July 2023 arXiv papers — page 84

Arya Thenapparambil, Graciely Elias dos Santos, Chang-An Li, Mohamed Abdelghany

Nonlinear planar magnetotransport is ubiquitous in topological HgTe structures, both in tensile (topological insulator) or compressively strained layers (Weyl semimetal phase). We show that the common reason for the nonlinear planar magnetotransport is the presence of tilted Dirac cones combined with the formation of charge puddles. The origin of the tilted

Miguel Sanz-Novo, Víctor M. Rivilla, Izaskun Jiménez-Serra, Jesús Martín-Pintado

After a quarter century since the detection of the last interstellar carboxylic acid, acetic acid (CH$_3$COOH), we report the discovery of a new one, the cis-trans form of carbonic acid (HOCOOH), toward the Galactic Center molecular cloud G+0.693-0.027. HOCOOH stands as the first interstellar molecule containing three oxygen atoms and also the third carboxyl

I. K. Kozlov

We study what Jordan-Kronecker invariants of Lie algebras, introduced by A. V. Bolsinov and P. Zhang, are possible. We completely solve this problem in the Jordan and the Kronecker cases. We prove that any JK invariants that contain the Kronecker $3 \times 3$ block or several Kronecker $1 \times 1$ blocks are possible. For other JK invariants, with Kronecker

Sandro Coriasco, Giovanni Girardi, N. Uday Kiran

We study a class of weakly hyperbolic Cauchy problems on $\mathbb{R}^d$, involving linear operators with characteristics of variable multiplicities, whose coefficients are unbounded in the space variable. The behaviour in the time variable is governed by a suitable "shape function". We develop a parameter-dependent symbolic calculus, corresponding to an appr

Xiao-Yu Li, Qin-Sheng Zhu, Yong Hu, Hao Wu

The Hidden Quantum Markov Model (HQMM) has significant potential for analyzing time-series data and studying stochastic processes in the quantum domain as an upgrading option with potential advantages over classical Markov models. In this paper, we introduced the split HQMM (SHQMM) for implementing the hidden quantum Markov process, utilizing the conditional

R. Kibbee, E. Prebys, V. Nagaslaev

The Mu2e Experiment has stringent beam structure requirements; namely, its proton bunches with a time structure of 1.7 $\mu$s in the Fermilab Delivery Ring. This beam structure will be delivered using the Fermilab 8-GeV Booster, the 8-GeV Recycler Ring, and the Delivery Ring. The 1.7-$\mu$s period of the Delivery Ring will generate the required beam structur

Roberta Volpe, Belle II Collaboration

We report on recent results obtained by the Belle II experiment related to searches for beyond-the-standard-model physics. The $B$ meson decay data sample used corresponds to an integrated luminosity of $L = 189$ fb$^{-1}$. In recent years, discrepancies from standard-model predictions, which suggest violation of lepton-flavor universality, have emerged in m

Ivan Carvalho, Ramon Lawrence

This work analyzes and parallelizes LearnedSort, the novel algorithm that sorts using machine learning models based on the cumulative distribution function. LearnedSort is analyzed under the lens of algorithms with predictions, and it is argued that LearnedSort is a learning-augmented SampleSort. A parallel LearnedSort algorithm is developed combining Learne

Zhaiyu Chen, Yilei Shi, Liangliang Nan, Zhitong Xiong

We present PolyGNN, a polyhedron-based graph neural network for 3D building reconstruction from point clouds. PolyGNN learns to assemble primitives obtained by polyhedral decomposition via graph node classification, achieving a watertight and compact reconstruction. To effectively represent arbitrary-shaped polyhedra in the neural network, we propose a skele

Erika S. Alcorta, Mahesh Madhav, Scott Tetrick, Neeraja J. Yadwadkar

Modern computer designs support composite prefetching, where multiple individual prefetcher components are used to target different memory access patterns. However, multiple prefetchers competing for resources can drastically hurt performance, especially in many-core systems where cache and other resources are shared and very limited. Prior work has proposed

Sergio J. Sciutto, Luis A. Anchordoqui, Carlos Garcia Canal, Felix Kling

We investigate the observed muon deficit in air shower simulations when compared to ultrahigh-energy cosmic ray (UHECR) data. Gleaned from the observed enhancement of strangeness production in ALICE data, the associated $\pi \leftrightarrow K$ swap is taken as a cornerstone to resolve the muon puzzle via its corresponding impact on the shower evolution. We d

