May 2023 arXiv papers — page 156

Hannaneh Akrami, Bhaskar Ray Chaudhury, Jugal Garg, Kurt Mehlhorn

We study fair division of indivisible chores among $n$ agents with additive disutility functions. Two well-studied fairness notions for indivisible items are envy-freeness up to one/any item (EF1/EFX) and the standard notion of economic efficiency is Pareto optimality (PO). There is a noticeable gap between the results known for both EF1 and EFX in the goods

Mohamed Slim Kammoun

The work of Vershik and Kerov [1977], Logan and Shepp [1977] established that the shape of the scaled random young diagram in Russian notation, as determined by the Plancherel measure, converges to a deterministic shape. In this article, we focus on the scenario where the number of fixed points is substantial. We provide evidence that, subject to specific re

J. Nevalainen, S. Molendi

We applied a scientific approach to the problem of the effective area cross-calibration of the XMM-Newton EPIC instruments. Using a sample of galaxy clusters observed with the XMM-Newton EPIC, we quantified the effective area cross-calibration bias between the EPIC instruments as implemented in the public calibration data base on November 2021 in the 0.5-6.1

F. Aroca, L. Bossinger, S. Falkensteiner, C. Garay Lopez

We consider a finite-dimensional vector space $W\subset K^E$ over an arbitrary field $K$ and an arbitrary set $E$. We show that the set $C(W)\subset 2^E$ consisting of the minimal supports of $W$ are the circuits of a matroid on $E$. In particular, we show that this matroid is cofinitary (hence, tame). When the cardinality of $K$ is large enough (with respec

Lila Cadi Tazi, Alex J. W. Thom

The recent developments of quantum computing present potential novel pathways for quantum chemistry, as the increased computational power of quantum computers could be harnessed to naturally encode and solve electronic structure problems. Theoretically exact quantum algorithms for chemistry have been proposed (e.g. Quantum Phase Estimation) but the limited c

David Wan, Shiyue Zhang, Mohit Bansal

Language models (LMs) can generate hallucinations and incoherent outputs, which highlights their weak context dependency. Cache-LMs, which augment LMs with a memory of recent history, can increase context dependency and have shown remarkable performance in diverse language generation tasks. However, we find that even with training, the performance gain stemm

Ankita Jindal, Sudesh Kaur Khanduja

Let $n\geq 2$ be an integer. Let $\phi(x)$ belonging to $\mathbb{Z}[x]$ be a monic polynomial which is irreducible modulo all primes less than or equal to $n$. Let $a_0(x), a_1(x), \dots, a_{n-1}(x)$ belonging to $\mathbb{Z}[x]$ be polynomials each having degree less than $\deg \phi(x)$ and $a_n$ be an integer. Assume that $a_n$ and the content of $a_0(x)$ a

Matteo Fadel

The Schr\"odinger equation predicts the validity of the superposition principle at any scale, yet we do not experience cats being in a superposition of "dead" and "alive" in our everyday lives. Modifications to quantum theory at the fundamental level may be responsible for the objective collapse of the wave function above a critical mass, thereby breaking do

Benedikt Steinar Magnússon, Álfheiður Edda Sigurðardóttir, Ragnar Sigurðsson, Bergur Snorrason

This paper is a survey of plurisubharmonic theory where the usual polynomial ring is replaced by a polynomial ring $\mathcal P^S(\mathbb C^n)$ where the $m$-th degree polynomials have exponents restricted to $mS$, where $S\subseteq \mathbb R^n_+$ is compact, convex and $0\in S$. We assume no other conditions on $S$ as these are necessary for $\mathcal P^S(\m

Ashwin K. Boddeti, Yi Wang, Xitlali G. Juarez, Alexandra Boltasseva

Dimensionality plays a crucial role in long-range dipole-dipole interactions (DDIs). We demonstrate that a resonant nanophotonic structure modifies the apparent dimensionality in an interacting ensemble of emitters, as revealed by population decay dynamics. Our measurements on a dense ensemble of interacting quantum emitters in a resonant nanophotonic struct

Marco A. A. de Paula, Haroldo C. D. Lima Junior, Pedro V. P. Cunha, Luís C. B. Crispino

Within nonlinear electrodynamics (NED), photons follow null geodesics of an effective geometry, which is different from the geometry of the spacetime itself. Over the last years, several works were dedicated to investigate the motion of photons in the effective geometry of NED-based magnetically charged regular black hole (RBH) solutions. However, there are

