March 2023 arXiv papers — page 25

Sudin Ganguly, Santanu K. Maiti

The present work discusses the possibility to realize correlated disorder in electrical circuits and studies the localization phenomena in terms of two-port impedance. The correlated disorder is incorporated using the Aubry-Andr\'{e}-Harper (AAH) model. One-dimensional and quasi-one-dimensional AAH structures are explored and directly mapped with their tight

Nikos Katzourakis, Roger Moser

For an elliptic, semilinear differential operator of the form $S(u) = A : D^2 u + b(x, u , Du)$, consider the functional $E_\infty(u) = \mathop{\mathrm{ess \, sup}}_\Omega |S(u)|$. We study minimisers of $E_\infty$ for prescribed boundary data. Because the functional is not differentiable, this problem does not give rise to a conventional Euler-Lagrange equa

Elia Fioravanti, Annette Karrer, Alessandro Sisto, Stefanie Zbinden

We consider cusped hyperbolic $n-$manifolds, and compute \v{C}ech cohomology groups of the Morse boundaries of their fundamental groups. In particular, we show that the reduced \v{C}ech cohomology with real coefficients vanishes in dimension at most $n-3$ and does not vanish in dimension $n-2$. A similar result holds for relatively hyperbolic groups with vir

Jie Pan, Bing Zhang, Yuxiao Hou, Ting Zhang

By using the five Angstrom diameter pores of calcined zeolite as the template, we have fabricated boron doped carbon nanotube networks via the chemical vapor deposition method. Raman data indicate the network to comprise segments of interconnected carbon nano tubes. Transport measurements showed a superconducting transition initiating at 40K, with a sharp do

Ziwen Huang, L. Teriaca, R. Aznar Cuadrado, L. P. Chitta

The smallest extreme-ultraviolet (EUV) brightening events that were detected so far, called campfires, have recently been uncovered by the High Resolution EUV telescope (HRIEUV), which is part of the Extreme Ultraviolet Imager (EUI) on board Solar Orbiter. HRIEUV has a broad bandpass centered at 17.4 nm that is dominated by Fe ix and Fe x emission at about 1

Louie Hong Yao, Sascha Wald

Disorder in coined quantum walks generally leads to localization. We investigate the influence of the localization on the entanglement properties of coined quantum walks. Specifically, we consider quantum walks on the line and explore the effects of quenched disorder in the coin operations. After confirming that our choice of disorder localizes the walker, w

Damiano Ricciarelli, Giovanni Mannino, Ioannis Deretzis, Gaetano Calogero

Ultraviolet nanosecond laser annealing (LA) is a powerful tool where strongly confined heating and melting are desirable. In semiconductor technologies the importance of LA increases with the increasing complexity of the proposed integration schemes. Optimizing the LA process along with the experimental design is challenging, especially when complex 3D nanos

Ansgar Freyer, Martin Henk

In 2013, Koldobsky posed the problem to find a constant $d_n$, depending only on the dimension $n$, such that for any origin-symmetric convex body $K\subset\mathbb{R}^n$ there exists an $(n-1)$-dimensional linear subspace $H\subset\mathbb{R}^n$ with \[ |K\cap\mathbb Z^n| \leq d_n\,|K\cap H\cap \mathbb Z^n|\,\mathrm{vol}(K)^{\frac 1n}. \] In this article we s

Mingxuan Liu, Subhankar Roy, Zhun Zhong, Nicu Sebe

Discovering novel concepts in unlabelled datasets and in a continuous manner is an important desideratum of lifelong learners. In the literature such problems have been partially addressed under very restricted settings, where novel classes are learned by jointly accessing a related labelled set (e.g., NCD) or by leveraging only a supervisedly pre-trained mo

Mikhail V. Petrenko, Anatoly S. Pazgalev, Anton K. Vershovskii

We present the concept and the results of an investigation of an all-optical vector magnetic field sensor scheme developed for biological applications such as non-zero field magnetoencephalography and magnetocardiography. The scheme differs from the classical two-beam Bell-Bloom scheme in that the detecting laser beam is split into two beams, which are intro

Suman Adhya, Avishek Lahiri, Debarshi Kumar Sanyal

Dropout is a widely used regularization trick to resolve the overfitting issue in large feedforward neural networks trained on a small dataset, which performs poorly on the held-out test subset. Although the effectiveness of this regularization trick has been extensively studied for convolutional neural networks, there is a lack of analysis of it for unsuper

Michael Hagenow, Emmanuel Senft, Nitzan Orr, Robert Radwin

Shared autonomy methods, where a human operator and a robot arm work together, have enabled robots to complete a range of complex and highly variable tasks. Existing work primarily focuses on one human sharing autonomy with a single robot. By contrast, in this paper we present an approach for multi-robot shared autonomy that enables one operator to provide r

