March 2023 arXiv papers — page 84

Leonardo Pipolo de Gioia, Ana-Maria Raclariu

We show that time intervals of width $\Delta \tau$ in 3-dimensional conformal field theories (CFT$_3$) on the Lorentzian cylinder admit an infinite dimensional symmetry enhancement in the limit $\Delta \tau \rightarrow 0$. The associated vector fields are approximate solutions to the conformal Killing equations in the strip labelled by a function and a confo

Manran Zhu, Taha Yasseri, János Kertész

With the rapid accumulation of online information, efficient web navigation has grown vital yet challenging. To create an easily navigable cyberspace catering to diverse demographics, understanding how people navigate differently is paramount. While previous research has unveiled individual differences in spatial navigation, such differences in knowledge spa

Shuzheng Qu, Mohammed Abouheaf, Wail Gueaieb, Davide Spinello

The flocking motion control is concerned with managing the possible conflicts between local and team objectives of multi-agent systems. The overall control process guides the agents while monitoring the flock-cohesiveness and localization. The underlying mechanisms may degrade due to overlooking the unmodeled uncertainties associated with the flock dynamics

Rhyd Lewis

This paper describes the shortest path problem in weighted graphs and examines the differences in efficiency that occur when using Dijkstra's algorithm with a Fibonacci heap, binary heap, and self-balancing binary tree. Using C++ implementations of these algorithm variants, we find that the fastest method is not always the one that has the lowest asymptotic

Chuanhe Liu, Xinjie Zhang, Xiaolong Liu, Tenggan Zhang

This paper presents our submission to the Expression Classification Challenge of the fifth Affective Behavior Analysis in-the-wild (ABAW) Competition. In our method, multimodal feature combinations extracted by several different pre-trained models are applied to capture more effective emotional information. For these combinations of visual and audio modal fe

Marcel Blind, Christopher Schauerte, Anne-Marie Schreyer, Andrea Beck

In this paper we present experimental and numerical reference data for a NACA 64A-110 airfoil at two angles of attack for $Ma=0.72$ and a Reynolds number of $Re_c=930.000$ with respect to the chord length. The test cases are designed to provide data for an uninclined airfoil at $0^\circ$ and for the case of a stable, steady shock at $3^\circ$. For both cases

Chris Verhoek, Julian Berberich, Sofie Haesaert, Frank Allgöwer

We derive direct data-driven dissipativity analysis methods for Linear Parameter-Varying (LPV) systems using a single sequence of input-scheduling-output data. By means of constructing a semi-definite program subject to linear matrix inequality constraints based on this data-dictionary, direct data-driven verification of $(Q,S,R)$-type of dissipativity prope

Julia Kostin, Felix Krahmer, Dominik Stöger

In this paper, we study the problem of recovering two unknown signals from their convolution, which is commonly referred to as blind deconvolution. Reformulation of blind deconvolution as a low-rank recovery problem has led to multiple theoretical recovery guarantees in the past decade due to the success of the nuclear norm minimization heuristic. In particu

Arman Pour Tak Dost, Mischa P. Woods

When an atom is in an excited state, after some amount of time, it will decay to a lower energy state emitting a photon in the process. This is known as spontaneous emission. It is one of the three elementary light-matter interactions. If it has not decayed at time $t$, then the probability that it does so in the next infinitesimal time step $[t, t+\delta t]

Sergio Cabello, David Gajser

For a set $Q$ of points in the plane and a real number $\delta \ge 0$, let $\mathbb{G}_\delta(Q)$ be the graph defined on $Q$ by connecting each pair of points at distance at most $\delta$. We consider the connectivity of $\mathbb{G}_\delta(Q)$ in the best scenario when the location of a few of the points is uncertain, but we know for each uncertain point a

Stefano Silvestri

Launched on December 9, 2021, the Imaging X-ray Polarimetry Explorer (IXPE) is the first imaging polarimeter ever flown, providing sensitivity in the 2--8 keV range, and during the 2-year initial phase of the mission will sample tens of X-ray sources among different source classes. While most of the measurements will be statistics-limited, for some of the br

Izabella Ingrid Farkas, Edita Pelantová, Milena Svobodová

To represent real $m$-dimensional vectors, a positional vector system given by a non-singular matrix $M \in \mathbb{Z}^{m \times m}$ and a digit set $\mathcal{D} \subset \mathbb{Z}^m$ is used. If $m = 1$, the system coincides with the well known numeration system used to represent real numbers. We study some properties of the vector systems which are transfo