Jyothi Rikhab Chand, Mathews Jacob

We introduce multi-scale energy models to learn the prior distribution of images, which can be used in inverse problems to derive the Maximum A Posteriori (MAP) estimate and to sample from the posterior distribution. Compared to the traditional single-scale energy models, the multi-scale strategy improves the estimation accuracy and convergence of the MAP al

Baxi Chong, Juntao He, Daniel Soto, Tianyu Wang

While the transport of matter by wheeled vehicles or legged robots can be guaranteed in engineered landscapes like roads or rails, locomotion prediction in complex environments like collapsed buildings or crop fields remains challenging. Inspired by principles of information transmission which allow signals to be reliably transmitted over noisy channels, we

Mairieli Wessel, Tom Mens, Alexandre Decan, Pooya Rostami Mazrae

Large-scale software development has become a highly collaborative and geographically distributed endeavour, especially in open-source software development ecosystems and their associated developer communities. It has given rise to modern development processes (e.g., pull-based development) that involve a wide range of activities such as issue and bug handli

Yu-Rong Shu, Shao-Kai Jian, Anders W. Sandvik, Shuai Yin

Deconfined quantum criticality (DQC) arises from fractionalization of quasi-particles and leads to fascinating behaviors beyond the Landau-Ginzburg-Wilson description of phase transitions. Here, we study the critical dynamics when driving a two-dimensional quantum magnet through a weakly first-order transition point near a putative deconfined multicritical p

Elijah Fender, Sangjin Lee, Beomjun Sohn

We study the topological entropy of Reeb flows on contact manifolds with Liouville fillings. With the theory of persistence modules, we define SH-barcode entropy from the symplectic homology of a filling. We prove that the SH-barcode entropy is independent of the choice of the filling and that the barcode entropy provides a lower bound for the topological en

Kishaan Jeeveswaran, Prashant Bhat, Bahram Zonooz, Elahe Arani

The ability of deep neural networks to continually learn and adapt to a sequence of tasks has remained challenging due to catastrophic forgetting of previously learned tasks. Humans, on the other hand, have a remarkable ability to acquire, assimilate, and transfer knowledge across tasks throughout their lifetime without catastrophic forgetting. The versatili

Renato Spigler

We evaluate the {\em three-dimensional}, {\em non-axis-symmetric}, {\em time-dependent} Newton potential generated by a pair of mutually orbiting objects such as pairs of ordinary or neutron stars and, in some approximations, black holes, spinning around each other. The `vertical component' of the gravitational force (that is, that orthogonal to the plane of

Radu Curticapean

Given graphs $H$ and $G$, possibly with vertex-colors, a homomorphism is a function $f:V(H)\to V(G)$ that preserves colors and edges. Many interesting counting problems (e.g., subgraph and induced subgraph counts) are finite linear combinations $p(\cdot)=\sum_{H}\alpha_{H}\hom(H,\cdot)$ of homomorphism counts, and such linear combinations are known to be har

Yuanzhi Cai, Jagannath Aryal, Yuan Fang, Hong Huang

Semantic segmentation of multichannel images is a fundamental task for many applications. Selecting an appropriate channel combination from the original multichannel image can improve the accuracy of semantic segmentation and reduce the cost of data storage, processing and future acquisition. Existing channel selection methods typically use a reasonable sele

Sergio Vessella

These Notes are intended for graduate or undergraduate students who have familiarity with Lebesgue measure theory, partial differential equations, and functional analysis. The main topics covered in this work are the study of the Cauchy problem and unique continuation properties associated with partial differential equations. The primary objective is to fami

Yinghao Chen, Zehao Hu, Chen Zhi, Junxiao Han

Unit testing is an essential yet frequently arduous task. Various automated unit test generation tools have been introduced to mitigate this challenge. Notably, methods based on large language models (LLMs) have garnered considerable attention and exhibited promising results in recent years. Nevertheless, LLM-based tools encounter limitations in generating a

Xiao ling, Rongjun Qin

Texture mapping as a fundamental task in 3D modeling has been well established for well-acquired aerial assets under consistent illumination, yet it remains a challenge when it is scaled to large datasets with images under varying views and illuminations. A well-performed texture mapping algorithm must be able to efficiently select views, fuse and map textur

Fangjing Mu, Hao Wang, Zhanhang He, Qian Gou

Several short-chain fatty acids and their corresponding potential existing hydrated forms are important molecules in interstellar space. Their structures were optimized with twelve different computational methods. The dipole moments and the spectral constants, including rotational constants and centrifugal distortion constants were obtained. According to the

Dixeena Lopez, Shubhanshu Tiwari, Michael Ebersold

Binary neutron stars (BNSs) and neutron star--black hole (NSBH) binaries are two of the most promising gravitational wave (GW) sources to probe matter effects. Upcoming observing runs of LIGO-Virgo-KAGRA detectors and future third generation detectors like Einstein Telescope and Cosmic Explorer will allow the extraction of detailed information on these matte

