March 2024 arXiv papers — page 112

Max H. Cohen, Tamas G. Molnar, Aaron D. Ames

Modern autonomous systems, such as flying, legged, and wheeled robots, are generally characterized by high-dimensional nonlinear dynamics, which presents challenges for model-based safety-critical control design. Motivated by the success of reduced-order models in robotics, this paper presents a tutorial on constructive safety-critical control via reduced-or

Javad Mohamadichamgavi, Mark Broom

Evolutionary game theory examines how strategies spread and persist in populations through reproduction and imitation based on their fitness. Traditionally, models assume instantaneous dynamics where fitness depends on the current population state. However, some real-world processes unfold over time, with outcomes emerging from history. This motivates incorp

Maciej Satkiewicz

Deep neural networks learn fragile "shortcut" features, rendering them difficult to interpret (black box) and vulnerable to adversarial attacks. This paper proposes semantic features as a general architectural solution to this problem. The main idea is to make features locality-sensitive in the adequate semantic topology of the domain, thus introducing a str

Robin Scholle, Walter Metzner, Demetrio Vilardi, Pietro M. Bonetti

We obtain an almost complete understanding of the mean-field phase diagram of the two-dimensional Hubbard model on a square lattice with a sizable next-nearest neighbor hopping and a moderate interaction strength. In particular, we clarify the nature of the transition region between the spiral and the stripe phase. Complementing previous [Phys. Rev. B 108, 0

Jiazhao Wang, Wenchao Jiang, Ruofeng Liu, Bin Hu

A physical-layer modulator is a vital component for an IoT gateway to map the symbols to signals. However, due to the soldered hardware chipsets on the gateway's motherboards or the diverse toolkits on different platforms for the software radio, the existing solutions either have limited extensibility or are platform-specific. Such limitation is hard to igno

Boris Maulén, Sergio Davis, Daniel Pons

In this article we derive a useful expectation identity using the language of quantum statistical mechanics, where density matrices represent the state of knowledge about the system. This identity allows to establish relations between different quantum observables depending on a continuous parameter. Such a parameter can be contained in the observables itsel

Zohar Rimon, Tom Jurgenson, Orr Krupnik, Gilad Adler

Meta-reinforcement learning (meta-RL) is a promising framework for tackling challenging domains requiring efficient exploration. Existing meta-RL algorithms are characterized by low sample efficiency, and mostly focus on low-dimensional task distributions. In parallel, model-based RL methods have been successful in solving partially observable MDPs, of which

Shaina Raza, Tahniat Khan, Veronica Chatrath, Drai Paulen-Patterson

In today's technologically driven world, the rapid spread of fake news, particularly during critical events like elections, poses a growing threat to the integrity of information. To tackle this challenge head-on, we introduce FakeWatch, a comprehensive framework carefully designed to detect fake news. Leveraging a newly curated dataset of North American ele

Chenxi Liu, Zhenyi Wang, Tianyi Xiong, Ruibo Chen

Few-Shot Class-Incremental Learning (FSCIL) models aim to incrementally learn new classes with scarce samples while preserving knowledge of old ones. Existing FSCIL methods usually fine-tune the entire backbone, leading to overfitting and hindering the potential to learn new classes. On the other hand, recent prompt-based CIL approaches alleviate forgetting

Run Huang, Souti Chattopadhyay

Stack Overflow is widely recognized by software practitioners as the go-to resource for addressing technical issues and sharing practical solutions. While not typically seen as a scholarly forum, users on Stack Overflow commonly refer to academic sources in their discussions. Yet, little is known about these referenced academic works and how they intersect t

Simon R. Dicker, Karen Perez Sarmiento, Brian Mason, Tanay Bhandarkar

In this paper we present the results of a blind survey for compact sources in 243 Galaxy clusters that were identified using the thermal Sunyaev-Zeldovich effect (tSZ). The survey was carried out at 90 GHz using MUSTANG2 on the Green Bank telescope and achieved a $5\sigma$ detection limit of 1 mJy in the center of each cluster. We detected 24 discrete source

Pierrick Pochelu

Among numerical libraries capable of computing gradient descent optimization, JAX stands out by offering more features, accelerated by an intermediate representation known as Jaxpr language. However, editing the Jaxpr code is not directly possible. This article introduces JaxDecompiler, a tool that transforms any JAX function into an editable Python code, es

Daniel Younis, Songbo Xie, Joseph H. Eberly

In order to elucidate the correlated motion of atomic electrons, we investigate the attosecond-scale dynamics of their entanglement arising due to nonsequential ionization driven by a strong, linearly-polarized laser field. The calculation is based on numerical integration of the time-dependent Schr\"{o}dinger equation for helium irradiated by a one-cycle, n