Gregory Moille, Christy Li, Jordan Stone, Michal Chojnacky

Dissipative Kerr solitons (DKSs) intrinsically exhibit two degrees of freedom through their group and phase rotation velocity. Periodic extraction of the DKS into a waveguide produces a pulse train and yields the resulting optical frequency comb's repetition rate and carrier-envelope offset, respectively. Here, we demonstrate that it is possible to create a

E. Finhold, C. Gärtner, R. Grindel, T. Heller

Industrial electricity consumers with flexible demand can profit by adjusting their load to short-term prices and by providing balancing services to the grid. Markets which support this kind of short-term position adjustment are the day-ahead market and balancing markets. We propose a formulation for a combined optimization model that computes an optimal dis

Daniele Masti, Filippo Fabiani, Giorgio Gnecco, Alberto Bemporad

We propose a counter-example guided inductive synthesis (CEGIS) scheme for the design of control Lyapunov functions and associated state-feedback controllers for linear systems affected by parametric uncertainty with arbitrary shape. In the CEGIS framework, a learner iteratively proposes a candidate control Lyapunov function and a tailored controller by solv

Carlo Alberto De Bernardi

Let $E$ be a $(\mathrm{IV})$-polyhedral Banach space. We show that, for each $\epsilon>0$, $E$ admits an $\epsilon$-equivalent $\mathrm{(V)}$-polyhedral norm such that the corresponding closed unit ball is the closed convex hull of its extreme points. In particular, we obtain that every separable isomorphically polyhedral Banach space, for each $\epsilon>0$,

Matthias Bitzer, Mona Meister, Christoph Zimmer

Learning precise surrogate models of complex computer simulations and physical machines often require long-lasting or expensive experiments. Furthermore, the modeled physical dependencies exhibit nonlinear and nonstationary behavior. Machine learning methods that are used to produce the surrogate model should therefore address these problems by providing a s

Zhengying Lou, Baha Eddine Youcef Belmekki, Mohamed-Slim Alouini

Utilizing terahertz (THz) transmission to enhance coverage has proven various benefits compared to traditional radio frequency (RF) counterparts. This letter proposes a dual-hop decode-and-forward (DF) routing protocol in a hybrid RF and THz relay network named hybrid relay selection (HRS). The coverage probability of the HRS protocol is derived. The HRS pro

Haohan Huang, Tian Liang, Lin Fu

In this paper, a new five-point targeted essentially non-oscillatory (TENO) scheme with adaptive dissipation is proposed. With the standard TENO weighting strategy, the cut-off parameter $C_T$ determines the nonlinear numerical dissipation of the resultant TENO scheme. Moreover, according to the dissipation-adaptive TENO5-A scheme, the choice of the cut-off

Rasmus Netterstrøm, Nikolay Kutuzov, Sune Darkner, Maurits Jørring Pallesen

Tracking single molecules is instrumental for quantifying the transport of molecules and nanoparticles in biological samples, e.g., in brain drug delivery studies. Existing intensity-based localisation methods are not developed for imaging with a scanning microscope, typically used for in vivo imaging. Low signal-to-noise ratios, movement of molecules out-of

Jonathan Berrisch, Florian Ziel

This paper presents a new method for combining (or aggregating or ensembling) multivariate probabilistic forecasts, considering dependencies between quantiles and marginals through a smoothing procedure that allows for online learning. We discuss two smoothing methods: dimensionality reduction using Basis matrices and penalized smoothing. The new online lear

Karolina Klockmann, Tatyana Krivobokova

A new nonparametric estimator for Toeplitz covariance matrices is proposed. This estimator is based on a data transformation that translates the problem of Toeplitz covariance matrix estimation to the problem of mean estimation in an approximate Gaussian regression. The resulting Toeplitz covariance matrix estimator is positive definite by construction, full

K. Lackner, R. Burhenn, S. Fietz, A. v. Müller

We comment on the note "Low Q nuclear fusion in a volume heated mixed fuel reactor" by Ruhl and Korn in which hydrodynamic life-time considerations are included in estimates of ignition energy for uncompressed fusion fuel targets. For the case of DT fusion, the authors arrive at a required hot-spot energy of 1MJ. We point out that their Q = 1 estimate is not

Nicole E. Pashley, Luke Keele, Luke W. Miratrix

Experiments studying get-out-the-vote (GOTV) efforts estimate the causal effect of various mobilization efforts on voter turnout. However, there is often substantial noncompliance in these studies. A usual approach is to use an instrumental variable (IV) analysis to estimate impacts for compliers, here being those actually contacted by the investigators. Unf

