November 2022 arXiv papers — page 39

Cheng Feng, Pingge Hu

In the research area of anomaly detection, novel and promising methods are frequently developed. However, most existing studies exclusively focus on the detection task only and ignore the interpretability of the underlying models as well as their detection results. Nevertheless, anomaly interpretation, which aims to provide explanation of why specific data i

Michael J. Wilensky, Jordan Brown, Bryna J. Hazelton

We explore error distributions in Epoch of Reionization 21-cm power spectrum estimators using a combination of mathematical analysis and numerical simulations. We provide closed form solutions for the error distributions of individual bins in 3d-power spectra for two estimators currently in use in the field, which we designate as ``straight-square" and ``cro

Mikhail K. Volkov, K. Nurlan

The branching fractions of $\tau$ lepton decays with the production of strange scalar mesons both in the ground and first radially excited states $\tau \to \nu_\tau [K^*_0(700), K^*_0(1430)]$ and $\tau \to \nu_\tau [K^*_0(700)\pi, K^*_0(1430)\pi, K^*_0(700) K, K^*_0 (700)\eta]$ are calculated in the extended $U(3) \times U(3)$ chiral quark NJL model. All mes

Natalia Markovich

A network evolution with predicted tail and extremal indices of PageRank and the Max-Linear Model used as node influence indices in random graphs is considered. The tail index shows a heaviness of the distribution tail. The extremal index is a measure of clustering (or local dependence) of the stochastic process. The cluster implies a set of consecutive exce

Fariba Armandoust, Ehsan Tohidi, Martin Kasparick, Li Wang

Reconfigurable antennas (RAs) are a promising technology to enhance the capacity and coverage of wireless communication systems. However, RA systems have two major challenges: (i) High computational complexity of mode selection, and (ii) High overhead of channel estimation for all modes. In this paper, we develop a low-complexity iterative mode selection alg

Zisong Xu, Rafael Papallas, Mehmet Dogar

We propose a method to track the 6D pose of an object over time, while the object is under non-prehensile manipulation by a robot. At any given time during the manipulation of the object, we assume access to the robot joint controls and an image from a camera. We use the robot joint controls to perform a physics-based prediction of how the object might be mo

Byunghyun Ban, Jejong Lee, Hyeonmok Hwang

A text-mining-based word class categorization method and LSTM-based vocabulary pattern prediction method are introduced in this paper. A preprocessing method based on simple text appearance frequency analysis is first described. This method was developed as a data screening tool but showed 4.35 ~ 6.21 times higher than previous works. An LSTM deep learning m

Kira Bangert, Georg Dolzmann

Existence and uniqueness of solutions for a class of models for stress-modulated growth is proven in one spatial dimension. The model features the multiplicative decomposition of the deformation gradient $F$ into an elastic part $F_e$ and a growth-related part $G$. After the transformation due to the growth process, governed by $G$, an elastic deformation de

László Tóth

In this paper we study sums of Dirichlet series whose coefficients are terms of the Thue-Morse sequence and variations thereof. We find closed-form expressions for such sums in terms of known constants and functions including the Riemann zeta function and the Dirichlet eta function using elementary methods.

A A Watson

The origins of the series of European Cosmic-Ray Symposia are briefly described. The first meeting in the series, on Hadronic Interactions and Extensive Air Showers, held in Lodz, Poland in 1968, was attended by the author: some memories are recounted.

Yotam Dikstein

We present a new construction of high dimensional expanders based on covering spaces of simplicial complexes. High dimensional expanders (HDXs) are hypergraph analogues of expander graphs. They have many uses in theoretical computer science, but unfortunately only few constructions are known which have arbitrarily small local spectral expansion. We give a ra

Théo Delemazure, Tom Demeulemeester, Manuel Eberl, Jonas Israel

In party-approval multiwinner elections the goal is to allocate the seats of a fixed-size committee to parties based on the approval ballots of the voters over the parties. In particular, each voter can approve multiple parties and each party can be assigned multiple seats. Two central requirements in this setting are proportional representation and strategy

Alexander Gasnikov, Darina Dvinskikh, Pavel Dvurechensky, Eduard Gorbunov

This review presents modern gradient-free methods to solve convex optimization problems. By gradient-free methods, we mean those that use only (noisy) realizations of the objective value. We are motivated by various applications where gradient information is prohibitively expensive or even unavailable. We mainly focus on three criteria: oracle complexity, it

