October 2022 arXiv papers — page 80

Stefano Galanda

We study the relative entropy, in the sense of Araki, for the representation of a self-dual CAR algebra $\mathfrak{A}_{SDC}(\mathcal{H},\Gamma)$. We notice, for a specific choice of $f \in \mathcal{H}$, that the associated element in $\mathfrak{A}_{SDC}(\mathcal{H},\Gamma)$ is unitary. As a consequence, we explicitly compute the relative entropy between a qu

Mathias Parger, Chengcheng Tang, Thomas Neff, Christopher D. Twigg

Convolutional neural network inference on video input is computationally expensive and requires high memory bandwidth. Recently, DeltaCNN managed to reduce the cost by only processing pixels with significant updates over the previous frame. However, DeltaCNN relies on static camera input. Moving cameras add new challenges in how to fuse newly unveiled image

James David M. Tuñacao, Adrian G. Abac, Roland Emerito S. Otadoy

In quantum gravity phenomenology, the effect of the generalized uncertainty principle (GUP) on white dwarfs has been given much attention in the literature. However, these studies assume a zero temperature equation of state (EoS), consequently excluding young white dwarfs whose initial temperatures are substantially high. To that cause, this paper calculates

Zhiheng Zhang

Due to the unobservability of confoundings, there has been widespread concern about how to compute causality quantitatively. To address this challenge, proxy-based negative control approaches have been commonly adopted, where auxiliary outcome variables $\bm{W}$ are introduced as the proxy of confoundings $\bm{U}$. However, these approaches rely on strong as

Ruoxin Xiao, Xinyu Ying, Hengxu Li, Kexin Liu

We find that three factors: Dogecoin network externalities, momentum, and tweet sentiment that capture the time-series expected Dogecoin returns. Dogecoin returns are exposed to Dogecoin network factors. We construct the network factors to capture the user adoption of Dogecoin. Moreover, there is a strong time-series momentum effect, and proxies for investor

V. Hucl, M. Cizek, J. Hrabina, B. Mikel

In scanning probe microscopy laser interferometers are usually used for measuring the position of the probe tip with a metrological traceability. As the most of the AFM setups are designed to work under standard atmospheric conditions the changes of the refractive index of air have an influence to measured values of the length with 1.0e-4 relatively. In orde

Martin Šarbort, Šimon Řeřucha, Petr Jedlička, Josef Lazar

We have addressed the challenge to carry out the angular tilt stabilization of a laser guiding mirror which is intended to route a laser beam with a high energy density. Such an application requires good angular accuracy as well as large operating range, long term stability and absolute positioning. We have designed an instrument for such a high precision an

Taichi Kosugi, Hirofumi Nishi, Yuichiro Matsushita

We propose a nonvariational scheme for geometry optimization of molecules for the first-quantized eigensolver, a recently proposed framework for quantum chemistry using the probabilistic imaginary-time evolution (PITE) on a quantum computer. While the electrons in a molecule are treated in the scheme as quantum mechanical particles, the nuclei are treated as

Mikhail Sodin, Aron Wennman, Oren Yakir

We describe a construction of random meromorphic functions with prescribed simple poles with unit residues at a given stationary point process. We characterize those stationary processes with finite second moment for which, after subtracting the mean, the random function becomes stationary. These random meromorphic functions can be viewed as random analogues

Xizixiang Wei, Cong Shen, Jing Yang, H. Vincent Poor

We propose a novel communication design, termed random orthogonalization, for federated learning (FL) in a massive multiple-input and multiple-output (MIMO) wireless system. The key novelty of random orthogonalization comes from the tight coupling of FL and two unique characteristics of massive MIMO -- channel hardening and favorable propagation. As a result

Yudong Xu, Elias B. Khalil, Scott Sanner

The Abstraction and Reasoning Corpus (ARC) aims at benchmarking the performance of general artificial intelligence algorithms. The ARC's focus on broad generalization and few-shot learning has made it difficult to solve using pure machine learning. A more promising approach has been to perform program synthesis within an appropriately designed Domain Specifi