Alessandro Ottaviano, Thomas Benz, Paul Scheffler, Luca Benini

Power and cost constraints in the internet-of-things (IoT) extreme-edge and TinyML domains, coupled with increasing performance requirements, motivate a trend toward heterogeneous architectures. These designs use energy-efficient application-class host processors to coordinate compute-specialized multicore accelerators, amortizing the architectural costs of

Belle II Collaboration, F. Abudinén, I. Adachi, K. Adamczyk

We report a search for lepton-flavor-violating decays $\tau^- \to \ell^- \phi$ ($\ell^- =e^-,\mu^-$) at the Belle II experiment, using a sample of electron-positron data produced at the SuperKEKB collider in 2019-2021 and corresponding to an integrated luminosity of 190 fb$^{-1}$. We use a new untagged selection for $e^+e^- \to \tau^+\tau^-$ events, where th

David Christian Ohnmacht, Wolfgang Belzig, Juan Carlos Cuevas

With the help of scanning tunneling microscopy (STM) it has become possible to address single magnetic impurities on superconducting surfaces and to investigate the peculiar properties of the in-gap states known as Yu-Shiba-Rusinov (YSR) states. However, until very recently YSR states were only investigated with conventional tunneling spectroscopy, missing t

Ziyang Luo, Can Xu, Pu Zhao, Xiubo Geng

Large Language Models (LLMs) have significantly advanced natural language processing (NLP) with their impressive language understanding and generation capabilities. However, their performance may be suboptimal for domain-specific tasks that require specialized knowledge due to limited exposure to the related data. Additionally, the lack of transparency of mo

Ahmed Ali Hassan, Ahmed Adnan Qidan, Taisir Elgorashi, Jaafar Elmirghani

Optical Wireless Communication networks (OWC) has emerged as a promising technology that enables high-speed and reliable communication bandwidth for a variety of applications. In this work, we investigated applying Random Linear Network Coding (RLNC) over NOMA-based OWC networks to improve the performance of the proposed high density indoor optical wireless

Uwe Peters, Mary Carman

Many ethical frameworks require artificial intelligence (AI) systems to be explainable. Explainable AI (XAI) models are frequently tested for their adequacy in user studies. Since different people may have different explanatory needs, it is important that participant samples in user studies are large enough to represent the target population to enable genera

Ross Anderson, Nicholas Boucher

In this paper we're going to explore the ways in which security proofs can fail, and their broader lessons for security engineering. To mention just one example, Larry Paulson proved the security of SSL/TLS using his theorem prover Isabelle in 1999, yet it's sprung multiple leaks since then, from timing attacks to Heartbleed. We will go through a number of o

Vít Škvára, Tomáš Pevný, Václav Šmídl

The area under receiver operating characteristics (AUC) is the standard measure for comparison of anomaly detectors. Its advantage is in providing a scalar number that allows a natural ordering and is independent on a threshold, which allows to postpone the choice. In this work, we question whether AUC is a good metric for anomaly detection, or if it gives a

Sukhpal Singh Gill, Rupinder Kaur

Artificial intelligence (AI) and machine learning have changed the nature of scientific inquiry in recent years. Of these, the development of virtual assistants has accelerated greatly in the past few years, with ChatGPT becoming a prominent AI language model. In this study, we examine the foundations, vision, research challenges of ChatGPT. This article inv

Arianna Vasini, Francesca Matteucci, Emanuele Spitoni, Thomas Siegert

Short-lived radionuclides, such as 26Al and 60Fe, are tracers of star formation. Therefore, their abundances can unravel the recent star formation history of the host galaxy. In view of future gamma-ray surveys, we predict the masses and fluxes of these two elements in the Large Magellanic Cloud (LMC) using new chemical evolution models. Our best model repro

Jing Niu, Kang Jiao, Peng He, Tong-Jie Zhang

Dark energy is believed to be responsible for the acceleration of the universe. In this paper, we reconstruct the dark energy scalar field potential $V(\phi)$ using the Hubble parameter $H(z)$ through Gaussian Process analysis. Our goal is to investigate dark energy using various $H(z)$ datasets and priors. We find that the selection of prior and the $H(z)$

Lukas Bonfert, Jonas Nehme

We provide a convenient formulation of the definition of Cartan graphs and Weyl groupoids introduced by Heckenberger and Schneider, and construct Cartan graphs for regular symmetrizable contragredient Lie superalgebras. For $\mathfrak{sl}(m|n)$, $\mathfrak{osp}(2m+1|2n)$ and $\mathfrak{osp}(2m|2n)$ we explicitly describe the Cartan graph in terms of partitio