Jaš Bensa, Marko Žnidarič

We study purity decay -- a measure of bipartite entanglement -- in a chain of $n$ qubits under the action of various geometries of nearest-neighbor random two-site unitary gates. We use a Markov chain description of average purity evolution, using further reduction to obtain a transfer matrix of only polynomial dimension in $n$. In most circuits, an exceptio

Jiawei Mao, Guangyi Zhao, Yuanqi Chang, Xuesong Yin

Facial expression recognition (FER) plays a significant role in the ubiquitous application of computer vision. We revisit this problem with a new perspective on whether it can acquire useful representations that improve FER performance in the image generation process, and propose a novel generative method based on the image inversion mechanism for the FER ta

Pablo Carrasco, Rodrigo Hernández

The main purpose of this paper is to obtain sharp bounds of the norm of Schwarzian derivative for convex mappings of order $alpha$ in terms of the value of $f''(0)$, in particular, when this quantity is equal to zero. In addition, we obtain sharp bounds for distortion and growth for this mappings and we generalized the results obtained by Suita and Yamashita

Sen Zou, Shuai Lu, Boxi Xu

We investigate the increasing stability of the inverse Schr\"{o}dinger potential problem with integer power type nonlinearities at a large wavenumber. By considering the first order linearized system with respect to the unknown potential function, a combination formula of the first order linearization is proposed, which provides a Lipschitz type stability fo

Dongmin Gang, Dongyeob Kim

By applying the recently proposed (3D rank-0 $\mathcal{N}$=4 SCFT)/(non-unitary TQFTs) correspondence to S-fold SCFTs, we construct an exotic class of non-unitary TQFTs labelled by an integer $k\geq 3$. The SCFTs are obtained by gauging diagonal $SU(2)$ subgroup of $T[SU(2)]$ theory with Chern-Simons level $k$. We give the explicit expression for modular dat

A. Seza Doğruöz, Gabriel Skantze

Open-domain chatbots are supposed to converse freely with humans without being restricted to a topic, task or domain. However, the boundaries and/or contents of open-domain conversations are not clear. To clarify the boundaries of "openness", we conduct two studies: First, we classify the types of "speech events" encountered in a chatbot evaluation data set

Luis C. García-Lirola, Guillaume Grelier, Gonzalo Martínez-Cervantes, Abraham Rueda Zoca

We prove that, given two Banach spaces $X$ and $Y$ and bounded, closed convex sets $C\subseteq X$ and $D\subseteq Y$, if a nonzero element $z\in \overline{\mathrm{co}}(C\otimes D)\subseteq X\widehat{\otimes}_\pi Y$ is a preserved extreme point then $z=x_0\otimes y_0$ for some preserved extreme points $x_0\in C$ and $y_0\in D$, whenever $K(X,Y^*)$ separates p

Sonja Hohloch, Guner Muarem

In this paper, we provide tools to study the dynamics of point vortex dynamics on $\mathbb{CP}^n$ and the flag manifold $\mathbb{F}_{1,2}(\mathbb{C}^3)$. These are the only K\"ahler twistor spaces arising from 4-manifolds. We give an explicit expression for Green's function on $\mathbb{CP}^n$ which enables us to determine the Hamiltonian $H$ and the equation

Hartwig Fronthaler, Klaus Kollreider, Josef Bigun, Julian Fierrez

Signal-quality awareness has been found to increase recognition rates and to support decisions in multisensor environments significantly. Nevertheless, automatic quality assessment is still an open issue. Here, we study the orientation tensor of fingerprint images to quantify signal impairments, such as noise, lack of structure, blur, with the help of symmet

Minbo Yang, Weiwei Ye, Shuijin Zhang

In this paper, we study the existence of solutions for a critical time-harmonic Maxwell equation in nonlocal media. By introducing some suitable Coulomb spaces involving curl operator, we are able to obtain the ground state solutions of the curl-curl equation via the method of constraining Nehari-Pankov manifold. Correspondingly, some sharp constants of the

Shu Ma, Weifeng Qiu, Xiaofeng Yang

The optimal error estimate that depending only on the polynomial degree of $ \varepsilon^{-1}$ is established for the temporal semi-discrete scheme of the Cahn-Hilliard equation, which is based on the scalar auxiliary variable (SAV) formulation. The key to our analysis is to convert the structure of the SAV time-stepping scheme back to a form compatible with

Fernando Alonso-Fernandez, Julian Fierrez, Daniel Ramos, Joaquin Gonzalez-Rodriguez

As biometric technology is increasingly deployed, it will be common to replace parts of operational systems with newer designs. The cost and inconvenience of reacquiring enrolled users when a new vendor solution is incorporated makes this approach difficult and many applications will require to deal with information from different sources regularly. These in