A. Yu. Orlov

We construct two series of commuting Hamiltonians parametrized by a constant matrix. The first series was my guess and the second one was know, and in our approach follows from the first series. For the proof we use familier facts known from our previous consideration of the links between random matrices and Hurwitz numbers, however the text is self-consiste

R. Abbasi, M. Ackermann, J. Adams, S. K. Agarwalla

The LIGO/Virgo collaboration published the catalogs GWTC-1, GWTC-2.1 and GWTC-3 containing candidate gravitational-wave (GW) events detected during its runs O1, O2 and O3. These GW events can be possible sites of neutrino emission. In this paper, we present a search for neutrino counterparts of 90 GW candidates using IceCube DeepCore, the low-energy infill a

Jitai Yang, Yang Cong, You Li, Hui Li

As an ensemble average result, vibrational spectrum simulation can be time-consuming with high accuracy methods. We present a machine learning approach based on the range-corrected deep potential (DPRc) model to improve computing efficiency. DPRc method divides the system into ``probe region'' and ``solvent region''; ``solvent-solvent'' interactions are not

Dario Daghero, Erik Piatti, Nikolai D. Zhigadlo, Renato S. Gonnelli

It is well known that point-contact Andreev reflection spectroscopy provides reliable measurements of the energy gap(s) in a superconductor when the contact is in the ballistic or nearly-ballistic regime. However, especially when the mean free path of the material under study is small, obtaining ballistic contacts can be a major challenge. One of the signatu

Rong Cao, Liang Bao, Chase Wu, Panpan Zhangsun

Configuration tuning for large software systems is generally challenging due to the complex configuration space and expensive performance evaluation. Most existing approaches follow a two-phase process, first learning a regression-based performance prediction model on available samples and then searching for the configurations with satisfactory performance u

Kaiyuan Cao, Hao Guo, Guangwen Yang

We investigate the dynamical quantum phase transition (DQPT) in the multi-band Bloch Hamiltonian of the one-dimensional periodic Kitaev model, focusing on quenches from a Bloch band. By analyzing the dynamical free energy and Pancharatnam geometric phase, we show that the critical times of DQPTs deviate from periodic spacing due to the multi-band effect, con

Nicola K Dinsdale, Mark Jenkinson, Ana IL Namburete

To represent the biological variability of clinical neuroimaging populations, it is vital to be able to combine data across scanners and studies. However, different MRI scanners produce images with different characteristics, resulting in a domain shift known as the `harmonisation problem'. Additionally, neuroimaging data is inherently personal in nature, lea

Muhammad Akbar Husnoo, Adnan Anwar, Haftu Tasew Reda, Nasser Hosseizadeh

With growing security and privacy concerns in the Smart Grid domain, intrusion detection on critical energy infrastructure has become a high priority in recent years. To remedy the challenges of privacy preservation and decentralized power zones with strategic data owners, Federated Learning (FL) has contemporarily surfaced as a viable privacy-preserving alt

Dániel Gerbner

The generalized Tur\'an number $\mathrm{ex}(n,H,F)$ is the largest number of copies of $H$ in $n$-vertex $F$-free graphs. We denote by $tF$ the vertex-disjoint union of $t$ copies of $F$. Gerbner, Methuku and Vizer in 2019 determined the order of magnitude of $\mathrm{ex}(n,K_s,tK_r)$. We extend this result in three directions. First, we determine $\mathrm{e

Giovanna Maria Dimitri, Simeon Spasov, Andrea Duggento, Luca Passamonti

Recently, it has become progressively more evident that classic diagnostic labels are unable to reliably describe the complexity and variability of several clinical phenotypes. This is particularly true for a broad range of neuropsychiatric illnesses (e.g., depression, anxiety disorders, behavioral phenotypes). Patient heterogeneity can be better described b

Leila M. Calcaferro, Alejandro H. Córsico, Leandro G. Althaus, Isaac D. Lopez

(Abridged) We present an exploration of the internal rotation of GD 278, the first pulsating extremely low-mass white dwarf that shows rotational splittings within its periodogram. We assess the theoretical frequency splittings expected for different rotation profiles and compare them to the observed frequency splittings of GD 278. To this aim, we employ an

Raheel Hammad, Amar Kumar, Tharangattu N. Narayanan, Soumya Ghosh

Light chargeable metal-ion batteries using semiconductor heterostructures are gaining enormous interest. A few such heterostructures such as MoS2/MoOy and TiS2/TiO2 have been shown to function as photocathodes in photochargeable Li-ion batteries, where the type II set-up has been proposed to generate spatially separated (longer-lived) excitons upon photo-exp

