July 2023 arXiv papers — page 78

Cameron Calk, Philippe Malbos, Damien Pous, Georg Struth

We introduce $\omega$-catoids as generalisations of (strict) $\omega$-categories and in particular the higher path categories generated by computads or polygraphs in higher-dimensional rewriting. We also introduce $\omega$-quantales that generalise the $\omega$-Kleene algebras recently proposed for algebraic coherence proofs in higher-dimensional rewriting.

Emma Perracchione, Fabiana Camattari, Anna Volpara, Paolo Massa

Aims: To formulate, implement, and validate a user-independent release of CLEAN for Fourier-based image reconstruction of hard X-rays flaring sources. Methods: CLEAN is an iterative deconvolution method for radio and hard X-ray solar imaging. In a specific step of its pipeline, CLEAN requires the convolution between an idealized version of the instrumental P

Paolo Piazza, Hessel Posthuma, Yanli Song, Xiang Tang

Let $G$ be a connected, linear real reductive group and let $X$ be a cocompact $G$-proper manifold without boundary. We define delocalized eta invariants associated to a $L^2$-invertible perturbed Dirac operator $D_X+A$ with $A$ a suitable smoothing perturbation. We also investigate the case in which $D_X$ is not invertible but $0$ is isolated in the $L^2$-s

Natalia Zdanowska

In spite of being one of the smallest and wealthiest countries in the European Union in terms of GDP per capita, Luxembourg is facing socio-economic challenges due to recent rapid urban transformations. This article contributes by approaching this phenomenon at the most granular and rarely analysed geographical level - the neighbourhoods of the capital, Luxe

Haoyu Zhai, Juan F. Torres, Yongling Zhao, Feng Xu

The development of thermal boundary layers and plume near a section-triangular roof under different isothermal heating conditions have been the focus of numerous numerical studies. However, flow transition in this type of flow has never been observed experimentally. Here, phase-shifting interferometry and thermistor measurements are employed to experimentall

Márton Á. Goda, Ron Beloosesky, Chen Ben David, Zeev Weiner

Premature births can lead to complications, with fetal lung immaturity being a primary concern. Currently, fetal lung maturity (FLM) requires an invasive surfactant extraction procedure between the 32nd and 39th weeks of pregnancy. Unfortunately, there is no non-invasive method for FLM assessment. This work hypothesized that fetal breathing movement (FBM) an

Dejan Vukobratović, Nikolaos Bartzoudis, Mona Ghassemian, Firooz Saghezchi

With the advent of the multimodal immersive communication system, people can interact with each other using multiple devices for sensing, communication and/or control either onsite or remotely. As a breakthrough concept, a distributed sensing, computing, communications, and control (DS3C) fabric is introduced in this paper for provisioning 6G services in mul

Yazheng Yang, Yuqi Wang, Guang Liu, Ledell Wu

Recent advancements in NLP have witnessed the groundbreaking impact of pretrained models, yielding impressive outcomes across various tasks. This study seeks to extend the power of pretraining methodologies to facilitating the prediction over tables in data science, a domain traditionally overlooked, yet inherently challenging due to the plethora of table sc

Longxing Tan, Hongying Yue

Nowadays, wind energy has drawn increasing attention as its important role in carbon neutrality and sustainable development. When wind power is integrated into the power grid, precise forecasting is necessary for the sustainability and security of the system. However, the unpredictable nature and long sequence prediction make it especially challenging. In th

Kyung Hoon Han, Seung-Hyeok Kye

In this paper, we consider all possible variants of Choi matrices of linear maps, and show that they are determined by non-degenerate bilinear forms on the domain space. We will do this in the setting of finite dimensional vector spaces. In case of matrix algebras, we characterize all variants of Choi matrices which retain the usual correspondences between $

Hyung Joo Lee, Sigrid Brell-Cokcan

Teleoperation is vital in the construction industry, allowing safe machine manipulation from a distance. However, controlling machines at a joint level requires extensive training due to their complex degrees of freedom. Task space control offers intuitive maneuvering, but precise control often requires dynamic models, posing challenges for hydraulic machine

Hai-Jun Li

It was shown that the required high quality of the Peccei-Quinn (PQ) symmetry can be a natural outcome of the multiple QCD axions model. In the axiverse, a hypothetical mass mixing between the QCD axions and axion-like particles (ALPs) can occur, which leads to an interesting phenomenon called the level crossing. In this paper, we investigate this mass mixin

