March 2023 arXiv papers — page 51

Jun Gao, Oliver Janzer, Hong Liu, Zixiang Xu

We study the Tur\'{a}n problem for highly symmetric bipartite graphs arising from geometric shapes and periodic tilings commonly found in nature. 1. The prism $C_{2\ell}^{\square}:=C_{2\ell}\square K_{2}$ is the graph consisting of two vertex disjoint $2\ell$-cycles and a matching pairing the corresponding vertices of these two cycles. We show that for every

Steve Alpern, Thomas Lidbetter

Adversarial search of a network for an immobile Hider (or target) was introduced and solved for rooted trees by Gal (1979). In this zero-sum game, a Hider picks a point to hide on the tree and a Searcher picks a unit speed trajectory starting at the root. The payoff (to the Hider) is the search time. In Gal's model (and many subsequent investigations), the S

Carlo Bellingeri, Raul Penaguiao

Discrete signatures are invariants computed from time series corresponding to the discretised version of the signature of paths. We study the algebraic varieties arising from their images, the discrete signature varieties. We introduce them and compute their dimension in many cases. From a particular subclass of these varieties, we derive a partial solution

Haiwen Diao, Ying Zhang, Wei Liu, Xiang Ruan

Exploiting fine-grained correspondence and visual-semantic alignments has shown great potential in image-text matching. Generally, recent approaches first employ a cross-modal attention unit to capture latent region-word interactions, and then integrate all the alignments to obtain the final similarity. However, most of them adopt one-time forward associatio

Denis R. Candido, Michael E. Flatté

Decoherence and relaxation of solid-state defect qutrits near a crystal surface, where they are commonly used as quantum sensors, originates from charge and magnetic field noise. A complete theory requires a formalism for decoherence and relaxation that includes all Hamiltonian terms allowed by the defect's point-group symmetry. This formalism, presented her

H. Meer, O. Gomonay, A. Wittmann, M. Kläui

Antiferromagnetic transition metal oxides are an established and widely studied materials system in the context of spin-based electronics, commonly used as passive elements in exchange bias-based memory devices. Currently, major interest has resurged due to the recent observation of long-distance spin transport, current-induced switching, and THz emission. A

Moritz Hoesch, Olena Fedchenko, Mao Wang, Christoph Schlueter

Multiple dopant configurations of Te impurities in close vicinity in silicon are investigated using photoelectron spectroscopy, photoelectron diffraction, and Bloch wave calculations. The samples are prepared by ion implantation followed by pulsed laser annealing. The dopant concentration is variable and high above the solubility limit of Te in silicon. The

Wensheng Gan, Zhenqiang Ye, Shicheng Wan, Philip S. Yu

With the rapid growth of the Internet, human daily life has become deeply bound to the Internet. To take advantage of massive amounts of data and information on the internet, the Web architecture is continuously being reinvented and upgraded. From the static informative characteristics of Web 1.0 to the dynamic interactive features of Web 2.0, scholars and e

Daoyuan Chen, Dawei Gao, Yuexiang Xie, Xuchen Pan

Federated Learning (FL) aims to train high-quality models in collaboration with distributed clients while not uploading their local data, which attracts increasing attention in both academia and industry. However, there is still a considerable gap between the flourishing FL research and real-world scenarios, mainly caused by the characteristics of heterogene

ALICE Collaboration

The measurements of the inclusive J/$\psi$ yield at midrapidity ($\left | y \right | < 0.9$) and forward rapidity (2.5 $< y <$ 4) in Pb$-$Pb collisions at $\sqrt{s_{\mathrm{NN}}}=5.02$ TeV with the ALICE detector at the LHC are reported. The inclusive J/$\psi$ production yields and nuclear modification factors, $R_{\rm AA}$, are measured as a function of the

Falk Schupp, Michael Bölting, Patrick Achenbach, Sebastian Bleser

In the PANDA experiment's hypernuclear and hyperatom setup, a positioning system for the primary production target is required, which will be located in the center of the solenoid magnet, in ultra-high vacuum, and exposed to high radiation levels. In this work, a prototype for a positioning sensor was built using a bisected light guide for infrared light and

Inga Seidler, Malte Neul, Eugen Kammerloher, Matthias Künne

Gate-layouts of spin qubit devices are commonly adapted from previous successful devices. As qubit numbers and the device complexity increase, modelling new device layouts and optimizing for yield and performance becomes necessary. Simulation tools from advanced semiconductor industry need to be adapted for smaller structure sizes and electron numbers. Here,

