May 2023 arXiv papers — page 106

Jessie Henshaw

In physics, I noticed subjects not explained by formulas were often not studied, like how uncontrolled growth systems changed form. Weather, businesses, societies, environments, communities, cultures, groups, relationships, lives, and livelihoods all do it following some variation of an 'S' curve. It is a slow-fast-slow process of self-animated contextual en

Denis Tarasov, Vladislav Kurenkov, Alexander Nikulin, Sergey Kolesnikov

Recent years have witnessed significant advancements in offline reinforcement learning (RL), resulting in the development of numerous algorithms with varying degrees of complexity. While these algorithms have led to noteworthy improvements, many incorporate seemingly minor design choices that impact their effectiveness beyond core algorithmic advances. Howev

Paulina Cecchi Bernales, María Isabel Cortez, Jaime Gómez

Let $G$ be a countable residually finite group (for instance $\mathbb{F}_2$) and let $\overleftarrow{G}$ be a totally disconnected metric compactification of $G$ equipped with the action of $G$ by left multiplication. For every $r\geq 1$ we construct a Toeplitz $G$-subshift $(X,\sigma,G)$, which is an almost one-to-one extension of $\overleftarrow{G}$, havin

Jinyuan Wu

In high energy physics experiment trigger systems, track segment seeding is a resource consuming function and the primary reason is the computing complexity of the segment finding process. As the Moore's Law is reaching its physical limit, reducing computing complexity should be carefully considered, rather than keep piling up silicon resources. The Tiny Tri

Shaofeng Yuan, Feng Yang

Automatic and accurate segmentation of aortic vessel tree (AVT) in computed tomography (CT) scans is crucial for early detection, diagnosis and prognosis of aortic diseases, such as aneurysms, dissections and stenosis. However, this task remains challenges, due to the complexity of aortic vessel tree and amount of CT angiography data. In this technical repor

Cyril Shih-Huan Hsu, Jorge Martín-Pérez, Danny De Vleeschauwer, Luca Valcarenghi

Cellular Vehicle-to-Everything (C-V2X) is currently at the forefront of the digital transformation of our society. By enabling vehicles to communicate with each other and with the traffic environment using cellular networks, we redefine transportation, improving road safety and transportation services, increasing efficiency of vehicular traffic flows, and re

Pei-Lin Yin, Chen Chen, Christian S. Fischer, Craig D. Roberts

A quark+diquark Faddeev equation treatment of the baryon bound state problem in Poincar\'e-invariant quantum field theory is used to deliver parameter-free predictions for all six $\Delta$-baryon elastic weak form factors. Amongst the results, it is worth highlighting that there are two distinct classes of such $\Delta$-baryon form factors, $(g_1, g_3, G_{\p

D. Edstrom, D. Broemmelsiek, K. Carlson, J. -P. Carneiro

The IOTA Proton Injector (IPI), currently under installation at the Fermilab Accelerator Science and Technology facility, is a beamline capable of delivering 20-mA pulses of protons at 2.5 MeV to the Integrable Optics Test Accelerator (IOTA) ring. First beam in the IPI beamline is anticipated in 2023, when it will operate alongside the existing electron inje

B. M. Smart, L. M. Haffner, K. A. Barger, D. A. Ciampa

The Large Magellanic Cloud (LMC) has an extensive H$_{\alpha}$ emission halo that traces an extended, warm ionized component of its interstellar medium. Using the Wisconsin H$_{\alpha}$ Mapper (WHAM) telescope, we present the first kinematic \ha\ survey of an extensive region around the LMC, from $l,b = (264\deg .5,\,-45\deg .5)$ to $(295\deg .5,\,-19\deg .5

Asher Trockman, J. Zico Kolter

It is notoriously difficult to train Transformers on small datasets; typically, large pre-trained models are instead used as the starting point. We explore the weights of such pre-trained Transformers (particularly for vision) to attempt to find reasons for this discrepancy. Surprisingly, we find that simply initializing the weights of self-attention layers

Calvin Preston, Alexandra Amon, George Efstathiou

Weak galaxy lensing surveys have consistently reported low values of the $S_8$ parameter compared to the $\textit{Planck}\ \Lambda\rm{CDM}$ cosmology. Amon & Efstathiou (2022) used KiDS-1000 cosmic shear measurements to propose that this tension can be reconciled if the matter fluctuation spectrum is suppressed more strongly on non-linear scales than assumed