Lester Sandles, Francesco D'Eugenio, Jakob M. Helton, Roberto Maiolino

We report the discovery of a quiescent galaxy at $z=2.34$ with a stellar mass of only $M_\star = 9.5^{+1.8}_{-1.2} \times 10^{8} \mathrm{M}_\odot$, based on deep JWST/NIRSpec spectroscopy. This is the least massive quiescent galaxy found so far at high redshift. We use a Bayesian approach to model the spectrum and photometry, and find the target to have been

Jory Sonneveld

After the successful installation and first operation of the new Inner Tracking System (ITS2), which consists of about 10 m$^2$ of monolithic silicon pixel sensors, ALICE is pioneering the usage of bent, wafer-scale pixel sensors for the ITS3 for Run 4 at the LHC in 2029. Sensors larger than typical reticle sizes can be produced using the technique of stitch

Xin Zhao, Heng Liu, Shiqi Gong, Xin Ju

Aiming at providing wireless communication systems with environment-perceptive capacity, emerging integrated sensing and communication (ISAC) technologies face multiple difficulties, especially in balancing the performance trade-off between the communication and radar functions. In this paper, we introduce a reconfigurable intelligent surface (RIS) to assist

Yanjie Xia, Shaochen Wang, Zhen Kan

Robot-assisted surgery has made great progress with the development of medical imaging and robotics technology. Medical scene understanding can greatly improve surgical performance while the semantic segmentation of the robotic instrument is a key enabling technology for robot-assisted surgery. However, how to locate an instrument's position and estimate the

Yongsheng Yu, Heng Fan, Libo Zhang

Recent video inpainting methods have made remarkable progress by utilizing explicit guidance, such as optical flow, to propagate cross-frame pixels. However, there are cases where cross-frame recurrence of the masked video is not available, resulting in a deficiency. In such situation, instead of borrowing pixels from other frames, the focus of the model shi

Darcy Camargo, Luigi Vigneri, Andrew Cullen

A significant portion of research on distributed ledgers has focused on circumventing the limitations of leader-based blockchains mainly in terms of scalability, decentralization and power consumption. Leaderless architectures based on directed acyclic graphs (DAGs) avoid many of these limitations altogether, but their increased flexibility and performance c

László Erdős, Hong Chang Ji

We consider the Brown measure of the free circular Brownian motion, $\boldsymbol{a}+\sqrt{t}\boldsymbol{x}$, with an arbitrary initial condition $\boldsymbol{a}$, i.e. $\boldsymbol{a}$ is a general non-normal operator and $\boldsymbol{x}$ is a circular element $*$-free from $\boldsymbol{a}$. We prove that, under a mild assumption on $\boldsymbol{a}$, the den

V. A. Khoze, M. G. Ryskin

We analyse the cross-section of events with Large Rapidity Gaps observed in proton-lead collisions by the CMS collaboration. The role of the transverse size of elementary $pN$ amplitude is discussed. We emphasize that the cross-section of incoming proton dissociation caused by the photon radiated off the lead ion is close to the value of $d\sigma/d\Delta\eta

Yutao Sun, Li Dong, Shaohan Huang, Shuming Ma

In this work, we propose Retentive Network (RetNet) as a foundation architecture for large language models, simultaneously achieving training parallelism, low-cost inference, and good performance. We theoretically derive the connection between recurrence and attention. Then we propose the retention mechanism for sequence modeling, which supports three comput

Do-Yup Kim, Chae-Bong Sohn, Hyun-Suk Lee

The separate receiver architecture with a time- or power-splitting mode, widely used for simultaneous wireless information and power transfer (SWIPT), has a major drawback: Energy-intensive local oscillators and mixers need to be installed in the information decoding (ID) component to downconvert radio frequency (RF) signals to baseband signals, resulting in

Frank X. Lee, Walter Wilcox, Andrei Alexandru, Chris Culver

Electromagnetic dipole polarizabilities are fundamental properties of a hadron that represent its resistance to deformation under external fields. For a charged hadron, the presence of acceleration and Landau levels complicates the isolation of its deformation energy in the conventional background field method. In this work, we explore a general method based

Eric Bersin, Madison Sutula, Yan Qi Huan, Aziza Suleymanzade

Practical quantum networks require interfacing quantum memories with existing channels and systems that operate in the telecom band. Here we demonstrate low-noise, bidirectional quantum frequency conversion that enables a solid-state quantum memory to directly interface with telecom-band systems. In particular, we demonstrate conversion of visible-band singl

Abdourahman Khaireh-Walieh, Denis Langevin, Pauline Bennet, Olivier Teytaud

Nanophotonic devices manipulate light at sub-wavelength scales, enabling tasks such as light concentration, routing, and filtering. Designing these devices is a challenging task. Traditionally, solving this problem has relied on computationally expensive, iterative methods. In recent years, deep learning techniques have emerged as promising tools for tacklin