Jan Niklas Böhm, Philipp Berens, Dmitry Kobak

Visualization methods based on the nearest neighbor graph, such as t-SNE or UMAP, are widely used for visualizing high-dimensional data. Yet, these approaches only produce meaningful results if the nearest neighbors themselves are meaningful. For images represented in pixel space this is not the case, as distances in pixel space are often not capturing our s

Qunfeng Dai, Junyu Quan, Xiaoping Lou, Qin Li

Blind quantum computation (BQC) allows a client with limited quantum power to delegate his quantum computational task to a powerful server and still keep his input, output, and algorithm private. There are mainly two kinds of models about BQC, namely circuit-based and measurement-based models. In addition, a hybrid model called ancilla-driven universal blind

Tabish Ahmed, Sahan Bulathwela

Extracting useful information from the user history to clearly understand informational needs is a crucial feature of a proactive information retrieval system. Regarding understanding information and relevance, Wikipedia can provide the background knowledge that an intelligent system needs. This work explores how exploiting the context of a query using Wikip

John Paul R. Bernaldez, Adrian G. Abac, Roland Emerito S. Otadoy

A modification to the Heisenberg uncertainty principle is called the generalized uncertainty principle (GUP), which emerged due to the introduction of a minimum measurable length, common among phenomenological approaches to quantum gravity. One approach to GUP is called linear-quadratic GUP (LQGUP) which satisfies both the minimum measurable length and the m

Erika Cortese, David B. Cassidy, Simone De Liberato

Recent experimental advances in Positronium (Ps) physics have made it possible to produce dense Ps ensembles in which Ps-Ps interactions may occur, leading to the production of Ps$_2$ molecules and paving the way to the realization of a Ps Bose-Einstein Condensate (BEC). In order to achieve this latter goal it would be advantageous to develop new methods to

Roberto Vittorio Roell, Arif Warsi Laskar, Franz Richard Huybrechts, Martin Weitz

Quantum Hall physics is at the heart of research on both matter and artificial systems, such as cold atomic gases, with non-trivial topological order. We report on the observation of a chiral edge current by transferring atomic wavepackets simultaneously to opposite edges of a synthetic Hall system realized in the two-dimensional state space formed by one sp

Lei Wang, Bo Ai, Yong Niu, Zhangdui Zhong

The rapid development of high-speed railways (HSRs) puts forward high requirements on the corresponding communication system. Millimeter wave (mmWave) can be a promising solution due to its wide bandwidth, narrow beams, and rich spectrum resources. However, with the large number of antenna elements employed, energy-efficient solutions at mmWave frequencies a

Wojciech Flieger, William J. Torres Bobadilla

Using the decomposition of the $D$-dimensional space-time into parallel and perpendicular subspaces, we study and prove a connection between Landau and leading singularities for $N$-point one-loop Feynman integrals by applying multi-dimensional theory of residues. We show that if $D=N$ and $D=N+1$, the leading singularity corresponds to the inverse of the sq

Zhengyang Yu, Jochen Triesch

The vision transformer (ViT) has achieved state-of-the-art results in various vision tasks. It utilizes a learnable position embedding (PE) mechanism to encode the location of each image patch. However, it is presently unclear if this learnable PE is really necessary and what its benefits are. This paper explores two alternative ways of encoding the location

Yu Cheng, Jonathan C. Tan, John J. Tobin, Ruben Fedriani

The unprecedented angular resolution and sensitivity of ALMA makes it possible to unveil disk populations in distant ($>$2 kpc), embedded young cluster environments. We have conducted an observation towards the central region of the massive protocluster G286.21+0.16 at 1.3 mm. With a spatial resolution of 23 mas and a sensitivity of 15 $\rm \mu Jy~beam^{-1}$

Xiaojuan Li

In this paper, we study a stochastic optimal control problem under degenerate G-expectation. By using implied partition method, we show that the approximation result for admissible controls still hold. Based on this result, we prove that the value function is deterministic, and obtain the dynamic programming principle. Furthermore, we prove that the value fu

