October 2023 arXiv papers — page 125

A. Erhart, V. Wagner, A. Wex, C. Goupy

Rare-event search experiments located on-surface, such as short-baseline reactor neutrino experiments, are often limited by muon-induced background events. Highly efficient muon vetos are essential to reduce the detector background and to reach the sensitivity goals. We demonstrate the feasibility of deploying organic plastic scintillators at sub-Kelvin temp

Michael Wiemeler

In 1996 Stolz conjectured that a string manifold with positive Ricci curvature has vanishing Witten genus. Here we prove this conjecture for toric string Fano manifolds and for string torus manifolds admitting invariant metrics of non-negative sectional curvature.

Valentijn Braun, Debarati Bhaumik, Diptish Dey

Albeit the widespread application of recommender systems (RecSys) in our daily lives, rather limited research has been done on quantifying unfairness and biases present in such systems. Prior work largely focuses on determining whether a RecSys is discriminating or not but does not compute the amount of bias present in these systems. Biased recommendations m

Katharina Eickhoff, Meike Neuwohner, Britta Peis, Niklas Rieken

We consider dynamic auctions for finding Walrasian equilibria in markets with indivisible items and strong gross substitutes valuation functions. Each price adjustment step in these auction algorithms requires finding an inclusion-wise minimal maximal overdemanded set or an inclusion-wise minimal maximal underdemanded set at the current prices. Both can be f

Peter R. Wiecha

Deep learning is currently being hyped as an almost magical tool for solving all kinds of difficult problems that computers have not been able to solve in the past. Particularly in the fields of computer vision and natural language processing, spectacular results have been achieved. The hype has now infiltrated several scientific communities. In (nano-)photo

Défi Junior Jubgang Fandio, Aswin Vishnuradhan, Eeswar Kumar Yalavarthi, Wei Cui

We combine parametric frequency upconversion with single-photon counting technology to achieve detection sensitivity down to the terahertz (THz) single-photon level. Our relatively simple detection scheme employs a near-infrared ultrafast source, a GaP nonlinear crystal, optical filters, and a single photon avalanche diode. This configuration is capable of d

Marlin Berger, Frederik Cloppenburg, Jens Eufinger, Thomas Gries

In manufacturing sectors such as textiles and electronics, manual processes are a fundamental part of production. The analysis and monitoring of the processes is necessary for efficient production design. Traditional methods for analyzing manual processes are complex, expensive, and inflexible. Compared to established approaches such as Methods-Time-Measurem

Jeff Calder, Wonjun Lee

We introduce a novel algorithm that converges to level-set convex viscosity solutions of high-dimensional Hamilton-Jacobi equations. The algorithm is applicable to a broad class of curvature motion PDEs, as well as a recently developed Hamilton-Jacobi equation for the Tukey depth, which is a statistical depth measure of data points. A main contribution of ou

Micha Christoph, Kalina Petrova, Raphael Steiner

A tantalizing open problem, posed independently by Stiebitz in 1995 and by Alon in 2006, asks whether for every pair of integers $s,t \ge 1$ there exists a finite number $F(s,t)$ such that the vertex set of every digraph of minimum out-degree at least $F(s,t)$ can be partitioned into non-empty parts $A$ and $B$ such that the subdigraphs induced on $A$ and $B

Tsz Ho Chan

Let $s_1, s_2, s_3, \cdots$ be the set of squarefree numbers in ascending order. In this paper, we prove that the following asymptotic on moments of gaps between squarefree numbers \[ \sum_{s_{k+1} \le x} (s_{k+1} - s_k)^\gamma \sim B(\gamma) x \; \; \mbox{ with some constant} \; \; B(\gamma) > 0 \] is true for $0 \le \gamma < 3.75$. This improves the previo

Marko Lindner, Dennis Schmeckpeper

The stability of an approximating sequence $(A_n)$ for an operator $A$ usually requires, besides invertibility of $A$, the invertibility of further operators, say $B, C, \dots$, that are well-associated to the sequence $(A_n)$. We study this set, $\{A,B,C,\dots\}$, of so-called stability indicators of $(A_n)$ and connect it to the asymptotics of $\|A_n\|$, $

Xiangyan Liu, Rongxue Li, Wei Ji, Tao Lin

The reasoning capabilities of LLM (Large Language Model) are widely acknowledged in recent research, inspiring studies on tool learning and autonomous agents. LLM serves as the "brain" of the agent, orchestrating multiple tools for collaborative multi-step task solving. Unlike methods invoking tools like calculators or weather APIs for straightforward tasks,

