October 2022 arXiv papers — page 88

Xuanmin Cao, Matteo Baggioli, Hui Liu, Danning Li

Pseudo-Goldstone modes appear in many physical systems and display robust universal features. First, their mass $m$ obeys the so-called Gell-Mann-Oakes-Renner (GMOR) relation $f^2\,m^2=H\,\bar{\sigma}$, with $f$ the Goldstone stiffness, $H$ the explicit breaking scale and $\bar{\sigma}$ the spontaneous condensate. More recently, it has been shown that their

Mikuláš Matoušek, Michał Hapka, Libor Veis, Katarzyna Pernal

A multiconfigurational adiabatic connection (AC) formalism is an attractive approach to computing dynamic correlation within CASSCF and DMRG models. Practical realizations of AC have been based on two approximations: i) fixing one- and two-electron reduced density matrices (1- and 2-RDMs) at the zero-coupling constant limit and ii) extended random phase appr

Zhaozhi Wang, Kefan Su, Jian Zhang, Huizhu Jia

In this paper, we propose multi-agent automated machine learning (MA2ML) with the aim to effectively handle joint optimization of modules in automated machine learning (AutoML). MA2ML takes each machine learning module, such as data augmentation (AUG), neural architecture search (NAS), or hyper-parameters (HPO), as an agent and the final performance as the r

Yildiray Anagun, Sahin Isik

An activation function has a significant impact on the efficiency and robustness of the neural networks. As an alternative, we evolved a cutting-edge non-monotonic activation function, Negative Stimulated Hybrid Activation Function (Nish). It acts as a Rectified Linear Unit (ReLU) function for the positive region and a sinus-sigmoidal function for the negati

Yatin Nandwani, Rishabh Ranjan, Mausam, Parag Singla

There is a recent focus on designing architectures that have an Integer Linear Programming (ILP) layer within a neural model (referred to as Neural ILP in this paper). Neural ILP architectures are suitable for pure reasoning tasks that require data-driven constraint learning or for tasks requiring both perception (neural) and reasoning (ILP). A recent SOTA a

Giulia Bertaglia

With the rapid advance of Machine Learning techniques and the deep increase of availability of scientific data, data-driven approaches have started to become progressively popular across science, causing a fundamental shift in the scientific method after proving to be powerful tools with a direct impact in many areas of society. Nevertheless, when attempting

William Krinsman

An active area of research interest is the inference of ecological models of complex microbial communities. Inferring such ecological models entails understanding the interactions between microbes and how they affect each other's growth. This dissertation employs a statistical perspective to contribute further to the knowledge currently addressing this probl

Peter Bult, Giulio C. Mancuso, Tod E. Strohmayer, Arianna C. Albayati

We present observations of the historic transient 4U 1730-22 as observed with the Neutron Star Interior Composition Explorer (NICER). After remaining in quiescence since its 1972 discovery, this X-ray binary showed renewed outburst activity in 2021 and 2022. We observed 4U 1730-22 extensively with NICER, detecting a total of 17 thermonuclear X-ray bursts. Fr

Mahmoud Darwich

Video streams tremendously occupied the highest portion of online traffic. Multiple versions of a video are created to fit the user's device specifications. In cloud storage, Keeping all versions of frequently accessed video streams in the repository for the long term imposes a significant cost paid by video streaming providers. Generally, the popularity of

Swarnim Shirke, Suprovo Ghosh, Debarati Chatterjee

At the ultra-high densities existing in the core of neutron stars, it is expected that a phase transition from baryonic to deconfined quark matter may occur. Such a phase transition would affect the underlying equation of state (EoS) as well as the observable astrophysical properties of neutron stars. Comparison of EoS model predictions with astronomical dat

Žarko Mijajlović, Danijela Branković

A nonstandard proof of a generalization of Karamata uniform convergence theorem for slowly varying functions is presented. Properties of a related operator $\mathcal{L}$ and its connection with slowly varying functions are discussed.