Zhiquan Zhang, Tianyu Li, Nadia Figueroa

Passivity is necessary for robots to fluidly collaborate and interact with humans physically. Nevertheless, due to the unconstrained nature of passivity-based impedance control laws, the robot is vulnerable to infeasible and unsafe configurations upon physical perturbations. In this paper, we propose a novel control architecture that allows a torque-controll

Harish Gadey, Stuart Arm, Justin Clarity, Pavlo Ivanusa

During the past few decades, there has been a renewed interest in advanced reactor concepts, especially the high-temperature gas-cooled and the molten salt-cooled technologies for energy production as well as hydrogen or process heat generation. Tri-structural isotropic fuel is intended to be used in some of these emerging reactor technologies. The fuel bear

Davood Momeni, Phongpichit Channuie, Mudhahir Al-Ajmi

We investigate static cylindrical solutions within an extended theory of modified gravity. By incorporating various coupling functions through a straightforward boost symmetry approach, we establish the equations of motion in a self-consistent manner and subsequently determine the linear scalar field profile. Utilizing analytical methods, we solve the system

Jakob Steidel, Ina Michalsky, Mohsen Ajdari, Milan Kivala

Bridged triarylamines, so-called N-heterotriangulenes (N-HTAs) are promising organic semiconductors for applications in optoelectronic devices. Thereby the electronic structure at organic/metal interfaces and within thin films as well as the electronically excited states dynamics after optical excitation is essential for the performance of organic-molecule-b

Jiayi Wu, Xiaomin Lin, Shahriar Negahdaripour, Cornelia Fermüller

Tasks such as autonomous navigation, 3D reconstruction, and object recognition near the water surfaces are crucial in marine robotics applications. However, challenges arise due to dynamic disturbances, e.g., light reflections and refraction from the random air-water interface, irregular liquid flow, and similar factors, which can lead to potential failures

Tao Li, Quanyan Zhu

We are currently facing unprecedented cyber warfare with the rapid evolution of tactics, increasing asymmetry of intelligence, and the growing accessibility of hacking tools. In this landscape, cyber deception emerges as a critical component of our defense strategy against increasingly sophisticated attacks. This chapter aims to highlight the pivotal role of

Ante Wang, Linfeng Song, Ye Tian, Baolin Peng

Calibration, which establishes the correlation between accuracy and model confidence, is important for LLM development. We design three off-the-shelf calibration methods based on self-consistency (Wang et al., 2022) for math reasoning tasks. Evaluation on two popular benchmarks (GSM8K and MathQA) using strong open-source LLMs (Mistral and LLaMA2), our method

Harish Gadey, Lucas Vander Wal, Robert Joseph

The United States DOE Office of Integrated Waste Management program is planning for the transportation, storage, and eventual disposal of spent nuclear fuel and high-level radioactive waste from nuclear power plant sites across the United States. The Next Generation System Analysis Model is an agent-based simulation toolkit that is used for system level simu

Sabrina Guastavino, Katsiaryna Bahamazava, Emma Perracchione, Fabiana Camattari

This study addresses the prediction of geomagnetic disturbances by exploiting machine learning techniques. Specifically, the Long-Short Term Memory recurrent neural network, which is particularly suited for application over long time series, is employed in the analysis of in-situ measurements of solar wind plasma and magnetic field acquired over more than on

Ji-Eun Lee, Shaohua Yan, Sehoon Oh, Jinwoong Hwang

Fe$_3$GaTe$_2$, a recently discovered van der Waals ferromagnet, demonstrates intrinsic ferromagnetism above room temperature, necessitating a comprehensive investigation of the microscopic origins of its high Curie temperature ($\textit{T}$$_C$). In this study, we reveal the electronic structure of Fe$_3$GaTe$_2$ in its ferromagnetic ground state using angl

Hsun-Yeong Yang, Barry T. Chiang, Guan-Ming Su, Hsi-Yu Schive

Fuzzy dark matter (FDM), an attractive dark matter candidate comprising ultralight bosons (axions) with a particle mass $m_a\sim10^{-22}$ eV, is motivated by the small-scale challenges of cold dark matter and features a kpc-size de Broglie wavelength. Quantum wave interference inside an FDM halo gives rise to stochastically fluctuating density granulation; t

Cezar Joiţa, Mihai Tibăr

The image of a holomorphic map germ is not necessarily locally open, and it is not always well-defined as a set germ. We find the structure of what becomes the image of a map germ when the target is a surface. We encode it as a decorated tree and we derive a complexity degree.

