July 2023 arXiv papers — page 43

Simanta Lahkar, Raghavan Ranganathan

Thermal rectifiers are devices that have different thermal conductivities in opposing directions of heat flow. The realization of practical thermal rectifiers relies significantly on a sound understanding of the underlying mechanisms of asymmetric heat transport, and two-dimensional materials offer a promising opportunity in this regard owing to their simpli

Sabri Mustafa Kahya, Muhammet Sami Yavuz, Eckehard Steinbach

Detecting human presence indoors with millimeter-wave frequency-modulated continuous-wave (FMCW) radar faces challenges from both moving and stationary clutter. This work proposes a robust and real-time capable human presence and out-of-distribution (OOD) detection method using 60 GHz short-range FMCW radar. HOOD solves the human presence and OOD detection p

Lucas Ambrozio, Rafael Montezuma, Roney Santos

We develop a Morse-Lusternik-Schnirelmann theory for the distance between two points of a smoothly embedded circle in a complete Riemannian manifold. This theory suggests very naturally a definition of width that generalises the classical definition of the width of plane curves. Pairs of points of the circle realising the width bound one or more minimising g

Tareq Jaouni, Xiaoqin Gao, Sören Arlt, Mario Krenn

In 1987, Vaidman, Aharanov, and Albert put forward a puzzle called the Mean King's Problem (MKP) that can be solved only by harnessing quantum entanglement. Prime-powered solutions to the problem have been shown to exist, but they have not yet been experimentally realized for any dimension beyond two. We propose a general first-of-its-kind experimental schem

Risto Raitio

We analyze the significance of supersymmetry in two topological models and the standard model (SM). We conclude that the two topological field theory models favor hidden supersymmetry. The SM superpartners, instead, have not been found.

Aleksandar Vučković, Benedikt Stock, Alexander V. Hopp, Mathias Winkel

The need for large amounts of training data in modern machine learning is one of the biggest challenges of the field. Compared to the brain, current artificial algorithms are much less capable of learning invariance transformations and employing them to extrapolate knowledge from small sample sets. It has recently been proposed that the brain might encode pe

William W. Howard, Anthony F. Martone, R. Michael Buehrer

Cognitive radar networks (CRNs) are capable of optimizing operating parameters in order to provide actionable information to an operator or secondary system. CRNs have been proposed to answer the need for low-cost devices tracking potentially large numbers of targets in geographically diverse regions. Networks of small-scale devices have also been shown to o

Christopher Clarke, Matthew Hall, Gaurav Mittal, Ye Yu

Classic approaches to content moderation typically apply a rule-based heuristic approach to flag content. While rules are easily customizable and intuitive for humans to interpret, they are inherently fragile and lack the flexibility or robustness needed to moderate the vast amount of undesirable content found online today. Recent advances in deep learning h

Giovanni Di Fratta, Valeriy Slastikov, Arghir Zarnescu

The paper concerns the analysis of global minimizers of a Dirichlet-type energy functional defined on the space of vector fields $H^1(S,T)$, where $S$ and $T$ are surfaces of revolution. The energy functional we consider is closely related to a reduced model in the variational theory of micromagnetism for the analysis of observable magnetization states in cu

Chuming Li, Ruonan Jia, Jie Liu, Yinmin Zhang

Model-based reinforcement learning (RL) has demonstrated remarkable successes on a range of continuous control tasks due to its high sample efficiency. To save the computation cost of conducting planning online, recent practices tend to distill optimized action sequences into an RL policy during the training phase. Although the distillation can incorporate b

Alek Westover

In Linear Hashing ($\mathsf{LH}$) with $\beta$ bins on a size $u$ universe ${\mathcal{U}=\{0,1,\ldots, u-1\}}$, items $\{x_1,x_2,\ldots, x_n\}\subset \mathcal{U}$ are placed in bins by the hash function $$x_i\mapsto (ax_i+b)\mod p \mod \beta$$ for some prime $p\in [u,2u]$ and randomly chosen integers $a,b \in [1,p]$. The "maxload" of $\mathsf{LH}$ is the num

Fabio Camilli, Alessandro Goffi, Cristian Mendico

We provide some new integral estimates for solutions to Hamilton-Jacobi equations and we discuss several consequences, ranging from $L^p$-rates of convergence for the vanishing viscosity approximation to regularizing effects for the Cauchy problem in the whole Euclidean space and Liouville-type theorems. Our approach is based on duality techniques \`a la Eva

