March 2023 arXiv papers — page 95

Rahul Goel, Waleed Ammar, Aditya Gupta, Siddharth Vashishtha

Research interest in task-oriented dialogs has increased as systems such as Google Assistant, Alexa and Siri have become ubiquitous in everyday life. However, the impact of academic research in this area has been limited by the lack of datasets that realistically capture the wide array of user pain points. To enable research on some of the more challenging a

Zan Xu, Juan J. Alonso, Eric Darve

Krylov subspace methods are extensively used in scientific computing to solve large-scale linear systems. However, the performance of these iterative Krylov solvers on modern supercomputers is limited by expensive communication costs. The $s$-step strategy generates a series of $s$ Krylov vectors at a time to avoid communication. Asymptotically, the $s$-step

Sylvain Veilleux, Weizhe Liu, Andrey Vayner, Dominika Wylezalek

Quasar feedback may regulate the growth of supermassive black holes, quench coeval star formation, and impact galaxy morphology and the circumgalactic medium. However, direct evidence for quasar feedback in action at the epoch of peak black hole accretion at z ~ 2 remains elusive. A good case in point is the z = 1.6 quasar WISEA J100211.29+013706.7 (XID 2028

Tarek Allam, Julien Peloton, Jason D. McEwen

A new golden age in astronomy is upon us, dominated by data. Large astronomical surveys are broadcasting unprecedented rates of information, demanding machine learning as a critical component in modern scientific pipelines to handle the deluge of data. The upcoming Legacy Survey of Space and Time (LSST) of the Vera C. Rubin Observatory will raise the big-dat

Guosheng Fu, Stanley Osher, Wuchen Li

We design and compute first-order implicit-in-time variational schemes with high-order spatial discretization for initial value gradient flows in generalized optimal transport metric spaces. We first review some examples of gradient flows in generalized optimal transport spaces from the Onsager principle. We then use a one-step time relaxation optimization p

Jae Hee Lee

We present a method for constructing covariantly constant endomorphisms for the mod $p$ equivariant quantum connection, using the quantum Steenrod power operations of Fukaya and Wilkins. The example of the cotangent bundle of the projective line is fully computed, and we discuss the relationship with the mod $p$ solutions of trigonometric KZ equation recentl

Peter K. F. Kuhfittig

This paper discusses traversable wormholes in a dark-energy setting by starting with a model due to Sung-Won Kim. This model, based on the Friedmann-Lemaitre-Robertson-Walker model, is combined with a generalized Kaluza-Klein model. It is well known that phantom dark energy can in principle support traversable wormholes due to the violation of the null energ

Milad Azizkhani, Anthony L. Gunderman, Alex S. Qiu, Ai-Ping Hu

Blackberry harvesting is a labor-intensive and costly process, consuming up to 50\% of the total annual crop hours. This paper presents a solution for robotic harvesting through the design, manufacturing, integration, and control of a pneumatically actuated, kinematically redundant soft arm with a tendon-driven soft robotic gripper. The hardware design is op

Shafquat T. Islam, Wentao Ma, John G. Michopoulos, Kevin Wang

The generation of plasma from hypervelocity impacts is an active research topic due to its important science and engineering ramifications in various applications. Previous studies have mainly focused on the ionization of the solid materials that constitute the projectile and the target. In this letter, we consider impact events that occur in a fluid (e.g.,~

Kolja Knauer, William T. Trotter

Let $X$ be a finite set. A family $P$ of subsets of $X$ is called a convex geometry with ground set $X$ if (1) $\emptyset, X\in P$; (2) $A\cap B\in P$ whenever $A,B\in P$; and (3) if $A\in P$ and $A\neq X$, there is an element $\alpha\in X-A$ such that $A\cup\{\alpha\}\in P$. As a non-empty family of sets, a convex geometry has a well defined VC-dimension. I

Mohamed Djallel Dilmi, Hanene Azzag, Mustapha Lebbah

Genetic algorithms are a well-known example of bio-inspired heuristic methods. They mimic natural selection by modeling several operators such as mutation, crossover, and selection. Recent discoveries about Epigenetics regulation processes that occur "on top of" or "in addition to" the genetic basis for inheritance involve changes that affect and improve gen

Saba Ahmadi, Avrim Blum, Omar Montasser, Kevin Stangl

A fundamental problem in robust learning is asymmetry: a learner needs to correctly classify every one of exponentially-many perturbations that an adversary might make to a test-time natural example. In contrast, the attacker only needs to find one successful perturbation. Xiang et al.[2022] proposed an algorithm that in the context of patch attacks for imag

Uri Bader, Alexander Lubotzky, Roman Sauer, Shmuel Weinberger

Using cohomological methods, we show that lattices in semisimple groups are typically stable with respect to the Frobenius norm but not with respect to the operator norm.