Chenxi Hu, Yujia Li, Yunhe Hou

Ice storms, known for their severity and predictability, necessitate proactive resilience enhancement in power systems. Traditional approaches often overlook the endogenous uncertainties inherent in human decisions and underutilize predictive information like forecast accuracy and preparation time. To bridge these gaps, we proposed a two-stage risk-informed

Shuaihao Zhang, Sérgio D. N. Lourenço, Dong Wu, Chi Zhang

Since the tension instability was discovered in updated Lagrangian smoothed particle hydrodynamics (ULSPH) at the end of the 20th century, researchers have made considerable efforts to suppress its occurrence. However, up to the present day, this problem has not been fundamentally resolved. In this paper, the concept of hourglass modes is firstly introduced

Patrick L. Combettes

We propose a geometric framework to describe and analyze a wide array of operator splitting methods for solving monotone inclusion problems. The initial inclusion problem, which typically involves several operators combined through monotonicity-preserving operations, is seldom solvable in its original form. We embed it in an auxiliary space, where it is asso

Hu Yu, Li Shen, Jie Huang, Hongsheng Li

Denoising diffusion models have emerged as a dominant approach for image generation, however they still suffer from slow convergence in training and color shift issues in sampling. In this paper, we identify that these obstacles can be largely attributed to bias and suboptimality inherent in the default training paradigm of diffusion models. Specifically, we

Y. I. Izotov, T. X. Thuan, N. G. Guseva, D. Schaerer

We present observations with the Cosmic Origins Spectrograph onboard the Hubble Space Telescope of nine most metal-deficient compact star-forming galaxies with oxygen abundances 12+log(O/H)=6.97-7.23, redshifts z=0.02811-0.13320, and stellar masses M*<10^7Msun. We aim to study the properties of Ly-alpha emission in these extremely metal-deficient objects. We

Xin Chen, Yucheng Ouyang, Xin Chen, Zhenchuan Chen

Molecular dynamics simulations have emerged as a potent tool for investigating the physical properties and kinetic behaviors of materials at the atomic scale, particularly in extreme conditions. Ab initio accuracy is now achievable with machine learning based interatomic potentials. With recent advancements in high-performance computing, highly accurate and

Lisa V. Drummond, Philip Lynch, Alexandra G. Hanselman, Devin R. Becker

Understanding the orbits of spinning bodies in curved spacetime is important for modeling binary black hole systems with small mass ratios. At zeroth order in mass ratio, the smaller body moves on a geodesic. Post-geodesic effects are needed to model the system accurately. One very important post-geodesic effect is the gravitational self-force, which describ

Muhammed Golec, Guneet Kaur Walia, Mohit Kumar, Felix Cuadrado

Recently, academics and the corporate sector have paid attention to serverless computing, which enables dynamic scalability and an economic model. In serverless computing, users only pay for the time they actually use resources, enabling zero scaling to optimise cost and resource utilisation. However, this approach also introduces the serverless cold start p

Navita Goyal, Connor Baumler, Tin Nguyen, Hal Daumé

AI systems have been known to amplify biases in real-world data. Explanations may help human-AI teams address these biases for fairer decision-making. Typically, explanations focus on salient input features. If a model is biased against some protected group, explanations may include features that demonstrate this bias, but when biases are realized through pr

Junjie Cao, Xinglong Jia, Jingwei Lian, Lei Meng

The CMS and ATLAS collaborations recently published their results searching for light Higgs bosons, using the complete Run 2 data of the LHC. Both reported an excess in the diphoton invariant mass distribution at $m_{\gamma \gamma} \simeq 95.4~{\rm GeV}$ with compatible signal strengths. The combined result corresponded to a local significance of $3.1\sigma$

Ravindu G. Thalagala, Sahan M. Gunawardena, Oscar De Silva, Awantha Jayasiri

This paper presents a unique outdoor aerial visual-inertial-LiDAR dataset captured using a multi-sensor payload to promote the global navigation satellite system (GNSS)-denied navigation research. The dataset features flight distances ranging from 300m to 5km, collected using a DJI M600 hexacopter drone and the National Research Council (NRC) Bell 412 Advanc

Risshin Okabe, Satoshi Shirai

Recently, a novel collider, called $\mu$TRISTAN, has been proposed, offering the capability to achieve high-energy collisions of anti-muons. This high-energy collider presents an exceptional opportunity for the discovery of electroweak-interacting massive particles (EWIMPs), which are predicted by various new physics models. In a lepton collider like $\mu$TR

