April 2023 arXiv papers — page 85

Leonardo Oliveira, Jeppe Ormstrup, Marta Majkut, Maja Makarovic

While BiFeO3-based solid solutions show great promise for applications in energy conversion and storage, realizing this promise necessitates understanding the structure-property relationship in particular pertaining to the relaxor-like characteristics often exhibited by solid solutions with polar-to-non-polar morphotropic phase boundaries. To this end, we in

Yuta Yagi, Ryohei Konno, Tasuku Hayashi, Keita Tanaka

A 57Fe nucleus in the solar core could emit a 14.4-keV monochromatic axion through the M1 transition if a hypothetical elementary particle, axion, exists to solve the strong CP problem. Transition edge sensor (TES) X-ray microcalorimeters can detect such axions very efficiently if they are again converted into photons by a 57Fe absorber. We have designed and

Renato Luis Garrido Cavalcante, Lorenzo Miretti, Slawomir Stanczak

We establish necessary and sufficient conditions for a network configuration to provide utilities that are both fair and efficient in a well-defined sense. To cover as many applications as possible with a unified framework, we consider utilities defined in an axiomatic way, and the constraints imposed on the feasible network configurations are expressed with

Clàudia Soriano-Guerrero, Daniele Viganò, Rosalba Perna, Taner Akgün

While magnetism in exoplanets remains largely unknown, Hot Jupiters have been considered as natural candidates to harbour intense magnetic fields, both due to their large masses and their high energy budgets coming from irradiation as a consequence of their vicinity to their host stars. In this work we perform MHD simulations of a narrow day-side atmospheric

Junyang Wu, Tianyi Li, Lu Chen, Yunjun Gao

Entity alignment (EA) aims to find equivalent entities in different knowledge graphs (KGs). State-of-the-art EA approaches generally use Graph Neural Networks (GNNs) to encode entities. However, most of them train the models and evaluate the results in a fullbatch fashion, which prohibits EA from being scalable on largescale datasets. To enhance the usabilit

Sarad Venugopalan, Heiko Aydt

Smart cities are data driven and collect data from a variety of sources. Certain types of data such as building data is under-represented and remains harder to find despite its value. Our goal is to incentivise the stakeholders to make building data easier to avail by turning it into an asset. We use tokenized building data assets on a blockchain to improve

Antonio Ocello

The focus of this article is studying an optimal control problem for branching diffusion processes. Initially, we introduce the problem in its strong formulation and expand it to include linearly growing drifts. Then, we present a relaxed formulation that provides a suitable characterization based on martingale measures. Considering weak controls, we prove t

Hang Yin, Zihao Wang, Yangqiu Song

Reasoning on knowledge graphs is a challenging task because it utilizes observed information to predict the missing one. Particularly, answering complex queries based on first-order logic is one of the crucial tasks to verify learning to reason abilities for generalization and composition. Recently, the prevailing method is query embedding which learns the e

Fuyuki Kitagawa, Ryo Nishimaki, Takashi Yamakawa

We present a general compiler to add the publicly verifiable deletion property for various cryptographic primitives including public key encryption, attribute-based encryption, and quantum fully homomorphic encryption. Our compiler only uses one-way functions, or more generally hard quantum planted problems for NP, which are implied by one-way functions. It

Hao Wen, Hongming Wang, Jiaxuan Liu, Yuanchun Li

This paper introduces DroidBot-GPT, a tool that utilizes GPT-like large language models (LLMs) to automate the interactions with Android mobile applications. Given a natural language description of a desired task, DroidBot-GPT can automatically generate and execute actions that navigate the app to complete the task. It works by translating the app GUI state

Minchul Kim, Feng Liu, Anil Jain, Xiaoming Liu

Generating synthetic datasets for training face recognition models is challenging because dataset generation entails more than creating high fidelity images. It involves generating multiple images of same subjects under different factors (\textit{e.g.}, variations in pose, illumination, expression, aging and occlusion) which follows the real image conditiona

Sara Casao, Andrés Otero, Álvaro Serra-Gómez, Ana C. Murillo

Robotic applications involving people often require advanced perception systems to better understand complex real-world scenarios. To address this challenge, photo-realistic and physics simulators are gaining popularity as a means of generating accurate data labeling and designing scenarios for evaluating generalization capabilities, e.g., lighting changes,

Reihaneh Mirjalili, Michael Krawez, Wolfram Burgard

Visual place recognition is essential for vision-based robot localization and SLAM. Despite the tremendous progress made in recent years, place recognition in changing environments remains challenging. A promising approach to cope with appearance variations is to leverage high-level semantic features like objects or place categories. In this paper, we propos

