December 2023 arXiv papers — page 55

Mateusz Wilinski, Andrey Y. Lokhov

Recent years have seen a lot of progress in algorithms for learning parameters of spreading dynamics from both full and partial data. Some of the remaining challenges include model selection under the scenarios of unknown network structure, noisy data, missing observations in time, as well as an efficient incorporation of prior information to minimize the nu

Anthony Man, Mohammad Jadidi, Amir Keshmiri, Hujun Yin

Recent growing interest in using machine learning for turbulence modelling has led to many proposed data-driven turbulence models in the literature. However, most of these models have not been developed with overcoming non-unique mapping (NUM) in mind, which is a significant source of training and prediction error. Only NUM caused by one-dimensional channel

Xidong Mu, Jiaqi Xu, Yuanwei Liu, Lajos Hanzo

Reconfigurable intelligent surface (RIS)-aided near-field communications is investigated. First, the necessity of investigating RIS-aided near-field communications and the advantages brought about by the unique spherical-wave-based near-field propagation are discussed. Then, the family of patch-array-based RISs and metasurface-based RISs are introduced along

Anna Jenčová, Sylvia Pulmannová

For convex and sequential effect algebras, we study spectrality in the sense of Foulis. We show that under additional conditions (strong archimedeanity, closedness in norm and a certain monotonicity property of the sequential product), such effect algebra is spectral if and only if every maximal commutative subalgebra is monotone $\sigma$-complete. Two previ

Lou Guérin, Cédric Flageul, Laurent Cordier, Stéphane Grieu

This work investigates spanwise wall oscillation (SWO) as a method to preferentially enhance heat transfer over drag in turbulent channel flow. Direct numerical simulations at $Re_\tau=180$ and $\Pr=1$ show set of wall-oscillation parameters reducing drag also decrease heat transfer similarly, maintaining coupled transport. However, large period ($T^+=500$)

Suriyaprasanth Shanmugasundaram, Rounak Agrawal, Dhanoj Gupta

We theoretically calculate the electron impact partial and total ionization cross sections of R-carvone $(\mathrm{C_{10}H_{14}O})$, 2-butanol $(\mathrm{C_{4}H_{10}O})$, imidazole $(\mathrm{C_3H_4N_2})$ and 2-nitroimidazole $(\mathrm{C_3H_3N_3O_2})$. We have used the Binary Encounter Bethe (BEB) model to obtain the total electron impact ionization cross secti

Alireza Amirshahi, Giovanni Ansaloni, David Atienza

The increasing complexity of transformer models in artificial intelligence expands their computational costs, memory usage, and energy consumption. Hardware acceleration tackles the ensuing challenges by designing processors and accelerators tailored for transformer models, supporting their computation hotspots with high efficiency. However, memory bandwidth

Jiaxi Cui, Liuzhenghao Lv, Jing Wen, Rongsheng Wang

We present a novel approach for integrating Myers-Briggs Type Indicator (MBTI) personality traits into large language models (LLMs), addressing the challenges of personality consistency in personalized AI. Our method, "Machine Mindset," involves a two-phase fine-tuning and Direct Preference Optimization (DPO) to embed MBTI traits into LLMs. This approach ens

Konrad Waldorf

We provide a concise and accessible introduction to (geometric) string structures, highlighting their connection to loop spaces and outlining relationships with neighboring topics.

Ran Gao, Zhengxiang Li, Kai Liao, He Gao

Ultralight axion or axionlike particles are one of the most promising candidates for dark matter because they are a well-motivated solution for the theoretical strong $CP$ problem and observational issues on small scales, i.e. the core-cusp problem and the satellite problem. A tiny coupling of axions and photons induces birefringence. We propose the differen

Jack R. C. King, Steven J. Lind

The accurate and stable simulation of viscoelastic flows remains a significant computational challenge, exacerbated for flows in non-trivial and practical geometries. Here we present a new high-order meshless approach with variable resolution for the solution of viscoelastic flows across a range of Weissenberg numbers. Based on the Local Anisotropic Basis Fu

Bruno Arcanjo, Bruno Ferrarini, Maria Fasli, Michael Milford

Visual place recognition (VPR) enables autonomous systems to localize themselves within an environment using image information. While VPR techniques built upon a Convolutional Neural Network (CNN) backbone dominate state-of-the-art VPR performance, their high computational requirements make them unsuitable for platforms equipped with low-end hardware. Recent