Anže Pirnat, Blaž Bertalanič, Gregor Cerar, Mihael Mohorčič

Non-intrusive load monitoring (NILM) is the process of obtaining appliance-level data from a single metering point, measuring total electricity consumption of a household or a business. Appliance-level data can be directly used for demand response applications and energy management systems as well as for awareness raising and motivation for improvements in e

Daniel De Almeida Braga, Natalia Kulatova, Mohamed Sabt, Pierre-Alain Fouque

It is universally acknowledged that Wi-Fi communications are important to secure. Thus, the Wi-Fi Alliance published WPA3 in 2018 with a distinctive security feature: it leverages a Password-Authenticated Key Exchange (PAKE) protocol to protect users' passwords from offline dictionary attacks. Unfortunately, soon after its release, several attacks were repor

Alexander Pushnitski, Alexander Sobolev

We consider the class of bounded self-adjoint Hankel operators $\mathbf H$, realised as integral operators on the positive semi-axis, that commute with dilations by a fixed factor. By analogy with the spectral theory of periodic Schr\"{o}dinger operators, we develop a Floquet-Bloch decomposition for this class of Hankel operators $\mathbf H$, which represent

Márton Á. Goda, Peter H. Charlton, Joachim A. Behar

Efficient and accurate evaluation of long-term photoplethysmography (PPG) recordings is essential for both clinical assessments and consumer products. In 2021, the top opensource peak detectors were benchmarked on the Multi-Ethnic Study of Atherosclerosis (MESA) database consisting of polysomnography (PSG) recordings and continuous sleep PPG data, where the

Yu Seon Jeong, Mary Hall Reno

Neutrino experiments in a Forward Physics Facility at the Large Hadron Collider can measure neutrino and antineutrino cross sections for energies up to a few TeV. For neutrino energies below 100 GeV, the inelastic cross section evaluations have contributions from weak structure functions at low momentum transfers and low hadronic final state invariant mass.

Andrea Del Prete

Let $\mathbb{E}$ be a connected and orientable Riemannian 3-manifold with a non-singular Killing vector field whose associated one-parameter group of the isometries of $\mathbb{E}$ acts freely and properly on $\E$. Then, there exists a Killing Submersion from $\E$ onto a connected and orientable surface $M$ whose fibers are the integral curves of the Killing

Geetika Barman, B. S. Daya Sagar

We proposed a simple yet effective morphological approach to convert a sparse Digital Elevation Model (DEM) to a dense Digital Elevation Model. The conversion is similar to that of the generation of high-resolution DEM from its low-resolution DEM. The approach involves the generation of median contours to achieve the purpose. It is a sequential step of the I

Dustin Aganian, Mona Köhler, Benedict Stephan, Markus Eisenbach

As collaborative robots (cobots) continue to gain popularity in industrial manufacturing, effective human-robot collaboration becomes crucial. Cobots should be able to recognize human actions to assist with assembly tasks and act autonomously. To achieve this, skeleton-based approaches are often used due to their ability to generalize across various people a

Jianzhu Huai, Xiang Gao

The extended Kalman filter (EKF) is a common state estimation method for discrete nonlinear systems. It recursively executes the propagation step as time goes by and the update step when a set of measurements arrives. In the update step, the EKF linearizes the measurement function only once. In contrast, the iterated EKF (IEKF) refines the state in the updat

Yu-Hau Tseng, Ming-Chih Lai

In this paper, we present a discontinuity and cusp capturing physics-informed neural network (PINN) to solve Stokes equations with a piecewise-constant viscosity and singular force along an interface. We first reformulate the governing equations in each fluid domain separately and replace the singular force effect with the traction balance equation between s

Simon Hochgerner

Methods from controlled Lagrangians, double bracket dissipation and interconnection and damping assignment -- passivity based control (IDA-PBC) are used to construct nonlinear feedback controls which (asymptotically) stabilize previously unstable equilibria of Lie-Poisson Hamiltonian systems. The results are applied to find an asymptotically stabilizing cont

Hongying Guo

We investigate the gravitational Faraday effect in the Kerr-Newman-Taub-NUT space-time under the weak deflection limit. Contrary to previously stated zero net effect when the source and the observer are remote from the black hole, a non-zero Faraday rotation has been found. The rotation angle is dependent on the spin and the mass of the black hole and the ob

Alastair A. Abbott, Mehdi Mhalla, Pierre Pocreau

The standard model of quantum circuits assumes operations are applied in a fixed sequential "causal" order. In recent years, the possibility of relaxing this constraint to obtain causally indefinite computations has received significant attention. The quantum switch, for example, uses a quantum system to coherently control the order of operations. Several ad

Pavel Naumov, Anna Ovchinnikova

Prior proposes the term "egocentric" for logical systems that study properties of agents rather than properties of possible worlds. In such a setting, the paper introduces two different modalities capturing de re and de dicto knowledge and proves that these two modalities are not definable through each other.

