July 2022 arXiv papers — page 67

Chengming Bai, Li Guo, Guilai Liu, Tianshui Ma

We establish a bialgebra structure on Rota-Baxter Lie algebras following the Manin triple approach to Lie bialgebras. Explicitly, Rota-Baxter Lie bialgebras are characterized by generalizing matched pairs of Lie algebras and Manin triples of Lie algebras to the context of Rota-Baxter Lie algebras. The coboundary case leads to the introduction of the admissib

Julyan H. E. Cartwright

Could nature be harnessing quantum mechanics in cilia to optimize the sensitivity of the mechanism of left-right symmetry breaking during development in vertebrates? I evaluate whether mechanosensing -- i.e., the detection of a left-right asymmetric signal through mechanical stimulation of sensory cilia, as opposed to biochemical signalling -- might be funct

Stasys Jukna

A monotone Boolean (OR,AND) circuit computing a monotone Boolean function f is a read-k circuit if the polynomial produced (purely syntactically) by the arithmetic (+,x) version of the circuit has the property that for every prime implicant of f, the polynomial contains at least one monomial with the same set of variables, each appearing with degree at most

William Borrelli, Nour Kerraoui, Thomas Ourmières-Bonafos

We consider the two-dimensional Dirac operator with infinite mass boundary conditions posed in a tubular neighborhood of a $C^4$-planar curve. Under generic assumptions on its curvature $\kappa$, we prove that in the thin-width regime the splitting of the eigenvalues is driven by the one dimensional Schr\"odinger operator on $L^2(\mathbb R)$ \[ \mathcal{L}_e

Francesco Cappio Borlino, Silvia Bucci, Tatiana Tommasi

Semantic novelty detection aims at discovering unknown categories in the test data. This task is particularly relevant in safety-critical applications, such as autonomous driving or healthcare, where it is crucial to recognize unknown objects at deployment time and issue a warning to the user accordingly. Despite the impressive advancements of deep learning

Sara Varotto, Annika Johansson, Börge Göbel, Luis M. Vicente-Arche

Rashba interfaces have emerged as promising platforms for spin-charge interconversion through the direct and inverse Edelstein effects. Notably, oxide-based two-dimensional electron gases (2DEGs) display a large and gate-tunable conversion efficiency, as determined by transport measurements. However, a direct visualization of the Rashba-split bands in oxide

Beniamino Accattoli, Giulio Guerrieri

The denotational semantics of the untyped lambda-calculus is a well developed field built around the concept of solvable terms, which are elegantly characterized in many different ways. In particular, unsolvable terms provide a consistent notion of meaningless term. The semantics of the untyped call-by-value lambda-calculus (CbV) is instead still in its infa

E. Cristiani, M. Menci, A. Malagnino, G. G. Amaro

In this paper we deal with pedestrian modeling, aiming at simulating crowd behavior in normal and emergency scenarios, including highly congested mass events. We are specifically concerned with a new agent-based, continuous-in-space, discrete-in-time, nondifferential model, where pedestrians have finite size and are compressible to a certain extent. The mode

Derek Frydel

In this work, we obtain third order linear differential equation for stationary distributions of run-and-tumble particles in two-dimensions in a harmonic trap. The equation represents the condition $j = 0$ where $j$ is a flux and is obtained from inference, using different known results in the limiting conditions. Since the analogous equation for passive Bro

Florio M. Ciaglia, Fabio Di Cosmo, Alberto Ibort, Giuseppe Marmo

Given a real, finite-dimensional, smooth parallelizable Riemannian manifold $(\mathcal{N},G)$ endowed with a teleparallel connection $\nabla$ determined by a choice of a global basis of vector fields on $\mathcal{N}$, we show that the $G$-dual connection $\nabla^{*}$ of $\nabla$ in the sense of Information Geometry must be the teleparallel connection determi

Fernando G. Gardim, Jean-Yves Ollitrault

In recent years, there has been a significant effort to extract the temperature-dependent shear ($\eta/s$) and bulk ($\zeta/s$) viscosity over entropy ratios of the quark-gluon plasma from a global comparison of heavy-ion data with results of hydrodynamic simulations. However, anisotropic flow, which is arguably the most sensitive probe of viscosity, is only

Sergey Bravyi, Dmitri Maslov, Yunseong Nam

We consider quantum circuits composed of single-qubit operations and global entangling gates generated by Ising-type Hamiltonians. It is shown that such circuits can implement a large class of unitary operators commonly used in quantum algorithms at a very low cost -- using a constant or effectively constant number of global entangling gates. Specifically, w