Alireza Zaeemzadeh, Giulio Tononi

Originally developed as a theory of consciousness, integrated information theory provides a mathematical framework to quantify the causal irreducibility of systems and subsets of units in the system. Specifically, mechanism integrated information quantifies how much of the causal powers of a subset of units in a state, also referred to as a mechanism, cannot

Richard Hind, Tommaso Sferruzza, Adriano Tomassini

Let $(M,J)$ be a $2n$-dimensional almost complex manifold and let $x\in M$. We define the notion of almost complex blow-up of $(M,J)$ at $x$. We prove the existence of almost complex blow-ups at $x$ under suitable assumptions on the almost complex structure $J$ and we provide explicit examples of such a construction. We note that almost complex blow-ups are

Doriane Olewicki, Sarra Habchi, Mathieu Nayrolles, Mojtaba Faramarzi

Nowadays, software analytics tools using machine learning (ML) models to, for example, predict the risk of a code change are well established. However, as the goals of a project shift over time, and developers and their habits change, the performance of said models tends to degrade (drift) over time. Current retraining practices typically require retraining

Monika Wolfmayr

An approach to parameter optimization for the low-rank matrix recovery method in hyperspectral imaging is discussed. We formulate an optimization problem with respect to the initial parameters of the low-rank matrix recovery method. The performance for different parameter settings is compared in terms of computational times and memory. The results are evalua

H. Decauchy, T. Dufour

In this work, a jet of cold plasma is generated in a device supplied in helium and powered with a high-voltage nanopulse power supply, hence generating guided streamers. We focus on the interaction between these guided streamers and two targets placed in a series: a metal mesh target (MM) at floating potential followed by a metal plate target (MP) grounded b

Tadeja Veršič, Marina Rejkuba, Magda Arnaboldi, Ortwin Gerhard

Cosmological simulations predict dark matter shapes that deviate from spherical symmetry. The exact shape depends on the prescription of the simulation and the interplay between dark matter and baryons. This signature is most pronounced in the diffuse galactic haloes that can be observationally probed with planetary nebulae and globular clusters (GCs). The k

Shenjie Huang, Danial Chitnis, Cheng Chen, Harald Haas

Optical wireless communication (OWC) offers several complementary advantages to radio-frequency wireless networks such as its massive available spectrum; hence, it is widely anticipated that OWC will assume a pivotal role in the forthcoming sixth generation wireless communication networks. Although significant progress has been achieved in OWC over the past

Hans W. A. Hanley, Zakir Durumeric

As large language models (LLMs) like ChatGPT have gained traction, an increasing number of news websites have begun utilizing them to generate articles. However, not only can these language models produce factually inaccurate articles on reputable websites but disreputable news sites can utilize LLMs to mass produce misinformation. To begin to understand thi

Saikat Banerjee, Nikolai A. Sinitsyn

We investigate magnetic fluctuations of a mesoscopic critical region at the interface induced by smooth time-independent spacial changes of a control parameter across its critical value. Near the spatial critical point, the order parameter fluctuations are mesoscopic, i.e., much larger than the lattice constant but decaying away from the critical region. We

C. Favreau, A. Tribondeau, M. Marugan, F. Guyot

Halophilic microorganisms have long been known to survive within the brine inclusions of salt crystals, as evidenced by the change in color for salt crystals containing pigmented halophiles. However, the molecular mechanisms allowing this survival has remained an open question for decades. While protocols for the surface sterilization of halite (NaCl) have e

Benjamin Fine, Gerhard Rosenberger, Leonard Wienke

We consider a class of groups, called groups of F-type, which includes some known and important classes like Fuchsian groups of geometric rank $\ge 3$, surface groups of genus $\ge 2$, cyclically pinched one-relator groups and torus-knot groups, and discuss algebraic and geometric properties of groups of F-type.

Tianyu Chen

The current state-of-the-art Diffusion model has demonstrated excellent results in generating images. However, the images are monotonous and are mostly the result of the distribution of images of people in the training set, making it challenging to generate multiple images for a fixed number of individuals. This problem can often only be solved by fine-tunin

Bryce Cyr, Jens Chluba, Sandeep Kumar Acharya

If they exist, networks of superconducting cosmic strings are capable of injecting copious amounts of electromagnetic energy into the background over a broad range of frequencies. We study this injection both analytically, as well as numerically using the thermalization code CosmoTherm. With our refined analytic formalism, we update constraints from CMB spec