Awad Abdelhalim, Montasir Abbas

Accurate representation of observed driving behavior is critical for effectively evaluating safety and performance interventions in simulation modeling. In this study, we implement and evaluate a safety-based Optimal Velocity Model (OVM) to provide a high-fidelity replication of safety-critical behavior in microscopic simulation and showcase its implications

Bhavesh Shrimali, Oscar Lopez-Pamies

Strikingly, "pure-shear" fracture tests have repeatedly shown that fracture nucleation in (common hydrocarbon and other types of) viscoelastic elastomers occurs at a critical stretch that is independent of the stretch rate at which the test is carried out. In this Letter, we demonstrate that this remarkable -- yet overlooked -- experimental finding implies t

Furkan Kınlı, Barış Özcan, Furkan Kıraç

RAW image datasets are more suitable than the standard RGB image datasets for the ill-posed inverse problems in low-level vision, but not common in the literature. There are also a few studies to focus on mapping sRGB images to RAW format. Mapping from sRGB to RAW format could be a relevant domain for reverse style transferring since the task is an ill-posed

Iñaki García-Elcano, Jaime Merino, Jorge Bravo-Abad, Alejandro González-Tudela

Fermi arcs, i.e., surface states connecting topologically-distinct Weyl points, represent a paradigmatic manifestation of the topological aspects of Weyl physics. Here, we investigate a light-matter interface based on the photonic counterpart of these states and we prove that it can lead to phenomena with no analogue in other setups. First, we show how to im

Bibhuti Kumar Jha

The Sun shows a wide range of temporal variations, from a few seconds to decades and even centuries, broadly classified into two classes short-term and Long-term. The solar dynamo mechanism is believed to be responsible for these global changes happening in the Sun. Hence, many dynamo models have been proposed to explain the observed behaviour of the Sun. Th

Ashutosh Agarwal, Chetan Arora

Monocular Depth Estimation (MDE) aims to predict pixel-wise depth given a single RGB image. For both, the convolutional as well as the recent attention-based models, encoder-decoder-based architectures have been found to be useful due to the simultaneous requirement of global context and pixel-level resolution. Typically, a skip connection module is used to

Šárka Nečasová, Florian Oschmann

We consider the evolutionary compressible Navier-Stokes equations in a two-dimensional perforated domain, and show that in the subcritical case of very tiny holes, the density and velocity converge to a solution of the evolutionary compressible Navier-Stokes equations in the non-perforated domain.

Hendrik Kähler, Holger Arthaber, Robert Winkler, Robert G. West

One of the challenges of nanoelectromechanical systems (NEMS) is the effective transduction of the tiny resonators. Vertical structures, such as nanomechanical pillar resonators, which are exploited in a wide range of fields, such as optomechanics, acoustic metamaterials, and nanomechanical sensing, are particularly challenging to transduce. Existing electro

C. Adam, K. Oles, T. Romanczukiewicz, A. Wereszczynski

We find that for various solitonic processes the corresponding canonical moduli space can have a boundary which is accessible in a finite time evolution. We show that such a boundary is not a failure of the moduli space approach but has a physical meaning. In our example, it corresponds to the complete annihilation of a colliding kink and antikink after a fi

H. Buglia, M. Jarmolovicius, A. Vasylchenkova, E. Sillekens

A closed-form model for the nonlinear interference in distributed Raman amplified links is presented, the formula accounts for both forward and backward pumping.

Felix Kübler

In this paper, I consider a simple heterogeneous agents model of a production economy with uncertain climate change and examine constrained efficient carbon taxation. If there are frictionless, complete financial markets, the simple model predicts a unique Pareto-optimal level of carbon taxes and abatement. In the presence of financial frictions, however, th

Marc-Olivier Renou, Xiangling Xu, Laurens T. Ligthart

Characterising the correlations that arise from locally measuring a single part of a joint quantum system is one of the main problems of quantum information theory. The seminal work [M. Navascu\'es et al., New J. Phys. 10, 073013 (2008)], known as the Navascu\'es-Pironio-Ac\'in (NPA) hierarchy, reformulated this question as a polynomial optimisation problem

Pierre Berger, Nicolaz Gourmelon, Mathieu Helfter

For any $1\le r\le \infty$, we show that every diffeomorphism of a manifold of the form $\mathbb{R}/\mathbb{Z} \times M$ is a total renormalization of a $C^r$-close to identity map. In other words, for every diffeomorphism $f$ of $\mathbb{R}/\mathbb{Z} \times M$, there exists a map $g$ arbitrarily close to identity such that the first return map of $g$ to a

Oliver Pooley, David Wallace

Brian Pitts has recently claimed to show via straightforward calculation that, at least in the case of Hamiltonian electromagnetism, an arbitrary first-class constraint ``generates not a gauge transformation, but a bad physical change'' (Annals of Physics 351 (2014) pp.382-406; arXiv:1310.2756). We show, via a straightforward calculation, that a transformati