Paul A Crowther

An overview is provided of the scientific goals of the Magellanic Cloud component of the STScI Directors Discretionary UV initiative ULLYSES, together with the complementary spectroscopic survey XShootU (VLT/Xshooter) and other ancillary datasets. Together, ULLYSES and XShootU permit the first comprehensive, homogeneous study of wind densities and velocities

Achilles D. Speliotopoulos

A recently proposed extension of the geodesic equations of motion, where the worldline traced by a test particle now depends on the scalar curvature, is used to study the formation of galaxies and galactic rotation curves. This extension is applied to the motion of a fluid in a spherical geometry, resulting in a set of evolution equations for the fluid in th

Partha Nandi, Sounak Pal, Sayan Kumar Pal, Bibhas Ranjan Majhi

The detection of low frequency gravitational waves (LFGWs) astronomy has marked an advent of new era in the domain of astrophysics and general relativity. Using the framework of interaction between GWs and a point two-particles like detector, within linearized gravity approach, we propose a toy detector model whose quantum state is being investigated at a lo

Justin Y. Chen, Piotr Indyk, Tal Wagner

Histograms, i.e., piece-wise constant approximations, are a popular tool used to represent data distributions. Traditionally, the difference between the histogram and the underlying distribution (i.e., the approximation error) is measured using the $L_p$ norm, which sums the differences between the two functions over all items in the domain. Although useful

Itzhak Goldman, Robert Fleck

Continued star formation over the lifetime of a galaxy suggests that low metalicity gas is steadily flowing in from the circumgalactic medium. Also, cosmological simulations of large-scale structure formation imply that gas is accreted onto galaxies from the halo inside which they formed. Direct observations are difficult, but in recent years observational i

Iosif Petrakis, Max Zeuner

Bishop's measure theory (BMT) is an abstraction of the measure theory of a locally compact metric space $X$, and the use of an informal notion of a set-indexed family of complemented subsets is crucial to its predicative character. The more general Bishop-Cheng measure theory (BCMT) is a constructive version of the classical Daniell approach to measure and i

Ziv Goldfeld, Kengo Kato, Gabriel Rioux, Ritwik Sadhu

We study limit theorems for entropic optimal transport (EOT) maps, dual potentials, and the Sinkhorn divergence. The key technical tool we use is a first and second-order Hadamard differentiability analysis of EOT potentials with respect to the marginal distributions, which may be of independent interest. Given the differentiability results, the functional d

Yair Caro, John R. Schmitt

We generalize the notion of Erd\H{o}s-Ginzburg-Ziv constants -- along the same lines we generalized in earlier work the notion of Davenport constants -- to a ``higher degree" and obtain various lower and upper bounds. These bounds are sometimes exact as is the case for certain finite commutative rings of prime power cardinality. We also consider to what exte

Sachin Gautham, Tarak Patra

Grafting polymer chains on nanoparticles surfaces is a well-known route to control their self assembly and distribution in a polymer matrix. A wide variety of self assembled structures are achieved by changing the grafting patterns on an individual nanoparticle surface. However, accurate estimation of the effective potential of mean force between a pair of g

Nicolas Berti, Kilian Baudin, Adrien Fusaro, Guy Millot

We address the problem of thermalization in the presence of a time-dependent disorder in the framework of the nonlinear Schr\"odinger (or Gross-Pitaevskii) equation with a random potential. The thermalization to the Rayleigh-Jeans distribution is driven by the nonlinearity. On the other hand, the structural disorder is responsible for a relaxation toward the

Sofia Herbers, Sebastian Häfner, Sören Dörscher, Tim Lücke

We present a transportable ultra-stable clock laser system based on a Fabry-P\'erot cavity with crystalline Al$_{0.92}$Ga$_{0.08}$As/GaAs mirror coatings, fused silica (FS) mirror substrates and a 20~cm-long ultra-low expansion (ULE\textsuperscript{\textregistered}) glass spacer with a predicted thermal noise floor of $\mathrm{mod}\,\sigma_\mathrm{y} = 7 \ti

René van Bevern, Daniel A. Skachkov

The NP-hard graphical traveling salesman problem (GTSP) is to find a closed walk of total minimum weight that visits each vertex in an undirected edge-weighted and not necessarily complete graph. We present a problem kernel with $\tau^2+\tau$ vertices for GTSP, where $\tau$ is the vertex cover number of the input graph. Any $\alpha$-approximate solution for

Wanhua Li, Zhexuan Cao, Jianjiang Feng, Jie Zhou

Objects are usually associated with multiple attributes, and these attributes often exhibit high correlations. Modeling complex relationships between attributes poses a great challenge for multi-attribute learning. This paper proposes a simple yet generic framework named Label2Label to exploit the complex attribute correlations. Label2Label is the first atte

