May 2023 arXiv papers — page 141

Andrey Ananev, Aleksey Khlyupin

This research paper addresses the stability of search algorithms in complex networks when dealing with incomplete information or uncertainty. We propose a theoretical model to investigate whether a global search algorithm with incomplete prior information can be outperformed by a stochastic greedy search on average. The model incorporates random variables to

Yige Chen, KyungTae Lim, Jungyeul Park

In the paper, we propose a novel way of improving named entity recognition in the Korean language using its language-specific features. While the field of named entity recognition has been studied extensively in recent years, the mechanism of efficiently recognizing named entities in Korean has hardly been explored. This is because the Korean language has di

Max Klabunde, Tobias Schumacher, Markus Strohmaier, Florian Lemmerich

Measuring similarity of neural networks to understand and improve their behavior has become an issue of great importance and research interest. In this survey, we provide a comprehensive overview of two complementary perspectives of measuring neural network similarity: (i) representational similarity, which considers how activations of intermediate layers di

Nivishree Palvannan, Chris Brown

Peer code reviews are crucial for maintaining the quality of the code in software repositories. Developers have introduced a number of software bots to help with the code review process. Despite the benefits of automating code review tasks, many developers face challenges interacting with these bots due to non-comprehensive feedback and disruptive notificati

Santhosh Ganapa

We will discuss various aspects of thermalization, chaos and hydrodynamics in one dimensional classical Hamiltonian systems. We study two problems. First, we will revisit the Fermi-Pasta-Ulam-Tsingou (FPUT) problem in order to understand what thermalization is and discuss what leads the system starting from a typical initial condition to a thermal state. Her

Kevin Levy, Srinivasan Raghunathan, Kaustuv Basu

Galaxy clusters induce a distinct dipole pattern in the cosmic microwave background (CMB) through the effect of gravitational lensing. Extracting this lensing signal will enable us to constrain cluster masses, even for high redshift clusters ($z \gtrsim 1$) that are expected to be detected by future CMB surveys. However, cluster-correlated foreground signals

Quentin G. Bailey

In this chapter, we discuss recent work on precision Earth laboratory tests of different aspects of gravity. In particular the discussion is focused on those tests that can be used to probe hypothesis for physics beyond Newtonian gravity and General Relativity. The latter includes tests of foundations like local Lorentz invariance, Weak-Equivalence Principle

Hassan Akbari, Dan Kondratyuk, Yin Cui, Rachel Hornung

We present Integrated Multimodal Perception (IMP), a simple and scalable multimodal multi-task training and modeling approach. IMP integrates multimodal inputs including image, video, text, and audio into a single Transformer encoder with minimal modality-specific components. IMP makes use of a novel design that combines Alternating Gradient Descent (AGD) an

Fatemeh P. A. Beik, Yousef Saad

This paper introduces the notion of tubular eigenvalues of third-order tensors with respect to T-products of tensors and analyzes their properties. A focus of the paper is to discuss relations between tubular eigenvalues and two alternative definitions of eigenvalue for third-order tensors that are known in the literature, namely eigentuple and T-eigenvalue.

Zhiguo Ding, Michael E. Zieve

We determine all permutations in two large classes of polynomials over finite fields, where the construction of the polynomials in each class involves the denominators of a class of rational functions generalizing the classical Redei functions. Our results generalize eight recent results from the literature, and our proofs of our more general results are muc

Xiaoshuai Wu, Xin Liao, Bo Ou

Malicious Deepfakes have led to a sharp conflict over distinguishing between genuine and forged faces. Although many countermeasures have been developed to detect Deepfakes ex-post, undoubtedly, passive forensics has not considered any preventive measures for the pristine face before foreseeable manipulations. To complete this forensics ecosystem, we thus pu

Richard Lieu, Chun-Hui Shi

The evolution of superhorizon curvature perturbations in a two-component interacting universe is considered. It is found that adiabatic modes conserve the total curvature perturbation $\zeta$, unless there are stages in which the rate of dissipation of one component into another is not constant. Moreover, our result shows that when the rate is varying it is

Sean K. Maden, Sang Ho Kwon, Louise A. Huuki-Myers, Leonardo Collado-Torres

Deconvolution of cell mixtures in "bulk" transcriptomic samples from homogenate human tissue is important for understanding the pathologies of diseases. However, several experimental and computational challenges remain in developing and implementing transcriptomics-based deconvolution approaches, especially those using a single cell/nuclei RNA-seq reference