Georgios Giannarakis, Ilias Tsoumas, Stelios Neophytides, Christiana Papoutsa

The concept of sustainable intensification in agriculture necessitates the implementation of management practices that prioritize sustainability without compromising productivity. However, the effects of such practices are known to depend on environmental conditions, and are therefore expected to change as a result of a changing climate. We study the impact

Rafael Ramos Tubino, Remy Cazabet, Natkamon Tovanich, Celine Robardet

We study the real economic activity in the Bitcoin blockchain that involves transactions from/to retail users rather than between organizations such as marketplaces, exchanges, or other services. We first introduce a heuristic method to classify Bitcoin players into three main categories: Frequent Receivers (FR), Neighbors of FR, and Others. We show that mos

Tim Rohwedder, Daile Osorio-Roig, Christian Rathgeb, Christoph Busch

Traditional minutiae-based fingerprint representations consist of a variable-length set of minutiae. This necessitates a more complex comparison causing the drawback of high computational cost in one-to-many comparison. Recently, deep neural networks have been proposed to extract fixed-length embeddings from fingerprints. In this paper, we explore to what ex

Mohammadsadegh Mohagheghi, Khayyam Salehi

Model checking has been proposed as a formal verification approach for analyzing computer-based and cyber-physical systems. The state space explosion problem is the main obstacle for applying this approach for sophisticated systems. Bisimulation minimization is a prominent method for reducing the number of states in a labeled transition system and is used to

Qijin Chen, Zhiqiang Wang, Rufus Boyack, K. Levin

In this paper we address the question of whether high-temperature superconductors have anything in common with BCS-BEC crossover theory. Towards this goal, we present a proposal and related predictions which provide a concrete test for the applicability of this theoretical framework. These predictions characterize the behavior of the Ginzburg-Landau coherenc

Yeong Gyun Kim, Kang Young Lee, Soo-hyeon Nam

We propose a novel approach for discovering a light dark photon in the forward experiments at the LHC, including the SND@LHC and the FASER experiments. Assuming the dark photon is lighter than twice the electron mass and feebly interacts with ordinary matter, it is long-lived enough to pass through 100 m of rock in front of the forward experiments and also t

Ziwei Su, Raghu Pasupathy, Yingchieh Yeh, Peter W. Glynn

We propose a general purpose confidence interval procedure (CIP) for statistical functionals constructed using data from a stationary time series. The procedures we propose are based on derived distribution-free analogues of the $\chi^2$ and Student's $t$ random variables for the statistical functional context, and hence apply in a wide variety of settings i

Thomas Bartz-Beielstein

This document provides a comprehensive guide to hyperparameter tuning using spotPython for scikit-learn, PyTorch, and river. The first part introduces spotPython's surrogate model-based optimization process, while the second part focuses on hyperparameter tuning. Several case studies are presented, including hyperparameter tuning for sklearn models such as S

William Soyars, Tomasz Banaszkiewicz, Ram Dhuley

The Proton Improvement Plan-II (PIP-II) is a superconducting linear accelerator being built at Fermilab that will provide 800 MeV proton beam for neutrino production. The linac consists of a total of twenty-three (23) cryomodules of five (5) different types. Cooling is required at 2K, 5K and 40K. The Cryogenic Distribution System (CDS) consists of a Distribu

Takehiko Gappo, Sandra Müller, Grigor Sargsyan

Based on earlier work of the third author, we construct a Chang-type model with supercompact measures extending a derived model of a given hod mouse with a regular cardinal $\delta$ that is both a limit of Woodin cardinals and a limit of ${<}\delta$-strong cardinals. The existence of such a hod mouse is consistent relative to a Woodin cardinal that is a limi

Ahmed Murtada, Bhavani Shankar Mysore Rama Rao, Udo Schroeder

The ability of widely distributed radar systems to capture diverse spatial scattering properties substantially improves radar imaging performance. Traditional imaging methods leverage regularized optimization techniques to reconstruct sparse images from local sensors and later combine them to create a global image. Alternatively, we proposed in an earlier wo

Idrissa Ba, Mohamed Elhamdadi

This paper gives a new way of characterizing L-space $3$-manifolds by using orderability of quandles. Hence, this answers a question of Adam Clay et al. [Question 1.1 of Canad. Math. Bull. 59 (2016), no. 3, 472-482]. We also investigate both the orderability and circular orderability of dynamical extensions of orderable quandles. We give conditions under whi

Rituparna Ghosh

This paper gives the relation between quasi completely inverse semirings and strongly additively quasi completely inverse semirings and generates the necessary and sufficient conditions for a strongly additively quasi completely inverse semiring to be a strong b-lattice of quasi skew-rings.