Zixiang Zhao, Jiangshe Zhang, Xiang Gu, Chengli Tan

Guided depth map super-resolution (GDSR), as a hot topic in multi-modal image processing, aims to upsample low-resolution (LR) depth maps with additional information involved in high-resolution (HR) RGB images from the same scene. The critical step of this task is to effectively extract domain-shared and domain-private RGB/depth features. In addition, three

Yankai Zeng, Abhiramon Rajasekharan, Parth Padalkar, Kinjal Basu

Achieving human-like communication with machines remains a classic, challenging topic in the field of Knowledge Representation and Reasoning and Natural Language Processing. These Large Language Models (LLMs) rely on pattern-matching rather than a true understanding of the semantic meaning of a sentence. As a result, they may generate incorrect responses. To

Sandra Alves, Delia Kesner, Miguel Ramos

We show that recent approaches of static analysis based on quantitative typing systems can be extended to programming languages with global state. More precisely, we define a call-by-value language equipped with operations to access a global memory, together with a semantic model based on a (tight) multi-type system that captures exact measures of time and s

Raúl Lara-Cabrera, Fernando Ortega, Edgar Talavera, Daniel López-Fernández

Students' perception of excessive difficulty in STEM degrees lowers their motivation and therefore affects their performance. According to prior research, the use of gamification techniques promote engagement, motivation and fun when learning. Badges, which are a distinction that is given as a reward to students, are a well-known gamification tool. This cont

Nengkun Yu, Tzu-Chieh Wei

Beyond computer science, quantum complexity theory can potentially revolutionize multiple branches of physics, ranging from quantum many-body systems to quantum field theory. In this paper, we investigate the relationship between the sample complexity of learning a quantum state and the circuit complexity of the state. The circuit complexity of a quantum sta

Maarten Löffler, Tim Ophelders, Frank Staals, Rodrigo I. Silveira

Any surface that is intrinsically polyhedral can be represented by a collection of simple polygons (fragments), glued along pairs of equally long oriented edges, where each fragment is endowed with the geodesic metric arising from its Euclidean metric. We refer to such a representation as a portalgon, and we call two portalgons equivalent if the surfaces the

Emilio Onorati, Tamara Kohler, Toby S. Cubitt

Understanding how to characterise and mitigate errors is a key challenge in developing reliable quantum architecture for near-term applications. Recent work (arXiv:2103.17243) provides an efficient set of algorithms for analysing unknown noise processes requiring only tomographic snapshots of the quantum operator under consideration, without the need of any

Ahmad Bilal Asghar, Shreyas Sundaram, Stephen L. Smith

In this paper we study multi-robot path planning for persistent monitoring tasks. We consider the case where robots have a limited battery capacity with a discharge time $D$. We represent the areas to be monitored as the vertices of a weighted graph. For each vertex, there is a constraint on the maximum allowable time between robot visits, called the latency

Wenxin Jiang, Nicholas Synovic, Purvish Jajal, Taylor R. Schorlemmer

Due to the cost of developing and training deep learning models from scratch, machine learning engineers have begun to reuse pre-trained models (PTMs) and fine-tune them for downstream tasks. PTM registries known as "model hubs" support engineers in distributing and reusing deep learning models. PTM packages include pre-trained weights, documentation, model

Steve Paul, Wenyuan Li, Brian Smyth, Yuzhou Chen

Efficient multi-robot task allocation (MRTA) is fundamental to various time-sensitive applications such as disaster response, warehouse operations, and construction. This paper tackles a particular class of these problems that we call MRTA-collective transport or MRTA-CT -- here tasks present varying workloads and deadlines, and robots are subject to flight

Zeyd Boukhers, Christoph Lange, Oya Beyan

Our vision paper outlines a plan to improve the future of semantic interoperability in data spaces through the application of machine learning. The use of data spaces, where data is exchanged among members in a self-regulated environment, is becoming increasingly popular. However, the current manual practices of managing metadata and vocabularies in these sp

Nanna Inie, Jeanette Falk, Steven Tanimoto

Generative AI, i.e., the group of technologies that automatically generate visual or written content based on text prompts, has undergone a leap in complexity and become widely available within just a few years. Such technologies potentially introduce a massive disruption to creative fields. This paper presents the results of a qualitative survey ($N$ = 23)

Attila Jung

We propose a combinatorial framework to analyze quantitative Helly-type questions. Using this framework, we prove a Quantitative Fractional Helly Theorem with Fractional Helly Number 3d and a stability version of the Quantitative Helly Theorem of B\'ar\'any, Katchalski, and Pach.