Liu-Ye Meng, Rong-Yao Yang, Wei-Zhou Jiang

The mid-infrared heating of interfacial water with different initial temperatures is studied using non-equilibrium molecular dynamics simulation. It is found that under the irradiation of a pulse at 3360-3380 $cm^{-1}$ the two-dimensional water monolayer on a hydrophilic surface at a lower initial temperature acquires a much larger temperature jump. The mech

Geoffrey Négiar, Michael W. Mahoney, Aditi S. Krishnapriyan

We introduce a practical method to enforce partial differential equation (PDE) constraints for functions defined by neural networks (NNs), with a high degree of accuracy and up to a desired tolerance. We develop a differentiable PDE-constrained layer that can be incorporated into any NN architecture. Our method leverages differentiable optimization and the i

Yuhao Huang, Hang Dong, Jinshan Pan, Chao Zhu

The success of existing video super-resolution (VSR) algorithms stems mainly exploiting the temporal information from the neighboring frames. However, none of these methods have discussed the influence of the temporal redundancy in the patches with stationary objects and background and usually use all the information in the adjacent frames without any discri

Alfredo Reichlin, Giovanni Luca Marchetti, Hang Yin, Ali Ghadirzadeh

Learning from previously collected datasets of expert data offers the promise of acquiring robotic policies without unsafe and costly online explorations. However, a major challenge is a distributional shift between the states in the training dataset and the ones visited by the learned policy at the test time. While prior works mainly studied the distributio

Rong-Yao Yang, Wei-Zhou Jiang, Pei-Ying Huo, Qi-Lin Zhang

The energy absorption on nanometer scale is vital for many bio and chemical systems. We report here that a two times amplification in absorption efficiency can be achieved by water molecules confined in carbon nanotubes with small radius, compared with situations in normal bulk water, under irradiations of short mid-infrared pulses. The effect of confinement

Xavier Calmet, Stephen D. H. Hsu

In this invited review, we describe Hawking's information paradox and a recently proposed resolution of it. Explicit calculations demonstrate the existence of quantum hair on black holes, meaning that the quantum state of the external graviton field depends on the internal state of the black hole. Simple quantum mechanics then implies that Hawking radiation

Ricardo Baptista, Youssef Marzouk, Olivier Zahm

We consider the problem of reducing the dimensions of parameters and data in non-Gaussian Bayesian inference problems. Our goal is to identify an "informed" subspace of the parameters and an "informative" subspace of the data so that a high-dimensional inference problem can be approximately reformulated in low-to-moderate dimensions, thereby improving the co

Karlheinz Gröchenig, José Luis Romero, Michael Speckbacher

We study one-parameter families of pseudodifferential operators whose Weyl symbols are obtained by dilation and a smooth deformation of a symbol in a weighted Sj\"ostrand class. We show that their spectral edges are Lipschitz continuous functions of the dilation or deformation parameter. Suitably local estimates hold also for the edges of every spectral gap.

Jacob Renn, Ian Sotnek, Benjamin Harvey, Brian Caffo

Neural networks have seen an explosion of usage and research in the past decade, particularly within the domains of computer vision and natural language processing. However, only recently have advancements in neural networks yielded performance improvements beyond narrow applications and translated to expanded multitask models capable of generalizing across

Emily Tyler, Anne M. Green, Simon P. Goodwin

Dark matter in the form of compact objects with mass $M_{\rm co} \gtrsim 10 M_{\odot}$ can be constrained by its dynamical effects on wide binary stars. Motivated by the recent interest in Primordial Black Hole dark matter, we revisit the theoretical modelling involved in these constraints. We improve on previous studies in several ways. Specifically, we i)

Ping Li, Weijie Zhao

In this work, we demonstrate the advantage of the pGMM (``powered generalized min-max'') kernel in the context of (ridge) regression. In recent prior studies, the pGMM kernel has been extensively evaluated for classification tasks, for logistic regression, support vector machines, as well as deep neural networks. In this paper, we provide an experimental stu

Saad Ashfaq, MohammadHossein AskariHemmat, Sudhakar Sah, Ehsan Saboori

Deep Learning has been one of the most disruptive technological advancements in recent times. The high performance of deep learning models comes at the expense of high computational, storage and power requirements. Sensing the immediate need for accelerating and compressing these models to improve on-device performance, we introduce Deeplite Neutrino for pro

