July 2022 arXiv papers — page 31

Isaac Konan

For all positive integers $k,l,n$, the Little Glaisher theorem states that the number of partitions of $n$ into parts not divisible by $k$ and occurring less than $l$ times is equal to the number of partitions of $n$ into parts not divisible by $l$ and occurring less than $k$ times. While this refinement of Glaisher theorem is easy to establish by computatio

Tomasz Jakubowski, Grzegorz Serafin

We consider the fractional Burgers equation $ \Delta^{\alpha/2} u + b\cdot \nabla (u|u|^{(\alpha-1)/\beta})$ on ${\mathbf R}^d$, $d\geq2$, with {$\alpha \in (1,2)$ and} $\beta>1$ and prove the existence of a solution for a large class of initial conditions, which contains functions that do not belong to any $L^p({\mathbf R}^d)$, $1\leq p\leq\infty$. Next, we

Rashmish K. Mishra

The relation between confinement scale $\Lambda_c$ of a gauge theory and the Hubble scale $H$ of the background quasi de Sitter space, required to satisfy the Festina Lente criteria ($\Lambda_c \gtrsim H$) from swampland principles, are investigated for a holographic theory using the Karch-Randall setup. A purely gravitational description admits unstable de

Claudia García, Javier Gómez-Serrano

In this paper we construct a large class of non-trivial (non-radial) self-similar solutions of the generalized surface quasi-geostrophic equation (gSQG). To the best of our knowledge, this is the first rigorous construction of any self-similar solution for these equations. The solutions are of spiral type, locally integrable, and may have mixed sign. Moreove

Leonardo Bonati, Michele Polese, Salvatore D'Oro, Stefano Basagni

Open Radio Access Network (RAN) architectures will enable interoperability, openness and programmable data-driven control in next generation cellular networks. However, developing and testing efficient solutions that generalize across heterogeneous cellular deployments and scales, and that optimize network performance in such diverse environments is a comple

Alessandro Achille, Stefano Soatto

We revisit the classic signal-to-symbol barrier in light of the remarkable ability of deep neural networks to generate realistic synthetic data. DeepFakes and spoofing highlight the feebleness of the link between physical reality and its abstract representation, whether learned by a digital computer or a biological agent. Starting from a widely applicable de

C. Reinhoffer, P. Pilch, A. Reinold, P. Derendorf

We report on high-order harmonic generation in the two-band superconductor MgB$_2$ driven by intense terahertz electromagnetic pulses. Third- and fifth-order harmonics are resolved in time domain and investigated as a function of temperature and in applied magnetic fields crossing the superconducting phase boundary. The high-order harmonics in the supercondu

Pedro Machado, T. M. McGinnity

Robots are expected to grasp a wide range of objects varying in shape, weight or material type. Providing robots with tactile capabilities similar to humans is thus essential for applications involving human-to-robot or robot-to-robot interactions, particularly in those situations where a robot is expected to grasp and manipulate complex objects not previous

Xiaoyue Ma, Tianyi Gu

Oscillation can be observed in candle flames under certain circumstances. This research theoretically proposed an hydrodynamic-instability-based approach towards the oscillation and coupling of candle flames, claiming that the visible flame is part of a jet flow undergoing three stages: laminar, wave, and turbulence. In the ordinary stable combustion the vis

Kathleen Mandt, Adrienn Luspay-Kuti, Jacob Lustig-Yaeger, Ryan Felton

The TRAPPIST-1 system is home to at least seven terrestrial planets and is a target of interest for future James Webb Space Telescope (JWST) observations. Additionally, these planets will be of interest to future missions making observations in the ultraviolet (UV). Although several of these planets are located in the traditional habitable zone, where liquid

Sicheng Gong, Vladimir Ćuk, Tiago Castelo de Oliveira, J. F. G. Cobben

This chapter proposes an evolved concept of "hosting capacity" using the term of "feasible region". Through converting the grid model into a more compact one, "hosting capacity region" not only is promising to further exploit the grid potential for power delivery, but also benefits grid operation feasibility investigation with concise formulas. The hosting c

C. T. Donnan, D. J. McLeod, J. S. Dunlop, R. J. McLure

We reduce and analyse the available James Webb Space Telescope (JWST) ERO and ERS NIRCam imaging (SMACS0723, GLASS, CEERS) in combination with the latest deep ground-based near-infrared imaging in the COSMOS field (provided by UltraVISTA DR5) to produce a new measurement of the evolving galaxy UV luminosity function (LF) over the redshift range $z = 8 - 15$.