Patricio A. Gallardo, Roberto Puddu, Kathleen Harrington, Bradford Benson

CMB-S4, the next-generation ground-based cosmic microwave background (CMB) observatory, will provide detailed maps of the CMB at millimeter wavelengths to dramatically advance our understanding of the origin and evolution of the universe. CMB-S4 will deploy large and small aperture telescopes with hundreds of thousands of detectors to observe the CMB at arcm

Alan A. Coley, Alexandre Landry, Robert J. van den Hoogen, David D. McNutt

Theories of gravity based on teleparallel geometries are characterized by the torsion, which is a function of the coframe, derivatives of the coframe, and a zero curvature and metric compatible spin connection. The appropriate notion of a symmetry in a teleparallel geometry is that of an affine symmetry. Due to the importance of the de Sitter geometry and Ei

Alessandro Goffi

We provide a proof of strong maximum and minimum principles for fully nonlinear uniformly parabolic equations of second order. The approach is of parabolic nature, slightly differs from the earlier one proposed by L. Nirenberg and does not exploit the parabolic Harnack inequality.

Alejandro Rodriguez Sponheimer

Let $(X,\mu,T,d)$ be a metric measure-preserving dynamical system such that $3$-fold correlations decay exponentially for Lipschitz continuous observables. Given a sequence $(M_k)$ that converges to $0$ slowly enough, we obtain a strong dynamical Borel--Cantelli result for recurrence, i.e., for $\mu$-a.e. $x\in X$ \[ \lim_{n \to \infty}\frac{\sum_{k=1}^{n} \

Marius Costandin

In this paper the problem of maximizing the distance to a given fixed point over an intersection of balls is considered. It is known that this problem is NP complete in the general case, since any subset sum problem can be solved upon solving a maximization of the distance over an intersection of balls to a point inside the convex hull. The general context i

Clay Cordova, Kantaro Ohmori

We describe the interplay between electric-magnetic duality and higher symmetry in Maxwell theory. When the fine-structure constant is rational, the theory admits non-invertible symmetries which can be realized as composites of electric-magnetic duality and gauging a discrete subgroup of the one-form global symmetry. These non-invertible symmetries are appro

Ayush Sekhari, Karthik Sridharan, Wen Sun, Runzhe Wu

We consider the problem of contextual bandits and imitation learning, where the learner lacks direct knowledge of the executed action's reward. Instead, the learner can actively query an expert at each round to compare two actions and receive noisy preference feedback. The learner's objective is two-fold: to minimize the regret associated with the executed a

Pete Rigas

We prove that the phase transition for the Gaussian free field (GFF) is sharp. In comparison to a previous argument due to Rodriguez in 2017 which characterized a $0-1$ law for the Massive Gaussian Free Field by analyzing crossing probabilities below a threshold $h_{**}$, we implement a strategy due to Duminil-Copin and Manolescu in 2016, which establishes t

Viktor Stasenko, Konstantin Belotsky

Primordial black hole (PBH) binaries forming in the early Universe may contribute to the merger events observed by the LIGO-Virgo-KAGRA collaborations. Moreover, the inferred merger rate constraints the fraction of PBH with masses $m \sim 10 \, M_{\odot}$ in the dark matter (DM) to $f_{PBH} \lesssim 10^{-3}$. This constraint assumes that after the formation

Alessia andò, Roderick Edwards, Nicola Guglielmi

In a recent paper by Guglielmi and Hairer (SIADS 2015), an analysis in the $\varepsilon\to 0$ limit was proposed of regularized discontinuous ODEs in codimension-2 switching domains; this was obtained by studying a certain 2-dimensional system describing the so-called hidden dynamics. In particular, the existence of a unique limit solution was not proved in

Maitham G. Yousif, Lamiaa Al-Maliki, Jinan J. Al-Baghdadi, Nasser Ghaly Yousif

This study aimed to comprehensively investigate the post-COVID-19 effects on female fertility in patients with a history of severe COVID-19 infection. Data were collected from 340 patients who had previously experienced severe COVID-19 symptoms and sought medical assistance at private clinics and fertility centers in various provinces of Iraq. A comparative

Michael J. Schlosser

We introduce an algebra of elliptic commuting variables involving a base $q$, nome $p$, and $2r$ noncommuting variables. This algebra, which for $r=1$ reduces to an algebra considered earlier by the author, is an elliptic extension of the well-known algebra of $r$ $q$-commuting variables. We present a multinomial theorem valid as an identity in this algebra,

Elena Bunina, Maria Vladykina

In this paper we prove that every automorphism of a Chevalley group with the root system G_2 over a commutative ring R with 1/3, generated by all its invertible elements and the ideal 2R is a composition of ring and inner automorphisms.