Raghavendra Badiger, M. Prabhakar

Currently, the telehealth monitoring field has gained huge attention due to its noteworthy use in day-to-day life. This advancement has led to an increase in the data collection of electrophysiological signals. Due to this advancement, electrocardiogram (ECG) signal monitoring has become a leading task in the medical field. ECG plays an important role in the

Jonas Schießl, Ruchuan Ou, Timm Faulwasser, Michael Heinrich Baumann

We investigate pathwise turnpike behavior of discrete-time stochastic linear-quadratic optimal control problems. Our analysis is based on a novel strict dissipativity notion for such problems, in which a stationary stochastic process replaces the optimal steady state of the deterministic setting. The analytical findings are illustrated by a numerical example

Wei Zhu, Hong-Kun Zhang, P. G. Kevrekidis

We introduce a methodology for seeking conservation laws within a Hamiltonian dynamical system, which we term ``neural deflation''. Inspired by deflation methods for steady states of dynamical systems, we propose to {iteratively} train a number of neural networks to minimize a regularized loss function accounting for the necessity of conserved quantities to

Wael Al Hanaineh, Jose Matas, Jorge. El mariachet, Josep. M. Guerrero

The trend toward Microgrids (MGs) is significantly increasing by employing Distributed Generators (DGs) which leads to new challenges, especially in the fault detection. This paper proposes an algorithm based on the Total Harmonic Distortion (THD) of the grid voltages to detect the events of faults in MGs. The algorithm uses the THD together with the estimat

Andrei Golutvin, Aleksandr Iniukhin, Andrea Mauri, Patrick Owen

We propose a new method based on machine learning to \emph{play the devil's advocate} and investigate the impact of unknown systematic effects in a quantitative way. This method proceeds by reversing the measurement process and using the physics results to interpret systematic effects under the Standard Model hypothesis. We explore this idea with two alterna

A. R. Kuzmak

In the last two decades, magnetic, thermodynamic properties and bipartite thermal entanglement in diamond spin clusters and chains have been studied. Such spin structures are presented in various compounds. The ions of $Cu^{2+}$ in the natural mineral azurite are arranged in a diamond spin chain. There are no studies of the entanglement behaviour during the

Ming Xu, Qiang Ai, Ruimin Li, Yunyi Ma

Real-time what-if traffic prediction is crucial for decision making in intelligent traffic management and control. Although current deep learning methods demonstrate significant advantages in traffic prediction, they are powerless in what-if traffic prediction due to their nature of correla-tion-based. Here, we present a simple deep learning framework called

Matt Gorbett, Darrell Whitley

The Multi-Prize Lottery Ticket Hypothesis posits that randomly initialized neural networks contain several subnetworks that achieve comparable accuracy to fully trained models of the same architecture. However, current methods require that the network is sufficiently overparameterized. In this work, we propose a modification to two state-of-the-art algorithm

Dominik Brennecken

We study analytic aspects of the Dunkl-type Hankel transform, which goes back to Baker and Forrester and, in an earlier symmetrized version, to Macdonald. Moreover, we introduce a Dunkl analogue of the Bessel function and K-Bessel function generalizing those of a symmetric cone. Further, we take a look at zeta integrals and their distributional extensions in

Peng Wang, Yuan Liu, Zhaoxi Chen, Lingjie Liu

This paper presents a novel grid-based NeRF called F2-NeRF (Fast-Free-NeRF) for novel view synthesis, which enables arbitrary input camera trajectories and only costs a few minutes for training. Existing fast grid-based NeRF training frameworks, like Instant-NGP, Plenoxels, DVGO, or TensoRF, are mainly designed for bounded scenes and rely on space warping to

Chenghan Wu, Steven Brems, Didit Yudistira, Daire Cott

Graphene-based devices have shown great promise for several applications. For graphene devices to be used in real-world systems, it is necessary to demonstrate competitive device performance, repeatability of results, reliability, and a path to large-scale manufacturing with high yield at low cost. Here, we select single-layer graphene electro-absorption mod

Corentin Larroche

Detecting malicious activity within an enterprise computer network can be framed as a temporal link prediction task: given a sequence of graphs representing communications between hosts over time, the goal is to predict which edges should--or should not--occur in the future. However, standard temporal link prediction algorithms are ill-suited for computer ne

Matthijs Vernooij, Melchior Wirth

We prove that the generator of the $L^2$ implementation of a KMS-symmetric quantum Markov semigroup can be expressed as the square of a derivation with values in a Hilbert bimodule, extending earlier results by Cipriani and Sauvageot for tracially symmetric semigroups and the second-named author for GNS-symmetric semigroups. This result hinges on the introdu

