesh B., S. M. Mallikarjunaiah

Accurate triangulation of the domain plays a pivotal role in computing the numerical approximation of the differential operators. A good triangulation is the one which aids in reducing discretization errors. In a standard collocation technique, the smooth curved domain is typically triangulated with a mesh by taking points on the boundary to approximate them

Zhiyao Ren, Yibing Zhan, Baosheng Yu, Liang Ding

The copilot framework, which aims to enhance and tailor large language models (LLMs) for specific complex tasks without requiring fine-tuning, is gaining increasing attention from the community. In this paper, we introduce the construction of a Healthcare Copilot designed for medical consultation. The proposed Healthcare Copilot comprises three main componen

Sabah Al-Fedaghi

Requirement specifications in software engineering involve developing a conceptual model of a target domain. The model is based on ontological exploration of things in reality. Many things in such a process closely tie to problems in metaphysics, the field of inquiry of what reality fundamentally is. According to some researchers, metaphysicians are trying t

Jorge Lauret, Cynthia Will

Given any compact homogeneous space $H/K$ with $H$ simple, we consider the new space $M=H\times H/\Delta K$, where $\Delta K$ denotes diagonal embedding, and study the existence, classification and stability of $H\times H$-invariant Einstein metrics on $M$, as a first step into the largely unexplored case of homogeneous spaces of compact non-simple Lie group

Kenji Sakugawa

Let $p$ be a prime number and let $V$ be a continuous representation of $\mathrm{Gal}(\overline {\mathbf Q}/\mathbf Q)$ on a finite dimensional $\mathbf Q_p$-vector space, which is geometric. One of the Bloch-Kato conjectures for $V$ predicts that the rank of the Hasse-Weil $L$-function of $V$ at $s=0$ coincides with the rank of Blcoh-Kato Selmer group of $V

Yanzhen Shen, Yu Zhang, Yunyi Zhang, Jiawei Han

Entity set expansion, taxonomy expansion, and seed-guided taxonomy construction are three representative tasks that can be applied to automatically populate an existing taxonomy with emerging concepts. Previous studies view them as three separate tasks. Therefore, their proposed techniques usually work for one specific task only, lacking generalizability and

A. Balbi, C. Grimaldi

The probability of detecting technosignatures (i.e. evidence of technological activity beyond Earth) increases with their longevity, or the time interval over which they manifest. Therefore, the assumed distribution of longevities has some bearing on the chances of success of technosignature searches, as well as on the inferred age of technosignatures follow

Jiaqi Ma, Vivian Lai, Yiming Zhang, Chacha Chen

Recently, there has been a surge of explainable AI (XAI) methods driven by the need for understanding machine learning model behaviors in high-stakes scenarios. However, properly evaluating the effectiveness of the XAI methods inevitably requires the involvement of human subjects, and conducting human-centered benchmarks is challenging in a number of ways: d

Denis Lukovnikov, Asja Fischer

While text-to-image diffusion models can generate highquality images from textual descriptions, they generally lack fine-grained control over the visual composition of the generated images. Some recent works tackle this problem by training the model to condition the generation process on additional input describing the desired image layout. Arguably the most

Dániel Gerbner

Xu in 2011 determined the largest value of the second Zagreb index in an $n$-vertex graph $G$ with clique number $k$, and also the smallest value with the additional assumption that $G$ is connected. We extend these results to other degree-based topological indices. The key property of the clique number in the first result is that $G$ is $K_{k+1}$-free, whil

Arpan Biswas, Sai Mani Prudhvi Valleti, Rama Vasudevan, Maxim Ziatdinov

Both computational and experimental material discovery bring forth the challenge of exploring multidimensional and often non-differentiable parameter spaces, such as phase diagrams of Hamiltonians with multiple interactions, composition spaces of combinatorial libraries, processing spaces, and molecular embedding spaces. Often these systems are expensive or

Sarka Necasova, Justyna Ogorzaly, Jan Scherz

We study a model of a general compressible viscous fluid subject to the Coulomb friction law boundary condition. For this model, we introduce a dissipative formulation and prove the existence of dissipative solutions. The proof of this result consists of a three-level approximation method: A Galerkin approximation, the classical parabolic regularization of t

Pramith Devulapalli, Steve Hanneke

Understanding the self-directed learning complexity has been an important problem that has captured the attention of the online learning theory community since the early 1990s. Within this framework, the learner is allowed to adaptively choose its next data point in making predictions unlike the setting in adversarial online learning. In this paper, we study