Jaime Arias, Kyungmin Bae, Carlos Olarte, Peter Csaba Ölveczky

Parametric time Petri nets with inhibitor arcs (PITPNs) support flexibility for timed systems by allowing parameters in firing bounds. In this paper we present and prove correct a concrete and a symbolic rewriting logic semantics for PITPNs. We show how this allows us to use Maude combined with SMT solving to provide sound and complete formal analyses for PI

Hoda Memarzadeh, Nasser Ghadiri, Matthias Samwald, Maryam Lotfi Shahreza

Clinical notes containing valuable patient information are written by different health care providers with various scientific levels and writing styles. It might be helpful for clinicians and researchers to understand what information is essential when dealing with extensive electronic medical records. Entities recognizing and mapping them to standard termin

Luke Keyte, Mihkel Kama, Alice S. Booth, Edwin A. Bergin

The elemental carbon-to-oxygen ratio (C/O) in the atmosphere of a giant planet is a promising diagnostic of that planet's formation history in a protoplanetary disk. Alongside efforts in the exoplanet community to measure C/O in planetary atmospheres, observational and theoretical studies of disks are increasingly focused on understanding how the gas-phase C

Raktim Gautam Goswami, Prashanth Krishnamurthy, Farshad Khorrami

A methodology is developed to learn a feedback linearization (i.e., nonlinear change of coordinates and input transformation) using a data-driven approach for a single input control-affine nonlinear system with unknown dynamics. We employ deep neural networks to learn the feedback law (input transformation) in conjunction with an extension of invertible neur

Edgar Assing

We use a (pre)-Kuznetsov type formula to prove a density result for the Borel-type congruence subgroup of GLn. This has some arithmetic applications to optimal lifting and counting considered earlier by A. Kamber and H. Lavner for $GL_3$.

William Q. Erickson, Jan Kretschmann

A nonnegative integer matrix is said to be width-one if its nonzero entries lie along a path consisting of steps to the south and to the east. These matrices are important in optimal transport theory: the northwest corner algorithm, for example, takes supply and demand vectors and outputs a width-one matrix. The problem in this paper is to write down an expl

Yue Pan, Federico Magistri, Thomas Läbe, Elias Marks

Monitoring plants and fruits at high resolution play a key role in the future of agriculture. Accurate 3D information can pave the way to a diverse number of robotic applications in agriculture ranging from autonomous harvesting to precise yield estimation. Obtaining such 3D information is non-trivial as agricultural environments are often repetitive and clu

Daniele Fargion, Pier Giorgio De Sanctis Lucentini, Maxim Y. Khlopov

Abstract. We discuss recent results on the clustering, composition and distribution of Ultra-High Energy Cosmic Rays (UHECR) in the sky; from the energy of several tens of EeV in the dipole anisotropy, up to the highest energy of a few narrow clusters, those of Hot Spots. Following the early UHECR composition records deviations from proton, we noted that the

Sébastien Breteaux, Jérémy Faupin, Marius Lemm, Dong Hao Ou Yang

We consider Markovian open quantum dynamics (MOQD). We show that, up to small-probability tails, the supports of quantum states evolving under such dynamics propagate with finite speed in any finite-energy subspace. More precisely, we prove that if the initial quantum state is localized in space, then any finite-energy part of the solution of the von Neumann

Chenbin Pan, Zhiqi Zhang, Senem Velipasalar, Yi Xu

Capturing interaction of hands with objects is important to autonomously detect human actions from egocentric videos. In this work, we present a pyramid video transformer with a dynamic class token generator for egocentric action recognition. Different from previous video transformers, which use the same static embedding as the class token for diverse inputs

Tejpreet Kaur

The short-lived radionuclides (SLRs) have a half-life $\leq$ 100 Myr. The $\gamma$-ray observations and excess abundance of their daughter nuclides in various meteoritic phases confirm the existence of SLRs in the Galaxy and early solar system (ESS), respectively. In this work, we have developed Galactic Chemical Evolution (GCE) models for SLRs, $^{26}$Al, a

Rebecca L. Larson, Steven L. Finkelstein, Dale D. Kocevski, Taylor A. Hutchison

We report the discovery of an accreting supermassive black hole at z=8.679, in CEERS_1019, a galaxy previously discovered via a Ly$\alpha$-break by Hubble and with a Ly$\alpha$ redshift from Keck. As part of the Cosmic Evolution Early Release Science (CEERS) survey, we observed this source with JWST/NIRSpec spectroscopy, MIRI and NIRCam imaging, and NIRCam/W