Andreas Osterloh, Juan Polo, Wayne J. Chetcuti, Luigi Amico

We consider a gas of repulsive $N$-component fermions confined in a ring-shaped potential, subject to an effective magnetic field. For large repulsion strengths, we work out a Bethe ansatz scheme to compute the two-point correlation matrix and then the one-particle density matrix. Our results holds in the mesoscopic regime of finite but sufficiently large nu

Yoichiro Hanaoka

We developed an automated method for sunspot detection using digital white-light solar images to achieve a performance similar to that of visual drawing observations in sunspot counting. To identify down to small, isolated spots correctly, we pay special attention to the accurate derivation of the quiet-disk component of the Sun, which is used as a reference

Sergio Izquierdo, Javier Civera

Estimating a dense depth map from a single view is geometrically ill-posed, and state-of-the-art methods rely on learning depth's relation with visual appearance using deep neural networks. On the other hand, Structure from Motion (SfM) leverages multi-view constraints to produce very accurate but sparse maps, as matching across images is typically limited b

Dmitry V. Gugnin

We obtain all coset $n$-valued topological groups on $S^3$ and $\mathbb{R}P^3$, arising from compact Lie groups Sp(1) and SO(3) and there finite groups of automorphisms.

Yuan Mao, Zheng-Chu Guo

In recent years, functional linear models have attracted growing attention in statistics and machine learning, with the aim of recovering the slope function or its functional predictor. This paper considers online regularized learning algorithm for functional linear models in reproducing kernel Hilbert spaces. Convergence analysis of excess prediction error

Ho V. N. Phuong, Quang Hoa Tran

A standard graded artinian monomial complete intersection algebra $A=\Bbbk[x_1,x_2,\ldots,x_n]/(x_1^{a_1},x_2^{a_2},\ldots,x_n^{a_n})$, with $\Bbbk$ a field of characteristic zero, has the strong Lefschetz property due to Stanley in 1980. In this paper, we give a new proof for this result by using only the basic properties of linear algebra. Furthermore, our

Ana Niño-López, Salvador Chulián, Álvaro Martínez-Rubio, Cristina Blázquez-Goñi

Acute Lymphoblastic Leukemia (ALL) accounts for the 80% of leukemias when coming down to pediatric ages. Survival of these patients has increased by a considerable amount in recent years. However, around 15-20% of treatments are unsuccessful. For this reason, it is definitely required to come up with new strategies to study and select which patients are at h

Zhichuang Liang, Yunlei Zhao

Number theoretic transform (NTT) is the most efficient method for multiplying two polynomials of high degree with integer coefficients, due to its series of advantages in terms of algorithm and implementation, and is consequently widely-used and particularly fundamental in the practical implementations of lattice-based cryptographic schemes. Especially, rece

Ksenia Bestuzheva, Ambros Gleixner, Tobias Achterberg

The reformulation-linearization technique (RLT) is a prominent approach to constructing tight linear relaxations of non-convex continuous and mixed-integer optimization problems. The goal of this paper is to extend the applicability and improve the performance of RLT for bilinear product relations. First, a method for detecting bilinear product relations imp

Jérémie Lasue, Pierre Bousquet, Michel Blanc, Nicolas André

This chapter reviews for each province and destination of the Solar System the representative space missions that will have to be designed and implemented by 2061 to address the six key science questions about the diversity, origins, workings and habitability of planetary systems (described in chapter 1) and to perform the critical observations that have bee

William Dorrell, Maria Yuffa, Peter Latham

Training data is always finite, making it unclear how to generalise to unseen situations. But, animals do generalise, wielding Occam's razor to select a parsimonious explanation of their observations. How they do this is called their inductive bias, and it is implicitly built into the operation of animals' neural circuits. This relationship between an observ

Rojo Randrianomentsoa, Hans van Ditmarsch, Roman Kuznets

Combinatorial topology is used in distributed computing to model concurrency and asynchrony. The basic structure in combinatorial topology is the simplicial complex, a collection of subsets called simplices of a set of vertices, closed under containment. Pure simplicial complexes describe message passing in asynchronous systems where all processes (agents) a

Rishabh Gupta, Ashutosh Kumar Singh

Nowadays, more and more machine learning applications, such as medical diagnosis, online fraud detection, email spam filtering, etc., services are provided by cloud computing. The cloud service provider collects the data from the various owners to train or classify the machine learning system in the cloud environment. However, multiple data owners may not en