Mateusz Gołębiewski, Riccardo Hertel, Vitaliy Vasyuchka, Mathias Weiler

A new concept in magnonics studies the dynamics of spin waves (SWs) in three-dimensional nanosystems. It is a natural evolution from conventionally used planar systems to explore magnetization configurations and dynamics in 3D nanostructures with lengths near intrinsic magnetic scales. In this work, we perform broadband ferromagnetic resonance (BBFMR) measur

Wanderlã L. Scopel, F. Crasto de Lima, Pedro H. Souza, José E. Padilha

Currently, solid interfaces composed of two-dimensional materials (2D) in contact with metal surfaces (m-surf) have been the subject of intense research, where the borophene bilayer (BBL) has been considered a prominent material for the development of electronic devices based on 2D platforms. In this work, we present a theoretical study of the energetic, str

Sijing Liu

We consider discontinuous Galerkin methods for an elliptic distributed optimal control problem and we propose multigrid methods to solve the discretized system. We prove that the $W$-cycle algorithm is uniformly convergent in the energy norm and is robust with respect to a regularization parameter on convex domains. Numerical results are shown for both $W$ -

Vassily Olegovich Manturov, Igor Mikhailovich Nikonov

We introduce a family of groups $\Gamma_n^k$ for integer parameters $n>k$. These groups originate from discussion of braid groups on $2$-surfaces. On the other hand, they turn out to be related to 3-manifolds (in particular, they lead to new relationships between braids and manifolds), triangulations (ideal triangulations) cluster algebras, dynamics of movin

Olaf Wysocki, Yan Xia, Magdalena Wysocki, Eleonora Grilli

Reconstructing semantic 3D building models at the level of detail (LoD) 3 is a long-standing challenge. Unlike mesh-based models, they require watertight geometry and object-wise semantics at the fa\c{c}ade level. The principal challenge of such demanding semantic 3D reconstruction is reliable fa\c{c}ade-level semantic segmentation of 3D input data. We prese

William Detmold, Fernando Romero-López, Phiala E. Shanahan

Finite-volume pionless effective field theory (FVEFT$_{ \pi\!/ }$) at next-to-leading order (NLO) is used to analyze the two-nucleon lattice QCD spectrum of Ref.~\cite{Amarasinghe:2021lqa}, performed at quark masses corresponding to a pion mass of approximately $800 $ MeV. Specifically, the effective theory is formulated in finite volume, and variational set

Michele Coppola, Zoubair Daouma, Malte Henkel

The quantum fluctuation-dissipation theorem is a central ingredient in the construction of quantum dynamics of Brownian motion which necessarily is non-Markovian. Yet, often Markovian approximations to quantum dynamics are studied in the literature. In this work, we investigate the limitations of the Markovian approximation within two paradigmatic models des

Xiang Yue, Boshi Wang, Ziru Chen, Kai Zhang

A recent focus of large language model (LLM) development, as exemplified by generative search engines, is to incorporate external references to generate and support its claims. However, evaluating the attribution, i.e., verifying whether the generated statement is fully supported by the cited reference, remains an open problem. Although human evaluation is c

Katherine Chworowsky, Steven L. Finkelstein, Justin S. Spilker, Gene C. K. Leung

We present a sample of 30 massive (log$(M_{\ast}/M_\odot) >11$) $z=3-5$ quiescent galaxies selected from the \textit{Spitzer-}HETDEX Exploratory Large Area (SHELA) Survey and observed at 1.1mm with Atacama Large Millimeter/submillimeter Array (ALMA) Band 6 observations. These ALMA observations would detect even modest levels of dust-obscured star-formation,

Tian-Wen Luo, Pin Yu

This is the second paper in a series studying the nonlinear stability of rarefaction waves in multi-dimensional gas dynamics. We construct initial data near singularities in the rarefaction wave region and, combined with the a priori energy estimates from the first paper, demonstrate that any smooth perturbation of constant states on one side of the diaphrag

Ahsi Lo, Gabriella Pangelinan, Michael C. King

As virtual and physical identity grow increasingly intertwined, the importance of privacy and security in the online sphere becomes paramount. In recent years, multiple news stories have emerged of private companies scraping web content and doing research with or selling the data. Images uploaded online can be scraped without users' consent or knowledge. Use

YuXuan Liu, Xi Chen, Pieter Abbeel

Instance segmentation is a fundamental skill for many robotic applications. We propose a self-supervised method that uses grasp interactions to collect segmentation supervision for an instance segmentation model. When a robot grasps an item, the mask of that grasped item can be inferred from the images of the scene before and after the grasp. Leveraging this