Ce Zheng, Xianpeng Liu, Guo-Jun Qi, Chen Chen

Transformer architectures have achieved SOTA performance on the human mesh recovery (HMR) from monocular images. However, the performance gain has come at the cost of substantial memory and computational overhead. A lightweight and efficient model to reconstruct accurate human mesh is needed for real-world applications. In this paper, we propose a pure trans

Alexandr Buryak, Danil Gubarevich

One of many manifestations of a deep relation between the topology of the moduli spaces of algebraic curves and the theory of integrable systems is a recent construction of Arsie, Lorenzoni, Rossi, and the first author associating an integrable system of evolutionary PDEs to an F-cohomological field theory (F-CohFT), which is a collection of cohomology class

Hanyao Huang, Ou Zheng, Dongdong Wang, Jiayi Yin

The ChatGPT, a lite and conversational variant of Generative Pretrained Transformer 4 (GPT-4) developed by OpenAI, is one of the milestone Large Language Models (LLMs) with billions of parameters. LLMs have stirred up much interest among researchers and practitioners in their impressive skills in natural language processing tasks, which profoundly impact var

Robert Ziegler

Standard Model extensions with light axions are well-motivated by the observed Dark Matter abundance and the Peccei-Quinn solution to the Strong CP Problem. In general such axions can have large flavor-violating couplings to SM fermions, which naturally arise in scenarios where the Peccei-Quinn symmetry also explains the hierarchical pattern of fermion masse

Rakhee Kallimani, Krishna Pai, Prasoon Raghuwanshi, Sridhar Iyer

In recent years, Artificial Intelligence (AI) and Machine learning (ML) have gained significant interest from both, industry and academia. Notably, conventional ML techniques require enormous amounts of power to meet the desired accuracy, which has limited their use mainly to high-capability devices such as network nodes. However, with many advancements in t

Dhruv Mauria Saxena, Maxim Likhachev

Real-world manipulation problems in heavy clutter require robots to reason about potential contacts with objects in the environment. We focus on pick-and-place style tasks to retrieve a target object from a shelf where some `movable' objects must be rearranged in order to solve the task. In particular, our motivation is to allow the robot to reason over and

Debayan Banerjee, Sushil Awale, Ricardo Usbeck, Chris Biemann

In this work we create a question answering dataset over the DBLP scholarly knowledge graph (KG). DBLP is an on-line reference for bibliographic information on major computer science publications that indexes over 4.4 million publications published by more than 2.2 million authors. Our dataset consists of 10,000 question answer pairs with the corresponding S

Yuxin Lin, Elena Mantovan, Deepesh Singhal

Given a family of abelian covers of $\mathbb{P}^1$ and a prime $p$ of good reduction, by considering the associated Deligne--Mostow Shimura variety, we obtain lower bounds for the Ekedahl-Oort type, and the Newton polygon, at $p$ of the curves in the family. In this paper, we investigate whether such lower bounds are sharp. In particular, we prove sharpness

ALICE Collaboration

Measurements of the production of electrons from heavy-flavour hadron decays in pp collisions at $\sqrt{s} = 13$ TeV at midrapidity with the ALICE detector are presented down to a transverse momentum ($p_{\rm T}$) of 0.2 GeV$/c$ and up to $p_{\rm T} = 35$ GeV$/c$, which is the largest momentum range probed for inclusive electron measurements in ALICE. In p$-

ALICE Collaboration

The knowledge of the material budget with a high precision is fundamental for measurements of direct photon production using the photon conversion method due to its direct impact on the total systematic uncertainty. Moreover, it influences many aspects of the charged-particle reconstruction performance. In this article, two procedures to determine data-drive

ALICE Collaboration

This letter presents the first measurement of the angle between different jet axes (denoted as ${\Delta}R$) in Pb$-$Pb collisions. The measurement is carried out in the 0$-$10% most-central events at $\sqrt{s_{\rm NN}} = 5.02$ TeV. Jets are assembled by clustering charged particles at midrapidity using the anti-$k_{\rm T}$ algorithm with resolution parameter

Giovanni Amici, Paolo Brandimarte, Francesco Messeri, Patrizia Semeraro

The goal of this paper is to investigate how the marginal and dependence structures of a variety of multivariate L\'evy models affect calibration and pricing. To this aim, we study the approaches of Luciano and Semeraro (2010) and Ballotta and Bonfiglioli (2016) to construct multivariate processes. We explore several calibration methods that can be used to f

Zexian Liu, Yan Ni, Hongwei Liu, Wumei Sun

Subspace minimization conjugate gradient (SMCG) methods have become a class of quite efficient iterative methods for unconstrained optimization and have attracted extensive attention recently. Usually, the search directions of SMCG methods are generated by minimizing approximate models with the approximation matrix $ B_k $ of the objective function at the cu