Jinshuai Bai, Hyogu Jeong, C. P. Batuwatta-Gamage, Shusheng Xiao

Physics-informed neural network (PINN) has recently gained increasing interest in computational mechanics. In this work, we present a detailed introduction to programming PINN-based computational solid mechanics. Besides, two prevailingly used physics-informed loss functions for PINN-based computational solid mechanics are summarised. Moreover, numerical exa

Nicolai Engelmann, Heinz Koeppl

Hidden semi-Markov Models (HSMM's) - while broadly in use - are restricted to a discrete and uniform time grid. They are thus not well suited to explain often irregularly spaced discrete event data from continuous-time phenomena. We show that non-sampling-based latent state inference used in HSMM's can be generalized to latent Continuous-Time semi-Markov Cha

Luca Esposito, Lorenzo Lamberti

We study a class of variational problems involving both bulk and interface energies. The bulk energy is of Dirichlet type albeit of very general form allowing the dependence from the unknown variable $u$ and the position $x$. We employ the regularity theory of $\Lambda$-minimizers to study the regularity of the free interface. The hallmark of the paper is th

Jianing Wang, Chengcheng Han, Chengyu Wang, Chuanqi Tan

Few-shot Named Entity Recognition (NER) aims to identify named entities with very little annotated data. Previous methods solve this problem based on token-wise classification, which ignores the information of entity boundaries, and inevitably the performance is affected by the massive non-entity tokens. To this end, we propose a seminal span-based prototypi

Guillaume Dulac, Thomas Simon

We investigate the cumulative Tsallis entropy, an information measure recently introduced as a cumulative version of the classical Tsallis differential entropy, which is itself a generalization of the Boltzmann-Gibbs statistics. This functional is here considered as a perturbation of the expected mean residual life via some power weight function. This point

Yousef Alqasrawi

The use of bag of visual words (BOW) model for modelling images based on local invariant features computed at interest point locations has become a standard choice for many computer vision tasks. Visual vocabularies generated from image feature vectors are expected to produce visual words that are discriminative to improve the performance of image annotation

Joseph Hart, Bart van Bloemen Waanders

A common goal throughout science and engineering is to solve optimization problems constrained by computational models. However, in many cases a high-fidelity numerical emulation of systems cannot be optimized due to code complexity and computational costs which prohibit the use of intrusive and many query algorithms. Rather, lower-fidelity models are constr

Cyril Pannetier, Philippe Berio, Denis Mourard, Sylvain Rousseau

SPICA-FT is part of the CHARA/SPICA instrument which combines a visible 6T fibered instrument (SPICAVIS) with a H-band 6T fringe sensor. SPICA-FT is a pairwise ABCD integrated optics combiner. The chip is installed in the MIRC-X instrument. The MIRC-X spectrograph could be fed either by the classical 6T fibered combiner or by the SPICA-FT integrated optics c

Johan du Buisson

We solve two problems related to the fluctuations of time-integrated functionals of Markov diffusions, used in physics to model nonequilibrium systems. In the first we derive and illustrate the appropriate boundary conditions on the spectral problem used to obtain the large deviations of current-type observables for reflected diffusions. For the second probl

Joseph Hart, Bart van Bloemen Waanders

Model discrepancy, defined as the difference between model predictions and reality, is ubiquitous in computational models for physical systems. It is common to derive partial differential equations (PDEs) from first principles physics, but make simplifying assumptions to produce tractable expressions for the governing equations or closure models. These PDEs

Gregory Moille, Curtis Menyuk, Yanne K. Chembo, Avik Dutt

Dissipative Kerr solitons (DKSs) in optical microresonators have been intensely studied from the perspective of both fundamental nonlinear physics and portable and low power technological applications in communications, sensing, and metrology. In parallel, synthetic dimensions offer the promise of studying physical phenomena with a dimensionality beyond that

Ritwick Sarkar, Ion Santra, Urna Basu

We study the stationary state of a chain of harmonic oscillators driven by two active reservoirs at the two ends. These reservoirs exert correlated stochastic forces on the boundary oscillators which eventually leads to a nonequilibrium stationary state of the system. We consider three most well-known dynamics for the active force, namely, active Ornstein-Uh

Homayoun Jafari, Arunesh Roy, Jagoda Sławińska

Ferroelectric materials hold great potential for alternative memories and computing, but several challenges need to be overcome before bringing the ideas to applications. In this context, the recently discovered link between electric polarization and spin textures in some classes of ferroelectrics expands the perspectives of the design of devices that could

Joonil Kim

Since Varchenko's seminal paper, the asymptotics of oscillatory integrals and related problems have been elucidated through the Newton polyhedra associated with the phase $P$. The supports of those integrals are concentrated on sufficiently small neighborhoods. The aim of this paper is to investigate the estimates of sub-level-sets and oscillatory integrals