Elena Shrestha, Chetan Reddy, Hanxi Wan, Yulun Zhuang

Model-based reinforcement learning (MBRL) techniques have recently yielded promising results for real-world autonomous racing using high-dimensional observations. MBRL agents, such as Dreamer, solve long-horizon tasks by building a world model and planning actions by latent imagination. This approach involves explicitly learning a model of the system dynamic

Zhen Qin, Xiaodong Han, Weixuan Sun, Bowen He

Sequence modeling has important applications in natural language processing and computer vision. Recently, the transformer-based models have shown strong performance on various sequence modeling tasks, which rely on attention to capture pairwise token relations, and position embedding to inject positional information. While showing good performance, the tran

Snezhana Kirusheva, Thomas S. Salisbury

We consider the problem of optimizing lifetime consumption under a habit formation model, both with and without an exogenous pension. Unlike much of the existing literature, we apply a power utility to the ratio of consumption to habit, rather than to their difference. The martingale/duality method becomes intractable in this setting, so we develop a greedy

Xiang Li, Rongfei Fan, Han Hu, Xiangming Li

Mobile edge computing (MEC) enables resource-limited IoT devices to complete computation-intensive or delay-sensitive task by offloading the task to adjacent edge server deployed at the base station (BS), thus becoming an important technology in 5G and beyond. Due to channel occlusion, some users may not be able to access the computation capability directly

Ambar Pal, Jeremias Sulam

Randomized smoothing is a technique for providing provable robustness guarantees against adversarial attacks while making minimal assumptions about a classifier. This method relies on taking a majority vote of any base classifier over multiple noise-perturbed inputs to obtain a smoothed classifier, and it remains the tool of choice to certify deep and comple

David Futschik, Kelvin Ritland, James Vecore, Sean Fanello

We introduce light diffusion, a novel method to improve lighting in portraits, softening harsh shadows and specular highlights while preserving overall scene illumination. Inspired by professional photographers' diffusers and scrims, our method softens lighting given only a single portrait photo. Previous portrait relighting approaches focus on changing the

Akshata Magar, Somesh K, Vikram Singh, J. J. Abraham

Single-crystal growth, magnetic properties, and magnetocaloric effect of the $S = 3/2$ kagome ferromagnet Li$_9$Cr$_3$(P$_2$O$_7$)$_3$(PO$_4$)$_2$ (trigonal, space group: $P\bar{3}c1$) are reported. Magnetization data suggest dominant ferromagnetic intra-plane coupling with a weak anisotropy and the onset of ferromagnetic ordering at $T_{\rm C} \simeq 2.6$ K

Antoine Mellet

We study a singular limit of the classical parabolic-elliptic Patlak-Keller-Segel (PKS) model for chemotaxis with non linear diffusion. The main result is the $\Gamma$ convergence of the corresponding energy functional toward the perimeter functional. Following recent work on this topic, we then prove that under an energy convergence assumption, the solution

Abdul Rashid Mussah, Maged Shoman, Mark Amo-Boateng, Yaw Adu-Gyamfi

Real-time traffic and sensor data from connected vehicles have the potential to provide insights that will lead to the immediate benefit of efficient management of the transportation infrastructure and related adjacent services. However, the growth of electric vehicles (EVs) and connected vehicles (CVs) has generated an abundance of CV data and sensor data t

Takuya Hashimoto, Javier Álvarez-Márquez, Yoshinobu Fudamoto, Luis Colina

The protoclusters in the epoch of reionization, traced by galaxies overdensity regions, are ideal laboratories for studying the process of stellar assembly and cosmic reionization. We present the spectroscopic confirmation of the core of the most distant protocluster at $z = 7.88$, A2744-z7p9OD, with the James Webb Space Telescope NIRSpec integral field unit

Takaaki Fujita

Linear-width is a well-known and highly regarded graph parameter. The concept of Single Ideal and Linear obstacle serves as an obstruction to linear-width on a connectivity sysem. In this concise paper, we present an alternative proof for the equivalence between Single ideal and linear obstacle.