Florian Wittbold, Rebecca Bernemann, Reiko Heckel, Tobias Heindel

We introduce stochastic decision Petri nets (SDPNs), which are a form of stochastic Petri nets equipped with rewards and a control mechanism via the deactivation of controllable transitions. Such nets can be translated into Markov decision processes (MDPs), potentially leading to a combinatorial explosion in the number of states due to concurrency. Hence we

Stefan Kluth, Wolfgang Ochs, Redamy Perez Ramos

The production of a heavy quark is accompanied by gluon bremsstrahlung which is suppressed at small angles $\Theta\lesssim M_Q/E$ for mass $M_Q$ and high energy $E$ according to perturbative Quantum Chromo Dynamics (QCD) (``dead cone effect''). As particles at small angles typically have large momenta, the heavy quark mass also causes a suppression of high m

Matti Lassas, Medet Nursultanov, Lauri Oksanen, Lauri Ylinen

We consider the inverse problem to determine a smooth compact Riemannian manifold $(M,g)$ from a restriction of the source-to-solution operator, $\Lambda_{\mathcal{S,R}}$, for the wave equation on the manifold. Here, $\mathcal{S}$ and $\mathcal{R}$ are open sets on $M$, and $\Lambda_{\mathcal{S,R}}$ represents the measurements of waves produced by smooth sou

François Ledrappier, Pablo Lessa

We consider a random walk on $SL_d(\mathbb{R})$ with finite first moment and finite entropy. We show that the distributions of the unstable flag space and of the stable flag space are exact dimensional.

Idan Glassberg, Tom Hope

This short technical report demonstrates a simple technique that yields state of the art results in medical image-text matching tasks. We analyze the use of OpenAI's CLIP, a general image-text matching model, and observe that CLIP's limited textual input size has negative impact on downstream performance in the medical domain where encoding longer textual co

Cezary Migaszewski

In this work, we investigate the dynamical origin of extreme trans-Neptunian objects (ETNOs) under the action of the External Field Effect (EFE), which is a consequence of Modified Newtonian Dynamics (MOND) applied to gravity around the Sun embedded in the gravitational field of the Galaxy. We perform N-body integrations of known ETNOs treated as massless pa

J. Greiner, C. Maitra, F. Haberl, R. Willer

Type Ia supernovae are cosmic distance indicators, and the main source of iron in the Universe, but their formation paths are still debated. Several dozen supersoft X-ray sources, in which a white dwarf accretes hydrogen-rich matter from a non-degenerate donor star, have been observed and suggested as Type Ia supernovae progenitors. However, observational ev

Nitin Malapally, Viacheslav Bolnykh, Estela Suarez, Paolo Carloni

The 3D Discrete Fourier Transform (DFT) is a technique used to solve problems in disparate fields. Nowadays, the commonly adopted implementation of the 3D-DFT is derived from the Fast Fourier Transform (FFT) algorithm. However, evidence indicates that the distributed memory 3D-FFT algorithm does not scale well due to its use of all-to-all communication. Here

Chenshuang Zhang, Chaoning Zhang, Sheng Zheng, Mengchun Zhang

Generative AI has demonstrated impressive performance in various fields, among which speech synthesis is an interesting direction. With the diffusion model as the most popular generative model, numerous works have attempted two active tasks: text to speech and speech enhancement. This work conducts a survey on audio diffusion model, which is complementary to

Vojtěch Patkóš, Vladimir A. Yerokhin, Krzysztof Pachucki

The nuclear polarizability effects in hyperfine splitting of light atomic systems are not well known. The only system for which they were previously calculated is the hydrogen atom, where these effects were shown to contribute about 5\% of the total nuclear correction. One generally expects the polarizability effects to become more pronounced for composite n

Yao Chen, Shan Huang, Wensheng Gan, Gengsen Huang

The metaverse, which is at the stage of innovation and exploration, faces the dilemma of data collection and the problem of private data leakage in the process of development. This can seriously hinder the widespread deployment of the metaverse. Fortunately, federated learning (FL) is a solution to the above problems. FL is a distributed machine learning par

Jayson G. Cosme, Jim Skulte, Ludwig Mathey

We elucidate the role that the dissipation in a bosonic channel plays in the prevalence and stability of time crystals (TCs) in a periodically driven spin-boson system described by the Dicke model. Here, the bosons are represented by photons, and they mediate the infinite-range interactions between the spin systems. For strong dissipation, we study the dynam