Mponeng Kopana, Sheean Jolicoeur, Roy Maartens

The fluctuations generated by Inflation are nearly Gaussian in the simplest models, but may be non-Gaussian in more complex models, potentially leading to signatures in the late Universe. In particular, local type primordial non-Gaussianity induces scale-dependent bias in tracers of the matter distribution. This non-Gaussian imprint in the tracer power spect

Pit Duwentäster, Vadim Guzey, Ilkka Helenius, Hannu Paukkunen

We present numerical studies of the leading non-linear corrections to the Dokshitzer-Gribov-Lipatov-Altarelli-Parisi evolution equations of parton distribution functions (PDFs) resulting from gluon recombination. The effect of these corrections is to reduce the pace of evolution at small momentum fractions $x$, while slightly increasing it at intermediate $x

Jacob S. Christiansen, Benjamin Eichinger, Olof Rubin

This article examines the asymptotic behavior of the Widom factors, denoted $\mathcal{W}_n$, for Chebyshev polynomials of finite unions of Jordan arcs. We prove that, in contrast to Widom's proposal, when dealing with a single smooth Jordan arc, $\mathcal{W}_n$ converges to 2 exclusively when the arc is a straight line segment. Our main focus is on analysing

Anatael Cabrera, Yang Han, Steven Calvez, Emmanuel Chauveau

Neutrino detectors are among the largest photon detection instruments, built to capture scarce photons upon energy deposition. Many discoveries in neutrino physics, including the neutrino itself, are inseparable from the advances in photon detection technology, particularly in photo-sensors and readout electronics, to yield ever higher precision and richer d

Maximilian Ernst Tschuchnig, Julia Coste-Marin, Philipp Steininger, Michael Gadermayr

Semantic segmentation is a crucial task in medical image processing, essential for segmenting organs or lesions such as tumors. In this study we aim to improve automated segmentation in CBCTs through multi-task learning. To evaluate effects on different volume qualities, a CBCT dataset is synthesised from the CT Liver Tumor Segmentation Benchmark (LiTS) data

Emily Groves, Minhong Wang, Yusuf Abdulle, Holger Kunz

Automated knowledge curation for biomedical ontologies is key to ensure that they remain comprehensive, high-quality and up-to-date. In the era of foundational language models, this study compares and analyzes three NLP paradigms for curation tasks: in-context learning (ICL), fine-tuning (FT), and supervised learning (ML). Using the Chemical Entities of Biol

Peize Li, Qingyi Si, Peng Fu, Zheng Lin

Visual question answering is a multimodal task that requires the joint comprehension of visual and textual information. However, integrating visual and textual semantics solely through attention layers is insufficient to comprehensively understand and align information from both modalities. Intuitively, object attributes can naturally serve as a bridge to un

Abdallah M. Al Zahrani

We study circular orbits that are tilted with respect to the equatorial plane around a Kerr black hole. We write the equations for the parameters of a tilted circular orbit in terms of the orbit's radius and the Carter constant, or equivalently, the tilt angle. The tilted innermost stable circular orbits (TISCO)s are discussed as well as the last circular or

LHCb collaboration, R. Aaij, A. S. W. Abdelmotteleb, C. Abellan Beteta

A study of $B_c^+ \rightarrow \chi_c \pi^+$ decays is reported using proton-proton collision data, collected with the LHCb detector at centre-of-mass energies of 7, 8, and 13 TeV, corresponding to an integrated luminosity of 9fb$^{-1}$. The decay $B_c^+ \rightarrow \chi_{c2} \pi^+$ is observed for the first time, with a significance exceeding seven standard

Christian A. Rosiek, Massimiliano Rossi, Albert Schliesser, Anders S. Sørensen

Generating macroscopic non-classical quantum states is a long-standing challenge in physics. Anharmonic dynamics is an essential ingredient to generate these states, but for large mechanical systems, the effect of the anharmonicity tends to become negligible compared to decoherence. As a possible solution to this challenge, we propose to use a motional squee

Deep Ghosh, Sourav Gope, Satyanarayan Mukhopadhyay

The initial density of dark matter (DM) particles, otherwise secluded from the standard model (SM), may be generated at reheating, with an initial temperature ratio for internal thermalizations, $\xi_i=T_{\rm DM,i}/T_{\rm SM,i}$. This scenario necessarily implies inflaton-mediated scatterings between DM and SM after reheating, with a rate fixed by the relic

Alberto García Martín-Caro, Miguel Huidobro, Yoshitaka Hatta

We compute the mass radius, scalar radius, tensor radius, baryon number radius and mechanical radius of nuclei with baryon number $B=1,2,3,4,5,6,7,8,32,108$ in the Skyrme model. The relations between these radii and the nuclear gravitational form factors are investigated. We also compute the `pressure' distribution and find that it is negative in the core re