Benjamin Biggs, James McMahon, Philip Baldoni, Daniel J. Stilwell

We provide theoretical bounds on the worst case performance of the greedy algorithm in seeking to maximize a normalized, monotone, but not necessarily submodular objective function under a simple partition matroid constraint. We also provide worst case bounds on the performance of the greedy algorithm in the case that limited information is available at each

Weslei B. Fontana, Rodrigo G. Pereira

We study the fracton phase described by the Chamon model in a manifold with a boundary. The new processes and excitations emerging at the boundary can be understood by means of a diagrammatic framework. From a continuum perspective, the boundary theory is described by a set of scalar fields in similarity with the standard $K$-matrix Chern-Simons theory. The

Sravanti Addepalli, Kaushal Bhogale, Priyam Dey, R. Venkatesh Babu

Self-supervision has emerged as a propitious method for visual representation learning after the recent paradigm shift from handcrafted pretext tasks to instance-similarity based approaches. Most state-of-the-art methods enforce similarity between various augmentations of a given image, while some methods additionally use contrastive approaches to explicitly

Weiqiang Yang, William Giarè, Supriya Pan, Eleonora Di Valentino

In this paper we consider the effects of adding curvature in extended cosmologies involving a free-to-vary neutrino sector and different parametrizations of Dark Energy (DE). We make use of the Planck 2018 cosmic microwave background temperature and polarization data, Baryon Acoustic Oscillations and Pantheon type Ia Supernovae data. Our main result is that

Gholamali Aminian, Yuheng Bu, Laura Toni, Miguel R. D. Rodrigues

Various approaches have been developed to upper bound the generalization error of a supervised learning algorithm. However, existing bounds are often loose and even vacuous when evaluated in practice. As a result, they may fail to characterize the exact generalization ability of a learning algorithm. Our main contributions are exact characterizations of the

Markus Firmbach, Arnd Bäcker, Roland Ketzmerick

Chaotic transport in Hamiltonian systems is often restricted due to the presence of partial barriers, leading to a limited flux between different regions in phase phase. Typically, the most restrictive partial barrier in a 2D symplectic map is based on a cantorus, the Cantor set remnants of a broken 1D torus. For a 4D symplectic map we establish a partial ba

Daniel Duverney, Iekata Shiokawa

We give a concise introduction to the theory of continuants and show how Perron used them in his proof of Tietze theorem on the convergence of infinite semi-regular continued fractions, as well as for the study of the convergence of purely periodic continued fractions.

Yuewen Chen, Shing-Tung Yau

In this letter, we find the first dynamically stable non-singular solution spherically symmetric SU(2) Einstein-Yang-Mills equation. This solutions is regular at r=0 and asymptotically flat. Since the Yang-Mills field strength decay exponentially, the Einstein-Yang-Mills particle perhaps can be used to be a candidate for dark matter.

Giuseppe De Nittis, Danilo Polo

Deformations in piezoelectric materials lead to conduction effects, which are due to two contributions: the relative displacements of the ionic cores, and the so-called orbital polarization. This work is devoted to the rigorous derivation of the celebrated King-Smith and Vanderbilt formula for orbital polarization in a generalized setting that includes conti

Xiang Fei, Yanghai Yu, Mingwen Fei

In this paper, we give a new construction of $u_0\in B^\sigma_{p,\infty}$ such that the corresponding solution to the hyperbolic Keller-Segel model starting from $u_0$ is discontinuous at $t = 0$ in the metric of $B^\sigma_{p,\infty}(\R^d)$ with $d\geq1$ and $1\leq p\leq\infty$, which implies the ill-posedness for this equation in $B^\sigma_{p,\infty}$. Our

Faezeh Khodabandehlou, Christian Maes, Irene Maes, Karel Netočný

We present the mathematical ingredients for an extension of the Third Law of Thermodynamics (Nernst heat postulate) to nonequilibrium processes. The central quantity is the excess heat which measures the quasistatic addition to the steady dissipative power when a parameter in the dynamics is changed slowly. We prove for a class of driven Markov jump processe