Raffaele Esposito, Rossana Marra

We consider a Hamiltonian system of particles, interacting through of a smooth pair potential. We look at the system on a space scale of order {\epsilon}^1, times of order {\epsilon}^2, and mean velocities of order {\epsilon}, with {\epsilon} a scale parameter, under initial conditions where the system is in a local Gibbs state with parameters corresponding

M. Nikhil Krishnan, Myna Vajha, Vinayak Ramkumar, P. Vijay Kumar

For a convolutional code in the presence of a symbol erasure channel, the information debt $I(t)$ at time $t$ provides a measure of the number of additional code symbols required to recover all message symbols up to time $t$. Information-debt-optimal streaming ($i$DOS) codes are convolutional codes which allow for the recovery of all message symbols up to $t

Nico Gubernari, Méril Reboud, Danny van Dyk, Javier Virto

We perform the first simultaneous dispersive analysis of the $B\to K$, $B\to K^*$, and $B_s\to \phi$ form factors. By means of an improved parametrization, we take into account the form factors' below-threshold branch cuts arising from on-shell $\bar{B}_s \pi^0$ and $\bar{B}_s \pi^0 \pi^0$ states, which so far have been ignored in the literature. In this way

Ehsan Kamalloo, Xinyu Zhang, Odunayo Ogundepo, Nandan Thakur

The ever-increasing size of language models curtails their widespread availability to the community, thereby galvanizing many companies into offering access to large language models through APIs. One particular type, suitable for dense retrieval, is a semantic embedding service that builds vector representations of input text. With a growing number of public

Chantal Shaib, Millicent L. Li, Sebastian Joseph, Iain J. Marshall

Large language models, particularly GPT-3, are able to produce high quality summaries of general domain news articles in few- and zero-shot settings. However, it is unclear if such models are similarly capable in more specialized, high-stakes domains such as biomedicine. In this paper, we enlist domain experts (individuals with medical training) to evaluate

Yuta Kuroda, Kunimasa Miyazaki

Some nonequilibrium systems exhibit anomalous suppression of the large-scale density fluctuations, so-called hyperuniformity. Recently, hyperuniformity was found numerically in a simple model of chiral active fluids [Q.-L. Lei et al., Sci. Adv. 5, eaau7423 (2019)]. We revisit this phenomenon and put forward a microscopic theory to explain it. An effective fl

Gennie Mansi, Mark Riedl

A core assumption of explainable AI systems is that explanations change what users know, thereby enabling them to act within their complex socio-technical environments. Despite the centrality of action, explanations are often organized and evaluated based on technical aspects. Prior work varies widely in the connections it traces between information provided

Macarena Arenas

We show that under suitable hypotheses, the second homotopy group of the coned-off space associated to a $C(9)$ cubical presentation is trivial, and use this to provide classifying spaces for proper actions for the fundamental groups of many quotients of square complexes admitting such cubical presentations. When the cubical presentations satisfy a condition

Lillian Muyama, Antoine Neuraz, Adrien Coulet

Clinical diagnosis guidelines aim at specifying the steps that may lead to a diagnosis. Inspired by guidelines, we aim to learn the optimal sequence of actions to perform in order to obtain a correct diagnosis from electronic health records. We apply various deep reinforcement learning algorithms to this task and experiment on a synthetic but realistic datas

Hongbo Zhang, Chen Tang, Tyler Loakman, Bohao Yang

Commonsense knowledge is crucial to many natural language processing tasks. Existing works usually incorporate graph knowledge with conventional graph neural networks (GNNs), resulting in a sequential pipeline that compartmentalizes the encoding processes for textual and graph-based knowledge. This compartmentalization does, however, not fully exploit the co

N. V. Filina, S. S. Baturin

We present the time dynamics of twisted quantum states. We find an explicit connection between the well-known stationary Landau state and an evolving twisted state, even when the Hamiltonian accounts for linear energy dissipation. Utilizing this unitary connection, we analyze nonstationary Landau states and unveil some of their properties. The proposed trans

Erica Weng, Hana Hoshino, Deva Ramanan, Kris Kitani

Multi-modal trajectory forecasting methods commonly evaluate using single-agent metrics (marginal metrics), such as minimum Average Displacement Error (ADE) and Final Displacement Error (FDE), which fail to capture joint performance of multiple interacting agents. Only focusing on marginal metrics can lead to unnatural predictions, such as colliding trajecto

Vadapalli Surya Prasanth, Arun K. Singh

This research article presents stress distribution and fracture analysis of a cantilever beam considering both continuum and lumped distribution of gravity force. Airy stress function is used to derive two-dimensional stress distribution using power series and boundary conditions. It is concluded that bending stress is the most dominant over other two stress