H. Decauchy, T. Dufour

Trains of positive guided streamers are generated within an atmospheric pressure plasma jet supplied in helium and polarized by a high-voltage nanosecond pulse generator. The device is completed by a grounded annular electrode and a grounded surface electrode on which they can interact. The resulting transmitted and multiple reflected guided streamers are me

Shahroz Khan, Panagiotis Kaklis, Kosa Goucher-Lambert

Typical parametric approaches restrict the exploration of diverse designs by generating variations based on a baseline design. In contrast, generative models provide a solution by leveraging existing designs to create compact yet diverse generative design spaces (GDSs). However, the effectiveness of current exploration methods in complex GDSs, especially in

Deepak Giri, Erin Brady

The last few years have significantly increased global interest in generative artificial intelligence. Deepfakes, which are synthetically created videos, emerged as an application of generative artificial intelligence. Fake news and pornographic content have been the two most prevalent negative use cases of deepfakes in the digital ecosystem. Deepfakes have

Filip Blaschke, Ondřej Nicolas Karpíšek, Lukáš Rafaj

We present an updated version of a general-purpose collective coordinate model that aims to fully map out the dynamics of a single scalar field in (1+1)-dimensions. This is achieved by a procedure that we call a `mechanization': we reduce the infinite number of degrees of freedom down to a finite and controllable number by chopping the field into flat segmen

Valentin Zieglmeier, Alexander Pretschner

Employees work in increasingly digital environments that enable advanced analytics. Yet, they lack oversight over the systems that process their data. That means that potential analysis errors or hidden biases are hard to uncover. Recent data protection legislation tries to tackle these issues, but it is inadequate. It does not prevent data misusage while at

Maria Kitsara, Gaelle Revet, Jean-Sebastien, Vartanian-Grimaldi

As part of applications dealing with cardiovascular tissue engineering, drop-cast polyvinylidene fluoride (PVDF) scaffolds have been treated by cold plasma to enhance their adherence to cardiac cells. The scaffolds were treated in a dielectric barrier device where cold plasma was generated in a gaseous environment combining a carrier gas (helium or argon) wi

Henri Decauchy, Allan Pavy, Marine Camus, Laura Fouassier

For the past twelve years, cold plasmas have been positioned as a breakthrough technology for treating cancer thanks to their antitumor properties. The innovation of ad hoc plasma sources and personalized protocols appears crucial to treat cancers with a very poor prognosis. This is the case for cholangiocarcinoma (CCA) , whose treatment with cold plasma req

Xiang Cheng, Kai-Chi Chang, Zhenda Xie, Murat Can Sarihan

Recent progress in quantum computing and networking enables high-performance large-scale quantum processors by connecting different quantum modules. Optical quantum systems show advantages in both computing and communications, and integrated quantum photonics further increases the level of scaling and complexity. Here we demonstrate an efficient SWAP gate th

Scott Mutchnik

We show that approximations of strict order can calibrate the fine structure of genericity. Particularly, we find exponential behavior within the $\mathrm{NSOP}_{n}$ hierarchy from model theory. Let $0$-$\eth$-independence denote forking-independence. Inductively, a formula $(n+1)$-$\eth$-divides over $M$ if it divides by every $n$-$\eth$-independent Morley

Enyu Cai, Jiaqi Guo, Changye Yang, Edward J. Delp

The sorghum panicle is an important trait related to grain yield and plant development. Detecting and counting sorghum panicles can provide significant information for plant phenotyping. Current deep-learning-based object detection methods for panicles require a large amount of training data. The data labeling is time-consuming and not feasible for real appl

James Schneeloch, Richard J. Birrittella, Christopher C. Tison, Gregory A. Howland

We lay down a general scheme to quantify the amount of genuine tripartite entanglement present in the spatial and energy-time degrees of freedom of entangled photon triplets using a resource-based measure known as the tripartite entanglement of formation. Quantifying genuine tripartite entanglement relative to a number of maximally entangled three-qubit Gree

Vishal Tiwari, Bing Gu, Ignacio Franco

Recent advances in laser technology now enable engineering the electronic structure of matter through strong light-matter interactions. However, the effective physicochemical properties of these laser-dressed nonequilibrium materials are not well understood. Here we develop a general theory that now enables modeling and interpreting the linear optical absorp

Fran Jelenić, Josip Jukić, Nina Drobac, Jan Šnajder

Active learning (AL) aims to reduce labeling costs by querying the examples most beneficial for model learning. While the effectiveness of AL for fine-tuning transformer-based pre-trained language models (PLMs) has been demonstrated, it is less clear to what extent the AL gains obtained with one model transfer to others. We consider the problem of transferab