Tianyu Han, Lisa C. Adams, Jens-Michalis Papaioannou, Paul Grundmann

As large language models (LLMs) like OpenAI's GPT series continue to make strides, we witness the emergence of artificial intelligence applications in an ever-expanding range of fields. In medicine, these LLMs hold considerable promise for improving medical workflows, diagnostics, patient care, and education. Yet, there is an urgent need for open-source mode

Tianyuan Zhu, Shiqing Deng, Shi Liu

Ferroelectric memories experienced a revival in the last decade due to the discovery of ferroelectricity in HfO$_2$-based nanometer-thick thin films. These films exhibit exceptional silicon compatibility, overcoming the scaling and integration obstacles that impeded perovskite ferroelectrics' use in high-density integrated circuits. The exact phase responsib

Yixuan Li, Bolin Chen, Baoliang Chen, Meng Wang

Recent years have witnessed an exponential increase in the demand for face video compression, and the success of artificial intelligence has expanded the boundaries beyond traditional hybrid video coding. Generative coding approaches have been identified as promising alternatives with reasonable perceptual rate-distortion trade-offs, leveraging the statistic

Jean-Marie Malherbe

H$\alpha$ heliographs are imaging instruments designed to produce monochromatic images of the solar chromosphere at fast cadence (60 s or less). They are designed to monitor efficiently dynamic phenomena of solar activity, such as flares or material ejections. Meudon and Haute Provence observatories started systematic observations in the frame of the Interna

Lukas Seitner, Johannes Popp, Ina Heckelmann, Réka-Eszter Vass

Ring quantum cascade lasers have recently gained considerable attention, showing ultrastable frequency comb and soliton operation, thus opening a way to integrated spectrometers in the midinfrared and terahertz fingerprint regions. Thanks to a self-consistent Maxwell-Bloch model, we demonstrate, in excellent agreement with the experimental data, that a small

Ciro Ciliberto

Let $\G(k,r)$ be the Grassmannian of $k$--subspaces in $\Proj^r$ embedded in $\Proj^{N(k,r)}$, with $N(k,r)={{r+1}\choose {k+1}}-1$, via the Pl\"ucker embedding. In this paper, extending some classical results by Gallarati (see \cite {Gal1,Gal2}), we give a sharp upper bound for the number of independent sections of $H^0(\G(k,r), \O_{\G(k,r)}(m))$ vanishing

Zhi-Yong Zhou, Chun-Yong Li, Zhiguang Xiao

By simultaneously analyzing the cross section data of $e^+e^-\rightarrow D\bar D, D\bar D^*, D^*\bar D^*, D\bar D\pi$ in a coupled-channel scheme with unitarity, we found that, in contrast to the conventional wisdom, the pole of $\psi(2^3D_1)$ might be located at about $\sqrt{s}=4222-32i\mathrm{MeV}$. This observation implies a possibility that the two reson

Jaime Spencer, C. Stella Qian, Michaela Trescakova, Chris Russell

This paper discusses the results for the second edition of the Monocular Depth Estimation Challenge (MDEC). This edition was open to methods using any form of supervision, including fully-supervised, self-supervised, multi-task or proxy depth. The challenge was based around the SYNS-Patches dataset, which features a wide diversity of environments with high-q

Gary Detlefs, Wolfdieter Lang

The standard formula for the multi-section of the general linear three-term recurrence relation is simplified in terms of Chebyshev S-polynomials.

M Atemkeng, S Perkins, E Seck, S Makhathini

This work proposes to reduce visibility data volume using a baseline-dependent lossy compression technique that preserves smearing at the edges of the field-of-view. We exploit the relation of the rank of a matrix and the fact that a low-rank approximation can describe the raw visibility data as a sum of basic components where each basic component correspond

Ruth A. Crothers, Nicholas H. P. Orr, Berend van der Meer, Roel P. A. Dullens

We optimize and characterize the preparation of 3-trimethoxysilyl propylmethacrylate (TPM) colloidal suspensions for three-dimensional confocal microscopy. We revisit a simple synthesis of TPM microspheres by nucleation of droplets from pre-hydrolyzed TPM oil in a 'zero-flow' regime, and demonstrate how precise and reproducible control of particle size may b

Maxime Haddouche, Benjamin Guedj

PAC-Bayes learning is an established framework to both assess the generalisation ability of learning algorithms, and design new learning algorithm by exploiting generalisation bounds as training objectives. Most of the exisiting bounds involve a \emph{Kullback-Leibler} (KL) divergence, which fails to capture the geometric properties of the loss function whic