Patrizio Bifulco, Joachim Kerner

In this note we elaborate on some notions of surface area for discrete graphs which are closely related to the inverse degree. These notions then naturally lead to associated connectivity measures of graphs and to the definition of a special class of large graphs, called social graphs, that might prove interesting for applications. In addition, we derive spe

Elliot Chane-Sane, Cordelia Schmid, Ivan Laptev

The ability to specify robot commands by a non-expert user is critical for building generalist agents capable of solving a large variety of tasks. One convenient way to specify the intended robot goal is by a video of a person demonstrating the target task. While prior work typically aims to imitate human demonstrations performed in robot environments, here

Lukas Heidemann

Framed combinatorial topology is a recent approach to tame geometry which expresses higher-dimensional stratified spaces via tractable combinatorial data. The resulting theory of spaces is well-behaved and computable. In this paper we extend FCT by allowing labelling systems of meshes and trusses in $\infty$-categories, and build an alternative model of FCT

Abdallah Daddi-Moussa-Ider, Yuto Hosaka, Andrej Vilfan, Ramin Golestanian

Green's function plays an important role in many areas of physical sciences and is a prime tool for solving diverse hydrodynamic equations in the linear regime. In the present contribution, the axisymmetric low-Reynolds-number Brinkman flow induced by monopole and dipole singularities in proximity of a stationary plate of circular shape is theoretically inve

Joel Mabillard, Pierre Gaspard

The local-equilibrium approach to transport processes is related to the approach based on time-dependent correlation functions and their associated spectral functions characterizing the equilibrium fluctuations of particle, momentum and other densities. On the one hand, the transport coefficients are calculated with the Einstein-Helfand formulas derived in t

Leo Tsukada, Prathamesh Joshi, Shomik Adhicary, Richard George

Starting from May 2023, the LIGO Scientific, Virgo and KAGRA Collaboration is planning to conduct the fourth observing run with improved detector sensitivities and an expanded detector network including KAGRA. Accordingly, it is vital to optimize the detection algorithm of low-latency search pipelines, increasing their sensitivities to gravitational waves fr

Jan De Beule, Jonathan Mannaert, Valentino Smaldore

In this paper we develop non-existence results for $m$-ovoids in the classical polar spaces $Q^-(2r+1,q), W(2r-1,q)$ and $H(2r,q^2)$ for $r>2$. In [4] a lower bound on $m$ for the existence of $m$-ovoids of $H(4,q^2)$ is found by using the connection between $m$-ovoids, two-character sets, and strongly regular graphs. This approach is generalized in [3] for

Laura Garcia-Herrero, Stevo Lavrnic, Valentina Guerrieri, Attilio Toscano

Sustainable water management has become an urgent challenge due to irregular water availability patterns and water quality issues. The effect of climate change exacerbates this phenomenon in water-scarce areas, such as the Mediterranean region, stimulating the implementation of solutions aiming to mitigate or improve environmental, social, and economic condi

Thomas Jenrich

In 1933, Karol Borsuk asked whether each bounded set in the $n$-dimensional Euclidean space can be divided into $n$+1 parts of smaller diameter. Because it would not make sense otherwise, one usually assumes that he just forgot to require that the whole set contains at least two points. The hypothesis that the answer to that question is positive became famou

Yaozhong W. Qiu

We continue the program first initiated in [Geom. Funct. Anal. 26, 288-305 (2016)] and develop a modification of the technique introduced in that paper to study the spectral asymptotics, namely the Riesz means and eigenvalue counting functions, of functional difference operators $\smash{H_0 = \mathcal F^{-1} M_{\cosh(\xi)} \mathcal F}$ with potentials of the

Can Pu, Chuanyu Yang, Jinnian Pu, Radim Tylecek

Recovering an outdoor environment's surface mesh is vital for an agricultural robot during task planning and remote visualization. Our proposed solution is based on a newly-designed panoramic stereo camera along with a hybrid novel software framework that consists of three fusion modules. The panoramic stereo camera with a pentagon shape consists of 5 stereo

Subhrajit Sikdar

The current research work encompasses design modelling and fabrication of vertically aligned nanowire metal oxide semiconductor based voltage tunable quantum dot devices for optoelectronic applications. A novel device scheme is proposed for developing such VTQDs by combining the effects of nanowire geometry dependent structural confinement in transverse dire

Julien Béguinot, Yi Liu, Olivier Rioul, Wei Cheng

A common countermeasure against side-channel attacks on secret key cryptographic implementations is $d$th-order masking, which splits each sensitive variable into $d+1$ random shares. In this paper, maximal leakage bounds on the probability of success of any side-channel attack are derived for any masking order. Maximal leakage (Sibson's information of order

