March 2024 arXiv papers — page 40

Kyungsun Lee, Akhil Sivakumar, Junggi Yoon

We study the gravitational edge mode in the $\mathcal{N}=1$ Jackiw-Teitelboim~(JT) supergravity on the disk and it $osp(2|1)$ BF formulation. We revisit the derivation of the finite-temperature Schwarzian action in the conformal gauge of the bosonic JT gravity through wiggling boundary and the frame fluctuation descriptions. Extending our method to $\mathcal

Sulaiman Aburakhia, Abdallah Shami, George K. Karagiannidis

Recent advancements in sensing, measurement, and computing technologies have significantly expanded the potential for signal-based applications, leveraging the synergy between signal processing and Machine Learning (ML) to improve both performance and reliability. This fusion represents a critical point in the evolution of signal-based systems, highlighting

Rita Fioresi, Robert Yuncken

These notes present a quick introduction to the q-deformations of semisimple Lie groups from the point of view of unitary representation theory. In order to remain concrete, we concentrate entirely on the case of the lie algebra $\mathrm{sl}(2,\mathbb{C})$ and its associated compact and complex semisimple Lie groups $\mathrm{SU}(2)$ and $\mathrm{SL}(2,\mathb

Stefano Schmidt, Sarah Caudill

We propose a novel signal-consistency test applicable to a broad search for gravitational waves emitted by generic binary black hole (BBH) systems. The test generalizes the time domain $\xi^2$ signal-consistency test currently utilized by the GstLAL pipeline, which quantifies the discrepancy between the expected signal-to-noise ratio timeseries with the meas

Alexander N. Pechen, Sergey Borisenok, Alexander L. Fradkov

We develop and analyze a new method for manipulation of energy in a quantum harmonic oscillator using coherent, e.g., electromagnetic, field and incoherent control. Coherent control is typically implemented by shaped laser pulse or tailored electromagnetic field. Incoherent control is implemented by engineered environment, whose mean number of excitations at

Yalda Zafari-Ghadim, Ahmed Soliman, Yousif Yousif, Ahmed Ibrahim

Stroke segmentation plays a crucial role in the diagnosis and treatment of stroke patients by providing spatial information about affected brain regions and the extent of damage. Segmenting stroke lesions accurately is a challenging task, given that conventional manual techniques are time consuming and prone to errors. Recently, advanced deep models have bee

Joshua Peeples, Salim Al Kharsa, Luke Saleh, Alina Zare

In the computer vision literature, many effective histogram-based features have been developed. These engineered features include local binary patterns and edge histogram descriptors among others and they have been shown to be informative features for a variety of computer vision tasks. In this paper, we explore whether these features can be learned through

Ali Abedi, Shehroz S. Khan

Engagement in virtual learning is crucial for a variety of factors including student satisfaction, performance, and compliance with learning programs, but measuring it is a challenging task. There is therefore considerable interest in utilizing artificial intelligence and affective computing to measure engagement in natural settings as well as on a large sca

Mahyar JafariNodeh, Amir Ajorlou, Ali Jadbabaie

In this paper, we consider the problem of social learning, where a group of agents embedded in a social network are interested in learning an underlying state of the world. Agents have incomplete, noisy, and heterogeneous sources of information, providing them with recurring private observations of the underlying state of the world. Agents can share their le

Rangel Daroya, Aaron Sun, Subhransu Maji

Modeling and visualizing relationships between tasks or datasets is an important step towards solving various meta-tasks such as dataset discovery, multi-tasking, and transfer learning. However, many relationships, such as containment and transferability, are naturally asymmetric and current approaches for representation and visualization (e.g., t-SNE) do no

Franziska Borer, Marcos T. O. Pimenta, Patrick Winkert

In this paper we consider degenerate Kirchhoff-type equations of the form \[-\phi(\Xi(u)) \left(\mathcal{A}(u)-|u|^{p-2}u\right) = f(x,u)\quad \text{in } \Omega,\] \[\phantom{aaiaaaaaaaaa}\phi (\Xi(u)) \mathcal{B}(u) \cdot \nu = g(x,u) \quad \text{on } \partial\Omega,\] where $\Omega\subseteq \mathbb{R}^N$, $N\geq 2$, is a bounded domain with Lipschitz bound

Kobra Mahdavipour, Farzam Nosrati, Stefania Sciara, Roberto Morandotti

Indistinguishability of identical particles is a resource for quantum information processing and has been utilized to generate entanglement from independent particles that spatially overlap only at the detection stage. Here we provide a general controllable scheme capable of generating, from a pure product state of $N$ qubits, a comprehensive class of multip