Carlos H. S. Vieira, Jefferson L. D. de Oliveira, Jonas F. G. Santos, Pedro R. Dieguez

Quantum thermodynamics seeks to extend non-equilibrium stochastic thermodynamics to small quantum systems where non-classical features are essential to its description. Such a research area has recently provided meaningful theoretical and experimental advances by exploring the wealth and the power of quantum features along with informational aspects of a sys

Neil Chulpongsatorn, Wesley Willett, Ryo Suzuki

We contribute interaction techniques for augmenting mixed reality (MR) visualizations with smartphone proxies. By combining head-mounted displays (HMDs) with mobile touchscreens, we can augment low-resolution holographic 3D charts with precise touch input, haptics feedback, high-resolution 2D graphics, and physical manipulation. Our approach aims to compleme

Ahmad Rezaei, Mahdi Taheri, Ali Mahani, Sebastian Magierowski

The first important step in extracting DNA characters is using the output data of MinION devices in the form of electrical current signals. Various cutting-edge base callers use this data to detect the DNA characters based on the input. In this paper, we discuss several shortcomings of prior base callers in the case of time-critical applications, privacy-awa

Wei Lin, Leonid Karlinsky, Nina Shvetsova, Horst Possegger

Large scale Vision-Language (VL) models have shown tremendous success in aligning representations between visual and text modalities. This enables remarkable progress in zero-shot recognition, image generation & editing, and many other exciting tasks. However, VL models tend to over-represent objects while paying much less attention to verbs, and require add

Alexander Tyulenev

Let $(\operatorname{X},\operatorname{d},\mu)$ be a metric measure space with uniformly locally doubling measure $\mu$. Given $p \in (1,\infty)$, assume that $(\operatorname{X},\operatorname{d},\mu)$ supports a weak local $(1,p)$-Poincar\'e inequality. We characterize trace spaces of the first-order Sobolev $W^{1}_{p}(\operatorname{X})$-spaces to subsets $S$

Xuchen Han, Joseph Masterjohn, Alejandro Castro

We present a novel convex formulation that models rigid and deformable bodies coupled through frictional contact. The formulation incorporates a new corotational material model with positive semi-definite Hessian, which allows us to extend our previous work on the convex formulation of compliant contact to model large body deformations. We rigorously charact

Mahmoud A. Shawky, Syed Tariq Shah, Ahmed G. Abdellatif, Muhammad Ali Imran

Intelligent transportation systems increasingly depend on wireless communication for broadcasting traffic messages and facilitating real-time vehicular communication. In this context, message authentication is crucial for establishing secure and reliable communication. However, security solutions must consider the dynamic nature of vehicular communication li

Qiang Miao, Thomas Barthel

Strongly-correlated quantum many-body systems are difficult to study and simulate classically. We recently proposed a variational quantum eigensolver (VQE) based on the multiscale entanglement renormalization ansatz (MERA) with tensors constrained to certain Trotter circuits. Here, we determine the scaling of computation costs for various critical spin chain

Takuya Kanazawa, Chetan Gupta

Sequential decision making in the real world often requires finding a good balance of conflicting objectives. In general, there exist a plethora of Pareto-optimal policies that embody different patterns of compromises between objectives, and it is technically challenging to obtain them exhaustively using deep neural networks. In this work, we propose a novel

Allan Borodin, Calum MacRury

We consider the classical online bipartite matching problem in the probe-commit model. In this problem, when an online vertex arrives, its edges must be probed to determine if they exist, based on known edge probabilities. A probing algorithm must respect commitment, meaning that if a probed edge exists, it must be used in the matching. Additionally, each on

Christian Schubert, Rashid Shaisultanov

The worldline formalism has previously been used for deriving compact master formulas for the QED $N$ - photon amplitudes in vacuum, in a constant field and in a plane-wave field. Here we carry this program one step further by deriving master formulas for the scalar and spinor QED $N$-photon amplitudes in the background of the "parallel" special case of a co

Won Jo, Geuntaek Lim, Gwangjin Lee, Hyunwoo Kim

In content-based video retrieval (CBVR), dealing with large-scale collections, efficiency is as important as accuracy; thus, several video-level feature-based studies have actively been conducted. Nevertheless, owing to the severe difficulty of embedding a lengthy and untrimmed video into a single feature, these studies have been insufficient for accurate re