Mohamed Soliman, Kirsten Gericke, Paris Avgeriou

Software engineers share their architectural knowledge (AK) in different places on the Web. Recent studies show that architectural blogs contain the most relevant AK, which can help software engineers to make design steps. Nevertheless, we know little about blogs, and specifically architectural blogs, where software engineers share their AK. In this paper, w

Yilun Zhou

Counterfactual (CF) explanations, also known as contrastive explanations and algorithmic recourses, are popular for explaining machine learning models in high-stakes domains. For a subject that receives a negative model prediction (e.g., mortgage application denial), the CF explanations are similar instances but with positive predictions, which informs the s

S. V. Notley, N. A. Thacker, L. Horsley, R. A. Little

Summary mean DCE-MRI variables show a clear dependency between signal and noise variance, which can be shown to reduce the effectiveness of difference assessments. Appropriate transformation of these variables supports statistically efficient and robust comparisons. The capabilities of DCE-MRI based descriptions of hepatic colorectal tumour classification wa

Konstantinos Kouroumpatzakis, Andreas Zezas, Elias Kyritsis, Samir Salim

The stellar mass ($M_\star$) and the star-formation rate (SFR) are among the most important features that characterize galaxies. Measuring these fundamental properties accurately is critical for understanding the present state of galaxies, and their history. This work explores the dependence of the IR emission of galaxies on their extinction, and the age of

Kang-hyurk Lee, Aeryeong Seo

Let $\mathbb B^n$ be the unit ball in $\mathbb C^n$ and $\mathbb H^n$ be the homogeneous Siegel domain of the second kind which is biholomorphic to $\mathbb B^n$. We show that the K\"ahler potential of $\mathbb H^n$ is unique up to the automorphisms among K\"ahler potentials whose differentials have constant norms. As an application, we consider a domain $\O

Romeo Mestrovic, Branislav Dragovic

A few new indices to characterize the scientific output of scientists are defined in the paper. These indices are compared with -index and its alternative indices using some proven assertions. The gd-indices are introduced as extensions of the g-index to define H-index as an improvement of the h-index. Numerous computational results which are conducted indic

Javier Peralta, Juan A. Prieto, Pilar Orozco-Sáenz, Jesús González

Astronomy and astrophysics are regarded as highly motivating topics for students in primary and secondary schools, and they have been a recurrent and effective resource to inspire passion about science. In fact, during the last years we have witnessed a boost of facilities providing small robotic telescopes for teachers and students to remotely undertake the

Alessandro Monti, Stefano Olivieri, Marco E. Rosti

Flexible filamentous beds interacting with a turbulent flow represent a fundamental setting for many environmental phenomena, e.g., aquatic canopies in marine current. Exploiting direct numerical simulations at high Reynolds number where the canopy stems are modelled individually, we provide evidence on the essential features of the honami/monami collective

Julien Hauret, Thomas Joubaud, Véronique Zimpfer, Éric Bavu

This paper presents a configurable version of Extreme Bandwidth Extension Network (EBEN), a Generative Adversarial Network (GAN) designed to improve audio captured with body-conduction microphones. We show that although these microphones significantly reduce environmental noise, this insensitivity to ambient noise happens at the expense of the bandwidth of t

Asha Viswanath, Diab W Abueidda, Mohamad Modrek, Kamran A Khan

Triply periodic minimal surface (TPMS) metamaterials characterized by mathematically-controlled topologies exhibit better mechanical properties compared to uniform structures. The unit cell topology of such metamaterials can be further optimized to improve a desired mechanical property for a specific application. However, such inverse design involves multipl

Matthias Köhler, Lisa Krügel, Lars Grüne, Matthias A. Müller

We analyse the closed-loop performance of a model predictive control (MPC) for tracking formulation with artificial references. It has been shown that such a scheme guarantees closed-loop stability and recursive feasibility for any externally supplied reference, even if it is unreachable or time-varying. The basic idea is to consider an artificial reference

Debraj Chakrabarti, Luke D. Edholm

For $1<p<\infty$, we emulate the Bergman projection on Reinhardt domains by using a Banach-space basis of $L^p$-Bergman space. The construction gives an integral kernel generalizing the ($L^2$) Bergman kernel. The operator defined by the kernel is shown to be absolutely bounded projection on the $L^p$-Bergman space on a class of domains where the $L^p$-bound

Bing Xie, Yigeng Zhao, Yongqiang Zhao

In this paper, we apply the combinatorial results on counting permutations with fixed pinnacle and vale sets to evaluate the special values of the spectral zeta functions of Sturm-Liouville differential operators. As applications, we get a combinatorial formula for the special values of spectral zeta functions and give a new explicit formula for Bernoulli nu