Fergus Hayes, Ik Siong Heng, Gavin Lamb, En-Tzu Lin

We present a novel fully Bayesian analysis to constrain short gamma-ray burst jet structures associated with cocoon, wide-angle and simple top-hat jet models, as well as the binary neutron star merger rate. These constraints are made given the distance and inclination information from GW170817, observed flux of GRB170817A, observed rate of short gamma-ray bu

Liam Cripwell, Joël Legrand, Claire Gardent

To date, most work on text simplification has focused on sentence-level inputs. Early attempts at document simplification merely applied these approaches iteratively over the sentences of a document. However, this fails to coherently preserve the discourse structure, leading to suboptimal output quality. Recently, strategies from controllable simplification

Kaya Alpturer, Joseph Y. Halpern, Ron van der Meyden

Work on \emph{optimal} protocols for \emph{Eventual Byzantine Agreement} (EBA) -- protocols that, in a precise sense, decide as soon as possible in every run and guarantee that all nonfaulty agents decide on the same value -- has focused on emph{full-information protocols} (FIPs), where agents repeatedly send messages that completely describe their past obse

Maria Vaz Pinto, Rafael H. Villarreal

This is a survey article featuring some of Wolmer Vasconcelos' contributions to commutative algebra, and explaining how Vasconcelos' work and insights have contributed to the development of commutative algebra and its interaction with other areas to the present. We discuss the Vasconcelos' function and the Vasconcelos' number (v-number for short) of graded i

John F. Barry, Matthew H. Steinecker, Scott T. Alsid, Jonah Majumder

Quantum sensing with solid-state spins offers the promise of high spatial resolution, bandwidth, and dynamic range at sensitivities comparable to more mature quantum sensing technologies, such as atomic vapor cells and superconducting devices. However, despite comparable theoretical sensitivity limits, the performance of bulk solid-state quantum sensors has

Abdelaziz Bounhar, Mireille Sarkiss, Michèle Wigger

This paper establishes the fundamental limits of a two-user single-receiver system where communication from User 1 (but not from User 2) needs to be undetectable to an external warden. Our fundamental limits show a tradeoff between the highest rates (or square-root rates) that are simultaneously achievable for the two users. Moreover, coded time-sharing for

Stefan Schacht

We review a new method in order to determine the parameter $\bar{\eta}$ of the Cabibbo-Kobayashi-Maskawa matrix from $K\rightarrow \mu^+\mu^-$ decays, using interference effects in the time-dependent decay rate. Furthermore, we discuss a new precision relation for the phase-shift of the time-dependent oscillation. The new methodology enables the discovery po

Shlomi Hillel, Ron Schreier, Noam Soker

We conduct a three-dimensional hydrodynamical simulation of a common envelope evolution (CEE) where a neutron star (NS) spirals-in inside the envelope of a red supergiant (RSG) star in a predetermined orbit. We find that the jets shed pairs of vortices in an expanding spiral pattern, inflate two expanding spirally-shaped low-density bubbles, one above and on

Luis E. Young-S., S. K. Adhikari

We study dipole-mode and scissors-mode oscillations of a harmonically-trapped dipolar supersolid, composed of dipolar droplets arranged on a one-dimensional (1D) or a two-dimensional (2D) lattice, to establish the robustness of its crystalline structure under translation and rotation, using a beyond-mean-field model including a Lee-Huang-Yang interaction. Th

Varadharajan Muruganandam, Manas Sajjan, Sabre Kais

Analyzing phase transitions using the inherent geometrical attributes of a system has garnered enormous interest over the past few decades. The usual candidate often used for investigation is graphene -- the most celebrated material among the family of tri co-ordinated graphed lattices. We show in this report that other inhabitants of the family demonstrate

Adam T. Stevenson, Carole A. Haswell, John R. Barnes, Joanna K. Barstow

We present additional HARPS radial velocity observations of the highly eccentric ($e \sim 0.6$) binary system DMPP-3AB, which comprises a K0V primary and a low-mass companion at the hydrogen burning limit. The binary has a $507$ d orbital period and a $1.2$ au semi-major axis. The primary component harbours a known $2.2$ M$_{\oplus}$ planet, DMPP-3A b, with

Phuong-Nam Nguyen

The discovery of biomarker sets for a targeted pathway is a challenging problem in biomedical medicine, which is computationally prohibited on classical algorithms due to the massive search space. Here, I present a quantum algorithm named QuantAnts Machine to address the task. The proposed algorithm is a quantum analog of the classical Ant Colony Optimizatio