Stefanos Eleftheriadis, Dominic Richards, James Hensman

We revisit the Gaussian process model with spherical harmonic features and study connections between the associated RKHS, its eigenstructure and deep models. Based on this, we introduce a new class of kernels which correspond to deep models of continuous depth. In our formulation, depth can be estimated as a kernel hyper-parameter by optimizing the evidence

Ryo Hachiuma, Tomohiro Shimizu, Hideo Saito, Hiroki Kajita

Recording surgery in operating rooms is an essential task for education and evaluation of medical treatment. However, recording the desired targets, such as the surgery field, surgical tools, or doctor's hands, is difficult because the targets are heavily occluded during surgery. We use a recording system in which multiple cameras are embedded in the surgica

Edoardo D'Amico, Khalil Muhammad, Elias Tragos, Barry Smyth

Graph Convolutional Networks (GCN) have been recently employed as core component in the construction of recommender system algorithms, interpreting user-item interactions as the edges of a bipartite graph. However, in the absence of side information, the majority of existing models adopt an approach of randomly initialising the user embeddings and optimising

Ilan Newman, Yuri Rabinovich

We study deterministic online embeddings of metrics spaces into normed spaces and into trees against an adaptive adversary. Main results include a polynomial lower bound on the (multiplicative) distortion of embedding into Euclidean spaces, a tight exponential upper bound on embedding into the line, and a $(1+\epsilon)$-distortion embedding in $\ell_\infty$

Haiquan Mao, Feng Hong, Man-wai Mak

Recent studies have shown that pseudo labels can contribute to unsupervised domain adaptation (UDA) for speaker verification. Inspired by the self-training strategies that use an existing classifier to label the unlabeled data for retraining, we propose a cluster-guided UDA framework that labels the target domain data by clustering and combines the labeled s

Lukas Renelt, Christian Engwer, Mario Ohlberger

In this contribution we propose an optimally stable ultraweak Petrov-Galerkin variational formulation and subsequent discretization for stationary reactive transport problems. The discretization is exclusively based on the choice of discrete approximate test spaces, while the trial space is a priori infinite dimensional. The solution in the trial space or ev

A. Naumov, Ar. Melnikov, V. Abronin, F. Oxanichenko

Neural networks have revolutionized many aspects of society but in the era of huge models with billions of parameters, optimizing and deploying them for commercial applications can require significant computational and financial resources. To address these challenges, we introduce the Tetra-AML toolbox, which automates neural architecture search and hyperpar

Xidong Wang

This article focuses on the globally composite adaptive law-based intelligent finite-/fixed- time (FnT/FxT) tracking control issue for a family of uncertain strict-feedback nonlinear systems. First, intelligent approximators with new composite updating laws are developed to model uncertain nonlinear terms, which encompass prediction errors to enhance intelli

Léo Bénard, Ryoto Tange, Anh T. Tran, Jun Ueki

We study the divisor of the Reidemeister torsion on the variety of irreducible ${\rm SL}_2\mathbb{C}$-characters of certain knots and links, and provide a geometric interpretation of them. We focus in particular on the family of odd-twisted Whitehead links $W_{2n-1}$ and prove that these divisors have multiplicity two. Furthermore, we apply these results to

Viktor van der Valk, Douwe Atsma, Roderick Scherptong, Marius Staring

Electrocardiography is the most common method to investigate the condition of the heart through the observation of cardiac rhythm and electrical activity, for both diagnosis and monitoring purposes. Analysis of electrocardiograms (ECGs) is commonly performed through the investigation of specific patterns, which are visually recognizable by trained physicians

Qi Gege, Yuefeng Chen, Xiaofeng Mao, Yao Zhu

In a transfer-based attack against Automatic Speech Recognition (ASR) systems, attacks are unable to access the architecture and parameters of the target model. Existing attack methods are mostly investigated in voice assistant scenarios with restricted voice commands, prohibiting their applicability to more general ASR related applications. To tackle this c

David Melching, Erik Schultheis, Eric Breitbarth

Digital image correlation (DIC) has become a valuable tool to monitor and evaluate mechanical experiments of cracked specimen, but the automatic detection of cracks is often difficult due to inherent noise and artefacts. Machine learning models have been extremely successful in detecting crack paths and crack tips using DIC-measured, interpolated full-field

Ivo M. Baltruschat, Felix Kreis, Alexander Hoelscher, Melanie Dohmen

Generative adversarial networks (GANs) have shown remarkable success in generating realistic images and are increasingly used in medical imaging for image-to-image translation tasks. However, GANs tend to suffer from a frequency bias towards low frequencies, which can lead to the removal of important structures in the generated images. To address this issue,