Mena Nagiub, Thorsten Beuth, Ganesh Sistu, Heinrich Gotzig

Indirect Time of Flight LiDARs can indirectly calculate the scene's depth from the phase shift angle between transmitted and received laser signals with amplitudes modulated at a predefined frequency. Unfortunately, this method generates ambiguity in calculated depth when the phase shift angle value exceeds $2\pi$. Current state-of-the-art methods use raw sa

Nicola Fonzi, Steven L. Brunton, Urban Fasel

Aeroelasticity in the transonic regime is challenging because of the strongly nonlinear phenomena involved in the formation of shock waves and flow separation. In this work, we introduce a computationally efficient framework for accurate transonic aeroelastic analysis. We use dynamic mode decomposition with control (DMDc) to extract surrogate models from hig

N Mont-Geli, A Tarifeño-Saldivia, L M Fraile, S Viñals

miniBELEN is a modular and transportable neutron moderated counter with a nearly flat neutron detection efficiency up to 10 MeV. Modularity implies that the moderator can be reassembled in different ways in order to obtain different types of response. The detector has been developed in the context of the Measurement of Alpha Neutron Yields (MANY) collaborati

Benoit Oriol, Alexandre Miot

This work addresses large dimensional covariance matrix estimation with unknown mean. The empirical covariance estimator fails when dimension and number of samples are proportional and tend to infinity, settings known as Kolmogorov asymptotics. When the mean is known, Ledoit and Wolf (2004) proposed a linear shrinkage estimator and proved its convergence und

Armen Edigarian

In \cite{G-Z} G.~Ghosh and W. Zwonek introduced a new class of domains $\bL_n$, $n\ge1$, which are 2-proper holomorphic images of the Cartan domains of type four. This family contains biholomorphic images of the symmetrized bidisc and the tetrablock. It is well-known, that symmetrized bidisc and tetrablock are Lempert type domains. In our paper we show that

Wenbin Wu, Zeping Shi, Mykhaylo Ozerov, Yuhan Du

Arising from the extreme/saddle point in electronic bands, Van Hove singularity (VHS) manifests divergent density of states (DOS) and induces various new states of matter such as unconventional superconductivity. VHS is believed to exist in one and two dimensions, but rarely found in three dimension (3D). Here, we report the discovery of 3D VHS in a topologi

Yifang Qin, Wei Ju, Hongjun Wu, Xiao Luo

Sequential recommendation aims at understanding user preference by capturing successive behavior correlations, which are usually represented as the item purchasing sequences based on their past interactions. Existing efforts generally predict the next item via modeling the sequential patterns. Despite effectiveness, there exist two natural deficiencies: (i)

Yifang Qin, Hongjun Wu, Wei Ju, Xiao Luo

Next Point-of-Interest (POI) recommendation is a critical task in location-based services that aim to provide personalized suggestions for the user's next destination. Previous works on POI recommendation have laid focused on modeling the user's spatial preference. However, existing works that leverage spatial information are only based on the aggregation of

Reginald Christian Bernardo, Kin-Wang Ng

Incredible progress on the theoretical uncertainty of the spatial correlations of the stochastic gravitational wave (GW) background were recently made. However, it remains to realize the impact of this theoretical uncertainty on PTA cross correlations analysis. This paper pushes forward in this direction, as a proof--of--principle: showing the potential role

Yuhui Wu, Chen Pan, Guoqing Wang, Yang Yang

Low-light image enhancement (LLIE) investigates how to improve illumination and produce normal-light images. The majority of existing methods improve low-light images via a global and uniform manner, without taking into account the semantic information of different regions. Without semantic priors, a network may easily deviate from a region's original color.

Roger Dufresne, Giulio Del Zanna, Helen Mason

The use of the coronal approximation to model line emission from the solar transition region has led to discrepancies with observations over many years, particularly for Li- and Na-like ions. Studies have shown that a number of atomic processes are required to improve the modelling for this region, including the effects of high densities, solar radiation and

Stefano Ferraro, Toon Van de Maele, Tim Verbelen, Bart Dhoedt

Humans perceive and interact with hundreds of objects every day. In doing so, they need to employ mental models of these objects and often exploit symmetries in the object's shape and appearance in order to learn generalizable and transferable skills. Active inference is a first principles approach to understanding and modeling sentient agents. It states tha