Miguel Camarasa, Fabio Pizzichillo

We investigate the self-adjointness of the two dimensional Dirac operator with infinite mass boundary conditions on an unbounded domain with an infinite number of corners. We prove that if the domain has no concave corners, then the operator is self-adjoint. On the other hand, when concave corners are present, the operator is no longer self-adjoint and self-

Vasilis Belis, Patrick Odagiu, Thea Klæboe Årrestad

The detection of out-of-distribution data points is a common task in particle physics. It is used for monitoring complex particle detectors or for identifying rare and unexpected events that may be indicative of new phenomena or physics beyond the Standard Model. Recent advances in Machine Learning for anomaly detection have encouraged the utilization of suc

Frank Aurzada, Mikhail Lifshits, Dominic T. Schickentanz

We condition a Brownian motion on having an atypically small $L_2$-norm on a long time interval. The obtained limiting process is a non-stationary Ornstein-Uhlenbeck process.

Marek Filakovský, Tamio-Vesa Nakajima, Jakub Opršal, Gianluca Tasinato

A linearly ordered (LO) $k$-colouring of a hypergraph is a colouring of its vertices with colours $1, \dots, k$ such that each edge contains a unique maximal colour. Deciding whether an input hypergraph admits LO $k$-colouring with a fixed number of colours is NP-complete (and in the special case of graphs, LO colouring coincides with the usual graph colouri

Andreas Gross, Inder Kaur, Martin Ulirsch, Annette Werner

Let $A$ be an abelian variety with totally degenerate reduction over a non-Archimedean field. We describe the moduli space of semihomogeneous vector bundles on $A$ from the perspective of non-Archimedean uniformization and show that the essential skeleton may be identified with a tropical analogue of this moduli space. For $H=0$ our moduli space may be ident

Jinsu Kim, Jeongwon Lee, Jaemin Seo, Young-Chul Ghim

Disruption in tokamak plasmas, stemming from various instabilities, poses a critical challenge, resulting in detrimental effects on the associated devices. Consequently, the proactive prediction of disruptions to maintain stability emerges as a paramount concern for future fusion reactors. While data-driven methodologies have exhibited notable success in dis

Ping Wang, Li-Ming Song, Shao-Lin Xiong, Xiao-Yun Zhao

Understanding the nature of repeating fast radio bursts (FRBs) is crucial to probe their underlying physics. In this work, we analyze the waiting time statistics between bursts of three repeating FRBs from four datasets. We find a universally pronounced dependency of the waiting times on the previous time interval (denoted as $\lambda_0$). We observe a tempo

Anam Tahir, Kai Cui, Bastian Alt, Amr Rizk

The significance of the freshness of sensor and control data at the receiver side, often referred to as Age of Information (AoI), is fundamentally constrained by contention for limited network resources. Evidently, network congestion is detrimental for AoI, where this congestion is partly self-induced by the sensor transmission process in addition to the con

Yann Carteret, Vincent Bourrier, William Dethier

The characterization of exoplanetary atmospheres via transit spectroscopy is based on the comparison between the stellar spectrum filtered through the atmosphere and the unadulterated spectrum from the occulted stellar region. The disk-integrated spectrum is often used as a proxy for the occulted spectrum, yet they differ along the transit chord depending on

Alexandru Chirvasitu

We (a) prove that continuous morphisms from locally compact groups to locally exponential (possibly infinite-dimensional) Lie groups factor through Lie quotients, recovering a result of Shtern's on factoring norm-continuous representations on Banach spaces; (b) characterize the maximal almost-periodicity of the identity component $\mathbb{G}_0\le \mathbb{G}$

Jakub Wardak, Tiberius Georgescu, Giulio Gasbarri, Alessio Belenchia

Matter-wave interferometry with increasingly larger masses could pave the way to understanding the nature of wavefunction collapse, the quantum to classical transition or even how an object in a spatial superposition interacts with its gravitational field. In order to improve upon the current mass record, it is necessary to move into the nano-particle regime

Anam Tahir, Kai Cui, Heinz Koeppl

Scalable load balancing algorithms are of great interest in cloud networks and data centers, necessitating the use of tractable techniques to compute optimal load balancing policies for good performance. However, most existing scalable techniques, especially asymptotically scaling methods based on mean field theory, have not been able to model large queueing