Samyadeep Basu, Shell Xu Hu, Maziar Sanjabi, Daniela Massiceti

Image-text contrastive models like CLIP have wide applications in zero-shot classification, image-text retrieval, and transfer learning. However, they often struggle on compositional visio-linguistic tasks (e.g., attribute-binding or object-relationships) where their performance is no better than random chance. To address this, we introduce SDS-CLIP, a light

Meng Hua, Qingqing Wu, Wen Chen, Zesong Fei

The target sensing/localization performance is fundamentally limited by the line-of-sight link and severe signal attenuation over long distances. This paper considers a challenging scenario where the direct link between the base station (BS) and the target is blocked due to the surrounding blockages and leverages the intelligent reflecting surface (IRS) with

Vivek Balasaheb Sabale, Atul Kumar, Subhashish Banerjee

In this manuscript, we analyze universal quantum teleportation in the presence of memory or memory-less dynamics with applications of partial collapse measurement operators. Our results show that the combined effects of memory or non-Markovianity and weak measurements can lead to universal quantum teleportation (UQT). Our study involves noise models of physi

Mary Paterson, James Moor, Luisa Cutillo

Introduction: Cases of throat cancer are rising worldwide. With survival decreasing significantly at later stages, early detection is vital. Artificial intelligence (AI) and machine learning (ML) have the potential to detect throat cancer from patient speech, facilitating earlier diagnosis and reducing the burden on overstretched healthcare systems. However,

Gregor Schaumann

We develop a categorical approach to quivers and their modules. Naturally this leads to a notion of an action of a monoidal category on quivers. Using this, we construct for a large class of quivers rigid monoidal structures on their categories of modules. This fusion product on the quiver modules induces a graded ring structure with duality and trace on the

M. K. Volkov, A. A. Pivovarov, K. Nurlan

Branching fractions of decays $\tau \to K^0 \pi^- \eta\nu_\tau$, $\tau \to K^- \pi^0 \eta\nu_\tau$, $\tau \to K^-K^0 \eta\nu_\tau$ and $\tau \to K^- \eta \eta \nu_\tau$ are calculated in the $U(3)\times U(3)$ chiral NJL quark model. The contact, vector, axial-vector and pseudoscalar channels are considered. It is shown that the axial vector channel is domina

Angelina Agabin, J. Xavier Prochaska, Peter C. Cornillon, Christian E. Buckingham

Remote sensing observations of the Earth's surface are frequently stymied by clouds, water vapour, and aerosols in our atmosphere. These degrade or preclude the measurementof quantities critical to scientific and, hence, societal applications. In this study, we train a natural language processing (NLP) algorithm with high-fidelity ocean simulations in order

Yuan Liu, Moein Ahmadi, Johann Fuchs, Mohammad Alaee-Kerahroodi

Radar simulation is a promising way to provide data-cube with effectiveness and accuracy for AI-based approaches to radar applications. This paper develops a channel simulator to generate frequency-modulated continuous-wave (FMCW) waveform multiple inputs multiple outputs (MIMO) radar signals. In the proposed simulation framework, an open-source animation to

Chenyu Tang, Wentian Yi, Edoardo Occhipinti, Yanning Dai

A human body digital twin (DT) is a virtual representation of an individual's physiological state, created using real-time data from sensors and medical test devices, with the purpose of simulating, predicting, and optimizing health outcomes through advanced analytics and simulations. The human body DT has the potential to revolutionize healthcare and wellne

M. Imbrogno, G. L. Israel, G. A. Rodríguez Castillo, D. A. H. Buckley

During a systematic search for new X-ray pulsators in the XMM-Newton archive, we discovered a high amplitude ($PF\simeq86\%$) periodic ($P\simeq7.25\,\mathrm{s}$) modulation in the X-ray flux of 4XMM J045626.3-694723 (J0456 hereafter), a previously unclassified source in the Large Magellanic Cloud (LMC). The period of the modulation is strongly suggestive of

Hong-Yue Jiang, Meng-Ting Wang, Yu-Xiao Liu

Recently, the complexity equals any gravitational observable conjecture has been proposed in [Phys. Rev. Lett. 128, 081602 (2022)], which is an extension of the complexity equals volume proposal. These gravitational observables are referred to as generalized volumes. In this paper, we investigate the generalized volume-complexity for black holes with one or