Michał Balcerek, Agnieszka Wyłomańska, Krzysztof Burnecki, Ralf Metzler

The stochastic trajectories of molecules in living cells, as well as the dynamics in many other complex systems, often exhibit memory in their path over long periods of time. In addition, these systems can show dynamic heterogeneities due to which the motion changes along the trajectories. Such effects manifest themselves as spatiotemporal correlations. Desp

Alexander Roth, Carlos Gaete-Morales, Dana Kirchem, Wolf-Peter Schill

Heat pumps play a major role in decreasing fossil fuel use in heating. They increase electricity demand, but could also foster the system integration of variable renewable energy sources. We analyze three scenarios for expanding decentralized heat pumps in Germany by 2030, focusing on the role of buffer heat storage. Using an open-source power sector model,

Haocong Rao, Cyril Leung, Chunyan Miao

With rapid advancements in depth sensors and deep learning, skeleton-based person re-identification (re-ID) models have recently achieved remarkable progress with many advantages. Most existing solutions learn single-level skeleton features from body joints with the assumption of equal skeleton importance, while they typically lack the ability to exploit mor

Benny Wong

Optimization methods are essential in solving complex problems across various domains. In this research paper, we introduce a novel optimization method called Gaussian Crunching Search (GCS). Inspired by the behaviour of particles in a Gaussian distribution, GCS aims to efficiently explore the solution space and converge towards the global optimum. We presen

Hannaneh Akrami, Jugal Garg, Eklavya Sharma, Setareh Taki

We consider fair division of a set of indivisible goods among $n$ agents with additive valuations using the fairness notion of maximin share (MMS). MMS is the most popular share-based notion, in which an agent finds an allocation fair to her if she receives goods worth at least her ($1$-out-of-$n$) MMS value. An allocation is called MMS if all agents receive

Srijoni Majumdar, Evangelos Pournaras

The legitimacy of bottom-up democratic processes for the distribution of public funds by policy-makers is challenging and complex. Participatory budgeting is such a process, where voting outcomes may not always be fair or inclusive. Deliberation for which project ideas to put for voting and choose for implementation lack systematization and do not scale. Thi

Pedro Orvalho, Jelle Piepenbrock, Mikoláš Janota, Vasco Manquinho

Automated program analysis is a pivotal research domain in many areas of Computer Science -- Formal Methods and Artificial Intelligence, in particular. Due to the undecidability of the problem of program equivalence, comparing two programs is highly challenging. Typically, in order to compare two programs, a relation between both programs' sets of variables

Ming Y. Lu, Bowen Chen, Drew F. K. Williamson, Richard J. Chen

The accelerated adoption of digital pathology and advances in deep learning have enabled the development of powerful models for various pathology tasks across a diverse array of diseases and patient cohorts. However, model training is often difficult due to label scarcity in the medical domain and the model's usage is limited by the specific task and disease

Barnali Das, Nur Jaman, M Sami

We investigate the production process of induced gravity waves due to large scalar fluctuations in the paradigm of quintessential inflation. We numerically solve the Mukhanov-Sasaki equation for different sets of parameters to obtain the power spectra. We demonstrate that the induced gravity wave signal generated in this framework can falls within the region

Beatriz Dias, Robert Koenig

We propose efficient algorithms for classically simulating fermionic linear optics operations applied to non-Gaussian initial states. By gadget constructions, this provides algorithms for fermionic linear optics with non-Gaussian operations. We argue that this problem is analogous to that of simulating Clifford circuits with non-stabilizer initial states: Al

M. Atzori Corona, M. Cadeddu, N. Cargioli, F. Dordei

The search for coherent elastic neutrino nucleus scattering (CE$\nu$NS) using reactor antineutrinos represents a formidable experimental challenge, recently boosted by the observation of such a process at the Dresden-II reactor site using a germanium detector. This observation relies on an unexpected enhancement at low energies of the measured quenching fact

Wan Luo, Aparna Baskaran, Robert A. Pelcovits, Thomas R. Powers

Using a minimal hydrodynamic model, we theoretically and computationally study active gels in straight and annular two-dimensional channels subject to an externally imposed shear. The gels are isotropic in the absence of externally- or activity-driven shear, but have nematic order that increases with shear rate. Using the finite element method, we determine

Shangzan Zhang, Sida Peng, Yinji ShenTu, Qing Shuai

Recently, the editing of neural radiance fields (NeRFs) has gained considerable attention, but most prior works focus on static scenes while research on the appearance editing of dynamic scenes is relatively lacking. In this paper, we propose a novel framework to edit the local appearance of dynamic NeRFs by manipulating pixels in a single frame of training