Dhawal Gupta, Scott M. Jordan, Shreyas Chaudhari, Bo Liu

In this paper, we introduce a fresh perspective on the challenges of credit assignment and policy evaluation. First, we delve into the nuances of eligibility traces and explore instances where their updates may result in unexpected credit assignment to preceding states. From this investigation emerges the concept of a novel value function, which we refer to

Emanuele Dotto, Achim Krause, Thomas Nikolaus, Irakli Patchkoria

We give a new construction of $p$-typical Witt vectors with coefficients in terms of ghost maps and show that this construction is isomorphic to the one defined in terms of formal power series from the authors' previous paper. We show that our construction recovers Kaledin's polynomial Witt vectors in the case of vector spaces over a perfect field of charact

Junjie Gao, Pengfei Wang, Qiujie Dong, Qiong Zeng

Establishing accurate and representative matches is a crucial step in addressing the point cloud registration problem. A commonly employed approach involves detecting keypoints with salient geometric features and subsequently mapping these keypoints from one frame of the point cloud to another. However, methods within this category are hampered by the repeat

Howard E. Haber

Explicit formulae for the $4\times 4$ Lorentz transformation matrices corresponding to a pure boost and a pure three-dimensional rotation are very well-known. Significantly less well-known is the explicit formula for a general Lorentz transformation with arbitrary nonzero boost and rotation parameters. We revisit this more general formula by presenting two d

Pablo Rivière-Marichalar, Enrique Macías, Clément Baruteau, Asunción Fuente

Observational constraints on dust properties in protoplanetary disks are key to better understanding disks' evolution. We continue our exploration of the protoplanetary disk around AB Aur by characterizing its dust properties. We present ALMA observations at 2.2 mm and VLA observations at 6.8 mm. Together with previous ALMA and NOEMA observations at 0.87 and

Anton Vladyka, Eemeli A. Eronen, Johannes Niskanen

We present a PyTorch-powered implementation of the emulator-based component analysis used for ill-posed numerical non-linear inverse problems, where an approximate emulator for the forward problem is known. This emulator may be a numerical model, an interpolating function, or a fitting function such as a neural network. With the help of the emulator and a da

Emilie Eliseussen, Arnoldo Frigessi, Valeria Vitelli

Data in the form of rankings, ratings, pair comparisons or clicks are frequently collected in diverse fields, from marketing to politics, to understand assessors' individual preferences. Combining such preference data with features associated with the assessors can lead to a better understanding of the assessors' behaviors and choices. The Mallows model is a

Jef Laga, Ari Shnidman

We show that the Ceresa cycle $\kappa(C_t)$ of the genus $3$ curve $C_t \colon y^3 = x^4 + 2tx^2 + 1$ is torsion if and only if $Q_t=( \sqrt[3]{t^2 -1},t)$ is a torsion point on the elliptic curve $y^2 = x^3 + 1$. This shows that there are infinitely many smooth plane quartic curves over $\mathbb{C}$ (resp. $\mathbb{Q}$) with torsion (resp. infinite order) C

Yiqin Wang, Shu Sun, Chong Han

Extremely large-scale antenna array (ELAA) technologies consisting of ultra-massive multiple-input-multiple-output (UM-MIMO) or reconfigurable intelligent surfaces (RISs), are emerging to meet the demand of wireless systems in sixth-generation and beyond communications for enhanced coverage and extreme data rates up to Terabits per second. For ELAA operating

Oleg Antipin, Jahmall Bersini, Pantelis Panopoulos, Francesco Sannino

We determine anomalous dimensions of a family of fixed hypercharge operators in the Standard Model featuring the general Cabibbo-Kobayashi-Maskawa structure. The results are obtained at infinite orders in the couplings and to leading and subleading orders in the charge. The computed anomalous dimensions are shown to agree with the maximum known order in pert

Itzhak Tamo

This paper focuses on incidences over finite fields, extending to higher degrees a result by Vinh \cite{VINH20111177} on the number of point-line incidences in the plane $\mathbb{F}^2$, where $\mathbb{F}$ is a finite field. Specifically, we present a bound on the number of incidences between points and polynomials of bounded degree in $\mathbb{F}^2$. Our app

Thibaud Ehret, Roger Marí, Dawa Derksen, Nicolas Gasnier

Radiance fields have been a major breakthrough in the field of inverse rendering, novel view synthesis and 3D modeling of complex scenes from multi-view image collections. Since their introduction, it was shown that they could be extended to other modalities such as LiDAR, radio frequencies, X-ray or ultrasound. In this paper, we show that, despite the impor