Mama Kabir Njoya Mforifoum, Andreas Buchleitner, Gabriel Dufour

We study the Hong-Ou-Mandel interference of two identical, composite particles, each formed of two bosonic or fermionic constituents, as they scatter against a potential barrier in a one-dimensional lattice. For tightly bound composites, we show that the combination of their constituents' mutual interactions and exchange symmetry gives rise to an effective n

Maximilian Fürst, Denis Kochan, Ioachim-Gheorghe Dusa, Cosimo Gorini

Studies of the formation of Landau levels based on the Schr\"odinger equation for electrons constrained to curved surfaces have a long history. These include as prime examples surfaces with constant positive and negative curvature, the sphere [Phys. Rev. Lett. 51, 605 (1983)] and the pseudosphere [Annals of Physics 173, 185 (1987)]. Now, topological insulato

Chaoyang Zhu, Long Chen

As the most fundamental scene understanding tasks, object detection and segmentation have made tremendous progress in deep learning era. Due to the expensive manual labeling cost, the annotated categories in existing datasets are often small-scale and pre-defined, i.e., state-of-the-art fully-supervised detectors and segmentors fail to generalize beyond the

Antonis Hadjipittas, Agapi Emmanouilidou

The potential energy curves for molecular ions up to $N_2^{4+}$ are calculated in an ab initio manner using the multi configurational self-consistent field method. Specifically, we implement in an automatic way a previously used double loop optimisation scheme within the multi configurational self-consisted field method. We obtain the potential energy curves

Peter Bank, Christian Bayer, Peter K. Friz, Luca Pelizzari

In this work, we introduce a novel pricing methodology in general, possibly non-Markovian local stochastic volatility (LSV) models. We observe that by conditioning the LSV dynamics on the Brownian motion that drives the volatility, one obtains a time-inhomogeneous Markov process. Using tools from rough path theory, we describe how to precisely understand the

Ran Luo, Qing-Rui Wang, Yi-Nan Wang

In this lecture note, we give a basic introduction to the rapidly developing concepts of generalized symmetries, from the perspectives of both high energy physics and condensed matter physics. In particular, we emphasize on the (invertible) higher-form and higher-group symmetries. For the physical applications, we discuss the geometric engineering of QFTs in

Michael Amir, Dmitry Rabinovich, Alfred M. Bruckstein

This work addresses the challenge of patrolling regular grid graphs of any dimension using a single mobile agent with minimal memory and limited sensing range. We show that it is impossible to patrol some grid graphs with $0$ bits of memory, regardless of sensing range, and give an exact characterization of those grid graphs that can be patrolled with $0$ bi

Niharika Sravan, Matthew J. Graham, Michael W. Coughlin, Tomas Ahumada

Joint observations in electromagnetic and gravitational waves shed light on the physics of objects and surrounding environments with extreme gravity that are otherwise unreachable via siloed observations in each messenger. However, such detections remain challenging due to the rapid and faint nature of counterparts. Protocols for discovery and inference stil

Itay Safran, Daniel Reichman, Paul Valiant

We study the size of a neural network needed to approximate the maximum function over $d$ inputs, in the most basic setting of approximating with respect to the $L_2$ norm, for continuous distributions, for a network that uses ReLU activations. We provide new lower and upper bounds on the width required for approximation across various depths. Our results es

Liyi Bai, Changming Ke, Zhongshen Luo, Tianyuan Zhu

Two-dimensional (2D) ferroelectric semiconductors present opportunities for integrating ferroelectrics into high-density ultrathin nanoelectronics. Among the few synthesized 2D ferroelectrics, $\alpha$-In$_2$Se$_3$, known for its electrically addressable vertical polarization has attracted significant interest. However, the understanding of many fundamental

Nathaniel Josephs, Arash A. Amini, Marina Paez, Lizhen Lin

We introduce the nested stochastic block model (NSBM) to cluster a collection of networks while simultaneously detecting communities within each network. NSBM has several appealing features including the ability to work on unlabeled networks with potentially different node sets, the flexibility to model heterogeneous communities, and the means to automatical

Pranav Narayanan Venkit, Mukund Srinath, Shomir Wilson

We analyze sentiment analysis and toxicity detection models to detect the presence of explicit bias against people with disability (PWD). We employ the bias identification framework of Perturbation Sensitivity Analysis to examine conversations related to PWD on social media platforms, specifically Twitter and Reddit, in order to gain insight into how disabil

