April 2024 arXiv papers — page 158

Javier J. Sanchez-Medina

After the launch of ChatGPT v.4 there has been a global vivid discussion on the ability of this artificial intelligence powered platform and some other similar ones for the automatic production of all kinds of texts, including scientific and technical texts. This has triggered a reflection in many institutions on whether education and academic procedures sho

Jianfeng Wang

This thesis studies advanced probabilistic models, including both their theoretical foundations and practical applications, for different semi-supervised learning (SSL) tasks. The proposed probabilistic methods are able to improve the safety of AI systems in real applications by providing reliable uncertainty estimates quickly, and at the same time, achieve

Zachary Stier

We study the problem of state synthesis in the DQC1 (One Clean Qubit) model of quantum computation, which provides a single pure qubit and $n$ maximally mixed qubits, and after applying any quantum circuit some subset of the qubits are measured or discarded. In the case of discarding, we show that it is impossible to prepare additional pure qubits, and that

Pedro Taborda, Hugo Matias, Daniel Silvestre, Pedro Lourenço

This paper delves into a rendezvous scenario involving a chaser and a target spacecraft, focusing on the application of Model Predictive Control (MPC) to design a controller capable of guiding the chaser toward the target. The operational principle of spacecraft thrusters, requiring a minimum activation time that leads to the existence of a control deadband,

Ruihao Gu, Wenchao Li

Under some non-invertibility and irreducibility condition, for nilmanifold Anosov maps with one-dimensional stable bundle, we get the equivalence among the existence of invariant unstable bundle, the existence of topological conjugacy to its linear part, and a constant periodic stable Lyapunov exponent.

Natalia Ruiz-Pino, Antonio Prados

In feedback-controlled systems, an external agent -- the feedback controller -- measures the state of the system and modifies its subsequent dynamics depending on the outcome of the measurement. In this paper, we build a Markovian description for the joint stochastic process that comprises both the system and the controller variables. This Markovian descript

Henrik Eisenmann

We present a new approach to compute eigenvalues and eigenvectors of locally definite multiparameter eigenvalue problems by its signed multiindex. The method has the interpretation of a semismooth Newton method applied to certain functions that have a unique zero. We can therefore show local quadratic convergence, and for certain extreme eigenvalues even glo

Yunlong Wang, Lei Zhang, Yuyang Tu, Hui Zhang

The exploration of robotic dexterous hands utilizing tools has recently attracted considerable attention. A significant challenge in this field is the precise awareness of a tool's pose when grasped, as occlusion by the hand often degrades the quality of the estimation. Additionally, the tool's overall pose often fails to accurately represent the contact int

Lorenzo Cipriani, Francesco Fazzini, Edward Wilson-Ewing

We study gravitational collapse in effective loop quantum gravity, focusing on non-marginally bound configurations in Lema\^itre-Tolman-Bondi spacetimes. In the homogeneous limit we recover the effective dynamics of loop quantum cosmology for Friedman cosmologies with spatial curvature. We study a particular family of configurations with a homogeneous interi

Jean Servais, Jérémy Dohet-Eraly

A method combining the Lagrange-mesh and the complex Kohn variational methods is developed for computing the $\mathcal{S}$ matrix of a 2$+$1 elastic scattering in the frame of three-body Coulomb systems. Resonance parameters can be obtained from values of the $\mathcal{S}$ matrix at several scattering energies. The method is illustrated with the $S$-wave low

Etienne de Klerk, Juan Vera Lizcano

The Schm\"udgen's Positivstellensatz gives a certificate to verify positivity of a strictly positive polynomial $f$ on a compact, basic, semi-algebraic set $\mathbf{K} \subset \mathbb{R}^n$. A Positivstellensatz of this type is called effective if one may bound the degrees of the polynomials appearing in the certificate in terms of properties of $f$. If $\ma

Jonatas Marques, Alexis Schrubbe, Nicole P. Marwell, Nick Feamster

In 2021, the Broadband Equity, Access, and Deployment (BEAD) program allocated $42.45 billion to enhance high-speed internet access across the United States. As part of this funding initiative, The Federal Communications Commission (FCC) developed a national coverage map to guide the allocation of BEAD funds. This map was the key determinant to direct BEAD i

João Vitorino, Miguel Silva, Eva Maia, Isabel Praça

The growing cybersecurity threats make it essential to use high-quality data to train Machine Learning (ML) models for network traffic analysis, without noisy or missing data. By selecting the most relevant features for cyber-attack detection, it is possible to improve both the robustness and computational efficiency of the models used in a cybersecurity sys

