April 2023 arXiv papers — page 119

Julia Cantisán, Serhiy Yanchuk, Jesús M. Seoane, Miguel A. F. Sanjuán

A variation in the environment of a system, such as the temperature, the concentration of a chemical solution or the appearance of a magnetic field, may lead to a drift in one of the parameters. If the parameter crosses a bifurcation point, the system can tip from one attractor to another (bifurcation-induced tipping). Typically, this stability exchange occu

Jonas Hall, Logan E. Beaver, Christos G. Cassandras, Sean B. Andersson

In this paper we study an infinite-horizon persistent monitoring problem in a two-dimensional mission space containing a finite number of statically placed targets, at each of which we assume a constant rate of uncertainty accumulation. Equipped with a sensor of finite range, the agent is capable of reducing the uncertainty of nearby targets. We derive a ste

Daichi Nishikawa, Kazuki Maezawa, Shun Fujii, Makoto Okano

We report on an Er-doped fiber (EDF)-laser-based dual-comb system that allows us to perform triggerless asynchronous optical sampling (ASOPS) pump-probe measurements of ultrafast demagnetization and spin precession in magnetic materials. Because the oscillation frequencies of the two frequency-comb light sources are highly stabilized, the pulse-to-pulse timi

Ryan Singh, Christopher L. Buckley

Attention mechanisms are a central property of cognitive systems allowing them to selectively deploy cognitive resources in a flexible manner. Attention has been long studied in the neurosciences and there are numerous phenomenological models that try to capture its core properties. Recently attentional mechanisms have become a dominating architectural choic

Maria Galloway-Sprietsma, Jaehan Bae, Richard Teague, Myriam Benisty

We study the kinematics of the AS 209 disk using the J=2-1 transitions of $^{12}$CO, $^{13}$CO, and C$^{18}$O. We derive the radial, azimuthal, and vertical velocity of the gas, taking into account the lowered emission surface near the annular gap at ~1.7 (200 au) within which a candidate circumplanetary disk-hosting planet has been reported previously. In $

Miljana D. Jovanovic, Goran Damljanovic, Francois Taris, Alok C. Gupta

Here we present the first optical photometric monitoring results of a sample of twelve newly discovered blazars from the ICRF - Gaia CRF astrometric link. The observations were performed from April 2013 until August 2019 using eight telescopes located in Europe. For a robust test for the brightness and colour variability, we use Abbe criterion and F-test. Mo

Antonio Amariti, Nicolò Petri, Alessia Segati

We study the compactification of the $\mathcal{N}=2$ AdS$_5$ consistent truncation of the conifold, in presence of a Betti vector multiplet, on the spindle. We derive the BPS equations and solve them at the poles, computing the central charge for both the twist and the anti-twist class, turning on the magnetic charge associated to the baryonic symmetry. Then

Antonio Gascó, Ignacio Pagonabarraga, Andrea Scagliarini

Active turbulence is a paradigmatic and fascinating example of self-organized motion at large scales occurring in active matter. We employ massive hydrodynamic simulations of suspensions of resolved model microswimmers to tackle the phenomenon in semi-dilute conditions at a mesoscopic level. We measure the kinetic energy spectrum and we detect a $k^{-3}$ pow

Avraham Moriel, Edan Lerner, Eran Bouchbinder

A hallmark of glasses is an excess of low-frequency, nonphononic vibrations, in addition to phonons. It is associated with the intrinsically nonequilibrium and disordered nature of glasses, and is generically manifested as a THz peak -- the boson peak -- in the ratio of the vibrational density of state (VDoS) and Debye's VDoS of phonons. Yet, the excess vibr

Elham Ghorani, Beyhan Puliçe, Farruh Atamurotov, Javlon Rayimbaev

Extended metric-Palatini gravity, quadratic in the antisymmetric part of the affine curvature, is known to lead to the general relativity plus a geometric Proca field. The geometric Proca, equivalent of the non-metricity vector in the torsion-free affine connection, qualifies to be a distinctive signature of the affine curvature. In the present work, we expl

Madeline Schiappa, Raiyaan Abdullah, Shehreen Azad, Jared Claypoole

In recent years large visual-language (V+L) models have achieved great success in various downstream tasks. However, it is not well studied whether these models have a conceptual grasp of the visual content. In this work we focus on conceptual understanding of these large V+L models. To facilitate this study, we propose novel benchmarking datasets for probin

Stephen Merriman, Saranshu Singla, Ali Dhinojwala

Polymer brushes have found extensive applications as responsive surfaces, particularly in achieving tunable friction in solvent environments. Despite recent interest in extending this technology to air environments, little is known about the impact of vapor absorption on friction. Considering polyelectrolyte brushes, we report findings that reveal, with incr