HsiaoYuan Hsu, Xiangteng He, Yuxin Peng, Hao Kong

Content-aware visual-textual presentation layout aims at arranging spatial space on the given canvas for pre-defined elements, including text, logo, and underlay, which is a key to automatic template-free creative graphic design. In practical applications, e.g., poster designs, the canvas is originally non-empty, and both inter-element relationships as well

Sebastian Wallot, Dan Mønster

One challenge with the analysis of complex systems and the interaction between such systems is that they are composed of different numbers of components, or simply the fact that a different number of observables is available for each system. The challenge is how to analyze the interaction of two systems which are not described by the same number of variables

Riccardo Crupi, Giuseppe Dilillo, Kester Ward, Elisabetta Bissaldi

HERMES (High Energy Rapid Modular Ensemble of Satellites) pathfinder is an in-orbit demonstration consisting of a constellation of six 3U nano-satellites hosting simple but innovative detectors for the monitoring of cosmic high-energy transients. The main objective of HERMES Pathfinder is to prove that accurate position of high-energy cosmic transients can b

Lin Zhao, Lu Zhang, Zihao Wu, Yuzhong Chen

Artificial General Intelligence (AGI) has been a long-standing goal of humanity, with the aim of creating machines capable of performing any intellectual task that humans can do. To achieve this, AGI researchers draw inspiration from the human brain and seek to replicate its principles in intelligent machines. Brain-inspired artificial intelligence is a fiel

Hideki Matsumura

Let $K$ be a field. In this article, we derive a formula for the discriminant of a sequence $\{r_{A,n}+c r_{A,n-1}\}$ of polynomials. Here, $c \in K$ and $\{r_{A,n} \}$ is a sequence of polynomials satisfying a certain recurrence relation that is considered by Ulas or Turaj. There are several works calculating the discriminants of given polynomials. For exam

Oscar Higgott, Craig Gidney

In this work, we introduce a fast implementation of the minimum-weight perfect matching (MWPM) decoder, the most widely used decoder for several important families of quantum error correcting codes, including surface codes. Our algorithm, which we call sparse blossom, is a variant of the blossom algorithm which directly solves the decoding problem relevant t

Yaowei Li, Bang Yang, Xuxin Cheng, Zhihong Zhu

Automatic radiology report generation has attracted enormous research interest due to its practical value in reducing the workload of radiologists. However, simultaneously establishing global correspondences between the image (e.g., Chest X-ray) and its related report and local alignments between image patches and keywords remains challenging. To this end, w

Nuno Lau, Luis Paulo Reis, David Simoes, Mohammadreza Kasaei. Miguel Abreu

The FC Portugal 3D team is developed upon the structure of our previous Simulation league 2D/3D teams and our standard platform league team. Our research concerning the robot low-level skills is focused on developing behaviors that may be applied on real robots with minimal adaptation using model-based approaches. Our research on high-level soccer coordinati

Matthias Hübler, Wolfgang Belzig

Quantum transport in the presence of time-dependent drives is dominated by quantum interference and many-body effects at low temperatures. For a periodic driving, the analysis of the full counting statistics revealed the elementary events that determine the statistical properties of the charge transport. As a result, the noise correlations display quantum os

Olaf Hartwig, Marc Lilley, Martina Muratore, Mauro Pieroni

We explore the impact of choosing different sets of Time-Delay Interferometry (TDI) variables for detecting and reconstructing Stochastic Gravitational Wave Background (SGWB) signals and estimating the instrumental noise in LISA. Most works in the literature build their data analysis pipelines relying on a particular set of TDI channels, the so-called AET va

M. Marvá, E. Venturino, M. C. Vera

This work presents a model combining the simplest communicable and non-communicable disease models. The latter is, by far, the leading cause of sickness and death in the World, and introduces basal heterogeneity in populations where communicable diseases evolve. The model can be interpreted as a risk-structured model, another way of accounting for population

Steven Rendon Restrepo, Pierre Barge

To mimic protoplanetary discs (PPDs) evolution, 2D simulations with self-gravity must introduce a softening prescription of the gravitational potential. When the disc is only made of gas the smoothing length is proportional to the gas scale height. On the other hand when a dust component is included, the question arises as whether the smoothing length approa

Willem A. de Graaf

We illustrate the Lie theoretic capabilities of the computational algebra system GAP4 by reporting on results on nilpotent orbits of simple Lie algebras that have been obtained using computations in that system. Concerning reachable elements in simple Lie algebras we show by computational means that the simple Lie algebras of exceptional type have the Panyus