Ping Liu, Yanchen He, Habib Ammari

A priori information on the positivity of source intensities is ubiquitous in imaging fields and is also important for a multitude of super-resolution and deconvolution algorithms. However, the fundamental resolution limit of positive sources is still unknown, and research in this field is very limited indeed. In this work, we analyze the super-resolving cap

Robert Denk, David Ploß, Sophia Rau, Jörg Seiler

We consider linear boundary value problems for higher-order parameter-elliptic equations, where the boundary data do not belong to the classical trace spaces. We employ a class of Sobolev spaces of mixed smoothness that admits a generalized boundary trace with values in Besov spaces of negative order. We prove unique solvability for rough boundary data in th

Aritra Laha, Santosh Kumar

Multiple input multiple output (MIMO) approach in fiber optical communication has emerged as an effective proposition to address the ever increasing demand for information exchange. In the ergodic case, the multiple channels, associated with multiple modes or cores or both in the optical fiber, is modeled by the Jacobi ensemble of random matrices. A key quan

Muhittin Evren Aydin

In this short note, we investigate the effect of the local fractional derivatives on the Riemann curvature tensor that is a common tool in calculating curvature of a Riemannian manifold. For this, first we introduce a general local fractional derivative operator that involves the mostly used ones in the literature as conformable, alternative, truncated $M-$

John Fernley

The voter model is a classical interacting particle system, modelling how global consensus is formed by local imitation. We analyse the time to consensus for a particular family of voter models when the underlying structure is a scale-free inhomogeneous random graph, in the high edge density regime where this graph features a giant component. In this regime,

Andrea Vicari, Nana Obayashi, Francesco Stella, Gaetan Raynaud

The success of soft robots in displaying emergent behaviors is tightly linked to the compliant interaction with the environment. However, to exploit such phenomena, proprioceptive sensing methods which do not hinder their softness are needed. In this work we propose a new sensing approach for soft underwater slender structures based on embedded pressure sens

Seonhye Park, Alsharif Abuadbba, Shuo Wang, Kristen Moore

Training deep neural networks (DNNs) requires large datasets and powerful computing resources, which has led some owners to restrict redistribution without permission. Watermarking techniques that embed confidential data into DNNs have been used to protect ownership, but these can degrade model performance and are vulnerable to watermark removal attacks. Rec

Qi Li, Yuzhu Han, Jian Wang

\ In this paper, the following biharmonic elliptic problem \begin{eqnarray*} \begin{cases} \Delta^2u-\lambda\frac{|u|^{q-2}u}{|x|^s}=|u|^{2^{**}-2}u+ f(x,u), &x\in\Omega,\\ u=\dfrac{\partial u}{\partial n}=0, &x\in\partial\Omega \end{cases} \end{eqnarray*} is considered. The main feature of the equation is that it involves a Hardy term and a nonlinearity wit

Harm Lameris, Shivam Mehta, Gustav Eje Henter, Joakim Gustafson

Spontaneous speech has many affective and pragmatic functions that are interesting and challenging to model in TTS. However, the presence of reduced articulation, fillers, repetitions, and other disfluencies in spontaneous speech make the text and acoustics less aligned than in read speech, which is problematic for attention-based TTS. We propose a TTS archi

Andreas Klingler, Mirte van der Eyden, Sebastian Stengele, Tobias Reinhart

Several physically inspired problems have been proven undecidable; examples are the spectral gap problem and the membership problem for quantum correlations. Most of these results rely on reductions from a handful of undecidable problems, such as the halting problem, the tiling problem, the Post correspondence problem or the matrix mortality problem. All the

A. A. Kopasov, I. M. Tsar'kov, A. S. Mel'nikov

We study the features of the superconductivity nucleation and vortex configurations in superconductors with modulated disorder. Using the Ginzburg-Landau-type theory with spatially varying diffusion coefficient, we uncover and explain the switching between the vortex-defect attraction to the repulsion upon the increase in the external magnetic field. It is s

Antonio Papangelo, Michele Ciavarella

We show that the detachment of a flat punch from a viscoelastic substrate has a relatively simple behavior, framed between the Kendall's elastic solution at the relaxed modulus and at the instantaneous modulus, and the cohesive strength limit. We find hardly any dependence of the pull-off force on the details of the loading process, including maximum indenta

Yecheol Kim, Konyul Park, Minwook Kim, Dongsuk Kum

Fusing data from cameras and LiDAR sensors is an essential technique to achieve robust 3D object detection. One key challenge in camera-LiDAR fusion involves mitigating the large domain gap between the two sensors in terms of coordinates and data distribution when fusing their features. In this paper, we propose a novel camera-LiDAR fusion architecture calle