Laura Duarte, Pedro Neto

Collaborative robots are increasingly present in industry to support human activities. However, to make the human-robot collaborative process more effective, there are several challenges to be addressed. Collaborative robotic systems need to be aware of the human activities to (1) anticipate collaborative/assistive actions, (2) learn by demonstration, and (3

Rares Ambrosie, Cezar Oniciuc

In this paper, we first prove that a quadratic form from $\mathbb{S}^m$ to $\mathbb{S}^n$ is non-harmonic biharmonic if and only if it has constant energy density $(m+1)/2$. Then, we give a positive answer to an open problem concerning the structure of non-harmonic biharmonic quadratic forms. As a direct application, using classification results for harmonic

Elena Berardini, Xavier Caruso

We introduce the first geometric construction of codes in the sum-rank metric, which we called linearized Algebraic Geometry codes, using quotients of the ring of Ore polynomials with coefficients in the function field of an algebraic curve. We study the parameters of these codes and give lower bounds for their dimension and minimum distance. Our codes exhib

Clemens Giuliani, Filippo Vicentini, Riccardo Rossi, Giuseppe Carleo

Neural network approaches to approximate the ground state of quantum hamiltonians require the numerical solution of a highly nonlinear optimization problem. We introduce a statistical learning approach that makes the optimization trivial by using kernel methods. Our scheme is an approximate realization of the power method, where supervised learning is used t

James M Sullivan, Tijan Prijon, Uros Seljak

Local primordial non-Gaussianity (LPNG) is predicted by many non-minimal models of inflation, and creates a scale-dependent contribution to the power spectrum of large-scale structure (LSS) tracers, whose amplitude is characterized by $b_{\phi}$. Knowledge of $b_{\phi}$ for the observed tracer population is therefore crucial for learning about inflation from

Ryan Othniel Kearns

Trust is an important aspect of human life. It provides instrumental value in allowing us to collaborate on and defer actions to others, and intrinsic value in our intimate relationships with romantic partners, family, and friends. In this paper I examine the nature of trust from a philosophical perspective. Specifically I propose to view trust as a context-

Ewa A. Drzazga-Szczȩśniak, Piotr Szczepanik, Adam Z. Kaczmarek, Dominik Szczȩśniak

The concept of entropy is not uniquely relevant to the statistical mechanics but among others it can play pivotal role in the analysis of a time series, particularly the stock market data. In this area sudden events are especially interesting as they describe abrupt data changes which may have long-lasting effects. Here, we investigate the impact of such eve

Iñigo Sáez-Casares, Yann Rasera, Baojiu Li

In order to probe modifications of gravity at cosmological scales, one needs accurate theoretical predictions. N-body simulations are required to explore the non-linear regime of structure formation but are very time consuming. In this work, we release a new public emulator, dubbed e-MANTIS, that performs an accurate and fast interpolation between the predic

Eileen T. Meyer, Aamil Shaik, Karthik Reddy, Markos Georganopoulos

Despite the fact that jets from black holes were first understood to exist over 40 years ago, we are still in ignorance about many primary aspects of these systems -- including the radiation mechanism at high energies, the particle makeup of the jets, and how particles are accelerated, possibly to energies as high as 100 TeV and hundreds of kpc from the cent

Potsawee Manakul, Adian Liusie, Mark J. F. Gales

Generative Large Language Models (LLMs) such as GPT-3 are capable of generating highly fluent responses to a wide variety of user prompts. However, LLMs are known to hallucinate facts and make non-factual statements which can undermine trust in their output. Existing fact-checking approaches either require access to the output probability distribution (which

Ting Bai, Yuchao Li, Karl H. Johansson, Jonas Mårtensson

Freight drivers of electric trucks need to design charging strategies for where and how long to recharge the truck in order to complete delivery missions on time. Moreover, the charging strategies should be aligned with drivers' driving and rest time regulations, known as hours-of-service (HoS) regulations. This letter studies the optimal charging problems o

Zachary Flores, Angelo Taranto, Eric Bond, Yakir Forman

What provides the highest level of assurance for correctness of execution within a programming language? One answer, and our solution in particular, to this problem is to provide a formalization for, if it exists, the denotational semantics of a programming language. Achieving such a formalization provides a gold standard for ensuring a programming language

Shady E. Ahmed, Panos Stinis

Projection-based reduced order models (PROMs) have shown promise in representing the behavior of multiscale systems using a small set of generalized (or latent) variables. Despite their success, PROMs can be susceptible to inaccuracies, even instabilities, due to the improper accounting of the interaction between the resolved and unresolved scales of the mul