Inigo Val Slijepcevic, Anna M. M. Scaife, Mike Walmsley, Micah Bowles

Unknown class distributions in unlabelled astrophysical training data have previously been shown to detrimentally affect model performance due to dataset shift between training and validation sets. For radio galaxy classification, we demonstrate in this work that removing low angular extent sources from the unlabelled data before training produces qualitativ

Kyriakos Schwarz, Daniel Trejo Banos, Giulia Rathmes, Michael Krauthammer

In recent decades, there has been an increase in polypharmacy, the concurrent administration of multiple drugs per patient. Studies have shown that polypharmacy is linked to adverse patient outcomes and there is interest in elucidating the exact causes behind this observation. In this paper, we are studying the relationship between drug prescriptions, drug-d

Marah Halawa, Olaf Hellwich, Pia Bideau

Trajectory prediction is an essential task for successful human robot interaction, such as in autonomous driving. In this work, we address the problem of predicting future pedestrian trajectories in a first person view setting with a moving camera. To that end, we propose a novel action-based contrastive learning loss, that utilizes pedestrian action informa

A. La Rooij, C. Ulm, E. Haller, S. Kuhr

Quantum-gas microscopes are used to study ultracold atoms in optical lattices at the single particle level. In these system atoms are localised on lattice sites with separations close to or below the diffraction limit. To determine the lattice occupation with high fidelity, a deconvolution of the images is often required. We compare three different technique

Lissa de Souza Campos, Claudio Dappiaggi, Luca Sinibaldi

We review the construction of ground states focusing on a real scalar field whose dynamics is ruled by the Klein-Gordon equation on a large class of static spacetimes. As in the analysis of the classical equations of motion, when enough isometries are present, via a mode expansion the construction of two-point correlation functions boils down to solving a se

Philipp Schienbein

Vibrational spectroscopy is a key technique to elucidate microscopic structure and dynamics. Without the aid of theoretical approaches, it is however, often difficult to understand such spectra at a microscopic level. Ab initio molecular dynamics have repeatedly proved to be suitable for this purpose, however, the computational cost can be daunting. Here, th

Hong-Yan Zhou, Fu-Lai Wang, Zhan-Wei Liu, Xiang Liu

In this work, we discuss the electromagnetic properties of the $S$-wave $\Sigma_c^{(*)}D^{(*)}$-type doubly charmed molecular pentaquarks, which have close relation to their inner structures. Both the $S$-$D$ wave mixing effect and the coupled channel effect are taken into account. We analyze the magnetic moments for the $S$-wave $\Sigma_c^{(*)}D^{(*)}$ mole

I. Bochkov

We show that the analytic continuations of Helson zeta functions $ \zeta_\chi (s)= \sum_1^{\infty}\chi(n)n^{-s} $ can have essentially arbitrary poles and zeroes in the strip $ 21/40 < \Re s < 1 $ (unconditionally), and in the whole critical strip $ 1/2 < \Re s <1 $ under Riemann Hypothesis for the function $ \chi $ taking values in cubic roots of unity. If

Matteo Gaibotti, Davide Bigoni, Sofia G. Mogilevskaya

A circular elastic disk is coated with an elastic beam, absorbing shear and normal forces without deformation and linearly reacting to a bending moment with a change in curvature. The inexstensibility of the elastic beam introduces an isoperimetric constraint, so that the length of the initial circumference of the disk is constrained to remain fixed during t

Isaac McMahon, Markus Michael Rau, Rachel Mandelbaum

The calibration of redshift distributions for photometric samples using spectroscopic surveys is plagued by the difficulty in modelling the selection functions of spectroscopic surveys. In this work, we analyse how these selection functions impact redshift inference and quantify the induced biases using local calibration tests in photometry space. The study

Haolin Liu, Yujian Zheng, Guanying Chen, Shuguang Cui

We present a new framework to reconstruct holistic 3D indoor scenes including both room background and indoor objects from single-view images. Existing methods can only produce 3D shapes of indoor objects with limited geometry quality because of the heavy occlusion of indoor scenes. To solve this, we propose an instance-aligned implicit function (InstPIFu) f

Marvin Klimke, Jasper Gerigk, Benjamin Völz, Michael Buchholz

The improvement of traffic efficiency at urban intersections receives strong research interest in the field of automated intersection management. So far, mostly non-learning algorithms like reservation or optimization-based ones were proposed to solve the underlying multi-agent planning problem. At the same time, automated driving functions for a single ego

Tiantian Zhang, Shuichi Murakami

Weyl points, carrying a Z-type monopole charge C, have bulk-surface correspondence (BSC) associated with helical surface states (HSSs). When |C| > 1, multi-HSSs can appear in a parallel manner. However, when a pair of Weyl points carrying C = \pm 1 meet, a Dirac point carrying C = 0 can be obtained and the BSC vanishes. Nonetheless, a recent study in Ref. [a