Lina C. Jaurigue, Kathy Lüdge

Task specific hyperparameter tuning in reservoir computing is an open issue, and is of particular relevance for hardware implemented reservoirs. We investigate the influence of directly including externally controllable task specific timescales on the performance and hyperparameter sensitivity of reservoir computing approaches. We show that the need for hype

Spyros Basilakos, Dimitri V. Nanopoulos, Theodoros Papanikolaou, Emmanuel N. Saridakis

In this Letter, we derive for the first time a characteristic three-peaked GW signal within the framework of no-scale Supergravity, being the low-energy limit of Superstring theory. We concentrate on the primordial gravitational wave (GW) spectrum induced due to second-order gravitational interactions by inflationary curvature perturbations as well as by iso

Jory Sonneveld

The CERN RD50 collaboration develops depleted monolithic active pixel CMOS sensors for future colliders with the aim of high radiation tolerance, good time resolution, and high granularity pixel detectors. The most recent prototype, the RD50-MPW3, is a 150 nm High Voltage CMOS LFoundry chip that features pixels with a 62 $\mu$m pitch that integrate both digi

Han-Chuan Kou, Peng Li

According to the Kibble-Zurek mechanism, there is a universal power-law relationship between the defect density and the quench rate during a slow linear quench through a critical point. It is generally accepted that a fast quench results in a deviation from the Kibble-Zurek scaling law and leads to the formation of a saturated plateau in the defect density.

Shawn L. Beaulieu, Sam Kriegman

Embodiment has recently enjoyed renewed consideration as a means to amplify the faculties of smart machines. Proponents of embodiment seem to imply that optimizing for movement in physical space promotes something more than the acquisition of niche capabilities for solving problems in physical space. However, there is nothing in principle which should so dis

Yui Iioka, Yu Yoshida, Yuiga Wada, Shumpei Hatanaka

In this study, we aim to develop a model that comprehends a natural language instruction (e.g., "Go to the living room and get the nearest pillow to the radio art on the wall") and generates a segmentation mask for the target everyday object. The task is challenging because it requires (1) the understanding of the referring expressions for multiple objects i

Ueli M. Angst, Emanuele Rossi, Carolina Boschmann Käthler, David Mannes

The steel-concrete interface (SCI) is known to play a major role in corrosion of steel in concrete, but a fundamental understanding is still lacking. One reason is that concrete's opacity complicates the study of internal processes. Here, we report on the application of bimodal X-ray and neutron microtomography as in-situ imaging techniques to elucidate the

Jayoon Jang, Emmanuel Candès

It is well known that it is impossible to construct useful confidence intervals (CIs) about the mean or median of a response $Y$ conditional on features $X = x$ without making strong assumptions about the joint distribution of $X$ and $Y$. This paper introduces a new framework for reasoning about problems of this kind by casting the conditional problem at di

C. Allaire, R. Ammendola, E. -C. Aschenauer, M. Balandat

The Electron-Ion Collider (EIC), a state-of-the-art facility for studying the strong force, is expected to begin commissioning its first experiments in 2028. This is an opportune time for artificial intelligence (AI) to be included from the start at this facility and in all phases that lead up to the experiments. The second annual workshop organized by the A

Ilan Doron-Arad, Hadas Shachnai

We consider the classic budgeted maximum weight independent set (BMWIS) problem. The input is a graph $G = (V,E)$, a weight function $w:V \rightarrow \mathbb{R}_{\geq 0}$, a cost function $c:V \rightarrow \mathbb{R}_{\geq 0}$, and a budget $B \in \mathbb{R}_{\geq 0}$. The goal is to find an independent set $S \subseteq V$ in $G$ such that $\sum_{v \in S} c(v

Adam Piróg, Halina Kwaśnicka

Despite tremendous advancements in Artificial Intelligence, learning from large sets of data in an unsupervised manner remains a significant challenge. Classical clustering algorithms often fail to discover complex dependencies in large datasets, especially considering sparse, high-dimensional spaces. However, deep learning techniques proved to be successful

Ayodeji O. Abioye, Mohammad Naiseh, William Hunt, Jediah Clark

Despite the advantages of having robot swarms, human supervision is required for real-world applications. The performance of the human-swarm system depends on several factors including the data availability for the human operators. In this paper, we study the human factors aspect of the human-swarm interaction and investigate how having access to high-qualit

Jérôme Sol, Hugo Prod'homme, Luc Le Magoarou, Philipp del Hougne

The reconfigurability of radio environments with programmable metasurfaces is considered a key feature of next-generation wireless networks. Identifying suitable metasurface configurations for desired wireless functionalities requires a precise setting-specific understanding of the intricate impact of the metasurface configuration on the wireless channels. Y