Xiuwen Yang, Hajo Broersma, Ligong Wang

The $k$-th Laplacian spectral moment of a digraph $G$ is defined as $\sum_{i=1}^n \lambda_i^k$, where $\lambda_i$ are the eigenvalues of the Laplacian matrix of $G$ and $k$ is a nonnegative integer. For $k=2$, this invariant is better known as the Laplacian energy of $G$. We extend recently published results by characterizing the digraphs which attain the mi

Erica M. Porter, Christopher T. Franck, Stephen Adams

We propose a Bayesian model selection approach that allows medical practitioners to select among predictor variables while taking their respective costs into account. Medical procedures almost always incur costs in time and/or money. These costs might exceed their usefulness for modeling the outcome of interest. We develop Bayesian model selection that uses

Wael Mattar, Nir Sharon

Modeling data using manifold values is a powerful concept with numerous advantages, particularly in addressing nonlinear phenomena. This approach captures the intrinsic geometric structure of the data, leading to more accurate descriptors and more efficient computational processes. However, even fundamental tasks like compression and data enhancement present

Marco Aymone, Gopal Maiti, Olivier Ramaré, Priyamvad Srivastav

We study a certain class of arithmetic functions that appeared in Klurman's classification of $\pm 1$ multiplicative functions with bounded partial sums, c.f., Comp. Math. 153 (8), 2017, pp. 1622-1657. These functions are periodic and $1$-pretentious. We prove that if $f_1$ and $f_2$ belong to this class, then $\sum_{n\leq x}(f_1\ast f_2)(n)=\Omega(x^{1/4})$

Piyush J. Shah, Derek A. Bas, Abbass Hamadeh, Michael Wolf

The use of a complex ferromagnetic system to manipulate GHz surface acoustic waves is a rich current topic under investigation, but the high-power nonlinear regime is under-explored. We introduce focused surface acoustic waves, which provide a way to access this regime with modest equipment. Symmetry of the magneto-acoustic interaction can be tuned by interd

Johanna Kölbel, Moritz L. Anuschek, Ivonne Stelzl, Supawan Santitewagun

Terahertz time-domain spectroscopy and differential scanning calorimetry were used to study the role of the dynamics of biomolecules decoupled from solvent effects. Lyophilised sucrose exhibited steadily increasing absorption with temperature as anharmonic excitations commence as the system emerges from a deep minimum of the potential energy landscape where

Brayan Ferreira

We prove the existence of an elliptic Reeb orbit for some contact forms on the real projective three space $\mathbb{R} P^3$. The main ingredient of the proof is the existence of a distinguished pseudoholomorphic curve in the symplectization given by the $U$ map on ECH. Also, we check that the first value on the ECH spectrum coincides with the smallest action

Jacob K Goeree

General equilibrium, the cornerstone of modern economics and finance, rests on assumptions many markets do not meet. Spectrum auctions, electricity markets, and cap-and-trade programs for resource rights often feature non-convexities in preferences or production that can cause non-existence of Walrasian equilibrium and render general equilibrium vacuous. Yqu

Yakov Braver, Egidijus Anisimovas, Krzysztof Sacha

We demonstrate the possibility of using time-space crystalline structures to simulate eight-dimensional systems based on only two physical dimensions. A suitable choice of system parameters allows us to obtain a gapped energy spectrum, making topological effects become relevant. The nontrivial topology of the system is evinced by considering the adiabatic st

Amnon Yekutieli

We prove that a quasi-isomorphism $f : A \to B$ between commutative DG rings, where $B$ admits a divided power structure, can be factored as $f = \tilde{f} \circ e$, where $e : A \to \tilde{B}$ is a split injective quasi-isomorphism, and $\tilde{f} : \tilde{B} \to B$ is a surjective quasi-isomorphism. This result is used in our work on a DG approach to the c

Saeedeh Mokarian Zanjani, Sadra Sadeghi, Afshin Shahalizad, Majid Pahlevani

The aerobic and thermal stability of quantum-dot light-emitting diodes (QLEDs) is an important factor for the practical applications of these devices under harsh environmental conditions. In this paper, we demonstrate all-solution-processed amber QLEDs with an external quantum efficiency (EQE) of >14% with almost negligible efficiency roll-off (droop) and a

Thays Guerra Araujo Duarte, Srinivasan Arunachalam, Arthriya Subgranon, Seymour M J Spence