Ninell Oldenburg, Tan Zhi-Xuan

A universal feature of human societies is the adoption of systems of rules and norms in the service of cooperative ends. How can we build learning agents that do the same, so that they may flexibly cooperate with the human institutions they are embedded in? We hypothesize that agents can achieve this by assuming there exists a shared set of norms that most o

William R. Milner, Stefan Lannig, Mikhail Mamaev, Lingfeng Yan

Measurement science now connects strongly with engineering of quantum coherence, many-body states, and entanglement. To scale up the performance of an atomic clock using a degenerate Fermi gas loaded in a three-dimensional optical lattice, we must understand complex many-body Hamiltonians to ensure meaningful gains for metrological applications. In this work

Yifan Wang, Vyom Pathak, Daisy Zhe Wang

Similarity join finds all pairs of close points within a given distance threshold. Many similarity join methods have been proposed, but they are usually not efficient on high-dimensional space due to the curse of dimensionality and data-unawareness. We investigate the possibility of using metric space Bloom filter (MSBF), a family of data structures checking

Brad N. Barlow, Thomas Kupfer, Bryce A. Smith, Veronika Schaffenroth

Detailed studies of hot subdwarf B stars with red dwarf or brown dwarf companions can shed light on the effects of binarity on late stellar evolution. Such systems exhibit a strong, quasi-sinusoidal reflection effect due to irradiation of the cool companion, and some even show primary and secondary eclipses. Here we compute Fourier transforms of TESS light c

Arnab Kumar Maity

The quest for understanding the complex phenomena of the world has led to the development of various fields of science, each with its own methods, models, and assumptions. However, sometimes these fields can intersect and inspire each other, revealing new insights and perspectives that transcend the boundaries of their domains. In this paper, we explore one

Kaiqi Jiang, Wenzhe Fan, Mao Li, Xinhua Zhang

Fairness-aware classification models have gained increasing attention in recent years as concerns grow on discrimination against some demographic groups. Most existing models require full knowledge of the sensitive features, which can be impractical due to privacy, legal issues, and an individual's fear of discrimination. The key challenge we will address is

Dongni Zhang, Tom Britton

We consider an SEIR epidemic model on a network also allowing random contacts, where recovered individuals could either recover naturally or be diagnosed. Upon diagnosis, manual contact tracing is triggered such that each infected network contact is reported, tested and isolated with some probability and after a random delay. Additionally, digital tracing (b

Solvejg Wastvedt, Joshua Snoke, Denis Agniel, Julie Lai

Health care decisions are increasingly informed by clinical decision support algorithms, but these algorithms may perpetuate or increase racial and ethnic disparities in access to and quality of health care. Further complicating the problem, clinical data often have missing or poor quality racial and ethnic information, which can lead to misleading assessmen

Nursultan Kuanyshov

We define and develop a homotopy invariant notion for the sequential topological complexity of a map $f:X\to Y,$ denoted $TC_{r}(f)$, that interacts with $TC_{r}(X)$ and $TC_{r}(Y)$ in the same way Jamie Scott's topological complexity map $TC(f)$ interacts with $TC(X)$ and $TC(Y).$ Furthermore, we apply $TC_{r}(f)$ to studying group homomorphisms $\phi: \Gam

Nils Graef

This micro-paper describes a trick to speed up inference of transformers with RoPE (such as LLaMA, Mistral, PaLM, and Gemma). For these models, a large portion of the first transformer layer can be precomputed, which results in slightly lower latency and lower cost-per-token. Because this trick optimizes only one layer, the relative savings depend on the tot

Julian Boesch

In an age where the distribution of information is crucial, current file sharing solutions suffer significant deficiencies. Popular systems such as Google Drive, torrenting and IPFS suffer issues with compatibility, accessibility and censorship. This paper introduces DistriFS, a novel decentralized approach tailored for efficient and large-scale distribution

C. Alexander Thomas, Lauren M. Weiss, Howard Isaacson, Hilke E. Schlichting

In order to understand the relationship between planet multiplicity, mass, and composition, we present newly measured masses of five planets in two planetary systems: Kepler-323 and Kepler-104. We used the HIRES instrument at the W.M. Keck Observatory to collect 79 new radial velocity measurements (RVs) for Kepler-323, which we combined with 48 literature RV