Eloy Ayón-Beato, Mokhtar Hassaine

Recently, an extension of the standard four-dimensional scalar conformal action, yielding a second-order field equation that remains conformally invariant, was proposed. In spite of this, the corresponding action is not invariant under conformal transformations and this motivates us to define the notion of non-Noetherian conformal scalar field. In this artic

Finn Archinuk, Rehan Hafeez, Sébastien Fabbro, Hossen Teimoorinia

For natural guide start adaptive optics (AO) systems, pyramid wavefront sensors (PWFSs) can provide significant increase in sensitivity over the traditional Shack-Hartmann, but at the cost of a reduced linear range. When using a linear reconstructor, non-linearities result in wavefront estimation errors, which can have a significant impact on the image quali

Minjeong Jeon, Michael Schweinberger

The recent shift to remote learning and work has aggravated long-standing problems, such as the problem of monitoring the mental health of individuals and the progress of students towards learning targets. We introduce a novel latent process model with a view to monitoring the progress of individuals towards a hard-to-measure target of interest, measured by

Nathann T. Rodrigues, Tiago J. Oliveira, Thomas Prellberg

In recent work [PRE 100, 022121 (2019)] evidence was found that the surface adsorption transition of interacting self-avoiding trails (ISATs) placed on the square lattice displays a non-universal behavior at the special adsorption point (SAP) where the collapsing polymers adsorb. In fact, different surface exponents $\phi^{(s)}$ and $1/\delta^{(s)}$ were fou

Evan King, Haoxiang Yu, Sangsu Lee, Christine Julien

Smart home assistants function best when user commands are direct and well-specified (e.g., "turn on the kitchen light"), or when a hard-coded routine specifies the response. In more natural communication, however, human speech is unconstrained, often describing goals (e.g., "make it cozy in here" or "help me save energy") rather than indicating specific tar

Daniel Jespersen, Lorenzo Costigliola, Jeppe C. Dyre, Shibu Saw

This paper studies size-polydisperse Lennard-Jones systems described by active Ornstein-Uhlenbeck particle dynamics. The focus is on the existence of isomorphs (curves of invariant structure and dynamics) in the model's three-dimensional phase diagram. Isomorphs are traced out from a single steady-state configuration by means of the configurational-temperatu

Gavin Abercrombie, Amanda Cercas Curry, Tanvi Dinkar, Verena Rieser

Automated dialogue or conversational systems are anthropomorphised by developers and personified by users. While a degree of anthropomorphism may be inevitable due to the choice of medium, conscious and unconscious design choices can guide users to personify such systems to varying degrees. Encouraging users to relate to automated systems as if they were hum

Eric Brigham, Nicholas Hopper

Secure messaging applications often offer privacy to users by protecting their messages from would be observers through end-to-end encryption techniques. However, the metadata of who communicates with whom cannot be concealed by encryption alone. Signal's Sealed Sender mechanism attempts to enhance its protection of this data by obfuscating the sender of any

Nimrod Dvir, Elaine Friedman, Suraj Commuri, Fan Yang

Little research has explored how information engagement (IE), the degree to which individuals interact with and use information in a manner that manifests cognitively, behaviorally, and affectively. This study explored the impact of phrasing, specifically word choice, on IE and decision making. Synthesizing two theoretical models, User Engagement Theory UET

Mohsen Fathi

We give a fully analytical description of radial and angular geodesics for massive particles that travel in the spacetime provided by a (3+1)-dimensional scale-dependent black hole in the cosmological background, for which, the quantum corrections are assumed to be small. We show that the equations of motion for radial orbits can be solved by means of Lauric

Luis Paris, Olga Varghese

Graph products of cyclic groups and Coxeter groups are two families of groups that are defined by labeled graphs. The family of Dyer groups contains these both families and gives us a framework to study these groups in a unified way. This paper focuses on the growth series of a Dyer group $D$ with respect to the standard generating set. We give a recursive f

Maximilian Parzen, Davide Fioriti, Aristides Kiprakis

As the world seeks to transition to a sustainable energy future, energy storage technologies are increasingly recognized as critical enablers. However, the macro-energy system assessment of energy storage has often focused on isolated storage technologies and neglected competition between them, thus leaving out which energy storage to prioritise. The article