Danila Amoroso, Bertrand Dupe, Matthieu J. Verstraete

Magnetic rare-earth orthoferrites $R$FeO$_3$ host a variety of functional properties from multiferroicity and strong magnetostriction, to spin-reorientation transitions and ultrafast light-driven manipulation of magnetism, which can be exploited in spintronics and next-generation devices. Among these systems, SmFeO$_3$ is attracting a particular interest for

Pierre Colombo, Eduardo D. C. Gomes, Guillaume Staerman, Nathan Noiry

Deep learning methods have boosted the adoption of NLP systems in real-life applications. However, they turn out to be vulnerable to distribution shifts over time which may cause severe dysfunctions in production systems, urging practitioners to develop tools to detect out-of-distribution (OOD) samples through the lens of the neural network. In this paper, w

Wei Lin, Muhammad Jehanzeb Mirza, Mateusz Kozinski, Horst Possegger

Although action recognition systems can achieve top performance when evaluated on in-distribution test points, they are vulnerable to unanticipated distribution shifts in test data. However, test-time adaptation of video action recognition models against common distribution shifts has so far not been demonstrated. We propose to address this problem with an a

Ali Sahraee

Spectre attacks exploit speculative execution to leak sensitive information. In the last few years, a number of static side-channel detectors have been proposed to detect cache leakage in the presence of speculative execution. However, these techniques either ignore branch prediction mechanism, detect static pre-defined patterns which is not suitable for det

Christoph Laaber, Tao Yue, Shaukat Ali

Ensuring that software performance does not degrade after a code change is paramount. A solution is to regularly execute software microbenchmarks, a performance testing technique similar to (functional) unit tests, which, however, often becomes infeasible due to extensive runtimes. To address that challenge, research has investigated regression testing techn

Yinhuai Wang, Yujie Hu, Jiwen Yu, Jian Zhang

Consistency and realness have always been the two critical issues of image super-resolution. While the realness has been dramatically improved with the use of GAN prior, the state-of-the-art methods still suffer inconsistencies in local structures and colors (e.g., tooth and eyes). In this paper, we show that these inconsistencies can be analytically elimina

Floriana Ciaglia, Francesco Saverio Zuppichini, Paul Guerrie, Mark McQuade

The evaluation of object detection models is usually performed by optimizing a single metric, e.g. mAP, on a fixed set of datasets, e.g. Microsoft COCO and Pascal VOC. Due to image retrieval and annotation costs, these datasets consist largely of images found on the web and do not represent many real-life domains that are being modelled in practice, e.g. sat

Johanna Wydra, Robin Größle, Alexander Marsteller, Michael Sturm

Experimental values for the viscosity of the radioactive hydrogen isotopologue tritium are still unknown in literature. Existing values from ab initio calculations disregard quantum mechanic effects and are therefore only good approximations for room temperature and above. To fill in these missing experimental values, a measurement setup has been designed, t

Takato Tokuno, Takeru K. Suzuki, Munehito Shoda

We investigate the role of latitudinal differential rotation (DR) in the spin evolution of solar-type stars. Recent asteroseismic observation detected the strong equator-fast DR in some solar-type stars. Numerical simulations show that the strong equator-fast DR is a typical feature of young fast-rotating stars and that this tendency is gradually reduced wit

H. Wells, M. E. Hubbard, A. Cangiani

We present a velocity-based moving mesh virtual element method for the numerical solution of PDEs involving moving boundaries. The virtual element method is used for computing both the mesh velocity and a conservative Arbitrary Lagrangian-Eulerian solution transfer on general polygonal meshes. The approach extends the linear finite element method to polygona

V. V. Anashin, O. V. Anchugov, A. V. Andrianov, K. V. Astrelina

We present the study of the decay $J/\psi \rightarrow \rho\pi$. The results are based on of 5.2~million $J/\psi$ events collected by the KEDR detector at the VEPP-4M collider. The branching fractions are measured to be $\B(J/\psi \rightarrow \rho\pi) = \big(2.072\pm 0.017 \pm 0.062 \big)\cdot 10^{-2}$ and $\B(J/\psi \rightarrow \pi^+\pi^-\pi^0) = \big(1.878

Fan Yang, Shigeyuki Odashima, Shoichi Masui, Shan Jiang

We propose a Cascaded Buffered IoU (C-BIoU) tracker to track multiple objects that have irregular motions and indistinguishable appearances. When appearance features are unreliable and geometric features are confused by irregular motions, applying conventional Multiple Object Tracking (MOT) methods may generate unsatisfactory results. To address this issue,