Pier Paolo Tricomi, Lisa Facciolo, Giovanni Apruzzese, Mauro Conti

Did you know that over 70 million of Dota2 players have their in-game data freely accessible? What if such data is used in malicious ways? This paper is the first to investigate such a problem. Motivated by the widespread popularity of video games, we propose the first threat model for Attribute Inference Attacks (AIA) in the Dota2 context. We explain how (a

Kai Wei, Tian Zhao, Xiujie Fang, Zitong Xu

Achieving high energy resolution in spin systems is important for fundamental physics research and precision measurements, with alkali-noble-gas comagnetometers being among the best available sensors. We found a new relaxation mechanism in such devices, the gradient of the Fermi-contact-interaction field that dominates the relaxation of hyperpolarized nuclea

Sanli Tang, Zhongyu Zhang, Zhanzhan Cheng, Jing Lu

Knowledge distillation learns a lightweight student model that mimics a cumbersome teacher. Existing methods regard the knowledge as the feature of each instance or their relations, which is the instance-level knowledge only from the teacher model, i.e., the local knowledge. However, the empirical studies show that the local knowledge is much noisy in object

Ahmet Gokberk Gul, Oezdemir Cetin, Christoph Reich, Tim Prangemeier

Whole Slide Image (WSI) analysis is a powerful method to facilitate the diagnosis of cancer in tissue samples. Automating this diagnosis poses various issues, most notably caused by the immense image resolution and limited annotations. WSIs commonly exhibit resolutions of 100Kx100K pixels. Annotating cancerous areas in WSIs on the pixel level is prohibitivel

Ling Tang, Wen Shen, Zhanpeng Zhou, Yuefeng Chen

In this paper, we prove the representation defects of a cascaded convolutional decoder network, considering the capacity of representing different frequency components of an input sample. We conduct the discrete Fourier transform on each channel of the feature map in an intermediate layer of the decoder network. Then, we extend the 2D circular convolution th

Yanmei Shi, Zhiruo Li, Qi Zhang

Inference and prediction under the sparsity assumption have been a hot research topic in recent years. However, in practice, the sparsity assumption is difficult to test, and more importantly can usually be violated. In this paper, to study hypothesis test of any group of parameters under non-sparse high-dimensional linear models, we transform the null hypot

William Giarè, Fabrizio Renzi, Olga Mena, Eleonora Di Valentino

The Data Release 4 of the Atacama Cosmology Telescope (ACT) shows an agreement with an Harrison-Zel'dovich primordial spectrum ($n_s=1.009 \pm 0.015$), introducing a tension with a significance of $99.3\%$ CL with the results from the Planck satellite. The discrepancy on the value of the scalar spectral index is neither alleviated with the addition of large

Tobias M. Wolff, Victor G. Lopez, Matthias A. Müller

In this paper, a robust data-driven moving horizon estimation (MHE) scheme for linear time-invariant discrete-time systems is introduced. The scheme solely relies on offline collected data without employing any system identification step. We prove practical robust exponential stability for the setting where both the online measurements and the offline collec

Joseph A. M. Paddison

Magnetic diffuse scattering -- the broad magnetic scattering features observed in neutron-diffraction data above a material's magnetic ordering temperature -- provides a rich source of information about the material's magnetic Hamiltonian. However, this information has often remained under-utilised due to a lack of available computer software that can fit va

Avinash Kori, Ben Glocker, Francesca Toni

An effective way to obtain different perspectives on any given topic is by conducting a debate, where participants argue for and against the topic. Here, we propose a novel debate framework for understanding and explaining a continuous image classifier's reasoning for making a particular prediction by modeling it as a multiplayer sequential zero-sum debate g

F. J. Sanchez-Salcedo, R. O. Chametla, O. Chrenko

Planets can carve gaps in the surface density of protoplanetary discs. The formation of these gaps can reduce the corotation torques acting on the planets. In addition, gaps can halt the accretion of solids onto the planets as dust and pebbles can be trapped at the edge of the gap. This accumulation of dust could explain the origin of the ring-like dust stru

Yu-Qin Chen, Shi-Xin Zhang, Chang-Yu Hsieh, Shengyu Zhang

Ground-state preparation for a given Hamiltonian is a common quantum-computing task of great importance and has relevant applications in quantum chemistry, computational material modeling, and combinatorial optimization. We consider an approach to simulate dissipative non-Hermitian Hamiltonian quantum dynamics using Hamiltonian simulation techniques to effic