Domenico D'Alessandro

We describe a framework for the controllability analysis of networks of $n$ quantum systems of an arbitrary dimension $d$, {\it qudits}, with dynamics determined by Hamiltonians that are invariant under the permutation group $S_n$. Because of the symmetry, the underlying Hilbert space, ${\cal H}=(\mathbb{C}^d)^{\otimes n}$, splits into invariant subspaces fo

Zihan Wang, Xiangyang Li, Jiahao Yang, Yeqi Liu

Vision-and-language navigation (VLN) enables the agent to navigate to a remote location following the natural language instruction in 3D environments. To represent the previously visited environment, most approaches for VLN implement memory using recurrent states, topological maps, or top-down semantic maps. In contrast to these approaches, we build the top-

Md Abrar Jahin, Md Sakib Hossain Shovon, Md. Saiful Islam, Jungpil Shin

Supply chain management relies on accurate backorder prediction for optimizing inventory control, reducing costs, and enhancing customer satisfaction. However, traditional machine-learning models struggle with large-scale datasets and complex relationships, hindering real-world data collection. This research introduces a novel methodological framework for su

M. W. AlMasri

Logic gates can be written in terms of complex differential operators, where the inputs and outputs are holomorphic functions with several variables. Using the polar representation of complex numbers, we arrive at an immediate connection between the oscillatory behavior of the system and logic gates. We discuss the universality of this formalism in a variety

Lukas Gonon, Antoine Jacquier

Universal approximation theorems are the foundations of classical neural networks, providing theoretical guarantees that the latter are able to approximate maps of interest. Recent results have shown that this can also be achieved in a quantum setting, whereby classical functions can be approximated by parameterised quantum circuits. We provide here precise

Swastika Roy, Hatim Chergui, Christos Verikoukis

In the context of sixth-generation (6G) networks, where diverse network slices coexist, the adoption of AI-driven zero-touch management and orchestration (MANO) becomes crucial. However, ensuring the trustworthiness of AI black-boxes in real deployments is challenging. Explainable AI (XAI) tools can play a vital role in establishing transparency among the st

Bertalan Bodor, Gergő Gyenizse, Miklós Maróti, László Zádori

We study the Taylor varieties and obtain new characterizations of them via compatible reflexive digraphs. Based on our findings, we prove that in the lattice of interpretability types of varieties, the filter of the types of all Taylor varieties is prime.

Riccardo Giannini

The non-hyperelliptic connected components of the strata of translation surfaces are conjectured to be orbifold classifying spaces for some groups commensurable to some mapping class groups. The topological monodromy map of the non-hyperelliptic components projects naturally to the mapping class group of the underlying punctured surface and is an obvious can

Hu Zhang, Yanchen Li, Luziwei Leng, Kaiwei Che

Event-based sensors, distinguished by their high temporal resolution of 1 $\mathrm{\mu}\text{s}$ and a dynamic range of 120 $\text{dB}$, stand out as ideal tools for deployment in fast-paced settings like vehicles and drones. Traditional object detection techniques that utilize Artificial Neural Networks (ANNs) face challenges due to the sparse and asynchron

Pavel S. Gevorgyan

Shape theory was founded by K.~Borsuk 50 years ago. In essence, this is spectral homotopy theory; it occupies an important place in geometric topology. The article presents the basic concepts and the most important, in our opinion, results of shape theory. Unfortunately, many other interesting problems and results related to this theory could not be covered

Evangelos Markakis, Georgios Papasotiropoulos

In recent years, the study of various models and questions related to Liquid Democracy has been of growing interest among the community of Computational Social Choice. A concern that has been raised, is that current academic literature focuses solely on static inputs, concealing a key characteristic of Liquid Democracy: the right for a voter to change her mi

Parnian Kassraie, Nicolas Emmenegger, Andreas Krause, Aldo Pacchiano

Model selection in the context of bandit optimization is a challenging problem, as it requires balancing exploration and exploitation not only for action selection, but also for model selection. One natural approach is to rely on online learning algorithms that treat different models as experts. Existing methods, however, scale poorly ($\text{poly}M$) with t

Łukasz Dębowski

The article introduces corrections to Zipf's and Heaps' laws based on systematic models of the proportion of hapaxes, i.e., words that occur once. The derivation rests on two assumptions. The first one is the standard urn model which predicts that marginal frequency distributions for shorter texts look as if word tokens were sampled blindly from a gi