E. Cannon, M. Montargès, A. de Koter, A. Matter

The 'Great Dimming' of the prototypical red supergiant Betelgeuse, which occurred between December 2019 and April 2020, gives us unprecedented insight into the processes occurring on the stellar surface and in the inner wind of this type of star. In particular it may bring further understanding of their dust nucleation and mass loss processes. Here, we prese

Oded Ovadia, Adar Kahana, Panos Stinis, Eli Turkel

We combine vision transformers with operator learning to solve diverse inverse problems described by partial differential equations (PDEs). Our approach, named ViTO, combines a U-Net based architecture with a vision transformer. We apply ViTO to solve inverse PDE problems of increasing complexity, namely for the wave equation, the Navier-Stokes equations and

Melina Gómez-Bock, Wendy Gonzalez-Olivares, Martin Hentschinski, Alfonso Rosado

We explore the parameter space for processes with fermionic flavor violation within the 2HDM type III, processes of Flavor Changing Neutral Currents are present at LO as dynamics beyond the Standard Model are included. We analyze the possible Yukawa couplings beyond the SM involving the quark top, as the experimental signatures would be a clear signal to con

Yingchen Ma, Bing He, Nathan Subrahmanian, Srijan Kumar

Online misinformation has been a serious threat to public health and society. Social media users are known to reply to misinformation posts with counter-misinformation messages, which have been shown to be effective in curbing the spread of misinformation. This is called social correction. However, the characteristics of tweets that attract social correction

Lukas Zbinden, Lars Doorenbos, Theodoros Pissas, Adrian Thomas Huber

Semantic segmentation has made significant progress in recent years thanks to deep neural networks, but the common objective of generating a single segmentation output that accurately matches the image's content may not be suitable for safety-critical domains such as medical diagnostics and autonomous driving. Instead, multiple possible correct segmentation

Weston Hall, Barbara G. Castanheira, Agnès Bischoff-Kim

All single stars that are born with masses up to 8.5 - 10 $M_\odot$ will end their lives as a white dwarf (WD) star. In this evolutionary stage, WDs enter the cooling sequence, where the stars radiate away their thermal energy, and are basically cooling. As these stars cool, they reach temperatures and conditions that cause the stars to pulsate. Using differ

Qian Lou, Muhammad Santriaji, Ardhi Wiratama Baskara Yudha, Jiaqi Xue

Fully homomorphic encryption (FHE) is a powerful encryption technique that allows for computation to be performed on ciphertext without the need for decryption. FHE will thus enable privacy-preserving computation and a wide range of applications, such as secure cloud computing on sensitive medical and financial data, secure machine learning, etc. Prior resea

Patrycja Jaros, Subrata Ghosh, Dawid Dudkowski, Syamal K. Dana

How higher-order interactions influence the dynamics of second order phase oscillators? We address this question using three coupled Kuramoto phase oscillators with inertia under both pairwise and higher order interactions, finding collective states, which are absent for pair-wise interactions. Chimera states appear in an expanded parameter region of the 3-n

Hector Vargas Alvarez, Gianluca Fabiani, Nikolaos Kazantzis, Constantinos Siettos

We present a physics-informed machine learning (PIML) scheme for the feedback linearization of nonlinear discrete-time dynamical systems. The PIML finds the nonlinear transformation law, thus ensuring stability via pole placement, in one step. In order to facilitate convergence in the presence of steep gradients in the nonlinear transformation law, we addres

Riccardo Albertoni, David Browning, Simon Cox, Alejandra N. Gonzalez-Beltran

DCAT is an RDF vocabulary designed to facilitate interoperability between data catalogs published on the Web. Since its first release in 2014 as a W3C Recommendation, DCAT has seen a wide adoption across communities and domains, particularly in conjunction with implementing the FAIR data principles (for findable, accessible, interoperable and reusable data).

Marco Baldi, Sebastian Bitzer, Alessio Pavoni, Paolo Santini

Several recently proposed code-based cryptosystems base their security on a slightly generalized version of the classical (syndrome) decoding problem. Namely, in the so-called restricted (syndrome) decoding problem, the error values stem from a restricted set. In this paper, we propose new generic decoders, that are inspired by subset sum solvers and tailore

Tianshi Xu, Ruipeng Li, Daniel Osei-Kuffuor

This paper presents a parallel preconditioning approach based on incomplete LU (ILU) factorizations in the framework of Domain Decomposition (DD) for general sparse linear systems. We focus on distributed memory parallel architectures, specifically, those that are equipped with graphic processing units (GPUs). In addition to block Jacobi, we present general