Carlos Gómez-Rodríguez, Paul Williams

We evaluate a range of recent LLMs on English creative writing, a challenging and complex task that requires imagination, coherence, and style. We use a difficult, open-ended scenario chosen to avoid training data reuse: an epic narration of a single combat between Ignatius J. Reilly, the protagonist of the Pulitzer Prize-winning novel A Confederacy of Dunce

Jihoon Kim, Roopendra Rajawat, Tianhong Wang, Gennady Shvets

We demonstrate an ion acceleration scheme capable of simultaneously focusing and accelerating a multispecies ion beam with monoenergetic spectra to a few micron radius. The focal length and ion mean energy can be independently controlled: the former by using a different front-surface shape and the latter by tuning the laser-plasma parameters. We interpret th

Xingsi Dong, Si Wu

Bayesian brain theory suggests that the brain employs generative models to understand the external world. The sampling-based perspective posits that the brain infers the posterior distribution through samples of stochastic neuronal responses. Additionally, the brain continually updates its generative model to approach the true distribution of the external wo

Lachezar Filchev, Vasil Kolev

During past decades a marked manifestation of widespread erosion phenomena was studied worldwide. Global conservation community has launched campaigns at local, regional and continental level in developing countries for preservation of soil resources in order not only to stop or mitigate human impact on nature but also to improve life in rural areas introduc

Facundo Manuel Quiroga, Franco Ronchetti, Laura Lanzarini, Aurelio Fernandez-Bariviera

Convolutional Neural Networks (CNN) offer state of the art performance in various computer vision tasks. Many of those tasks require different subtypes of affine invariances (scale, rotational, translational) to image transformations. Convolutional layers are translation equivariant by design, but in their basic form lack invariances. In this work we investi

Alessandro Pietro Contini

The geometric theory of pseudo-differential and Fourier Integral Operators relies on the symplectic structure of cotangent bundles. If one is to study calculi with some specific feature adapted to a geometric situation, the corresponding notion of cotangent bundle needs to be adapted as well and leads to spaces with a singular symplectic structure. Analysing

Vladimir V. Bazhanov, Sergey M. Sergeev

In this paper we present a new solution of the star-triangle relation having positive Boltzmann weights. The solution defines an exactly solvable two-dimensional Ising-type (edge interaction) model of statistical mechanics where the local "spin variables" can take arbitrary integer values, i.e., the number of possible spin states at each site of the lattice

J. Butts, C. Wendt, R. Bowler, C. P. Hersh

Multiple data views measured on the same set of participants is becoming more common and has the potential to deepen our understanding of many complex diseases by analyzing these different views simultaneously. Equally important, many of these complex diseases show evidence of subgroup heterogeneity (e.g., by sex or race). HIP (Heterogeneity in Integration a

Hanpu Shen, Cheng-Long Wang, Zihang Xiang, Yiming Ying

This paper focuses on the problem of Differentially Private Stochastic Optimization for (multi-layer) fully connected neural networks with a single output node. In the first part, we examine cases with no hidden nodes, specifically focusing on Generalized Linear Models (GLMs). We investigate the well-specific model where the random noise possesses a zero mea

Taotao He, Siyue Liu, Mohit Tawarmalani

This paper develops a correspondence relating convex hulls of fractional functions with those of polynomial functions over the same domain. Using this result, we develop a number of new reformulations and relaxations for fractional programming problems. First, we relate 0-1 problems involving a ratio of affine functions with the boolean quadric polytope, and

Helgi Sigurðsson, Hai Chau Nguyen, Hai Son Nguyen

Bound states in the continuum have recently been utilized in photonic crystal gratings to achieve strong coupling and ultralow power-driven condensation of bosonic exciton-polariton quasiparticles with atypical Dirac-like features in their dispersion relation. Here, we develop the single- and many-body theory of these new effective relativistic exciton-polar

Bilizimbeye Edjeou, Bernadette Faye

Let $ \{P_{n}\}_{n\geq 0} $ be the sequence of Pell numbers defined by $ P_0=0 $, $ P_1 =1$ and $ P_{n+2}= 2P_{n+1} +P_n$ for all $ n\geq 0 $ and let $ \{Q_{n}\}_{n\geq 0} $ be its companion sequence, the Pell-Lucas numbers defined by $ Q_0=Q_1 =2$ and $ Q_{n+2}= 2Q_{n+1} +Q_n$ for all $ n\geq 0 $ . In this paper, we find all Pell and Pell-Lucas numbers whic