Eliron Rahimi, Kfir Girstein, Roman Malits, Avi Mendelson

Real-Time systems are essential for promptly responding to external stimuli and completing tasks within predefined time constraints. Ensuring high reliability and robust security in these systems is therefore critical. This requires addressing reliability-related events, such as sensor failures and subsystem malfunctions, as well as cybersecurity threats. Th

Tongrui Wang

In this paper, we consider a connected orientable closed Riemannian manifold $M^{n+1}$ with positive Ricci curvature. Suppose $G$ is a compact Lie group acting by isometries on $M$ with $3\leq {\rm codim}(G\cdot p)\leq 7$ for all $p\in M$. Then we show the equivariant min-max $G$-hypersurface $\Sigma$ corresponding to the fundamental class $[M]$ is a multipl

Ashley N. Blackwell, Riad Yahiaoui, Yi-Huan Chen, Pai-Yen Chen

Photonic systems utilized as components for optical computing promise the potential of enhanced computational ability over current computer architectures. Here, an all-dielectric photonic metastructure is investigated for application as a quantum algorithm emulator (QAE) in the terahertz frequency regime; specifically, we show implementation of the Deustsh-J

Ahmed Jaber, Michael Reitz, Avinash Singh, Ali Maleki

Physical and chemical properties of materials can be modified by a resonant optical mode. Such recent demonstrations have mostly relied on a planar cavity geometry, others have relied on a plasmonic resonator. However, the combination of these two device architectures have remained largely unexplored, especially in the context of maximizing light-matter inte

Leizhen Chen, Liangliang Lu, Lijun Xia, Yanqing Lu

Integrated quantum photonics has recently emerged as a powerful platform for generating, manipulating, and detecting entangled photons. Multipartite entangled states lie at the heart of the quantum physics and are the key enabling resources for scalable quantum information processing. Dicke state is an important class of genuinely entangled state, which has

Corrie Green, Chloë Farr, Yang Jiang

Virtual reality is expected to play a significant role in the transformation of education and psychological studies. The possibilities for its application as a visual research method can be enhanced as established frameworks and toolkits are made more available to users, not just developers, advocates, and technical academics, enhancing its controlled study

Jinlong Lei, Uday V. Shanbhag, Jie Chen

We consider a class of nonsmooth aggregative games over networks in stochastic regimes, where each player is characterized by a composite cost function $f_i+r_i$, $f_i$ is a smooth expectation-valued function dependent on its own strategy and an aggregate function of rival strategies, and $r_i$ is a nonsmooth convex function of its strategy with an efficient

Naiyu Fang, Lemiao Qiu, Shuyou Zhang, Zili Wang

As bird's-eye-view (BEV) semantic segmentation is simple-to-visualize and easy-to-handle, it has been applied in autonomous driving to provide the surrounding information to downstream tasks. Inferring BEV semantic segmentation conditioned on multi-camera-view images is a popular scheme in the community as cheap devices and real-time processing. The recent w

Jesus Silva-Rodriguez, Xingpeng Li

This paper proposes a decentralized energy management (DEM) strategy for a network of local microgrids, providing economically balanced energy schedules for all participating microgrids. The proposed DEM strategy can preserve the privacy of each microgrid by only requiring them to share network power exchange information. The proposed DEM strategy enhances t

Xiaoqing Chen, Ross Bannister, Gavin Shaddick, James V. Zidek

This work is motivated by the ECMWF CAMS reanalysis data, a valuable resource for researchers in environmental-related areas, as they contain the most updated atmospheric composition information on a global scale. Unlike observational data obtained from monitoring equipment, such reanalysis data are produced by computers via a 4D-Var data assimilation mechan

P. Diego-Palazuelos

When coupled to electromagnetism via a Chern-Simons interaction, axion-like particles (ALP) produce a rotation of the plane of linear polarization of photons known as cosmic birefringence. Recent measurements of cosmic birefringence obtained from the polarization of the cosmic microwave background (CMB) hint at the existence of an isotropic birefringence ang

Anique Tahir, Lu Cheng, Huan Liu

We propose a simple yet effective solution to tackle the often-competing goals of fairness and utility in classification tasks. While fairness ensures that the model's predictions are unbiased and do not discriminate against any particular group or individual, utility focuses on maximizing the model's predictive performance. This work introduces the idea of