Nicholas Castillo

In this work we develop an algorithmic procedure for associating a function defined on the Riemann surface of the $\log$ to given asymptotic data from a function at an essential singularity. We do this by means of rational approximations (Pad\'e approximants) used in tandem with Borel-\'Ecalle summation. Our method is capable of handling situations where cla

Venktesh V, Abhijit Anand, Avishek Anand, Vinay Setty

Automated fact checking has gained immense interest to tackle the growing misinformation in the digital era. Existing systems primarily focus on synthetic claims on Wikipedia, and noteworthy progress has also been made on real-world claims. In this work, we release QuanTemp, a diverse, multi-domain dataset focused exclusively on numerical claims, encompassin

Danny Neftin, Michael E. Zieve

The combination of this paper and its companion complete the classification of monodromy groups of indecomposable coverings of complex curves $f:X\rightarrow \mathbb P^1$ of sufficiently large degree in comparison to the genus of $X$. In this paper we determine all such coverings with monodromy group $G\leq S_\ell\wr S_t$ of product type for $t\ge 2$.

Danny Neftin, Michael E. Zieve

For each nonnegative integer $g$, we classify the ramification types and monodromy groups of indecomposable coverings of complex curves $f: X\to Y$ where $X$ has genus $g$, under the hypothesis that $n:=\deg(f)$ is sufficiently large and the monodromy group is not $A_n$ or $S_n$. This proves a conjecture of Guralnick and several conjectures of Guralnick and

Jason T. Dong, Yilmaz Gul, Aaron N. Engel, Teun A. J. van Schijndel

High In content InGaAs quantum wells (In $\geq$ 75%) are potentially useful for topological quantum computing and spintronics applications. In high mobility InGaAs quantum wells, alloy disorder scattering is a limiting factor. In this report, we demonstrate that by growing the InGaAs quantum wells as a digital alloy, or a short period superlattice, we can re

Jessilyn Dunn, Varun Mishra, Md Mobashir Hasan Shandhi, Hayoung Jeong

Smartphones and wearable sensors offer an unprecedented ability to collect peripheral psychophysiological signals across diverse timescales, settings, populations, and modalities. However, open-source software development has yet to keep pace with rapid advancements in hardware technology and availability, creating an analytical barrier that limits the scien

Hannah Janmohamed, Marta Wolinska, Shikha Surana, Thomas Pierrot

Crystal structures are indispensable across various domains, from batteries to solar cells, and extensive research has been dedicated to predicting their properties based on their atomic configurations. However, prevailing Crystal Structure Prediction methods focus on identifying the most stable solutions that lie at the global minimum of the energy function

Federico Carollo, Igor Lesanovsky

Understanding quantum many-body systems with long-range or infinite-range interactions is of relevance across a broad set of physical disciplines, including quantum optics, nuclear magnetic resonance and nuclear physics. From a theoretical viewpoint, these systems are appealing since they can be efficiently studied with numerics, and in the thermodynamic lim

Tubagus Aryandi Gunawan, Lilianna Gittoes, Cecelia Isaac, Chris Greig

We present design methods and insights for CO2 capture, transport, and storage systems for clusters of industrial facilities, with a case-study focus on the state of Louisiana. Our analytical framework includes: (1) evaluating the scale and concentration of capturable CO2 emissions at individual facilities for the purpose of estimating the cost of CO2 captur

Sergi Martinez, Robert J. Griffin, Carlos Mastalli

Optimal estimation is a promising tool for estimation of payloads' inertial parameters and localization of robots in the presence of multiple contacts. To harness its advantages in robotics, it is crucial to solve these large and challenging optimization problems efficiently. To tackle this, we (i) develop a multiple shooting solver that exploits both tempor

Prasasthy Balasubramanian, Justin Seby, Panos Kostakos

In response to the escalating cyber-attacks in the modern IT and IoT landscape, we developed CYGENT, a conversational agent framework powered by GPT-3.5 turbo model, designed to aid system administrators in ensuring optimal performance and uninterrupted resource availability. This study focuses on fine-tuning GPT-3 models for cybersecurity tasks, including c

Attila Lischka, Jiaming Wu, Rafael Basso, Morteza Haghir Chehreghani

Most of the recent studies tackling routing problems like the Traveling Salesman Problem (TSP) with machine learning use a transformer or Graph Neural Network (GNN) based encoder architecture. However, many of them apply these encoders naively by allowing them to aggregate information over the whole TSP instances. We, on the other hand, propose a data prepro

Kexin Luo, Yue Mao, Bei Zhang, Sophie Hao

Inspired by the concept of the male gaze (Mulvey, 1975) in literature and media studies, this paper proposes a framework for analyzing gender bias in terms of female objectification: the extent to which a text portrays female individuals as objects of visual pleasure. Our framework measures female objectification along two axes. First, we compute an agency b