Keshab Chandra Bakshi, Satyajit Guin, Sruthymurali

This paper originates from a naive attempt to establish various non-commutative Fourier theoretic inequalities for an inclusion of simple C*-algebras equipped with a conditional expectation of index-finite type. In this setting, we discuss the Hausdorff-Young inequality and Young's inequality. As a consequence, we prove the Hirschman-Beckner uncertainty prin

Sajan Kumar, Mayanak K. Gupta, Prabhatasree Goel, Ranjan Mittal

We present the investigations on atomic dynamics and Li+ diffusion in crystalline and amorphous Li2Si2O5 using quasielastic (QENS) and inelastic neutron scattering (INS) studies supplemented by ab-initio molecular dynamics simulations (AIMD). The QENS measurements in the amorphous phase of Li2Si2O5 show a narrow temperature window (700 < T < 775 K), exhibiti

Richard G. Freedman, Joseph B. Mueller, Jack Ladwig, Steven Johnston

Robots that interact with humans in a physical space or application need to think about the person's posture, which typically comes from visual sensors like cameras and infra-red. Artificial intelligence and machine learning algorithms use information from these sensors either directly or after some level of symbolic abstraction, and the latter usually parti

Furkan Kınlı, Sami Menteş, Barış Özcan, Furkan Kıraç

This paper introduces the methods and the results of AIM 2022 challenge on Instagram Filter Removal. Social media filters transform the images by consecutive non-linear operations, and the feature maps of the original content may be interpolated into a different domain. This reduces the overall performance of the recent deep learning strategies. The main goa

J. Lillo-Box, D. Gandolfi, D. J. Armstrong, K. A. Collins

The current architecture of a given multi-planetary system is a key fingerprint of its past formation and dynamical evolution history. Long-term follow-up observations are key to complete their picture. In this paper we focus on the confirmation and characterization of the components of the TOI-969 planetary system, where TESS detected a Neptune-size planet

Enes Yavuz Ugan, Christian Huber, Juan Hussain, Alexander Waibel

Code-Switching (CS) is referred to the phenomenon of alternately using words and phrases from different languages. While today's neural end-to-end (E2E) models deliver state-of-the-art performances on the task of automatic speech recognition (ASR) it is commonly known that these systems are very data-intensive. However, there is only a few transcribed and al

Bin Zheng, Fangfu Ye, Shigeyuki Komura, Masao Doi

We analyze the translocation process of a spherical vesicle, made of membrane and incompressible fluid, through a hole smaller than the vesicle size, driven by pressure difference $\Delta P$. We show that such a vesicle shows certain universal characteristics which is independent of the details of the membrane elasticity; (i) there is a critical pressure $\D

Baoxiong Jia, Yu Liu, Siyuan Huang

The ability to decompose complex natural scenes into meaningful object-centric abstractions lies at the core of human perception and reasoning. In the recent culmination of unsupervised object-centric learning, the Slot-Attention module has played an important role with its simple yet effective design and fostered many powerful variants. These methods, howev

Masaki Ochi, Tatsuro Kawamoto

Visualization of the adjacency matrix enables us to capture macroscopic features of a network when the matrix elements are aligned properly. Community structure, a network consisting of several densely connected components, is a particularly important feature, and the structure can be identified through the adjacency matrix when it is close to a block-diagon

Gao Mengyu, Dong Qiulei

Semantic segmentation for SAR (Synthetic Aperture Radar) images has attracted increasing attention in the remote sensing community recently, due to SAR's all-time and all-weather imaging capability. However, SAR images are generally more difficult to be segmented than their EO (Electro-Optical) counterparts, since speckle noises and layovers are inevitably i

Sofiane Bouarroudj, Abdenacer Makhlouf

The main goal of this paper is to develop the structure theory of Hom-Lie superalgebras in characteristic 2. We discuss their representations, semidirect product, $\alpha^k$-derivations and provide a classification in low dimension. We introduce another notion of restrictedness on Hom-Lie algebras in characteristic 2, different from one given by Guan and Che

ALICE Collaboration

The study of the azimuthal anisotropy of inclusive muons produced in p-Pb collisions at $\sqrt{s_{\rm NN}} = 8.16$ TeV, using the ALICE detector at the LHC is reported. The measurement of the second-order Fourier coefficient of the particle azimuthal distribution, $v_2$, is performed as a function of transverse momentum $p_{\rm T}$ in the 0-20% high-multipli

Thomas Loruenser, Stephan Krenn, Christoph Pacher, Bernhard Schrenk

Quantum key distribution (QKD) has been researched for almost four decades and is currently making its way to commercial applications. However, deployment of the technology at scale is challenging, because of the very particular nature of QKD and its physical limitations. Among others, QKD is computationally intensive in the post-processing phase and devices

Fang Chen, Lei Zhou, Long Wang

Direct reciprocity facilitates the evolution of cooperation when individuals interact repeatedly. Most previous studies on direct reciprocity implicitly assume compulsory interactions. Yet, interactions are often voluntary in human societies. Here, we consider repeated optional games, where individuals can freely opt out of each interaction and rejoin later.