Jiaoyue Yuan, Yubi Chen, Bolin Liao

Achieving high thermoelectric performance requires efficient manipulation of thermal conductivity and a fundamental understanding of the microscopic mechanisms of phonon transport in crystalline solids. One of the major challenges in thermal transport is achieving ultralow lattice thermal conductivity. In this study, we use the anti-bonding character of the

Desong Du, Shaohang Han, Naiming Qi, Haitham Bou Ammar

Reinforcement learning (RL) exhibits impressive performance when managing complicated control tasks for robots. However, its wide application to physical robots is limited by the absence of strong safety guarantees. To overcome this challenge, this paper explores the control Lyapunov barrier function (CLBF) to analyze the safety and reachability solely based

Subhadip Kumar

Todays Information Technology world is cloud-centric. Companies are intrigued to migrate their workload private cloud from on-premise Datacenter to Public cloud to take advantage of the latest innovations. It drives the business growth and competitiveness of the organization. At the same time, it is important for Enterprise Architects to understand the drawb

Nisha Chandramoorthy, Florian Schaefer, Youssef Marzouk

We propose a new approach for sampling and Bayesian computation that uses the score of the target distribution to construct a transport from a given reference distribution to the target. Our approach is an infinite-dimensional Newton method, involving a linear PDE, for finding a zero of a ``score-residual'' operator. We prove sufficient conditions for conver

Chen Zhang, Yong Gao, Cheng-Jun Xia, Renxin Xu

Solid states of strange-cluster matter called strangeon matter can form strangeon stars that are highly compact. We show that strangeon matter and strangeon stars can be recast into dimensionless forms by a simple reparametrization and rescaling, through which we manage to maximally reduce the number of degrees of freedom. With this dimensionless scheme, we

Aliakbar Sepehri, Run R. Li, Mark R. Hoffmann

The importance of Localized Molecular Orbitals in correlation treatments beyond mean-field calculation and in the illustration of chemical bonding can hardly be overstated. However, generation of orthonormal localized occupied MOs is significantly more straightforward than obtaining orthonormal localized virtual MOs. Orthonormal molecular orbitals allow faci

Na Li, Hanane Kteich, Zied Bouraoui, Steven Schockaert

Learning vectors that capture the meaning of concepts remains a fundamental challenge. Somewhat surprisingly, perhaps, pre-trained language models have thus far only enabled modest improvements to the quality of such concept embeddings. Current strategies for using language models typically represent a concept by averaging the contextualised representations

J. Ng, B. M. Walsh, L. -J. Chen, Y. Omelchenko

Interactions between solar wind ions and neutral hydrogen atoms in Earth's exosphere can lead to the emission of soft X-rays. Upcoming missions such as SMILE and LEXI aim to use soft X-ray imaging to study the global structure of the magnetosphere. Although the magnetosheath and dayside magnetopause can often be driven by kinetic physics, it has typically be

Xupeng Miao, Gabriele Oliaro, Zhihao Zhang, Xinhao Cheng

This paper introduces SpecInfer, a system that accelerates generative large language model (LLM) serving with tree-based speculative inference and verification. The key idea behind SpecInfer is leveraging small speculative models to predict the LLM's outputs; the predictions are organized as a token tree, whose nodes each represent a candidate token sequence

Piotr Faliszewski, Andrzej Kaczmarczyk, Krzysztof Sornat, Stanisław Szufa

We consider the notions of agreement, diversity, and polarization in ordinal elections (that is, in elections where voters rank the candidates). While (computational) social choice offers good measures of agreement between the voters, such measures for the other two notions are lacking. We attempt to rectify this issue by designing appropriate measures, prov

Ali Gorji, Andisheh Amrollahi, Andreas Krause

Despite the capacity of neural nets to learn arbitrary functions, models trained through gradient descent often exhibit a bias towards ``simpler'' functions. Various notions of simplicity have been introduced to characterize this behavior. Here, we focus on the case of neural networks with discrete (zero-one), high-dimensional, inputs through the lens of the

He Chen, Elie Diaz, Cem Yuksel

We introduce a method for efficiently computing the exact shortest path to the boundary of a mesh from a given internal point in the presence of self-intersections. We provide a formal definition of shortest boundary paths for self-intersecting objects and present a robust algorithm for computing the actual shortest boundary path. The resulting method offers

Md Manjurul Ahsan, Shivakumar Raman, Zahed Siddique

Class imbalanced problems (CIP) are one of the potential challenges in developing unbiased Machine Learning (ML) models for predictions. CIP occurs when data samples are not equally distributed between the two or multiple classes. Borderline-Synthetic Minority Oversampling Techniques (SMOTE) is one of the approaches that has been used to balance the imbalanc

Domingos Djinja, Sergei Silvestrov, Alex Behakanira Tumwesigye

Representations of polynomial covariant type commutation relations by pairs of linear integral operators and multiplication operators on Banach spaces $L_p$ are constructed.