Wenzhi Ruan, Limei Yan, Rony Keppens

Turbulent plasma motion is common in the universe, and invoked in solar flares to drive effective acceleration leading to high energy electrons. Unresolved mass motions are frequently detected in flares from extreme ultraviolet (EUV) observations, which are often regarded as turbulence. However, how this plasma turbulence forms during the flare is still larg

Guilherme Catumba, Atsuki Hiraguchi, George W. -S. Hou, Karl Jansen

We study two different SU(2) gauge-scalar theories in 3 and 4 spacetime dimensions. Firstly, we focus on the 3 dimensional SU(2) theory with multiple Higgs fields in the adjoint representation, that can be mapped to cuprate systems in condensed matter physics which host a rich phase diagram including high-Tc superconductivity. It has been proposed that the t

Renaud Detcherry, Thomas Le Fils, Ramanujan Santharoubane

For any irreducible representation of a surface group into $\mathrm{SL}_2(\mathbb{C})$, we show that there exists a pants decomposition where the restriction to any pair of pants is irreducible and where no curve of the decomposition is sent to a trace $\pm 2$ element. We prove a similar property for $\mathrm{SO}_3$-representations. We also investigate the t

He Sun, Junfeng Zhu, Yipeng Xu

In the future situation, aiming to seek more resources, human beings decided to march towards the mysterious and bright starry sky, which opened the era of great interstellar exploration. According to the Outer Space Treaty, any exploration of celestial bodies should be aimed at promoting global equality and for the benefit of all nations. Firstly, we define

Henry Wilton

New invariants for 2-dimensional cell complexes are defined, which can be interpreted as curvature bounds. These invariants are proved to be rational and computable in a companion article. This document is a survey that collects theorems about these invariants, computes examples, and lays out a programme of conjectures.

Sravanti Addepalli, Samyak Jain, Gaurang Sriramanan, R. Venkatesh Babu

The vulnerability of Deep Neural Networks to Adversarial Attacks has fuelled research towards building robust models. While most Adversarial Training algorithms aim at defending attacks constrained within low magnitude Lp norm bounds, real-world adversaries are not limited by such constraints. In this work, we aim to achieve adversarial robustness within lar

Shubhadip Moulick, Rafiqul Alam, Atindra Nath Pal

Substrate plays a crucial role in determining transport and low frequency noise behavior of graphene field effect devices. Typically, heavily dope Si/SiO$_2$ substrate is used to fabricate these devices for efficient gating. Trapping-detrapping processes closed to the graphene/substrate interface are the dominant sources of resistance fluctuations in the gra

Liqiang Jin, Qiuping Huang, Qiubin Gao, Yongqiang Fei

Deep learning (DL) based channel state information (CSI) feedback in multiple-input multiple-output (MIMO) systems recently has attracted lots of attention from both academia and industrial. From a practical point of views, it is huge burden to train, transfer and deploy a DL model for each parameter configuration of the base station (BS). In this paper, we

Lukas Wolff, Jörg Evers

Owing to their extremely narrow line-widths and exceptional coherence properties, M\"ossbauer nuclei form a promising platform for quantum optics, spectroscopy and dynamics at energies of hard x-rays. A key requirement for further progress is the development of more powerful measurement and data analysis techniques. As one approach, recent experiments have e

Yu Yuan, Jiaqi Wu, Zhongliang Jing, Henry Leung

The fusion of images taken by heterogeneous sensors helps to enrich the information and improve the quality of imaging. In this article, we present a hybrid model consisting of a convolutional encoder and a Transformer-based decoder to fuse multimodal images. In the encoder, a non-local cross-modal attention block is proposed to capture both local and global