Mama Kabir Njoya Mforifoum, Andreas Buchleitner, Gabriel Dufour

We describe the Hong-Ou-Mandel interference of two identical particles evolving on a one-dimensional tight-binding lattice where a potential barrier plays the role of a beam splitter. Careful consideration of the symmetries underlying the two-particle interference effect allows us to reformulate the problem in terms of ordinary wave interference in a Michels

Suresh Guttikonda, Jan Achterhold, Haolong Li, Joschka Boedecker

In autonomous navigation settings, several quantities can be subject to variations. Terrain properties such as friction coefficients may vary over time depending on the location of the robot. Also, the dynamics of the robot may change due to, e.g., different payloads, changing the system's mass, or wear and tear, changing actuator gains or joint friction. An

Fan Feng, Sara Magliacane

In many reinforcement learning tasks, the agent has to learn to interact with many objects of different types and generalize to unseen combinations and numbers of objects. Often a task is a composition of previously learned tasks (e.g. block stacking). These are examples of compositional generalization, in which we compose object-centric representations to s

Bastien Chaudet-Dumas, Martin J. Gander

When considered as a standalone iterative solver for elliptic boundary value problems, the Dirichlet-Neumann (DN) method is known to converge geometrically for domain decompositions into strips, even for a large number of subdomains. However, whenever the domain decomposition includes cross-points, i.e.$\!$ points where more than two subdomains meet, the con

Kaname Matsue

We describe blow-up behavior for ODEs by means of dynamics at infinity with complex asymptotic behavior in autonomous systems, as well as in nonautonomous systems. Based on preceding studies, a variant of closed embeddings of phase spaces and the time-scale transformation determined by the structure of vector fields at infinity reduce our description of blow

Magnin Yann, Dirand Estelle, Maurin Guillaume, Llewellyn Philip

Carbon mitigation is one challenging issue that the world is facing. To tackle deleterious impacts of CO2, processes emerged, including chemisorption from amine based solvents, and more recently physisorption in porous solids. While CO2 capture from amine is more mature, this process is corrosive and detrimental for environment. Physisorption in Metal-Organi

Miljenko Huzak, Snježana Lubura Strunjak, Andreja Vlahek Štrok

For a fixed $T$ and $k \geq 2$, a $k$-dimensional vector stochastic differential equation $dX_t=\mu(X_t, \theta)dt+\nu(X_t)dW_t,$ is studied over a time interval $[0,T]$. Vector of drift parameters $\theta$ is unknown. The dependence in $\theta$ is in general nonlinear. We prove that the difference between approximate maximum likelihood estimator of the drif

Jiang-Chuan Yu, Yue-Hui Yao, Yong Tang, Yue-Liang Wu

Ultralight bosonic fields (ULBFs) are predicted by various theories beyond the standard model of particle physics and are viable candidates of cold dark matter. There have been increasing interests to search for the ULBFs in physical and astronomical experiments. In this paper, we investigate the sensitivity of several planned space-based gravitational-wave

Indranil Biswas, Swarnava Mukhopadhyay, Richard Wentworth

For a simple, simply connected, complex group G, we prove an explicit formula to compute the Atiyah class of parabolic determinant of cohomology line bundle on the moduli space of parabolic $G$-bundles. This generalizes an earlier result of Beilinson-Schechtman.

Yoichi Takeda

IW Per, a single-lined spectroscopic binary with a short period of 0.92d, is known to be a A-type metallic-line (Am) star showing anomalous line strengths of specific elements. Previously, Kim (1980) reported that its equivalent widths of CaII 3934, SrII 4215, and ScII 4320 lines (important key lines characterizing the Am anomaly) show cyclic variations in a

Werner Bauer, Rüdiger Brecht

We introduce a structure preserving discretization of stochastic rotating shallow water equations, stabilized with an energy conserving Casimir (i.e. potential enstrophy) dissipation. A stabilization of a stochastic scheme is usually required as, by modeling subgrid effects via stochastic processes, small scale features are injected which often lead to noise

Zhenhao Jiang, Biao Zeng, Hao Feng, Jin Liu

Large-scale online recommender system spreads all over the Internet being in charge of two basic tasks: Click-Through Rate (CTR) and Post-Click Conversion Rate (CVR) estimations. However, traditional CVR estimators suffer from well-known Sample Selection Bias and Data Sparsity issues. Entire space models were proposed to address the two issues via tracing th

Patrick Oliveira Santos

Let $X_1,..., X_n \in \mathbb{R}^d$ be independent Gaussian random vectors with independent entries and variance profile $(b_{ij})_{i \in [d],j \in [n]}$. A major question in the study of covariance estimation is to give precise control on the deviation of $\sum_{j \in [n]}X_jX_j^T-\mathbb{E} X_jX_j^T$. We show that under mild conditions, we have \begin{alig