Guodong Ding, Angela Yao

We present a semi-supervised learning approach to the temporal action segmentation task. The goal of the task is to temporally detect and segment actions in long, untrimmed procedural videos, where only a small set of videos are densely labelled, and a large collection of videos are unlabelled. To this end, we propose two novel loss functions for the unlabel

Alejandra Aguirre-Santaella, Miguel A. Sánchez-Conde, Go Ogiya, Jens Stücker

In this work, we carry out a suite of specially-designed numerical simulations to shed further light on dark matter (DM) subhalo survival at mass scales relevant for gamma-ray DM searches, a topic subject to intense debate nowadays. Specifically, we have developed and employed an improved version of DASH, a GPU $N$-body code, to study the evolution of low-ma

James McCarthy, Rahul Nair, Elizabeth Daly, Radu Marinescu

Explainability of Reinforcement Learning (RL) policies remains a challenging research problem, particularly when considering RL in a safety context. Understanding the decisions and intentions of an RL policy offer avenues to incorporate safety into the policy by limiting undesirable actions. We propose the use of a Boolean Decision Rules model to create a po

Zihao Wang, Ravi Suppiah

Upper limb movement classification, which maps input signals to the target activities, is a key building block in the control of rehabilitative robotics. Classifiers are trained for the rehabilitative system to comprehend the desires of the patient whose upper limbs do not function properly. Electromyography (EMG) signals and Electroencephalography (EEG) sig

Christopher J. Paciorek

We develop a flexible spline-based Bayesian hidden Markov model stochastic weather generator to statistically model daily precipitation over time by season at individual locations. The model naturally accounts for missing data (considered missing at random), avoiding potential sensitivity from systematic missingness patterns or from using arbitrary cutoffs t

Laurent Bonnasse-Gahot

There has been a long history of works showing that neural networks have hard time extrapolating beyond the training set. A recent study by Balestriero et al. (2021) challenges this view: defining interpolation as the state of belonging to the convex hull of the training set, they show that the test set, either in input or neural space, cannot lie for the mo

J. J. A. Baselmans, F. Facchin, A. Pascual Laguna, J. Bueno

Future actively cooled space-borne observatories for the far-infrared, loosely defined as a 1--10 THz band, can potentially reach a sensitivity limited only by background radiation from the Universe. This will result in an increase in observing speed of many orders of magnitude. A spectroscopic instrument on such an observatory requires large arrays of detec

Mohammad Tohidi Vahdat, Kumar Agrawal Varoon, Giovanni Pizzi

Two-dimensional (2D) materials have been a central focus of recent research because they host a variety of properties, making them attractive both for fundamental science and for applications. It is thus crucial to be able to identify accurately and efficiently if bulk three-dimensional (3D) materials are formed by layers held together by a weak binding ener

Alexander Venus, Erik Leitinger, Stefan Tertinek, Klaus Witrisal

This paper presents a factor graph formulation and particle-based sum-product algorithm (SPA) for robust sequential localization in multipath-prone environments. The proposed algorithm jointly performs data association, sequential estimation of a mobile agent position, and adapts all relevant model parameters. We derive a novel non-uniform false alarm (FA) m

David Lindner, Andreas Krause, Giorgia Ramponi

Inverse Reinforcement Learning (IRL) is a powerful paradigm for inferring a reward function from expert demonstrations. Many IRL algorithms require a known transition model and sometimes even a known expert policy, or they at least require access to a generative model. However, these assumptions are too strong for many real-world applications, where the envi

Demba Barry, Alexandre Masquelein, Anne Quéguiner-Mathieu

Using the Rost invariant for non split simply connected groups, we define a relative degree $3$ cohomological invariant for pairs of orthogonal or unitary involutions having isomorphic Clifford or discriminant algebras. The main purpose of this paper is to study general properties of this invariant in the unitary case, that is for torsors under groups of out

Arjan Cornelissen, Yassine Hamoudi

We present a novel quantum algorithm for estimating Gibbs partition functions in sublinear time with respect to the logarithm of the size of the state space. This is the first speed-up of this type to be obtained over the seminal nearly-linear time algorithm of \v{S}tefankovi\v{c}, Vempala and Vigoda [JACM, 2009]. Our result also preserves the quadratic spee

C. T. Nguyen, G. Costa, L. Girardi, G. Volpato

We present a new comprehensive collection of stellar evolutionary tracks and isochrones for rotating low- and intermediate-mass stars assembled with the updated version of PARSEC V2.0. This version includes our recent calibration of the extra mixing from overshooting and rotation, as well as several improvements in nuclear reaction network, treatment of conv

Qi-Yang Zheng

We prove that there exist infinitely many (-1,1)-Carmichael numbers, that is, square-free, composite integers n such that p+1 divides n-1 for each prime p dividing n.