Sven Ebel, Nahid Talebi

Controlling free-electron momentum states is of high interest in electron microscopy to achieve momentum and energy resolved probing and manipulation of physical systems. Free-electron and light interactions have emerged as a powerful technique to accomplish this. Here, we demonstrate both longitudinal and transverse phase control of a slow electron wavepack

Matthew Collins, Jared J. Beard, Nicholas Ohi, Yu Gu

The increasing use of autonomous robot systems in hazardous environments underscores the need for efficient search and rescue operations. Despite significant advancements, existing literature on object search often falls short in overcoming the difficulty of long planning horizons and dealing with sensor limitations, such as noise. This study introduces a no

V. Manuilov

Given an essential ideal $J\subset A$ of a C*-algebra $A$, and a Hilbert C*-module $M$ over $A$, we place $M$ between two other Hilbert C*-modules over $A$, $M_J\subset M\subset M^J$, in such a way that each submodule here is thick, i.e. its orthogonal conmplement in the greater module is trivial. We introduce the class $\mathbb B_J(M)$ of $J$-adjointable op

Dipendu Halder, Srijata Lahiri, Saurabh Basu

The Bernevig-Hughes-Zhang (BHZ) model, which serves as a cornerstone in the study of the quantum spin Hall insulators, showcases robust spin-filtered helical edge states in a nanoribbon geometry. In the presence of an in-plane magnetic field, these (first-order) helical states gap out to be replaced by second-order corner states under suitable open-boundary

Pasindu Tennage, Antoine Desjardins, Lefteris Kokoris-Kogias

Widely deployed consensus protocols in the cloud are often leader-based and optimized for low latency under synchronous network conditions. However, cloud networks can experience disruptions such as network partitions, high-loss links, and configuration errors. These disruptions interfere with the operation of leader-based protocols, as their view change mec

Muhammad Ubadah, Saif Khan Mohammed, Ronny Hadani, Shachar Kons

The Zak-OTFS input/output (I/O) relation is predictable and non-fading when the delay and Doppler periods are greater than the effective channel delay and Doppler spreads, a condition which we refer to as the crystallization condition. The filter taps can simply be read off from the response to a single Zak-OTFS point (impulse) pulsone waveform, and the I/O

B Shayak, Sana Jahedi, James A Yorke

When fitting a multi-parameter model to a data set, computer algorithms may suggest that a range of parameters provide equally reasonable fits, making the parameter estimation difficult. Here, we prove this fact for an SIR model. We say a set of parameter values is a good fit to outbreak data if the solution has the data's three most significant characterist

G. D'Onofrio, F. Polito, Z. Tomovski

We present a class of positive discrete random variables extending the Conway--Maxwell-Poisson distribution. This class emerges in a natural way from an application in queueing theory and contains distributions exhibiting quite different features. Some of these distributions are characterized by the presence of Bernstein and inverse Bernstein functions. As a

Weile Li, Muqing Shi, Zhonghua Hong

Traditional deep learning-based object detection networks often resize images during the data preprocessing stage to achieve a uniform size and scale in the feature map. Resizing is done to facilitate model propagation and fully connected classification. However, resizing inevitably leads to object deformation and loss of valuable information in the images.

Xiaogang Qiang, Shixin Ma, Haijing Song

Classical random walk formalism shows a significant role across a wide range of applications. As its quantum counterpart, the quantum walk is proposed as an important theoretical model for quantum computing. By exploiting the quantum effects such as superposition, interference and entanglement, quantum walks and their variety have been extensively studied fo

José L. Risco-Martín, Ignacio-Iker Prado-Rujas, Javier Campoy, María S. Pérez

As solar power continues to grow and replace traditional energy sources, the need for reliable forecasting models becomes increasingly important to ensure the stability and efficiency of the grid. However, the management of these models still needs to be improved, and new tools and technologies are required to handle the deployment and control of solar facil

Rohit Kumar Shukla, Gaurav Rudra Malik, S. Aravinda, Sunil Kumar Mishra

The dynamic region of out-of-time-ordered correlators (OTOCs) serves as a powerful indicator of chaos in classical and semiclassical systems, capturing the characteristic exponential growth. In contrast, this signature fails to appear in spin systems, where even chaotic dynamics lack such exponential escalation, making this region an unreliable marker of cha