Dragana Pilipovic

A minimum length universe is enforced via a diffusive Markovian field. Requiring the invariance of the proper time functional under spacetime transformations generated by such fields provides us with many new terms added to the Christoffel Connection, Equations of Motion, and Friedmann Equation. Under the Robertson-Walker (RW) metric, we obtain species-speci

Chiyi Luo, Yun Zhao

This paper considers $C^2$ random dynamical systems in a Banach space, and proves that under some mild conditions, SRB measures are characterized by invariant measures satisfying Pesin's entropy formula, in which entropy is equal to the sum of positive Lyapunov exponents of the system. This can be regarded as a random version of the main result in Blumenthal

Philipp Teutsch, Patrick Mäder

Sequence-to-sequence models based on LSTM and GRU are a most popular choice for forecasting time series data reaching state-of-the-art performance. Training such models can be delicate though. The two most common training strategies within this context are teacher forcing (TF) and free running (FR). TF can be used to help the model to converge faster but may

Tingyu Qu, Tinne Tuytelaars, Marie-Francine Moens

We revisit the weakly supervised cross-modal face-name alignment task; that is, given an image and a caption, we label the faces in the image with the names occurring in the caption. Whereas past approaches have learned the latent alignment between names and faces by uncertainty reasoning over a set of images and their respective captions, in this paper, we

Pan Li, Peizhuo Lv, Shenchen Zhu, Ruigang Liang

Unlike traditional static deep neural networks (DNNs), dynamic neural networks (NNs) adjust their structures or parameters to different inputs to guarantee accuracy and computational efficiency. Meanwhile, it has been an emerging research area in deep learning recently. Although traditional static DNNs are vulnerable to the membership inference attack (MIA)

John Haslegrave

Foucaud, Krishna and Lekshmi recently introduced the concept of monitoring edge-geodetic sets in graphs, and a related graph invariant. These are sets of vertices such that the removal of any edge changes the distance between some pair of vertices in the set. They studied the minimum possible size of such a set in a given graph, which we call the monitoring

Larsen Louder, Michael Magee with Appendix by Will Hide, Michael Magee

We prove that all finitely generated fully residually free groups (limit groups) have a sequence of finite dimensional unitary representations that `strongly converge' to the regular representation of the group. The corresponding statement for finitely generated free groups was proved by Haagerup and Thorbj{\o}rnsen in 2005. In fact, we can take the unitary

David Alonso, Steffen Bauer, Markus Kirkilionis, Lisa Maria Kreusser

Rule-based models have been successfully used to represent different aspects of the COVID-19 pandemic, including age, testing, hospitalisation, lockdowns, immunity, infectivity, behaviour, mobility and vaccination of individuals. These rule-based approaches are motivated by chemical reaction rules which are traditionally solved numerically with the standard

Yash Goel, Narunas Vaskevicius, Luigi Palmieri, Nived Chebrolu

We investigate the task of object goal navigation in unknown environments where the target is specified by a semantic label (e.g. find a couch). Such a navigation task is especially challenging as it requires understanding of semantic context in diverse settings. Most of the prior work tackles this problem under the assumption of a discrete action policy whe

Theo W. Costain, Victor Adrian Prisacariu

We present ApproxConv, a novel method for compressing the layers of a convolutional neural network. Reframing conventional discrete convolution as continuous convolution of parametrised functions over space, we use functional approximations to capture the essential structures of CNN filters with fewer parameters than conventional operations. Our method is ab

Minh N. Dao, Hassan Saoud, Michel Théra

In this paper, we are interested in studying the asymptotic behavior of the solutions of differential inclusions governed by maximally monotone operators. In the case where the LaSalle's invariance principle is inconclusive, we provide a refined version of the invariance principle theorem. This result derives from the problem of locating the $\omega$-limit s