Nikolay N. Shchechilin, Mikhail E. Gusakov, Andrey I. Chugunov

We model the nuclear evolution of an accreted matter as it sinks toward the stellar center, in order to find its composition and equation of state. To this aim, we developed a simplified reaction network that allows for redistribution of free neutrons in the inner crust to satisfy the recently suggested neutron hydrostatic and diffusion equilibrium condition

Zhenghui Huo, Brett D. Wick

We study the $L^p$ regularity of the Bergman projection $P$ over the symmetrized polydisc in $\mathbb C^n$. We give a decomposition of the Bergman projection on the polydisc and obtain an operator equivalent to the Bergman projection over anti-symmetric function spaces. Using it, we obtain the $L^p$ irregularity of $P$ for $p=\frac{2n}{n-1}$ which also impli

Moshe Adrian, Shuichiro Takeda

We prove a local converse theorem for $GL_n$ over the archimedean local fields which characterizes an infinitesimal equivalence class of irreducible admissible representations of $GL_n(\mathbb{R})$ or $GL_n(\mathbb{C})$ in terms of twisted local gamma factors.

Francesco Marchiori, Mauro Conti, Nino Vincenzo Verde

The automatic extraction of information from Cyber Threat Intelligence (CTI) reports is crucial in risk management. The increased frequency of the publications of these reports has led researchers to develop new systems for automatically recovering different types of entities and relations from textual data. Most state-of-the-art models leverage Natural Lang

Shaoheng Fang, Zi Wang, Yiqi Zhong, Junhao Ge

Vision-centric joint perception and prediction (PnP) has become an emerging trend in autonomous driving research. It predicts the future states of the traffic participants in the surrounding environment from raw RGB images. However, it is still a critical challenge to synchronize features obtained at multiple camera views and timestamps due to inevitable geo

Krzysztof Bardadyn, Bartosz K. Kwaśniewski, Andrew McKee

We introduce Banach algebras associated to twisted \'etale groupoids $(\mathcal{G},\mathcal{L})$ and to twisted inverse semigroup actions. This provides a unifying framework for numerous recent papers on $L^p$-operator algebras and the theory of groupoid $C^*$-algebras. We prove disintegrations theorems that allow to study Banach algebras associated to $(\ma

Kaito Yamada, Noboru Ito

We specify the computational complexity of crosscap numbers of alternating knots by introducing an automatic computation. For an alternating knot $K$, let $\cal{E}$ be the number of edges of its diagram. Then there exists a code such that the complexity of this computation of the crosscap number of $K$ is estimated by $O(\cal{E}^3)$.

O. Duranthon, L. Zdeborová

The stochastic block model (SBM) is widely studied as a benchmark for graph clustering aka community detection. In practice, graph data often come with node attributes that bear additional information about the communities. Previous works modeled such data by considering that the node attributes are generated from the node community memberships. In this work

Ella Lan

Diabetes mellitus is a global concern, and early detection can prevent serious complications. 50% of people with diabetes live undiagnosed, disproportionately afflicting low-income groups. Non-invasive methods have emerged for timely detection; however, their limited accuracy constrains clinical usage. In this research, we present a novel Higher-Dimensional

Mohammed Abouheaf, Wail Gueaieb, Davide Spinello, Salah Al-Sharhan

Model-reference adaptive systems refer to a consortium of techniques that guide plants to track desired reference trajectories. Approaches based on theories like Lyapunov, sliding surfaces, and backstepping are typically employed to advise adaptive control strategies. The resulting solutions are often challenged by the complexity of the reference model and t

Jan Petr, Julien Portier

In this paper we prove that Sweller has a strategy so that the Sweller-Start Competition-Independence game lasts at least $(5n+3)/13$ moves for every tree. Moreover, we show that there exist arbitrarily large trees such that the Sweller-Start Competition-Independence game lasts at most $(5n+26)/12$ moves, disproving a conjecture by Henning.