Daniel Le, Bao Viet Le Hung, Stefano Morra

Let $F/F^+$ be a CM extension and $H_{/F^+}$ a definite unitary group in three variables that splits over $F$. We describe Hecke isotypic components of mod $p$ algebraic modular forms on $H$ at first principal congruence level at $p$ and "minimal" level away from $p$ in terms of the restrictions of the associated Galois representation to decomposition groups

Giacomo Garaccione, Tommaso Fulcini, Paolo Stefanut Bodnarescul, Riccardo Coppola

Software testing is a crucial phase in software development, enabling the detection of issues and defects that may arise during the development process. Addressing these issues enhances software applications' quality, reliability, user experience, and performance. Graphical User Interface (GUI) testing, one such technique, involves mimicking a regular user's

Luis Felipe Casas, Ninad Khargonkar, Balakrishnan Prabhakaran, Yu Xiang

We introduce a large-scale dataset named MultiGripperGrasp for robotic grasping. Our dataset contains 30.4M grasps from 11 grippers for 345 objects. These grippers range from two-finger grippers to five-finger grippers, including a human hand. All grasps in the dataset are verified in the robot simulator Isaac Sim to classify them as successful and unsuccess

Johann Zöllner, Philipp Stegmann, Jürgen König, Eric Kleinherbers

Electronic transport through nanostructures can be suppressed by coherent population trapping, in which quantum coherence leads to a dark state that decouples from the drain electrode. Finite transport, then, relies on decoherence of the dark state. An alternative scenario for reduced transport is weak coupling of a state, referred to as a blocking state, to

Mohsen Ajdari, Ronja Pappenberger, Christian Walla, Ina Michalsky

N-heterotriangulenes (N-HTAs) represent a class of functional molecules with high potential for optoelectronic materials, for example as electron donating compounds in donor/acceptor (D/A) systems. The capability of two different N-HTAs, N-HTA 550 and N-HTA 557, the latter containing an additional 7-membered ring, to act as electron donors at interfaces with

Barath Venkateswaran, Trevor J. Jones, Grace Kresge, Joel Marthelot

The interplay between thin film hydrodynamics and solidification produces formidably intricate geophysical structures, such as stalactites and icicles, whose shape is a testimony of their long growth. In simpler settings, liquid films can also produce regular patterns. When coated on the underside of a flat plate, these films are unstable and yield lattices

Al Amin, Kamrul Hasan, Saleh Zein-Sabatto, Deo Chimba

In the healthcare domain, Magnetic Resonance Imaging (MRI) assumes a pivotal role, as it employs Artificial Intelligence (AI) and Machine Learning (ML) methodologies to extract invaluable insights from imaging data. Nonetheless, the imperative need for patient privacy poses significant challenges when collecting data from diverse healthcare sources. Conseque

R. David Mayrhofer, Peter Wölfle, Andrey V. Chubukov

We analyze the quasiparticle interaction function (the fully dressed and antisymmetrized interaction between fermions) for a two-dimensional Fermi liquid at zero temperature close to a q=0 charge quantum critical point (QCP) in the $s-$wave channel (the one leading to phase separation). By the Ward identities, this vertex function must be related to quasipar

Sergey A. Moiseev, Ali. A. Kamli

We show how the area theorem is applicable to the analytical description of the nonlinear interaction of surface plasmon modes with resonant two-level atoms. A closed analytical solution is obtained, which shows that surface plasmons can form long-propagating $2\pi$ pulses when interacting with an optically dense two-level atomic ensemble. The possible appli

Atah Nuh Mih, Alireza Rahimi, Asfia Kawnine, Francis Palma

This paper proposes an optimization of an existing Deep Neural Network (DNN) that improves its hardware utilization and facilitates on-device training for resource-constrained edge environments. We implement efficient parameter reduction strategies on Xception that shrink the model size without sacrificing accuracy, thus decreasing memory utilization during

E. Goffo, P. Chaturvedi, F. Murgas, G. Morello

We report the confirmation and mass determination of a mini-Neptune transiting the M3.5 V star TOI-4438 (G 182-34) every 7.44 days. A transit signal was detected with NASA's TESS space mission in the sectors 40, 52, and 53. In order to validate the planet TOI-4438 b and to determine the system properties, we combined TESS data with high-precision radial velo

Zhifan Sun, Antonio Valerio Miceli-Barone

Large Language Models (LLMs) are increasingly becoming the preferred foundation platforms for many Natural Language Processing tasks such as Machine Translation, owing to their quality often comparable to or better than task-specific models, and the simplicity of specifying the task through natural language instructions or in-context examples. Their generali