Stefano Buccheri, Tommaso Leonori, Julio D. Rossi

The starting point of this paper is the study of the asymptotic behavior, as $p\to\infty$, of the following minimization problem $$ \min\left\{\frac1{p}\int|\nabla v|^{p}+\frac12\int(v-f)^2 \,, \quad \ v\in W^{1,p} (\Omega)\right\}. $$ We show that the limit problem provides the best approximation, in the $L^2$-norm, of the datum $f$ among all Lipschitz func

M. Sacerdoti, V. Toso, G. Vinelli, G. Rosi

Positronium (Ps) has emerged as a promising test particle within the QUPLAS collaboration for investigating the gravitational effect. In this work, we present a novel approach to generate a monoenergetic and highly coherent Ps beam by creating a negative Ps ion (Ps$^-$, consisting of two electrons and one positron). The necessary positron beam is formed by u

Laurent Kloeker, Gregor Joeken, Lutz Eckstein

Smart roadside infrastructure sensors in the form of intelligent transportation system stations (ITS-Ss) are increasingly deployed worldwide at relevant traffic nodes. The resulting digital twins of the real environment are suitable for developing and validating connected and automated driving functions and for increasing the operational safety of intelligen

Anav Sood, Trevor Hastie

We consider the problem of selecting a small subset of representative variables from a large dataset. In the computer science literature, this dimensionality reduction problem is typically formalized as Column Subset Selection (CSS). Meanwhile, the typical statistical formalization is to find an information-maximizing set of Principal Variables. This paper s

Leonid Prokhorov, Sam Cooper, Amit Singh Ubhi, Conor Mow-Lowry

We present the design, control system, and noise analysis of a 6-axis seismometer comprising a mass suspended by a single fused silica fibre. We utilise custom-made, compact Michelson interferometers for the readout of the mass motion relative to the table and successfully overcome the sensitivity of existing commercial seismometers by over an order of magni

R. Basak, R. Kozlowski, L. A. Pugnaloni, M. Kramar

In quasi-two-dimensional experiments with photoelastic particles confined to an annular region, an intruder constrained to move in a circular path halfway between the annular walls experiences stick-slip dynamics. We discuss the response of the granular medium to the driven intruder, focusing on the evolution of the force network during sticking periods. Bec

Paolo Acampora, Vincenzo Amato, Emanuele Cristoforoni

We investigate the relationship between the Neumann and Steklov principal eigenvalues emerging from the study of collapsing convex domains in $\mathbb{R}^2$. Such a relationship allows us to give a partial proof of a conjecture concerning estimates of the ratio of the former to the latter: we show that thinning triangles maximize the ratio among convex thinn

Masahiro Kanazaki, Takeharu Toyoda

In this study, we propose an improvement to the direct mating method, a constraint handling approach for multi-objective evolutionary algorithms, by hybridizing it with local mating. Local mating selects another parent from the feasible solution space around the initially selected parent. The direct mating method selects the other parent along the optimal di

Enric Gusó, Joanna Luberadzka, Martí Baig, Umut Sayin Saraç

We investigate the objective performance of five high-end commercially available Hearing Aid (HA) devices compared to DNN-based speech enhancement algorithms in complex acoustic environments. To this end, we measure the HRTFs of a single HA device to synthesize a binaural dataset for training two state-of-the-art causal and non-causal DNN enhancement models.

Domenico P. L. Castrigiano

The positive operator valued localizations (POL) of a massive scalar boson are constructed and a characterization and structural analyses of their kernels are obtained. In the focus of this article are the causal features of the POL. There is the well-known causal time evolution (CT). Recently a POL by Terno and Moretti, which is a kinematical deformation of

Jin Qiao, Zhao Li, Ran Ji, Tao Zhu

This paper explores the evolutionary behavior of the Earth-satellite binary system within the framework of the ghost-free parity-violating gravity and the corresponding discussion on the parity-violating effect from the laser-ranged satellites. For this purpose, we start our study with the Parameterized Post-Newtonian (PPN) metric of this gravity theory to s

Animesh Chatterjee, Srubabati Goswami, Supriya Pan

Results from experiments like LSND and MiniBooNE hint towards the possible presence of an extra eV scale sterile neutrino. The addition of such a neutrino will significantly impact the standard three flavour neutrino oscillations. In particular, it can give rise to additional degeneracies due to additional sterile parameters. For an eV scale sterile neutrino

Neil Pritchard, Thomas Weighill

We prove an equivalence between open questions about the embeddability of the space of persistence diagrams and the space of probability distributions (i.e.~Wasserstein space). It is known that for many natural metrics, no coarse embedding of either of these two spaces into Hilbert space exists. Some cases remain open, however. In particular, whether coarse