Pietro Faccioli, Ilse Krätschmer, Carlos Lourenço

Several fixed-target experiments reported J/$\psi$ and $\Upsilon$ polarization measurements, as functions of Feynman $x$ ($x_{\rm F}$) and transverse momentum ($p_{\rm T}$), in three different polarization frames, using different combinations of beam particles, target nuclei and collision energies. The data form such a diverse and heterogeneous picture that,

Emanuele Maiorana, Chiara Romano, Emiliano Schena, Carlo Massaroni

Wearable devices are increasingly used, thanks to the wide set of applications that can be deployed exploiting their ability to monitor physical activity and health-related parameters. Their usage has been recently proposed to perform biometric recognition, leveraging on the uniqueness of the recorded traits to generate discriminative identifiers. Most of th

Henry Wilton

Let $X$ be a finite, 2-dimensional cell complex. The curvature invariants $\rho_\pm(X)$ and $\sigma_\pm(X)$ were defined in [13], and a programme of conjectures was outlined. Here, we prove the foundational result that the quantities $\rho_\pm(X)$ and $\sigma_\pm(X)$ are the extrema of explicit rational linear-programming problems. As a result they are ratio

Ayyoob Imani, Silvia Severini, Masoud Jalili Sabet, François Yvon

Part-of-Speech (POS) tagging is an important component of the NLP pipeline, but many low-resource languages lack labeled data for training. An established method for training a POS tagger in such a scenario is to create a labeled training set by transferring from high-resource languages. In this paper, we propose a novel method for transferring labels from m

Eric Boulter, Ruxandra Moraru

In this paper, we study Higgs and co-Higgs bundles on non-K\"ahler elliptic surfaces. We show, in particular, that non-trivial stable Higgs bundles only exist when the base of the elliptic fibration has genus at least two and use this existence result to give explicit topological conditions ensuring the smoothness of moduli spaces of stable rank-2 sheaves on

Francesco Cellarosi, Tariq Osman

We consider quadratic Weyl sums $S_N(x;\alpha,\beta)=\sum_{n=1}^N \exp\!\left[2\pi i\left( \left(\tfrac{1}{2}n^2+\beta n\right)\!x+\alpha n\right)\right]$ for $(\alpha,\beta)\in\mathbb{Q}^2$, where $x\in\mathbb{R}$ is randomly distributed according to a probability measure absolutely continuous with respect to the Lebesgue measure. We prove that the limiting

Ali Rohan

In fault detection and diagnosis of prognostics and health management (PHM) systems, most of the methodologies utilize machine learning (ML) or deep learning (DL) through which either some features are extracted beforehand (in the case of ML) or filters are used to extract features autonomously (in case of DL) to perform the critical classification task. Par

Stephan Kürten, Marvin Zanke, Bastian Kubis, Danny van Dyk

Using dispersive methods, we study the $B \to \gamma^*$ form factors underlying the decay $B^- \to \ell^- \bar{\nu}_\ell \ell^{\prime-} \ell^{\prime+}$. We discuss the ambiguity that arises from a separation of the full $B^- \to \ell^- \bar{\nu}_\ell \ell^{\prime-} \ell^{\prime+}$ amplitude into a hadronic tensor and a final-state-radiation piece, including

Junyu Quan, Qin Li, Lvzhou Li

Quantum computing has considerable advantages in solving some problems over its classical counterpart. Currently various physical systems are developed to construct quantum computers but it is still challenging and the first use of quantum computers may adopt the cloud style. Blind quantum computing (BQC) provides a solution for clients with limited quantum

Guitao Lyu, Kui-Tian Xi, Sukjin Yoon, Qijin Chen

Experimental evidence of the Higgs mode in strongly interacting superfluid Fermi gases had not been observed until recently [Behrle et al., Nat. Phys. 14, 781 (2018)]. Due to the coupling with other collective modes and quasiparticle excitations, generating stable Higgs-mode oscillations is challenging. We study how to excite long-lived Higgs-mode oscillatio

Matteo Barigozzi, Daniele Massacci

We study a novel large dimensional approximate factor model with regime changes in the loadings driven by a latent first order Markov process. By exploiting the equivalent linear representation of the model, we first recover the latent factors by means of Principal Component Analysis. We then cast the model in state-space form, and we estimate loadings and t