Moses Ganardi, Danny Hucke, Markus Lohrey, Konstantinos Mamouras

We study the space complexity of the following problem: For a fixed regular language $L$, we receive a stream of symbols and want to test membership of a sliding window of size $n$ in $L$. For deterministic streaming algorithms we prove a trichotomy theorem, namely that the (optimal) space complexity is either constant, logarithmic or linear, measured in the

Federica Stolf, David B. Dunson

Joint species distribution models are popular in ecology for modeling covariate effects on species occurrence, while characterizing cross-species dependence. Data consist of multivariate binary indicators of the occurrences of different species in each sample, along with sample-specific covariates. A key problem is that current models implicitly assume that

Jeremy Bailey, Ian D. Howarth, Daniel V. Cotton, Lucyna Kedziora-Chudczer

We present time-series linear-polarization observations of the bright O4 supergiant $\zeta$ Puppis. The star is found to show polarization variation on timescales of around an hour and longer. Many of the observations were obtained contemporaneously with Transiting Exoplanet Survey Satellite (TESS) photometry. We find that the polarization varies on similar

Nithin Govindarajan, Shivkumar Chandrasekaran, Patrick Dewilde

We present a unification and generalization of what is known in the literature as sequentially and hierarchically semi-separable (SSS and HSS) representations for matrices. Describing rank-structured representations of (inverses of) sparse matrices whose adjacency graph is a tree, it is shown that these so-called tree quasi-separable (TQS) matrices inherit a

Joshua F. Cooper, Seung Jin Choi, I. Esra Buyuktahtakin

In this study, we introduce an innovative deep learning framework that employs a transformer model to address the challenges of mixed-integer programs, specifically focusing on the Capacitated Lot Sizing Problem (CLSP). Our approach, to our knowledge, is the first to utilize transformers to predict the binary variables of a mixed-integer programming (MIP) pr

Weiye Chen, Yiqun Xie, Xiaowei Jia, Erhu He

When dealing with data from distinct locations, machine learning algorithms tend to demonstrate an implicit preference of some locations over the others, which constitutes biases that sabotage the spatial fairness of the algorithm. This unfairness can easily introduce biases in subsequent decision-making given broad adoptions of learning-based solutions in p

Alexandre Rege

We present two results related to magnetized Vlasov equations. Our first contribution concerns the stability of solutions to the magnetized Vlasov-Poisson system with a non-uniform magnetic field using the optimal transport approach introduced by Loeper [24]. We show that the extra magnetized terms can be suitably controlled by imposing stronger decay in vel

Kenneth Gill

We introduce a new complexity measure for finite strings using probabilistic finite-state automata (PFAs), in the same spirit as existing notions employing DFAs and NFAs, and explore its properties. The PFA complexity $A_P(x)$ is the least number of states of a PFA for which $x$ is the most likely string of its length to be accepted. The variant $A_{P,\delta

Cornelius Fritz, Co-Pierre Georg, Angelo Mele, Michael Schweinberger

Software development relies on code reuse to minimize costs, creating vulnerability risks through dependencies with substantial economic impact, as seen in the Crowdstrike and HeartBleed incidents. We analyze 52,897 dependencies across 16,102 Python repositories using a strategic network formation model incorporating observable and unobservable heterogeneity

Ivan Sekulić, Silvia Terragni, Victor Guimarães, Nghia Khau

In the realm of dialogue systems, user simulation techniques have emerged as a game-changer, redefining the evaluation and enhancement of task-oriented dialogue (TOD) systems. These methods are crucial for replicating real user interactions, enabling applications like synthetic data augmentation, error detection, and robust evaluation. However, existing appr

Nicola Neophytou, Afaf Taïk, Golnoosh Farnadi

The aftermath of the Covid-19 pandemic saw more severe outcomes for racial minority groups and economically-deprived communities. Such disparities can be explained by several factors, including unequal access to healthcare, as well as the inability of low income groups to reduce their mobility due to work or social obligations. Moreover, senior citizens were

Achraf Badahmane, Ahmed Ratnani, Hassane Sadok

We have presented a fast method for solving a specific type of block four-by-four saddlepoint problem arising from the finite element discretization of the generalized 3D Stokes problem. We analyze the eigenvalue distribution and the eigenvectors of the preconditioned matrix. Furthermore, we suggested utilizing the preconditioned global conjugate gradient me

Jing Han Sun, Ali Emami

While Large Language Models (LLMs) excel at the Winograd Schema Challenge (WSC), a coreference resolution task testing common-sense reasoning through pronoun disambiguation, they struggle with instances that feature minor alterations or rewording. To address this, we introduce EvoGrad, an open-source platform that harnesses a human-in-the-loop approach to cr