Andrey Alexandrov, Takashi Asada, Fabio Borbone, Valeri Tioukov

We propose a new wide-field imaging method that exploits the Localized Surface Plasmon Resonance phenomenon to produce super-resolution images with an optical microscope equipped with a custom design polarization analyzer module. In this paper we describe the method and apply it to the analysis of low-energy carbon ion tracks implanted in a nuclear emulsion

Antonio Prlj, Daniel Hollas, Basile F. E. Curchod

Nonadiabatic molecular dynamics offers a powerful tool for studying the photochemistry of molecular systems. Key to any nonadiabatic molecular dynamics simulation is the definition of its initial conditions, ideally representing the initial molecular quantum state of the system of interest. In this work, we provide a detailed analysis of how initial conditio

Mike Shengbo Wang, Florian Beutler, Naonori S. Sugiyama

Triumvirate is a Python/C++ package for measuring the three-point clustering statistics in large-scale structure (LSS) cosmological analyses. Given a catalogue of discrete particles (such as galaxies) with their spatial coordinates, it computes estimators of the multipoles of the three-point correlation function, also known as the bispectrum in Fourier space

Zhenyu Zhang, Yehui Hou, Zezhou Hu, Minyong Guo

In this work, we study the images of a Kerr black hole (BH) immersed in uniform magnetic fields, illuminated by the synchrotron radiation of charged particles in the jet. We particularly focus on the spontaneously vortical motions (SVMs) of charged particles in the jet region and investigate the polarized images of electromagnetic radiations from the traject

Muhammad Akbar Husnoo, Adnan Anwar, Haftu Tasew Reda, Nasser Hosseinzadeh

With the growing concern about the security and privacy of smart grid systems, cyberattacks on critical power grid components, such as state estimation, have proven to be one of the top-priority cyber-related issues and have received significant attention in recent years. However, cyberattack detection in smart grids now faces new challenges, including priva

Nadine El-Naggar, Pranava Madhyastha, Tillman Weyde

Previous work has established that RNNs with an unbounded activation function have the capacity to count exactly. However, it has also been shown that RNNs are challenging to train effectively and generally do not learn exact counting behaviour. In this paper, we focus on this problem by studying the simplest possible RNN, a linear single-cell network. We co

Marco Carpentiero, Vincenzo Matta, Ali H. Sayed

In this work we derive the performance achievable by a network of distributed agents that solve, adaptively and in the presence of communication constraints, a regression problem. Agents employ the recently proposed ACTC (adapt-compress-then-combine) diffusion strategy, where the signals exchanged locally by neighboring agents are encoded with randomized dif

Kamrul H Foysal, Bipasha Kundu, Jo Woon Chong

Since late 2019, the global spread of COVID-19 has affected people's daily life. Temperature is an early and common symptom of Covid. Therefore, a convenient and remote temperature detection method is needed. In this paper, a non-contact method for detecting body temperature is proposed. Our developed algorithm based on blackbody radiation calculates the bod

Liangliang Shang, Yang Zhang

We present an application, EasyScan_HEP, for connecting programs to scan the parameter space of High Energy Physics (HEP) models using various sampling algorithms. We develop EasyScan_HEP according to the principle of flexibility and usability. EasyScan_HEP allows us to connect different programs that calculate physical observables, and apply constraints by

Changlong Jiang, Yang Xiao, Cunlin Wu, Mingyang Zhang

3D interacting hand pose estimation from a single RGB image is a challenging task, due to serious self-occlusion and inter-occlusion towards hands, confusing similar appearance patterns between 2 hands, ill-posed joint position mapping from 2D to 3D, etc.. To address these, we propose to extend A2J-the state-of-the-art depth-based 3D single hand pose estimat

Oslenne Araújo, Patrícia Gonçalves, Alexandre B. Simas

In this article, we study the hydrodynamic limit for a stochastic interacting particle system whose dynamics consists in a superposition of several dynamics: the exclusion rule, that dictates that no more than a particle per site with a fixed velocity is allowed; a collision dynamics, that dictates that particles at the same site can collide and originate pa

Xianghong Chen, Lixin Yan, Yue Zhong

Keich (1999) showed that the sharp gauge function for the generalized Hausdorff dimension of Besicovitch sets in $\mathbb R^2$ is between $r^2\log 1/r$ and $r^2(\log 1/r) (\log\log 1/r)^{2+\varepsilon}$ by refining an argument of Bourgain (1991). It is not known whether the iterated logarithms in Keich's bound are necessary. In this paper we construct a fami

Guozheng Lin, Zhangang Han, Amir Shee, Cristián Huepe

We report and characterize the emergence of a noise-induced state of quenched disorder in a generic model describing a dense sheet of active polar disks with non-isotropic rotational and translational dynamics. In this state, randomly oriented self-propelled disks become jammed, only displaying small fluctuations about their mean positions and headings. The