Kinga Skorupska, Maciej Grzeszczuk, Anna Jaskulska, Monika Kornacka

Alpha-XR Mission conducted by XR Lab PJAIT focused on research related to individual and crew well-being and participatory team collaboration in ICE (isolated, confined and extreme) conditions. In this two-week mission within an analog space habitat, collaboration, objective execution and leisure was facilitated and studied by virtual reality (VR) tools. The

S. Juillard, V. Christiaens, O. Absil

Recent observations have shown that protoplanetary disks around young stars can embed a wide variety of features. Raw disk images produced by high-contrast imaging instruments are corrupted by slowly varying residual stellar light in the form of quasi-static speckles. Hence, image processing is required to remove speckles from images and to recover circumste

Ashkan Ganj, Yiqin Zhao, Federico Galbiati, Tian Guo

To understand how well a proposed augmented reality (AR) solution works, existing papers often conducted tailored and isolated evaluations for specific AR tasks, e.g., depth or lighting estimation, and compared them to easy-to-setup baselines, either using datasets or resorting to time-consuming data capturing. Conceptually simple, it can be extremely diffic

Yang Liu, Yuexian Hou

Syntax has been proven to be remarkably effective in neural machine translation (NMT). Previous models obtained syntax information from syntactic parsing tools and integrated it into NMT models to improve translation performance. In this work, we propose a method to incorporate syntax information into a complex-valued Encoder-Decoder architecture. The propos

Sudipta Banerjee, Govind Mittal, Ameya Joshi, Chinmay Hegde

The performance of automated face recognition systems is inevitably impacted by the facial aging process. However, high quality datasets of individuals collected over several years are typically small in scale. In this work, we propose, train, and validate the use of latent text-to-image diffusion models for synthetically aging and de-aging face images. Our

Luc Dessart, W. V. Jacobson-Galán

A large fraction of red-supergiant stars seem to be enshrouded by circumstellar material (CSM) at the time of explosion. Relative to explosions in a vacuum, this CSM causes both a luminosity boost at early times as well as the presence of symmetric emission lines with a narrow core and electron-scattering wings typical of type IIn supernovae (SNe). For this

Zi-Xiang Yang, Zi-Qi Zeng, Ying Tian, Shun Wang

Entangled qudits, the high-dimensional entangled states, play an important role in the study of quantum information. How to prepare entangled qudits in an efficient and easy-to-operate manner is still a challenge in quantum technology. Here, we demonstrate a method to engineer frequency entangled qudits in a spontaneous parametric downconversion process. The

Yang Zhao, Zhijie Lin, Daquan Zhou, Zilong Huang

LLMs have demonstrated remarkable abilities at interacting with humans through language, especially with the usage of instruction-following data. Recent advancements in LLMs, such as MiniGPT-4, LLaVA, and X-LLM, further enlarge their abilities by incorporating multi-modal inputs, including image, video, and speech. Despite their effectiveness at generating p

Samir Datta, Asif Khan, Anish Mukherjee

Planar Embedding is a drawing of a graph on the plane such that the edges do not intersect each other except at the vertices. We know that testing the planarity of a graph and computing its embedding (if it exists), can efficiently be computed, both sequentially [HT] and in parallel [RR94], when the entire graph is presented as input. In the dynamic setting,

Joshua R. Minot, Marc Maier, Bradford Demarest, Nicholas Cheney

Over the past decade, the gender pay gap has remained steady with women earning 84 cents for every dollar earned by men on average. Many studies explain this gap through demand-side bias in the labor market represented through employers' job postings. However, few studies analyze potential bias from the worker supply-side. Here, we analyze the language in mi

Weifeng Lin, Ziheng Wu, Jiayu Chen, Jun Huang

This paper presents a new vision Transformer, Scale-Aware Modulation Transformer (SMT), that can handle various downstream tasks efficiently by combining the convolutional network and vision Transformer. The proposed Scale-Aware Modulation (SAM) in the SMT includes two primary novel designs. Firstly, we introduce the Multi-Head Mixed Convolution (MHMC) modul

Anjana Uday, Gertjan Lippertz, Kristof Moors, Henry F. Legg

Inducing Cooper pairing in a thin ferromagnetic topological insulator in the quantum anomalous Hall state (called quantum anomalous Hall insulator, QAHI) is a promising way to realize topological superconductivity with associated chiral Majorana edge states. However, finding evidence of superconducting proximity effect in a QAHI has proven to be a considerab

Sijin Cai, Nanfeng Zhang, Jiaying Zhu, Yanjie Liu

Background: Depression is a common mental disorder with societal and economic burden. Current diagnosis relies on self-reports and assessment scales, which have reliability issues. Objective approaches are needed for diagnosing depression. Objective: Evaluate the potential of GPT technology in diagnosing depression. Assess its ability to simulate individuals