Vivien van Veldhuizen, Sharvaree Vadgama, Onno J. de Boer, Sybren Meijer

Early detection of Barrett's Esophagus (BE), the only known precursor to Esophageal adenocarcinoma (EAC), is crucial for effectively preventing and treating esophageal cancer. In this work, we investigate the potential of geometric Variational Autoencoders (VAEs) to learn a meaningful latent representation that captures the progression of BE. We show that hy

Haixin Wang, Jianlong Chang, Xiao Luo, Jinan Sun

Despite recent competitive performance across a range of vision tasks, vision Transformers still have an issue of heavy computational costs. Recently, vision prompt learning has provided an economic solution to this problem without fine-tuning the whole large-scale models. However, the efficiency of existing models are still far from satisfactory due to inse

U. Arjun, K. M. Ranjith, A. Jesche, F. Hirschberger

Attaining milli-Kelvin temperatures is often a prerequisite for the study of novel quantum phenomena and the operation of quantum devices. Adiabatic demagnetization refrigeration (ADR) is an effective, easy and sustainable alternative to evaporation or dilution cooling with the rare and super-expensive $^3$He. Paramagnetic salts, traditionally used for mK-AD

Rui Luo, Buddhika Nettasinghe, Vikram Krishnamurthy

We propose a new way to measure inequalities such as the glass ceiling effect in attributed networks. Existing measures typically rely solely on node degree distribution or degree assortativity, but our approach goes beyond these measures by using mutual information (based on Shannon and more generally, Renyi entropy) between the conditional probability dist

Jens Müller, Stefan T. Radev, Robert Schmier, Felix Draxler

We investigate a "learning to reject" framework to address the problem of silent failures in Domain Generalization (DG), where the test distribution differs from the training distribution. Assuming a mild distribution shift, we wish to accept out-of-distribution (OOD) data from a new domain whenever a model's estimated competence foresees trustworthy respons

Jiawei Mao, Yuanqi Chang, Xuesong Yin, Binling Nie

Compared to other severe weather image restoration tasks, single image desnowing is a more challenging task. This is mainly due to the diversity and irregularity of snow shape, which makes it extremely difficult to restore images in snowy scenes. Moreover, snow particles also have a veiling effect similar to haze or mist. Although current works can effective

Md Mamunur Rahaman, Ewan K. A. Millar, Erik Meijering

Tumour heterogeneity in breast cancer poses challenges in predicting outcome and response to therapy. Spatial transcriptomics technologies may address these challenges, as they provide a wealth of information about gene expression at the cell level, but they are expensive, hindering their use in large-scale clinical oncology studies. Predicting gene expressi

Nat Wannawas, A. Aldo Faisal

Functional electrical stimulation (FES) has been increasingly integrated with other rehabilitation devices, including robots. FES cycling is one of the common FES applications in rehabilitation, which is performed by stimulating leg muscles in a certain pattern. The appropriate pattern varies across individuals and requires manual tuning which can be time-co

Giuseppe Filippone

We extend the map Exp for elliptic curves in short Weierstrass form over $ \mathbb{C} $ to Edwards curves over local fields. Subsequently, we compute the map Exp for Edwards curves over the local field $ \mathbb{Q}_{p} $ of $ p $-adic numbers.

Kjell Eriksson, Susanne Höfner, Bernhard Aringer

The properties and the evolution of asymptotic giant branch (AGB) stars are strongly influenced by their mass loss through a stellar wind. This is believed to be caused by radiation pressure due to the absorption and scattering of the stellar radiation by the dust grains formed in the atmosphere. The optical properties of dust are often estimated using the s

Mikhail Korobko, Jan Südbeck, Sebastian Steinlechner, Roman Schnabel

The most efficient approach to laser interferometric force sensing to date uses monochromatic carrier light with its signal sideband spectrum in a squeezed vacuum state. Quantum decoherence, i.e. mixing with an ordinary vacuum state due to optical losses, is the main sensitivity limit. In this work, we present both theoretical and experimental evidence that

Zi-Pei Zhu, Wei-Hua Lei, Daniele B. Malesani, Shao-Yu Fu

High-redshift gamma-ray bursts (GRBs) provide a powerful tool to probe the early universe, but still for relatively few do we have good observations of the afterglow. We here report the optical and near-infrared observations of the afterglow of a relatively high-redshift event, GRB\,220101A, triggered on New Year's Day of 2022. With the optical spectra obtai

Soyeon Jung, Amelia Hardy, Mykel J. Kochenderfer

Realistic aircraft trajectory models are useful in the design and validation of air traffic management (ATM) systems. Models of aircraft operated under instrument flight rules (IFR) require capturing the variability inherent in how aircraft follow standard flight procedures. The variability in aircraft behavior differs among flight stages. In this paper, we

Mikhail Karapetyants

In this manuscript we would like to address the classical optimization problem of minimizing a proper, convex and lower semicontinuous function via the second order in time dynamics, combining viscous and Hessian-driven damping with a Tikhonov regularization technique. In our analysis we heavily exploit the Moreau envelope of the objective function and its p