Pierre Nazé

Modeling of physical systems must be based on their suitability to unavoidable physical laws. In this work, in the context of classical, isothermal, finite-time, and weak drivings, I demonstrate that physical systems, driven simultaneously at the same rate in two or more external parameters, must have the Fourier transform of their relaxation functions compo

Yan-Qi Du, Ping Wang, Li-Ming Song, Shao-Lin Xiong

Fast Radio Bursts (FRBs) are energetic phenomena that have significant implications for understanding fundamental physics and the universe. Recent observations of FRB 121102, FRB 20220912A, and FRB 20201124A by the Five-hundred-meter Aperture Spherical Telescope (FAST) showed high burst rates and distinctive energy distribution and temporal properties. In th

Xiaoqiang Wang, Bang Liu, Siliang Tang, Lingfei Wu

We present $\textbf{$\texttt{SkillQG}$}$: a question generation framework with controllable comprehension types for assessing and improving machine reading comprehension models. Existing question generation systems widely differentiate questions by $\textit{literal}$ information such as question words and answer types to generate semantically relevant questi

Qiang Fu, Dongchu Xu, Ashia Wilson

Non-convex optimization plays a key role in a growing number of machine learning applications. This motivates the identification of specialized structure that enables sharper theoretical analysis. One such identified structure is quasar-convexity, a non-convex generalization of convexity that subsumes convex functions. Existing algorithms for minimizing quas

Martin Gruber, Gordon Fraser

Non-deterministically behaving (i.e., flaky) tests hamper regression testing as they destroy trust and waste computational and human resources. Eradicating flakiness in test suites is therefore an important goal, but automated debugging tools are needed to support developers when trying to understand the causes of flakiness. A popular example for an automate

Amina Benaceur, Barbara Verfürth

This paper is a contribution in the context of variational data assimilation combined with statistical learning. The framework of data assimilation traditionally uses data collected at sensor locations in order to bring corrections to a numerical model designed using knowledge of the physical system of interest. However, some applications do not have availab

Valentin Garino, Lauri Viitasaari

We consider equidistant Riemann approximations of stochastic integrals $\int_0^T f(B^H_s)dB^H_s$ with respect to the fractional Brownian motion with $H>\frac12$, where $f$ is an arbitrary function of locally bounded variation, hence possibly possessing discontinuities. We prove that properly normalised approximation error converge in the $L^2$-topology to a

Zhi-Guo Tao, Guo-Jun Zhu, Weibin Chu, Xin-Gao Gong

Charge transfer in type-II heterostructures plays important roles in determining device performance for photovoltaic and photocatalytic applications. However, current theoretical studies of charge transfer process don't consider the effects of operating conditions such as illuminations and yield systemically larger interlayer transfer time of hot electrons i

Jieru Zhu

Motivated by the M-diagrams defined by Tymoczko, we show that these locally non-crossing $\mathfrak{sl}_3$-webs form a basis of the Specht module for the partition $(n,n,n)$. They further admit a unitriangular base change to both the polytabloid basis and the non-elliptic web basis.

Ioannis Kalogerakis

The aim of this thesis is to systematically and consistently study strongly coupled bosonic and fermionic conformal field theories using the large quantum number expansion. The idea behind it is to study sectors of conformal field theories that are characterised by large quantum numbers under global symmetries. In this limit, the conformal field theories, ev

Hank Chen

Following the general theory of categorified quantum groups developed by the author previously (arxiv:2304.07398), we construct the 2-Drinfel'd double associated to a finite group $N=G_0$. For $N=\mathbb{Z}_2$, we explicitly compute the braided 2-categories of 2-representations of certain version of this 2-Drinfel'd double, and prove that they characterize p

Aida Koch, Alix Petit

Abstract: In this article, we will analyze in detail the coding limit of an individual sequence by introducing the latest developments brought by the Set Shaping Theory. This new theory made us realize that there is a huge difference between source entropy and zero order empirical entropy. Understanding the differences between these two variables allows us t

Bartosz Kamiński, Agata Zielińska, Anna Musiał, Ching-Wen Shih

We characterized optically In0.37Ga0.63As/GaAs quantum dots and Al0.2Ga0.8As/Al0.9Ga0.1As distributed Bragg reflector based cavities. The main mechanisms of quantum dots photoluminescence quenching were identified. We measured reflectivity spectra of the cavity structure which allowed us to verify the proposed layer design and its fabrication by comparing th

André Correia, Luís Alexandre

Deploying reinforcement learning agents in the real world can be challenging due to the risks associated with learning through trial and error. We propose a task-agnostic method that leverages small sets of safe and unsafe demonstrations to improve the safety of RL agents during learning. The method compares the current trajectory of the agent with both sets

Anna Kh. Balci, Mikhail Surnachev

In this article we study convex non-autonomous variational problems with differential forms and corresponding function spaces. We introduce a general framework for constructing counterexamples to the Lavrentiev gap, which we apply to several models, including the double phase, borderline case of double phase potential, and variable exponent. The results for