Spencer Kraisler, Mehran Mesbahi

We consider direct policy optimization for the linear-quadratic Gaussian (LQG) setting. Over the past few years, it has been recognized that the landscape of dynamic output-feedback controllers of relevance to LQG has an intricate geometry, particularly pertaining to the existence of degenerate stationary points, that hinders gradient methods. In order to ad

Aryanna Schiebelbein-Zwack, Maya Fishbach

The connection between the binary black hole (BBH) mergers observed by LIGO-Virgo-KAGRA (LVK) and their stellar progenitors remains uncertain. Specifically, the fraction $\epsilon$ of stellar mass that ends up in BBH mergers and the delay time $\tau$ between star formation and BBH merger carry information about the astrophysical processes that give rise to m

Weimin Lyu, Xiao Lin, Songzhu Zheng, Lu Pang

Textual backdoor attacks pose significant security threats. Current detection approaches, typically relying on intermediate feature representation or reconstructing potential triggers, are task-specific and less effective beyond sentence classification, struggling with tasks like question answering and named entity recognition. We introduce TABDet (Task-Agno

Jaskirat Singh, Emad Fallahzadeh, Bram Adams, Ahmed E. Hassan

Deciding what combination of operators to use across the Edge AI tiers to achieve specific latency and model performance requirements is an open question for MLOps engineers. This study aims to empirically assess the accuracy vs inference time trade-off of different black-box Edge AI deployment strategies, i.e., combinations of deployment operators and deplo

N. V. Lukashov

We generalize methods, developed by S. Ghilardi, and apply them to a subsystem J$_2$ of bimodal provability logic GLB. We describe projective formulas in J$_2$ in terms of Kripke semantics and prove that logic J$_2$ has finitary unification type. As an application, we show that admissibility problem for J$_2$ is decidable.

G. M. Ferguson, Hari P. Nair, Nathaniel J. Schreiber, Ludi Miao

We conduct local magnetic measurements on superconducting thin-film samples of Sr$\mathrm{_2}$RuO$\mathrm{_4}$ using scanning Superconducting Quantum Interference Device (SQUID) susceptometry. From the diamagnetic response, we extract the magnetic penetration depth, $\lambda$, which exhibits a quadratic temperature dependence at low temperatures. Although a

Bahram Mashhoon

The Rotational Doppler Effect (RDE) involves both the orbital angular momentum of electromagnetic radiation as well as its helicity. The RDE phenomena associated with photon helicity go beyond the standard theory of relativity. The purpose of this paper is to elucidate the theoretical basis of the helicity-dependent RDE in terms of the general phenomenon of

Slobodan N. Simić

We generalize the classical Frobenius integrability theorem to plane fields of class $C^Q$, a regularity class introduced by Reimann [Rei76] for vector fields in Euclidean spaces. A $C^Q$ vector field is uniquely integrable and its flow is a quasiconformal deformation. We show that an a.e. involutive $C^Q$ plane field (defined in a suitable way) in $\mathbb{

Martina Giachello, Francesco Scardino, Giacomo Gradenigo

We present here the first lattice simulation of symplectic quantization, a new functional approach to quantum field theory which allows to define an algorithm to numerically sample the quantum fluctuations of fields directly in Minkowski space-time, at variance with all other present approaches. Symplectic quantization is characterized by a Hamiltonian deter

Evgeny Skvortsov, Yihao Yin

Higher spin gravities do not have a low energy limit where higher-spin fields decouple from gravity. Nevertheless, it is possible to construct fine-tuned exact solutions that activate low-spin fields without sourcing the higher-spin fields. We show that BPST (Belavin-Polyakov-Schwartz-Tyupkin) instanton is an exact solution of Chiral Higher Spin Gravity, i.e

Leo Cazenille, Nicolas Lobato-Dauzier, Alessia Loi, Mika Ito

Swarm robotics promises adaptability to unknown situations and robustness against failures. However, it still struggles with global tasks that require understanding the broader context in which the robots operate, such as identifying the shape of the arena in which the robots are embedded. Biological swarms, such as shoals of fish, flocks of birds, and colon

Lingzi Hong, Pengcheng Luo, Eduardo Blanco, Xiaoying Song

Automatic counterspeech generation methods have been developed to assist efforts in combating hate speech. Existing research focuses on generating counterspeech with linguistic attributes such as being polite, informative, and intent-driven. However, the real impact of counterspeech in online environments is seldom considered. This study aims to develop meth