Jimeng Shi, Zeda Yin, Arturo Leon, Jayantha Obeysekera

In coastal river systems, frequent floods, often occurring during major storms or king tides, pose a severe threat to lives and property. However, these floods can be mitigated or even prevented by strategically releasing water before extreme weather events with hydraulic structures such as dams, gates, pumps, and reservoirs. A standard approach used by loca

Yifan Ding, Qingkai Zeng, Tim Weninger

Entity Linking (EL) is an essential and challenging task in natural language processing that seeks to link some text representing an entity within a document or sentence with its corresponding entry in a dictionary or knowledge base. Most existing approaches focus on creating elaborate contextual models that look for clues the words surrounding the entity-te

Wei Hou, Tim Colonius

We solve the incompressible Navier-Stokes equations using a lattice Green's function (LGF) approach, including immersed boundaries (IB) and adaptive mesh refinement (AMR), for external flows with one homogeneous direction (e.g. infinite cylinders of arbitrary cross-section). We hybridize a Fourier collocation (pseudo-spectral) method for the homogeneous dire

Karam Ghanem, Danilo Bzdok

Through Diffusion Models (DMs), we have made significant advances in generating high-quality images. Our exploration of these models delves deeply into their core operational principles by systematically investigating key aspects across various DM architectures: i) noise schedules, ii) samplers, and iii) guidance. Our comprehensive examination of these model

Md Rifat Arefin, Yan Zhang, Aristide Baratin, Francesco Locatello

Models prone to spurious correlations in training data often produce brittle predictions and introduce unintended biases. Addressing this challenge typically involves methods relying on prior knowledge and group annotation to remove spurious correlations, which may not be readily available in many applications. In this paper, we establish a novel connection

Anis Bousclet, Frederic Boyer, Yacine Chitour, Swann Marx

In this paper, we present an intrinsic derivation of the equations ruling the dynamics motion of a snake robot dynamics. Based on a Cosserat beam model, we first show that the extended configuration space is a Lie group. Endowing it with an appropriate left invariant metric, the corresponding Euler-Poincar\'e equations can be reduced to a system of hyperboli

Omer Cohen, Ron Meir, Nir Weinberger

We consider a statistical version of curriculum learning (CL) in a parametric prediction setting. The learner is required to estimate a target parameter vector, and can adaptively collect samples from either the target model, or other source models that are similar to the target model, but less noisy. We consider three types of learners, depending on the lev

Mark L. Lewis, Zhencai Shen, Quanfu Yan

Let $G$ be a finite group and $N_{\Omega}(G)$ be the intersection of the normalizers of all subgroups belonging to the set $\Omega(G),$ where $\Omega(G)$ is a set of all subgroups of $G$ which have some theoretical group property. In this paper, we show that $N_{\Omega}(G)= Z_{\infty}(G)$ if $\Omega(G)$ is one of the following: (i) the set of all self-normal

Yinghao Li, Rampi Ramprasad, Chao Zhang

Large language models (LLMs) have demonstrated impressive abilities in generating unstructured natural language according to instructions. However, their performance can be inconsistent when tasked with producing text that adheres to specific structured formats, which is crucial in applications like named entity recognition (NER) or relation extraction (RE).

Bikash C. Barik, Himadri Chakraborti, Aditya K. Jain, Buddhadeb Pal

A system in equilibrium keeps ``exploring" nearby states in the phase space and consequently, fluctuations can contain information, that the mean value does not. However, such measurements involve a fairly complex interplay of effects arising in the device and measurement electronics, that are non-trivial to disentangle. In this paper, we briefly analyse som

Raphaël Belliard

The Renormalisation Group (RG) is a systematic procedure used to regularise divergences appearing as artefacts when constructing solutions to a large class of differential problems, whether perturbatively or not. This paper is devoted to performing it in the non-perturbative context of flat sections of meromorphic connections in holomorphic principal bundles

C. A. Knapek, D. P. Mohr, P. Huber

A new experimental method for creating void-free complex (``dusty'') plasmas under microgravity conditions is presented. The method is based on a pulsed operation mode of a four-channel radio-frequency generator for plasma sustainment. A dust cloud of micrometer-sized particles can be immersed in the bulk of a low temperature plasma under microgravity condit