Yi Chen, Austin Baty, Dennis Perepelitsa, Christopher McGinn

We present the first anti-k$_{T}$ jet spectrum and substructure measurements using the archived ALEPH $e^+e^-$ data taken in 1994 at a center of mass energy of $\sqrt{s} = 91.2$ GeV. Jets are reconstructed with the anti-k$_{T}$ algorithm with a resolution parameter of 0.4. It is the cleanest test of jets and QCD without the complication of hadronic initial s

Haiyang Yu, Jingye Chen, Bin Li, Xiangyang Xue

The flourishing blossom of deep learning has witnessed the rapid development of Chinese character recognition. However, it remains a great challenge that the characters for testing may have different distributions from those of the training dataset. Existing methods based on a single-level representation (character-level, radical-level, or stroke-level) may

Jack White, Karel Adamek, Wes Armour

Using the Fourier Domain Acceleration Search (FDAS) method to search for binary pulsars is a computationally costly process. Next generation radio telescopes will have to perform FDAS in real time, as data volumes are too large to store. FDAS is a matched filtering approach for searching time-domain radio astronomy datasets for the signatures of binary pulsa

Xuao Zhang

Our paper presents two main results. First, we study the renormalized free energies of Euclidean Einstein gravity in asymptotically AdS$_8$ and various field theories on a squashed seven sphere. In the gravity theory, we demonstrate the absence of the Hawking-Page transition, while in the field theory, we focus on the O($N$) vector model and the massless fre

Yueqing Sun, Yu Zhang, Le Qi, Qi Shi

Unsupervised commonsense question answering requires mining effective commonsense knowledge without the rely on the labeled task data. Previous methods typically retrieved from traditional knowledge bases or used pre-trained language models (PrLMs) to generate fixed types of knowledge, which have poor generalization ability. In this paper, we aim to address

Alexander Roocroft, Giuliano Punzo, Muhamad Azfar Ramli

Accurate static traffic assignment models are important tools for the assessment of strategic transportation policies. In this article we present a novel approach to partition road networks through network modularity to produce data-driven static traffic assignment models from loop detector data on large road systems. The use of partitioning allows the estim

Jelle Wemmenhove, Dick Arends, Thijs Beurskens, Maitreyee Bhaid

In order to help students learn how to write mathematical proofs, we adapt the Coq proof assistant into an educational tool we call Waterproof. Like with other interactive theorem provers, students write out their proofs inside the software using a specific syntax, and the software provides feedback on the logical validity of each step. Waterproof consists o

Chul-Moon Yoo

This paper is a biased review of primordial black hole (PBH) formation and abundance estimation. We first review the three-zone model for PBH formation to help an intuitive understanding of the PBH formation process. Then, for more accurate analyses, we introduce necessary tools such as cosmological long-wavelength solutions, the definition of the mass and c

Xin-Yuan Gao, Chin-Yuan Ong, Chun-Shing Lee, Cho-Tung Yip

The configurational entropy of supercooled liquids extrapolates to zero at the Kauzmann temperature, causing a crisis called the Kauzmann paradox. Here, using a class of multicomponent lattice glass models, we study a resolution of the paradox characterized by a sudden but smooth turn in the entropy as temperature goes sufficiently low. A scalar variant of t

Daigo Oue, Kun Ding, J. B. Pendry

In this study, we reveal noncontact frictional forces between surfaces in the presence of peristaltic permittivity modulation. Our setup comprises a conducting medium, an air gap, and a dielectric substrate on which we have a space-time-modulated grating that emits electromagnetic radiation. The radiation receives energy and momentum from the grating, which

Fan Yang, Shigeyuki Odashima, Shoichi Masui, Shan Jiang

This is our 2nd-place solution for the ECCV 2022 Multiple People Tracking in Group Dance Challenge. Our method mainly includes two steps: online short-term tracking using our Cascaded Buffer-IoU (C-BIoU) Tracker, and, offline long-term tracking using appearance feature and hierarchical clustering. Our C-BIoU tracker adds buffers to expand the matching space

Xidan Song, Youcheng Sun, Mustafa A. Mustafa, Lucas Cordeiro

We present AIREPAIR, a platform for repairing neural networks. It features the integration of existing network repair tools. Based on AIREPAIR, one can run different repair methods on the same model, thus enabling the fair comparison of different repair techniques. We evaluate AIREPAIR with three state-of-the-art repair tools on popular deep-learning dataset