Yueming Lyu, Kang Zhao, Bo Peng, Huafeng Chen

Text-guided image editing faces significant challenges when considering training and inference flexibility. Much literature collects large amounts of annotated image-text pairs to train text-conditioned generative models from scratch, which is expensive and not efficient. After that, some approaches that leverage pre-trained vision-language models have been

Shervin Halat, Mohammad Rahmati, Ehsan Nazerfard

Recently, significant advancements in artificial intelligence have been attributed to the integration of self-supervised learning (SSL) scheme. While SSL has shown impressive achievements in natural language processing (NLP), its progress in computer vision has comparatively lagged behind. However, the incorporation of contrastive learning into existing visu

Yifei Zhang, Siyi Gu, Bo Pan, Guangji Bai

Visual explanation (attention)-guided learning uses not only labels but also explanations to guide model reasoning process. While visual attention-guided learning has shown promising results, it requires a large number of explanation annotations that are time-consuming to prepare. However, in many real-world situations, it is usually desired to prompt the mo

Patrick Chao, Alexander Robey, Edgar Dobriban, Hamed Hassani

There is growing interest in ensuring that large language models (LLMs) align with human values. However, the alignment of such models is vulnerable to adversarial jailbreaks, which coax LLMs into overriding their safety guardrails. The identification of these vulnerabilities is therefore instrumental in understanding inherent weaknesses and preventing futur

Zeyin Hou, Shuai Lu, Yijun Xu, Haifeng Qiu

The thermal inertia of buildings brings considerable flexibility to the heating and cooling load, which is known to be a promising demand response resource. The aggregate model that can describe the thermal dynamics of the building cluster is an important interference for energy systems to exploit its intrinsic thermal inertia. However, the private informati

Nicolas André da Costa Morazotti, Adonai Hilário da Silva, Gabriel Audi, Felipe Fernandes Fanchini

We introduce a strategy to develop optimally designed fields for continuous dynamical decoupling. Using our methodology, we obtain the optimal continuous field configuration to maximize the fidelity of a general one-qubit quantum gate. To achieve this, considering dephasing-noise perturbations, we employ an auxiliary qubit instead of the boson bath to implem

Gabriella Holden, Daniel Shiu, Lauren Strutt

We introduce and analyse a family of hash and predicate functions that are more likely to produce collisions for small reducible configurations of vectors. These may offer practical improvements to lattice sieving for short vectors. In particular, in one asymptotic regime the family exhibits significantly different convergent behaviour than existing hash fun

Ummya Salma, Md. Fazlul Huq Khan

This study explores the relationship between political stability and inflation in four South Asian countries, employing panel data spanning from 2001 to 2021. To analyze this relationship, the study utilizes the dynamic ordinary least square (DOLS) and fully modified ordinary least square (FMOLS) methods, which account for cross-sectional dependence and slop

Friederike Preusse, Anna Vesely, Thorsten Dickhaus

In multiple hypotheses testing it has become widely popular to make inference on the true discovery proportion (TDP) of a set $\mathcal{M}$ of null hypotheses. This approach is useful for several application fields, such as neuroimaging and genomics. Several procedures to compute simultaneous lower confidence bounds for the TDP have been suggested in prior l

Mehdi Kermanshah, Calin Belta, Roberto Tron

We propose an approach to synthesize linear feedback controllers for linear systems in polygonal environments. Our method focuses on designing a robust controller that can account for uncertainty in measurements. Its inputs are provided by a perception module that generates probability mass functions (PMFs) for predefined landmarks in the environment, such a

Davide Basile

Modal Transition Systems (MTS) are a well-known formalism that extend Labelled Transition Systems (LTS) with the possibility of specifying necessary and permitted behaviour. Modal refinement ($\preceq_m$) of MTS represents a step of the design process, namely the one in which some optional behaviour is discarded while other optional behaviour becomes necessa

Peter Fischer, Julian Baer, Moritz Cimander, Volker Wiechert

Changing the macroscopic properties of quantum materials by optically activating collective lattice excitations has recently become a major trend in solid state physics. One of the most commonly employed light-matter interaction routes is the displacive mechanism. However, the fundamental contribution to this process remains elusive, as the effects of free-c

Qiuhong Wei, Zhengxiong Yao, Ying Cui, Bo Wei

Large language models such as ChatGPT are increasingly explored in medical domains. However, the absence of standard guidelines for performance evaluation has led to methodological inconsistencies. This study aims to summarize the available evidence on evaluating ChatGPT's performance in medicine and provide direction for future research. We searched ten med