Dominique Eckert, Fabio Gastaldello, Ewan O'Sullivan, Alexis Finoguenov

The co-evolution between supermassive black holes and their environment is most directly traced by the hot atmospheres of dark matter halos. Cooling of the hot atmosphere supplies the central regions with fresh gas, igniting active galactic nuclei (AGN) with long duty cycles. Outflows from the central engine tightly couple with the surrounding gaseous medium

Hridoy Debnath, Pavel Fileviez Perez, Kevin Gonzalez-Quesada

We discuss a simple theory for neutrino masses where the total lepton number is a local gauge symmetry spontaneously broken below the multi-TeV scale. In this context, the neutrino masses are generated through the canonical seesaw mechanism and a Majorana dark matter candidate is predicted from anomaly cancellation. We discuss in great detail the dark matter

Alistair Plum, Tharindu Ranasinghe, Christoph Purschke

Relation extraction is essential for extracting and understanding biographical information in the context of digital humanities and related subjects. There is a growing interest in the community to build datasets capable of training machine learning models to extract relationships. However, annotating such datasets can be expensive and time-consuming, in add

Andrew Lamperski, Tyler Lekang

Neural networks are regularly employed in adaptive control of nonlinear systems and related methods of reinforcement learning. A common architecture uses a neural network with a single hidden layer (i.e. a shallow network), in which the weights and biases are fixed in advance and only the output layer is trained. While classical results show that there exist

Kailai Yang, Zhiwei Liu, Qianqian Xie, Jimin Huang

Recent advancements in large language models (LLMs) focus on aligning to heterogeneous human expectations and values via multi-objective preference alignment. However, existing methods are dependent on the policy model parameters, which require high-cost repetition of their alignment algorithms for each new policy model, and they cannot expand to unseen obje

Anna M. Seiler, Yaroslav Zhumagulov, Klaus Zollner, Chiho Yoon

Spin-orbit coupling (SOC) and electron-electron interaction can mutually influence each other and give rise to a plethora of intriguing phenomena in condensed matter systems. In pristine bilayer graphene, which has weak SOC, intrinsic Lifshitz transitions and concomitant van-Hove singularities lead to the emergence of many-body correlated phases. Layer-selec

Christian Ewerhart, Stanisław Kaźmierowski

Colonel Blotto games with discrete strategy spaces effectively illustrate the intricate nature of multidimensional strategic reasoning. This paper studies the equilibrium set of such games where, in line with prior experimental work, the tie-breaking rule is allowed to be flexible. We begin by pointing out that equilibrium constructions known from the litera

Stefano Gherardini, Gabriele De Chiara

In this tutorial, we present the definition, interpretation and properties of some of the main quasiprobabilities that can describe the statistics of measurement outcomes evaluated at two or more times. Such statistics incorporate the incompatibility of the measurement observables and the state of the measured quantum system. We particularly focus on Kirkwoo

Nilanjan Roy, Bo Peng, Bo Yang

We investigate the quantum Hall effect in a single Landau level in the presence of a square superlattice of $\delta$-function potentials. The interplay between the superlattice spacing $a_s$ and the magnetic length $\ell_B$ in clean system leads to three interesting characteristic regimes corresponding to $a_s \lt \ell_B$, $a_s \gg \ell_B$ and the intermedia

Zhaoyang Xiang, Victor Paredes, Guillermo A. Castillo, Ayonga Hereid

Traditional one-step preview planning algorithms for bipedal locomotion struggle to generate viable gaits when walking across terrains with restricted footholds, such as stepping stones. To overcome such limitations, this paper introduces a novel multi-step preview foot placement planning algorithm based on the step-to-step discrete evolution of the Divergen

Yumeng Yang, Ashley Gilliam, Ethan B Ludmir, Kirk Roberts

Clinical trials are pivotal in medical research, and NLP can enhance their success, with application in recruitment. This study aims to evaluate the generalizability of eligibility classification across a broad spectrum of clinical trials. Starting with phase 3 cancer trials, annotated with seven eligibility exclusions, then to determine how well models can

Islem Bouzenia, Premkumar Devanbu, Michael Pradel

Automated program repair has emerged as a powerful technique to mitigate the impact of software bugs on system reliability and user experience. This paper introduces RepairAgent, the first work to address the program repair challenge through an autonomous agent based on a large language model (LLM). Unlike existing deep learning-based approaches, which promp

Tony Feng, Adeel A. Khan

Higher theta series on moduli spaces of Hermitian shtukas were constructed by Feng--Yun--Zhang and conjectured to be modular, parallel to classical conjectures in the Kudla program. In this paper we prove the modularity of higher theta series after restriction to the generic locus. The proof is an upgrade, using motivic homotopy theory, of earlier work of Fe