Paul H Frampton

The entropies of the known entities in the universe add to a total which is some twenty orders of magnitude below the holographic limit. Based on an assumption that the entropies should saturate the limit, we suggest that there exists dark matter, in the form of extremely massive primordial black holes, in addition to the dark matter known to exist inside ga

Alex Andrew, Sam Spillard, Joshua Collyer, Neil Dhir

In this paper we explore cyber security defence, through the unification of a novel cyber security simulator with models for (causal) decision-making through optimisation. Particular attention is paid to a recently published approach: dynamic causal Bayesian optimisation (DCBO). We propose that DCBO can act as a blue agent when provided with a view of a simu

Christopher Ekman

We consider integrable boundary states in the XXX spin-1/2 spin chain. We begin by briefly reviewing the algebraic Bethe Ansatz as well as integrable boundary states in spin chains. Then a recently discovered class of integrable states known as crosscap states is described and expanded. In these states each spin is entangled with its antipodal spin. We prese

Eric Sihite, Paul Ghanem, Adarsh Salagame, Alireza Ramezani

Flying animals possess highly complex physical characteristics and are capable of performing agile maneuvers using their wings. The flapping wings generate complex wake structures that influence the aerodynamic forces, which can be difficult to model. While it is possible to model these forces using fluid-structure interaction, it is very computationally exp

A. Singh, H. Y. Huang, J. D. Xie, J. Okamoto

Electron quasiparticles play a crucial role in simplifying the description of many-body physics in solids with surprising success. Conventional Landau's Fermi-liquid and quasiparticle theories for high-temperature superconducting cuprates have, however, received skepticism from various angles. A path-breaking framework of electron fractionalization has been

Ilya Khayutin, Paul D. Nelson, Raphael S. Steiner

For an $L^2$-normalized holomorphic newform $f$ of weight $k$ on a hyperbolic surface of volume $V$ attached to an Eichler order of squarefree level in an indefinite quaternion algebra over $\mathbb{Q}$, we prove the sup-norm estimate \[ \| \Im(\cdot)^{\frac{k}{2}} f \|_{\infty} \ll_{\epsilon} (k V)^{\frac{1}{4}+\epsilon} \] with absolute implied constant. F

Ourania Spantidi, Georgios Zervakis, Iraklis Anagnostopoulos, Jörg Henkel

Deep Neural Networks (DNNs) are being heavily utilized in modern applications and are putting energy-constraint devices to the test. To bypass high energy consumption issues, approximate computing has been employed in DNN accelerators to balance out the accuracy-energy reduction trade-off. However, the approximation-induced accuracy loss can be very high and

Minglei Yang, Diego del-Castillo-Negrete, Guannan Zhang, Matthew Beidler

An interpolation method to evaluate magnetic fields given unstructured, scattered magnetic data is presented. The method is based on the reconstruction of the global magnetic field using a superposition of orthogonal functions. The coefficients of the expansion are obtained by minimizing a cost function defined as the L^2 norm of the difference between the g

Elvira Fleig, Jonas Geistert, Erik Bochinski, Rolf Jongebloed

Steered-Mixtures-of-Experts (SMoE) models provide sparse, edge-aware representations, applicable to many use-cases in image processing. This includes denoising, super-resolution and compression of 2D- and higher dimensional pixel data. Recent works for image compression indicate that compression of images based on SMoE models can provide competitive performa

Aleksandr Berdnikov, Larry Guth, Fedor Manin

We study the degree of an $L$-Lipschitz map between Riemannian manifolds, proving new upper bounds and constructing new examples. For instance, if $X_k$ is the connected sum of $k$ copies of $\mathbb CP^2$ for $k \ge 4$, then we prove that the maximum degree of an $L$-Lipschitz self-map of $X_k$ is between $C_1 L^4 (\log L)^{-4}$ and $C_2 L^4 (\log L)^{-1/2}

Rakshith Subramanyam, Mark Heimann, Jayram Thathachar, Rushil Anirudh

Model agnostic meta-learning algorithms aim to infer priors from several observed tasks that can then be used to adapt to a new task with few examples. Given the inherent diversity of tasks arising in existing benchmarks, recent methods use separate, learnable structure, such as hierarchies or graphs, for enabling task-specific adaptation of the prior. While

Kelly R. Moran, Katrin Heitmann, Earl Lawrence, Salman Habib

Modern cosmological surveys are delivering datasets characterized by unprecedented quality and statistical completeness; this trend is expected to continue into the future as new ground- and space-based surveys come online. In order to maximally extract cosmological information from these observations, matching theoretical predictions are needed. At low reds