Sucharita Giri, Gopal Dixit, Jean Christophe Tremblay

This contribution presents numerical simulations of N-electron dynamics in heterocyclic five-membered ring molecules to shed light on the effect of molecular symmetry on charge migration. Laser-driven dynamics is studied using the hybrid time-dependent density functional theory/configuration methodology, and the ensuing field-free charge migration is investi

Daniel Sinambela, Weiren Zhao

In this paper, we study the generation of eigenvalues of a stable monotonic shear flow under perturbations in $C^s$ with $s<2$. More precisely, we study the Rayleigh operator $\mathcal{L}_{U_{m,\gamma}}= U_{m,\gamma}\partial_x-U''_{m,\gamma}\partial_x\Delta^{-1}$ associated with perturbed shear flow $(U_{m,\gamma}(y),0)$ in a finite channel $\mathbb{T}_{2\pi

Zhiyong Sun

This paper proposes a time-varying matrix solution to the Brockett stabilization problem. The key matrix condition shows that if the system matrix product $CB$ is a Hurwitz H-matrix, then there exists a time-varying diagonal gain matrix $K(t)$ such that the closed-loop minimum-phase linear system with decentralized output feedback is exponentially convergent

Marica Branchesi, Michele Maggiore, David Alonso, Charles Badger

The Einstein Telescope (ET), the European project for a third-generation gravitational-wave detector, has a reference configuration based on a triangular shape consisting of three nested detectors with 10 km arms, where in each arm there is a `xylophone' configuration made of an interferometer tuned toward high frequencies, and an interferometer tuned toward

Antonio Rios-Navarro, Enrique Piñero-Fuentes, Salvador Canas-Moreno, Aqib Javed

This paper presents a sensory fusion neuromorphic dataset collected with precise temporal synchronization using a set of Address-Event-Representation sensors and tools. The target application is the lip reading of several keywords for different machine learning applications, such as digits, robotic commands, and auxiliary rich phonetic short words. The datas

Alessandro R. Mazza, Elizabeth Skoropata, Jason Lapano, Michael A. Chilcote

Magnetic interfaces and the phenomena arising from them drive both the design of modern spintronics and fundamental research. Recently, it was revealed that through designing magnetic frustration in configurationally complex entropy stabilized oxides, exchange bias can occur in structurally single crystal films. This eliminates the need for complex heterostr

Sašo Grozdanov, Mile Vrbica

Pole-skipping is a property of gravitational waves dictated by their behaviour at horizons of black holes. It stems from the inability to unambiguously impose ingoing boundary conditions at the horizon at an infinite discrete set of Fourier modes. The phenomenon has been best understood, when such a description exists, in terms of dual holographic (AdS/CFT)

Wei Liu, Jing Li, Zixiang Chen, Hao Sun

We explore the potential to use machine learning methods to search for heavy neutrinos, from their hadronic final states including a fat-jet signal, via the processes $pp \rightarrow W^{\pm *}\rightarrow \mu^{\pm} N \rightarrow \mu^{\pm} \mu^{\mp} W^{\pm} \rightarrow \mu^{\pm} \mu^{\mp} J$ at hadron colliders. We use either the Gradient Boosted Decision Tree

Ahmad Bdeir, Kristian Schwethelm, Niels Landwehr

Real-world visual data exhibit intrinsic hierarchical structures that can be represented effectively in hyperbolic spaces. Hyperbolic neural networks (HNNs) are a promising approach for learning feature representations in such spaces. However, current HNNs in computer vision rely on Euclidean backbones and only project features to the hyperbolic space in the

Tony Lelièvre, Régis Santet, Gabriel Stoltz

Hamiltonian Monte Carlo (HMC) is a Markov chain Monte Carlo method that allows to sample high dimensional probability measures. It relies on the integration of the Hamiltonian dynamics to propose a move which is then accepted or rejected thanks to a Metropolis procedure. Unbiased sampling is guaranteed by the preservation by the numerical integrators of two

Wieslaw Bartkowski, Andrzej Nowak, Filip Ignacy Czajkowski, Albrecht Schmidt

When we go for a walk with friends, we can observe an interesting effect: From step lengths to arm movements - our movements unconsciously align; they synchronize. Prior research found that this synchronization is a crucial aspect of human relations that strengthens social cohesion and trust. Generalizing from these findings in synchronization theory, we pro

Dominique Mercier, Andreas Dengel, Sheraz Ahmed

Deep learning has proven to be successful in various domains and for different tasks. However, when it comes to private data several restrictions are making it difficult to use deep learning approaches in these application fields. Recent approaches try to generate data privately instead of applying a privacy-preserving mechanism directly, on top of the class