Bei-Bei Wang, Long Zhang

We investigate the dynamical characterization theory for periodically driven systems in which Floquet topology can be fully detected by emergent topological patterns of quench dynamics in momentum subspaces called band-inversion surfaces. We improve the results of a recent work [Zhang et al., Phys. Rev. Lett. 125, 183001 (2020)] and propose a more flexible s

Carla Rodríguez, Sören Arlt, Leonhard Möckl, Mario Krenn

Driven by human ingenuity and creativity, the discovery of super-resolution techniques, which circumvent the classical diffraction limit of light, represent a leap in optical microscopy. However, the vast space encompassing all possible experimental configurations suggests that some powerful concepts and techniques might have not been discovered yet, and mig

Prim Plansangkate

We develop a procedure to implement the method of quadric ansatz to a class of second order partial differential equations (PDEs), which includes the four-dimensional K\"ahler-Einstein equation with symmetry and the one-sided type-D Einstein equation with nonzero scalar curvature. The procedure, which reduces the PDEs to ordinary differential equations (ODEs

Numair Sani, Atalanti A. Mastakouri

Probabilities of Causation (PoC) play a fundamental role in decision-making in law, health care and public policy. Nevertheless, their point identification is challenging, requiring strong assumptions, in the absence of which only bounds can be derived. Existing work to further tighten these bounds by leveraging extra information either provides numerical bo

Marco Schumann, Frank K. Wilhelm, Alessandro Ciani

In variational quantum algorithms the parameters of a parameterized quantum circuit are optimized in order to minimize a cost function that encodes the solution of the problem. The barren plateau phenomenon manifests as an exponentially vanishing dependence of the cost function with respect to the variational parameters, and thus hampers the optimization pro

Christian Kern

In the theory of composites, hierarchical laminate microstructures are known to often show optimal behavior. In this paper, their performance in the context of the Hall effect is evaluated. Using numerical calculations, it is shown that - despite the fact that they are the result of a simple layering process - they can mimic the behavior of chain-mail-inspir

Guangda Sun, Jialin Li

Decentralized storage networks (DSNs) are storage systems powered by permissionless nodes. Data placement in DSNs must tolerate not only storage-device failures but also adversarial behavior that targets data availability. Byzantine nodes introduce unique challenges due to collusion and adaptive attacks. They can target specific data blocks by clustering wit

Rajkumar Sarma, Steffen Hardt

The thermoelectric response of thermally activated electrolytes (TAE) in a slit channel is studied theoretically and by numerical simulations. The term TAE refers to electrolytes whose charge carrier concentration is a function of temperature, as recently suggested for ionic liquids and highly concentrated aqueous electrolyte solutions. Two competing mechani

Paolo Burgio, Gianluca Brilli

The rise of power-efficient embedded computers based on highly-parallel accelerators opens a number of opportunities and challenges for researchers and engineers, and paved the way to the era of edge computing. At the same time, advances in embedded AI for object detection and categorization such as YOLO, GoogleNet and AlexNet reached an unprecedented level

Benjamin Briggs, James C. Cameron, Janina C. Letz, Josh Pollitz

We define a local homomorphism $(Q,k)\to (R,\ell)$ to be Koszul if its derived fiber $R \otimes^{\mathsf{L}}_Q k$ is formal, and if $\operatorname{Tor}^Q(R,k)$ is Koszul in the classical sense. This recovers the classical definition when $Q$ is a field, and more generally includes all flat deformations of Koszul algebras. The non-flat case is significantly m

De-Liang Bao, Mingquan Xu, Ao-Wen Li, Gang Su

The advent of monochromated electron energy-loss spectroscopy has enabled atomic-resolution vibrational spectroscopy, which triggered interest in spatially localized or quasi-localized vibrational modes in materials. Here we report the discovery of phonon vortices at heavy impurities in two-dimensional materials. We use density-functional-theory calculations

Ozdemir Can Kara, Charles Everson, Farshid Alambeigi

In this paper, with the goal of quantifying the qualitative image outputs of a Vision-based Tactile Sensor (VTS), we present the design, fabrication, and characterization of a novel Quantitative Surface Tactile Sensor (called QS-TS). QS-TS directly estimates the sensor's gel layer deformation in real-time enabling safe and autonomous tactile manipulation and

Erin M. Schliep, Alan E. Gelfand, Christopher W. Clark, Charles M. Mayo

Marine mammals are increasingly vulnerable to human disturbance and climate change. Their diving behavior leads to limited visual access during data collection, making studying the abundance and distribution of marine mammals challenging. In theory, using data from more than one observation modality should lead to better informed predictions of abundance and