Cheng Peng, Sougata Mardanya, Alexander N. Petsch, Vineet Kumar Sharma

The Kitaev interaction, found in candidate materials such as $\alpha$-RuCl$_3$, occurs through the metal ($M$)-ligand ($X$)-metal ($M$) paths of the edge-sharing octahedra because the large spin-orbit coupling (SOC) on the metal atoms activates directional spin interactions. Here, we show that even in $3d$ transition-metal compounds, where the SOC of the met

Davide Talon, Phillip Lippe, Stuart James, Alessio Del Bue

Causal Representation Learning (CRL) aims at identifying high-level causal factors and their relationships from high-dimensional observations, e.g., images. While most CRL works focus on learning causal representations in a single environment, in this work we instead propose a first step towards learning causal representations from temporal sequences of imag

M. A. Weiss, F. S. Herbst, S. Eggert, M. Nakajima

Although often viewed as detrimental, fluctuations carry valuable information about the physical system from which they emerge. Femtosecond noise correlation spectroscopy (FemNoC) has recently been established to probe the ultrafast fluctuation dynamics of thermally populated magnons by measurement of their amplitude autocorrelation. Subharmonic lock-in dete

Adam Tupper, Christian Gagné

Data augmentation is one of the most effective techniques to improve the generalization performance of deep neural networks. Yet, despite often facing limited data availability in medical image analysis, it is frequently underutilized. This appears to be due to a gap in our collective understanding of the efficacy of different augmentation techniques across

Yiqing Shen, Jingxing Li, Xinyuan Shao, Blanca Inigo Romillo

Segment anything models (SAMs) are gaining attention for their zero-shot generalization capability in segmenting objects of unseen classes and in unseen domains when properly prompted. Interactivity is a key strength of SAMs, allowing users to iteratively provide prompts that specify objects of interest to refine outputs. However, to realize the interactive

S. Rathnayaka, S. Yano, K. Kawashima, J. Akimitsu

The recent observation of unconventional superconductivity in thin films of LaNiO2 (critical temperature, Tc~10 K) and in bulk single crystals of La3Ni2O7 (327) under pressure (Tc~80 K), has brought to light a long sought-after class of superconducting nickelates. Through structural measurements in the 327-system, it was shown that the absence of superconduc

Bin Cai, Hui Zhu

Magnetic field line curvature (FLC) scattering is an effective mechanism for collisionless particle scattering. In the terrestrial magnetosphere, the FLC scattering plays an essential role in shaping the outer boundary of protons radiation belt, the rapid decay of ring current, and the formation of proton isotropic boundary (IB). However, previous studies ha

Kartick C. Sarkar

Galactic outflows are ubiquitous in galaxies containing active star formation or supermassive black hole activity. The presence of a large-scale outflow from the center of our own Galaxy was confirmed after the discovery of two large ($\sim 8-10$ kpc) \gamma-ray bubbles using the \textit{Fermi-LAT} telescope. These bubbles, known as the Fermi Bubbles, are hi

Sepehr Mosadegh, Sina Kheirkhah

The effects of heterogeneous and homogeneous atomizations on combustion dynamics and flame spread rates of multi-droplets are experimentally investigated. The utilized fuel is biodiesel, which is doped with graphene oxide and blended with ethanol. Stable fuel suspensions are prepared. Either one droplet is positioned at the intersection of two thin fibers or

Jack Kramer, Omar Barrera, Sinwoo Cho, Vakhtang Chulukhadze

This work reports the first study of periodically poled piezoelectric film (P3F) lithium niobate (LiNbO3) resonators at cryogenic temperatures. We experimentally investigate the temperature dependency of resonant frequencies and quality factor (Q) of higher-order Lamb modes up to 20 GHz between 80{\deg}K and 297{\deg}K, using a tri-layer P3F LiNbO3 resonator

Luciano Abadias, Marta De León-Contreras, Alejandro Mahillo

In this paper we prove characterizations of the discrete Besov spaces in terms of the heat and Poisson semigroups associated with the discrete Laplacian that will allow us to prove regularity results for the fractional powers of the discrete Laplacian and the discrete Bessel potentials. Moreover, we provide new estimates for the derivatives of the discrete h

Olga Chekeres, Vladimir Salnikov

Previously, Wilson surface observables were interpreted as a class of Poisson sigma models. We profit from this construction to define and study the super version of Wilson surfaces. We provide some `proof of concept' examples to illustrate modifications resulting from appearance of odd degrees of freedom in the target.