Shiyu Huang, Wentse Chen, Yiwen Sun, Fuqing Bie

We present OpenRL, an advanced reinforcement learning (RL) framework designed to accommodate a diverse array of tasks, from single-agent challenges to complex multi-agent systems. OpenRL's robust support for self-play training empowers agents to develop advanced strategies in competitive settings. Notably, OpenRL integrates Natural Language Processing (NLP)

Van Bang Le, Felicia Lucke, Daniël Paulusma, Bernard Ries

A matching cut in a graph G is an edge cut of G that is also a matching. This short survey gives an overview of old and new results and open problems for Maximum Matching Cut, which is to determine the size of a largest matching cut in a graph. We also compare this problem with the related problems Matching Cut, Minimum Matching Cut, and Perfect Matching Cut

K. Mishima, G. Ichikawa, Y. Fuwa, T. Hasegawa

To solve the ''neutron lifetime puzzle,'' where measured neutron lifetimes differ depending on the measurement methods, an experiment with pulsed neutron beam at J-PARC is in progress. In this experiment, neutrons are bunched into 40-cm lengths using a spin flip chopper (SFC), where the statistical sensitivity was limited by the aperture size of the SFC. The

Pankaj Upadhyay, Subodh Sharma, Guangdong Bai

The Thread protocol (or simply Thread ) is a popular networking protocol for the Internet of Things (IoT). It allows seamless integration of a set of applications and protocols, hence reducing the risk of incompatibility among different applications or user protocols. Thread has been deployed in many popular smart home products by the majority of IoT manufac

AmirHossein Niksirat

Micro spacecraft have garnered increasing favor for their adaptability in space missions. Cold gas propellant-based (CGP) micro propulsion systems assume a pivotal role in enabling maneuvering, monitoring, and precise attitude control in micro/nanosatellites, offering attributes of simplicity, non-toxicity, and minimal leakage compared to alternative propuls

Beltrán Labrador, Manuel Otero-Gonzalez, Alicia Lozano-Diez, Daniel Ramos

This paper presents VoxCeleb-ESP, a collection of pointers and timestamps to YouTube videos facilitating the creation of a novel speaker recognition dataset. VoxCeleb-ESP captures real-world scenarios, incorporating diverse speaking styles, noises, and channel distortions. It includes 160 Spanish celebrities spanning various categories, ensuring a representa

P. Kiran, Hemant Shreepad Hegde, Harsha Miriam Reji, R. Prabhu

Quantum information with many-body quantum spin systems has, from time to time, given intriguing and intuitive outcomes to our understanding of multiport quantum communications. We identify that in an anisotropic many-body quantum spin system with two- and three-body interactions, when its two-spin subsystems are all negative under partial transpose, one can

Lucia Morotti

We prove generalised row and column removal results for decomposition numbers of spin representations of symmetric groups in characteristic 2, similar to Donkin's results for decomposition numbers of representations of symmetric groups.

Eerik Alamikkotervo, Risto Ojala, Alvari Seppänen, Kari Tammi

Detection of the drivable area in all conditions is crucial for autonomous driving and advanced driver assistance systems. However, the amount of labeled data in adverse driving conditions is limited, especially in winter, and supervised methods generalize poorly to conditions outside the training distribution. For easy adaption to all conditions, the need f

Ian Short, Matty Van Son, Andrei Zabolotskii

Frieze patterns have attracted significant attention recently, motivated by their relationship with cluster algebras. A longstanding open problem has been to provide a combinatorial model for frieze patterns over the ring of integers modulo $n$ akin to Conway and Coxeter's celebrated model for positive integer frieze patterns. Here we solve this problem usin

The Tien Mai

In this study, we address the problem of high-dimensional binary classification. Our proposed solution involves employing an aggregation technique founded on exponential weights and empirical hinge loss. Through the employment of a suitable sparsity-inducing prior distribution, we demonstrate that our method yields favorable theoretical results on prediction

R. Fraga-Encinas, M. Moscibrodzka, H. Falcke

The nature of the emission region around Sagittarius A* (Sgr A*), the supermassive black hole at the Galactic Center, remains under debate. A prediction of jet models is that a frequency-dependent shift in the position of the radio core (core-shift) of active galactic nucleii occurs when observing emission dominated by a highly collimated relativistic outflo

Rita Pardini, Piotr Pokora

The main aim of the note is to provide an upper-bound for the characteristic number of conic-line arrangements with ordinary singularities in the complex projective plane.