Cinzia Soresina, Quoc Bao Tang, Bao Ngoc Tran

The fast-reaction limit for reaction--diffusion systems modelling predator--prey interactions is investigated. In the considered model, predators exist in two possible states, namely searching and handling. The switching rate between these two states happens on a much faster time scale than other processes, leading to the consideration of the fast-reaction l

Seungjae Lee, Katharina Krischer

In a network of coupled oscillators, a symmetry-broken dynamical state characterized by the coexistence of coherent and incoherent parts can spontaneously form. It is known as a chimera state. We study chimera states in a network consisting of six populations of identical Kuramoto-Sakaguchi phase oscillators. The populations are arranged in a ring and oscill

Aakash Bansal, Bonita Sharif, Collin McMillan

Neural source code summarization is the task of generating natural language descriptions of source code behavior using neural networks. A fundamental component of most neural models is an attention mechanism. The attention mechanism learns to connect features in source code to specific words to use when generating natural language descriptions. Humans also p

Bekir Yavuz Koc, Taner Arsan, Onder Pekcan

Cardiac diseases are one of the leading mortality factors in modern, industrialized societies, which cause high expenses in public health systems. Due to high costs, developing analytical methods to improve cardiac diagnostics is essential. The heart's electric activity was first modeled using a set of nonlinear differential equations. Following this, variat

Robert L. Bryant

The local generality of the space of solitons for the Laplacian flow of closed $G_2$-structures is analyzed, and it is shown that the germs of such structures depend, up to diffeomorphism, on 16 functions of 6 variables (in the sense of E. Cartan). The method is to construct a natural exterior differential system whose integral manifolds describe such solito

Keller VandeBogert, Mark E. Walker

The Total Rank Conjecture is a coarser version of the Buchsbaum-Eisenbud-Horrocks conjecture which, loosely stated, predicts that modules with large annihilators must also have ``large'' syzygies. This conjecture was proved by the second author for rings of odd characteristic by taking advantage of the Adams operations on the category of perfect complexes wi

Hua Shen, Chieh-Yang Huang, Tongshuang Wu, Ting-Hao 'Kenneth' Huang

Despite a surge collection of XAI methods, users still struggle to obtain required AI explanations. Previous research suggests chatbots as dynamic solutions, but the effective design of conversational XAI agents for practical human needs remains under-explored. This paper focuses on Conversational XAI for AI-assisted scientific writing tasks. Drawing from hu

Carolina Rodríguez-Gallo, Antonio Ortiz-Ambriz, Cristiano Nisoli, Pietro Tierno

We combine experiments and numerical simulations to investigate the low energy states and the emergence of topological defects in an artificial colloidal ice in the Cairo geometry. This type of geometry is characterized by a mixed coordination ($z$), with coexistence of both $z=3$ and $z=4$ vertices. We realize this particle ice by confining field tunable pa

Ian E. Ochs, Nathaniel J. Fisch

By producing localized wave regions at the ends of an open-field-line magnetic confinement system, ponderomotive walls can be used to differentially confine different species in the plasma. Furthermore, if the plasma is rotating, this wall can be magnetostatic in the lab frame, resulting in simpler engineering and better power flow. However, recent work on s

Artem Alexandrov, Alexander Gorsky

In this Letter we consider the out-of-equilibrium phenomena in the complex Sachdev-Ye-Kitaev (SYK) model supplemented with the attractive Hubbard interaction (SYK+U). This model provides the clear-cut transition from non-Fermi liquid phase in pure SYK to the superconducting phase through the pseudogap phase with non-synchronized Cooper pairs. We investigate

H. Mete Soner, Valentin Tissot-Daguette

We study the properties of the free boundaries and the corresponding hitting times in the context of optimal stopping in discrete time. We first prove the continuity of the map from the boundaries to the expected value of the corresponding stopping policy both in the supremum norm and also in a weaker, novel topology induced by the relaxed $L^\infty$ metric

Abraham George, Alison Bartsch, Amir Barati Farimani

Across the robotics field, quality demonstrations are an integral part of many control pipelines. However, collecting high-quality demonstration trajectories remains time-consuming and difficult, often resulting in the number of demonstrations being the performance bottleneck. To address this issue, we present a method of Virtual Reality (VR) Teleoperation t