Ildoo Kim

In soap film experiments, the insertion of an external object is necessary to produce vorticity. However, this insertion causes local thickness changes, or simply {\it meniscus}, near the object. Because the meniscus formation may alter the flow near the object, the characterization of meniscus is of considerable importance for the accurate interpretation of

J. B. Potoine, R. Bruce, R. Cai, F. Cerutti

The LHC heavy-ion program with $^{208}$Pb$^{82+}$ beams will benefit from a significant increase of the beam intensity when entering its High-Luminosity era in Run~3 (2023). The stored energy is expected to surpass 20~MJ per beam. The LHC is equipped with a betatron collimation system, which intercepts the transverse beam halo and protects sensitive equipmen

Girtrude Hamm

We introduce the multi-width of a lattice polytope and use this to classify and count all lattice tetrahedra with multi-width $(1,w_2,w_3)$. The approach used in this classification can be extended into a computer algorithm to classify lattice tetrahedra of any given multi-width. We use this to classify tetrahedra with multi-width $(2,w_2,w_3)$ for small $w_

Donald Shenaj, Marco Toldo, Alberto Rigon, Pietro Zanuttigh

The standard class-incremental continual learning setting assumes a set of tasks seen one after the other in a fixed and predefined order. This is not very realistic in federated learning environments where each client works independently in an asynchronous manner getting data for the different tasks in time-frames and orders totally uncorrelated with the ot

Hannes Keppler, Thomas Muller

In Gurau and Keppler 2022 (arXiv:2207.01993), a relation between orthogonal and symplectic tensor models with quartic interactions was proven. In this paper, we provide an alternative proof that extends to polynomial interactions of arbitrary order. We consider tensor models of order D with no symmetry under permutation of the indices that transform in the t

Daniel Leiker, Ashley Ricker Gyllen, Ismail Eldesouky, Mutlu Cukurova

Recent advances in generative artificial intelligence (AI) have captured worldwide attention. Tools such as Dalle-2 and ChatGPT suggest that tasks previously thought to be beyond the capabilities of AI may now augment the productivity of creative media in various new ways, including through the generation of synthetic video. This research paper explores the

Alireza Ataei

In this work, a generalized Hopf's lemma and a global boundary Harnack inequality are proved for solutions to fractional $p$-Laplacian equations. Then, the isolation of the first $(s,p)$-eigenvalue is shown in bounded open sets satisfying the Wiener criterion.

Fangwei Zhong, Xiao Bi, Yudi Zhang, Wei Zhang

Active Object Tracking (AOT) aims to maintain a specific relation between the tracker and object(s) by autonomously controlling the motion system of a tracker given observations. AOT has wide-ranging applications, such as in mobile robots and autonomous driving. However, building a generalizable active tracker that works robustly across different scenarios r

Maxim Dvornikov

We study spin and flavor oscillations of astrophysical neutrinos under the influence of external fields in curved spacetime. First, we consider spin oscillations in case of neutrinos gravitationally scattered off a rotating supermassive black hole surrounded by a thin magnetized accretion disk. We find that the gravitational interaction only does not result

Fabio D'Agostino, Marco Gallo, Matteo Saviozzi, Federico Silvestro

This work proposes an optimal power management strategy for shipboard microgrids equipped with diesel generators and a battery energy storage system. The optimization provides both the unit commitment and the optimal power dispatch of all the resources, in order to ensure reliable power supply at minimum cost and with minimum environmental impact. The optimi

Mayank Gupta, Amit Chauhan, S. Satpathy, B. R. K. Nanda

The state-of-the-art defect engineering techniques have paved the way to realize novel quantum phases out of pristine materials. Here, through density-functional calculations and model studies, we show that the chain-doped monolayer transition metal dichalcogenides (TMDs), where M atoms on a single the zigzag chains are replaced by a higher-valence transitio

Hazan Daglayan, Simon Vary, Valentin Leplat, Nicolas Gillis

We propose to use low-rank matrix approximation using the component-wise L1-norm for direct imaging of exoplanets. Exoplanet detection by direct imaging is a challenging task for three main reasons: (1) the host star is several orders of magnitude brighter than exoplanets, (2) the angular distance between exoplanets and star is usually very small, and (3) th

Henry Jaspars

We establish the rationality of the stable conjugation-invariant word norm on free groups and virtually free Coxeter groups.