A. A. Araújo Filho, J. R. Nascimento, A. Yu. Petrov, P. J. Porfírio

In this work, we study the gravitational lensing by a Lorentz-violating (LV) black hole inspired by the recent contribution [1]. Explicitly, we concentrate on a specific application: we perform the computation of gravitational lensing effects under the strong field limit. In particular, we analytically derive the deflection angle so that the lens equation ca

Jaeseok Hur, Meesoon Ha, Hawoong Jeong

The economic success of individuals is often determined by a combination of talent, luck, and assistance from others. We introduce a new agent-based model that simultaneously considers talent, luck, and social interaction. This model allows us to explore how network structure (how agents interact) and talent distribution among agents affect the dynamics of c

Pablo Ducru, Jonathan Raiman, Ronaldo Lemos, Clay Garner

This article investigates how AI-generated content can disrupt central revenue streams of the creative industries, in particular the collection of dividends from intellectual property (IP) rights. It reviews the IP and copyright questions related to the input and output of generative AI systems. A systematic method is proposed to assess whether AI-generated

Anteneh Getachew Gebrie, Ellen Hidemi Fukuda

In this paper, we propose a generalized conditional gradient method for multiobjective optimization, which can be viewed as an improved extension of the classical Frank-Wolfe (conditional gradient) method for single-objective optimization. The proposed method works for both constrained and unconstrained benchmark multiobjective optimization problems, where t

Zishen Wan, Che-Kai Liu, Mohamed Ibrahim, Hanchen Yang

Disentangling attributes of various sensory signals is central to human-like perception and reasoning and a critical task for higher-order cognitive and neuro-symbolic AI systems. An elegant approach to represent this intricate factorization is via high-dimensional holographic vectors drawing on brain-inspired vector symbolic architectures. However, holograp

Donghoon Kim, Tomotaka Kuwahara, Keiji Saito

The area law of the bipartite information measure characterizes one of the most fundamental aspects of quantum many-body physics. In thermal equilibrium, the area law for the mutual information universally holds at arbitrary temperatures as long as the systems have short-range interactions. In systems with power-law decaying interactions, $r^{-\alpha}$ ($r$:

Xinyu Ma, Xu Chu, Zhibang Yang, Yang Lin

With the increasingly powerful performances and enormous scales of pretrained models, promoting parameter efficiency in fine-tuning has become a crucial need for effective and efficient adaptation to various downstream tasks. One representative line of fine-tuning methods is Orthogonal Fine-tuning (OFT), which rigorously preserves the angular distances withi

Kévin Ballu, Jia-Hui Lim, Thomas G. Parton, Richard M. Parker

Cellulose nanocrystals (CNCs) are elongated nanoparticles derived from natural cellulose, with potential applications ranging from rheological modifiers and emulsion stabilizers to photonic pigments and sensors. For most applications, precise control over CNC morphology and surface chemistry is essential, but the relationship between process parameters, CNC

Juan A. Paredes, Dennis S. Bernstein

Absolute stability is a technique for analyzing the stability of Lur'e systems, which arise in diverse applications, such as oscillators with nonlinear damping or nonlinear stiffness. A special class of Lur'e systems consists of self-excited systems (SES), in which bounded oscillations arise from constant inputs. In many cases, SES can be stabilized by linea

Ilya Ilyankou, Aldo Lipani, Stefano Cavazzi, Xiaowei Gao

Sentence transformers are language models designed to perform semantic search. This study investigates the capacity of sentence transformers, fine-tuned on general question-answering datasets for asymmetric semantic search, to associate descriptions of human-generated routes across Great Britain with queries often used to describe hiking experiences. We find

Malik Abdul Sami, Zeeshan Rasheed, Muhammad Waseem, Zheying Zhang

Large Language Models (LLMs) are revolutionizing Software Engineering (SE) by introducing innovative methods for tasks such as collecting requirements, designing software, generating code, and creating test cases, among others. This article focuses on requirements engineering, typically seen as the initial phase of software development that involves multiple

Yang-Ting Chien, Oleh Fedkevych, Daniel Reichelt, Steffen Schumann

We study jet angularities for dijet production at the Relativistic Heavy Ion Collider (RHIC) in proton-proton (pp) and nucleus-nucleus (AA) collisions at 200 GeV nucleon-nucleon center-of-mass collision energy. In particular, we provide $\mathrm{NLL}$ resummed predictions for angularity observables of groomed and ungroomed jets produced in $\rm pp$ collision