A. C. Canbay, O. Cakir

We investigate the single production of vector-like quarks at the High Luminosity LHC (HL-LHC). With the assumed (enhanced) couplings to third generation quarks of the standard model, vector-like quarks $B/X$ are produced in association with a bottom ($b$) or top ($t$) quark, which correspond to $Bbq$ and $Btq/Xtq$ production modes, including an additional s

Yue Yu, Sophia Yi, Xi Nan, Leo Yu-Ho Lo

Food waste presents a substantial challenge with significant environmental and economic ramifications, and its severity on campus environments is of particular concern. In response to this, we introduce FoodWise, a dual-component system tailored to inspire and incentivize campus communities to reduce food waste. The system consists of a data storytelling das

Ana Sainz de Murieta, Thomas E. Collett, Mark R. Magee, Luke Weisenbach

Strong gravitationally lensed supernovae (glSNe) are a powerful probe to obtain a measure of the expansion rate of the Universe, but they are also extremely rare. To date, only two glSNe with multiple images strongly lensed by galaxies have been found, but their short time delays make them unsuitable for cosmography. Here, we simulate a realistic catalogue o

Suman Chatterjee, Medha Dandu, Pushkar Dasika, Rabindra Biswas

Excitonic states trapped in harmonic moir\'e wells of twisted heterobilayers is an intriguing testbed. However, the moir\'e potential is primarily governed by the twist angle, and its dynamic tuning remains a challenge. Here we demonstrate anharmonic tuning of moir\'e potential in a WS$_2$/WSe$_2$ heterobilayer through gate voltage and optical power. A gate

Marli R. Cantarino, Kevin R. Pakuszewski, Björn Salzmann, Pedro H. A. Moya

Chemical substitution is commonly used to explore new ground states in materials, yet the role of disorder is often overlooked. In Mn-substituted BaFe$_{2}$As$_{2}$ (MnBFA), superconductivity (SC) is absent, despite being observed for nominal hole-doped phases. Instead, a glassy magnetic phase emerges, associated with the $S=5/2$ Mn local spins. In this work

Olof Giselsson

We show that for $q\in (0,1),$ the $C^{*}$-algebra $SU_{q}(3)$ is isomorphic a rank $2$ graph $C^{*}$-algebra (in the sense of Pask and Kumjian). This graph is derived by passing the to the limit $q\to 0$ for a set of generators of $SU_{q}(3)$. Moreover, the isomorphism can be taken to be $\mathbb{T}^{2}$-equivariant with respect the right-action on $SU_{q}(

Judith Ortmann

We characterise integral points of bounded log-anticanonical height on a quartic del Pezzo surface of singularity type $\mathbf{A}_3$ over imaginary quadratic fields with respect to its singularity and its lines. Furthermore, we count these integral points of bounded height by using universal torsors and interpret the count geometrically to prove an analogue

F. R. Klinkhamer

We present a 5D metric which interpolates between the standard 4D Schwarzschild metric with mass parameter $M$ and a new 4D $M$-deformed vacuum-defect-wormhole metric. The 5D spacetime can, in principle, have an infinite mass density that gives rise to the $M$ parameter of the 4D $M$-deformed vacuum-defect wormhole. For completeness, we also give 4D interpol

Paolo D'Alberto, Veronica Milenkiy, Fairiz Fi Azizi

Mobile-phone advertising enables marketers to reach customers at a personal level and it enables the measure of costumers reaction by novel approaches, in real time, and at scale. By keeping a device anonymous, we can deliver custom adverts and we can check when the device owner will visit a specific mortar-and-brick location. This is the first step in a sal

Yimika Erinle, Yathin Kethepalli, Yebo Feng, Jiahua Xu

With the advent of decentralised digital currencies powered by blockchain technology, a new era of peer-to-peer transactions has commenced. The rapid growth of the cryptocurrency economy has led to increased use of transaction-enabling wallets, making them a focal point for security risks. As the frequency of wallet-related incidents rises, there is a critic

Jafar Sadeghi, Mohammad Ali S. Afshar, Saeed Noori Gashti, Mohammad Reza Alipour

It was shown that a standard ring of light can be imagined outside the event horizon for stationary rotating four-dimensional black holes with axial symmetry using the topological method\cite{001,002}. Based on this concept, in this paper, we investigate the topological charge and the conditions of existence of the photon sphere (PS) for a hyperscaling viola

Jacob-Junqi Tian, Omkar Dige, D. B. Emerson, Faiza Khan Khattak

Large language models (LLMs) are trained on vast, uncurated datasets that contain various forms of biases and language reinforcing harmful stereotypes that may be subsequently inherited by the models themselves. Therefore, it is essential to examine and address biases in language models, integrating fairness into their development to ensure that these models