Anton D. Putintsev, Kirsty E. McGhee, Denis Sannikov, Anton V. Zasedatelev

We investigate active spatial control of polariton condensates independently of the polariton-, gain-inducing excitation profile. This is achieved by introducing an extra intracavity semiconductor layer, non-resonant to the cavity mode. Saturation of the optical absorption in the uncoupled layer enables the ultra-fast modulation of the effective refractive i

Eduardo Canale, Claudio Qureshi, Alfredo Viola

In this paper we consider the closest vector problem (CVP) for lattices $\Lambda \subseteq \mathbb{Z}^n$ given by a generator matrix $A\in \mathcal{M}_{n\times n}(\mathbb{Z})$. Let $b>0$ be the maximum of the absolute values of the entries of the matrix $A$. We prove that the CVP can be reduced in polynomial time to a quadratic unconstrained binary optimizat

Georgia Saridaki, Alexandros G. Paspatis, Panos Kotsampopoulos, Nikos Hatziargyriou

Massive integration of power electronic devices with multiple control schemes in a wide frequency range pose new challenges regarding systems stability and reliability. Interactions between the fast control loops or between the fast control loops and passive elements of the grid, have been reported in literature and have led to introducing a new type of stab

M. S. Asif, Gayathri Malamal, A. N. Madhavanunni, Vikram Melapudi

Conventional ultrasound (US) imaging employs the delay and sum (DAS) receive beamforming with dynamic receive focus for image reconstruction due to its simplicity and robustness. However, the DAS beamforming follows a geometrical method of delay estimation with a spatially constant speed-of-sound (SoS) of 1540 m/s throughout the medium irrespective of the ti

M. Iskin

We first apply functional-integral approach to a multiband Hubbard model near the critical pairing temperature, and derive a generic effective action that is quartic in the fluctuations of the pairing order parameter. Then we consider time-reversal-symmetric systems with uniform (i.e., at both low-momentum and low-frequency) pairing fluctuations in a unit ce

Ronald Fischer, Markus Luczak-Roesch, Johannes A Karl

There has been concern about ideological basis and possible discrimination in text generated by Large Language Models (LLMs). We test possible value biases in ChatGPT using a psychological value theory. We designed a simple experiment in which we used a number of different probes derived from the Schwartz basic value theory (items from the revised Portrait V

Eduardo R. Mendoza, Dylan Antonio SJ. Talabis, Editha C. Jose, Lauro L. Fontanil

A kinetic system has an absolute concentration robustness (ACR) for a molecular species if its concentration remains the same in every positive steady state of the system. Just recently, a condition that sufficiently guarantees the existence of an ACR in a rank-one mass-action kinetic system was found. In this paper, it will be shown that this ACR criterion

Yuning Xing, Dexter Pham, Henry Williams, David Smith

Smart farming is a growing field as technology advances. Plant characteristics are crucial indicators for monitoring plant growth. Research has been done to estimate characteristics like leaf area index, leaf disease, and plant height. However, few methods have been applied to non-destructive measurements of leaf size. In this paper, an automated non-destruc

David Fiedler, Michal Čertický, Javier Alonso-Mora, Michal Pěchouček

Mobility-on-demand (MoD) systems consist of a fleet of shared vehicles that can be hailed for one-way point-to-point trips. The total distance driven by the vehicles and the fleet size can be reduced by employing ridesharing, i.e., by assigning multiple passengers to one vehicle. However, finding the optimal passenger-vehicle assignment in an MoD system is a

Yulin Zhou, Yiren Zhao, Ilia Shumailov, Robert Mullins

Current literature demonstrates that Large Language Models (LLMs) are great few-shot learners, and prompting significantly increases their performance on a range of downstream tasks in a few-shot learning setting. An attempt to automate human-led prompting followed, with some progress achieved. In particular, subsequent work demonstrates automation can outpe

J. K. Singh, Preeti Singh, Emmanuel N. Saridakis, Shynaray Myrzakul

We propose a novel dark-energy equation-of-state parametrization, with a single parameter $\eta$ that quantifies the deviation from $\Lambda$CDM cosmology. We first confront the scenario with various datasets, from Hubble function (OHD), Pantheon, baryon acoustic oscillations (BAO), and their joint observations, and we show that $\eta$ has a preference for a

Xiaoming Zhao, Xingming Wu, Weihai Chen, Peter C. Y. Chen

Image keypoints and descriptors play a crucial role in many visual measurement tasks. In recent years, deep neural networks have been widely used to improve the performance of keypoint and descriptor extraction. However, the conventional convolution operations do not provide the geometric invariance required for the descriptor. To address this issue, we prop