Francesco Salmaso, Mirko Trisolini, Camilla Colombo

The continuously growing number of objects orbiting around the Earth is expected to be accompanied by an increasing frequency of objects re-entering the Earth's atmosphere. Many of these re-entries will be uncontrolled, making their prediction challenging and subject to several uncertainties. Traditionally, re-entry predictions are based on the propagation o

Arno Förster, Erik van Lenthe, Edoardo Spadetto, Lucas Visscher

We report an all-electron, atomic orbital (AO) based, two-component (2C) implementation of the $GW$ approximation (GWA) for closed-shell molecules. Our algorithm is based on the space-time formulation of the GWA and uses analytical continuation of the self-energy, and pair-atomic density fitting (PADF) to switch between AO and auxiliary basis. By calculating

Johannes C. Joubert, Daniel N. Wilke, Patrick Pizette

This work investigates the effects of the choice of momentum diffusion operator on the evolution of multiphase fluid systems resolved with Meshless Lagrangian Methods (MLM). Specifically, the effects of a non-zero viscosity gradient at multiphase interfaces are explored. This work shows that both the typical Smoothed Particle Hydrodynamics (SPH) and Generali

Fengyun Wang, Dong Zhang, Hanwang Zhang, Jinhui Tang

Semantic Scene Completion (SSC) transforms an image of single-view depth and/or RGB 2D pixels into 3D voxels, each of whose semantic labels are predicted. SSC is a well-known ill-posed problem as the prediction model has to "imagine" what is behind the visible surface, which is usually represented by Truncated Signed Distance Function (TSDF). Due to the sens

Lennart Ronge

We develop a formula for the diagonal values of the Hadamard coefficients associated to a normally hyperbolic operator on a globally hyperbolic spacetime in terms of the advanced and retarded Green's operators. We develop a local formula as well as formulae for integrals over (parts of) the diagonal. Furthermore, we develop analogues of the Hadamard expansio

Saikat Roy, Gregor Koehler, Constantin Ulrich, Michael Baumgartner

There has been exploding interest in embracing Transformer-based architectures for medical image segmentation. However, the lack of large-scale annotated medical datasets make achieving performances equivalent to those in natural images challenging. Convolutional networks, in contrast, have higher inductive biases and consequently, are easily trainable to hi

Anna Biggs, Juan Maldacena

We study the gravity solution dual to the D0 brane quantum mechanics, or BFSS matrix model, in the 't Hooft limit. The classical physics described by this gravity solution is invariant under a scaling transformation, which changes the action with a specific critical exponent, sometimes called the hyperscaling violating exponent. We present an argument for th

Cong Chen, Dawei Zhai, Cong Xiao, Wang Yao

We propose a novel nonlinear dynamical Hall effect characteristic of layered materials with chiral symmetry, which is driven by the joint action of in-plane and time variation of out-of-plane ac fields $\boldsymbol{j}_{\text{H}}\sim\boldsymbol{\dot{E}_{\perp}}\times\boldsymbol{E}_{\parallel}$. A new band geometric quantity -- interlayer Berry connection pola

Jiawei Yang, Susanto Rahardja, Pasi Franti

We hypothesize that similar objects should have similar outlier scores. To our knowledge, all existing outlier detectors calculate the outlier score for each object independently regardless of the outlier scores of the other objects. Therefore, they do not guarantee that similar objects have similar outlier scores. To verify our proposed hypothesis, we propo

Alice Paul, Kyran Flynn, Cassandra Overney

In shared micromobility networks, such as bike-share and scooter-share networks, using trip data to accurately estimate demand in docked and dockless systems is critical to analyzing how the system is operating, such as identifying the number of dissatisfied users, operational costs, and equity in access, especially for city officials. However, the distribut

Tim Faber, Lado Filipovic, Jan Anton Koster

The hot carrier solar cell (HCSC) concept has been proposed to overcome the Shockley Queisser limit of a single p-n junction solar cell by harvesting carriers before they have lost their surplus energy. A promising family of materials for these purposes is metal halide perovskites (MHP). MHPs have experimentally shown very long cooling times, the key require

Zhandos A. Moldabekov, Jan Vorberger, Mani Lokamani, Tobias Dornheim

Linear-response time-dependent density functional theory (LR-TDDFT) simulations of disordered extended systems require averaging over different snapshots of ion configurations to minimize finite size effects due to the snapshot--dependence of the electronic density response function and related properties. We present a consistent scheme for the computation o

Alireza Aghamohammadi, Seyed-Hassan Mirian-Hosseinabadi

Test effectiveness refers to the capability of a test suite in exposing faults in software. It is crucial to be aware of factors that influence this capability. We aim at inferring the causal relationship between the two factors (i.e., Cover/Exec) and the capability of a test suite to expose and discover faults in software. Cover refers to the number of dist