Markus Nußbaum-Thom, Lyan Verwimp, Youssef Oualil

On-device automatic speech recognition systems face several challenges compared to server-based systems. They have to meet stricter constraints in terms of speed, disk size and memory while maintaining the same accuracy. Often they have to serve several applications with different distributions at once, such as communicating with a virtual assistant and spee

Corina Dunn, Trevor Bowen, Alfred Mallet, Samuel Badman

Magnetic fluctuations in the solar wind are often observed to maintain constant magnitude of the magnetic field in a manner consistent with spherically-polarized large-amplitude Alfv\'en waves. We investigate the effect of spherical polarization on the magnetic spectral index through a statistical survey of magnetic fluctuations observed by Parker Solar Prob

Ravi Prakash, Sara Abedi

Creep deformation in shale rocks is an important factor in many applications, such as the sustainability of geostructures, wellbore stability, evaluation of land subsidence, CO2 storage, toxic waste containment, and hydraulic fracturing. One mechanism leading to this time-dependent deformation under a constant load is the dissolution/formation processes acco

Javier Yu, Jun En Low, Keiko Nagami, Mac Schwager

This work was presented at the IEEE International Conference on Robotics and Automation 2023 Workshop on Unconventional Spatial Representations. Neural radiance fields (NeRFs) are a class of implicit scene representations that model 3D environments from color images. NeRFs are expressive, and can model the complex and multi-scale geometry of real world envir

A. Derevianko

We propose a novel, exotic physics, modality in multi-messenger astronomy. We are interested in a DIRECT detection of exotic fields emitted by the mergers. This approach must be contrasted with the INDIRECT detection strategies, e.g., based on minute exotic-physics induced changes in gravitational wave spectral features. While our strategy seems to be overly

Astghik Hakobyan, Insoon Yang

Differential dynamic programming (DDP) is a popular technique for solving nonlinear optimal control problems with locally quadratic approximations. However, existing DDP methods are not designed for stochastic systems with unknown disturbance distributions. To address this limitation, we propose a novel DDP method that approximately solves the Wasserstein di

Matthew Gerry, Dvira Segal

We study kinetic transport through modular networks consisting of alternating domains using both analytical and numerical methods. We demonstrate that the mean velocity is insensitive to the local structure of the network, and it indicates only on global, structural-averaged properties. However, by examining high-order cumulants characterizing the kinetics,

Aanisha Bhattacharya, Yaman K Singla, Balaji Krishnamurthy, Rajiv Ratn Shah

Multimedia content, such as advertisements and story videos, exhibit a rich blend of creativity and multiple modalities. They incorporate elements like text, visuals, audio, and storytelling techniques, employing devices like emotions, symbolism, and slogans to convey meaning. There is a dearth of large annotated training datasets in the multimedia domain hi

Hengyun Zhou, Haoyang Gao, Nathaniel T. Leitao, Oksana Makarova

We develop a formalism for the robust dynamical decoupling and Hamiltonian engineering of strongly interacting qudit systems. Specifically, we present a geometric formalism that significantly simplifies qudit pulse sequence design, while incorporating the necessary robustness conditions. We experimentally demonstrate these techniques in a strongly-interactin

Nayeon Kim, Yinhua Piao, Sun Kim

Leveraging knowledge from electronic health records (EHRs) to predict a patient's condition is essential to the effective delivery of appropriate care. Clinical notes of patient EHRs contain valuable information from healthcare professionals, but have been underused due to their difficult contents and complex hierarchies. Recently, hypergraph-based methods h

Sebastian Wohlrab, Sebastian J. Müller, Stephan Gekle

Biological cells are built up from many different constituents of varying size and stiffness which all contribute to the cell's mechanical properties. Despite this heterogeneity, in the analysis of experimental measurements such as atomic force microscopy or microfluidic characterisation a strongly simplified homogeneous cell is typically assumed and a singl

Karin Wittmann W, Leandro H. Ymai, Bruno H. C. Barros, Jon Links

We study the dynamics of entanglement and atomic populations of ultracold dipolar bosons in an aligned three-well potential described by an extended Bose-Hubbard model. We focus on a sufficiently strong interacting regime where the couplings are tuned to obtain an integrable system, in which the time evolution exhibits a resonant behavior that can be exactly