Mingwen Shao, Lingzhuang Meng, Yuanjian Qiao, Lixu Zhang

Since the training data of the target model is not available in the black-box substitute attack, most recent schemes utilize GANs to generate data for training the substitute model. However, these GANs-based schemes suffer from low training efficiency as the generator needs to be retrained for each target model during the substitute training process, as well

Young-ho Cho, Hao Zhu

Effective power flow modeling critically affects the ability to efficiently solve large-scale grid optimization problems, especially those with topology-related decision variables. In this work, we put forth a generative modeling approach to obtain a piecewise linear (PWL) approximation of AC power flow by training a simple neural network model from actual d

Yuqiu Fu, Kevin Ren, Haoyu Wang

Motivated by the study of the maximal operator for the Schr\"{o}dinger equation on the one-dimensional torus $ \mathbb{T}^1 $, it is conjectured that for any complex sequence $ \{b_n\}_{n=1}^N $, $$ \left\| \sup_{t\in [0,N^2]} \left|\sum_{n=1}^N b_n e \left(x\frac{n}{N} + t\frac{n^2}{N^2} \right) \right| \right\|_{L^4([0,N])} \leq C_\epsilon N^{\epsilon} N^{

Bingxin Xu, Zaijun Chen, Theodor W. Hänsch, Nathalie Picqué

Ultraviolet spectroscopy provides unique insights into the structure of matter with applications ranging from fundamental tests to photochemistry in the earth's atmosphere and astronomical observations from space telescopes. At longer wavelengths, dual-comb spectroscopy with two interfering laser frequency combs has evolved into a powerful technique that can

Yong-Hyun Park, Mingi Kwon, Jaewoong Choi, Junghyo Jo

Despite the success of diffusion models (DMs), we still lack a thorough understanding of their latent space. To understand the latent space $\mathbf{x}_t \in \mathcal{X}$, we analyze them from a geometrical perspective. Our approach involves deriving the local latent basis within $\mathcal{X}$ by leveraging the pullback metric associated with their encoding

E. Mitsi, K. Koutsomitis, G. Apostolopoulos

We propose two methods for evaluating athermal recombination corrected (arc) displacement damage parameters in ion irradiations employing the computer code SRIM (Stopping and Range of Ions in Matter). The first method consists of post-processing the detailed SRIM output for all simulated damage events and re-calculating according to the arc damage model. In

Johanna Schmidt, Bernhard Pointner, Silvia Miksch

Draco has been developed as an automated visualization recommendation system formalizing design knowledge as logical constraints in ASP (Answer-Set Programming). With an increasing set of constraints and incorporated design knowledge, even visualization experts lose overview in Draco and struggle to retrace the automated recommendation decisions made by the

Antonina A. Arkhipova, Yiqi Zhang, Yaroslav V. Kartashov, Sergei A. Zhuravitskii

Floquet systems with periodically varying in time parameters enable realization of unconventional topological phases that do not exist in static systems with constant parameters and that are frequently accompanied by appearance of novel types of the topological states. Among such Floquet systems are the Su-Schrieffer-Heeger lattices with periodically-modulat

Fabian Brand, Jürgen Seiler, André Kaup

Conditional coding is a new video coding paradigm enabled by neural-network-based compression. It can be shown that conditional coding is in theory better than the traditional residual coding, which is widely used in video compression standards like HEVC or VVC. However, on closer inspection, it becomes clear that conditional coders can suffer from informati

Marcel S. Claro, Javier Corral-Sertal, Adolfo O. Fumega, Santiago Blanco-Canosa

The emergence of symmetry-breaking orders such as ferromagnetism and the weak interlayer bonding in van der Waals materials, offers a unique platform to engineer novel heterostructures and tune transport properties like thermal conductivity. Here, we report the experimental and theoretical study of the cross-plane thermal conductivity, $\kappa_\perp$, of the

Helal El-Zaatari, Fei Yu, Michael R Kosorok

Statistical analysis of social networks provides valuable insights into complex network interactions across various scientific disciplines. However, accurate modeling of networks remains challenging due to the heavy computational burden and the need to account for observed network dependencies. Exponential Random Graph Models (ERGMs) have emerged as a promis

Sofie Castro Holbæk, Morten H. Christensen, Andreas Kreisel, Brian M. Andersen

Motivated by the recent discovery of superconductivity in the kagome $A$V$_3$Sb$_5$ ($A$: K, Rb, Cs) metals, we perform a theoretical study of the symmetry-allowed superconducting orders on the two-dimensional kagome lattice with focus on their response to disorder. We uncover a qualitative difference between the robustness of intraband spin-singlet (even-pa