Anh V. Vu, Alice Hutchings, Ross Anderson

Legislators and policymakers worldwide are debating options for suppressing illegal, harmful and undesirable material online. Drawing on several quantitative data sources, we show that deplatforming an active community to suppress online hate and harassment, even with a substantial concerted effort involving several tech firms, can be hard. Our case study is

Sijing Liu, Qilong Ying, Shuangchi He, Xin Yang

Ultrasound is the primary modality to examine fetal growth during pregnancy, while the image quality could be affected by various factors. Quality assessment is essential for controlling the quality of ultrasound images to guarantee both the perceptual and diagnostic values. Existing automated approaches often require heavy structural annotations and the pre

Matthias Kreuzer, Alexander Schmidt, Walter Kellermann

{In this paper, we address the challenging problem of detecting bearing faults from vibration signals. For this, several time- and frequency-domain features have been proposed already in the past. However, these features are usually evaluated on data originating from relatively simple scenarios and a significant performance loss can be observed if more reali

Thomas Walcher

The "proton radius puzzle" is the 7-standard-deviations difference of the charge radius of the proton as determined from the Lamb shift in electronic hydrogen and elastic electron scattering off the proton on the one side and the high precision determination from the Lamb shift in muonic hydrogen on the other side. So far the explanation of this difference h

Jacek Wesołowski, Robert Wieczorkowski, Wojciech Wójciak

The optimum sample allocation in stratified sampling is one of the basic issues of survey methodology. It is a procedure of dividing the overall sample size into strata sample sizes in such a way that for given sampling designs in strata the variance of the stratified $\pi$ estimator of the population total (or mean) for a given study variable assumes its mi

J. Alfredo Cruz-Carlon

Recently it has been shown that four constant memory, deterministic agents are able to discover the integer lattice if only local, constant-size communication is allowed. Moreover, if the agents' choices are determined with the help of a fair coin, it has been shown that three are necessary and sufficient to discover the integer lattice. In this paper, we sh

Carlo Cossu

The influence of stable and unstable stratification on the amplification of coherent structures in turbulent channel flows is investigated by computing the linear response to stochastic forcing. The responses to momentum and thermal forcing are considered separately. Consistently with results of previous direct numerical simulations, the influence of the mea

Berkcan Ustun, Ahmet Kagan Kaya, Ezgi Cakir Ayerden, Fazil Altinel

The exploitation of visible spectrum datasets has led deep networks to show remarkable success. However, real-world tasks include low-lighting conditions which arise performance bottlenecks for models trained on large-scale RGB image datasets. Thermal IR cameras are more robust against such conditions. Therefore, the usage of thermal imagery in real-world ap

Fuhu Che, Qasim Zeeshan Ahmed, Fahd Ahmed Khan, Faheem A. Khan

In this paper, we propose a novel Fine-Tuned attribute Weighted Na\"ive Bayes (FT-WNB) classifier to identify the Line-of-Sight (LoS) and Non-Line-of-Sight (NLoS) for UltraWide Bandwidth (UWB) signals in an Indoor Positioning System (IPS). The FT-WNB classifier assigns each signal feature a specific weight and fine-tunes its probabilities to address the mism

Andrea Esposito, Miriana Calvano, Antonio Curci, Giuseppe Desolda

In recent years, Artificial Intelligence has become more and more relevant in our society. Creating AI systems is almost always the prerogative of IT and AI experts. However, users may need to create intelligent solutions tailored to their specific needs. In this way, AI systems can be enhanced if new approaches are devised to allow non-technical users to be

Huizhong Guo, Jinfeng Li, Jingyi Wang, Xiangyu Liu

Deep learning-based recommender systems (DRSs) are increasingly and widely deployed in the industry, which brings significant convenience to people's daily life in different ways. However, recommender systems are also shown to suffer from multiple issues,e.g., the echo chamber and the Matthew effect, of which the notation of "fairness" plays a core role.Whil

Ashesh Chattopadhyay, Y. Qiang Sun, Pedram Hassanzadeh

Long-term stability and physical consistency are critical properties for AI-based weather models if they are going to be used for subseasonal-to-seasonal forecasts or beyond, e.g., climate change projection. However, current AI-based weather models can only provide short-term forecasts accurately since they become unstable or physically inconsistent when tim

Fernando Abellán, Walker H. Stern

In this work, we study the notion of cofinal functor of $\infty$-bicategories with respect to the theory of partially lax colimits. The main result of this paper is a characterization of cofinal functors of $\infty$-bicategories via generalizations of the conditions of Quillen's Theorem A. As a key ingredient for the proof of our main theorem we produce for