João Conde, Ricardo Moreira, João Torres, Pedro Cardoso

Monitoring the behavior of automated real-time stream processing systems has become one of the most relevant problems in real world applications. Such systems have grown in complexity relying heavily on high dimensional input data, and data hungry Machine Learning (ML) algorithms. We propose a flexible system, Feature Monitoring (FM), that detects data drift

Shulim Kaliman

Let $Z$ be an affine algebraic variety and $X$ be a smooth flexible variety. We develop some criteria under which $Z$ admits a closed embedding into $X$. In particular, we show that if $X$ is isomorphic (as an algebraic variety) to a special linear group and $\dim X \geq \max(2\dim Z+1, \dim TZ)$, then $Z$ admits a closed embedding into $X$.

Valerio De Luca

We dedicate this thesis to the study of signatures coming from the primordial epochs of the universe. We will focus in particular on Primordial Black Holes (PBHs), which may be formed from perturbations generated during inflation and might comprise a fraction of the dark matter in the universe. In the first part of the thesis, we will address the PBH propert

A. Marino, A. Anitra, S. M. Mazzola, T. Di Salvo

The neutron star low-mass X-ray binary SWIFT J1749.4-2807 is the only known eclipsing accreting millisecond X-ray pulsar. In this manuscript we perform a spectral characterization of the system throughout its 2021, two-week-long outburst, analyzing 11 NICER observations and quasi-simultaneous XMM-Newton and NuSTAR single observations at the outburst peak. Th

Jorge I. Zuluaga, Mario Sucerquia, Jaime A. Alvarado-Montes

Rings around exoplanets (exorings) are one of the most expected discoveries in exoplanetary research. There is an increasing number of theoretical and observational efforts for detecting exorings, but none of them have succeeded yet. Most of those methods focus on the photometric signatures of exorings during transits, whereas less attention has been paid to

Jiaan Wang, Tingyi Zhang, Haoxiang Shi

Sports game summarization aims to generate sports news based on real-time commentaries. The task has attracted wide research attention but is still under-explored probably due to the lack of corresponding English datasets. Therefore, in this paper, we release GOAL, the first English sports game summarization dataset. Specifically, there are 103 commentary-ne

Chen Feng, Zihao Qi, Duolikun Danier, Fan Zhang

It is well known that high dynamic range (HDR) video can provide more immersive visual experiences compared to conventional standard dynamic range content. However, HDR content is typically more challenging to encode due to the increased detail associated with the wider dynamic range. In this paper, we improve HDR compression performance using the effective

G. J. Escobar, L. J. Pellizza, G. E. Romero

Supernova remnants are believed to be the main sites where Galactic cosmic rays originate. This scenario, however, fails to explain some of the features observed in the cosmic-ray spectrum. Microquasars have been proposed as additional candidates, because their non-thermal emission indicates the existence of efficient particle acceleration mechanisms in thei

Jonas Berx

A detailed comparison is made between four different iterative procedures: Picard, Ishikawa, Mann and Picard-Krasnoselskii, within the framework of the BLUES function method and the variational iteration method. The resulting modified methods are subsequently applied to a nonlinear reaction-diffusion-advection differential equation to generate approximations

Chao Chen, Yu-Shen Liu, Zhizhong Han

Deep implicit functions have shown remarkable shape modeling ability in various 3D computer vision tasks. One drawback is that it is hard for them to represent a 3D shape as multiple parts. Current solutions learn various primitives and blend the primitives directly in the spatial space, which still struggle to approximate the 3D shape accurately. To resolve

Ziqiang Li, Chaoyue Wang, Heliang Zheng, Jing Zhang

Data-Efficient GANs (DE-GANs), which aim to learn generative models with a limited amount of training data, encounter several challenges for generating high-quality samples. Since data augmentation strategies have largely alleviated the training instability, how to further improve the generative performance of DE-GANs becomes a hotspot. Recently, contrastive

Chuang Liu, Xueqi Ma, Yibing Zhan, Liang Ding

Graph Neural Networks (GNNs) tend to suffer from high computation costs due to the exponentially increasing scale of graph data and the number of model parameters, which restricts their utility in practical applications. To this end, some recent works focus on sparsifying GNNs with the lottery ticket hypothesis (LTH) to reduce inference costs while maintaini