Evgenii Ievlev, Michael R. R. Good

Although non-intuitive, an accelerated electron along a particular trajectory can be shown to emit classical electromagnetic radiation in the form of a Fermi-Dirac spectral distribution when observed in a particular angular regime. We investigate the relationship between the distribution, spectrum, and particle count. The result for the moving point charge i

Kübra Benli, Giulia Cesana, Cécile Dartyge, Charlotte Dombrowsky

Let $s(n)$ denote the sum of proper divisors of an integer $n$. In 1992, Erd\H{o}s, Granville, Pomerance, and Spiro (EGPS) conjectured that if $\mathcal{A}$ is a set of integers with asymptotic density zero then $s^{-1}(\mathcal{A})$ also has asymptotic density zero. In this paper we show that the EGPS conjecture holds when $\mathcal{A}$ is taken to be a set

Wenao Ma, Cheng Chen, Jill Abrigo, Calvin Hoi-Kwan Mak

Intracerebral hemorrhage (ICH) is the second most common and deadliest form of stroke. Despite medical advances, predicting treat ment outcomes for ICH remains a challenge. This paper proposes a novel prognostic model that utilizes both imaging and tabular data to predict treatment outcome for ICH. Our model is trained on observational data collected from no

Yuehua Su, Kun Cao, Chao Zhang

In the study of strongly correlated electrons, one of the challenging core tasks is to develop the potential techniques for direct detection of the many-body correlations of strongly correlated electrons. The $(\gamma, 2e)$ photoemission technique has been developed to investigate the two-body correlations of the target correlated electrons. In this article,

Izzeddin Gur, Hiroki Furuta, Austin Huang, Mustafa Safdari

Pre-trained large language models (LLMs) have recently achieved better generalization and sample efficiency in autonomous web automation. However, the performance on real-world websites has still suffered from (1) open domainness, (2) limited context length, and (3) lack of inductive bias on HTML. We introduce WebAgent, an LLM-driven agent that learns from s

Xinyi Yu, Xiang Yin, Lars Lindemann

In time-critical systems, such as air traffic control systems, it is crucial to design control policies that are robust to timing uncertainty. Recently, the notion of Asynchronous Temporal Robustness (ATR) was proposed to capture the robustness of a system trajectory against individual time shifts in its sub-trajectories. In a multi-robot system, this may co

Reuben Tan, Matthias De Lange, Michael Iuzzolino, Bryan A. Plummer

Long-term activity forecasting is an especially challenging research problem because it requires understanding the temporal relationships between observed actions, as well as the variability and complexity of human activities. Despite relying on strong supervision via expensive human annotations, state-of-the-art forecasting approaches often generalize poorl

C. I. Ugwu, S. Casarin, O. Lanz

As a fundamental part of computational healthcare, Computer Tomography (CT) and Magnetic Resonance Imaging (MRI) provide volumetric data, making the development of algorithms for 3D image analysis a necessity. Despite being computationally cheap, 2D Convolutional Neural Networks can only extract spatial information. In contrast, 3D CNNs can extract three-dim

BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson

By analyzing 7.33 fb$^{-1}$ of $e^+e^-$ annihilation data collected at center-of-mass energies between 4.128 and 4.226 GeV with the BESIII detector, we report the observation of the semileptonic decay $D^+_s\to \eta^\prime \mu^+\nu_\mu$, with a statistical significance larger than 10$\sigma$, and the measurements of the $D_s^+ \to \eta\mu^+\nu_\mu$ and $D_s^

Hancheng Min, Enrique Mallada, René Vidal

This paper studies the problem of training a two-layer ReLU network for binary classification using gradient flow with small initialization. We consider a training dataset with well-separated input vectors: Any pair of input data with the same label are positively correlated, and any pair with different labels are negatively correlated. Our analysis shows th

Sean Hon, Jiamei Dong, Stefano Serra-Capizzano

In this work, we propose a novel preconditioned Krylov subspace method for solving an optimal control problem of wave equations, after explicitly identifying the asymptotic spectral distribution of the involved sequence of linear coefficient matrices from the optimal control problem. Namely, we first show that the all-at-once system stemming from the wave co

Sebastian Barney, Mahvish Khurum, Kai Petersen, Michael Unterkalmsteiner

Rubrics and oral feedback are approaches to help students improve performance and meet learning outcomes. However, their effect on the actual improvement achieved is inconclusive. This paper evaluates the effect of rubrics and oral feedback on student learning outcomes. An experiment was conducted in a software engineering course on requirements engineering,