Cora A. Duggan, Kevin C. Wolfe, Bradley Woosley, Marin Kobilarov

Multi-robot planning and coordination in uncertain environments is a fundamental computational challenge, since the belief space increases exponentially with the number of robots. In this paper, we address the problem of planning in uncertain environments with a heterogeneous robot team of fast scout vehicles for information gathering and more risk-averse ca

Yuanyuan Liang, Jianing Wang, Hanlun Zhu, Lei Wang

The task of Question Generation over Knowledge Bases (KBQG) aims to convert a logical form into a natural language question. For the sake of expensive cost of large-scale question annotation, the methods of KBQG under low-resource scenarios urgently need to be developed. However, current methods heavily rely on annotated data for fine-tuning, which is not we

Ondrej Skopek, Rahul Aralikatte, Sian Gooding, Victor Carbune

Despite recent advances, evaluating how well large language models (LLMs) follow user instructions remains an open problem. While evaluation methods of language models have seen a rise in prompt-based approaches, limited work on the correctness of these methods has been conducted. In this work, we perform a meta-evaluation of a variety of metrics to quantify

Eric R. Powers, Watcharaphol Paritmongkol, Dillon C. Yost, Woo Seok Lee

Hybrid organic-inorganic nanomaterials can exhibit transitional behavior that deviates from models developed for all-organic or all-inorganic materials systems. Here, we reveal the complexity of exciton-phonon interactions in a recently discovered 2D layered hybrid organic-inorganic semiconductor, silver phenylselenolate (AgSePh). Using femtosecond resonant

David C. Gordon, Alexander Winkler, Julian Bedei, Patrick Schaber

Model Predictive Control (MPC) provides an optimal control solution based on a cost function while allowing for the implementation of process constraints. As a model-based optimal control technique, the performance of MPC strongly depends on the model used where a trade-off between model computation time and prediction performance exists. One solution is the

Jingfeng Wu, Difan Zou, Zixiang Chen, Vladimir Braverman

Transformers pretrained on diverse tasks exhibit remarkable in-context learning (ICL) capabilities, enabling them to solve unseen tasks solely based on input contexts without adjusting model parameters. In this paper, we study ICL in one of its simplest setups: pretraining a linearly parameterized single-layer linear attention model for linear regression wit

Shiyang Yan, Zongxuan Liu, Lin Xu

Metric learning plays a critical role in training image retrieval and classification. It is also a key algorithm in representation learning, e.g., for feature learning and its alignment in metric space. Hyperbolic embedding has been recently developed. Compared to the conventional Euclidean embedding in most of the previously developed models, Hyperbolic emb

W. Riedel, O. Sipilä, E. Redaelli, P. Caselli

Aims. We aim to improve a previous model for the prediction of column densities and deuterium fractions of non- and singly deuterated methanol. Thereby, we try to identify crucial chemical and physical parameters, for which the study of deuteration could provide valuable additional constraints. Methods. We employed a gas-grain chemical code to devise a model

Árpád Kurkó, Nikolett Német, András Vukics

The photon-blockade breakdown bistability can be intuitively explained invoking the energy spectrum of the interacting qubit-mode system. Yet, the neoclassical solution of the driven-dissipative Jaynes-Cummings model has been shown to capture several key aspects of the phenomenon. In this paper, we set out to compare a fully quantum solution with the neo- an

Zhixuan Liang, Xingyu Zeng, Rui Zhao, Ping Luo

Active learning strategies aim to train high-performance models with minimal labeled data by selecting the most informative instances for labeling. However, existing methods for assessing data informativeness often fail to align directly with task model performance metrics, such as mean average precision (mAP) in object detection. This paper introduces Mean-

P. I. Cristofari, J. -F. Donati, C. Moutou, L. T. Lehmann

We present the results of an analysis aimed at probing the small-scale magnetic fields of M dwarfs observed with SPIRou, the nIR high-resolution spectro-polarimeter installed at the Canada-France-Hawaii Telescope, in the context of the SPIRou Legacy Survey. Our analysis relies on high-resolution median spectra built from several tens of spectra recorded betw

Gautam Bharali, Nikolai Nikolov

We prove two separate lower bounds -- one for nondegenerate convex domains and the other for nondegenerate $\mathbb{C}$-convex (but not necessarily convex) domains -- for the squeezing function that hold true for all domains in $\mathbb{C}^n$, for a fixed $n\geq 2$, of the stated class. We provide explicit expressions in terms of $n$ for these estimates.