Rafael Diógenes, Neilha Pinheiro, Ernani Ribeiro

In this article, we investigate the geometry of critical metrics of the volume functional on compact manifolds with boundary. We use the generalized Reilly's formula to derive new sharp integral estimates for critical metrics of the volume functional on $n$-dimensional compact manifolds with boundary. As application, we establish new boundary estimates for s

S. Sankar, Manil T. Mohan, S. Karthikeyan

In this paper, we obtain the existence and finite-time blow-up for the solution to a system of semilinear stochastic partial differential equations driven by a combination of Brownian and fractional Brownian motions. Under suitable assumptions, lower and upper bounds for the finite-time blow-up solution are obtained. We provide sufficient conditions for the

Paul H. Frampton

We discuss the predictions of the bilepton model which is an extension of the standard model in which the group $SU(2) \times U(1)$ is changed to $SU(3)\times U(1)$ and the fermion families are treated non-sequentially with the third assigned differently from the first two. Cancellation of triangle anomalies and asymptotic freedom require three families. The

Denis E. Sergeev, Neil T. Lewis, F. Hugo Lambert, Nathan J. Mayne

Using a 3D general circulation model, we demonstrate that a confirmed rocky exoplanet and a primary observational target, TRAPPIST-1e presents an interesting case of climate bistability. We find that the atmospheric circulation on TRAPPIST-1e can exist in two distinct regimes for a 1~bar nitrogen-dominated atmosphere. One is characterized by a single strong

P. A. Ameen Yasir, Abhaya S. Hegde, C. M. Chandrashekar

Quantum walks are more than tools for building quantum algorithms. They have been used effectively to model and simulate quantum dynamics in many complex physical processes. Particularly, a variant of discrete-time quantum walk known as split-step quantum walk is closely related to Dirac cellular automata and topological insulators whose realizations rely on

Swetapadma Sahoo, Valery Davydov, Viatcheslav Agafonov, Simeon I. Bogdanov

Optically active color centers in nanodiamonds offer unique opportunities for generating and manipulating quantum states of light. These mechanically, chemically, and optically robust emitters can be produced in mass quantities, deterministically manipulated, and integrated with a variety of quantum device geometries and photonic material platforms. Nanodiam

Yexiang Chen, Subhash Lakshminarayana, Fei Teng

As one of the most sophisticated attacks against power grids, coordinated cyber-physical attacks (CCPAs) damage the power grid's physical infrastructure and use a simultaneous cyber attack to mask its effect. This work proposes a novel approach to detect such attacks and identify the location of the line outages (due to the physical attack). The proposed app

Hakim Atek, Marko Shuntov, Lukas J. Furtak, Johan Richard

One of the main goals of the JWST is to study the first galaxies in the Universe. We present a systematic photometric analysis of very distant galaxies in the first JWST deep field towards the massive lensing cluster SMACS0723. As a result, we report the discovery of two galaxy candidates at $z\sim16$, only $250$ million years after the Big Bang. We also ide

A. Ferragamo, D. de Andres, A. Sbriglio, W. Cui

We develop a machine learning algorithm to infer the 3D cumulative radial profiles of total and gas mass in galaxy clusters from thermal Sunyaev-Zel'dovich effect maps. We generate around 73,000 mock images along various lines of sight using 2,522 simulated clusters from the \thethreehundred{} project at redshift $z< 0.12$ and train a model that combines an

Ruy Fabila-Monroy, Ana Laura Trujillo-Negrete

A diamond is the graph that is obtained from removing an edge from the complete graph on $4$ vertices. A ($C_4$,diamond)-free graph is a graph that does not contain a diamond or a cycle on four vertices as induced subgraphs. Let $G$ be a connected ($C_4$,diamond)-free graph on $n$ vertices. Let $1 \le k \le n-1$ be an integer. The $k$-token graph, $F_k(G)$,

Alexandros Alexakis, Sergio Chibbaro

Using highly resolved direct numerical simulations we examine the statistical properties of the local energy flux rate $\Pi_\ell(x)$ towards small scales for three isotropic turbulent magnetohydrodynamic flows, which differ in strength and structure of the magnetic field. We analyse the cascade process both in the kinetic and magnetic energy, disentangling t

Matt Dallas, Sara Pollock

In this paper we develop convergence and acceleration theory for Anderson acceleration applied to Newton's method for nonlinear systems in which the Jacobian is singular at a solution. For these problems, the standard Newton algorithm converges linearly in a region about the solution; and, it has been previously observed that Anderson acceleration can substa