Chinmoy Nath Saha, Abhishek Vaidya, A F M Anhar Uddin Bhuiyan, Lingyu Meng

This letter reports a highly scaled 90 nm gate length beta-Ga2O3 T-gate MOSFET with no current collapse and record power gain cut off frequency (fMAX). The epitaxial stack of 60 nm thin channel MOSFET was grown by Molecular Beam Epitaxy (MBE) and highly doped (n++) contact regrowth was carried out by Metal Organic Chemical Vapour Deposition (MOCVD) in the so

V. Banupriya, S. Anusuya

In the modern world, one of the most severe eye infections brought on by diabetes is known as diabetic retinopathy, which will result in retinal damage, and, thus, lead to blindness. Diabetic retinopathy can be well treated with early diagnosis. Retinal fundus images of humans are used to screen for lesions in the retina. However, detecting DR in the early s

Collin Connors, Dilip Sarkar

Blockchain technology has experienced substantial growth in recent years, yet the diversity of blockchain applications has been limited. Blockchain provides many desirable features for applications, including being append-only, immutable, tamper-evident, tamper-resistant, and fault-tolerant; however, many applications that would benefit from these features c

Bum Jun Kim, Hyeyeon Choi, Hyeonah Jang, Sang Woo Kim

Vision transformers (ViTs) that model an image as a sequence of partitioned patches have shown notable performance in diverse vision tasks. Because partitioning patches eliminates the image structure, to reflect the order of patches, ViTs utilize an explicit component called positional embedding. However, we claim that the use of positional embedding does no

Sandra Albrechtsen, Tony Huynh, Raphael W. Jacobs, Paul Knappe

We give an approximate Menger-type theorem for when a graph $G$ contains two $X-Y$ paths $P_1$ and $P_2$ such that $P_1 \cup P_2$ is an induced subgraph of $G$. More generally, we prove that there exists a function $f(d) \in O(d)$, such that for every graph $G$ and $X,Y \subseteq V(G)$, either there exist two $X-Y$ paths $P_1$ and $P_2$ such that the distanc

ChaeHun Park, Seungil Chad Lee, Daniel Rim, Jaegul Choo

Despite the recent advances in open-domain dialogue systems, building a reliable evaluation metric is still a challenging problem. Recent studies proposed learnable metrics based on classification models trained to distinguish the correct response. However, neural classifiers are known to make overly confident predictions for examples from unseen distributio

Shaozu Yuan, Aijun Dai, Zhiling Yan, Ruixue Liu

In this paper, we present a novel system (denoted as Polaca) to generate poetic Chinese landscape painting with calligraphy. Unlike previous single image-to-image painting generation, Polaca takes the classic poetry as input and outputs the artistic landscape painting image with the corresponding calligraphy. It is equipped with three different modules to co

Jan Ole von Hartz, Eugenio Chisari, Tim Welschehold, Wolfram Burgard

In policy learning for robotic manipulation, sample efficiency is of paramount importance. Thus, learning and extracting more compact representations from camera observations is a promising avenue. However, current methods often assume full observability of the scene and struggle with scale invariance. In many tasks and settings, this assumption does not hol

Gunnar S. Bali, Sara Collins, Simon Heybrock, Marius Löffler

We determine the axial, scalar and tensor isovector charges of the nucleon, sigma and cascade baryons as well as the difference between the up and down quark masses, $m_u-m_d$. We employ gauge ensembles with $N_f=2+1$ non-perturbatively improved Wilson fermions at six values of the lattice spacing in the range $a\approx (0.039 - 0.098) \,$fm, generated by th

Mannque Rho

The World-Class University/Hanyang Project launched in Korea in 2007 led to what's now called ``pseudo-conformal model" that addresses dense compact-star matter and is confronted in this short note with the presently available astrophysical observables, with focus on those from gravity waves. The predictions made nearly free of parameters by the model involv

Ciaran Bench, Ben T. Cox

Multiwavelength photoacoustic images encode information about a tissue's optical absorption distribution. This can be used to estimate its blood oxygen saturation distribution (sO2), an important physiological indicator of tissue health and pathology. However the wavelength dependence of the light fluence distribution complicates the recovery of accurate est

Hui Qin, Guowei Dai, Yuan Chen, Ting Jin

A spanning subgraph $H$ of a graph $G$ is called a $P_{\geq k}$-factor of $G$ if every component of $H$ is isomorphic to a path of order at least $k$, where $k\geq2$ is an integer. A graph $G$ is called a $(P_{\geq k},l)$-factor critical graph if $G-V'$ contains a $P_{\geq k}$-factor for any $V'\subseteq V(G)$ with $|V'|=l$. A graph $G$ is called a $(P_{\geq