Junhao Lu, Zhijian Luo, Zhu Chen, Liping Fu

Accurate estimation of photometric redshifts (photo-$z$) is crucial in studies of both galaxy evolution and cosmology using current and future large sky surveys. In this study, we employ Random Forest (RF), a machine learning algorithm, to estimate photo-$z$ and investigate the systematic uncertainties affecting the results. Using galaxy flux and color as in

Ricardo Ferreira, Marta Guimarães, Filipa Valdeira, Cláudia Soares

Due to the importance of satellites for society and the exponential increase in the number of objects in orbit, it is important to accurately determine the state (e.g., position and velocity) of these Resident Space Objects (RSOs) at any time and in a timely manner. State-of-the-art methodologies for initial orbit determination consist of Kalman-type filters

Simon Ghysbrecht, Luca Donati, Bettina G. Keller

Modern potential energy surfaces have shifted attention to molecular simulations of chemical reactions. While various methods can estimate rate constants for conformational transitions in molecular dynamics simulations, their applicability to studying chemical reactions remains uncertain due to the high and sharp energy barriers and complex reaction coordina

J. Fernando Barbero G., Marc Basquens, Eduardo J. S. Villaseñor

The Gotay-Nester-Hinds method is used in this paper to study the Hamiltonian formulation of the Euclidean self-dual action. This action can be used to arrive at the complex Ashtekar formulation of General Relativity or a real connection formulation for Euclidean General Relativity. The main result of the paper is a derivation of the Ashtekar formulation for

Hamidreza Gholamrezaei, Alireza Koochali, Andreas Dengel, Sheraz Ahmed

This paper introduces Structured Noise Space GAN (SNS-GAN), a novel approach in the field of generative modeling specifically tailored for class-conditional generation in both image and time series data. It addresses the challenge of effectively integrating class labels into generative models without requiring structural modifications to the network. The SNS

The Tien Mai

This study investigates the misclassification excess risk bound in the context of 1-bit matrix completion, a significant problem in machine learning involving the recovery of an unknown matrix from a limited subset of its entries. Matrix completion has garnered considerable attention in the last two decades due to its diverse applications across various fiel

Amir Y. Weiss Behar, Devora Zalaznik

We show that a compact open subgroup $H$ of a simple algebraic $p$-adic group $G$ is self-similar if and only if it is isotropic.

Jayesh M. Dhadphale, K. Hauke Kraemer, Maximilian Gelbrecht, Jürgen Kurths

Phase space reconstruction (PSR) methods allow for the analysis of low-dimensional data with methods from dynamical system theory, but their application to prediction models, like those from machine learning (ML), is limited. Therefore, we present here a model adaptive phase space reconstruction (MAPSR) method that unifies the process of PSR with the modelin

Saveliy V. Skresanov

A directed diameter of a directed graph is the maximum possible distance between a pair of vertices, where paths must respect edge orientations, while undirected diameter is the diameter of the undirected graph obtained by symmetrizing the edges. In 2006 Babai proved that for a connected directed Cayley graph on $n$ vertices the directed diameter is bounded

Subikash Choudhury

The multiple parton$-$parton interactions (MPIs) are an important element to describe the observed collective flow and strangeness enhancement in high multiplicity pp and p$-$Pb collisions, the so-called small systems. At LHC energy, MPIs affect both soft and hard scales of the event. Since quarkonium production involves both, it can be an excellent tool to

A. Duft, J. A. Koziol, P. Adelhardt, M. Mühlhauser

We investigate the quantum phase diagram of the $J_1$-$J_2$-$J_3$ antiferromagnetic transverse-field Ising model on the ruby lattice. In the low-field limit we derive an effective quantum dimer model, analyzing how the extensive ground-state degeneracy at zero field is lifted by an order-by-disorder scenario. We support our analysis by studying the gap-closi

Alessandro Traspadini, Marco Giordani, Giovanni Giambene, Tomaso De Cola

During the last few years, the use of Unmanned Aerial Vehicles (UAVs) equipped with sensors and cameras has emerged as a cutting-edge technology to provide services such as surveillance, infrastructure inspections, and target acquisition. However, this approach requires UAVs to process data onboard, mainly for person/object detection and recognition, which m

Ankit Bhardwaj, Marcos Vinicius Surmani Martins, Yi You, Ravalika Sajja

Fluidic channels at atomic scales regulate cellular trafficking and molecular filtration across membranes and thus play crucial roles in the functioning of living systems. However, constructing synthetic channels experimentally at these scales has been a significant challenge due to the limitations in nanofabrication techniques and the surface roughness of t

Shang Liu, Yang Cao, Takao Murakami, Jinfei Liu

Differentially private triangle counting in graphs is essential for analyzing connection patterns and calculating clustering coefficients while protecting sensitive individual information. Previous works have relied on either central or local models to enforce differential privacy. However, a significant utility gap exists between the central and local model