Jairo Giraldo, Masood Parvania

The integration of synchronous generators and energy storage systems operated through communication networks introduces new challenges and vulnerabilities to the electric grid, where cyber attacks can corrupt sensor measurements or control inputs and interrupt functions such as frequency regulation. This paper proposes a defense methodology for the design of

F. Crawford, S. Hisano, M. Golden, T. Kikunaga

We present four new fast radio bursts discovered in a search of the Parkes 70-cm pulsar survey data archive for dispersed single pulses and bursts. We searched dispersion measures (DMs) ranging between 0 to 5000 pc cm$^{-3}$ with the HEIMDALL and FETCH detection and classification algorithms. All four of the FRBs discovered have significantly larger widths (

Greta Monacelli, Lili Zhang, Winfried Schlee, Berthold Langguth

Recently the use of mobile technologies in Ecological Momentary Assessments (EMA) and Interventions (EMI) has made it easier to collect data suitable for intra-individual variability studies in the medical field. Nevertheless, especially when self-reports are used during the data collection process, there are difficulties in balancing data quality and the bu

Laurent Condat

It is common to have to process signals, whose values are points on the 3-D sphere. We consider a Tikhonov-type regularization model to smoothen or interpolate sphere-valued signals defined on arbitrary graphs. We propose a convex relaxation of this nonconvex problem as a semidefinite program, which is easy to solve numerically and is efficient in practice.

Francesco Mori, Satya N. Majumdar, Gregory Schehr

We consider a one-dimensional stationary time series of fixed duration $T$. We investigate the time $t_{\rm m}$ at which the process reaches the global maximum within the time interval $[0,T]$. By using a path-decomposition technique, we compute the probability density function $P(t_{\rm m}|T)$ of $t_{\rm m}$ for several processes, that are either at equilib

Claus Kadelka

Contact networks are heterogeneous. People with similar characteristics are more likely to interact, a phenomenon called assortative mixing or homophily. While age-assortativity is well-established and social contact matrices for populations stratified by age have been derived through extensive survey work, we lack empirical studies that describe contact pat

Mehrad Sarmashghi, Shantanu P. Jadhav, Uri T. Eden

Neurons can code for multiple variables simultaneously and neuroscientists are often interested in classifying neurons based on their receptive field properties. Statistical models provide powerful tools for determining the factors influencing neural spiking activity and classifying individual neurons. However, as neural recording technologies have advanced

Tian Liu, Xueyang Hu, Tao Shu

Due to the distributed nature of Federated Learning (FL), researchers have uncovered that FL is vulnerable to backdoor attacks, which aim at injecting a sub-task into the FL without corrupting the performance of the main task. Single-shot backdoor attack achieves high accuracy on both the main task and backdoor sub-task when injected at the FL model converge

Lorenzo Ceragioli, Letterio Galletta, Pierpaolo Degano, Luca Viganò

In a decentralized environment, exchanging resources requires users to bargain until an agreement is found. Moreover, human agreements involve a combination of collaborative and selfish behavior and often induce circularity, complicating the evaluation of exchange requests. We introduce MuAC, a policy language that allows users to state in isolation under wh

A. T. M. Anishur Rahman

Dark matter is a major constituent of our universe and the axion is a prime candidate. In this article, it is shown that by exploiting the axion induced magnetization in a magnetic rod and the Faraday effect, axions in the mass range $500$ to $5000~\mu$eV, a part of which ($> 3500~\mu$eV) is currently inaccessible to experiments, can be searched for using th

Robert F. Allen, Flavia Colonna

In this paper, we present the current results in the study of weighted composition operators on the Bloch space of bounded homogeneous domains in $\mathbb{C}^n$ with particular emphasis on the issues of boundedness and compactness. We also discuss the bounded and the compact weighted composition operators from the Bloch space to the Hardy space $H^\infty$.

Massimiliano Lupo Pasini, Junqi Yin

We propose a stable, parallel approach to train Wasserstein Conditional Generative Adversarial Neural Networks (W-CGANs) under the constraint of a fixed computational budget. Differently from previous distributed GANs training techniques, our approach avoids inter-process communications, reduces the risk of mode collapse and enhances scalability by using mul

Tingyuan Liang, Jingsong Chen, Lei Li, Wei Zhang

Custom standard cell libraries can improve the final quality of the corresponding VLSI designs but properly customizing standard cell libraries remains challenging due to the complex characteristics of the VLSI designs. This paper presents an automatic standard-cell library extension framework, AutoCellLibX. It can find a set of standard cell cluster pattern