Andres F. Izquierdo, Leonardo Testi, Stefano Facchini, Giovanni P. Rosotti

[Abridged] The aim of this work is to identify potential signatures from planet-disc interaction in the circumstellar discs around MWC 480, HD 163296, AS 209, IM Lup, and GM Aur, through the study of molecular lines observed as part of the ALMA large program MAPS. Extended and localised perturbations in velocity, line width, and intensity have been analysed

Zhu Cao

A quantum neural network (QNN) is a method to find patterns in quantum data and has a wide range of applications including quantum chemistry, quantum computation, quantum metrology, and quantum simulation. Efficiency and universality are two desirable properties of a QNN but are unfortunately contradictory. In this work, we examine a deep Ising Born machine

Azhar Iqbal, James M. Chappell, Claudia Szabo, Derek Abbott

We present a new framework for creating a quantum version of a classical game, based on Fine's theorem. This theorem shows that for a given set of marginals, a system of Bell's inequalities constitutes both necessary and sufficient conditions for the existence of the corresponding joint probability distribution. Using Fine's theorem, we re-express both the p

Abdallah M. Hussein, Enas M. Abu-Alrob, Fatima M. Alkhateri, Mashhoor A. Al-Wardat

We present a complete analysis of the individual components of the ABC visual triple system HIP 32475. AB pair was discovered during the Hipparcos mission, with a separation of 412 mas. Later, in 2015, a third component was added to the system by discovering it at a small angular distance from B. In our analysis, we follow Al-Wardat's method for analyzing bi

Chanania Steinbock, Eytan Katzav

We study the static and dynamic structure of thermally fluctuating elastic thin sheets by investigating the overdamped dynamic F\"oppl-von K\'arm\'an equation, in which the F\"oppl-von K\'arm\'an equation from elasticity theory is driven by white noise. This nonlinear equation is governed by a single nondimensional coupling parameter $g$ whose large and smal

Jouveer Naidoo, Nicholas Bates, Trevor Gee, Mahla Nejati

This research sets out to assess the viability of using game engines to generate synthetic training data for machine learning in the context of pallet segmentation. Using synthetic data has been proven in prior research to be a viable means of training neural networks and saves hours of manual labour due to the reduced need for manual image annotation. Machi

Jamie Heredge, Charles Hill, Lloyd Hollenberg, Martin Sevior

Quantum Computing offers a potentially powerful new method for performing Machine Learning. However, several Quantum Machine Learning techniques have been shown to exhibit poor generalisation as the number of qubits increases. We address this issue by demonstrating a permutation invariant quantum encoding method, which exhibits superior generalisation perfor

Liyang Lu, Zhaocheng Wang, Sheng Chen

We consider the greedy algorithms for the joint recovery of high-dimensional sparse signals based on the block multiple measurement vector (BMMV) model in compressed sensing (CS). To this end, we first put forth two versions of simultaneous block orthogonal least squares (S-BOLS) as the baseline for the OLS framework. Their cornerstone is to sequentially che

Simone Di Cataldo, Paul Worm, Liang Si, Karsten Held

A recent experiment [X. Ding et al., Nature 615, 50 (2023)] indicates that superconductivity in nickelates is restricted to a narrow window of hydrogen concentration: 0.22 < x < 0.28 in Nd$_{0.8}$Sr$_{0.2}$NiO$_{2}$H$_{x}$. This reported necessity of hydrogen suggests that it plays a crucial role for superconductivity, as it does in the vast field of hydride

Nicolas Garrel

In the case of quadratic forms over a field, it is well-known that the prime spectrum of the Witt ring and the space of orderings of the field determine one another, through associated signature maps. We show that a sililar relation holds for hermitian forms over algebras with involution of the first kind, replacing the usual Witt ring with the mixed Witt ri

Lide Cai, Junqing Chen

We propose reverse time migration (RTM) methods for the imaging of periodic obstacles using only measurements from lower or upper side of the obstacle arrays at a fixed frequency. We analyze the resolution of the lower side and upper side RTM methods in terms of the propagating part of the Rayleigh expansion, Helmholtz-Kirchhoff equation and the distance of

Z. A. Iakovlev, M. M. Glazov

The fine structure of attractive Fermi polarons in van der Waals heterostructures based on monolayer transition metal dichalcogenides in the presence of elastic strain is studied theoretically. The charged excitons (trions), three particle bound states of two electrons and hole or two holes and electron, do not show any strain-induced fine structure splittin

Zhujun Fang, Zhiyong Zhang, Bin Shi, Wei Jiang

Beam monitoring and evaluation are very important to boron neutron capture therapy (BNCT), and a variety of detectors have been developed for these applications. However, most of the detectors used in BNCT only have a small detection area, leading to the inconvenience of the full-scale 2-D measurement of the beam. Based on micromegas technology, we designed