Yuma Sugahara, Javier Álvarez-Márquez, Takuya Hashimoto, Luis Colina

We present JWST NIRCam imaging of B14-65666 ("Big Three Dragons"), a bright Lyman-break galaxy system ($M_\text{UV}=-22.5$ mag) at $z=7.15$. The high angular resolution of NIRCam reveals the complex morphology of two galaxy components: galaxy E has a compact core (E-core), surrounded by diffuse, extended, rest-frame optical emission, which is likely to be ti

Tatiana Krikella, Joel A. Dubin

Precision medicine is accelerating rapidly in the field of health research. This includes fitting predictive models for individual patients based on patient similarity in an attempt to improve model performance. We propose an algorithm which fits a personalized predictive model (PPM) using an optimal size of a similar subpopulation that jointly optimizes mod

Li-Wei Chen, Nils Thuerey

Effectively predicting transonic unsteady flow over an aerofoil poses inherent challenges. In this study, we harness the power of deep neural network (DNN) models using the attention U-Net architecture. Through efficient training of these models, we achieve the capability to capture the complexities of transonic and unsteady flow dynamics at high resolution,

Radu-Andrei Rosu, Mihaela-Elena Breaban, Henri Luchian

Dataset distillation aims at synthesizing a dataset by a small number of artificially generated data items, which, when used as training data, reproduce or approximate a machine learning (ML) model as if it were trained on the entire original dataset. Consequently, data distillation methods are usually tied to a specific ML algorithm. While recent literature

Boštjan Brešar, Michael A. Henning

A dominating set in a graph $G$ is a set $S$ of vertices such that every vertex in $V(G) \setminus S$ is adjacent to a vertex in $S$. A restrained dominating set of $G$ is a dominating set $S$ with the additional restraint that the graph $G - S$ obtained by removing all vertices in $S$ is isolate-free. The domination number $\gamma(G)$ and the restrained dom

Simon Kiefhaber, Simon Niklaus, Feng Liu, Simone Schaub-Meyer

Video frame interpolation, the task of synthesizing new frames in between two or more given ones, is becoming an increasingly popular research target. However, the current evaluation of frame interpolation techniques is not ideal. Due to the plethora of test datasets available and inconsistent computation of error metrics, a coherent and fair comparison acro

David Ardia, Sébastien Laurent, Rosnel Sessinou

We introduce a new framework for the mean-variance spanning (MVS) hypothesis testing. The procedure can be applied to any test-asset dimension and only requires stationary asset returns and the number of benchmark assets to be smaller than the number of time periods. It involves individually testing moment conditions using a robust Student-t statistic based

John Chambers

Protoplanetary disks are often assumed to change slowly and smoothly during planet formation. Here, we investigate the time evolution of isolated disks subject to viscosity and a disk wind. The viscosity is assumed to increase rapidly at around 900 K due to thermal ionization of alkali metals, or thermionic and ion emission from dust, and the onset of magnet

Georgios Chochlakis, Alexandros Potamianos, Kristina Lerman, Shrikanth Narayanan

In-context Learning (ICL) has emerged as a powerful paradigm for performing natural language tasks with Large Language Models (LLM) without updating the models' parameters, in contrast to the traditional gradient-based finetuning. The promise of ICL is that the LLM can adapt to perform the present task at a competitive or state-of-the-art level at a fraction

Yanwei Wang, Tsun-Hsuan Wang, Jiayuan Mao, Michael Hagenow

Grounding the common-sense reasoning of Large Language Models (LLMs) in physical domains remains a pivotal yet unsolved problem for embodied AI. Whereas prior works have focused on leveraging LLMs directly for planning in symbolic spaces, this work uses LLMs to guide the search of task structures and constraints implicit in multi-step demonstrations. Specifi

Jean-Luc Guermond, Matthias Maier, Eric Tovar

We introduce a high-order space-time approximation of the Shallow Water Equations with sources that is invariant-domain preserving (IDP) and well-balanced with respect to rest states. The employed time-stepping technique is a novel explicit Runge-Kutta (ERK) approach which is an extension of the class of ERK-IDP methods introduced by Ern and Guermond (SIAM J

Xiaodan Shao, Rui Zhang, Qijun Jiang, Robert Schober

Six-dimensional movable antenna (6DMA) is an effective approach to improve wireless network capacity by adjusting the 3D positions and 3D rotations of distributed antenna surfaces based on the users' spatial distribution and statistical channel information. Although continuously positioning/rotating 6DMA surfaces can achieve the greatest flexibility and thus

Jinming Li, Gongjun Xu, Ji Zhu

Factor analysis is a widely used statistical tool in many scientific disciplines, such as psychology, economics, and sociology. As observations linked by networks become increasingly common, incorporating network structures into factor analysis remains an open problem. In this paper, we focus on high-dimensional factor analysis involving network-connected ob