D. S. Shirokov

For the first time, a complete classification of all constant solutions of the Yang-Mills-Dirac equations with SU(2) gauge symmetry in Minkowski space ${\mathbb R}^{1,3}$ is given. The explicit form of all solutions is presented. We use the method of hyperbolic singular value decomposition of real and complex matrices and the two-sheeted covering of the grou

Pavel Abolmasov, Galina Lipunova

Accretion onto a highly-magnetised neutron star runs through a magnetospheric flow, where the plasma follows the magnetic field lines in the force-free regime. The flow entering the magnetosphere is accelerated by the gravity of the star and then abruptly decelerated in a shock located above the surface of the star. For large enough mass accretion rates, mos

N. Li, Q. Huang, X. Y. Yue, S. K. Guang

We study the magnetic susceptibility, magnetization, resistivity and thermal conductivity of intermetallic HoAgGe single crystals at low temperatures and in magnetic fields along the $a$ and $c$ axis, while the electric and heat currents are along the $c$ axis. The magnetization curves show a series of metamagnetic transitions and small hysteresis at low fie

Javier Caicedo, Pamela Acosta, Romel Pozo, Henry Guilcapi

Artificial Intelligence has enabled the implementation of more accurate and efficient solutions to problems in various areas. In the agricultural sector, one of the main needs is to know at all times the extent of land occupied or not by crops in order to improve production and profitability. The traditional methods of calculation demand the collection of da

Fengjun Li, Xin Feng, Fanglin Chen, Guangming Lu

Typical methods for blind image super-resolution (SR) focus on dealing with unknown degradations by directly estimating them or learning the degradation representations in a latent space. A potential limitation of these methods is that they assume the unknown degradations can be simulated by the integration of various handcrafted degradations (e.g., bicubic

A. L. Chudnovskiy, Alex Kamenev

We present a model of a strongly correlated system with a non-Fermi liquid high temperature phase. Its ground state undergoes an insulator to superconductor quantum phase transition (QPT) as a function of a pairing interaction strength. Both the insulator and the superconductor are originating from the same interaction mechanism. The resistivity in the insul

Zhixiang Chi, Rasoul Mohammadi Nasiri, Zheng Liu, Yuanhao Yu

Video frame interpolation~(VFI) algorithms have improved considerably in recent years due to unprecedented progress in both data-driven algorithms and their implementations. Recent research has introduced advanced motion estimation or novel warping methods as the means to address challenging VFI scenarios. However, none of the published VFI works considers t

Anushree Dey, Arpita Pal, Subhasish Dutta Gupta, Bimalendu Deb

We demonstrate theoretically the feasibility of correlated entangled photon-pair generation with vanishing threshold in a bimodal cavity setup that uses a single V-type three level atom pumped by dual incoherent sources and driven by two coherent fields. The photon-pair is shown to be entangled only for low levels of the incoherent pumps and owes its origin

Deborah Cohen, Moonkyung Ryu, Yinlam Chow, Orgad Keller

Despite recent advances in natural language understanding and generation, and decades of research on the development of conversational bots, building automated agents that can carry on rich open-ended conversations with humans "in the wild" remains a formidable challenge. In this work we develop a real-time, open-ended dialogue system that uses reinforcement

Felix Buchert, Nassir Navab, Seong Tae Kim

The availability of large labeled datasets is the key component for the success of deep learning. However, annotating labels on large datasets is generally time-consuming and expensive. Active learning is a research area that addresses the issues of expensive labeling by selecting the most important samples for labeling. Diversity-based sampling algorithms a

Clara M. Pennock, Jacco Th. van Loon, Joy O. Anih, Chandreyee Maitra

Following the discovery of SAGE0536AGN ($z \sim$ 0.14), with the strongest 10-$\mu$m silicate emission ever observed for an Active Galactic Nucleus (AGN), we discovered SAGE0534AGN ($z \sim$ 1.01), a similar AGN but with less extreme silicate emission. Both were originally mistaken as evolved stars in the Magellanic Clouds. Lack of far-infrared emission, and

Nicolas Petit

The multi-variable affine index polynomial was defined by the author in previous work. The aim of this short note is to update the definition so it is generalizable to virtual tangles and to show it is compatible with tangle decomposition. We also introduce the Turaev moves for virtual tangles, and discuss how to recover the weight of each crossing as an int

Carles Batlle, Victor Campello, Joaquim Gomis

We express the nonlocal BMS charges of a free massless Klein-Gordon scalar field in 2+1 in terms of the Green functions of the polyharmonic operators. Using the properties of these Green functions, we are able to discuss the asymptotic behaviour of the fields that ensures the existence of the charges, and prove that one obtains a realization of the 2+1 BMS a