Nicolas Aragon, Loïc Bidoux, Jesús-Javier Chi-Domínguez, Thibauld Feneuil

We exploit the idea of [Fen22] which proposes to build an efficient signature scheme based on a zero-knowledge proof of knowledge of a solution of a MinRank instance. The scheme uses the MPCitH paradigm, which is an efficient way to build ZK proofs. We combine this idea with another idea, the hypercube technique introduced in [AMGH+22], which leads to more e

Jun Nie, Danyang Xiao, Lei Yang, Weigang Wu

Data heterogeneity across clients is one of the key challenges in Federated Learning (FL), which may slow down the global model convergence and even weaken global model performance. Most existing approaches tackle the heterogeneity by constraining local model updates through reference to global information provided by the server. This can alleviate the perfo

D. Trabert, A. Geyer, N. Anders, M. Hofmann

We study strong field ionization of molecular hydrogen in highly intense co-rotating two-color (CoRTC) laser fields. The measured electron momentum distributions show alternating half-rings (AHR) that are characteristic for sub-cycle interference. We report on the role of the two-color field ratio for the visibility of this sub-cycle interference. The ratio

Luis Pedro Silvestrin, Shujian Yu, Mark Hoogendoorn

Coping with distributional shifts is an important part of transfer learning methods in order to perform well in real-life tasks. However, most of the existing approaches in this area either focus on an ideal scenario in which the data does not contain noises or employ a complicated training paradigm or model design to deal with distributional shifts. In this

Julius Rauscher, Raphael Buchmüller, Daniel A. Keim, Matthias Miller

Optimal ski route selection is a challenge based on a multitude of factors, such as the steepness, compass direction, or crowdedness. The personal preferences of every skier towards these factors require individual adaptations, which aggravate this task. Current approaches within this domain do not combine automated routing capabilities with user preferences

Pei-Ming Ho, Hikaru Kawai, Henry Liao, Yuki Yokokura

We study the interior metric of 4D spherically symmetric static black holes by using the semi-classical Einstein equation and find a consistent class of geometries with large curvatures. We approximate the matter fields by conformal fields and consider the contribution of the 4D Weyl anomaly, giving a state-independent constraint. Combining this with an equa

Karthik Soma, Vivek Shankar Vardharajan, Heiko Hamann, Giovanni Beltrame

One of the most important promises of decentralized systems is scalability, which is often assumed to be present in robot swarm systems without being contested. Simple limitations, such as movement congestion and communication conflicts, can drastically affect scalability. In this work, we study the effects of congestion in a binary collective decision-makin

ATLAS Collaboration

A search is performed for a heavy particle decaying into different-flavour, dilepton final states, using 139 $\mathrm{fb}^{-1}$ of proton-proton collision data at $\sqrt{s}=13$ TeV collected in 2015-2018 by the ATLAS detector at the Large Hadron Collider. Final states with electrons, muons and hadronically decaying tau leptons are considered ($e\mu$, $e\tau$

Jason Kaye, Zhen Huang, Hugo U. R. Strand, Denis Golež

We present a deterministic algorithm for the efficient evaluation of imaginary time diagrams based on the recently introduced discrete Lehmann representation (DLR) of imaginary time Green's functions. In addition to the efficient discretization of diagrammatic integrals afforded by its approximation properties, the DLR basis is separable in imaginary time, a

Raj Dahya

We generalise a technique of Bhat and Skeide (2015) to interpolate commuting families $\{S_{i}\}_{i \in \mathcal{I}}$ of contractions on a Hilbert space $\mathcal{H}$, to commuting families $\{T_{i}\}_{i \in \mathcal{I}}$ of contractive $\mathcal{C}_{0}$-semigroups on $L^{2}(\prod_{i \in \mathcal{I}}\mathbb{T}) \otimes \mathcal{H}$. As an excursus, we provid

Andrea Baronchelli

As Artificial Intelligence (AI) becomes increasingly integrated into our lives, the need for new norms is urgent. However, AI evolves at a much faster pace than the characteristic time of norm formation, posing an unprecedented challenge to our societies. This paper examines possible criticalities of the processes of norm formation surrounding AI. Thus, it f

Akshay Mehra, Yunbei Zhang, Bhavya Kailkhura, Jihun Hamm

Achieving high accuracy on data from domains unseen during training is a fundamental challenge in domain generalization (DG). While state-of-the-art DG classifiers have demonstrated impressive performance across various tasks, they have shown a bias towards domain-dependent information, such as image styles, rather than domain-invariant information, such as