Anirudha Sahoo

Due to availability of large amount of bandwidth in the 60 GHz band and support of contention-free channel access called Service Period (SP), the IEEE 802.11ad/ay Wi-Fi standard is well suited for low latency and high data rate applications. IEEE 802.11ad supports two types of SP user traffic: isochronous and asynchronous. These user traffic need guaranteed

V. K. Oikonomou

In this work we consider an axionic scalar-tensor theory of gravity and its effects on static neutron stars. The axionic theory is considered in the regime in which the axion oscillates around its potential minimum, which cosmologically occurs post-inflationary, when the Hubble rate is of the same order as the axion mass. We construct the TOV equations for t

Afsoon Alidadi Shamsabadi, Animesh Yadav, Halim Yanikomeroglu

Integrating non-terrestrial networks (NTNs), in particular high altitude platform stations (HAPS), with terrestrial networks, referred to as vHetNets, emerges as a promising future wireless network architecture for providing ubiquitous connectivity. In this context, optimizing the performance of vHetNets has become a paramount concern, particularly in harmon

D. Grüber, L. Sousa, P. P. Avelino

In this work we study the power spectrum of the Stochastic Gravitational Wave Background produced by standard and biased domain wall networks, using the Velocity-dependent One-Scale model to compute the cosmological evolution of their characteristic scale and root-mean-squared velocity. We consider a standard radiation + $\Lambda \rm CDM$ background and assu

Charly Robinson La Rocca, Jean-François Cordeau, Emma Frejinger

Efficient algorithms and solvers are required to provide optimal or near-optimal solutions quickly and enable organizations to react promptly to dynamic situations such as supply chain disruptions or changing customer demands. State-of-the-art mixed-integer programming (MIP) solvers are crafted to tackle a wide variety of problems, yet many real-world situat

Guglielmo Panelli, Shaun C. Burd, Erik J. Porter, Mark Kasevich

We demonstrate coherent Doppler-free three-photon excitation of the $^{1}S_{0}$$\leftrightarrow$$^{3}P_{0}$ optical clock transition and the $^{1}S_{0}$$\leftrightarrow$$^{3}P_{1}$ intercombination transition in free-space thermal clouds of $^{88}$Sr atoms. By appropriate orientation of the wavevectors of three lasers incident on the atoms, the first-order D

Ning Cheng, You Li, Jing Gao, Bin Fang

Tactility provides crucial support and enhancement for the perception and interaction capabilities of both humans and robots. Nevertheless, the multimodal research related to touch primarily focuses on visual and tactile modalities, with limited exploration in the domain of language. Beyond vocabulary, sentence-level descriptions contain richer semantics. Ba

Fabio Rigamonti, Luca Cortese, Francesco Bollati, Stefano Covino

We investigate the relevance of kinematically identified bulges, discs and their role relative to galaxy quenching. We utilize an analysis of the SDSS-MaNGA survey conducted with the GPU-based code BANG which simultaneously models galaxy photometry and kinematics to decompose galaxies into their structural components. Below M~1011 Msun, galaxies exhibit a wi

Christian M. Clausen, Jan Rossmeisl, Zachary W. Ulissi

Computational high-throughput studies, especially in research on high-entropy materials and catalysts, are hampered by high-dimensional composition spaces and myriad structural microstates. They present bottlenecks to the conventional use of density functional theory calculations, and consequently, the use of machine-learned potentials is becoming increasing

Chu Li, Zhihan Zhang, Michael Saugstad, Esteban Safranchik

Crowdsourcing platforms have transformed distributed problem-solving, yet quality control remains a persistent challenge. Traditional quality control measures, such as prescreening workers and refining instructions, often focus solely on optimizing economic output. This paper explores just-in-time AI interventions to enhance both labeling quality and domain-

Ziyu Liu, Azadeh Alavi, Minyi Li, Xiang Zhang

Self-supervised learning (SSL) has recently emerged as a powerful approach to learning representations from large-scale unlabeled data, showing promising results in time series analysis. The self-supervised representation learning can be categorized into two mainstream: contrastive and generative. In this paper, we will present a comprehensive comparative st

E. Bulbul, X. Zhang, M. Kluge, M. Brueggen

Odd radio circles (ORCs) are a newly discovered class of extended faint radio sources of unknown origin. We report the first detection of diffuse X-ray gas at the location of a low-redshift ORC (z=0.046) known as Cloverleaf ORC. This observation was performed with the XMM-Newton X-ray telescope. The physical extent of the diffuse X-ray emission corresponds t

Ties-A. Ohst, Benjamin Yadin, Birte Ostermann, Timo de Wolff

Understanding quantum phenomena which go beyond classical concepts is a focus of modern quantum physics. Here, we show how the theory of nonnegative polynomials emerging around Hilbert's 17th problem, can be used to optimally exploit data capturing the nonclassical nature of light. Specifically, we show that nonnegative polynomials can reveal nonclassicality