S. Konstantinou-Rizos

Bazhanov--Stroganov (4-simplex) maps are set-theoretical solutions to the 4-simplex equation, namely the fourth member of the family of $n$-simplex equations, which are fundamental equations of mathematical physics. In this paper, we develop a method for constructing Bazhanov--Stroganov maps as extensions of tetrahedron maps which are set-theoretical solutio

Mohammad Sadegh Nasr, Amir Hajighasemi, Paul Koomey, Parisa Boodaghi Malidarreh

In this paper, we introduce a Variational Autoencoder (VAE) based training approach that can compress and decompress cancer pathology slides at a compression ratio of 1:512, which is better than the previously reported state of the art (SOTA) in the literature, while still maintaining accuracy in clinical validation tasks. The compression approach was tested

Massimo Bilancioni, Massimiliano Esposito, Emanuele Penocchio

We study a model of synthetic molecular motor - a [3]-catenane consisting of two small macrocycles mechanically interlocked with a bigger one - subjected to a time-dependent driving using stochastic thermodynamics. The model presents nontrivial features due to the two interacting small macrocycles, but is simple enough to be treated analytically in limiting

Guy Ashiri-Prossner, Yuval Benjamini

In this paper we discuss how to evaluate the differences between fitted logistic regression models across sub-populations. Our motivating example is in studying computerized diagnosis for learning disabilities, where sub-populations based on gender may or may not require separate models. In this context, significance tests for hypotheses of no difference bet

Ming-Xiao Duan, Lin Qiu, Xi-Zhe Ling, Qiang Zhao

We demonstrate that triangle singularity (TS) and box singularity (BS) mechanisms can produce unique narrow enhancements at the $\Lambda_c\bar{D}$ and $\Lambda_c\bar{D}^*$ thresholds in the invariant mass spectra of $J/\psi p$ and $J/\psi p\pi$, respectively. Taking into account that such mechanisms only depend on the initial $\Sigma_c^{(*)}\bar{D}^{(*)}$ in

Surajit Basak, Aksel Kobiałka, Andrzej Ptok

Shandite with Ni$_{3}$Pb$_{2}$S$_{2}$ chemical formula and R$\bar{3}$m symmetry, contains the kagome sublattice formed by the transition metal atoms. Recent experimental results confirmed the possibility of successfully synthesizing Pd$_{3}$Pb$_{2}Ch_{2}$ ($Ch$=S,Se) with the same structure. In this paper, we theoretically investigate the dynamical propertie

Andrew James Bruce

We examine the heap of linear connections on anchored vector bundles and Lie algebroids. Naturally, this covers the example of affine connections on a manifold. We present some new interpretations of classical results via this ternary structure of connections. Endomorphisms of linear connections are studied, and their ternary structure, in particular the end

R. M. Brown

We prove a decay estimate for an operator that arises in two-dimensional scattering problem.

Malgorzata Wasilewska, Hanna Bogucka, H. Vincent Poor

This paper considers reliable and secure Spectrum Sensing (SS) based on Federated Learning (FL) in the Cognitive Radio (CR) environment. Motivation, architectures, and algorithms of FL in SS are discussed. Security and privacy threats on these algorithms are overviewed, along with possible countermeasures to such attacks. Some illustrative examples are also

Ying Cao, Elsa Rizk, Stefan Vlaski, Ali H. Sayed

The vulnerability of machine learning models to adversarial attacks has been attracting considerable attention in recent years. Most existing studies focus on the behavior of stand-alone single-agent learners. In comparison, this work studies adversarial training over graphs, where individual agents are subjected to perturbations of varied strength levels ac

Ismail Nejjar, Qin Wang, Olga Fink

Unsupervised Domain Adaptation Regression (DAR) aims to bridge the domain gap between a labeled source dataset and an unlabelled target dataset for regression problems. Recent works mostly focus on learning a deep feature encoder by minimizing the discrepancy between source and target features. In this work, we present a different perspective for the DAR pro

Shahabedin Nabavi, Hossein Simchi, Mohsen Ebrahimi Moghaddam, Ahmad Ali Abin

Background and Objectives: Cardiovascular magnetic resonance (CMR) imaging is a powerful modality in functional and anatomical assessment for various cardiovascular diseases. Sufficient image quality is essential to achieve proper diagnosis and treatment. A large number of medical images, the variety of imaging artefacts, and the workload of imaging centres

Chaoyi Gu, Varuna De Silva

Evaluating the performance of human is a common need across many applications, such as in engineering and sports. When evaluating human performance in completing complex and interactive tasks, the most common way is to use a metric having been proved efficient for that context, or to use subjective measurement techniques. However, this can be an error prone