Walter O. Krawec

Entropic uncertainty relations are powerful tools, especially in quantum cryptography. They typically bound the amount of uncertainty a third-party adversary may hold on a measurement outcome as a result of the measurement overlap. However, when the two measurement bases are biased towards one another, standard entropic uncertainty relations do not always pr

Nicola Rizzo, Manuel Cáceres, Veli Mäkinen

We study the problem of finding maximal exact matches (MEMs) between a query string $Q$ and a labeled graph $G$. MEMs are an important class of seeds, often used in seed-chain-extend type of practical alignment methods because of their strong connections to classical metrics. A principled way to speed up chaining is to limit the number of MEMs by considering

Sebastian Fajardo, Paul R. B. Kozowyk, Geeske H. J. Langejans

We implement a method from computer sciences to address a challenge in Paleolithic archaeology: how to infer cognition differences from material culture. Archaeological material culture is linked to cognition: more complex ancient technologies are assumed to have required complex cognition. We present an application of Petri net analysis to compare Neanderth

Shangbang Long, Siyang Qin, Dmitry Panteleev, Alessandro Bissacco

We organize a competition on hierarchical text detection and recognition. The competition is aimed to promote research into deep learning models and systems that can jointly perform text detection and recognition and geometric layout analysis. We present details of the proposed competition organization, including tasks, datasets, evaluations, and schedule. D

Marta Brzezińska, Oleg V. Yazyev

Motivated by the observation of polarization superlattices in twisted multilayers of hexagonal boron nitride ($h$-BN), we address the possibility of using these heterostructures for tailoring the properties of multilayer graphene by means of the electrostatic proximity effect. By using the combination of first-principles and large-scale tight-binding model c

Stanislaw Ambroszkiewicz, Waldemar Bartyna

We propose a simple protocol for Service Mesh management. The protocol specification consists of the formats of messages, and the actions taken by senders and recipients. The idea is that microservices of Cloud-Native Application should be also involved in configurations of their communication sessions. It does not interfere with the business logic of the mi

Tiep M. Hoang, Alireza Vahid, Hoang Duong Tuan, Lajos Hanzo

Security at the physical layer (PHY) is a salient research topic in wireless systems, and machine learning (ML) is emerging as a powerful tool for providing new data-driven security solutions. Therefore, the application of ML techniques to the PHY security is of crucial importance in the landscape of more and more data-driven wireless services. In this conte

Yabo Li, Hiroki Sukeno, Aswin Parayil Mana, Hendrik Poulsen Nautrup

Symmetry protected topological phases exhibit nontrivial short-ranged entanglement protected by symmetry and cannot be adiabatically connected to trivial product states while preserving the symmetry. In contrast, intrinsic topological phases do not need ordinary symmetry to stabilize them and their ground states exhibit long-range entanglement. It is known t

Junyu Wang, Shijie Wang, Ruijie Zhang, Zengqiang Zheng

We present RND-SCI, a novel framework for compressive hyperspectral image (HSI) reconstruction. Our framework decomposes the reconstructed object into range-space and null-space components, where the range-space part ensures the solution conforms to the compression process, and the null-space term introduces a deep HSI prior to constraining the output to hav

Alberto González-Sanz, Shayan Hundrieser

We establish weak limits for the empirical entropy regularized optimal transport cost, the expectation of the empirical plan and the conditional expectation. Our results require only uniform boundedness of the cost function and no smoothness properties, thus emphasizing the far-reaching regularizing nature of entropy penalization. To derive these results, we

Roberto Moretti, Marco Rossi, Matteo Biassoni, Andrea Giachero

The physics potential of massive liquid argon TPCs in the low-energy regime is still to be fully reaped because few-hits events encode information that can hardly be exploited by conventional classification algorithms. Machine learning (ML) techniques give their best in these types of classification problems. In this paper, we evaluate their performance agai

Luyan Yu, Jie-Xiang Yu, Jiadong Zang, Roger K. Lake

We theoretically show that the carrier transport in monolayer Fe3GeTe2 experiences a transition between anomalous Hall effect and spin Hall effect when the spin polarization of disorders switches between out-of-plane and in-plane. These Hall effects are allowed when the magnetization is polarized in-plane, breaking the C3 rotation symmetry. The transition or

Carolyn Abbott, Mark Hagen, Harry Petyt, Abdul Zalloum

We show that infinite cyclic subgroups of groups acting uniformly properly on injective metric spaces are uniformly undistorted. In the special case of hierarchically hyperbolic groups, we use this to study translation lengths for actions on the associated hyperbolic spaces. We then use quasimorphisms to produce examples where these latter results are sharp.