Clésio E. Mota, Juan M. Z. Pretel, César O. V. Flores

This study explores the behavior of compact stars within the framework of $f(R,L_m,T)$ gravity, focusing on the functional form $f(R,L_m,T) = R + \alpha TL_m$. The modified Tolman-Oppenheimer-Volkoff (TOV) equations are derived and numerically solved for several values of the free parameter $\alpha$ by considering both quark and hadronic matter -- described

Han Huang, Elchanan Mossel

We study the low-degree hardness of broadcasting on trees. Broadcasting on trees has been extensively studied in statistical physics, in computational biology in relation to phylogenetic reconstruction and in statistics and computer science in the context of block model inference, and as a simple data model for algorithms that may require depth for inference

CMS Collaboration

A search for exotic decays of the Higgs boson (H) with a mass of 125 GeV to a pair of light pseudoscalars $\mathrm{a}_1$ is performed in final states where one pseudoscalar decays to two b quarks and the other to a pair of muons or $\tau$ leptons. A data sample of proton-proton collisions at $\sqrt{s}$ = 13 TeV corresponding to an integrated luminosity of 13

Nick Fischer, Leo Wennmann

In this work we revisit the elementary scheduling problem $1||\sum p_j U_j$. The goal is to select, among $n$ jobs with processing times and due dates, a subset of jobs with maximum total processing time that can be scheduled in sequence without violating their due dates. This problem is NP-hard, but a classical algorithm by Lawler and Moore from the 60s sol

Yuanying Guan, Muqiao Huang, Ruodu Wang

We provide a new characterization of second-order stochastic dominance, also known as increasing concave order. The result has an intuitive interpretation that adding a risk with negative expected value in adverse scenarios makes the resulting position generally less desirable for risk-averse agents. A similar characterization is also found for convex order

Sabine El Khoury, Andrew R. Kustin

Let k be an arbitrary field, A be a standard graded Artinian Gorenstein k-algebra of embedding dimension four and socle degree three, and pi from P to A be a surjective graded homomorphism from a polynomial ring with four variables over k onto A. We give the minimal generators of the kernel of pi and the minimal homogeneous resolution of A by free P-modules.

Binh Duong Nguyen, Johannes Steiner, Peter Wellmann, Stefan Sandfeld

Detecting and analyzing various defect types in semiconductor materials is an important prerequisite for understanding the underlying mechanisms as well as tailoring the production processes. Analysis of microscopy images that reveal defects typically requires image analysis tasks such as segmentation and object detection. With the permanently increasing amo

Jiashi Yang

We study the flow of an electrically charged fluid through an elastic and porous medium. A three continuum model consisting of an elastic solid, a viscous fluid, and a mobile charge continuum is used. The relevant laws of physics are applied systematically to the constituents or the combined continuum, leading to their continuity equations for conservation o

Boran Apak, Medina Bandic, Aritra Sarkar, Sebastian Feld

Quantum algorithms, represented as quantum circuits, can be used as benchmarks for assessing the performance of quantum systems. Existing datasets, widely utilized in the field, suffer from limitations in size and versatility, leading researchers to employ randomly generated circuits. Random circuits are, however, not representative benchmarks as they lack t

Steven Rivetti, Ozlem Tugfe Demir, Emil Bjornson, Mikael Skoglund

Reconfigurable intelligent surfaces (RISs) have demonstrated significant potential for enhancing communication system performance if properly configured. However, a RIS might also pose a risk to the network security. In this letter, we explore the impact of a malicious RIS on a multi-user multiple-input single-output (MISO) system when the system is unaware

Sławomir Dadas, Michał Perełkiewicz, Rafał Poświata

We present Polish Information Retrieval Benchmark (PIRB), a comprehensive evaluation framework encompassing 41 text information retrieval tasks for Polish. The benchmark incorporates existing datasets as well as 10 new, previously unpublished datasets covering diverse topics such as medicine, law, business, physics, and linguistics. We conduct an extensive e

Zhaoyang Lv, Nicholas Charron, Pierre Moulon, Alexander Gamino

We present Aria Everyday Activities (AEA) Dataset, an egocentric multimodal open dataset recorded using Project Aria glasses. AEA contains 143 daily activity sequences recorded by multiple wearers in five geographically diverse indoor locations. Each of the recording contains multimodal sensor data recorded through the Project Aria glasses. In addition, AEA