Balaji Ganesan, Matheen Ahmed Pasha, Srinivasa Parkala, Neeraj R Singh

Explaining neural model predictions to users requires creativity. Especially in enterprise applications, where there are costs associated with users' time, and their trust in the model predictions is critical for adoption. For link prediction in master data management, we have built a number of explainability solutions drawing from research in interpretabili

Md Salman Shamil, Dibyadip Chatterjee, Fadime Sener, Shugao Ma

3D hand pose is an underexplored modality for action recognition. Poses are compact yet informative and can greatly benefit applications with limited compute budgets. However, poses alone offer an incomplete understanding of actions, as they cannot fully capture objects and environments with which humans interact. We propose HandFormer, a novel multimodal tr

Joshua Davy-Castillo, Javier A. Cano-Arango, Sergio B. Juárez, Joan A. Austrich-Olivares

In this paper, we extend the quantum geometric tensor for parameter-dependent curved spaces to higher dimensions, and introduce an equivalent definition that generalizes the Zanardi, et al, formulation of the tensor. The parameter-dependent metric modifies the behavior of both the quantum metric tensor and Berry curvature in a purely geometric way. Our focus

Natalia S. Dergacheva, Anton A. Klyachko

How complex must two finite 2-complexes be to admit a common, but not finite common, covering? We obtain an almost answer: the minimum possible number of triangles in a pseudo-simplicial triangulation of each complex is 3, 4, or 5.

Olga Kharlampovich, Alina Vdovina

We answer the question asked by Louder, McReynolds and Patel, and prove the following statement. Let L be a RAAG, H a word quasiconvex subgroup of L, then there is a finite dimensional representation of L that separates the subgroup H in the induced Zariski topology. As a corollary, we establish a polynomial upper bound on the size of the quotients used to s

N. Biava, A. Bonafede, F. Gastaldello, A. Botteon

Radio observations of a few cool-core galaxy clusters have revealed the presence of diffuse emission on cluster scales, similar to what was found in merging clusters in the form of radio halos. These sources might suggest that a minor merger, while not sufficiently energetic to disrupt the cool core, could still trigger particle acceleration in the intraclus

Atila Poro, Mahya Hedayatjoo, Maryam Nastaran, Mahshid Nourmohammad

The accuracy of absolute parameters' estimation in contact binary systems is important for investigating their evolution and solving some challenges. The Gaia DR3 parallax is one of the methods used for estimating the absolute parameters, in cases where photometric data is the only one that is available. The use of this method includes advantages and limitat

Wojciech Dybalski, Alexander Stottmeister, Yoh Tanimoto

The minimization of the action of a QFT with a constraint dictated by the block averaging procedure is an important part of Ba{\l}aban's approach to renormalization. It is particularly interesting for QFTs with non-trivial target spaces, such as gauge theories or non-linear sigma models on a lattice. We analyze this step for the $O(4)$ non-linear sigma model

Tomas Hodan, Martin Sundermeyer, Yann Labbe, Van Nguyen Nguyen

We present the evaluation methodology, datasets and results of the BOP Challenge 2023, the fifth in a series of public competitions organized to capture the state of the art in model-based 6D object pose estimation from an RGB/RGB-D image and related tasks. Besides the three tasks from 2022 (model-based 2D detection, 2D segmentation, and 6D localization of o

Patricia Arroba, José L. Risco-Martín, Marina Zapater, José M. Moya

This work proposes an automatic methodology for modeling complex systems. Our methodology is based on the combination of Grammatical Evolution and classical regression to obtain an optimal set of features that take part of a linear and convex model. This technique provides both Feature Engineering and Symbolic Regression in order to infer accurate models wit

Dana Alsagheer, Rabimba Karanjai, Nour Diallo, Weidong Shi

This paper delves into the dynamic landscape of artificial intelligence, specifically focusing on the burgeoning prominence of large language models (LLMs). We underscore the pivotal role of Reinforcement Learning from Human Feedback (RLHF) in augmenting LLMs' rationality and decision-making prowess. By meticulously examining the intricate relationship betwe

Petr Jizba, Gaetano Lambiase, Giuseppe Gaetano Luciano, Leonardo Mastrototaro

Both the Barrow and Tsallis $\delta$ entropies are one-parameter generalizations of the black-hole entropy, with the same microcanonical functional form. The ensuing deformation is quantified by a dimensionless parameter $\Delta$, which in the case of Barrow entropy represents the anomalous dimension, while in Tsallis' case, it describes the deviation of the

Emanuele Zappala

We study the deformations of a wide class of Yang-Baxter (YB) operators arising from Lie algebras. We relate the higher order deformations of YB operators to Lie algebra deformations. We show that the obstruction to integrating deformations of self-distributive (SD) objects lie in the corresponding Lie algebra third cohomology group, and interpret this resul