Gustavo Deco, Christopher Lynn, Yonatan Sanz Perl, Morten L. Kringelbach

The brain is a non-equilibrium system whose dynamics change in different brain states, such as wakefulness and deep sleep. Thermodynamics provides the tools for revealing these non-equilibrium dynamics. We used violations of the fluctuation-dissipation theorem to describe the hierarchy of non-equilibrium dynamics associated with different brain states. Toget

Busra Demir, Hashem Mohammad, M. P. Anantram, Ersin Emre Oren

DNAs charge transfer and self-assembly characteristics have made it a hallmark of molecular electronics for the past two decades. A fast and efficient charge transfer mechanism with programmable properties using DNA nanostructures is required for DNA-based nanoelectronics applications and devices. The ability to integrate DNA with inorganic substrates become

Jiaqi Wang, Shuzhen Yang

This paper introduces a new recursive stochastic optimal control problem driven by a forward-backward stochastic differential equations (FBSDEs), where the ter?minal time varies according to the constraints of the state of the forward equation. This new optimal control problem can be used to describe the investment portfolio problems with the varying investm

Oisin Fitzgerald, Oscar Perez-Concha, Blanca Gallego-Luxan, Alejandro Metke-Jimenez

Irregularly measured time series are common in many of the applied settings in which time series modelling is a key statistical tool, including medicine. This provides challenges in model choice, often necessitating imputation or similar strategies. Continuous time autoregressive recurrent neural networks (CTRNNs) are a deep learning model that account for i

Roos Leenen, Dai Aoki, Georg Knebel, Alexandre Pourret

Lifshitz transitions are being increasingly recognised as significant in a wide variety of strongly correlated and topological materials, and understanding the origin and influence of Lifshitz transitions is leading to deeper understanding of key aspects of magnetic, transport or quantum critical behavior. In the ferromagnetic superconductor UCoGe, a magneti

Matthias Kreuzer, David Schmidt, Simon Wokusch, Walter Kellermann

In this paper, we address the challenging problem of detecting bearing faults in railway vehicles by analyzing acoustic signals recorded during regular operation. For this, we introduce Mel Frequency Cepstral Coefficients (MFCCs) as features, which form the input to a simple Multi-Layer Perceptron classifier. The proposed method is evaluated with real-world

Meng Zhang, Andrea Ferrara, Bin Yue

ALMA observations have detected extended ($\simeq 10$ kpc) [C II] halos around high-redshift ($z \gtrsim 5$) star-forming galaxies. If such extended structures are common, they may have an impact on the line intensity mapping (LIM) signal. We compute the LIM power spectrum including both the central galaxy and the [C II] halo, and study the detectability of

Du Xinkai, Han Quanjie, Sun Yalin, Lv Chao

Multi-label text classification involves extracting all relevant labels from a sentence. Given the unordered nature of these labels, we propose approaching the problem as a set prediction task. To address the correlation between labels, we leverage Graph Convolutional Networks and construct an adjacency matrix based on the statistical relations between label

Jan Głowacki

The quantum reference frames program is based on the idea that reference frames should be treated as quantum physical systems. In this work, we combine these insights with the emphasis on operationality, understood as refraining from introducing into the framework objects not directly related to in principle verifiable probabilities of measurement outcomes,

Richard Blender

A dynamic equation for a large scale convective event in the tropical atmosphere similar to the Madden--Julian Oscillation (MJO) is suggested based on the meridional vorticity equation with buoyancy parametrized by Convective Available Potential Energy (CAPE). The propagation is determined by the nonlinear Burgers equation with a stationary solution describi

Jann Michael Weinand, Ganga Vandenberg, Stanley Risch, Johannes Behrens

Lithium is a critical material for the energy transition, but conventional procurement methods have significant environmental impacts. In this study, we utilize regional energy system optimizations to investigate the techno-economic potential of the low-carbon alternative of direct lithium extraction in deep geothermal plants. We show that geothermal plants

Lei Yu, Xinpeng Li, Youwei Li, Ting Jiang

Efficient deep learning-based approaches have achieved remarkable performance in single image super-resolution. However, recent studies on efficient super-resolution have mainly focused on reducing the number of parameters and floating-point operations through various network designs. Although these methods can decrease the number of parameters and floating-

Patrick Hemmer, Lukas Thede, Michael Vössing, Johannes Jakubik

Recent research suggests that combining AI models with a human expert can exceed the performance of either alone. The combination of their capabilities is often realized by learning to defer algorithms that enable the AI to learn to decide whether to make a prediction for a particular instance or defer it to the human expert. However, to accurately learn whi