Kristjan Greenewald, Brian Kingsbury, Yuancheng Yu

We study the problem of overcoming exponential sample complexity in differential entropy estimation under Gaussian convolutions. Specifically, we consider the estimation of the differential entropy $h(X+Z)$ via $n$ independently and identically distributed samples of $X$, where $X$ and $Z$ are independent $D$-dimensional random variables with $X$ sub-Gaussia

Nathan King, Haozhe Su, Mridul Aanjaneya, Steven Ruuth

Many geometry processing techniques require the solution of partial differential equations (PDEs) on manifolds embedded in $\mathbb{R}^2$ or $\mathbb{R}^3$, such as curves or surfaces. Such manifold PDEs often involve boundary conditions (e.g., Dirichlet or Neumann) prescribed at points or curves on the manifold's interior or along the geometric (exterior) b

Nikolaus Korfhage, Markus Mühling, Bernd Freisleben

We present ElasticHash, a novel approach for high-quality, efficient, and large-scale semantic image similarity search. It is based on a deep hashing model to learn hash codes for fine-grained image similarity search in natural images and a two-stage method for efficiently searching binary hash codes using Elasticsearch (ES). In the first stage, a coarse sea

Argyro Sasli, Nikolaos Karnesis, Nikolaos Stergioulas

In recent years, the field of Gravitational Wave Astronomy has flourished. With the advent of more sophisticated ground-based detectors and space-based observatories, it is anticipated that Gravitational Wave events will be detected at a much higher rate in the near future. One of the future data analysis challenges is performing robust statistical inference

J. S. Yodh, F. Giardina, S. Gokhale, L. Mahadevan

At sufficiently high concentrations, motile bacteria suspended in fluids exhibit a range of ordered and disordered collective motions. Here we explore the combined effects of confinement, periodicity and curvature induced by the active motion of E. coli bacteria in a thin spherical shell (cortex) of an oil-water-oil (O/B/O) double emulsion drop. Confocal mic

V. Venkatesha, N. S. Kavya, P. K. Sahoo

The aim of this manuscript is to study the traversable wormhole (WH) geometries in the curvature matter coupling gravity. We investigate static spherically symmetric Morris-Thorne WHs within the context of $f(R,L_m)$ gravity. To accomplish this, we examine the WH model in four different cases (i) linear $f(R,L_m)$ model, $f(R,L_m)=\alpha R+\beta L_m$ with an

Zita Abreu, Raquel Pinto, Rita Simões

Maximum distance separable convolutional codes are characterized by the property that the free distance reaches the generalized Singleton bound, which makes them optimal for error correction. However, the existing constructions of such codes are available over fields of large size. In this paper, we present the unique construction of MDS convolutional codes

Lorenzo Laneve

Black-box quantum-state preparation is a variant of quantum-state preparation where we want to construct an $n$-qubit state $|\psi_c\rangle \propto \sum_x c(x) |x\rangle$ with the amplitudes $c(x)$ given as a (quantum) oracle. This variant is particularly useful when the quantum state has a short and simple classical description. We use recent techniques, na

Pedro Figueroa-Romero, Miha Papič, Adrian Auer, Min-Hsiu Hsieh

A crucial task to obtain optimal and reliable quantum devices is to quantify their overall performance. The average fidelity of quantum gates is a particular figure of merit that can be estimated efficiently by Randomized Benchmarking (RB). However, the concept of gate-fidelity itself relies on the crucial assumption that noise behaves in a predictable, time

Jones Pontoh

Interestingly the numbers of young traders in Jakarta Stock Exchange had been increasing in recent years. Even in the middle of the global crisis caused by covid19 pandemic, in December 2021 according to KSEI, Individual investors were dominated by young investors. Data presented by KSEI showed that 60 percent of the investors listed in Indonesian Stock Exch

Gerhard Huisken, Thomas Koerber

Let $(M,g)$ be a complete, connected, non-compact Riemannian three-manifold with non-negative Ricci curvature satisfying $Ric\geq\varepsilon\,\operatorname{tr}(Ric)\,g$ for some $\varepsilon>0$. In this note, we give a new proof based on inverse mean curvature flow that $(M,g)$ is either flat or has non-Euclidean volume growth. In conjunction with results of

Yeqi Gao, Zhao Song, Xin Yang, Yufa Zhou

Large language models (LLMs), especially those based on the Transformer architecture, have had a profound impact on various aspects of daily life, such as natural language processing, content generation, research methodologies, and more. Nevertheless, a crucial concern regarding the inference results of large language models is the issue of security and priv