Ellie Prosser, Matthew Edwards

Powerful generative Large Language Models (LLMs) are becoming popular tools amongst the general public as question-answering systems, and are being utilised by vulnerable groups such as children. With children increasingly interacting with these tools, it is imperative for researchers to scrutinise the safety of LLMs, especially for applications that could l

Paul Dütting, Michal Feldman, Yoav Gal-Tzur, Aviad Rubinstein

In the combinatorial-action contract model (D\"utting et al., FOCS'21) a principal delegates the execution of a complex project to an agent, who can choose any subset from a given set of actions. Each set of actions incurs a cost to the agent, given by a set function $c$, and induces an expected reward to the principal, given by a set function $f$. To incent

Daniel Flögel, Lars Fischer, Thomas Rudolf, Tobias Schürmann

Mobile robots are being used on a large scale in various crowded situations and become part of our society. The socially acceptable navigation behavior of a mobile robot with individual human consideration is an essential requirement for scalable applications and human acceptance. Deep Reinforcement Learning (DRL) approaches are recently used to learn a robo

Yifan Li, Hangyu Guo, Kun Zhou, Wayne Xin Zhao

In this paper, we study the harmlessness alignment problem of multimodal large language models (MLLMs). We conduct a systematic empirical analysis of the harmlessness performance of representative MLLMs and reveal that the image input poses the alignment vulnerability of MLLMs. Inspired by this, we propose a novel jailbreak method named HADES, which hides an

David Azriel, Yosef Rinott, Orna Tal, Benyamine Abbou

Efficient optimization of operating room (OR) activity poses a significant challenge for hospital managers due to the complex and risky nature of the environment. The traditional "one size fits all" approach to OR scheduling is no longer practical, and personalized medicine is required to meet the diverse needs of patients, care providers, medical procedures

Jesse Cohen

We show that there is a spectral sequence with $E^2$-page given by the Khovanov homology of a link in $S^1\times S^2$, as defined by Rozansky in arXiv:1011.1958, which converges to the Hochschild homology of an $A_\infty$-bimodule defined in terms of bordered Floer invariants. We also show that the homology algebras $H_*\mathfrak{h}_n$ of the algebras $\math

Nicolas Shu, David V. Anderson

There are many packages in Python which allow one to perform real-time processing on audio data. Unfortunately, due to the synchronous nature of the language, there lacks a framework which allows for distributed parallel processing of the data without requiring a large programming overhead and in which the data acquisition is not blocked by subsequent proces

Emanuele Costa, Giuseppe Scriva, Sebastiano Pilati

In recent years, machine learning models, chiefly deep neural networks, have revealed suited to learn accurate energy-density functionals from data. However, problematic instabilities have been shown to occur in the search of ground-state density profiles via energy minimization. Indeed, any small noise can lead astray from realistic profiles, causing the fa

Farrokh Razavinia

This paper is concerned with the structures introduced recently by the authors of the current paper concerning the multiplier Hopf $*$-graph algebras and also the Cuntz-Krieger algebras and their relations with the $C^*$-graph algebras, and once again by using the $C^*$-graph algebra constructions associated to our toy example, to initiate our first class of

Burak Çivitcioğlu, Rudolf A. Römer, Andreas Honecker

Detection of phase transitions is a critical task in statistical physics, traditionally pursued through analytic methods and direct numerical simulations. Recently, machine-learning techniques have emerged as promising tools in this context, with a particular focus on supervised and unsupervised learning methods, along with non-learning approaches. In this w

Anton Lipin

A subset $A$ of a topological space $X$ is called relatively functionally countable (RFC) in $X$, if for each continuous function $f : X \to \mathbb{R}$ the set $f[A]$ is countable. We prove that all RFC subsets of a product $\prod\limits_{n\in\omega}X_n$ are countable, assuming that spaces $X_n$ are Tychonoff and all RFC subsets of every $X_n$ are countable

Mladen Dimitrov, Chi-Yun Hsu

For each subset of primes in a totally real field above a rational prime $p$, there is the notion of partially classical Hilbert modular forms, where the empty set recovers the overconvergent forms and the full set of primes above $p$ yields classical forms. Given such a set, we $p$-adically interpolate the classical modular sheaves to construct families of

Garv Chauhan, Xun-Jie Xu

Light bosons can mediate long-range forces. We show that light bosonic mediators interacting with a background medium, in particular, with the cosmic neutrino background (C$\nu$B), may induce medium-dependent masses which could effectively screen long-range forces from detection. This leads to profound implications for long-range force searches in e.g. the E