Ronghua Shang, Songling Zhu, Yinan Wu, Weitong Zhang

Model compression plays a vital role in the practical deployment of deep neural networks (DNNs), and evolutionary multi-objective (EMO) pruning is an essential tool in balancing the compression rate and performance of the DNNs. However, due to its population-based nature, EMO pruning suffers from the complex optimization space and the resource-intensive stru

Anais Gauthier, Guillaume Ovarlez, Annie Colin

A number of dense particle suspensions experience a dramatic increase in viscosity with the shear stress, up to a solid-like response. This shear-thickening process is understood as a transition under flow of the nature of the contacts, from lubricated to frictional, between initially repellent particles. Most systems are now assumed to fit in with this scen

Cenk Beydeda, Konstantin Nikolaou, Marius Tochtermann, Nikolaj G. Ebensperger

Planar superconducting microwave transmission line resonators can be operated at multiple harmonic resonance frequencies. This allows covering wide spectral regimes with high sensitivity, as it is desired e.g. for cryogenic microwave spectroscopy. A common complication of such experiments is the presence of undesired 'spurious' additional resonances, which a

Florian Müller

Recent technological advances have made head-mounted displays (HMDs) smaller and untethered, fostering the vision of ubiquitous interaction with information in a digitally augmented physical world. For interacting with such devices, three main types of input - besides not very intuitive finger gestures - have emerged so far: 1) Touch input on the frame of th

Bernd Aichner, Lucas Backmeister, Max Karrer, Katja Wurster

The competition between intrinsic disorder in superconducting YBa$_{2}$Cu$_{3}$O$_{7-\delta}$ (YBCO) thin films and an ultradense triangular lattice of cylindrical pinning centers spaced at 30 nm intervals results in an ordered Bose glass phase of vortices. The samples were created by scanning the focused beam of a helium-ion microscope over the surface of t

Jiri Blazek, Jan Ebr, Jakub Vicha, Tanguy Pierog

We have implemented ad-hoc modifications to the CORSIKA Monte-Carlo generator which allow us to simultaneously adjust the multiplicity, elasticity and cross-section of hadronic interactions with respect to the predictions of the Sibyll 2.3d interaction model, in order to assess whether a reasonable combination of changes (that is not excluded by current expe

Akshat Mudgal

Given $d,s \in \mathbb{N}$, a finite set $A \subseteq \mathbb{Z}$ and polynomials $\varphi_1, \dots, \varphi_{s} \in \mathbb{Z}[x]$ such that $1 \leq deg \varphi_i \leq d$ for every $1 \leq i \leq s$, we prove that \[ |A^{(s)}| + |\varphi_1(A) + \dots + \varphi_s(A) | \gg_{s,d} |A|^{\eta_s} , \] for some $\eta_s \gg_{d} \log s / \log \log s$. Moreover if $\v

Vanessa Wirth, Vanessa Wirth

In this work, we investigate the phenomenon of Author-UnificAtion (AUA), which describes the high structural similarity of two co-authoring engineers that share the same forename, surname, institution, and academic career without being related by blood. So far, prior work has only explored similar surnames and institutions. On top of that, we elaborate on th

Jean-Lou Pierson

In this article, we investigate the inertial settling of an arbitrarily oriented cylinder settling under gravity. We focus on two regimes: the very short-time and long-time dynamic. By using the generalized Kirchhoff equations to describe the particle motion, we demonstrate that during the very short dynamic regime, a cylinder starting from rest behaves with

Zhifeng Li, Hai Lin, Rongxin Tang, Haitao Chen

In this study, we propose the application of non-Hermitian photonic crystals (PCs) with anisotropic emissions. Unlike a ring of exceptional points (EPs) in isotropic non-Hermitian PCs, the EPs of anisotropic non-Hermitian PCs appear as lines symmetrical about the $\Gamma$ point. The non-Hermitian Hamiltonian indicates that the formation of EPs is related to

Dawid Kielak, Marco Linton

Let $G$ be the fundamental group of a three-manifold. By piecing together many known facts about three manifold groups, we establish two properties of the group ring $\mathbb{C}G$. We show that if $G$ has rational cohomological dimension two, then $\mathbb{C}G$ is coherent. We also show that if $G$ is torsion-free, then $G$ satisfies the Strong Atiyah Conjec

Frédéric Déglise, Niels Feld, Fangzhou Jin

In this note we study the functoriality of the coniveau filtration in motivic homotopy theory via a moving lemma over a base scheme, extending previous works of Levine and Bachmann-Yakerson. The main result is that the motivic stable homotopy category can be modeled on a smaller site, the "smooth-smooth site". The proof is based on a new approach to the puri