Benjamin Kiefer, Matej Kristan, Janez Perš, Lojze Žust

The 1$^{\text{st}}$ Workshop on Maritime Computer Vision (MaCVi) 2023 focused on maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicle (USV), and organized several subchallenges in this domain: (i) UAV-based Maritime Object Detection, (ii) UAV-based Maritime Object Tracking, (iii) USV-based Maritime Obstacle Segmentation an

Agostino Martinelli

Identifiability is a structural property of any ODE model characterized by a set of unknown parameters. It describes the possibility of determining the values of these parameters from fusing the observations of the system inputs and outputs. This paper finds the general analytical solution of this fundamental problem and, based on this, provides a general an

Chavdar Dutsov, Timothy Hume, Philipp Schmidt-Wellenburg

At the Paul Scherrer Institute (PSI) we are developing a high precision instrument to measure the muon electric dipole moment (EDM). The experiment is based on the frozen-spin method in which the spin precession induced by the anomalous magnetic moment is suppressed, thus increasing the signal-to-noise ratio for EDM signals to achieve a sensitivity otherwise

Haidong Wang, Xiaogang Xiong, Mengting Lan, Yinghao Chu

Spiking Neural Networks (SNNs), regarded as the third generation of neural networks, emulate the brain's information processing with unparalleled biological plausibility compared to traditional neural networks. However, their non-linear, event-driven dynamics pose significant challenges for training, and existing methods often deviate from neuroscientific pr

Alexander Van-Brunt, Patrick E. Farrell, Charles W. Monroe

We present a method to embed local electroneutrality within Onsager-Stefan-Maxwell electrolytic-transport models, circumventing their formulation as differential systems with an algebraic constraint. Flux-explicit transport laws are formulated for general multicomponent electrolytes, in which the conductivity, component diffusivities, and transference number

Maurice Coquet

The production of quarkonia in hadronic collisions provides a unique testing ground for understanding quantum chromodynamics (QCD) since it involves both the perturbative and non-perturbative regimes of this theory. Given that a satisfactory description of quarkonia production has not yet been achieved, new measurements that can provide new insights, helping

Carlotta Sartore, Lorenzo Rapetti, Daniele Pucci

When a human and a humanoid robot collaborate physically, ergonomics is a key factor to consider. Assuming a given humanoid robot, several control architectures exist nowadays to address ergonomic physical human-robot collaboration. This paper takes one step further by considering robot hardware parameters as optimization variables in the problem of collabor

Jacquelin Luneau, Benoît Douçot, David Carpentier

We consider a quantum topological frequency converter, realized by coupling a qubit to two slow harmonic modes. The dynamics of such a system is the quantum analog of topological pumping. Our quantum mechanical description shows that an initial state generically evolves into a superposition of two adiabatic states. The topological nature of the coupling betw

Muneto Nitta, Kunihito Uzawa

We construct some new dynamical $p$-brane solutions to gravity theories on curved backgrounds. We discuss the relations between dynamical branes, a new time-dependent solution on complex projective space $\mathbb{C}{\rm P}^n$ and the static $p$-branes on the orbifold ${\mathbb C}^n/{\mathbb Z}_n$.

Tomáš Souček, Jean-Baptiste Alayrac, Antoine Miech, Ivan Laptev

We aim to learn to temporally localize object state changes and the corresponding state-modifying actions by observing people interacting with objects in long uncurated web videos. We introduce three principal contributions. First, we explore alternative multi-task network architectures and identify a model that enables efficient joint learning of multiple o

Ivan Panin

The category of framed correspondences $Fr_*(k)$ was invented by Voevodsky in his notes in order to give another framework for SH(k) more amenable to explicit calculations. Based on that notes and on their JAMS paper Garkusha and the author introduced in a very recent paper a triangulated category of framed bispectra $\text{SH}_{nis}^{fr}(k)$. It is shown in

Catherine Tony, Nicolás E. Díaz Ferreyra, Riccardo Scandariato

GitHub is a popular data repository for code examples. It is being continuously used to train several AI-based tools to automatically generate code. However, the effectiveness of such tools in correctly demonstrating the usage of cryptographic APIs has not been thoroughly assessed. In this paper, we investigate the extent and severity of misuses, specificall

Christian Düreth, Paul Seibert, Dennis Rücker, Stephanie Handford

Microstructure reconstruction, a major component of inverse computational materials engineering, is currently advancing at an unprecedented rate. While various training-based and training-free approaches are developed, the majority of contributions are based on generative adversarial networks. In contrast, diffusion models constitute a more stable alternativ