The simulation of stochastic wind loads is necessary for many applications in wind engineering. The proper orthogonal decomposition (POD)-based spectral representation method is a popular approach used for this purpose due to its computational efficiency. For general wind directions and building configurations, the data-driven POD-based stochastic model is a

Minheng Chen, Zhirun Zhang, Shuheng Gu, Youyong Kong

We present a novel deep learning-based framework: Embedded Feature Similarity Optimization with Specific Parameter Initialization (SOPI) for 2D/3D medical image registration which is a most challenging problem due to the difficulty such as dimensional mismatch, heavy computation load and lack of golden evaluation standard. The framework we design includes a

Wodson Mendson

We investigate the structure of the $p$-divisor for the Jouanolou foliation where we show, under some conditions, that it can be irreducible or has a $p$-factor. We study the reduction modulo $p$ of foliations on the projective plane and its applications to the problems of holomorphic foliations. We give new proof, via reduction modulo $2$, of the fact that

Shaocheng Liu, Qi Chen

Characterization of entropy functions is of fundamental importance in information theory. By imposing constraints on their Shannon outer bound, i.e., the polymatroidal region, one obtains the faces of the region and entropy functions on them with special structures. In this series of two papers, we characterize entropy functions on the 2-dimensional faces of

Lin Wang, Jiasheng Wu, Yue Gao, Jingjing Zhang

Cloud native technology has revolutionized 5G beyond and 6G communication networks, offering unprecedented levels of operational automation, flexibility, and adaptability. However, the vast array of cloud native services and applications presents a new challenge in resource allocation for dynamic cloud computing environments. To tackle this challenge, we inv

Louise Desplat, Bertrand Dupé

We explore the interplay between topology and eigenmodes by changing the stabilizing mechanism of skyrmion lattices (skX). We focus on two prototypical ultrathin films hosting an hexagonal (Pd/Fe/Ir(111)) and a square (Fe/Ir(111)) skyrmion lattice, which can both be described by an extended Heisenberg Hamiltonian. We first examine whether the Dzyaloshinkskii

Hanwen Deng, Weijia Zhang, Min-Ling Zhang

Label noise widely exists in large-scale datasets and significantly degenerates the performances of deep learning algorithms. Due to the non-identifiability of the instance-dependent noise transition matrix, most existing algorithms address the problem by assuming the noisy label generation process to be independent of the instance features. Unfortunately, n

Anton Bouter, Peter A. N. Bosman

Exploiting knowledge about the structure of a problem can greatly benefit the efficiency and scalability of an Evolutionary Algorithm (EA). Model-Based EAs (MBEAs) are capable of doing this by explicitly modeling the problem structure. The Gene-pool Optimal Mixing Evolutionary Algorithm (GOMEA) is among the state-of-the-art of MBEAs due to its use of a linka

Sergio Sanchez Cruz

A search for new physics in top quark production with additional final-state leptons is performed with 138 $\mathrm{fb}^{-1}$ of proton-proton collision data at $\sqrt{s}$ = 13 TeV. We use the framework of effective field theory to parametrize potential new physics effects in terms of 26 dimension-six EFT operators. The data are divided into several categori

Chakkrit Termritthikun, Ayaz Umer, Suwichaya Suwanwimolkul, Feng Xia

Automated multi-label chest X-rays (CXR) image classification has achieved substantial progress in clinical diagnosis via utilizing sophisticated deep learning approaches. However, most deep models have high computational demands, which makes them less feasible for compact devices with low computational requirements. To overcome this problem, we propose a kn

Samuel Matloob, Partha P. Datta, O. Patrick Kreidl, Ayan Dutta

Recent developments in robotic and sensor hardware make data collection with mobile robots (ground or aerial) feasible and affordable to a wide population of users. The newly emergent applications, such as precision agriculture, weather damage assessment, or personal home security often do not satisfy the simplifying assumptions made by previous research: th

Xiaosong Jia, Penghao Wu, Li Chen, Jiangwei Xie

End-to-end autonomous driving has made impressive progress in recent years. Existing methods usually adopt the decoupled encoder-decoder paradigm, where the encoder extracts hidden features from raw sensor data, and the decoder outputs the ego-vehicle's future trajectories or actions. Under such a paradigm, the encoder does not have access to the intended be

T. Masłowski, N. Sedlmayr

Dynamical quantum phase transitions occur in dynamically evolving quantum systems when non-analyticities occur at critical times in the return rate, a dynamical analogue of the free energy. This extension of the concept of phase transitions can be brought into contact with another, namely that of topological phase transitions in which the phase transition is