Xinrun Du, Zhouliang Yu, Songyang Gao, Ding Pan

In this study, we introduce CT-LLM, a 2B large language model (LLM) that illustrates a pivotal shift towards prioritizing the Chinese language in developing LLMs. Uniquely initiated from scratch, CT-LLM diverges from the conventional methodology by primarily incorporating Chinese textual data, utilizing an extensive corpus of 1,200 billion tokens, including

Evan M. O'Dorney

We consider the cohomology groups of line bundles $\mathcal{L}$ on the \emph{incidence correspondence}, that is, a general hypersurface $X \subset \mathbb{P}^{n-1} \times \mathbb{P}^{n-1}$ of degrees $(1,1)$. Whereas the characteristic $0$ situation is completely understood, the cohomology in characteristic $p$ depends in a mysterious way on the base-$p$ dig

Christopher E. Stuart

In this paper, a characterization of normed barrelled spaces is given, as well as a similar characterization of rings of sets with the Nikodym Property. Finally, a condition that is equivalent to a Banach space having a separable quotient is discussed.

Osmar M. Guerra-Alvarado, Carlos Carrasco-González, Enrique Macías, Nienke van der Marel

Aims. To comprehend the efficiency of dust evolution within protoplanetary disks, it is crucial to conduct studies of these disks using high-resolution observations at multiple wavelengths with the Atacama Large Millimeter/submillimeter Array (ALMA). Methods. In this work, we present high-frequency ALMA observations of the HL Tau disk using its Band 9 center

João Coelho, Bruno Martins, João Magalhães, Jamie Callan

This study investigates the existence of positional biases in Transformer-based models for text representation learning, particularly in the context of web document retrieval. We build on previous research that demonstrated loss of information in the middle of input sequences for causal language models, extending it to the domain of representation learning.

Le Xia, Yao Sun, Dusit Niyato, Lan Zhang

Recently, semantic communication (SemCom) has shown great potential in significant resource savings and efficient information exchanges, thus naturally introducing a novel and practical cellular network paradigm where two modes of SemCom and conventional bit communication (BitCom) coexist. Nevertheless, the involved wireless resource management becomes rathe

Laurent Pizzagalli, Sandrine Brochard, Julien Godet, Julien Durinck

Motivated by contradicting reports in the literature, we have investigated the structural stability of tungsten nanoparticles using density functional theory calculations. The comparison of BCC, FCC, A15, disordered, and icosahedral configurations unequivocally shows that BCC is the energetically most stable structure when the number of atoms is greater than

Yuchen Bi, Jie Zhou

For an integral $2$-varifold $V=\underline{v}(\Sigma,\theta_{\ge 1})$ in $\mathbb{R}^n$ with generalized mean curvature $H\in L^2$ such that $\mu(\mathbb{R}^n)=4\pi$ and $\int_{\Sigma}|H|^2d\mu\le 16\pi(1+\delta^2)$ , we show that $\Sigma$ is $W^{2,2}$ close to the standard embedding of the round sphere in a quantitative way when $\delta< \delta_0\ll 1$. For

Mengting Li, Chuang Zhu

In recent years, deep neural networks (DNNs) have gained remarkable achievement in computer vision tasks, and the success of DNNs often depends greatly on the richness of data. However, the acquisition process of data and high-quality ground truth requires a lot of manpower and money. In the long, tedious process of data annotation, annotators are prone to m

Christian Nöbel, Raphael Steiner

The Circuit diameter of polytopes was introduced by Borgwardt, Finhold and Hemmecke as a fundamental tool for the study of circuit augmentation schemes for linear programming and for estimating combinatorial diameters. Determining the complexity of computing the circuit diameter of polytopes was posed as an open problem by Sanit\`a as well as by Kafer, and w

Pavel Bakhvalov, Mikhail Surnachev

We consider finite-volume schemes for linear hyperbolic systems with constant coefficients on unstructured meshes. Under the stability assumption, they exhibit the convergence rate between $p$ and $p+1$ where $p$ is the order of the truncation error. Our goal is to explain this effect. The central point of our study is that the truncation error on $(p+1)$-th

Mads Erlend Bøe Lysø, Esten Ingar Grøtli, Kristin Ytterstad Pettersen

In this paper, we improve upon a method for optimal control of quadrupedal robots which utilizes a full-order model of the system. The original method utilizes offline nonlinear optimal control to synthesize a control scheme which exponentially orbitally stabilizes the closed-loop system. However, it is not able to handle the overactuated phases which freque