Luigi De Rosa, Marco Inversi

This paper is concerned with the incompressible Euler equations. In Onsager's critical classes we provide explicit formulas for the Duchon-Robert measure in terms of the regularization kernel and a family of vector-valued measures $\{\mu_z\}_z$, having some H\"older regularity with respect to the direction $z\in B_1$. Then, we prove energy conservation for $

Tomas Bueno Momčilović, Matthias Buchinger, Dian Balta

In its 14 years, distributed ledger technology has attracted increasing attention, investments, enthusiasm, and user base. However, ongoing doubts about its usefulness and recent losses of trust in prominent cryptocurrencies have fueled deeply skeptical assessments. Multiple groups attempted to disentangle the technology from the associated hype and controve

Hiroshi Oike, Hiromi Taniguchi, Kazuya Miyagawa, Kazushi Kanoda

It has been more than 40 years since superconductivity was discovered in organic conductors, and the way scientists view organic superconductors has changed over time. At first, the fact that organic conductors exhibit superconductivity was a novelty in itself, and subsequently it was shown that behind the superconductivity is the physics of electron correla

Abbigail K. Elms, Pier-Emmanuel Tremblay, Boris T. Gänsicke, Andrew Swan

Two recently discovered white dwarfs, WDJ041246.84$+$754942.26 and WDJ165335.21$-$100116.33, exhibit H$\alpha$ and H$\beta$ Balmer line emission similar to stars in the emerging DAHe class, yet intriguingly have not been found to have detectable magnetic fields. These white dwarfs are assigned the spectral type DAe. We present detailed follow-up of the two k

Eriola Hoxhaj, Josef Schicho

We present an algorithm for constructing a map $\mathbb{P}^2\to\mathbb{P}^2$ with a given branching curve. The stepping stone is the ramification curve, which is obtained as the linear normalization of the branching curve.

Jinghan Sun, Dong Wei, Zhe Xu, Donghuan Lu

Chest X-ray (CXR) anatomical abnormality detection aims at localizing and characterising cardiopulmonary radiological findings in the radiographs, which can expedite clinical workflow and reduce observational oversights. Most existing methods attempted this task in either fully supervised settings which demanded costly mass per-abnormality annotations, or we

Wenyu Zhang, Qing Ding, Jian Hu, Yi Ma

Graph convolutional networks (GCN) is widely used to handle irregular data since it updates node features by using the structure information of graph. With the help of iterated GCN, high-order information can be obtained to further enhance the representation of nodes. However, how to apply GCN to structured data (such as pictures) has not been deeply studied

Kilian Pfeiffer, Martin Rapp, Ramin Khalili, Jörg Henkel

With an increasing number of smart devices like internet of things (IoT) devices deployed in the field, offloadingtraining of neural networks (NNs) to a central server becomes more and more infeasible. Recent efforts toimprove users' privacy have led to on-device learning emerging as an alternative. However, a model trainedonly on a single device, using only

Elisa Goffo, Davide Gandolfi, Jo Ann Egger, Alexander J. Mustill

GJ 367 is a bright (V $\approx$ 10.2) M1 V star that has been recently found to host a transiting ultra-short period sub-Earth on a 7.7 hr orbit. With the aim of improving the planetary mass and radius and unveiling the inner architecture of the system, we performed an intensive radial velocity follow-up campaign with the HARPS spectrograph -- collecting 371

Adam LaClair

Since the introduction of binomial edge ideals $J_{G}$ by Herzog et al. and independently Ohtani, there has been significant interest in relating algebraic invariants of the binomial edge ideal with combinatorial invariants of the underlying graph $G$. Here, we take up a question considered by Herzog and Rinaldo regarding Castelnuovo--Mumford regularity of b

Jin Chang, Jun Gao, Iman Esmaeil Zadeh, Ali W. Elshaari

At the core of quantum photonic information processing and sensing, two major building pillarsare single-photon emitters and single-photon detectors. In this review, we systematically summarize the working theory, material platform, fabrication process, and game-changing applications enabled by state-of-the-art quantum dots in nanowire emitters and supercond

Jia-Hao Cao, Feng Chen, Qi Liu, Tian-Wei Mao

Discrimination of entangled states is an important element of quantum enhanced metrology. This typically requires low-noise detection technology. Such a challenge can be circumvented by introducing nonlinear readout process. Traditionally, this is realized by reversing the very dynamics that generates the entangled state, which requires a full control over t

Max Moebius, Maximilian Enderling, Sarah T. Bachinger

Participating in the shared task "Image Retrieval for arguments", we used different pipelines for image retrieval containing Image Generation, Stance Detection, Preselection and Feature Matching. We submitted four different runs with different pipeline layout and compare them to given baseline. Our pipelines perform similarly to the baseline.