Patrick Rall, Bryce Fuller

Amplitude estimation algorithms are based on Grover's algorithm: alternating reflections about the input state and the desired outcome. But what if we are given the ability to perform arbitrary rotations, instead of just reflections? In this situation, we find that quantum signal processing lets us estimate the amplitude in a more flexible way. We leverage t

Kshitijkumar Surjuse, Somesh Chamoli, Malaya K. Nayak, Achintya Kumar Dutta

We present the theory and the implementation of a low-cost four-component relativistic equation of motion coupled cluster method for ionized states based on frozen natural spinors. A single threshold (natural spinor occupancy) can control the accuracy of the calculated ionization potential values. Frozen natural spinors can significantly reduce the computati

Dragomir Šarić

We prove that an infinite Riemann surface $X$ is parabolic ($X\in O_G$) if and only if the union of the horizontal trajectories of any integrable holomorphic quadratic differential that are cross-cuts is of zero measure. Then we establish the density of the Jenkins-Strebel differentials in the space of all integrable quadratic differentials when $X\in O_G$ a

Andrea Kubin, Lorenzo Lamberti

We study the energy of a ferromagnetic/antiferromagnetic frustrated spin system with values on two disjoint circumferences of the 3-dimensional unit sphere in a one-dimensional and two-dimensional domain. It consists on the sum of a term that depends on the nearest and next-to-nearest interactions and a penalizing term that counts the spin's magnetic anisotr

Qi Zhang, Yuqing Song, Qin Jin

Dense video captioning aims to generate corresponding text descriptions for a series of events in the untrimmed video, which can be divided into two sub-tasks, event detection and event captioning. Unlike previous works that tackle the two sub-tasks separately, recent works have focused on enhancing the inter-task association between the two sub-tasks. Howev

Fabio Nicola, Paolo Tilli

Time-frequency localization operators (with Gaussian window) $L_F:L^2(\mathbb{R}^d)\to L^2(\mathbb{R}^d)$, where $F$ is a weight in $\mathbb{R}^{2d}$, were introduced in signal processing by I. Daubechies in 1988, inaugurating a new, geometric, phase-space perspective. Sharp upper bounds for the norm (and the singular values) of such operators turn out to be

Mohit Lal Bera, Manabendra Nath Bera

Classical Bayes' rule lays the foundation for the classical causal relation between cause (input) and effect (output). This causal relation is believed to be universally true for all physical processes. Here we show, on the contrary, that it is inadequate to establish correct correspondence between cause and effect in quantum mechanics. In fact, there are in

Mattia Bernetti, Giovanni Bussi

Conformational dynamics is crucial for ribonucleic acid (RNA) function. Techniques such as nuclear magnetic resonance, cryo-electron microscopy, small- and wide-angle X-ray scattering, chemical probing, single-molecule F\"orster resonance energy transfer or even thermal or mechanical denaturation experiments probe RNA dynamics at different time and space res

Amin Aboubrahim, Lutz Althueser, Michael Klasen, Pran Nath

In 2020 the XENON1T experiment observed an excess of events with an electron recoil energy $E_R$ in the range of $2\,$--$\,3\,$keV. Such an excess can arise from a variety of sources such as solar axions or a neutrino magnetic moment, but also from inelastic scattering of dark matter off the xenon atoms. The recoil energy of the electron then depends on the

Yao Zhou, K. Aleynikova, N. M. Ferraro

Sawtooth-like core electron temperature crashes have been observed in W7-X experiments with electron cyclotron current drive. We present nonlinear single-fluid magnetohydrodynamic simulations of this phenomenon using the newly developed stellarator modeling capability of the M3D-$C^1$ code. The near-axis current drive gives rise to two $\iota=1$ resonances i

Yordanka Velikova, Walter Simson, Mehrdad Salehi, Mohammad Farid Azampour

Abdominal aortic aneurysm (AAA) is a vascular disease in which a section of the aorta enlarges, weakening its walls and potentially rupturing the vessel. Abdominal ultrasound has been utilized for diagnostics, but due to its limited image quality and operator dependency, CT scans are usually required for monitoring and treatment planning. Recently, abdominal

Derui Sheng, Tau Zhou

This paper studies hitting properties for the system of generalized fractional kinetic equations driven by Gaussian noise fractional in time and white or colored in space. We derive the mean square modulus of continuity and some second order properties of the solution. These are applied to deduce lower and upper bounds for probabilities that the path process