Eliza M. -R. Kempton, Michael Zhang, Jacob L. Bean, Maria E. Steinrueck

There are no planets intermediate in size between Earth and Neptune in our Solar System, yet these objects are found around a substantial fraction of other stars. Population statistics show that close-in planets in this size range bifurcate into two classes based on their radii. It is hypothesized that the group with larger radii (referred to as "sub-Neptune

Charles Elbar, Benoît Perthame, Andrea Poiatti, Jakub Skrzeczkowski

The link between compressible models of tissue growth and the Hele-Shaw free boundary problem of fluid mechanics has recently attracted a lot of attention. In most of these models, only repulsive forces and advection terms are taken into account. In order to take into account long range interactions, we include for the first time a surface tension effect by

Adam D. Barwell, Ping Hou, Nobuko Yoshida, Fangyi Zhou

Session types provide a typing discipline for message-passing systems. However, most session type approaches assume an ideal world: one in which everything is reliable and without failures. Yet this is in stark contrast with distributed systems in the real world. To address this limitation, we introduce Teatrino, a code generation toolchain that utilises asy

Ngoc Nhi Nguyen

We study grand-canonical interacting fermionic systems in the mean-field regime, in a trapping potential. We provide the first order term of integrated and pointwise Weyl laws, but in the case with interaction. More precisely, we prove the convergence of the densities of the grand-canonical Hartree-Fock ground state to the Thomas-Fermi ground state in the se

Mohammad Mashayekhi, Sara Ahmadi Majd, Arian Amiramjadi, Babak Mashayekhi

X-ray images are the first steps for diagnosing and further treating dental problems. So, early diagnosis prevents the development and increase of oral and dental diseases. In this paper, we developed a semantic segmentation algorithm based on BEIT adaptor and Mask2Former to detect and identify teeth, roots, and multiple dental diseases and abnormalities suc

Xinjie He, Tomasz Tkocz, Katarzyna Wyczesany

We prove that the tail probabilities of sums of independent uniform random variables, up to a multiplicative constant, are dominated by the Gaussian tail with matching variance and find the sharp constant for such stochastic domination.

Robert E. Gaunt, Heather Sutcliffe

We obtain bounds to quantify the distributional approximation in the delta method for vector statistics (the sample mean of $n$ independent random vectors) for normal and non-normal limits, measured using smooth test functions. For normal limits, we obtain bounds of the optimal order $n^{-1/2}$ rate of convergence, but for a wide class of non-normal limits,

Süleyman Aslan, Brandon Yushan Feng, Amitabh Varshney

We present a novel technique for implicit neural representation of light fields at continuously defined viewpoints with high quality and fidelity. Our implicit neural representation maps 4D coordinates defining two-plane parameterization of the light fields to the corresponding color values. We leverage periodic activations to achieve high expressivity and a

Alexander Mielke, Tomas Roubicek, Ulisse Stefanelli

We present a dynamic model for inhomogeneous viscoelastic media at finite strains. The model features a Kelvin-Voigt rheology, and includes a self-generated gravitational field in the actual evolving configuration. In particular, a fully Eulerian approach is adopted. We specialize the model to viscoelastic (barotropic) fluids and prove existence and a certai

Brian Colquhoun, Laurence J. Cooper, Christine T. H. Davies, G. Peter Lepage

We calculate the decay rates for $\eta_c \to \gamma \gamma$, $J/\psi \to \gamma \eta_c$ and $J/\psi \to \eta_c e^+e^-$ in lattice QCD with $u$, $d$, $s$ and $c$ quarks in the sea for the first time. We improve significantly on previous theory calculations to achieve accuracies of 1--2\%, giving lattice QCD results that are now more accurate than the experime

William Kengne, Modou Wade

This paper carries out sparse-penalized deep neural networks predictors for learning weakly dependent processes, with a broad class of loss functions. We deal with a general framework that includes, regression estimation, classification, times series prediction, $\cdots$ The $\psi$-weak dependence structure is considered, and for the specific case of bounded

A. F. Andreev, L. A. Melnikovsky

Superfluidity in Fermi systems is not destroyed by a flow exceeding the Landau velocity threshold. The overcritical state acquires normal component even at zero temperature. We explore peculiar hydrodynamics of this system and discover two sound modes, for which the explicit universal dispersion relations are provided.

David Carrascal, Elisa Rojas, Diego Lopez-Pajares

Although the complete scope of the sixth generation of mobile technologies (6G) is still unclear, the prominence of the Internet of Things (IoT) and Artificial Intelligence (AI) / Machine Learning (ML) in the networking field is undeniable. In this regard, key technology enablers for the previous generation, 5G, such as software-defined networking and networ