Qingguo Xia, Jianke Du, Jiashi Yang

We study the propagation of plane waves in an unbounded body of a saturated ferromagnetoelastic solid. The equations by Tiersten for small fields superposed on finite initial fields in a saturated ferromagnetoelastic material are employed, with their quasistatic magnetic field extended to dynamic electric and magnetic fields for electromagnetic waves. Disper

Damiano F. G. Fiorillo, Mauricio Bustamante

The origin of the TeV--PeV astrophysical neutrinos seen by the IceCube telescope is unknown. If they are made in proton-photon interactions in astrophysical sources, their spectrum may show bump-like features. We search for such features in the 7.5-years High-Energy Starting Events (HESE), and forecast the power of such searches using larger data samples exp

Matthias Wödlinger, Jan Kotera, Manuel Keglevic, Jan Xu

In this paper, we present ECSIC, a novel learned method for stereo image compression. Our proposed method compresses the left and right images in a joint manner by exploiting the mutual information between the images of the stereo image pair using a novel stereo cross attention (SCA) module and two stereo context modules. The SCA module performs cross-attent

Quentin Uhl, Tommaso Pavan, Malwina Molendowska, Derek K. Jones

Biophysical models of diffusion tailored to quantify gray matter microstructure are gathering increasing interest. The two-compartment Neurite EXchange Imaging ($NEXI$) model has been proposed recently to account for neurites, extra-cellular space and exchange across the cell membrane. $NEXI$ parameter estimation requires multi-shell multi-diffusion time dat

Anastasia Natsiou, Luca Longo, Sean O'Leary

Controllable timbre synthesis has been a subject of research for several decades, and deep neural networks have been the most successful in this area. Deep generative models such as Variational Autoencoders (VAEs) have the ability to generate a high-level representation of audio while providing a structured latent space. Despite their advantages, the interpr

Karsten Kruse

We study strong linearisations and the uniqueness of preduals of locally convex Hausdorff spaces of scalar-valued functions. Strong linearisations are special preduals. A locally convex Hausdorff space $\mathcal{F}(\Omega)$ of scalar-valued functions on a non-empty set $\Omega$ is said to admit a strong linearisation if there are a locally convex Hausdorff s

Shijie Ma, Fei Zhu, Zhen Cheng, Xu-Yao Zhang

Efficiency and trustworthiness are two eternal pursuits when applying deep learning in real-world applications. With regard to efficiency, dataset distillation (DD) endeavors to reduce training costs by distilling the large dataset into a tiny synthetic dataset. However, existing methods merely concentrate on in-distribution (InD) classification in a closed-

Karla L. Cortez, Nathalie T. Khalil, Julio E. Solis

In this study, we investigate optimal control problems that involve sweeping processes with a drift term and mixed inequality constraints. Our goal is to establish necessary optimality conditions for these problems. We address the challenges that arise due to the combination of sweeping processes and inequality mixed constraints in two contexts: regular and

Yun Peng, Chaozheng Wang, Wenxuan Wang, Cuiyun Gao

Python is a popular dynamic programming language, evidenced by its ranking as the second most commonly used language on GitHub. However, its dynamic type system can lead to potential type errors, leading researchers to explore automatic type inference approaches for Python programs. The rule-based type inference approaches can ensure the accuracy of predicte

Vishesh Thakur

Gender bias in artificial intelligence (AI) and natural language processing has garnered significant attention due to its potential impact on societal perceptions and biases. This research paper aims to analyze gender bias in Large Language Models (LLMs) with a focus on multiple comparisons between GPT-2 and GPT-3.5, some prominent language models, to better

Yueyue Han, Yingyan Huang, Hangcheng Dong, Fengdong Chen

Online segmentation of laser-induced damage on large-aperture optics in high-power laser facilities is challenged by complicated damage morphology, uneven illumination and stray light interference. Fully supervised semantic segmentation algorithms have achieved state-of-the-art performance, but rely on plenty of pixel-level labels, which are time-consuming a

Xinyi Ye, Weiyue Zhao, Tianqi Liu, Zihao Huang

Learning-based multi-view stereo (MVS) methods deal with predicting accurate depth maps to achieve an accurate and complete 3D representation. Despite the excellent performance, existing methods ignore the fact that a suitable depth geometry is also critical in MVS. In this paper, we demonstrate that different depth geometries have significant performance ga