M. Masseroni, M. Gull, A. Panigrahi, N. Jacobsen

Van der Waals heterostructures provide a versatile platform for tailoring electronic properties through the integration of two-dimensional materials. Among these combinations, the interaction between bilayer graphene and transition metal dichalcogenides (TMDs) stands out due to its potential for inducing spin-orbit coupling (SOC) in graphene. Future devices

Seongjin Hong, Matthew A. Feldman, Claire E. Marvinney, Donghwa Lee

In recent years, distributed quantum sensing has gained interest for a range of applications requiring networks of sensors, from global-scale clock synchronization to high energy physics. In particular, a network of entangled sensors can improve not only the sensitivity beyond the shot noise limit, but also enable a Heisenberg scaling with the number of sens

Hui-Ke Jin, Johannes Knolle

Frustrated magnets can have accidental ground state degeneracies which may be lifted by various forms of disorder, for example in the form of thermal or quantum fluctuations. This order by disorder (ObD) paradigm is well established in equilibrium and here is generalized to Floquet many-body systems. Investigating a periodically-driven XXZ-compass model on t

Peter Zhang, Brent Logan, Michael Martens

In confirmatory clinical trials, survival outcomes are frequently studied and interim analyses for efficacy and/or futility are often desirable. Methods such as the log rank test and Cox regression model are commonly used to compare treatments in this setting. They rely on a proportional hazards (PH) assumption and are subject to type I error rate inflation

Caroline E. P. Robin, Gabriel Martínez-Pinedo

We compute $\beta$-decay half-lives of isotonic nuclear chains located at neutron shell closures $N=50$, $82$, $126$ and $184$, which are of particular importance for the $r$-process nucleosynthesis, and study the role of first-forbidden transitions in a framework that includes complex nucleonic correlations beyond the quasiparticle random phase approximatio

A. Ribes Metidieri, B. Bonga, B. Krishnan

It is generally believed that tidal deformations of a black hole in an external field, as measured using its gravitational field multipoles, vanish. However, this does not mean that the black hole horizon is not deformed. Here we shall discuss the deformations of a black hole horizon in the presence of an external field using a characteristic initial value f

E. Granado, C. W. Galdino, B. D. Moreno, G. King

Spin-state ordering - a periodic pattern of ions with different spin-state configurations along a crystal lattice - is a rare phenomenon, and its possible interrelation with other electronic degrees of freedom remains little explored. Here we perform a structural investigation of the mixed-valence Co homometallic ludwigite Co$_2^{2+}$Co$^{3+}$O$_2$BO$_3$. A

Nabeel Asharaf, Richard S. J. Tol

This study critically evaluates the impact of the Pradhan Mantri Ujjwala Yojana (PMUY) on LPG accessibility among poor households in India. Using Propensity Score Matching and Difference-in-Differences estimators and the National Family Health Survey (NFHS) dataset, the Average Treatment Effect on the interdedly Treated is a modest 2.1 percentage point incre

Max Potratzki, Timo Bröhl, Thorsten Rings, Klaus Lehnertz

We investigate topological and spectral properties of models of European and US-American power grids and of paradigmatic network models as well as their implications for the synchronization dynamics of phase oscillators with heterogeneous natural frequencies. We employ the complex-valued order parameter --~a widely-used indicator for phase ordering~-- to ass

Nuo Chen, Ya-Jun Pan

This paper proposes a vision-based framework for a 7-degree-of-freedom robotic manipulator, with the primary objective of facilitating its capacity to acquire information from human hand demonstrations for the execution of dexterous pick-and-place tasks. Most existing works only focus on the position demonstration without considering the orientations. In thi

Martin Rubey, Mei Yin

A parking function of length $n$ is a sequence $\pi=(\pi_1,\dots, \pi_n)$ of positive integers such that if $\lambda_1\leq\cdots\leq \lambda_n$ is the increasing rearrangement of $\pi_1,\dots,\pi_n$, then $\lambda_i\leq i$ for $1\leq i\leq n$. The index $i$ is a fixed point of the parking function $\pi$ if $\pi_i=i$. More generally, for $m\geq 1$, the indice

Daniel Dantchev, Nicholay Tonchev

Fluctuations exist in any material object $A$. If $A$ has non-zero temperature $T$, one speaks about thermal fluctuations. If $A$ is at very low $T$, the fluctuations are of quantum origin. Interesting effects appear if two bodies $A$ and $B$ are separated by a fluctuating medium $C$ (say a vacuum, or a fluid close to its {\it critical point}) when the fluct