Tianhan Xu, Tatsuya Harada

Recent advances in radiance fields enable photorealistic rendering of static or dynamic 3D scenes, but still do not support explicit deformation that is used for scene manipulation or animation. In this paper, we propose a method that enables a new type of deformation of the radiance field: free-form radiance field deformation. We use a triangular mesh that

Gilda Manfredi, Nicola Capece, Ugo Erra, Monica Gruosso

3D modeling of non-linear objects from stylized sketches is a challenge even for experts in Computer Graphics (CG). The extrapolation of objects parameters from a stylized sketch is a very complex and cumbersome task. In the present study, we propose a broker system that mediates between the modeler and the 3D modelling software and can transform a stylized

F. Kupka, F. Ahlborn, A. Weiss

Context. Mixing by convective overshooting has long been suggested to play an important role for the amount of hydrogen available to nuclear burning in convective cores of stars. The best way to model this effect is still debated. Aims. We suggest an improved model for the computation of the dissipation rate of turbulent kinetic energy which can be used in n

V. Sotnikov

Pushing the reach of NNLO QCD predictions to $2\to3$ production processes is one of the pillars of precision phenomenology program at the LHC. In this talk we will overview recent results and developments in the calculation of two-loop five-point amplitudes contributing towards achieving this goal. We will discuss challenges encountered in advancing the stat

Sebastian Ujevick, V. Zampronio, B. R. de Abreu, S. A. Vitiello

We investigate strongly correlated many-body systems composed of bosons and fermions with a fully quantum treatment using the path-integral ground state method, PIGS. To account for the Fermi-Dirac statistics, we implement the fixed-node approximation into PIGS, which we then call FN-PIGS. In great detail, we discuss the pair density matrices we use to const

Ruben Pompe, Matthias Hensen, Matthew Otten, Stephen K. Gray

In coupled quantum systems pure dephasing mechanisms acting on one constituent of the hybrid system break symmetry and enable optical transitions which are forbidden in the non-coupled system, i.e., the pure dephasing bath opens a cascaded dissipation pathway. Here we show that this mechanism enables single-photon induced parametric down-conversion in an ult

Eric B Gutierrez, Claire Delplancke, Matthias J Ehrhardt

Stochastic Primal-Dual Hybrid Gradient (SPDHG) is an algorithm proposed by Chambolle et al. (2018) to efficiently solve a wide class of nonsmooth large-scale optimization problems. In this paper we contribute to its theoretical foundations and prove its almost sure convergence for convex but neither necessarily strongly convex nor smooth functionals, as well

William M Feldman

We prove that minimizers and almost minimizers of one-phase free boundary energy functionals in periodic media satisfy large scale (1) Lipschitz estimates (2) free boundary flat implies Lipschitz estimates. The proofs are based on techniques introduced by De Silva and Savin for almost minimizers in homogeneous media.

Nikos Frantzikinakis, Borys Kuca

We give necessary and sufficient conditions for joint ergodicity results of collections of sequences with respect to systems of commuting measure preserving transformations. Combining these results with a new technique that we call "seminorm smoothening", we settle several conjectures related to multiple ergodic averages of commuting transformations with pol

Alexander Baikalov, Ramin Abolfath, Radhe Mohan, Emil Schüler

The mechanism responsible for the FLASH effect, normal tissue sparing by ultra-high dose rate (UHDR) irradiation with isoeffective tumor control compared to conventional dose rate (CDR) irradiation, remains undetermined. Here we investigate the contribution of interspur interactions (interactions between radiolytic species of individual particle tracks) to o

Langlang Xiong, Yu Zhang, Yufu Liu, Yaoxian Zheng

Corner states (CSs) in higher-order topological insulators (HOTIs) have recently been of great interest in both crystals and quasicrystals. In contrast to electronic systems, HOTIs have not been found in photonic quasicrystals (PQCs). Here, we systemically study the higher-order topology in the two-dimensional Thue-Morse photonic quasicrystals (TM-PQCs). Not

Alexey Lichkunov, Artem Popov, Alexander Studenikin

In this paper we study Dirac and Majorana neutrino oscillations in a magnetic field in the three-flavour case. A theoretical framework developed in \cite{Popov:2019} is extended to the case of three neutrino species, as well as to the Majorana neutrinos case. The closed expression for the Dirac neutrinos flavour and spin oscillations are given. Majorana neut