Mohamed Awadalla, François Bouffard

The daily operation of real-world power systems and their underlying markets relies on the timely solution of the unit commitment problem. However, given its computational complexity, several optimization-based methods have been proposed to lighten its problem formulation by removing redundant line flow constraints. These approaches often ignore the spatial

Gudmundur Stefansson, Suvrath Mahadevan, Yamila Miguel, Paul Robertson

In current theories of planet formation, close-orbiting planets as massive as Neptune are expected to be very rare around low-mass stars. We report the discovery of a Neptune-mass planet orbiting the `ultracool' star LHS 3154, which is nine times less massive than the Sun. The planet's orbital period is 3.7 days and its minimum mass is 13.2 Earth masses, giv

David Blanco-Mulero, Gokhan Alcan, Fares J. Abu-Dakka, Ville Kyrki

Pre-defined manipulation primitives are widely used for cloth manipulation. However, cloth properties such as its stiffness or density can highly impact the performance of these primitives. Although existing solutions have tackled the parameterisation of pick and place locations, the effect of factors such as the velocity or trajectory of quasi-static and dy

Pascal Michaillat

Immigration is often blamed for increasing unemployment among local workers. This sentiment is reflected in the rise of anti-immigration parties and policies in Western democracies. And in fact, numerous studies estimate that in the short run, the arrival of new workers in a labor market raises the unemployment rate of local workers. Yet, standard migration

Wasilij Barsukow, Raul Borsche

In this work we develop implicit Active Flux schemes for the scalar advection equation. At every cell interface we approximate the solution by a polynomial in time. This allows to evolve the point values using characteristics and to update the cell averages using fluxes obtained by integrating this polynomial. The resulting schemes have order of convergence

Brian Harbourne, Juan Migliore, Uwe Nagel

The notion of an unexpected curve in the plane was introduced in 2018, and was quickly generalized in several directions in a flurry of mathematical activity by many authors. In this expository paper we first describe some of the main results on unexpected hypersurfaces. Then we summarize two offshoots of this theory. First we look at sets of points in $\mat

Ran Long, Christian Rauch, Vladimir Ivan, Tin Lun Lam

This work presents a novel RGB-D-inertial dynamic SLAM method that can enable accurate localisation when the majority of the camera view is occluded by multiple dynamic objects over a long period of time. Most dynamic SLAM approaches either remove dynamic objects as outliers when they account for a minor proportion of the visual input, or detect dynamic obje

Emiland Garrabe, Martina Lamberti, Giovanni Russo

We consider the problem of designing agents able to compute optimal decisions by composing data from multiple sources to tackle tasks involving: (i) tracking a desired behavior while minimizing an agent-specific cost; (ii) satisfying safety constraints. After formulating the control problem, we show that this is convex under a suitable assumption and find th

Mathew Robertson, Antony Lewis

Gravitational lensing rotation of images is predicted to be negligible at linear order in density perturbations, but can be produced by the post-Born lens-lens coupling at second order. This rotation is somewhat enhanced for Cosmic Microwave Background (CMB) lensing due to the large source path length, but remains small and very challenging to detect directl

Martina Clairand, Ali Mozaffari, Jérôme Hardoüin, Rui Zhang

Cells are fundamental building blocks of living organisms displaying an array of shapes, morphologies, and textures that encode specific functions and physical behaviors. Elucidating the rules of this code remains a challenge. In this work, we create biomimetic structural building blocks by coating ellipsoidal droplets of a smectic liquid crystal with a prot

Yannick Klein, Gwenaelle Rousse, Françoise Damay, Florence Porcher

Barium ruthenate Ba$_{4}$Ru$_{3}$O$_{10}$, in which Ru$_{3}$O$_{12}$ trimers are connected together to form a chequered two-dimensional framework, has been synthesised and its structural, magnetic and transport properties studied between 300 K and 2 K. The paramagnetic to antiferromagnetic transition at $T_N \sim 105$ K evidenced on the susceptibility curve

Jannis Vamvas, Johannes Graën, Rico Sennrich

We present SwissBERT, a masked language model created specifically for processing Switzerland-related text. SwissBERT is a pre-trained model that we adapted to news articles written in the national languages of Switzerland -- German, French, Italian, and Romansh. We evaluate SwissBERT on natural language understanding tasks related to Switzerland and find th