Mikhail B. Salin, Artem V. Vitalsky

Photometry is a convenient operational method for monitoring such dynamically evolving phenomena as wind waves. Nowadays machine learning allows one to avoid explicit derivation of the solution to the problem, describing all the instructions for transforming the input data into the final result. Instead, an algorithm is used to independently find solutions t

Johannes M. Arend, Christoph Pörschmann, Stefan Weinzierl, Fabian Brinkmann

Head-related transfer functions (HRTFs) are essential for virtual acoustic realities, as they contain all cues for localizing sound sources in three-dimensional space. Acoustic measurements are one way to obtain high-quality HRTFs. To reduce measurement time, cost, and complexity of measurement systems, a promising approach is to capture only a few HRTFs on

Sándor Kajántó, Alexandru Kristály, Ioan Radu Peter, Wei Zhao

We present a generic functional inequality on Riemannian manifolds, both in additive and multiplicative forms, that produces well known and genuinely new Hardy-type inequalities. For the additive version, we introduce Riccati pairs that extend Bessel pairs developed by Ghoussoub and Moradifam (Proc. Natl. Acad. Sci. USA, 2008 & Math.A nn., 2011). This concep

Tian-Jun Li, Jie Min, Shengzhen Ning

It is known that the union of fibers over elliptic singularities of an almost toric fibered (ATF) closed symplectic four-manifold forms a symplectic log Calabi-Yau (LCY) divisor. In this paper, we show the converse: any symplectic LCY divisor can be realized as the boundary divisor of an ATF. For divisors in elliptic ruled surfaces, this realization occurs o

Mehmet Karahan, Mertcan Inal, Alperen Dilmen, Furkan Lacinkaya

Microstrip patch antennas are used in satellite imaging systems, wireless communication equipment, military radios, GPS (Global Positioning System) and GSM (Global System for Mobile Communications) applications. Its advantages are its small size and light weight, thin structure, low power consumption, use in dual frequency applications, and patching in vario

Guillaume Jeanneret, Loïc Simon, Frédéric Jurie

Counterfactual explanations and adversarial attacks have a related goal: flipping output labels with minimal perturbations regardless of their characteristics. Yet, adversarial attacks cannot be used directly in a counterfactual explanation perspective, as such perturbations are perceived as noise and not as actionable and understandable image modifications.

Maria Kourou, Konstantinos Zarvalis

We study the backward dynamics of one-parameter semigroups of holomorphic self-maps of the unit disk. More specifically, we introduce the speeds of convergence for petals of the semigroup, namely the total, orthogonal, and tangential speeds. These are analogous to speeds of convergence introduced by Bracci, yet profoundly different due to the nature of backw

Gözde Özcan, Stratis Ioannidis

In this paper, we study stochastic submodular maximization problems with general matroid constraints, that naturally arise in online learning, team formation, facility location, influence maximization, active learning and sensing objective functions. In other words, we focus on maximizing submodular functions that are defined as expectations over a class of

Patrick Tamburo, Philip S. Muirhead, Courtney D. Dressing

We simulate the yield of small (0.5-4.0 R$_\oplus$) transiting exoplanets around single mid-M and ultra-cool dwarfs (UCDs) in the Nancy Grace Roman Space Telescope Galactic Bulge Time Domain Survey. We consider multiple approaches for simulating M3-T9 sources within the survey fields, including scaling local space densities and using Galactic stellar populat

Sujan Pal, Jyotirmoy Poddar

Sets satisfying Central sets theorem and other Ramsey theoretic large sets were studied extensively in literature. Hindman and Strauss proved that product of some of these large sets is again large. In this paper we show that if we take two combinatorially large sets along idempotent filters, then their product is also a filter large set. The techniques used

Norman Meuschke, Apurva Jagdale, Timo Spinde, Jelena Mitrović

Extracting information from academic PDF documents is crucial for numerous indexing, retrieval, and analysis use cases. Choosing the best tool to extract specific content elements is difficult because many, technically diverse tools are available, but recent performance benchmarks are rare. Moreover, such benchmarks typically cover only a few content element

Yang-Fan Zhou, Kai-Lang Yao, Wu-Jun Li

Cytopathology report generation is a necessary step for the standardized examination of pathology images. However, manually writing detailed reports brings heavy workloads for pathologists. To improve efficiency, some existing works have studied automatic generation of cytopathology reports, mainly by applying image caption generation frameworks with visual