Jonathan Wilton, Nan Ye

We consider training decision trees using noisily labeled data, focusing on loss functions that can lead to robust learning algorithms. Our contributions are threefold. First, we offer novel theoretical insights on the robustness of many existing loss functions in the context of decision tree learning. We show that some of the losses belong to a class of wha

Eleonora Poeta, Gabriele Ciravegna, Eliana Pastor, Tania Cerquitelli

The field of explainable artificial intelligence emerged in response to the growing need for more transparent and reliable models. However, using raw features to provide explanations has been disputed in several works lately, advocating for more user-understandable explanations. To address this issue, a wide range of papers proposing Concept-based eXplainabl

Anisha Bahl, Silvere Segaud, Yijing Xie, Jonathan Shapey

Information about tissue oxygen saturation ($StO_2$) and other related important physiological parameters can be extracted from diffuse reflectance spectra measured through non-contact imaging. Three analytical optical reflectance models for homogeneous, semi-infinite, tissue have been proposed (Modified Beer-Lambert, Jacques 1999, Yudovsky 2009) but these h

Lucia Testa, Claudio Battiloro, Stefania Sardellitti, Sergio Barbarossa

In this work, we study the problem of stability of Graph Convolutional Neural Networks (GCNs) under random small perturbations in the underlying graph topology, i.e. under a limited number of insertions or deletions of edges. We derive a novel bound on the expected difference between the outputs of unperturbed and perturbed GCNs. The proposed bound explicitl

Siqi Gu, Chunrong Fang, Quanjun Zhang, Zhenyu Chen

Recently, creative generative artificial intelligence software has emerged as a pivotal assistant, enabling users to generate content and seek inspiration rapidly. Text-to-Image (T2I) software, one of the most widely used, synthesizes images with text input by engaging in a cross-modal process. However, despite substantial advancements in the T2I engine, T2I

Martin Hallnäs

We discuss integrable many-body systems in one dimension of Calogero-Moser-Sutherland type, both classical and quantum as well as nonrelativistic and relativistic. In particular, we consider fundamental properties such as integrability, the existence of explicit solutions as well as action-angle and bispectral dualities that relate different such systems. We

Annika Moucha

We show that the space $\mathcal{H}(\Omega)$ of holomorphic functions $F:\Omega\to\mathbb{C}$, where ${\Omega=\{(z,w)\in\widehat{\mathbb{C}}^2\,:\, z\cdot w\neq 1\}}$, possesses an orthogonal Schauder basis consisting of distinguished eigenfunctions of the canonical Laplacian on $\Omega$. Mapping $\Omega$ biholomorphically onto the complex two-sphere, we use

Miguel Salg, Dalibor Djukanovic, Georg von Hippel, Harvey B. Meyer

We present results for the electromagnetic form factors of the proton and neutron computed on the $(2 + 1)$-flavor Coordinated Lattice Simulations (CLS) ensembles including both quark-connected and -disconnected contributions. The $Q^2$-, pion-mass, lattice-spacing, and finite-volume dependence of our form factor data is fitted simultaneously to the expressi

Miguel Salg, Dalibor Djukanovic, Georg von Hippel, Harvey B. Meyer

We present results for the electromagnetic form factors of the proton and neutron computed on the $(2 + 1)$-flavor Coordinated Lattice Simulations (CLS) ensembles including both quark-connected and -disconnected contributions. The $Q^2$-, pion-mass, lattice-spacing, and finite-volume dependence of our form factor data is fitted simultaneously to the expressi

Saskia Demulder, Sibylle Driezen, Bob Knighton, Gerben Oling

We review different exact approaches to string theory. In the context of the Green-Schwarz superstring, we discuss the action in curved backgrounds and its supercoset formulation, with particular attention to superstring backgrounds of the $AdS_3$ type supported by both Ramond-Ramond and Neveu-Schwarz-Neveu-Schwarz fluxes. This is the basis for the discussio

Maxime Vassaux

Collagen type I is well-known for its outstanding mechanical properties which it inherits from its hierarchical structure. Collagen type I fibrils may be viewed as an heterogeneous material made of protein, macromolecules (such as glycosaminoglycans and proteoglycans) and water. Water content modulates the properties of these heterofibrils. Yet, the properti

Andre Weiner, Richard Semaan

We present a robust and flexible optimization approach for dynamic mode decomposition analysis of data with complex dynamics and low signal-to-noise ratios. The approach borrows techniques and insights from the field of deep learning. Specifically, we employ automatic differentiation and stochastic gradient descent to compute eigenvalues, modes, and mode amp