Kasturi Vasudevan, Surendra Kota, Lov Kumar, Himanshu Bhusan Mishra

Achieving high bit rates is the main goal of wireless technologies like 5G and beyond. This translates to obtaining high spectral efficiencies using large number of antennas at the transmitter and receiver (single user massive multiple input multiple output or SU-MMIMO). It is possible to have a large number of antennas in the mobile handset at mm-wave frequ

Christin Schmitt, Adithya Rajan, Grischa Beneke, Aditya Kumar

We study current-induced switching of the N\'eel vector in CoO/Pt bilayers to understand the underlaying antiferromagnetic switching mechanism. Surprisingly, we find that for ultra-thin CoO/Pt bilayers electrical pulses along the same path can lead to an increase or decrease of the spin Hall magnetoresistance signal, depending on the current density of the p

Songheng Zhang, Dong Ma, Yong Wang

Data visualizations have been widely used on mobile devices like smartphones for various tasks (e.g., visualizing personal health and financial data), making it convenient for people to view such data anytime and anywhere. However, others nearby can also easily peek at the visualizations, resulting in personal data disclosure. In this paper, we propose a per

Daniel Duffy, Joselle M. McCracken, Tayler S. Hebner, Timothy J. White

Liquid crystal elastomer films that morph into cones are strikingly capable lifters. Thus motivated, we combine theory, numerics, and experiments to reexamine the load-bearing capacity of conical shells. We show that a cone squashed between frictionless surfaces buckles at a smaller load, even in scaling, than the classical Seide/Koiter result. Such buckling

Bartosz Niewelt, Marcin Jastrzębski, Stanisław Kurzyna, Jan Nowosielski

The fractional Fourier transform (FrFT), a fundamental operation in physics that corresponds to a rotation of phase space by any angle, is also an indispensable tool employed in digital signal processing for noise reduction. Processing of optical signals in their time-frequency degree of freedom bypasses the digitization step and presents an opportunity to e

Cai-Hong Wang, Jiang-Tao Yuan, Zhi-Hao Ma, Shao-Ming Fei

It is known that every (single-qudit) Clifford operator maps the full set of generalized Pauli matrices (GPMs) to itself under unitary conjugation, which is an important quantum operation and plays a crucial role in quantum computation and information. However, in many quantum information processing tasks, it is required that a specific set of GPMs be mapped

J. Michael Brick, Jill M. DeMatteis

Survey researchers are increasingly turning to multimode data collection to deal with declines in survey response rates and increasing costs. An efficient approach offers the less costly modes (e.g., web) followed with a more expensive mode for a subsample of the units (e.g., households) within each primary sampling unit (PSU). We present two alternatives to

Adam Balcerzak, Mateusz Lisaj

In this paper, we introduce a non-minimally coupled varying speed of light and varying gravitational constant cosmological toy model. Using the Eisenhart-Duval lifting method, we extend the original minisuperspace of the model and depict the evolution of the system in the presence of the potential term as a geometrical flow associated with the lifted metric.

Sayan Roy, Christian Otto, Raphaël Menu, Giovanna Morigi

We analyse the dynamics of quantum correlations between two qubits coupled to a linear chain of oscillators. The chain mediates interactions between the qubits and acts as a non-Markovian reservoir. The the model is amenable to an analytical solution when the initial state of the chain is Gaussian}. We study the dynamics of the qubits concurrence starting fr

Atsushi Takizawa

Access graphs that indicate adjacency relationships from the perspective of flow lines of rooms are extracted automatically from a large number of floor plan images of a family-oriented rental apartment complex in Osaka Prefecture, Japan, based on a recently proposed access graph extraction method with slight modifications. We define and implement a graph co

Serhad Sarica, Jianxi Luo

Innovation, typically spurred by reusing, recombining, and synthesizing existing concepts, is expected to result in an exponential growth of the concept space over time. However, our statistical analysis of TechNet, which is a comprehensive technology semantic network encompassing over four million concepts derived from patent texts, reveals a linear rather

Avi Schwarzschild, Max Cembalest, Karthik Rao, Keegan Hines

As neural networks increasingly make critical decisions in high-stakes settings, monitoring and explaining their behavior in an understandable and trustworthy manner is a necessity. One commonly used type of explainer is post hoc feature attribution, a family of methods for giving each feature in an input a score corresponding to its influence on a model's o

Fangrui Lv, Jian Liang, Shuang Li, Jinming Zhang

Domain generalization (DG) tends to alleviate the poor generalization capability of deep neural networks by learning model with multiple source domains. A classical solution to DG is domain augmentation, the common belief of which is that diversifying source domains will be conducive to the out-of-distribution generalization. However, these claims are unders