Tianhao Lu, Chao Bian, Chao Qian

Evolutionary algorithms (EAs) are widely used for multi-objective optimization due to their population-based nature. Traditional multi-objective EAs (MOEAs) generate a large set of solutions to approximate the Pareto front, leaving a decision maker (DM) with the task of selecting a preferred solution. However, this process can be inefficient and time-consumi

Kausik Hira, Mohd Zaki, Dhruvil Sheth, Mausam

The discovery of new materials has a documented history of propelling human progress for centuries and more. The behaviour of a material is a function of its composition, structure, and properties, which further depend on its processing and testing conditions. Recent developments in deep learning and natural language processing have enabled information extra

Minh Le

This paper investigates the global existence and boundedness of solutions in a two-species chemotaxis system with two chemicals and sub-logistic sources. The presence of a sub-logistic source in only one cell density equation effectively prevents the occurrence of blow-up solutions, even in fully parabolic chemotaxis systems.

Hsi-Ai Tsao, Lei Hsiung, Pin-Yu Chen, Sijia Liu

Visual prompting (VP) is an emerging parameter-efficient fine-tuning approach to adapting pre-trained vision models to solve various downstream image-classification tasks. However, there has hitherto been little systematic study of the design space of VP and no clear benchmark for evaluating its performance. To bridge this gap, we propose AutoVP, an end-to-e

Francesca Guffanti

It is well-known in universal algebra that adding structure and equational axioms generates forgetful functors between varieties, and such functors all have left adjoints. The category of elementary doctrines provides a natural framework for studying algebraic theories, since each algebraic theory can be described by some syntactic doctrine and its models ar

Yuri Bakhtin, Konstantin Khanin, András Mészáros, Jeremy Voltz

We consider a last passage percolation model in dimension $1+1$ with potential given by the product of a spatial i.i.d. potential with symmetric bounded distribution and an independent i.i.d. in time sequence of signs. We assume that the density of the spatial potential near the edge of its support behaves as a power, with exponent $\kappa>-1$. We investigat

The Pierre Auger Collaboration, O. Lux, I. Krisch, O. Reitebuch

The wind mission Aeolus of the European Space Agency was a groundbreaking achievement for Earth observation. Between 2018 and 2023, the space-borne lidar instrument ALADIN onboard the Aeolus satellite measured atmospheric wind profiles with global coverage which contributed to improving the accuracy of numerical weather prediction. The precision of the wind

Matthew G. Boebinger, Ayana Ghosh, Kevin M. Roccapriore, Sudhajit Misra

Directed atomic fabrication using an aberration-corrected scanning transmission electron microscope (STEM) opens new pathways for atomic engineering of functional materials. In this approach, the electron beam is used to actively alter the atomic structure through electron beam induced irradiation processes. One of the impediments that has limited widespread

Moritz Willig, Matej Zečević, Devendra Singh Dhami, Kristian Kersting

Structural causal models (SCMs) are a powerful tool for understanding the complex causal relationships that underlie many real-world systems. As these systems grow in size, the number of variables and complexity of interactions between them does, too. Thus, becoming convoluted and difficult to analyze. This is particularly true in the context of machine lear

Clemens Etl, Mauro Ballicchia, Mihail Nedjalkov, Josef Weinbub

Applying a Weyl-Stratonovich transform to the evolution equation of the Wigner function in an electromagnetic field yields a multidimensional gauge-invariant equation which is numerically very challenging to solve. In this work, we apply simplifying assumptions for linear electromagnetic fields and the evolution of an electron in a plane (two-dimensional tra

John Bulava, Barbara Cid-Mora, Andrew D. Hanlon, Ben Hoerz

Recent results studying the masses and widths of low-lying baryon resonances in lattice QCD are presented. The $S$-wave $N\pi$ scattering lengths for both total isospins $I = 1/2$ and $I = 3/2$ are inferred from the finite-volume spectrum below the inelastic threshold together with the $I = 3/2$ $P$-wave containing the $\Delta(1232)$ resonance. A lattice QCD

Francesca Guffanti

We find a possible interpretation of Henkin's Theorem in the language of existential implicational doctrines. Under some smallness assumption, starting from an implicational existential doctrine, with non-trivial fibers, we construct a new doctrine which is rich -- meaning that for every formula $\varphi(x)$ there is a constant $c$ such that $\exists x\varph

Michael Hu Yiqing, Guangda Sun, Arun Fu, Akasha Zhu

Logical clocks are a fundamental tool to establish causal ordering of events in a distributed system. They have been used as the building block in weakly consistent storage systems, causally ordered broadcast, distributed snapshots, deadlock detection, and distributed system debugging. However, prior logical clock constructs fail to work in a permissionless