Alessandro Alla, Marta D'Elia, Christian Glusa, Hugo Oliveira

We explore the approximation of feedback control of integro-differential equations containing a fractional Laplacian term. To obtain feedback control for the state variable of this nonlocal equation we use the Hamilton--Jacobi--Bellman equation. It is well-known that this approach suffers from the curse of dimensionality, and to mitigate this problem we coup

Camille Papon, Ying Wang, Ravitej Uppu, Sven Scholz

We demonstrate the resonant excitation of two quantum dots in a photonic integrated circuit for on-chip single-photon generation in multiple spatial modes. The two quantum dots are electrically tuned to the same emission wavelength using a pair of isolated $p$-$i$-$n$ junctions and excited by a resonant pump laser via dual-mode waveguides. We demonstrate two

Lele Cao, Vilhelm von Ehrenheim, Sebastian Krakowski, Xiaoxue Li

Startups often represent newly established business models associated with disruptive innovation and high scalability. They are commonly regarded as powerful engines for economic and social development. Meanwhile, startups are heavily constrained by many factors such as limited financial funding and human resources. Therefore, the chance for a startup to eve

Arif Ali Khan, Muhammad Azeem Akbar, Aakash Ahmad, Mahdi Fahmideh

Quantum software systems are emerging software engineering (SE) genre that exploit principles of quantum bits (Qubit) and quantum gates (Qgates) to solve complex computing problems that today classic computers can not effectively do in a reasonable time. According to its proponents, agile software development practices have the potential to address many of t

Yulia Khristoforova, Lyudmila Bratchenko, Ivan Bratchenko

Raman spectroscopy is a promising technique used for noninvasive analysis of samples in various fields of application due to its ability for fingerprint probing of samples at the molecular level. Chemometrics methods are widely used nowadays for better understanding of the recorded spectral fingerprints of samples and differences in their chemical compositio

Alan Kostelecky

This contribution to the CPT'22 meeting provides a brief review of some concepts in Lorentz and CPT violation.

Jean-David Pailleron

This article is dedicated to solving the Einstein constraint equations with apparent horizon boundaries and freely specified mean curvature. The main novelty is that we study the conformal constraint equations assuming only low regularity.

Haode Yan, Sihem Mesnager, Xiantong Tan

Permutation polynomials over finite fields are fundamental objects as they are used in various theoretical and practical applications in cryptography, coding theory, combinatorial design, and related topics. This family of polynomials constitutes an active research area in which advances are being made constantly. In particular, constructing infinite classes

Mara Pistellato, Filippo Bergamasco

Reflectance Transformation Imaging (RTI) is a popular technique that allows the recovery of per-pixel reflectance information by capturing an object under different light conditions. This can be later used to reveal surface details and interactively relight the subject. Such process, however, typically requires dedicated hardware setups to recover the light

B Lekshmi, Kiran Jain, Rudolf W. Komm, Dibyendu Nandy

The extreme space weather conditions resulting from high energetic events likes solar flares and Coronal Mass Ejections (CMEs) demand for reliable space weather forecasting. The magnetic flux tubes while rising through the convection zone gets twisted by the turbulent plasma flows, energizing the system and resulting in flares. We investigate the relationshi

Patrick Haller, Andreas Säuberli, Sarah Elisabeth Kiener, Jinger Pan

Eye movements are known to reflect cognitive processes in reading, and psychological reading research has shown that eye gaze patterns differ between readers with and without dyslexia. In recent years, researchers have attempted to classify readers with dyslexia based on their eye movements using Support Vector Machines (SVMs). However, these approaches (i)

Seijin Kobayashi, Pau Vilimelis Aceituno, Johannes von Oswald

Identifying unfamiliar inputs, also known as out-of-distribution (OOD) detection, is a crucial property of any decision making process. A simple and empirically validated technique is based on deep ensembles where the variance of predictions over different neural networks acts as a substitute for input uncertainty. Nevertheless, a theoretical understanding o