Pedro H. A. Konzen, Leonardo F. Guidi, Thomas Richter

The quasi-random discrete ordinates method (QRDOM) is here proposed for the approximation of transport problems. Its central idea is to explore a quasi Monte Carlo integration within the classical source iteration technique. It preserves the main characteristics of the discrete ordinates method, but it has the advantage of providing mitigated ray effect solu

Peiyan Gu, Chuyu Zhang, Ruijie Xu, Xuming He

We tackle the problem of novel class discovery, which aims to learn novel classes without supervision based on labeled data from known classes. A key challenge lies in transferring the knowledge in the known-class data to the learning of novel classes. Previous methods mainly focus on building a shared representation space for knowledge transfer and often ig

Benjamin Lee, Michael Sedlmair, Dieter Schmalstieg

Situated visualization has become an increasingly popular research area in the visualization community, fueled by advancements in augmented reality (AR) technology and immersive analytics. Visualizing data in spatial proximity to their physical referents affords new design opportunities and considerations not present in traditional visualization, which resea

Monika Dalal, Sucheta Dutt, Ranjeet Sehmi

In this paper, necessary and sufficient conditions for the reversibility of a cyclic code of arbitrary length over a finite commutative chain ring have been derived. MDS reversible cyclic codes having length p^s over a finite chain ring with nilpotency index 2 have been characterized and a few examples of MDS reversible cyclic codes have been presented. Furt

Zewei Lin, Yanqing Shen, Sanping Zhou, Shitao Chen

In this paper, we propose a novel and effective Multi-Level Fusion network, named as MLF-DET, for high-performance cross-modal 3D object DETection, which integrates both the feature-level fusion and decision-level fusion to fully utilize the information in the image. For the feature-level fusion, we present the Multi-scale Voxel Image fusion (MVI) module, wh

B. Vollmer, M. Soida, R. Beck, J. D. P. Kenney

The relation between the resolved star formation rate per unit area and the non-thermal radio continuum emission is studied in 21 Virgo cluster galaxies and the two nearby spiral galaxies, NGC6946 and M51. For the interpretation and understanding of our results we used a 3D model where star formation, 2D cosmic ray (CR) propagation, and the physics of synchr

Shaoxu Li

We propose a method for synthesizing photo-realistic digital avatars from only one portrait as the reference. Given a portrait, our method synthesizes a coarse talking head video using driving keypoints features. And with the coarse video, our method synthesizes a coarse talking head avatar with a deforming neural radiance field. With rendered images of the

Jia Hui, Yuan-Hua Ni

This paper addresses a risk-constrained decentralized stochastic linear-quadratic optimal control problem with one remote controller and one local controller, where the risk constraint is posed on the cumulative state weighted variance in order to reduce the oscillation of system trajectory. In this model, local controller can only partially observe the syst

M. S. Srinath

We formulate a problem called \emph{Generalized Root Extraction} in finite Abelian groups that have more than one generator. We then study this problem for the specific case of the torsion subgroups of elliptic curves. We give a necessary and sufficient condition for the existence of a solution. We also present an algorithm to find a solution. Our algorithm

Joberto S. B. Martins, Tereza C. Carvalho, Rodrigo Moreira, Cristiano Both

Network Slicing (NS) is an essential technique extensively used in 5G networks computing strategies, mobile edge computing, mobile cloud computing, and verticals like the Internet of Vehicles and industrial IoT, among others. NS is foreseen as one of the leading enablers for 6G futuristic and highly demanding applications since it allows the optimization and

Alexander Lauer

Model-driven software engineering is a suitable method for dealing with the ever-increasing complexity of software development processes. Graphs and graph transformations have proven useful for representing such models and changes to them. These models must satisfy certain sets of constraints. An example are the multiplicities of a class structure. During th

Wenkang Xu, An Liu, Bingpeng Zhou, Minjian Zhao

For many practical applications in wireless communications, we need to recover a structured sparse signal from a linear observation model with dynamic grid parameters in the sensing matrix. Conventional expectation maximization (EM)-based compressed sensing (CS) methods, such as turbo compressed sensing (Turbo-CS) and turbo variational Bayesian inference (Tu

Yan Cui, Zhou Zhou

Accurate curve forecasting is of vital importance for policy planning, decision making and resource allocation in many engineering and industrial applications. In this paper we establish a theoretical foundation for the optimal short-term linear prediction of non-stationary functional or curve time series with smoothly time-varying data generating mechanisms