Jing Zhang, Zhao Li, Jiqiang Zhang, Lin Ma

Oscillatory behaviors are ubiquitous in nature and the human society. However, most previous works fail to reproduce them in the two-strategy game-theoretical models. Here we show that oscillatory behaviors naturally emerge if incomplete information is incorporated into the cooperation evolution of a non-Markov model. Specifically, we consider a population p

Palak, Vaibhav Raj Singh Parmar, Ranjini Bandyopadhyay

When a soft glassy colloidal suspension is displaced by a Newtonian fluid in a radial Hele-Shaw geometry, the pattern morphology that develops at the interface is determined by the complex rheology of the former. We had reported in an earlier work [Palak, V. R. S. Parmar, D. Saha and R. Bandyopadhyay, JCIS Open, 6 (2022) 100047] that a range of interfacial p

Pardeep Kaur, Sandeep Gautam, S. K. Adhikari

We demonstrate spontaneous generation of spatially-periodic supersolid-like super-lattice and stripe solitons in Rashba spin-orbit (SO) coupled spin-1 and spin-2 quasi-two-dimensional nonmagnetic Bose-Einstein condensates (BECs). The solitons in a weakly SO-coupled spin-1 BEC are circularly-symmetric of $(-1, 0, +1)$ and $(0, +1, +2)$ types and have inherent

T. A. Yoğurt, A. Keleş, M. Ö. Oktel

Self-bound quantum droplets form when the mean-field tendency of the gas to collapse is stabilized by the effectively repulsive beyond mean-field fluctuations. The beyond mean-field effects depend on Rabi-frequency $\omega_R$ and quadratic Zeeman effect $q$ for the Rabi-coupled Bose mixtures and the spinor gases, respectively. The effects of varying $\omega_

Denis-Charles Cisinski, Hoang Kim Nguyen

We give a new proof of the straightening/unstraightening correspondence by proving a generalization of the univalence property of the universal coCartesian fibration.

Anton Alekseev, Florian Naef, Ján Pulmann, Pavol Ševera

Let $\Sigma$ be a compact oriented 2-manifold (possibly with boundary), and let $\mathcal G_{\Sigma}$ be the linear span of free homotopy classes of closed oriented curves on $\Sigma$ equipped with the Goldman Lie bracket $[\cdot, \cdot]_\mathrm{Goldman}$ defined in terms of intersections of curves. A theorem of Goldman gives rise to a Lie homomorphism $\Phi

Yunkun Chen, Yi Peng, Xue Wang

The full compressible magnetohydrodynamic system in three-dimensional exterior domains is investigated. For the initial-boundary-value problem of this system with slip boundary condition for the velocity, adiabatic one for the temperature, and perfect one for the magnetic field, the global existence and uniqueness of classical solutions is established, under

Pavel Turek

Let $p$ be an odd prime and let $k$ be a field of characteristic $p$. We provide a practical algebraic description of the representation ring of $k\mathrm{SL}_2(\mathbb{F}_p)$ modulo projectives. We then investigate a family of modular plethysms of the natural $k\mathrm{SL}_2(\mathbb{F}_p)$-module $E$ of the form $\nabla^{\nu}\mathrm{Sym}^l E$ for a partitio

Elvis Nava, Seijin Kobayashi, Yifei Yin, Robert K. Katzschmann

We introduce meta-learning algorithms that perform zero-shot weight-space adaptation of neural network models to unseen tasks. Our methods repurpose the popular generative image synthesis techniques of natural language guidance and diffusion models to generate neural network weights adapted for tasks. We first train an unconditional generative hypernetwork m

Peng-Hui Chen, Hao Wu, Zu-Xing Yang, Xiang-Hua Zeng

In the framework of the dinuclear system model, the synthesis mechanism of the superheavy nuclides with atomic number $Z=112, 114, 115$ in the reactions of projectiles $^{40,48}$Ca bombarding on targets $^{238}$U, $^{242}$Pu, and $^{243}$Am at a wide incident energies (excitation energy from 0-100 MeV) have been investigated systematically. Based on the avai

Majid Gerami, Bikramjit Singh

Uplink configured Grant allocation has been introduced in 3rd Generation Partnership Project New Radio Release 15. This is beneficial in supporting Ultra-Reliable and Low Latency Communication for industrial communication, a key Fifth Generation mobile communication usage scenario. This scheduling mechanism enables a user with periodic traffic to transmits i

Ádám Gyenge, Szilárd Szabó

We investigate the behaviour of the spectrum of the quantum (or Dubrovin) connection of smooth projective surfaces under blow-ups. Our main result is that for small values of the parameters, the quantum spectrum of such a surface is asymptotically the union of the quantum spectrum of a minimal model of the surface and a finite number of additional points loc