Yaxin Xu, Kyu Hwan Choi, Sachit G. Nagella, Sho C. Takatori

Understanding multibody interactions between colloidal particles out of equilibrium has a profound impact on dynamical processes such as colloidal self assembly. However, traditional colloidal interactions are effectively quasi-static on colloidal timescales and cannot be modulated out of equilibrium. A mechanism to dynamically tune the interactions during c

Robbe De Prins, Yuan Yao, Anuj Apte, Filippo M. Miatto

Linear optical quantum circuits with photon number resolving (PNR) detectors are used for both Gaussian Boson Sampling (GBS) and for the preparation of non-Gaussian states such as Gottesman-Kitaev-Preskill (GKP), cat and NOON states. They are crucial in many schemes of quantum computing and quantum metrology. Classically optimizing circuits with PNR detector

Ol'ga Sipacheva

An example of two $\mathbb R$-factorizable groups whose product is not $\mathbb R$-factorizable is constructed. One of these groups is second-countable and the other Lindel\"of to any finite power.

Elliot Murphy

A comprehensive model of natural language processing in the brain must accommodate four components: representations, operations, structures and encoding. It further requires a principled account of how these components mechanistically, and causally, relate to each another. While previous models have isolated regions of interest for structure-building and lex

Andrew Gould, Yossi Shvartzvald, Jiyuan Zhang, Jennifer C. Yee

We systematically investigate the claim by Vandorou et al. (2023) to have detected the host star of the low mass-ratio ($q<10^{-4}$) microlensing planet OGLE-2016-BLG-1195Lb, via Keck adaptive optics (AO) measurements $\Delta t=4.12\,$yr after the peak of the event ($t_0$). If correct, this measurement would contradict the microlens parallax measurement deri

Ivan Laishevskiy, Artem Barger, Vladimir Gorgadze

The Hyperledger Fabric is well known and the most prominent enterprise-grade permissioned blockchain. The architecture of the Hyperledger Fabric introduces a new architecture paradigm of simulate-order-validate and pluggable architecture, allowing a greater level of customization where one of the critical components is the world state database, which is resp

Saad Hamid, Xingchen Wan, Martin Jørgensen, Binxin Ru

Ensembling can improve the performance of Neural Networks, but existing approaches struggle when the architecture likelihood surface has dispersed, narrow peaks. Furthermore, existing methods construct equally weighted ensembles, and this is likely to be vulnerable to the failure modes of the weaker architectures. By viewing ensembling as approximately margi

Giorgis Georgakoudis, Konstantinos Parasyris, Chunhua Liao, David Beckingsale

Heterogeneity has become a mainstream architecture design choice for building High Performance Computing systems. However, heterogeneity poses significant challenges for achieving performance portability of execution. Adapting a program to a new heterogeneous platform is laborious and requires developers to manually explore a vast space of execution paramete

Zachary K. Hardy, Jim. E. Morel

In this paper, a non-intrusive reduced-order model (ROM) for parametric reactor kinetics simulations is presented. Time-dependent ROMs are notoriously data intensive and difficult to implement when nonlinear multiphysics phenomena are considered. These challenges are exacerbated when parametric dependencies are included. The proper orthogonal decomposition m

Martha Cash, Joseph Murphy, Alexander Wyglinski

Unmanned Aerial Vehicles (UAVs) are a rapidly emerging technology offering fast and cost-effective solutions for many areas, including public safety, surveillance, and wireless networks. However, due to the highly dynamic network topology of UAVs, traditional mesh networking protocols, such as the Better Approach to Mobile Ad-hoc Networking (B.A.T.M.A.N.), a

S. A. Mikhailov

The in-plane photoelectric (IPPE) effect is a recently discovered [Sci. Adv. \textbf{8}, eabi8398 (2022)] quantum phenomenon which enables efficient detection of terahertz (THz) radiation in semiconductor structures with a two-dimensional (2D) electron gas. Here we develop a theory of the IPPE effect in quasi-one-dimensional electron systems in which the wid

Taegyun Kim, Jeong Han Kim, Soubhik Kumar, Adam Martin

Particles with masses much larger than the inflationary Hubble scale, $H_I$, can be pair-produced non-adiabatically during inflation. Due to their large masses, the produced particles modify the curvature perturbation around their locations. These localized perturbations eventually give rise to localized signatures on the Cosmic Microwave Background (CMB), i

Ali Ayoub, Haruko Wainwright, Giovanni Sansavini, Randall Gauntt

Nuclear energy has been gaining momentum recently as one of the solutions to tackle climate change. However, significant environmental and health-risk concerns remain associated with potential accidents. Despite significant preventive efforts, we must acknowledge that accidents may happen and, therefore, develop strategies and technologies for mitigating the