Vladimir L. Kalashnikov, Evgeni Sorokin, Irina T. Sorokina

A distributed Kerr-lens mode locking regime can be realized in a waveguide laser by spatial profiling of the pump beam, thus creating a spatio-temporal soliton. Additional slow temporal modulation of the pump source stabilizes the spatio-temporal solution in a broad range of parameters, which are defined by the dynamic gain saturation. We choose a Cr:ZnS wav

Shuhao Cao, Long Chen, Seulip Lee

This manuscript develops edge-averaged virtual element (EAVE) methodologies to address convection-diffusion problems effectively in the convection-dominated regime. It introduces a variant of EAVE that ensures monotonicity (producing an $M$-matrix) on Voronoi polygonal meshes, provided their duals are Delaunay triangulations with acute angles. Furthermore, t

Luan Hoang, Michael S. Jolly

We enable a theory of intrinsic asymptotic expansions for the steady state solutions of the full Navier-Stokes equations. Such a theory was first developed in Foias et al (2024 Commun. Pure Appl. Anal. 23, 269-303) for Galerkin approximations. To overcome the lack of local compactness in infinite dimensional spaces, we introduce the notion of asymptotic expa

Štěpánka Jansová, Zdeněk Jansa, Lucie Nedvědová, Ján Minár

Asbestos is the term for silicate minerals with a typical fibrous structure and crystallise as separable fibres that can be released into the environment as a result of natural processes and anthropogenic activities. There is a need to intensify geo-environmental monitoring of the occurrence of natural asbestos on a global scale. The study of this material i

Jouko Vaananen, Boban Velickovic

We define a new class of infinitary logics $\mathscr L^1_{\kappa,\alpha}$ generalizing Shelah's logic $\mathbb L^1_\kappa$ defined in \cite{MR2869022}. If $\kappa=\beth_\kappa$ and $\alpha <\kappa$ is infinite then our logic coincides with $\mathbb L^1_\kappa$. We study the relation between these logics for different parameters $\kappa$ and $\alpha$. We give

Matej Antol, Jiri Marek, Michaela Capandova, Jaroslav Juracek

This short paper presents a compact overview of the Czech approach to implementing the European Open Science Cloud and plans for developing a Czech national infrastructure for FAIR research data. Its purpose is to provide an all-encompassing summary of the near future of research data management in Czechia. As such, we deliberately attempt to explain complic

Yuan Yao, Fedir Yudin

An upward equilateral triangle of side $n$ can be partitioned into $n$ unit upward equilateral triangles and $\frac{n(n-1)}{2}$ unit rhombi with $60^{\circ}$ and $120^{\circ}$ angles. In this paper, we focus on understanding such partitions with a fixed arrangement of unit triangles. We formulate a criterion for such a partition being unique, identify a set

Marcos M. Flores, Alexander Kusenko, Misao Sasaki

We reexamine production of primordial black holes in a supercooled phase transition. While a mere overdensity associated with a surviving false-vacuum patch does not imply formation of a black hole, it is possible for such a patch to evolve and create a black hole, thanks to the gradient energy stored in the bubble wall.

Steven van den Broek, Wouter Meulemans, Bettina Speckmann

Constructing partitions of colored points is a well-studied problem in discrete and computational geometry. We study the problem of creating a minimum-cardinality partition into monochromatic islands. Our input is a set $S$ of $n$ points in the plane where each point has one of $k \geq 2$ colors. A set of points is monochromatic if it contains points of only

Deng Pan, Jie Lin, Ariel Amir

The Luria-Delbr\"uck model is a classic model of population dynamics with random mutations, that has been used historically to prove that random mutations drive evolution. In typical scenarios, the relevant mutation rate is exceedingly small, and mutants are counted only at the final time point. Here, inspired by recent experiments on DNA repair, we study a

Anand Kalvit, Aleksandrs Slivkins, Yonatan Gur

We study "incentivized exploration" (IE) in social learning problems where the principal (a recommendation algorithm) can leverage information asymmetry to incentivize sequentially-arriving agents to take exploratory actions. We identify posterior sampling, an algorithmic approach that is well known in the multi-armed bandits literature, as a general-purpose

Kuroush Allameh, Edgar Shaghoulian

We use thermal effective field theory to derive that the coefficient of the first subleading piece of the thermal free energy, $c_1$, is equal to the coefficient of the subleading piece of the Casimir energy on $S^1 \times S^{d-2}$ for $d \geq 4$. We conjecture that this coefficient obeys a sign constraint $c_1 \geq 0$ in CFT and collect some evidence for th