Hadi Bigdely, Eduardo Martínez-Pedroza

Consider the following classes of pairs consisting of a group and a finite collection of subgroups: $\mathcal{C}= \left\{ (G,\mathcal H) \mid \text{$\mathcal{H}$ is hyperbolically embedded in $G$} \right\}$ and $ \mathcal{D}= \left\{ (G,\mathcal H) \mid \text{the relative Dehn function of $(G,\mathcal H)$ is well-defined} \right\}.$ Let $G$ be a group that s

Konrad Deka, Steve Jackson, Dominik Kwietniak, Bill Mance

We study the descriptive complexity of sets of points defined by placing restrictions on statistical behaviour of their orbits in dynamical systems on Polish spaces. A particular examples of such sets are the set of generic points of a $T$-invariant Borel probability measure, but we also consider much more general sets (for example, $\alpha$-Birkhoff regular

Wenqi Yang, Guanying Chen, Chaofeng Chen, Zhenfang Chen

In this paper, we address the "dual problem" of multi-view scene reconstruction in which we utilize single-view images captured under different point lights to learn a neural scene representation. Different from existing single-view methods which can only recover a 2.5D scene representation (i.e., a normal / depth map for the visible surface), our method lea

Jacques Bloch, Robert Lohmayer

We present a tensor-network method for strong-coupling QCD with staggered quarks at nonzero chemical potential. After integrating out the gauge fields at infinite coupling, the partition function can be written as a full contraction of a tensor network consisting of coupled local numeric and Grassmann tensors. To evaluate the partition function and to comput

Xiaojian Liao, Zhe Yang, Jiwu Shu

Modern NVMe SSDs and RDMA networks provide dramatically higher bandwidth and concurrency. Existing networked storage systems (e.g., NVMe over Fabrics) fail to fully exploit these new devices due to inefficient storage ordering guarantees. Severe synchronous execution for storage order in these systems stalls the CPU and I/O devices and lowers the CPU and I/O

Shansan Gong, Mukai Li, Jiangtao Feng, Zhiyong Wu

Recently, diffusion models have emerged as a new paradigm for generative models. Despite the success in domains using continuous signals such as vision and audio, adapting diffusion models to natural language is under-explored due to the discrete nature of texts, especially for conditional generation. We tackle this challenge by proposing DiffuSeq: a diffusi

Shadi Shaqaqha

In this paper, we introduce the concept of fuzzy Hom-Lie subalgebras (ideals) of Hom-Lie algebras and we investigate some of their properties. We study the relationship between fuzzy Hom-Lie subalgebras (resp. ideals) and Hom-Lie subalgebras (resp. ideals). For a finite number of fuzzy Hom-Lie subalgebras, we construct a new fuzzy hom-Lie subalgebras on thei

Martin Scharpenberg, Werner Brannath

Three-arm `gold-standard' non-inferiority trials are recommended for indications where only unstable reference treatments are available and the use of a placebo group can be justified ethically. For such trials several study designs have been suggested that use the placebo group for testing 'assay sensitivity', i.e. the ability of the trial to replicate effi

Nirmal M R, Shampa Sarkar, Manoj Nambiar, Sriram Goverapet Srinivasan

A lot of progress has been made in recent times for simulating accurately the ground state energy of small molecules and their potential energy surface, using quantum-classical hybrid computing architecture. While these single point energy calculations are a significant milestone for quantum chemistry simulation on quantum hardware, a similarly important app

Gaurav Kumar Nayak, Ruchit Rawal, Anirban Chakraborty

Certified defense using randomized smoothing is a popular technique to provide robustness guarantees for deep neural networks against l2 adversarial attacks. Existing works use this technique to provably secure a pretrained non-robust model by training a custom denoiser network on entire training data. However, access to the training set may be restricted to

Mani Kakavand, Amin Nikoobin

In this paper, we deal with the power regulation of tethered-wing systems and demonstrate advantages of variable-pitch control in mitigating the dynamic mechanical loads and power fluctuations. The proposed scheme is based on a strategy that maximizes the energy capture during low-speed wind and prevents overloads during the high-speed wind. To realize this

Suman Ghosh, Guillermo Gallego

Event cameras are bio-inspired sensors that mimic the human retina by responding to brightness changes in the scene. They generate asynchronous spike-based outputs at microsecond resolution, providing advantages over traditional cameras like high dynamic range, low motion blur and power efficiency. Most event-based stereo methods attempt to exploit the high