Marko Djukanovic, Stefan Kapunac, Aleksandar Kartelj, Dragan Matic

This work focuses on developing an effective meta-heuristic approach to protect against simultaneous attacks on nodes of a network modeled using a graph. Specifically, we focus on the $k$-strong Roman domination problem, a generalization of the well-known Roman domination problem on graphs. This general problem is about assigning integer weights to nodes tha

Dominik Huber, Martin Schreiber, Martin Schulz, Howard Pritchard

With Dynamic Resource Management (DRM) the resources assigned to a job can be changed dynamically during its execution. From the system's perspective, DRM opens a new level of flexibility in resource allocation and job scheduling and therefore has the potential to improve system efficiency metrics such as the utilization rate, job throughput, energy efficien

Panpan Xu, Robin Jones, Georgios Sarris, Peter Huthwaite

Across non-destructive testing (NDT) and structural health monitoring (SHM), accurate knowledge of the systems' reliability for detecting defects, such as Probability of Detection (POD) analysis is essential to enabling widespread adoption. Traditionally this relies on access to extensive experimental data to cover all critical areas of the parametric space,

Eli Chien, Haoyu Wang, Ziang Chen, Pan Li

``The right to be forgotten'' ensured by laws for user data privacy becomes increasingly important. Machine unlearning aims to efficiently remove the effect of certain data points on the trained model parameters so that it can be approximately the same as if one retrains the model from scratch. We propose to leverage projected noisy stochastic gradient desce

Aviv Slobodkin, Eran Hirsch, Arie Cattan, Tal Schuster

Recent efforts to address hallucinations in Large Language Models (LLMs) have focused on attributed text generation, which supplements generated texts with citations of supporting sources for post-generation fact-checking and corrections. Yet, these citations often point to entire documents or paragraphs, burdening users with extensive verification work. In

Remy Sabathier, Niloy J. Mitra, David Novotny

We present a method to build animatable dog avatars from monocular videos. This is challenging as animals display a range of (unpredictable) non-rigid movements and have a variety of appearance details (e.g., fur, spots, tails). We develop an approach that links the video frames via a 4D solution that jointly solves for animal's pose variation, and its appea

Po-Han Huang, Shiqian Chen, Oliver Hartwig, David E. Marschner

Hierarchical structures are abundant in nature, such as in the superhydrophobic surfaces of lotus leaves and the structural coloration of butterfly wings. They consist of ordered features across multiple size scales, and their unique properties have attracted enormous interest in wide-ranging fields, including energy storage, nanofluidics, and nanophotonics.

Lenore Blum, Manuel Blum

We look at consciousness through the lens of Theoretical Computer Science, a branch of mathematics that studies computation under resource limitations, distinguishing functions that are efficiently computable from those that are not. From this perspective, we develop a formal machine model for consciousness. The model is inspired by Alan Turing's simple yet

Derek Driggs, Matthias J. Ehrhardt, Carola-Bibiane Schönlieb, Junqi Tang

The Condat-V\~u algorithm is a widely used primal-dual method for optimizing composite objectives of three functions. Several algorithms for optimizing composite objectives of two functions are special cases of Condat-V\~u, including proximal gradient descent (PGD). It is well-known that PGD exhibits suboptimal performance, and a simple adjustment to PGD can

Johannes F. Elfferich, Ebrahim Shahabi, Cosimo Della Santina, Dimitra Dodou

As global demand for fruits and vegetables continues to rise, the agricultural industry faces challenges in securing adequate labor. Robotic harvesting devices offer a promising solution to solve this issue. However, harvesting delicate fruits, notably blackberries, poses unique challenges due to their fragility. This study introduces and evaluates a prototy

Álvaro Muñiz-Brea

We consider a family of closed symplectic manifolds 4-manifolds which we call symplectic bielliptic surfaces and study its Lagrangian cobordism group of weakly-exact Lagrangian G-branes (that is, Lagrangians equipped with a grading, a Pin structure and a G-local system); relations come from Lagrangian cobordisms satisfying a tautologically unobstructedness-t

Noam Schiller, Tomer Alkalay, Changki Hong, Vladimir Umansky

The fractional quantum Hall (FQH) effect provides a paradigmatic example of a topological phase of matter. FQH edges are theoretically described via models belonging to the class of chiral Luttinger liquid (CLL) theories [1 (Wen, 2007)]. These theories predict exotic properties of the excitations, such as fractional charge and fractional statistics. Despite

Saikat Panja

Let $G$ be one of the finite general linear, unitary, symplectic or orthogonal groups over finite fields of odd order. We find the cardinality of the fibers of the square map at a given generic element. Using this we find the number of real conjugacy classes of $G$. This is primarily achieved by leveraging a recent solution to Brauer's problem 14.