Uroš A. Colović, Branislav I. Prvulović, Marko Radovanović

We study the $\mathbb Z_2$-zero-divisor cup-length, denoted by $\operatorname{zcl}_{\mathbb Z_2}(\widetilde G_{n,3})$, of the Grassmann manifolds $\widetilde G_{n,3}$ of oriented $3$-dimensional vector subspaces in $\mathbb R^n$. Some lower and upper bounds for this invariant are obtained for all integers $n\ge6$. For infinitely many of them the exact value

Alejandro Santacruz Hidalgo

Boundedness of an abstract formulation of Hardy operators between Lebesgue spaces over general measure spaces is studied and, when the domain is L^1, shown to be equivalent to the existence of a Hardy inequality on the half line with general Borel measures. This is done by extending the greatest decreasing minorant construction to general measure spaces depe

Sharon Felix, Antareep Gogoi, Kaitlyn Shavelle, Brandon Sike

JKCS041 ($z=1.8$) is one of the most distant galaxy cluster systems known, seen when the Universe was less than 4 billion years old. Recent Sunyaev-Zeldovich (SZ) observations show a temperature decrement that is less than expected based on mass estimates of the system from X-ray, weak gravitational lensing and galaxy richness measurements. In this paper we

D. Filipescu, I. Gheorghe, S. Goriely, A. Tudora

New measurements of photofission and photoneutron reactions on $^{238}$U and $^{232}$Th in the Giant Dipole Resonance (GDR) energy region have been performed at the laser Compton-scattering $\gamma$-ray source of the NewSUBARU synchrotron radiation facility using a high-and-flat efficiency moderated $^3$He detection array. The neutron-multiplicity sorting of

Kai-Hendrik Cohrs, Gherardo Varando, Nuno Carvalhais, Markus Reichstein

Hybrid modeling integrates machine learning with scientific knowledge to enhance interpretability, generalization, and adherence to natural laws. Nevertheless, equifinality and regularization biases pose challenges in hybrid modeling to achieve these purposes. This paper introduces a novel approach to estimating hybrid models via a causal inference framework

Anas Himmi, Guillaume Staerman, Marine Picot, Pierre Colombo

Hallucinated translations pose significant threats and safety concerns when it comes to the practical deployment of machine translation systems. Previous research works have identified that detectors exhibit complementary performance different detectors excel at detecting different types of hallucinations. In this paper, we propose to address the limitations

H. E. S. S. Collaboration, F. Aharonian, F. Ait Benkhali, J. Aschersleben

The radio galaxy M87 is a variable very-high energy (VHE) gamma-ray source, exhibiting three major flares reported in 2005, 2008, and 2010. Despite extensive studies, the origin of the VHE gamma-ray emission is yet to be understood. In this study, we investigate the VHE gamma-ray spectrum of M87 during states of high gamma-ray activity, utilizing 20.2$\,$ ho

Margaret-Anne Storey, Daniel Russo, Nicole Novielli, Takashi Kobayashi

As researchers, we are now witnessing a fundamental change in our technologically-enabled world due to the advent and diffusion of highly disruptive technologies such as generative AI, Augmented Reality (AR) and Virtual Reality (VR). In particular, software engineering has been profoundly affected by the transformative power of disruptive innovations for dec

Igor Shevchenko, Dan Crisan

This study proposes deterministic and stochastic energy-aware hybrid models that should enable simulations of idealized and primitive-equations Geophysical Fluid Dynamics (GFD) models at low resolutions without compromising on quality compared with high-resolution runs. Such hybrid models bridge the data-driven and physics-driven modelling paradigms by combi

Francesco Bertucci, Johan Henriksson, Brian McPeak, Sara Ricossa

In this paper, we explore positivity bounds for the effective field theory~(EFT) of a single weakly coupled massive vector field. The presence of both mass and spin makes the crossing properties of the amplitudes vastly complicated -- we address this by parametrizing the amplitudes as products of a polarization matrix and a vector of appropriately chosen fun

Andrei Neagu, Frédéric Godin, Clarence Simard, Leila Kosseim

Dynamic hedging is the practice of periodically transacting financial instruments to offset the risk caused by an investment or a liability. Dynamic hedging optimization can be framed as a sequential decision problem; thus, Reinforcement Learning (RL) models were recently proposed to tackle this task. However, existing RL works for hedging do not consider ma