Nadia Skoglund Taki, Kundan Kumar

In this paper, we study the well-posedness of a class of evolutionary variational-hemivariational inequalities coupled with a nonlinear ordinary differential equation in Banach spaces. The proof is based on an iterative approximation scheme showing that the problem has a unique mild solution. In addition, we established the continuity of the flow map with re

Junyi Gao, Chaoqi Yang, George Heintz, Scott Barrows

The COVID-19 pandemic has caused devastating economic and social disruption, straining the resources of healthcare institutions worldwide. This has led to a nationwide call for models to predict hospitalization and severe illness in patients with COVID-19 to inform distribution of limited healthcare resources. We respond to one of these calls specific to the

Yongjung Kim, Myungshin Im, Yiseul Jeon, Minjin Kim

We present the result of the Infrared Medium-deep Survey (IMS) $z\sim6$ quasar survey, using the combination of the IMS near-infrared images and the Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) optical images. The traditional color-selection method results in 25 quasar candidates over $86$ deg$^{2}$. We introduce the corrected Akaike Information Cri

Matthias Wright, Björn Ommer

The field of neural style transfer has experienced a surge of research exploring different avenues ranging from optimization-based approaches and feed-forward models to meta-learning methods. The developed techniques have not just progressed the field of style transfer, but also led to breakthroughs in other areas of computer vision, such as all of visual sy

Martin Ryner, Johan Karlsson

In this paper we propose an adaptive approach for clustering and visualization of data by an orthogonalization process. Starting with the data points being represented by a Markov process using the diffusion map framework, the method adaptively increase the orthogonality of the clusters by applying a feedback mechanism inspired by the Gromov-Wasserstein dist

Gregory Gutin, Matthias Mnich

We survey the field of algorithms and complexity for graph problems parameterized above or below guaranteed values, a research area which was pioneered by Venkatesh Raman. Those problems seek, for a given graph $G$, a solution whose value is at least $g(G)+k$ or at most $g(G)-k$, where $g(G)$ is a guarantee on the value that any solution on $G$ takes. The go

Omar Abdul Halim, Mohammad El Smaily

This paper is concerned with an integral equation that models discrete time dynamics of a population in a patchy landscape. The patches in the domain are reflected through the discontinuity of the kernel of the integral operator at a finite number of points in the whole domain. We prove the existence and uniqueness of a stationary state under certain assumpt

Ivan Horozov

This paper is a natural continuation of a joint paper with Bajpai, Harder and Moya Giusti \cite{BHHM}, even though it began as an answer to Goncharov's question. It that paper, we had complete description for all representations except for odd symmetric powers and their dual ones. For those representations we were left with two options: certain one dimension

Changming Yue, Hideo Aoki, Philipp Werner

Full or empty narrow bands near the Fermi level are known to enhance superconductivity by promoting scattering processes and spin fluctuations. Here, we demonstrate that doublon-holon fluctuations in systems with half-filled narrow bands can similarly boost the superconducting $T_c$. We study the half-filled attractive bilayer Hubbard model on the square lat

Vianney Taquet, Vincent Blot, Thomas Morzadec, Louis Lacombe

Estimating uncertainties associated with the predictions of Machine Learning (ML) models is of crucial importance to assess their robustness and predictive power. In this submission, we introduce MAPIE (Model Agnostic Prediction Interval Estimator), an open-source Python library that quantifies the uncertainties of ML models for single-output regression and

Ekta Chaubey

We highlight the latest developments in computing higher-order scattering amplitudes with massive internal propagators. The contributing Feynman integrals often lead to special classes of functions, for example, functions associated with elliptic curves. With the presence of more scales in the amplitudes, it becomes imperative to have a better understanding

Ashwij Mayya, Estelle Berthier, Laurent Ponson

Continuum mechanics describes compressive failure as a standard bifurcation in the response of a material to an increasing load: damage, which initially grows uniformly in the material, localizes within a thin band at failure. Yet, experiments recording the acoustic activity preceding localization evidence power-law distributed failure precursors of increasi

Pedro Sanchez, Antanas Kascenas, Xiao Liu, Alison Q. O'Neil

Reducing the requirement for densely annotated masks in medical image segmentation is important due to cost constraints. In this paper, we consider the problem of inferring pixel-level predictions of brain lesions by only using image-level labels for training. By leveraging recent advances in generative diffusion probabilistic models (DPM), we synthesize cou

Su Kyoung Kim, Michael Maurus, Mathias Trampler, Marc Tabie

Human-in-the-loop approaches are of great importance for robot applications. In the presented study, we implemented a multimodal human-robot interaction (HRI) scenario, in which a simulated robot communicates with its human partner through speech and gestures. The robot announces its intention verbally and selects the appropriate action using pointing gestur