Junbo Li, Keyan Chen, Gengju Tian, Lu Li

The segmentation and interpretation of the Martian surface play a pivotal role in Mars exploration, providing essential data for the trajectory planning and obstacle avoidance of rovers. However, the complex topography, similar surface features, and the lack of extensive annotated data pose significant challenges to the high-precision semantic segmentation o

Benoît Fauqué, Shan Jiang, Tom Fennell, Bertrand Roessli

Superconducting domes, ubiquitous across a variety of quantum materials, are often understood as a window favorite for pairing opened by the fluctuations of competing orders. Yet, a quantitative understanding of how such a window closes is missing. Here, we show that inelastic neutron scattering, by quantifying a length scale associated with polar fluctuatio

D. H. Lee, M. K. Cheoun, J. H. Choi, J. Y. Choi

JSNS$^2$ searches for short baseline neutrino oscillations with a baseline of 24~meters and a target of 17~tonnes of the Gd-loaded liquid scintillator. The correct algorithm on the event reconstruction of events, which determines the position and energy of neutrino interactions in the detector, are essential for the physics analysis of the data from the expe

Greger Torgrimsson

We derive analytical $\chi\ll1$ approximations for spin-dependent quantum radiation reaction for locally constant and locally monochromatic fields. We show how to factor out fast spin oscillations and obtain the degree of polarization in the plane orthogonal to the magnetic field from the Frobenius norm of the Mueller matrix. We show that spin effects lead t

Helmut Hörner, Lena Wild, Yevgeny Slobodkin, Gil Weinberg

A Coherent Perfect Absorber (CPA) exploits the interferometric nature of light to deposit all of a light field's incident energy into an otherwise weakly absorbing sample. The downside of this concept is that the necessary destructive interference in CPAs gets easily destroyed both by spectrally or spatially detuning the incoming light field. Each of these t

Nicole Meyer-Vernet, Alain Lecacheux

The recent paper by Li et al. on electron quasi-thermal noise in the outer heliosphere is flawed. It assumes the plasma drift speed to be much smaller than the electron thermal speed, even though both quantities are of the same order of magnitude in the outer heliosphere inward of the termination shock, because of the low plasma temperature. In this case, th

John Haslegrave, Peter Keevash

We consider a general framework for multi-type interacting particle systems on graphs, where particles move one at a time by random walk steps, different types may have different speeds, and may interact, possibly randomly, when they meet. We study the equilibrium time of the process, by which we mean the number of steps taken until no further interactions c

Xihan Ji, Hannah Übler, Roberto Maiolino, Francesco D'Eugenio

We report the chemical abundance pattern of GS\_3073, a galaxy at $z=5.55$ which was previously confirmed to host an overmassive active black hole, by leveraging the detection of about 40 emission lines, combining JWST/NIRSpec observations and ground-based (VLT/VIMOS) data. Based on the rest-frame UV emission lines, which trace high-density ($\sim 10^5~{\rm

Kunmin Wu, Sadeq S. Kadijani, Thomas L. Schmidt

We investigate a system of Majorana box qubits, where each of the Coulomb blockaded boxes is driven by an applied AC voltage and is embedded in a dissipative environment. The AC voltage is applied between a pair of quantum dots, each of which is coupled by tunneling to a Majorana box qubit. Moreover, the dissipation is created by the coupling to an electroma

Ravi Patel, Cosmin Safta, Reese E. Jones

Composite materials with different microstructural material symmetries are common in engineering applications where grain structure, alloying and particle/fiber packing are optimized via controlled manufacturing. In fact these microstructural tunings can be done throughout a part to achieve functional gradation and optimization at a structural level. To pred

Phuong M. Nguyen, Loc H. Nguyen, Huong T. T. Vu

This paper addresses the inverse scattering problem in the domain Omega. The input data, measured outside Omega, involve the waves generated by the interaction of plane waves with various directions and unknown scatterers fully occluded inside Omega. The output of this problem is the spatially dielectric constant of these scatterers. Our approach to solving

Ravi Kashikar, Arlies Valdespino, Charlton Ogg, Edvin Uppgard

Ferroelectricity has recently been demonstrated in germanium-based inorganic halide perovskites. We use atomistic first-principles-based simulations to study ultra-thin CsGeBr$_3$ films with thicknesses of 4-18 nm and develop a theory for ferroelectric ultrathin films. The theory introduces (i) a local order parameter, the local polarization, which allows th

Waleed El Hanafy

Similar to Rastall gravity we introduce matter-geometry nonminimal coupling which is proportional to the gradient of quadratic curvature invariants. Those are mimicking the conformal trace anomaly when backreaction of the quantum fields to a curved spacetime geometry is considered. We consider a static spherically symmetric stellar structure with anisotropic