Ronen Taub, Tanya Wasserman, Yonatan Savir

Machine learning, and representation learning in particular, has the potential to facilitate drug discovery by screening billions of compounds. For example, a successful approach is representing the molecules as a graph and utilizing graph neural networks (GNN). Yet, these approaches still require experimental measurements of thousands of compounds to constr

Jungsoo Kang

The original Arnold chord conjecture states that every closed Legendrian submanifold of the standard contact sphere $S^{2n-1}$ admits a Reeb chord with distinct endpoints with respect to any contact form. In this paper, we prove this conjecture for contact forms induced by strictly convex embeddings into $\mathbb{R}^{2n}$ under the assumption that minimal pe

Subrahmanyam Bandaru, Agnieszka M. Jastrzębska, Magdalena Birowska

Thermoelectricity is a next-generation solution for efficient waste heat management. Although various thermoelectric materials exist, there is still a lot of scope for advancement, especially in room temperature applications. Recently, two-dimensional (2D) materials, including MXenes, showed promise as thermoelectric materials. On the other hand, MXenes gene

Zhaoliang Chen, Zhihao Wu, Zhenghong Lin, Shiping Wang

Graph Convolutional Network (GCN) with the powerful capacity to explore graph-structural data has gained noticeable success in recent years. Nonetheless, most of the existing GCN-based models suffer from the notorious over-smoothing issue, owing to which shallow networks are extensively adopted. This may be problematic for complex graph datasets because a de

Xiaodan Hu, Yan Zhang, Hideaki Uchiyama, Naoya Isoyama

We present a smart sunglasses system engineered to assist individuals experiencing photophobia, particularly those highly sensitive to light intensity. The system integrates a high dynamic range (HDR) camera and a liquid crystal spatial light modulator (SLM) to dynamically regulate light, adapting to environmental scenes by modifying pixel transmittance thro

Martin Bordemann, Andrea Rivezzi, Thomas Weigel

In this note we give an introduction to Drinfel'd's associator coming from the Knizhnik-Zamolodchikov connections and a self-contained proof of the hexagon and pentagon equations by means of minimal amounts of analysis or differential geometry: we rather use limits of concrete parallel transports.

Daniel Neuen

Two graphs are homomorphism indistinguishable over a graph class $\mathcal{F}$, denoted by $G \equiv_{\mathcal{F}} H$, if $\operatorname{hom}(F,G) = \operatorname{hom}(F,H)$ for all $F \in \mathcal{F}$ where $\operatorname{hom}(F,G)$ denotes the number of homomorphisms from $F$ to $G$. A classical result of Lov\'{a}sz shows that isomorphism between graphs is

Wenxiong Li, Rong Geng, Suiyin Chen

In the field of reliability engineering, the Active learning reliability method combining Kriging and Monte Carlo Simulation (AK-MCS) has been developed and demonstrated to be effective in reliability analysis. However, the performance of AK-MCS is sensitive to the size of Candidate Sample Pool (CSP), particularly for systems with small failure probabilities

Piotr Graczyk, Patrice Sawyer

For the first time, the estimates of the non-centered Weyl-group invariant heat kernel for curved Riemannian spaces and for Opdam-Cherednik Laplacians are studied systematically. We prove sharp estimates for the root system $A_1$ with arbitrary multiplicity $k>0$. Sharp estimates of Opdam-Cherednik's radial heat kernel are conjectured for any root system.

Priyanka Maity

We revisited the problem of heavy particles suspended in homogeneous box turbulence flow subjected to rotation along the vertical axis, which introduces anisotropy along the vertical and horizontal planes. We investigate the effect of the emergent structures due to rotation, on the spatial distribution and temporal statistics of the particles. The spatial di

David Schlangen

How does one measure "ability to understand language"? If it is a person's ability that is being measured, this is a question that almost never poses itself in an unqualified manner: Whatever formal test is applied, it takes place on the background of the person's language use in daily social practice, and what is measured is a specialised variety of languag

Evelin Martine Christlmaier, Thomas Schraivogel, Pablo López Ríos, Ali Alavi

An efficient implementation for approximate inclusion of the three-body operator arising in transcorrelated methods via exclusion of explicit three-body components (xTC) is presented and tested against results in the "HEAT" benchmark set [A. Tajti et al., J. Chem. Phys. 121, 11599 (2004)]. Using relatively modest basis sets and computationally simple methods