Friederike Ihssen, Jan M. Pawlowski, Franz R. Sattler, Nicolas Wink

We apply the Local Discontinuous Galerkin discretisation to flow equations of the O(N)-model in the Local Potential Approximation. The improved stability is directly observed by solving the flow equation for various $N$ and space-time dimensions $d$. A particular focus of this work is the numerical discretisation and its implementation. The code is publicly

Niccolò Laurenti, Tanjona R. Rabemananjara, Roy Stegeman

We present a more reliable approach to approximate the unknown next-to-next-to-next-to-leading order (N3LO) transverse momentum distribution of colourless final states, namely the Higgs boson produced via gluon fusion and the lepton pair produced via Drell--Yan (DY) mechanism. The approximation we construct relies on the combination of various resummation fo

Emanuele Brugnoli, Marco Delmastro

The Covid-19 pandemic has sparked renewed attention on the prevalence of misinformation online, whether intentional or not, underscoring the potential risks posed to individuals' quality of life associated with the dissemination of misconceptions and enduring myths on health-related subjects. In this study, we analyze 6 years (2016-2021) of Italian vaccine d

Zhuowen Yuan, Fan Wu, Yunhui Long, Chaowei Xiao

Transfer learning through the use of pre-trained models has become a growing trend for the machine learning community. Consequently, numerous pre-trained models are released online to facilitate further research. However, it raises extensive concerns on whether these pre-trained models would leak privacy-sensitive information of their training data. Thus, in

Raul Fernandez, David Haws, Guy Lorberbom, Slava Shechtman

Sequence-to-Sequence Text-to-Speech architectures that directly generate low level acoustic features from phonetic sequences are known to produce natural and expressive speech when provided with adequate amounts of training data. Such systems can learn and transfer desired speaking styles from one seen speaker to another (in multi-style multi-speaker setting

Sabri Koraltan, Claas Abert, Florian Bruckner, Michael Heigl

We demonstrate the controlled generation and annihilation of (anti)skyrmions with tunable chirality in magnetic heterostructures by means of micromagnetic simulations. By making use of magnetic (anti)vortices in patterned ferromagnetic layer, we stabilize full lattices of (anti)skyrmions in an underlying skyrmionic thin film in a reproducible manner. The sta

AmirPouya Hemmasian, Francis Ogoke, Parand Akbari, Jonathan Malen

Powder-based additive manufacturing has transformed the manufacturing industry over the last decade. In Laser Powder Bed Fusion, a specific part is built in an iterative manner in which two-dimensional cross-sections are formed on top of each other by melting and fusing the proper areas of the powder bed. In this process, the behavior of the melt pool and it

Tan Wang, Qianru Sun, Sugiri Pranata, Karlekar Jayashree

We are interested in learning robust models from insufficient data, without the need for any externally pre-trained checkpoints. First, compared to sufficient data, we show why insufficient data renders the model more easily biased to the limited training environments that are usually different from testing. For example, if all the training swan samples are

Hongyan Guo, Haisheng Li, Shaobin Tan, Qing Wang

In this paper, we study a family of infinite-dimensional Lie algebras $\widehat{X}_{S}$, where $X$ stands for the type: $A,B,C,D$, and $S$ is an abelian group, which generalize the $A,B,C,D$ series of trigonometric Lie algebras. Among the main results, we identify $\widehat{X}_{S}$ with what are called the covariant algebras of the affine Lie algebra $\wideh

Jorge A. Mendez

A hallmark of human intelligence is the ability to construct self-contained chunks of knowledge and reuse them in novel combinations for solving different problems. Learning such compositional structures has been a challenge for artificial systems, due to the underlying combinatorial search. To date, research into compositional learning has largely proceeded

Igor Sadoune, Andrea Lodi, Marcelin Joanis

We present a deep learning solution to address the challenges of simulating realistic synthetic first-price sealed-bid auction data. The complexities encountered in this type of auction data include high-cardinality discrete feature spaces and a multilevel structure arising from multiple bids associated with a single auction instance. Our methodology combine

Adarsh Salagame, Shoghair Manjikian, Chenghao Wang, Kaushik Venkatesh Krishnamurthy

Animals, such as birds, widely use multi-modal locomotion by combining legged and aerial mobility with dominant inertial effects. The robotic biomimicry of this multi-modal locomotion feat can yield ultra-flexible systems in terms of their ability to negotiate their task spaces. The main objective of this paper is to discuss the challenges in achieving multi