Christophe Grojean, Jonathan Kley, Chang-Yuan Yao

Axions and axion-like particles (ALPs) are ubiquitous in popular attempts to solve supercalifragilisticexpialidocious puzzles of Nature. A widespread and vivid experimental programme spanning a vast range of mass scales and decades of couplings strives to find evidence for these elusive but theoretically well-motivated particles. In the absence of clear guid

Olivier Leblanc, Matthias Hofer, Siddharth Sivankutty, Hervé Rigneault

Lensless illumination single-pixel imaging with a multicore fiber (MCF) is a computational imaging technique that enables potential endoscopic observations of biological samples at cellular scale. In this work, we show that this technique is tantamount to collecting multiple symmetric rank-one projections (SROP) of a Hermitian \emph{interferometric} matrix -

Moshe Cohen, Abigail DiNardo, Adam M. Lowrance, Steven Raanes

The average genus of a 2-bridge knot with crossing number $c$ approaches $\frac{c}{4} + \frac{1}{12}$ as $c$ approaches infinity, as proven by Suzuki and Tran and independently Cohen and Lowrance. In this paper, for the genera of $2$-bridge knots of a fixed crossing number $c$, we show that the median and mode are both $\lfloor \frac{c+2}{4} \rfloor$ and tha

Alexander V. Kochin

The general circulation of the atmosphere determines the long-term variability of weather processes. This circulation is driven by the temperature differences between the poles and the equator, causing air to move along the Earth's surface. However, this requires enhanced pressure at the poles, which is not observed. To sustain the circulation, an additional

Yugang Zhang

We prove the existence of a gap around zero for canonical height functions associated to endomorphisms of projective spaces defined over complex function fields. We also prove that if the rational points of height zero are Zariski dense, then the endomorphism is birationally isotrivial. As a corollary, by a result of S. Cantat and J. Xie, we have a geometric

Ilaria Pallecchi, Elena Stellino, Paolo Postorino, Akira Iyo

The iron-based pnictide LaFe2As2 is not superconducting as-synthesized, but it becomes such below Tc around 12 K upon annealing, as a consequence of a structural transition from a phase with collapsed tetragonal crystal structure to an uncollapsed phase. In this work, we carry out specific heat, Raman spectroscopy and normal state electric and thermoelectric

Matthias Körschens, Solveig Franziska Bucher, Christine Römermann, Joachim Denzler

The plant community composition is an essential indicator of environmental changes and is, for this reason, usually analyzed in ecological field studies in terms of the so-called plant cover. The manual acquisition of this kind of data is time-consuming, laborious, and prone to human error. Automated camera systems can collect high-resolution images of the s

Loïc Bidoux, Jesús-Javier Chi-Domínguez, Thibauld Feneuil, Philippe Gaborit

We present a signature scheme based on the Syndrome-Decoding problem in rank metric. It is a construction from multi-party computation (MPC), using a MPC protocol which is a slight improvement of the linearized-polynomial protocol used in [Fen22], allowing to obtain a zero-knowledge proof thanks to the MPCitH paradigm. We design two different zero-knowledge

Fei Xia, Kyungduk Kim, Yaniv Eliezer, SeungYun Han

Optical information processing and computing can potentially offer enhanced performance, scalability and energy efficiency. However, achieving nonlinearity-a critical component of computation-remains challenging in the optical domain. Here we introduce a design that leverages a multiple-scattering cavity to passively induce optical nonlinear random mapping w

Roweno J. R. K. Heijmans

Strategic uncertainty complicates policy design in coordination games. To rein in strategic uncertainty, the Planner in this paper connects the problem of policy design to that of equilibrium selection. We characterize the subsidy scheme that induces coordination on a given outcome of the game as its unique equilibrium. Optimal subsidies are unique, symmetri

Shangqing Tong, Peng Ge, Yanan Jiao, Zhaofu Ma

Colorectal cancer is a deadly disease that has become increasingly prevalent in recent years. Early detection is crucial for saving lives, but traditional diagnostic methods such as colonoscopy and biopsy have limitations. Colonoscopy cannot provide detailed information within the tissues affected by cancer, while biopsy involves tissue removal, which can be

Kristóf Bérczi, Karthekeyan Chandrasekaran, Tamás Király, Shubhang Kulkarni

The splitting-off operation in undirected graphs is a fundamental reduction operation that detaches all edges incident to a given vertex and adds new edges between the neighbors of that vertex while preserving their degrees. Lov\'asz (1974) and Mader (1978) showed the existence of this operation while preserving global and local connectivities respectively i