Wei Jiang, Hans D. Schotten

User experience in mobile communications is vulnerable to worse quality at the cell edge, which cannot be compensated by enjoying excellent service at the cell center, according to the principle of risk aversion in behavioral economics. Constrained by weak signal strength and substantial inter-cell interference, the cell edge is always a major bottleneck of

Hafiq Anas, Ong Wee Hong, Owais Ahmed Malik

Current state-of-the-art crowd navigation approaches are mainly deep reinforcement learning (DRL)-based. However, DRL-based methods suffer from the issues of generalization and scalability. To overcome these challenges, we propose a method that includes a Collision Probability (CP) in the observation space to give the robot a sense of the level of danger of

Chunxiao Zheng, Sunmiao Fang, Weicun Chu, Jin Tan

The last decade has witnessed the emergence of hydrovoltaic technology, which can harvest electricity from different forms of water movement, such as raindrops, waves, flows, moisture, and natural evaporation. In particular, the evaporation-induced hydrovoltaic effect received great attention since its discovery in 2017 due to its negative heat emission prop

M. Lyatti, I. Gundareva, T. Röper, Z. Popovic

The d-wave symmetry of the order parameter with zero energy gap in nodal directions stands in the way of using high-temperature superconductors for quantum applications. We investigate the symmetry of the order parameter in ultra-thin YBa2Cu3O7-x (YBCO) films by measuring the electrical transport properties of nanowires and nanoconstrictions aligned at diffe

Etienne Donier-Meroz, Arnak S. Dalalyan, Francis Kramarz, Philippe Choné

Many real-world data sets can be presented in the form of a matrix whose entries correspond to the interaction between two entities of different natures (number of times a web user visits a web page, a student's grade in a subject, a patient's rating of a doctor, etc.). We assume in this paper that the mentioned interaction is determined by unobservable late

Cheng Gong, Ye Lu, Surong Dai, Deng Qian

Exploring the expected quantizing scheme with suitable mixed-precision policy is the key point to compress deep neural networks (DNNs) in high efficiency and accuracy. This exploration implies heavy workloads for domain experts, and an automatic compression method is needed. However, the huge search space of the automatic method introduces plenty of computin

Li Shen, Yan Sun, Zhiyuan Yu, Liang Ding

The field of deep learning has witnessed significant progress, particularly in computer vision (CV), natural language processing (NLP), and speech. The use of large-scale models trained on vast amounts of data holds immense promise for practical applications, enhancing industrial productivity and facilitating social development. With the increasing demands o

Jian Guan, Feiyang Xiao, Youde Liu, Qiaoxi Zhu

Existing contrastive learning methods for anomalous sound detection refine the audio representation of each audio sample by using the contrast between the samples' augmentations (e.g., with time or frequency masking). However, they might be biased by the augmented data, due to the lack of physical properties of machine sound, thereby limiting the detection p

Xu Hou, Yi Hu, Fujia Du, Michael C. B. Ashley

Atmospheric seeing is one of the most important parameters for evaluating and monitoring an astronomical site. Moreover, being able to predict the seeing in advance can guide observing decisions and significantly improve the efficiency of telescopes. However, it is not always easy to obtain long-term and continuous seeing measurements from a standard instrum

Feiyang Xiao, Jian Guan, Qiaoxi Zhu, Wenwu Wang

State-of-the-art audio captioning methods typically use the encoder-decoder structure with pretrained audio neural networks (PANNs) as encoders for feature extraction. However, the convolution operation used in PANNs is limited in capturing the long-time dependencies within an audio signal, thereby leading to potential performance degradation in audio captio

Mohammd Hasan Shamgholi, Vahid Saeedi, Javad Peymanfard, Leila Alhabib

TTS, or text-to-speech, is a complicated process that can be accomplished through appropriate modeling using deep learning methods. In order to implement deep learning models, a suitable dataset is required. Since there is a scarce amount of work done in this field for the Persian language, this paper will introduce the single speaker dataset: ArmanTTS. We c

Vladimir Rovenski, Sergey Stepanov, Irina Tsyganok

In the paper, we study complete almost Ricci solitons using the concepts and methods of geometric dynamics and geometric analysis. In particular, we characterize Einstein manifolds in the class of complete almost Ricci solitons. Then, we examine compact almost Ricci solitons using the orthogonal expansion of the Ricci tensor, this allows us to substantiate t