David Ardia, Clément Aymard, Tolga Cenesizoglu

We reassess Boehmer et al. (2021, BJZZ)'s seminal work on the predictive power of retail order imbalance (ROI) for future stock returns. First, we replicate their 2010-2015 analysis in the more recent 2016-2021 period. We find that the ROI's predictive power weakens significantly. Specifically, past ROI can no longer predict weekly returns on large-cap stock

Beliz Gunel, James B. Wendt, Jing Xie, Yichao Zhou

Users often struggle with decision-making between two options (A vs B), as it usually requires time-consuming research across multiple web pages. We propose STRUM-LLM that addresses this challenge by generating attributed, structured, and helpful contrastive summaries that highlight key differences between the two options. STRUM-LLM identifies helpful contra

Yiming Xie, Henglu Wei, Zhenyi Liu, Xiaoyu Wang

To advance research in learning-based defogging algorithms, various synthetic fog datasets have been developed. However, existing datasets created using the Atmospheric Scattering Model (ASM) or real-time rendering engines often struggle to produce photo-realistic foggy images that accurately mimic the actual imaging process. This limitation hinders the effe

Ekramul Haque, Kamrul Hasan, Imtiaz Ahmed, Md. Sahabul Alam

In the dynamic and ever-changing domain of Unmanned Aerial Vehicles (UAVs), the utmost importance lies in guaranteeing resilient and lucid security measures. This study highlights the necessity of implementing a Zero Trust Architecture (ZTA) to enhance the security of unmanned aerial vehicles (UAVs), hence departing from conventional perimeter defences that

Yi-Chien Lin, Gangda Deng, Viktor Prasanna

Training a Graph Neural Network (GNN) model on large-scale graphs involves a high volume of data communication and computations. While state-of-the-art CPUs and GPUs feature high computing power, the Standard GNN training protocol adopted in existing GNN frameworks cannot efficiently utilize the platform resources. To this end, we propose a novel Unified CPU

Zeyu Jia, Alexander Rakhlin, Ayush Sekhari, Chen-Yu Wei

We revisit the problem of offline reinforcement learning with value function realizability but without Bellman completeness. Previous work by Xie and Jiang (2021) and Foster et al. (2022) left open the question whether a bounded concentrability coefficient along with trajectory-based offline data admits a polynomial sample complexity. In this work, we provid

Vida Dujmović, Pat Morin

A subset $S$ of vertices in a planar graph $G$ is a free set if, for every set $P$ of $|S|$ points in the plane, there exists a straight-line crossing-free drawing of $G$ in which vertices of $S$ are mapped to distinct points in $P$. In this survey, we review - several equivalent definitions of free sets, - results on the existence of large free sets in plan

Ben Wang

The advent of ChatGPT and similar large language models (LLMs) has revolutionized the human-AI interaction and information-seeking process. Leveraging LLMs as an alternative to search engines, users can now access summarized information tailored to their queries, significantly reducing the cognitive load associated with navigating vast information resources.

Le Ngoc Tram, Thiem Hoang, Helmut Wiesemeyer, Isabelle Ristorcelli

Dust grains are important in various astrophysical processes and serve as indicators of interstellar medium structures, density, and mass. Understanding their physical properties and chemical composition is crucial in astrophysics. Dust polarisation is a valuable tool for studying these properties. The Radiative Torque (RAT) paradigm, which includes Radiativ

Togo Jean Yves Kioye, Paul-Marie Grollemund, Jocelyn Chauvet, Pierre Druilhet

Variable selection methods are required in practical statistical modeling, to identify and include only the most relevant predictors, and then improving model interpretability. Such variable selection methods are typically employed in regression models, for instance in this article for the Poisson Log Normal model (PLN, Chiquet et al., 2021). This model aim

Leonardo Garcia-Garcia, Diego Lopez-Camara, Davide Lazzati

The merger of two magnetized compact objects, such as neutron stars, forms a compact object which may launch a relativistic and collimated jet. Numerical simulations of the process show that a dense and highly magnetized medium surrounds the system. This study presents a semi-analytical model that models the effects that a static magnetized medium with a tan

Bin Shen, Victoria A. Ginga, Angel M. Arévalo-López, Gaston Garbarino

Pressure evolution of the crystal structure and magnetism of the honeycomb $\alpha$-RuBr$_3$ is studied using high-pressure x-ray diffraction, magnetometry, and density-functional band-structure calculations. Hydrostatic compression transforms antiferromagnetic $\alpha$-RuBr$_3$ ($R\bar 3$) into paramagnetic $\alpha'$-RuBr$_3$ ($P\bar 1$) where short Ru-Ru b