Claudia Anedda, Fabrizio Cuccu

Let $\Omega\subset\mathbb{R}^N$, $N\geq 1$, be an open bounded connected set. We consider the indefinite weighted eigenvalue problem $-\Delta u =\lambda m u$ in $\Omega$ with $\lambda \in \mathbb{R}$, $m\in L^\infty(\Omega)$ and with homogeneous Neumann boundary conditions. We study weak* continuity, convexity and G\^ateaux differentiability of the map $m\ma

Kshitij Chavan, Pratik Dabhade, D. J. Saikia

The excellent sensitivity and optimum resolution of LoTSS DR2 at 144 MHz has enabled us to discover a giant radio galaxy (J1225+4011) with three distinct episodes of jet activity, making it a member of a class of objects called triple-double radio galaxies (TDRGs). The source extends overall up to 1.35 Mpc in projected size, with the second episode extending

Shyam Balaji, Guillem Domènech, Gabriele Franciolini

Pulsar timing arrays gathered evidence of the presence of a gravitational wave background around nHz frequencies. If the gravitational wave background was induced by large and Gaussian primordial fluctuations, they would then produce too many sub-solar mass primordial black holes. We show that if at the time of gravitational wave generation the universe was

Christoph Sendner, Jasper Stang, Alexandra Dmitrienko, Raveen Wijewickrama

The Tor network is the most prominent system for providing anonymous communication to web users, with a daily user base of 2 million users. However, since its inception, it has been constantly targeted by various traffic fingerprinting and correlation attacks aiming at deanonymizing its users. A critical requirement for these attacks is to attract as much us

Christoph Sendner, Ruisi Zhang, Alexander Hefter, Alexandra Dmitrienko

Due to the immutable and decentralized nature of Ethereum (ETH) platform, smart contracts are prone to security risks that can result in financial loss. While existing machine learning-based vulnerability detection algorithms achieve high accuracy at the contract level, they require developers to manually inspect source code to locate bugs. To this end, we p

Weidong Mei, Zhi Chen, Rui Zhang

Intelligent reflecting surface (IRS) can be densely deployed in complex environments to create cascaded line-of-sight (LoS) links between base stations (BSs) and users, which significantly enhance the signal coverage. In this paper, we consider the wireless power transfer (WPT) from a multi-antenna BS to multiple energy users (EUs) by exploiting the signal b

Alexander Hefter, Christoph Sendner, Alexandra Dmitrienko

In the digitized world, smartphones and their apps play an important role. To name just a few examples, some apps offer possibilities for entertainment, others for online banking, and others offer support for two-factor authentication. Therefore, with smartphones also, sensitive information is shared; thus, they are a desirable target for malware. The follow

Zheng-Liang Liang, Ping Zhang

In recent years, the importance of the electronic in-medium effect in the sub-GeV dark matter (DM) direct detection has been recognized and a coherent formulation of the DM-electron scattering based the linear response theory has been well established in the literature. In this paper, we apply the formulation to the scattering between DM particles and solar

Roberto Mottola, Gianni Buser, Philipp Treutlein

We report spectroscopy experiments of rubidium vapor in a high magnetic field under conditions of electromagnetically induced transparency (EIT) and optical pumping. The 1.1 T static magnetic field decouples nuclear and electronic spins and shifts each magnetic state via the Zeeman effect, allowing us to resolve individual optical transitions of the D$_2$ li

Guandu Liu, Yukang Ding, Mading Li, Ming Sun

Look-up table(LUT)-based methods have shown the great efficacy in single image super-resolution (SR) task. However, previous methods ignore the essential reason of restricted receptive field (RF) size in LUT, which is caused by the interaction of space and channel features in vanilla convolution. They can only increase the RF at the cost of linearly increasi

Mike Kosek, Benedikt Spies, Jörg Ott

While the evolution of the Internet was driven by the end-to-end model, it has been challenged by many flavors of middleboxes over the decades. Yet, the basic idea is still fundamental: reliability and security are usually realized end-to-end, where the strong trend towards ubiquitous traffic protection supports this notion. However, reasons to break up, or

Giulio Principi, Peter P. Wakker, Ruodu Wang

Comonotonicity (``same variation'') of random variables minimizes hedging possibilities and has been widely used, e.g., in Gilboa and Schmeidler's ambiguity models. This paper investigates anticomonotonicity (``opposite variation''; abbreviated ``AC''), the natural counterpart to comonotonicity. It minimizes leveraging rather than hedging possibilities. Surp

Wanying Zhao, Siyi Guo, Kristina Lerman, Yong-Yeol Ahn

Narrative is a foundation of human cognition and decision making. Because narratives play a crucial role in societal discourses and spread of misinformation and because of the pervasive use of social media, the narrative dynamics on social media can have profound societal impact. Yet, systematic and computational understanding of online narratives faces crit