Jiwan Jung, Jungin Lee

In this paper, we study the combinatorial relations between the cokernels $\text{cok}(A_n+px_iI_n)$ ($1 \le i \le m$) where $A_n$ is an $n \times n$ matrix over the ring of $p$-adic integers $\mathbb{Z}_p$, $I_n$ is the $n \times n$ identity matrix and $x_1, \cdots, x_m$ are elements of $ \mathbb{Z}_p$ whose reductions modulo $p$ are distinct. For a positive

Mengqi Wu, Xiaoqing Wu, Qifeng Hou, Jiangbin Huang

Reactions between cyano radical and aromatic hydrocarbons are believed to be important pathways for the formation of aromatic nitriles in the interstellar medium (ISM) including those identified in the Taurus molecular cloud (TMC-1). Aromatic nitriles might participate in the formation of polycyclic aromatic nitrogen containing hydrocarbons (PANHs) in Titan'

Haoyuan Gao, Xiao Zhang

We provide an intrinsic formulation of the noncommutative differential geometry developed earlier by Chaichian, Tureanu, R. B. Zhang and the second author. This yields geometric definitions of covariant derivatives of noncommutative metrics and curvatures, as well as the noncommutative version of the first and the second Bianchi identities. Moreover, if a no

Jing Hao, Song Chen, Xiaodi Wang, Shumin Han

Pretraining on large-scale datasets can boost the performance of object detectors while the annotated datasets for object detection are hard to scale up due to the high labor cost. What we possess are numerous isolated filed-specific datasets, thus, it is appealing to jointly pretrain models across aggregation of datasets to enhance data volume and diversity

Antoine Deubaibe, Salvador Ndouwe, Baraka Mahamout Mahamat, Dagal Dari Yaya

Spheres, cylinders, cones, cuboids have been used in the literature to generate photonic jets at the back of these structures when illuminated by plane waves. We are working on the generalization (which we call electromagnetic jet) of this concept in guided structures in the microwave domain. The electromagnetic jet can be obtained from a rectangular wavegui

Mohsen Kazemian, Markus Helfert

Novel technological achievements in the fields of business intelligence, business management and data science are based on real-time and complex virtual networks. Sharing data between a large number of organizations that leads to a system with high computational complexity is one of the considerable characteristics of the current business networks. Discovery

Raphael van Kempen, Laurenz Adrian Heidrich, Bastian Lampe, Timo Woopen

Cooperation of automated vehicles (AVs) can improve safety, efficiency and comfort in traffic. Digital twins of Cooperative Intelligent Transport Systems (C-ITS) play an important role in monitoring, managing and improving traffic. Computing a live digital twin of traffic requires as input live perception data of preferably multiple connected entities such a

Masanori Iwamoto, Emanuele Sobacchi, Lorenzo Sironi

The nonlinear interaction between electromagnetic waves and plasmas attracts significant attention in astrophysics because it can affect the propagation of Fast Radio Bursts (FRBs) -- luminous millisecond-duration pulses detected at radio frequency. The filamentation instability (FI) -- a type of nonlinear wave-plasma interaction -- is considered to be domin

Massimiliano Proietti, Filippo Cerocchi, Massimiliano Dispenza

Photonic quantum computers, programmed within the framework of the measurement-based quantum computing (MBQC), currently concur with gate-based platforms in the race towards useful quantum advantage, and some algorithms emerged as main candidates to reach this goal in the near term. Yet, the majority of these algorithms are only expressed in the gate-based m

Abdul Sittar, Dunja Mladenic, Marko Grobelnik

News headlines can be a good data source for detecting the news spreading barriers in news media, which may be useful in many real-world applications. In this paper, we utilize semantic knowledge through the inference-based model COMET and sentiments of news headlines for barrier classification. We consider five barriers including cultural, economic, politic

Soumyajyoti Biswas, Arnab Chatterjee, Parongama Sen, Sudip Mukherjee

This review presents an overview of the current research in kinetic exchange models for opinion formation in a society. The review begins with a brief introduction to previous models and subsequently provides an in-depth discussion of the progress achieved in the Biswas-Chatterjee-Sen model proposed in 2012, also known as the BChS model in some later researc

Maximilian Fels, Lisa Hartung, Anton Klimovsky

We identify the fluctuations of the partition function of the continuous random energy model on a Galton-Watson tree in the so-called weak correlation regime. Namely, when the ``speed functions'', that describe the time-inhomogeneous variance, lie strictly below their concave hull and satisfy a certain weak regularity condition. We prove that the phase diagr

Enrico Drigo, Stefano Baroni

The application of a temperature gradient to an extended system generates an electromotive force that induces an electric current in conductors and a macroscopic polarization in insulators. The ratio of the electromotive force to the temperature difference, usually referred to as the Seebeck coefficient, is often computed using non-equilibrium techniques, su