Chandan Bose, Callum Bruce, Ignazio Maria Viola

This paper investigates the effect of permeability on two-dimensional rectangular plates at incidences. The flow topology is investigated for Reynolds number ($Re$) values between 30 and 90, and the forces on the plate are discussed for $Re=30$, where the wake is found to be steady for any value of the Darcy number ($Da$) and the flow incidence ($α$). At $Re

Xiaoxiao Hu, Haoran Lei

A multiproduct seller is more informed than consumers about the value of her products to consumers. The seller posts a price list and segments the market through cheap-talk communication. We find that when both seller's and consumers' incentive-compatibility constraints are satisfied, the seller cannot benefit from personalized pricing (i.e., third-degree pr

Torsten Schlett, Christian Rathgeb, Juan Tapia, Christoph Busch

Quality assessment algorithms can be used to estimate the utility of a biometric sample for the purpose of biometric recognition. "Error versus Discard Characteristic" (EDC) plots, and "partial Area Under Curve" (pAUC) values of curves therein, are generally used by researchers to evaluate the predictive performance of such quality assessment algorithms. An

Ege Özsoy, Tobias Czempiel, Felix Holm, Chantal Pellegrini

Modern surgeries are performed in complex and dynamic settings, including ever-changing interactions between medical staff, patients, and equipment. The holistic modeling of the operating room (OR) is, therefore, a challenging but essential task, with the potential to optimize the performance of surgical teams and aid in developing new surgical technologies

Matheus Adauto, Celina de Figueiredo, Glenn Hurlbert, Diana Sasaki

Graph pebbling is a game played on graphs with pebbles on their vertices. A pebbling move removes two pebbles from one vertex and places one pebble on an adjacent vertex. The pebbling number $\pi(G)$ is the smallest $t$ so that from any initial configuration of $t$ pebbles it is possible, after a sequence of pebbling moves, to place a pebble on any given tar

Dijs de Neeling, Diederik Roest, Marcello Seri, Holger Waalkens

The recent detection of gravitational waves emanating from inspiralling black hole binaries has triggered a renewed interest in the dynamics of relativistic two-body systems. The conservative part of the latter are given by Hamiltonian systems obtained from so called post-Newtonian expansions of the general relativistic description of black hole binaries. In

Guofeng Mei, Hao Tang, Xiaoshui Huang, Weijie Wang

Deep point cloud registration methods face challenges to partial overlaps and rely on labeled data. To address these issues, we propose UDPReg, an unsupervised deep probabilistic registration framework for point clouds with partial overlaps. Specifically, we first adopt a network to learn posterior probability distributions of Gaussian mixture models (GMMs)

Igor Ernst, Anton S. Galaev

We describe Lorentzian manifolds that admit metric connections with parallel torsion having zero twistorial component and non-zero vectorial component. We also describe Lorentzian manifolds admitting metric connections with closed parallel skew-symmetric torsion.

Pablo A. Cano, Marina David

We investigate higher derivative corrections to the extremal Kerr black hole in the context of heterotic string theory with $\alpha'$ corrections and of a cubic-curvature extension of general relativity. By analyzing the near-horizon extremal geometry of these black holes, we are able to compute the Iyer-Wald entropy as well as the angular momentum via gener

Matthew Tivnan, Jacopo Teneggi, Tzu-Cheng Lee, Ruoqiao Zhang

Score-based stochastic denoising models have recently been demonstrated as powerful machine learning tools for conditional and unconditional image generation. The existing methods are based on a forward stochastic process wherein the training images are scaled to zero over time and white noise is gradually added such that the final time step is approximately

Debayan Banerjee, Pranav Ajit Nair, Ricardo Usbeck, Chris Biemann

In this work, we present an end-to-end Knowledge Graph Question Answering (KGQA) system named GETT-QA. GETT-QA uses T5, a popular text-to-text pre-trained language model. The model takes a question in natural language as input and produces a simpler form of the intended SPARQL query. In the simpler form, the model does not directly produce entity and relatio

Hantao Yao, Rui Zhang, Changsheng Xu

Prompt tuning is an effective way to adapt the pre-trained visual-language model (VLM) to the downstream task using task-related textual tokens. Representative CoOp-based work combines the learnable textual tokens with the class tokens to obtain specific textual knowledge. However, the specific textual knowledge is the worse generalization to the unseen clas

Álvaro Rubio-García, Samuel Fernández-Lorenzo, Juan José García-Ripoll, Diego Porras