Simon Brendle, Sven Hirsch, Florian Johne

The Theorem of Bonnet--Myers implies that manifolds with topology $M^{n-1} \times \mathbb{S}^1$ do not admit a metric of positive Ricci curvature, while the resolution of Geroch's conjecture implies that the torus $\mathbb{T}^n$ does not admit a metric of positive scalar curvature. In this work we introduce a new notion of curvature interpolating between Ric

Debraj Chandra, Nur Alam

We introduce the weaker forms of the Scheepers property, namely almost Scheepers (${\sf aS}$), weakly Scheepers in the sense of Sakai (${\sf wS}$) and weakly Scheepers in the sense of Ko\v{c}inac (${\sf wS_k}$). We explore many topological properties of the weaker forms of the Scheepers property and present few illustrative examples to make distinction betwe

Yang Liu, Hongen Zhu, Haifeng Lv, Yuqiao Guo

Excitonic insulators are long-sought-after quantum materials predicted to spontaneously open a gap by the Bose condensation of bound electron-hole pairs, namely, excitons, in their ground state. Since the theoretical conjecture, extensive efforts have been devoted to pursuing excitonic insulator platforms for exploring macroscopic quantum phenomena in real m

ATLAS Collaboration

The total and differential Higgs boson production cross-sections are measured through a combined statistical analysis of the $H \rightarrow ZZ^* \rightarrow 4\ell$ and $H \rightarrow \gamma \gamma$ decay channels. The results are based on a dataset of 139 fb$^{-1}$ of proton-proton collisions at a centre-of-mass energy of 13 TeV, recorded by the ATLAS detect

Veekesh Kumar

Let $P(x):=a_d x^d+\cdots+a_0\in\mathbb{Q}[x]$, $a_d>0$, be a polynomial of degree $d\geq 2$. Let $(x_n)$ be a sequence of integers satisfying \begin{equation*} x_{n+1}=P(x_n)\mbox{for all}\quad n=0,1,2\ldots,\quad\mbox{and} \quad x_n\to\infty\quad\mbox{as}\quad n\to\infty. \end{equation*} Set $\alpha:=\lim_{n\to\infty} x^{d^{-n}}_n$. Then, under the assumpt

Marcelo Brutti Righi, Marlon Ruoso Moresco

We propose the Star-Shaped deviation measures in the same vein as Star-Shaped risk measures and Star-Shaped acceptability indexes. We characterize Star-Shaped deviation measures through Star-Shaped acceptance sets and as the minimum of a family of Convex deviation measures. We also expose an interplay between Star-Shaped risk measures and deviation measures.

Nico Hahn, Mario Kieburg, Omri Gat, Thomas Guhr

Topological invariance is a powerful concept in different branches of physics as they are particularly robust under perturbations. We generalize the ideas of computing the statistics of winding numbers for a specific parametric model of the chiral Gaussian Unitary Ensemble to other chiral random matrix ensembles. Especially, we address the two chiral symmetr

Arghya Chattopadhyay, Nihal M, Debangshu Mukherjee

We study the flow equations of the shear response functions for hyperscaling violating Lifshitz (hvLif) theories, with Lifshitz and hyperscaling violating exponents $z$ and $\theta$. Adapting the membrane paradigm approach of analysing response functions as developed by Iqbal and Liu, we focus specifically on the shear gravitational modes which now are coupl

Vladimir Kh. Dobruskin

The thermodynamic approach shows that the total energy produced by humanity disrupts the thermal balance of the planet and causes counteraction, that is, climate change, which can slow down the progress of civilization. This outcome not only confirms the consensus on the role of humanity in climate change, but also quantifies it. The calculation of the avera

Jin Gyu Lee, Rodolphe Sepulchre

This paper examines how weak synaptic coupling can achieve rapid synchronization in heterogeneous networks. The assumptions aim at capturing the key mathematical properties that make this possible for biophysical networks. In particular, the combination of nodal excitability and synaptic coupling are shown to be essential to the phenomenon.

Lakshman Balasubramanian, Jonas Wurst, Robin Egolf, Michael Botsch

Representation learning in recent years has been addressed with self-supervised learning methods. The input data is augmented into two distorted views and an encoder learns the representations that are invariant to distortions -- cross-view prediction. Augmentation is one of the key components in cross-view self-supervised learning frameworks to learn visual

Anna Sonnefeld, Aiky Razanahoera, Geoffrey Bodenhausen, Kirill Sheberstov

It is shown that long-lived states (LLS) involving pairs of methylene protons in nuclear magnetic resonance (NMR) can be readily excited in common molecules that contain two or more neighboring CH$_2$ groups. Accessing such LLS does not require any isotopic enrichment, nor does it require any stereogenic centers to lift the chemical equivalence of CH$_2$ pro