Kushwanth Sistu, Siddhartha S. Borkotoky

We propose data-recovery schemes to improve the uplink reliability of Internet of Things (IoT) networks in which a gateway mounted on an unmanned aerial vehicle (UAV) collects data from sensor nodes on the ground. The proposed techniques employ fountain coding and message replication to correct frame erasures on the sensor-to-UAV links. A salient feature of

Jeff Lazar, Ying-Ying Li, Carlos A. Arguelles, Vedran Brdar

Neutrino telescopes, including IceCube, can detect galactic supernova events by observing the collective rise in photomultiplier count rates with a sub-second time resolution. Leveraging precise timing, we demonstrate the ability of neutrino telescopes to explore new weakly coupled states emitted from supernovae and subsequently decaying to neutrinos. Our ap

Andrew D. Sellek, Naman S. Bajaj, Ilaria Pascucci, Cathie J. Clarke

[Ne II] 12.81 $\mu\mathrm{m}$ emission is a well-used tracer of protoplanetary disk winds due to its blueshifted line profile. MIRI-MRS recently observed T Cha, detecting this line along with lines of [Ne III], [Ar II] and [Ar III], with the [Ne II] and [Ne III] lines found to be extended while the [Ar II] was not. In this complementary work, we use these li

Chong-Chong He, Massimo Ricotti

The formation of circumstellar discs is a critical step in the formation of stars and planets. Magnetic fields can strongly affect the evolution of angular momentum during prestellar core collapse, potentially leading to the failure of protostellar disc formation. This phenomenon, known as the magnetic braking catastrophe, has been observed in ideal-MHD simu

Oana Silvia Serea, Antoine Tambue, Guy Tsafack

In this paper, we study the well-posedness and regularity of non-autonomous stochastic differential algebraic equations (SDAEs) with nonlinear, locally Lipschitz and monotone (2) coefficients of the form (1). The main difficulty is the fact that the operator A(.) is non-autonomous, i.~e. depends on t and the matrix $A(t)$ is singular for all $t\in \left[0,T\

Danny Horta, Yuxi, Lu, Melissa K. Ness

Reconstructing the mass assembly history of the Milky Way relies on obtaining detailed measurements of the properties of many stars in the Galaxy, especially in the stellar halo. One of the most constraining quantities is stellar age, as it can shed light on the accretion time and quenching of star formation in merging satellites. However, obtaining reliable

Guillermo Arias-Tamargo, Sebastián Franco, Diego Rodríguez-Gómez

We make progress in understanding the geometry associated to the Generalized Toric Polygons (GTPs) encoding the Physics of 5d Superconformal Field Theories (SCFTs), by exploiting the connection between Hanany-Witten transitions and the mathematical notion of polytope mutations. From this correspondence, it follows that the singular geometry associated to a G

Gonzalo F. Casas, Luis E. Ibáñez, Fernando Marchesano

We study limits of vanishing Yukawa couplings of 4d chiral matter fields in Quantum Gravity, using as a laboratory type IIA orientifolds with D6-branes. In these theories chiral fermions arise at brane intersections, where an infinite tower of charged particles dubbed gonions are localised. We show that in the limit $Y\rightarrow 0$ some of these towers beco

Haruki Katoh, Chikako Yasui, Yuji Ikeda, Naoto Kobayashi

In this study, we performed high-resolution near-infrared (NIR) spectroscopy (R = 28,000; ${\lambda} = 0.90$-1.35 ${\mu}$m) with a high signal-to-noise ratio on HD 200775, a very young (${\sim}$0.1 Myr old) and massive intermediate-mass star (a binary star with a mass of about 10 $M_{\odot}$ each) with a protoplanetary disk. The obtained spectra show eight f

Fabian Wunder

We investigate the small-mass asymptotics of a class of massive $d$ dimensional angular integrals. These integrals arise in a wide range of perturbative quantum field theory calculations. We derive expressions characterizing their behavior in the vicinity of the massless limit for all cases with up to two denominators. The results established in this work ar

Enrique Fernández-Martínez, Xabier Marcano, Daniel Naredo-Tuero

We perform a global analysis of the bounds from charged lepton flavour violating observables to new physics. We parametrize generic new physics through the Effective Field Theory formalism and perform global fits beyond the common one-operator-at-a-time analyses to investigate how much present data is able to constrain the full parameter space. We particular

O. Springer, E. O. Ofek, B. Zackay, R. Konno

Detection of moving sources over complicated background is important for several reasons. First is measuring the astrophysical motion of the source. Second is that such motion resulting from atmospheric scintillation, color refraction, or astrophysical reasons is a major source of false alarms for image subtraction methods. We extend the Zackay, Ofek, and Ga