Keyi Cheng, Stefan Inzer, Adrian Leung, Xiaoxian Shen

We propose a multi-scale hybridized topic modeling method to find hidden topics from transcribed interviews more accurately and efficiently than traditional topic modeling methods. Our multi-scale hybridized topic modeling method (MSHTM) approaches data at different scales and performs topic modeling in a hierarchical way utilizing first a classical method,

Zeyu Shangguan, Lian Huai, Tong Liu, Xingqun Jiang

Due to the scarcity of sampling data in reality, few-shot object detection (FSOD) has drawn more and more attention because of its ability to quickly train new detection concepts with less data. However, there are still failure identifications due to the difficulty in distinguishing confusable classes. We also notice that the high standard deviation of avera

Ke Li, Tim Rolff, Susanne Schmidt, Reinhard Bacher

Neural radiance field (NeRF), in particular its extension by instant neural graphics primitives, is a novel rendering method for view synthesis that uses real-world images to build photo-realistic immersive virtual scenes. Despite its potential, research on the combination of NeRF and virtual reality (VR) remains sparse. Currently, there is no integration in

Marcel Meyer, Corentin Déprez, Timo R. van Abswoude, Dingshan Liu

Highly uniform quantum systems are essential for the practical implementation of scalable quantum processors. While quantum dot spin qubits based on semiconductor technology are a promising platform for large-scale quantum computing, their small size makes them particularly sensitive to their local environment. Here, we present a method to electrically obtai

J. B. Natowitz, H. Pais, G. Röpke

Detailed assessments of the ability of recent theoretical approaches to modeling existing experimental data for ternary fission confirm earlier indications that the dominant mode of cluster formation in ternary fission is clusterization in very neutron rich, very low density, essentially chemically equilibrated, nucleonic matter. An extended study and compar

Nikoli Dryden, Torsten Hoefler

Many data have an underlying dependence on spatial location; it may be weather on the Earth, a simulation on a mesh, or a registered image. Yet this feature is rarely taken advantage of, and violates common assumptions made by many neural network layers, such as translation equivariance. Further, many works that do incorporate locality fail to capture fine-g

Yuanyuan Liu, Wenbin Wang, Yibing Zhan, Shaoze Feng

Self-supervised facial representation has recently attracted increasing attention due to its ability to perform face understanding without relying on large-scale annotated datasets heavily. However, analytically, current contrastive-based self-supervised learning (SSL) still performs unsatisfactorily for learning facial representation. More specifically, exi

D. Gotz, M. Boutelier, V. Burwitz, R. Chipaux

The Microchannel X-ray Telescope (MXT) will be the first focusing X-ray telescope based on a "Lobster-Eye" optical design to be flown on Sino-French mission SVOM. SVOM will be dedicated to the study of Gamma-Ray Bursts and more generally time-domain astrophysics. The MXT telescope is a compact (focal length ~ 1.15 m) and light (< 42 kg) instrument, sensitive

D. Hernández-Delfin, D. R. Tunuguntla, T. Weinhart, R. C. Hidalgo

It is well-known that granular mixtures that differ in size or shape segregate when sheared. In the past, two mechanisms have been proposed to describe this effect, and it is unclear if both exist. To settle this question, we consider a bidisperse mixture of spheroids of equal volume in a rotating drum, where the two mechanisms are predicted to act in opposi

Shuaifeng Jiang, Ahmed Hindy, Ahmed Alkhateeb

Can reconfigurable intelligent surfaces (RISs) operate in a standalone mode that is completely transparent to the 3GPP 5G initial access process? Realizing that may greatly simplify the deployment and operation of these surfaces and reduce the infrastructure control overhead. This paper investigates the feasibility of building standalone/transparent RIS syst

Zhiwei Lu, I. P. Miranda, Simon Streib, Manuel Pereiro

We study the influence of non-local damping on magnon properties of Fe, Co, Ni and Fe$_{1-x}$Co$_{x}$ ($x=30\%,50\%$) alloys. The Gilbert damping parameter is typically considered as a local scalar both in experiment and in theoretical modelling. However, recent works have revealed that Gilbert damping is a non-local quantity that allows for energy dissipati

Nikolay Kaleyski, Kjetil Nesheim, Patenlimon Stănică

We consider an infinite family of exponents $e(l,k)$ with two parameters, $l$ and $k$, and derive sufficient conditions for $e(l,k)$ to be 0-APN over $\mathbb{F}_{2^n}$. These conditions allow us to generate, for each choice of $l$ and $k$, an infinite list of dimensions $n$ where $x^{e(l,k)}$ is 0-APN much more efficiently than in general. We observe that t