Aswin Govindan Sheri, Jonathan Hickman, James Wright

We observe that classical arguments of Ricci--Stein can be used to prove $L^p$ bounds for maximal functions associated to lacunary dilates of a fixed measure in the setting of homogenous groups. This recovers some recent results on averages over Kor\'anyi spheres and horizontal spherical averages of a type introduced by Nevo--Thangavelu. Moreover, the main t

Thomas A. Henzinger, Mahyar Karimi, Konstantin Kueffner, Kaushik Mallik

A machine-learned system that is fair in static decision-making tasks may have biased societal impacts in the long-run. This may happen when the system interacts with humans and feedback patterns emerge, reinforcing old biases in the system and creating new biases. While existing works try to identify and mitigate long-run biases through smart system design,

Abhishek Roy, Sudhan Majhi

Golay complementary set (GCS) plays a vital role in reducing peak-to-mean envelope power ratio (PMEPR) in orthogonal frequency division multiplexing (OFDM). A more general version of GCS is a multiple shift complementary set (MSCS), where by relaxing the condition of zero auto-correlation sum throughout all the non-zero time shifts to the integer multiples o

Alexander Kamenshchik, Polina Petriakova

We examine the Newman-Janis algorithm's application to an exact regular static solution sustained by a minimally coupled scalar field with a non-standard kinetic term. Although coordinate complexification leads to a regular Kerr-like black hole, we are facing discrepancies in Einstein's equations in a fairly small domain, for which the regularizing parameter

Zachary P. Neal

Statistical analysis of bipartite networks frequently requires randomly sampling from the set of all bipartite networks with the same degree sequence as an observed network. Trade algorithms offer an efficient way to generate samples of bipartite networks by incrementally `trading' the positions of some of their edges. However, it is difficult to know how ma

Marcin Dziubiński, Krzysztof Jahn

We study discrete two player all-pay auction with complete information. We provide full characterization of mixed strategy Nash equilibria and show that they constitute a subset of Nash equilibria of discrete General Lotto game. We show that equilibria are not unique in general but they are interchangeable. We also show that equilibrium payoffs are unique, u

Vittorio De Falco, Francesco Bajardi, Rocco D'Agostino, Micol Benetti

Different astrophysical methods can be combined to detect possible deviations from General Relativity. In this work, we consider a class of $f(R)$ gravity models selected by the existence of Noether symmetries. In this framework, it is possible to determine a set of static and spherically symmetric black hole solutions, encompassing small departures from the

Sulthana Shams, Douglas Leith

In practice, users of a Recommender System (RS) fall into a few clusters based on their preferences. In this work, we conduct a systematic study on user-cluster targeted data poisoning attacks on Matrix Factorisation (MF) based RS, where an adversary injects fake users with falsely crafted user-item feedback to promote an item to a specific user cluster. We

Zita Abreu, Julia Lieb, Joachim Rosenthal

There exists a large literature of construction of convolutional codes with maximal or near maximal free distance. Much less is known about constructions of convolutional codes having optimal or near optimal column distances. In this paper, a new construction of convolutional codes over the binary field with optimal column distances is presented.

Karel Hrbacek, Mikhail G. Katz

We survey the effective foundations for analysis with infinitesimals developed by Hrbacek and Katz in 2021, and detail some applications. Theories SPOT and SCOT are conservative over respectively ZF and ZF+ADC. The range of applications of these theories illustrates the fact that analysis with infinitesimals requires no more choice than traditional analysis.

Roshan Dhakal, Md Ridwan Hossain Talukder, Gregory J. Stein

We consider a service robot in a household environment given a sequence of high-level tasks one at a time. Most existing task planners, lacking knowledge of what they may be asked to do next, solve each task in isolation and so may unwittingly introduce side effects that make subsequent tasks more costly. In order to reduce the overall cost of completing all

Ben Fei, Weidong Yang, Liwen Liu, Tianyue Luo

Point cloud data has been extensively studied due to its compact form and flexibility in representing complex 3D structures. The ability of point cloud data to accurately capture and represent intricate 3D geometry makes it an ideal choice for a wide range of applications, including computer vision, robotics, and autonomous driving, all of which require an u

Nicole F. Bell, Peter Cox, Matthew J. Dolan, Jayden L. Newstead

An ongoing challenge in dark matter direct detection is to improve the sensitivity to light dark matter in the MeV--GeV mass range. One proposal is to dope a liquid noble-element direct detection experiment with a lighter element such as hydrogen. This has the advantage of enabling larger recoil energies compared to scattering on a heavy target, while levera