Louis Saddier, Matteo Marsili

The available liquidity at any time in financial markets falls largely short of the typical size of the orders that institutional investors would trade. In order to reduce the impact on prices due to the execution of large orders, traders in financial markets split large orders into a series of smaller ones, which are executed sequentially. The resulting seq

Ian E. Nielsen, Ravi P. Ramachandran, Nidhal Bouaynaya, Hassan M. Fathallah-Shaykh

The expansion of explainable artificial intelligence as a field of research has generated numerous methods of visualizing and understanding the black box of a machine learning model. Attribution maps are generally used to highlight the parts of the input image that influence the model to make a specific decision. On the other hand, the robustness of machine

Theodoros Kapourniotis, Elham Kashefi, Dominik Leichtle, Luka Music

Secure multi-party computation (SMPC) protocols allow several parties that distrust each other to collectively compute a function on their inputs. In this paper, we introduce a protocol that lifts classical SMPC to quantum SMPC in a composably and statistically secure way, even for a single honest party. Unlike previous quantum SMPC protocols, our proposal o

Anmol Dwivedi, Ali Tajer

This paper proposes a data-driven graphical framework for the real-time search of risky cascading fault chains (FCs). While identifying risky FCs is pivotal to alleviating cascading failures, the complex spatio-temporal dependencies among the components of the power system render challenges to modeling and analyzing FCs. Furthermore, the real-time search of

Jan Oscar Cross-Zamirski, Praveen Anand, Guy Williams, Elizabeth Mouchet

Image-to-image reconstruction problems with free or inexpensive metadata in the form of class labels appear often in biological and medical image domains. Existing text-guided or style-transfer image-to-image approaches do not translate to datasets where additional information is provided as discrete classes. We introduce and implement a model which combines

Victor Rosendal, Walber Hugo Brito, Milan Radovic, Alla Chikina

Strontium niobate has triggered a lot of interest as a transparent conductor and as a possible realization of a correlated Dirac semi-metal. Using the lattice parameters as a tunable knob, the energy landscape of octahedral tilting was mapped using density functional theory calculations. We find that biaxial compressive strain induces tilting around the out-

Matteo Magoni, Radhika Joshi, Igor Lesanovsky

Atoms confined in optical tweezer arrays constitute a platform for the implementation of quantum computers and simulators. State-dependent operations are realized by exploiting electrostatic dipolar interactions that emerge, when two atoms are simultaneously excited to high-lying electronic states, so-called Rydberg states. These interactions also lead to st

Mariana S. Lazarova, Gabriela Canalizo, Mark Lacy, Wyatt Behn

Low-ionization Broad Absorption Line QSOs (LoBALs) are suspected to be merging systems in which extreme, AGN-driven outflows have been triggered. Whether or not LoBALs are uniquely associated with mergers, however, has yet to be established. To characterize the morphologies of LoBALs, we present the first high-resolution morphological analysis of a volume-li

Sebin Gracy, Yuan Wang, Philip E. Pare, Cesar A Uribe

We study the spread of multi-competitive viruses over a (possibly) time-varying network of individuals accounting for the presence of shared infrastructure networks that further enables transmission of the virus. We establish a sufficient condition for exponentially fast eradication of a virus for: 1) time-invariant graphs, 2) time-varying graphs with symmet

Tobias Wagner, Alexander Gepperth, Elmar Engels

This study proposes a framework for the automated hyperparameter optimization of a bearing fault detection pipeline for permanent magnet synchronous motors (PMSMs) without the need of external sensors. A automated machine learning (AutoML) pipeline search is performed by means of a genetic optimization to reduce human induced bias due to inappropriate parame

Matthew Ricks, Arianna E. Gleason, Francesca Miozzi, Hong Yang

We report on a novel approach to dynamic compression of materials that bridges the gap between previous static- and dynamic- compression techniques, allowing to explore a wide range of pathways in the pressure-temperature space. By combining a dynamic-diamond anvil cell setup with double-sided laser-heating and in situ X-ray diffraction, we are able to perfo

Jiajun Shen, Kananart Kuwaranancharoen, Raid Ayoub, Pietro Mercati

Model-based Reinforcement Learning (RL) integrates learning and planning and has received increasing attention in recent years. However, learning the model can incur a significant cost (in terms of sample complexity), due to the need to obtain a sufficient number of samples for each state-action pair. In this paper, we investigate the benefits of leveraging