Weijian Liu, Jun Liu, Tao Liu, Hui Chen

It is often difficult to obtain sufficient training data for adaptive signal detection, which is required to calculate the unknown noise covariance matrix. Additionally, interference is frequently present, which complicates the detecting issue. We provide a two-step method, termed interference cancellation before detection (ICBD), to address the issue of sig

Hongshi Tan, Xinyu Chen, Yao Chen, Bingsheng He

Graph dynamic random walks (GDRWs) have recently emerged as a powerful paradigm for graph analytics and learning applications, including graph embedding and graph neural networks. Despite the fact that many existing studies optimize the performance of GDRWs on multi-core CPUs, massive random memory accesses and costly synchronizations cause severe resource u

Yufeng Chen, Hongfei Dai, Wenlin Li, Fangmin Wang

Over the past few decades, fiber-optic time synchronization (FOTS) has provided fundamental support for the efficient operation of modern society. Looking toward the future beyond fifth-generation/sixth-generation (B5G/6G) scenarios and very large radio telescope arrays, developing high-precision, low-complexity and scalable FOTS technology is crucial for bu

Degui Li, Runze Li, Han Lin Shang

In this paper, we consider detecting and estimating breaks in heterogeneous mean functions of high-dimensional functional time series which are allowed to be cross-sectionally correlated and temporally dependent. A new test statistic combining the functional CUSUM statistic and power enhancement component is proposed with asymptotic null distribution theory

Ciprian-Octavian Truică, Andrei-Ionut Stan, Elena-Simona Apostol

Text simplification (TS) is the process of generating easy-to-understand sentences from a given sentence or piece of text. The aim of TS is to reduce both the lexical (which refers to vocabulary complexity and meaning) and syntactic (which refers to the sentence structure) complexity of a given text or sentence without the loss of meaning or nuance. In this

Samuel Crew, Veronica Fantini, Ankush Goswami, Robert Osburn

We prove resurgence properties for the Borel transform of a formal power series associated to elements in the Habiro ring that come from radial limits of partial theta series via strange identities. As an application, we prove a conjecture in quantum topology due to Costin and Garoufalidis for two families of torus knots.

Christina Sormani, Wenchuan Tian, Changliang Wang

In 2014, Gromov vaguely conjectured that a sequence of manifolds with nonnegative scalar curvature should have a subsequence which converges in some weak sense to a limit space with some generalized notion of nonnegative scalar curvature. The conjecture has been made precise at an IAS Emerging Topics meeting: requiring that the sequence be three dimensional

Gianmarco Caruso, Pierfrancesco Alaimo Di Loro, Marco Mingione, Luca Tardella

In this work, the goal is to estimate the abundance of an animal population using data coming from capture-recapture surveys. We leverage the prior knowledge about the population's structure to specify a parsimonious finite mixture model tailored to its behavioral pattern. Inference is carried out under the Bayesian framework, where we discuss suitable prior

Matthias Kreuzer, Walter Kellermann

In this article, we present our contribution to the ICPHM 2023 Data Challenge on Industrial Systems' Health Monitoring using Vibration Analysis. For the task of classifying sun gear faults in a gearbox, we propose a residual Convolutional Neural Network that operates on raw three-channel time-domain vibration signals. In conjunction with data augmentation an

Tuomas Lappi, Heikki Mäntysaari, Hannu Paukkunen, Mirja Tevio

We formulate the momentum-space Dokshitzer-Gribov-Lipatov-Altarelli-Parisi (DGLAP) evolution equations for structure functions measurable in deeply inelastic scattering. We construct a six-dimensional basis of structure functions that allows for a full three flavor structure and thereby provides a way to calculate perturbative predictions for physical cross

Benedikt Beckmann, Tarek A. El-Melegy, David Koch, Ulf Wiedwald

Reactive single-step hot-pressing at 1473 K and 35 MPa for 4 h produces dense, bulk, near single-phase, low-cost and low-criticality Fe$_2$Al$_{1.15}$B$_2$ and Fe$_2$Al$_{1.1}$B$_2$Ge$_{0.05}$Ga$_{0.05}$ MAB samples, showing a second-order magnetic phase transition with favorable magnetocaloric properties around room temperature. The magnetic as well as magn

Ji Bian, Teng Liu, Pengfei Lu, Qifeng Lao

Recently, experiments aimed at measuring gravity mediated entanglement (GME) using quantum information techniques have been proposed, based on the assumption that if two systems get entangled through local interactions with gravitational field, then this field must be quantum. While there is a debate about what could be drawn from GME, quantum simulation mig