Lorenzo Barban, Alberto Franceschini

We introduce the notion of rooftop flip, namely a small modification among normal projective varieties which is modeled by a smooth projective variety of Picard number 2 admitting two projective bundle structures. Examples include the Atiyah flop and the Mukai flop, modeled respectively by $\mathbb{P}^1\times \mathbb{P}^1$ and by $\mathbb{P}\left(T_{\mathbb{

Lei Ke, Martin Danelljan, Henghui Ding, Yu-Wing Tai

The recent advancement in Video Instance Segmentation (VIS) has largely been driven by the use of deeper and increasingly data-hungry transformer-based models. However, video masks are tedious and expensive to annotate, limiting the scale and diversity of existing VIS datasets. In this work, we aim to remove the mask-annotation requirement. We propose MaskFr

Roberta Angius, Jesus Huertas, Angel M. Uranga

Small black holes are a powerful tool to explore infinite distances in moduli spaces. However, we show that in 4d theories with a scalar potential growing fast enough at infinity, it is energetically too costly for scalars to diverge at the core, and the small black hole puffs up into a regular black hole, or follows a runaway behaviour. We derive a critical

Matteo Muratori, Nicola Soave

We investigate existence and qualitative properties of globally defined and positive radial solutions of the Lane-Emden system, posed on a Cartan-Hadamard model manifold $ \mathbb{M}^n $. We prove that, for critical or supercritical exponents, there exists at least a one-parameter family of such solutions. Depending on the stochastic completeness or incomple

Bakary Badjie, José Cecílio, António Casimiro

Adversarial attacks significantly threaten the robustness of deep neural networks (DNNs). Despite the multiple defensive methods employed, they are nevertheless vulnerable to poison attacks, where attackers meddle with the initial training data. In order to defend DNNs against such adversarial attacks, this work proposes a novel method that combines the defe

Jeonghwan Kim, Tianyu Li, Sehoon Ha

Generating natural and physically feasible motions for legged robots has been a challenging problem due to its complex dynamics. In this work, we introduce a novel learning-based framework of autoregressive motion planner (ARMP) for quadruped locomotion and navigation. Our method can generate motion plans with an arbitrary length in an autoregressive fashion

Knut Bjarte Haus, Gereon Quick

We construct a functorial pushforward homomorphism in geometric Hodge filtered complex cobordism along proper holomorphic maps between arbitrary complex manifolds. This significantly improves previous results on such transfer maps and is a much stronger result than the ones known for differential cobordism of smooth manifolds. This enables us to define and p

Bar Light

We study the properties of a subclass of stochastic processes called discrete time nonlinear Markov chains with an aggregator, which naturally appear in various topics such as strategic queueing systems, inventory dynamics, opinion dynamics, and wealth dynamics. In these chains, the next period's distribution depends on both the current state and a real-valu

Gaëtan Chenevier, Wee Teck Gan

We classify the pairs of group morphisms $\Gamma \rightarrow {\rm Spin}(7)$ which are element conjugate but not globally conjugate. As an application, we study the case where $\Gamma$ is the Weil group of a $p$-adic local field, which is relevant to the recent approach to the local Langlands correspondence for ${\rm G}_2$ and ${\rm PGSp}_6$ by Gan and Savin.

Alexander Hagg, Martin L. Kliemank, Alexander Asteroth, Dominik Wilde

Quality diversity algorithms can be used to efficiently create a diverse set of solutions to inform engineers' intuition. But quality diversity is not efficient in very expensive problems, needing 100.000s of evaluations. Even with the assistance of surrogate models, quality diversity needs 100s or even 1000s of evaluations, which can make it use infeasible.

Adrian Barquero-Sanchez, Gabriel Collado-Valverde, Nathan C. Ryan, Eduardo Salas-Jimenez

In this paper we develop a method to calculate the overpartition function efficiently using a Hardy-Rademacher-Ramanujan type formula, and we use this method to find many new Ramanujan-style congruences, whose existence is predicted by Treneer and a few of which were first discovered by Ryan, Scherr, Sirolli and Treneer.

Yizhou Liu, Liang Gao, Sownak Bose, Carlos S. Frenk

We take advantage of the unprecedented dynamical range provided by the "Cosmic-Zoom" project to study the mass accretion history (MAH) of present-day dark matter haloes over the entire mass range present in the $\Lambda$CDM paradigm when the dark matter is made of weakly interacting massive particles of mass $100\ \mathrm{GeV}$. In particular, we complement

Anna Frühstück, Nikolaos Sarafianos, Yuanlu Xu, Peter Wonka

We introduce VIVE3D, a novel approach that extends the capabilities of image-based 3D GANs to video editing and is able to represent the input video in an identity-preserving and temporally consistent way. We propose two new building blocks. First, we introduce a novel GAN inversion technique specifically tailored to 3D GANs by jointly embedding multiple fra