Jacopo Zanchettin

In this article, we study the Chern-Weil theory for Hopf-Galois extensions originally introduced by Hajac and Maszczyk in the context of coalgebra extensions. We show that the cyclic homology Chern-Weil homomorphism defines natural transformations between Hopf-Galois extensions with a strong connection (principal comodule algebras) and cyclic homology, there

Jaesung Rim, Junyong Lee, Heemin Yang, Sunghyun Cho

Mobile cameras, despite their significant advancements, still have difficulty in low-light imaging due to compact sensors and lenses, leading to longer exposures and motion blur. Traditional blind deconvolution methods and learning-based deblurring methods can be potential solutions to remove blur. However, achieving practical performance still remains a cha

Leehwa Yeh

We derive a set of Clifford-algebraic formulas for two major nonlinear conformal transformations of the physical quantities related to Maxwell's equations. The superiority of these formulas over their vector-tensorial counterparts are demonstrated through three illustrative examples.

Rongsheng Wang, Qingsong Yao, Zihang Jiang, Haoran Lai

Despite significant advancements in medical vision-language pre-training, existing methods have largely overlooked the inherent linguistic complexity and imbalanced isssue within medical reports, as well as the complex cross-modality contextual relationships between texts and images. To close this gap, we propose a novel Entity-centered Context-aware Medical

Indrajit Tah, Daniel Haertter, Janice M. Crawford, Daniel P. Kiehart

Dorsal closure is a process that occurs during embryogenesis of Drosophila melanogaster. During dorsal closure, the amnioserosa (AS), a one-cell thick epithelial tissue that fills the dorsal opening, shrinks as the lateral epidermis sheets converge and eventually merge. During this process, the aspect ratio of amnioserosa cells increases markedly. The standa

Rabia Nasir, Humaira Ashraf, NZ Jhanjhi

Vehicular Ad Hoc Networks (VANETs) play a crucial role in Intelligent Transportation Systems (ITS) by facilitating communication between vehicles and infrastructure. This communication aims to enhance road safety, improve traffic efficiency, and enhance passenger comfort. The secure and reliable exchange of information is paramount to ensure the integrity an

Miyama Tamotsu, Okada Shogo

This paper describes a dialogue system developed for the Dialogue Robot Competition 2023 that achieves topic control for trip planning by inserting text into prompts using the ChatGPT-API. We built a system that is capable of generating compliments for the user based on recognition of the user's appearance and creating travel plans by extracting the knowledg

Ilaria Battiston, Peter Boncz

In this research project, we investigate an alternative to the standard cloud-centralized data architecture. Specifically, we aim to leave part of the application data under the control of the individual data owners in decentralized personal data stores. Our primary goal is to increase data minimization, i. e., enabling more sensitive personal data to be und

Jean Richert, Tarek Khalil

The measurement process of observables in a quantum system comes out to be an unsovable problem which started in the early times of the development of the theory. In the present note we consider the measured system part of an open system interacting with the measuring device and show under which ideal conditions the measure process may ideally work. Our proc

Başak Oral, Pierre Dragicevic, Alexandru Telea, Evanthia Dimara

Is it true that if citizens understand hurricane probabilities, they will make more rational decisions for evacuation? Finding answers to such questions is not straightforward in the literature because the terms judgment and decision making are often used interchangeably. This terminology conflation leads to a lack of clarity on whether people make suboptima

Carlos Naya, Tommaso Bertolini, Johan Carlström

In classes of Weyl semimetals where the symmetry protects nodes with higher than unit charge, the nematic Weyl liquid appears as interactions destroy this underlying symmetry. In the symmetry-broken phase, the multiple-charge nodes are split into objects of unit charge, the position of which in momentum space is determined by the nematic order parameter. We

Yi-Fan Zhang, Zhang Zhang, Liang Wang, Tieniu Tan

To combat the potential misuse of Natural Language Generation (NLG) technology, a variety of algorithms have been developed for the detection of AI-generated texts. Traditionally, this task is treated as a binary classification problem. Although supervised learning has demonstrated promising results, acquiring labeled data for detection purposes poses real-w

Pan Xie, Taiyi Peng, Yao Du, Qipeng Zhang

Sign Language Production (SLP) is the tough task of turning sign language into sign videos. The main goal of SLP is to create these videos using a sign gloss. In this research, we've developed a new method to make high-quality sign videos without using human poses as a middle step. Our model works in two main parts: first, it learns from a generator and the