Jiayin Du, Lu Xu, Yong Li

In this paper, we consider a classical Hamiltonian normal form with degeneracy in normal direction. In previous results, one needs to assume that the perturbation satisfies certain non-degenerate conditions in order to remove the degeneracy in the normal form. In stead of that, we introduce a topological degree condition and a weak convexity condition, which

Yaozong Xiao, Hao Sun, Bo Liu, Zhentang Zhao

Attosecond x-ray pulse with known spectro-temporal information is an essential tool for the investigation of ultrafast electron dynamics in quantum systems. Ultrafast free-electron lasers (FELs) have the unique advantage on unprecedented high-intensity at x-ray wavelengths. However, no suitable method has been established so far for the spectro-temporal char

Filippo Ascolani, Giacomo Zanella

Gibbs samplers are popular algorithms to approximate posterior distributions arising from Bayesian hierarchical models. Despite their popularity and good empirical performances, however, there are still relatively few quantitative results on their convergence properties, e.g. much less than for gradient-based sampling methods. In this work we analyse the beh

Shalutha Rajapakshe, Dilanka Wickramasinghe, Sahan Gurusinghe, Deepana Ishtaweera

In disaster-stricken environments, it's vital to assess the damage quickly, analyse the stability of the environment, and allocate resources to the most vulnerable areas where victims might be present. These missions are difficult and dangerous to be conducted directly by humans. Using the complementary capabilities of both the ground and aerial robots, we i

Shishi Xiao, Yihan Hou, Cheng Jin, Wei Zeng

Retrieving charts from a large corpus is a fundamental task that can benefit numerous applications such as visualization recommendations.The retrieved results are expected to conform to both explicit visual attributes (e.g., chart type, colormap) and implicit user intents (e.g., design style, context information) that vary upon application scenarios. However

Peter Koepernik

We study a repulsion-diffusion equation with immigration, whose asymptotic behaviour is related to stability of long-term dynamics in spatial population models and other branching particle systems. We prove well-posedness and find sharp conditions on the repulsion under which a form of the maximum principle and a strong notion of global boundedness of soluti

Jun Zhong, Shuang Liu, Chao Sun

We perform a two-dimensional numerical study on the thermal effect of porous media on global heat transport and flow structure in Rayleigh-B\'enard (RB) convection, focusing on the role of thermal conductivity $\lambda$ of porous media, which ranges from $0.1$ to $50$ relative to the fluid. The simulation is carried out in a square RB cell with the Rayleigh

Litao Yan, Xiaohu Ge

Compared with the energy efficiency of conventional mobile communication systems, the energy efficiency of fifth generation (5G) communication systems has been improved more than 30 times. However, the energy consumption of 5G communication systems is 3 times of the energy consumption of fourth generation (4G) communication systems when the wireless traffic

Jonas Ney, Vincent Lauinger, Laurent Schmalen, Norbert Wehn

In recent years, communication engineers put strong emphasis on artificial neural network (ANN)-based algorithms with the aim of increasing the flexibility and autonomy of the system and its components. In this context, unsupervised training is of special interest as it enables adaptation without the overhead of transmitting pilot symbols. In this work, we p

Somia Boumimez, Carlos Castro

We propose a spectral collocation method to approximate the exact boundary control of the wave equation in a square domain. The idea is to introduce a suitable approximate control problem that we solve in the finite-dimensional space of polynomials of degree N in space. We prove that we can choose a sequence of discrete controls depending on the parameter N

Chao Liang, Yuanjiang Tang, An-Ning Xu, Yong-Chun Liu

Exceptional points (EPs) in non-Hermitian systems have recently attracted wide interests and spawned intriguing prospects for enhanced sensing. However, EPs have not yet been realized in thermal atomic ensembles, which is one of the most important platforms for quantum sensing. Here we experimentally observe EPs in multi-level thermal atomic ensembles, and r

Gergő Almádi, Robert J. MacG. Dawson, Gábor Domokos, Krisztina Regős

The monostatic property of polyhedra (i.e. the property of having just one stable or unstable static equilibrium point) has been in a focus of research ever since Conway and Guy \cite{Conway} published the proof of the existence of the first such object. In the same article they also proved that a homogeneous tetrahedron has at least two stable equilibrium p

Wenyang Liu, Yi Wang, Kejun Wu, Kim-Hui Yap

File fragment classification (FFC) on small chunks of memory is essential in memory forensics and Internet security. Existing methods mainly treat file fragments as 1d byte signals and utilize the captured inter-byte features for classification, while the bit information within bytes, i.e., intra-byte information, is seldom considered. This is inherently ina