Boyang Xue, Weichao Wang, Hongru Wang, Fei Mi

Pretrained language models (PLMs) based knowledge-grounded dialogue systems are prone to generate responses that are factually inconsistent with the provided knowledge source. In such inconsistent responses, the dialogue models fail to accurately express the external knowledge they rely upon. Inspired by previous work which identified that feed-forward netwo

Emmanuel Davoust

Henri Camichel was an astronomer at Pic du Midi Observatory, where he contributed to the study of planets of the solar system and their satellites with Audouin Dollfus and his team. In 1961, with Charles Boyer, he found that the upper atmosphere of Venus had a counter-clockwise rotation of four days, which was later confirmed by space probes, as were the tea

Una M. Kelly, Meike Nauta, Lu Liu, Luuk J. Spreeuwers

A morph is a combination of two separate facial images and contains identity information of two different people. When used in an identity document, both people can be authenticated by a biometric Face Recognition (FR) system. Morphs can be generated using either a landmark-based approach or approaches based on deep learning such as Generative Adversarial Ne

Honghui Yang, Sha Zhang, Di Huang, Xiaoyang Wu

In the context of autonomous driving, the significance of effective feature learning is widely acknowledged. While conventional 3D self-supervised pre-training methods have shown widespread success, most methods follow the ideas originally designed for 2D images. In this paper, we present UniPAD, a novel self-supervised learning paradigm applying 3D volumetr

Grigorii Trofimiuk

A novel search method for large polarization kernels is proposed. The algorithm produces a kernel with given partial distances by employing the depth-first search combined with the computation of coset leaders weight tables and sufficient conditions of code non-equivalence. Using the proposed method, we improved all existing lower bounds on the maximum error

Giovanni Burbi, Alberto Baldrati, Lorenzo Agnolucci, Marco Bertini

Multimodal image-text memes are prevalent on the internet, serving as a unique form of communication that combines visual and textual elements to convey humor, ideas, or emotions. However, some memes take a malicious turn, promoting hateful content and perpetuating discrimination. Detecting hateful memes within this multimodal context is a challenging task t

Xinyue Zheng, Haowei Lin, Kaichen He, Zihao Wang

Developing AI agents capable of interacting with open-world environments to solve diverse tasks is a compelling challenge. However, evaluating such open-ended agents remains difficult, with current benchmarks facing scalability limitations. To address this, we introduce Minecraft Universe (MCU), a comprehensive evaluation framework set within the open-world

Yan-Chen Bi, Yu-Mei Wu, Zu-Cheng Chen, Qing-Guo Huang

General relativity predicts that gravitational waves propagate at the speed of light. Although ground-based gravitational-wave detectors have successfully constrained the velocity of gravitational waves in the high-frequency range, extending this constraint to the lower frequency range remains a challenge. In this work, we utilize the deviations in the overl

Md. Rezaul Karim, Lina Molinas Comet, Md Shajalal, Oya Deniz Beyan

Domain experts often rely on most recent knowledge for apprehending and disseminating specific biological processes that help them design strategies for developing prevention and therapeutic decision-making in various disease scenarios. A challenging scenarios for artificial intelligence (AI) is using biomedical data (e.g., texts, imaging, omics, and clinica

Lihao Zhang, Haijian Sun, Jin Sun, Ramviyas Parasuraman

Urban vehicle-to-vehicle (V2V) link scheduling with shared spectrum is a challenging problem. Its main goal is to find the scheduling policy that can maximize system performance (usually the sum capacity of each link or their energy efficiency). Given that each link can experience interference from all other active links, the scheduling becomes a combinatori

Douglas Stryker

We show that min-max minimal hypersurfaces can be localized. As a consequence, we obtain the sharp generalization to complete manifolds of the famous Almgren-Pitts min-max theorem in closed manifolds. We use this result to prove the existence of a complete embedded finite area minimal hypersurface of index at most one in every balanced complete manifold.

Maha Riad, Vinicius de Carvalho, Fatemeh Golpayegani

Value-alignment in normative multi-agent systems is used to promote a certain value and to ensure the consistent behaviour of agents in autonomous intelligent systems with human values. However, the current literature is limited to the incorporation of effective norms for single-value alignment with no consideration of agents' heterogeneity and the requireme

Akinobu Goto, Kerstin Eder

Aiming for a society where humans and automated vehicles can coexist cooperatively, understanding what constitutes cooperative and trustworthy behaviour is essential to designing automated vehicle controllers that enable the integration of highly automated vehicles into the real world. This study investigates how merging vehicles can gain trust from human-dr