Maxime Devogèle, Luca Buzzi, Marco Micheli, Juan Luis Cano

Context. Near-Earth objects (NEOs) on an impact course with Earth can move at high angular speed. Understanding their properties, including rotation state, is crucial for assessing impact risks and mitigation strategies. Traditional photometric methods face challenges in collecting data on fast-moving NEOs accurately. Aims. This study introduces an innovativ

H. S. Xu, L. Jin

A coherent perfect absorber is capable of completely absorbing input waves. However, the coherent perfect absorption severely depends on the superposition of the input waves, and the perfect absorption is sensitive to the disorder of the absorber. Thus, a robust incoherent perfect absorption, being insensitive to the superposition of input waves and the syst

Botao Ren, Botian Xu, Xue Yang, Yifan Pu

In most modern object detection pipelines, the detection proposals are processed independently given the feature map. Therefore, they overlook the underlying relationships between objects and the surrounding background, which could have provided additional context for accurate detection. Because aerial imagery is almost orthographic, the spatial relations in

K Naveen Kumar, C Krishna Mohan, Aravind Machiry

Federated Learning (FL) is a collaborative learning paradigm enabling participants to collectively train a shared machine learning model while preserving the privacy of their sensitive data. Nevertheless, the inherent decentralized and data-opaque characteristics of FL render its susceptibility to data poisoning attacks. These attacks introduce malformed or

Olga Sunneborn Gudnadottir, Axel Gallén, Giulia Ripellino, Jochen Jens Heinrich

This study presents a novel method for the definition of signal regions in searches for new physics at collider experiments, specifically those conducted at CERNs Large Hadron Collider. By leveraging multi-dimensional histograms with precise arithmetic and utilizing the SparkDensityTree library, it is possible to identify high-density regions within the avai

Alexander A. Mushtukov, Albert Weng, Sergey S. Tsygankov, Ilya A. Mereminskiy

It is expected that extreme mass accretion rate onto strongly magnetised neutron star results in appearance of accretion columns above stellar surface. For a distant observer, rotation of a star results in periodic variations of X-ray flux. Because the mass accretion rate fluctuates around the average value, the pulse profiles are not stable and demonstrate

Paul M. Alsing, Carlo Cafaro, Shannon Ray

We examine the geodesic between two mixed states of arbitrary dimension by means of their geometric mean operator. We utilize the fiber bundle approach by which the distance between two mixed state density operators $\rho_1$ and $\rho_2$ in the base space $M$ is given by the shortest distance in the (Hilbert Schmidt) bundle space $E$ of their purifications.

Rubén Hurtado-Gutiérrez

In this PhD thesis, I investigate the properties of symmetry-breaking dynamical phase transitions that manifest in the fluctuations of time-integrated observables within classical systems. In particular, I analyze how these phase transitions impose stringent constraints on the structure of the eigenvectors of the system dynamical generator of the dynamics. A

Robert J. Saskowski

This thesis explores topics related to the study of quantum gravity, with a focus on precision holography and higher-derivative supergravity. First, we study subleading corrections to the free energy of a particular 3D N=3 Chern-Simons-matter theory found by Gaiotto and Tomasiello, which is given by a matrix model after supersymmetric localization. This theo

Tommaso Aschieri, Błażej Ruba, Jan Philip Solovej

We study completely positive and trace-preserving equivariant maps between operators on irreducible representations of $\mathrm{SU}(2)$. We find asymptotic approximations of channels in the limit of large output representation and we compute traces of functions of channel outputs. Our main tool is quantization using coherent states. We provide quantitative e

Sören Tempel, Tobias Brandt, Christoph Lüth, Christian Dietrich

Symbolic execution is an SMT-based software verification and testing technique. Symbolic execution requires tracking performed computations during software simulation to reason about branches in the software under test. The prevailing approach on symbolic execution of binary code tracks computations by transforming the code to be tested to an architecture-in

Frederico B. Sousa, Alessandra Ames, Mingzu Liu, Pedro L. Gastelois

Transition metal dichalcogenide (TMD) monolayers present a singular coupling in their spin and valley degrees of freedom. Moreover, by applying an external magnetic field it is possible to break the energy degeneracy between their K and $-$K valleys. This valley Zeeman effect opens the possibility of controlling and distinguishing the spin and valley charact