Haorui Chen, Shengshi Pang

The quantum Zeno effect is a distinctive phenomenon in quantum mechanics, describing the nontrivial effect of frequent projective measurements on hindering the evolution of a quantum system. However, when subjected to environmental noise, the quantum system may dissipate, and the quantum Zeno effect no longer works. This research starts from the physical mec

Samuel Bouaziz--Ermann, Garazi Muguruza

Pseudorandom Quantum States (PRS) were introduced by Ji, Liu and Song as quantum analogous to Pseudorandom Generators. They are an ensemble of states efficiently computable but computationally indistinguishable from Haar random states. Subsequent works have shown that some cryptographic primitives can be constructed from PRSs. Moreover, recent classical and

Francesca Bonaiti, Sonia Bacca

In this work, we present new ab initio coupled-cluster calculations of dipole-excited state properties of 8He based on the chiral effective field theory interaction 1.8/2.0 (EM). We focus on the dipole polarizability, and compare the results to our previous study [Phys. Rev. C 105, 034313 (2022)] and subsequent theoretical work. With the aim of connecting th

Chris Hamilton, Jean-Baptiste Fouvry

Stellar systems - star clusters, galaxies, dark matter haloes, and so on - are ubiquitous characters in the evolutionary tale of our Universe. This tutorial article is an introduction to the collective dynamical evolution of the very large numbers of stars and/or other self-gravitating objects that comprise such systems, i.e. their kinetic theory. We begin b

Ehud Ahissar, Daniel Polani, Merav Ahissar

Could the abstract ideas of our minds originate from neuronal interactions within our brains? To address this question, we examine interactions within 'brain-world' (BW) and 'brain-brain' (BB) domains, which represent the brain's physical interactions with its environment and the mental interactions between brains, respectively. BW interactions are character

Sergei Gukov, James Halverson, Fabian Ruehle

Machine learning techniques are increasingly powerful, leading to many breakthroughs in the natural sciences, but they are often stochastic, error-prone, and blackbox. How, then, should they be utilized in fields such as theoretical physics and pure mathematics that place a premium on rigor and understanding? In this Perspective we discuss techniques for obt

Pradyumna Sadhu, Yong Tian

We investigate the Baryonic Faber-Jackson Relation (BFJR), examining the correlation between baryonic mass and velocity dispersion in galaxy groups and clusters. Originally analysed in elliptical galaxies, the BFJR is derivable from the empirical Radial Acceleration Relation (RAR) and MOdified Newtonian Dynamics (MOND), both showcasing a characteristic accel

Federica Loiacono, Roberto Decarli, Marco Mignoli, Emanuele Paolo Farina

We present JWST/NIRSpec integral field data of the quasar PJ308-21 at $z=6.2342$. As shown by previous ALMA and HST imaging, the quasar has two companion sources, interacting with the quasar host galaxy. The high-resolution G395H/290LP NIRSpec spectrum covers the $2.87-5.27\ \rm \mu m$ wavelength range and shows the rest-frame optical emission of the quasar

FASER Collaboration, Roshan Mammen Abraham, John Anders, Claire Antel

The Forward Search Experiment (FASER) at CERN's Large Hadron Collider (LHC) has recently directly detected the first collider neutrinos. Neutrinos play an important role in all FASER analyses, either as signal or background, and it is therefore essential to understand the neutrino event rates. In this study, we update previous simulations and present prescri

Lorenzo Sironi, Aaron Tran

General relativistic magnetohydrodynamic (GRMHD) simulations of black hole tilted disks -- where the angular momentum of the accretion flow at large distances is misaligned with respect to the black hole spin -- commonly display standing shocks, within a few to tens of gravitational radii from the black hole. In GRMHD simulations of geometrically thick, opti

A. L. Faisst, T. Morishita

The recent discovery of a galaxy at z=7.3 with undetected optical emission lines and a blue UV to optical continuum ratio in JWST spectroscopy is surprising and needs to be explained physically. Here, we explore two possibilities that could cause such a seemingly quiescent ~5e8 $\rm M_\odot$ galaxy in the early Universe: (i) stochastic variations in the star

Amir H. Khoram, Bianca Poggianti, Alessia Moretti, Benedetta Vulcani

Extraplanar tails of ionized stripped gas, extending up to several tens of kiloparsecs beyond the stellar disk, are often observed in ram-pressure stripped (RPS) galaxies in low redshift clusters. Recent studies have identified similar tails also at high redshift and we here present the first analysis of the chemical composition of such tails beyond the loca