Yongjie Pan, Baocheng Zhang

We investigate the transition of a two-level atom as the Unruh-Dewitt detector accelerated in the electromagnetic field in this paper. The enhancement of the transition probability is found for different field states under the conditions that the anti-Unruh effect appears. In particular, the enhancement is the most prominent when the field state takes the sq

José Mário da Silva, Fernando Parisio

Taking advantage of the fact that the cardinalities of hidden variables in network scenarios can be assumed to be finite without loss of generality, a numerical tool for finding explicit local models that reproduce a given statistical behaviour was developed. The numerical procedure was then validated using families of statistical behaviours for which the ne

Jorge I. Rubiano-Murcia, Juan Galvis

In this short note, we show that the higher-order derivatives of the adjugate matrix $\mbox{Adj}(z-A)$, are related to the nilpotent matrices and projections in the Jordan decomposition of the matrix $A$. These relations appear as a factorization of the derivative of the adjugate matrix as a product of factors related to the eigenvalues, nilpotent matrices a

Yurui Chen, Chun Gu, Feihu Zhang, Li Zhang

Neural Radiance Fields (NeRF) have been proposed for photorealistic novel view rendering. However, it requires many different views of one scene for training. Moreover, it has poor generalizations to new scenes and requires retraining or fine-tuning on each scene. In this paper, we develop a new NeRF model for novel view synthesis using only a single image a

Zheng Qin, Hao Yu, Changjian Wang, Yuxing Peng

We study the problem of outlier correspondence pruning for non-rigid point cloud registration. In rigid registration, spatial consistency has been a commonly used criterion to discriminate outliers from inliers. It measures the compatibility of two correspondences by the discrepancy between the respective distances in two point clouds. However, spatial consi

Daniel Rogozin, Ilya Shapirovsky

We describe a family of decidable propositional dynamic logics, where atomic modalities satisfy some extra conditions (for example, given by axioms of the logics K5, S5, or K45 for different atomic modalities). It follows from recent results (Kikot, Shapirovsky, Zolin, 2014; 2020) that if a modal logic $L$ admits a special type of filtration (so-called defin

Seungmo Kim, Yeonho Jeong, Jae-Won Nam

There is no question to the fact that electric vehicles (EVs) are the most viable solution to the climate change that the planet has long been combating. Along the same line, it is a salient subject to expand the availability of charging infrastructure, which quintessentially necessitates the optimization of the charger's locations. This paper proposes to fo

Shuzheng Qu, Mohammed Abouheaf, Wail Gueaieb, Davide Spinello

The flock-guidance problem enjoys a challenging structure where multiple optimization objectives are solved simultaneously. This usually necessitates different control approaches to tackle various objectives, such as guidance, collision avoidance, and cohesion. The guidance schemes, in particular, have long suffered from complex tracking-error dynamics. Furt

Ming Li, Chengfeng Lin, Wei Chen, Yusheng Liu

Parametric optimization is an important product design technique, especially in the context of the modern parametric feature-based CAD paradigm. Realizing its full potential, however, requires a closed loop between CAD and CAE (i.e., CAD/CAE integration) with automatic design modifications and simulation updates. Conventionally the approach of model conversi

Arnaud Carignan-Dugas, Shashank Kumar Ranu, Patrick Dreher

Mitigation and calibration schemes are central to maximize the computational reach of today's Noisy Intermediate Scale Quantum (NISQ) hardware, but these schemes are often specialized to exclusively address either coherent or decoherent error sources. Quantifying the two types of errors hence constitutes a desirable feature when it comes to benchmarking erro

Jose Reina-Gálvez, Christoph Wolf, Nicolás Lorente

Motivated by recent developments in measurements of electron spin resonances of individual atoms and molecules with the scanning tunneling microscope (ESR-STM), we study electron transport through an impurity under periodic driving as a function of the transport parameters in a model junction. The model consists of a single-orbital quantum impurity connected

Antoine Goldsborough, Alessandro Sisto

The divergence of a group is a quasi-isometry invariant defined in terms of pairs of points and lengths of paths avoiding a suitable ball around the identity. In this paper we study "random divergence'', meaning the divergence at two points chosen according to independent random walks or Markov chains; the Markov chains version can be turned into a quasi-iso

Andrej Kržič, Nico Döll, Uday Chandrashekara, Christopher Spiess

Free-space quantum communication in daylight relies crucially on spatial filtering. The optimal filter configuration, however, depends on ever-changing link conditions. To this end, we developed an adjustable spatial filter that can be used to change the system field of view on the fly. We demonstrate its use in quantum key distribution over a 1.7-km free-sp