Cristóbal Camarero, Alejandro Cano, Carmen Martínez, Ramón Beivide

Interconnection networks are key actors that condition the performance of current large datacenter and supercomputer systems. Both topology and routing are critical aspects that must be carefully considered for a competitive system network design. Moreover, when daily failures are expected, this tandem should exhibit resilience and robustness. Low-diameter n

Yuan Wang, Sander Rhebergen

We present and analyze an a posteriori error estimator for a space-time hybridizable discontinuous Galerkin discretization of the time-dependent advection-diffusion problem. The residual-based error estimator is proven to be reliable and locally efficient. In the reliability analysis we combine a Peclet-robust coercivity type result and a saturation assumpti

Massimo Bartoletti, Lorenzo Benetollo, Michele Bugliesi, Silvia Crafa

Smart contracts have played a pivotal role in the evolution of blockchains and Decentralized Applications (DApps). As DApps continue to gain widespread adoption, multiple smart contract languages have been and are being made available to developers, each with its distinctive features, strengths, and weaknesses. In this paper, we examine the smart contract la

John Haslegrave, Peter Keevash

We consider an interacting particle system where equal-sized populations of two types of particles move by random walk steps on a graph, the two types may have different speeds, and meetings of opposite-type particles result in annihilation. The key quantity of interest is the expected extinction time. Even for the mean-field setting of complete graphs, the

Gabriele Marra, Ulysse Planta, Philipp Wüstenberg, Ali Abbasi

This paper details our journey in designing and selecting a suitable application sandboxing mechanism for a satellite under development, with a focus on small satellites. Central to our study is the development of selection criteria for sandboxing and assessing its appropriateness for our satellite payload. We also test our approach on two already operationa

Johannes Exenberger, Matteo Di Salvo, Thomas Hirsch, Franz Wotawa

Machine learning plays an important role in the operation of current wind energy production systems. One central application is predictive maintenance to increase efficiency and lower electricity costs by reducing downtimes. Integrating physics-based knowledge in neural networks to enforce their physical plausibilty is a promising method to improve current a

Martin Cooney, Lena Klasén, Fernando Alonso-Fernandez

Robots are being designed to help people in an increasing variety of settings--but seemingly little attention has been given so far to the specific needs of women, who represent roughly half of the world's population but are highly underrepresented in robotics. Here we used a speculative prototyping approach to explore this expansive design space: First, we

Mackenzie R. Neal, Alexa A. Sochaniwsky, Paul D. McNicholas

While advances continue to be made in model-based clustering, challenges persist in modeling various data types such as panel data. Multivariate panel data present difficulties for clustering algorithms because they are often plagued by missing data and dropouts, presenting issues for estimation algorithms. This research presents a family of hidden Markov mo

Kristian S. Hansen, Juan D. Moreno-Ternero, Lars P. Østerdal

We develop a unified framework for the measurement and valuation of health and productivity. Within this framework, we characterize evaluation functions allowing for compromises between the classical quality-adjusted life years (QALYs) and its polar productivity-adjusted life years (PALYs). Our framework and characterization results provide a new normative b

Dai Guowei, Zhang Yong

In this paper, we first construct two-dimensional periodic interface waves with point vortex and capillary effect and then obtain the global structure of the set of solutions. This is done using the local and global bifurcation argument. Especially, we establish a global continuation theorem by using the degree for $C^1$ Fredholm mappings. As far as we know,

Yidong Gong, Pradeep Kumar

We hypothesize that the absence of a standardized benchmark has allowed several fundamental pitfalls in GNN System design and evaluation that the community has overlooked. In this work, we propose GNNBench, a plug-and-play benchmarking platform focused on system innovation. GNNBench presents a new protocol to exchange their captive tensor data, supports cust

Luciano Pandolfi

The classical quadratic regulator problem has rarely been studied for systems with persistent memory until recent times. In this paper we study the quadratic tracking problem on a \emph{ finite time horizon} for a system described by a controlled linear Volterra integrodifferential equation in $\zzr^d$. We use the Fredholm equation approach and we derive the

Valérie Berthé, Reem Yassawi

Aperiodic order refers to the mathematical formalisation of quasicrystals. Substitutions and cut and project sets are among their main actors; they also play a key role in the study of dynamical systems, whether they are symbolic, generated by tilings, or point sets. We focus here on the relations between quasicrystals and self-similarity from an arithmetica