An actively managed portfolio almost never beats the market in the long term. Thus, many investors often resort to passively managed portfolios whose aim is to follow a certain financial index. The task of building such passive portfolios aiming also to minimize the transaction costs is called Index Tracking (IT), where the goal is to track the index by hold

Sascha A. Keweloh

This study proposes a combination of a statistical identification approach with potentially invalid short-run zero restrictions. The estimator shrinks towards imposed restrictions and stops shrinkage when the data provide evidence against a restriction. Simulation results demonstrate how incorporating valid restrictions through the shrinkage approach enhance

Song He, Yi Li, Yun-Ze Li, Yunda Zhang

In the context of $\rm AdS_3/CFT_2$, we investigate holographic correlators of the stress tensor of a conformal field theory (CFT) on a torus in this work. To calculate the correlators of the stress tensor, we employ the Einstein-Hilbert theory of gravity and perturbatively solve Einstein's equation in the bulk. We offer an explicit prescription to develop a

Giovanna K. Conrado, Amir K. Goharshady, Harshit J. Motwani, Sergei Novozhilov

We present efficient combinatorial parameterized algorithms for several classical graph-based counting problems in computational chemistry, including (i) Kekule structures, (ii) the Hosoya index, (iii) the Merrifield-Simmons index, and (iv) Graph entropy based on matchings and independent sets. All these problems were known to be #P-complete. Building on the

Alex Keilmann, Michael Godehardt, Ali Moghiseh, Claudia Redenbach

Elongated anisotropic Gaussian filters are used for the orientation estimation of fibers. In cases where computed tomography images are noisy, roughly resolved, and of low contrast, they are the method of choice even if being efficient only in virtual 2D slices. However, minor inaccuracies in the anisotropic Gaussian filters can carry over to the orientation

Chong Bao, Yinda Zhang, Bangbang Yang, Tianxing Fan

Despite the great success in 2D editing using user-friendly tools, such as Photoshop, semantic strokes, or even text prompts, similar capabilities in 3D areas are still limited, either relying on 3D modeling skills or allowing editing within only a few categories. In this paper, we present a novel semantic-driven NeRF editing approach, which enables users to

Jaitra Chattopadhyay, Anupam Saikia

The P\'{o}lya group of an algebraic number field is a particular subgroup of the ideal class group. This article provides an overview of recent results on P\'{o}lya groups of number fields, their connection with the ring of integer-valued polynomials and touches upon some results on number fields having large P\'{o}lya groups. For the sake of completeness, w

Aviv Karnieli, Shai Tsesses, Renwen Yu, Nicholas Rivera

Cavity quantum electrodynamics (QED), wherein a quantum emitter is coupled to electromagnetic cavity modes, is a powerful platform for implementing quantum sensors, memories, and networks. However, due to the fundamental tradeoff between gate fidelity and execution time, as well as limited scalability, the use of cavity-QED for quantum computation was overta

Ioannis Eleftheriadis

We consider categories of relational structures that fully embed every category of universal algebras, and prove a partial characterisation of these in terms of an infinitary variant of the notion of nowhere density of Ne\v{s}et\v{r}il and Ossona de Mendez. More precisely, we show that the Gaifman class of an algebraically universal category contains subdivi

Jiacheng Wei, Hao Wang, Jiashi Feng, Guosheng Lin

In this paper, we investigate an open research task of generating controllable 3D textured shapes from the given textual descriptions. Previous works either require ground truth caption labeling or extensive optimization time. To resolve these issues, we present a novel framework, TAPS3D, to train a text-guided 3D shape generator with pseudo captions. Specif

Dichucheng Li, Mingjin Che, Wenwu Meng, Yulun Wu

Instrument playing technique (IPT) is a key element of musical presentation. However, most of the existing works for IPT detection only concern monophonic music signals, yet little has been done to detect IPTs in polyphonic instrumental solo pieces with overlapping IPTs or mixed IPTs. In this paper, we formulate it as a frame-level multi-label classification

Joseph P Johnson, Susmita Jana, S. Shankaranarayanan

We show that very-long-baseline-interferometry (VLBI) observations of supermassive black holes will allow us to test the fundamental principles of General Relativity (GR). GR is based on the universality of gravity and Einstein's equivalence principle (EEP). However, EEP is not a basic principle of physics but an empirical fact. Non-minimal coupling (NMC) of

Alessandro Bellina, Claudio Castellano, Paul Pineau, Giulio Iannelli

A central role in shaping the experience of users online is played by recommendation algorithms. On the one hand they help retrieving content that best suits users taste, but on the other hand they may give rise to the so called "filter bubble" effect, favoring the rise of polarization. In the present paper we study how a user-user collaborative-filtering al