Kazuki Yoshida, Yoshiki Chazono, Kazuyuki Ogata

The proton-induced deuteron knockout reaction, ($p$,$pd$), is one of the interests in the studies for probing the deuteron-like $p$-$n$ correlation in nuclei. According to a recent study of the inclusive deuteron-induced reaction, $(d,d'x)$, the refraction effect of the deuteron has a significant effect on the elementary process, nucleon-deuteron ($N$-$d$) b

Wang Jun, Xu Fei, Zhang Yong

This paper focuses on the analysis of stratified steady periodic water waves that contain stagnation points. The initial step involves transforming the free-boundary problem into a quasilinear pseudodifferential equation through a conformal mapping technique, resulting in a periodic function of a single variable. By utilizing the theorems developed by Cranda

Jacek Wiland, Max Ploner, Alan Akbik

Knowledge probing assesses to which degree a language model (LM) has successfully learned relational knowledge during pre-training. Probing is an inexpensive way to compare LMs of different sizes and training configurations. However, previous approaches rely on the objective function used in pre-training LMs and are thus applicable only to masked or causal L

Georgy Gordeev, Christina Hill, Angelina Gudima, Stephanie Reich

Excitonic polarons are quasiparticles formed by a Coulomb-bound electron-hole pair with strong coupling to lattice vibrations. Despite high fundamental interest in excitonic polarons, the experimental investigation of these particles remains challenging. In this work, we exploit the resonant Raman effect to probe the excitonic polarons in bismuth vanadate. W

Romain Egele, Felix Mohr, Tom Viering, Prasanna Balaprakash

To reach high performance with deep learning, hyperparameter optimization (HPO) is essential. This process is usually time-consuming due to costly evaluations of neural networks. Early discarding techniques limit the resources granted to unpromising candidates by observing the empirical learning curves and canceling neural network training as soon as the lac

Dai Guowei, Xu Fei, Zhang Yong

In this paper, two-dimensional periodic capillary-gravity waves travelling under the effect of a vertical electric field are considered. The full system is a nonlinear, two-layered and free boundary problem. The interface dynamics arises from the coupling between the Euler equations for the lower fluid layer and an electric contribution from the upper gas la

Håkon Kristiansen, Einar Aurbakken

The purpose of this document is to describe the solution and implementation of the time-independent and time-dependent Schr\"odinger using pseudospectral methods. Currently, the description is for single particle systems interacting with a classical electromagnetic field in spherical coordinates.

Giovanni Ciatto, Andrea Agiollo, Matteo Magnini, Andrea Omicini

Background. Endowing intelligent systems with semantic data commonly requires designing and instantiating ontologies with domain-specific knowledge. Especially in the early phases, those activities are typically performed manually by human experts possibly leveraging on their own experience. The resulting process is therefore time-consuming, error-prone, and

A. Zubayer, N. Ghafoor, K. A. Thorarinsdottir, A. Glavic

The concept of scattering length density tuning for improved polarization is investigated for Fe/11B4CTi multilayers and compared to the commonly used Fe/Si system in polarizing multilayer neutron optics. X-ray and neutron reflectivity, magnetization, and neutron polarization have been measured on such multilayers, highlighting differences from conventional

Jerrod Wigmore, Brooke Shrader, Eytan Modiano

Deep Reinforcement Learning (DRL) offers a powerful approach to training neural network control policies for stochastic queuing networks (SQN). However, traditional DRL methods rely on offline simulations or static datasets, limiting their real-world application in SQN control. This work proposes Online Deep Reinforcement Learning-based Controls (ODRLC) as a

Michael Pedersen

The present study applies observations of individual predictions of the first three releases of the US output growth rate to evaluate how the applied judgment affects prediction efficiency and accuracy as well as if judgment is persistent. While the first two issues have been assessed in other studies, there is little evidence on the formation of judgment in

George Retsinas, Panagiotis P. Filntisis, Radek Danecek, Victoria F. Abrevaya

While existing methods for 3D face reconstruction from in-the-wild images excel at recovering the overall face shape, they commonly miss subtle, extreme, asymmetric, or rarely observed expressions. We improve upon these methods with SMIRK (Spatial Modeling for Image-based Reconstruction of Kinesics), which faithfully reconstructs expressive 3D faces from ima

Barkavi Sundararajan, Somayajulu Sripada, Ehud Reiter

Neural Table-to-Text models tend to hallucinate, producing texts that contain factual errors. We investigate whether such errors in the output can be traced back to problems with the input. We manually annotated 1,837 texts generated by multiple models in the politics domain of the ToTTo dataset. We identify the input problems that are responsible for many o