Edouard Pineau, Sébastien Razakarivony

In this paper, we describe a universal method for extracting the underlying monotonic trend factor from time series data. We propose an approach related to the Mann-Kendall test, a standard monotonic trend detection method and call it contrastive trend estimation (CTE). We show that the CTE method identifies any hidden trend underlying temporal data while av

Fausto Colantoni

We provide some equations for the Variance Gamma process due to the fact that we do not consider only the definition as a time-changed Brownian motion. This brings us to a new non-local equation, even true in the drifted case, involving generalized Weyl derivatives. Then we focus on the connection to special functions and we study a space equation for our pr

Yuta Matsunaga, Takaaki Saeki, Shinnosuke Takamichi, Hiroshi Saruwatari

We present a training method with linguistic speech regularization that improves the robustness of spontaneous speech synthesis methods with filled pause (FP) insertion. Spontaneous speech synthesis is aimed at producing speech with human-like disfluencies, such as FPs. Because modeling the complex data distribution of spontaneous speech with a rich FP vocab

Alexander Naumann, Felix Hertlein, Benchun Zhou, Laura Dörr

State-of-the-art approaches in computer vision heavily rely on sufficiently large training datasets. For real-world applications, obtaining such a dataset is usually a tedious task. In this paper, we present a fully automated pipeline to generate a synthetic dataset for instance segmentation in four steps. In contrast to existing work, our pipeline covers ev

Yijie Yang, Jian Shi, Dan Wang, Chenye Wu

The decarbonization of the power sector plays a pivotal role in economy-wide decarbonization to set the world on track to limit warming to 1.5{\deg}C by 2050. Carbon emission markets can play a significant role in this transition by putting a price on carbon and giving electricity producers an incentive to reduce their emissions. In this paper, we study the

Abhik Kumar Saha, Romain Dubessy

We use the mathematical toolbox of the inverse scattering transform to study quantitatively the number of solitons in far from equilibrium one-dimensional systems described by the defocusing nonlinear Schr{\"o}dinger equation. We present a simple method to identify the discrete eigenvalues in the Lax spectrum and provide a extensive benchmark of its efficien

Rong Zhang, Vishvesh Kumar, Michael Ruzhansky

In this paper, we study the radial symmetry and monotonicity of nonnegative solutions to nonlinear equations involving the logarithmic Schr$\ddot{\text{o}}$dinger operator $(\mathcal{I}-\Delta)^{\log}$ corresponding to the logarithmic symbol $\log(1 + |\xi|^2)$, which is a singular integral operator given by $$(\mathcal{I}-\Delta)^{\log}u(x) =c_{N}P.V.\int_{

Tiago Matos Santos

Integrated circuit design automation tools are essential for the feasibility of complex designs with millions of transistors. One of the steps performed within the process is the routing of interconnections between components of a circuit. This problem, which also aims to optimize the utilization of connection resources, has been shown to be NP-Complete and

Ankur Chauhan, Manuel Del Rio Viera, Doris Eckstein, Finn Feindt

A new generation of Monolithic Active Pixel Sensors (MAPS), produced in a 65 nm CMOS imaging process, promises higher densities of on-chip circuits and, for a given pixel size, more sophisticated in-pixel logic compared to larger feature size processes. MAPS are a cost-effective alternative to hybrid pixel sensors since flip-chip bonding is not required. In

Mahalakshmi Sabanayagam, Pascal Esser, Debarghya Ghoshdastidar

The fundamental principle of Graph Neural Networks (GNNs) is to exploit the structural information of the data by aggregating the neighboring nodes using a `graph convolution' in conjunction with a suitable choice for the network architecture, such as depth and activation functions. Therefore, understanding the influence of each of the design choice on the n

Mirsad Cosovic, Dragisa Miskovic, Muhamed Delalic, Darijo Raca

We consider the problem of maximum likelihood estimation in linear models represented by factor graphs and solved via the Gaussian belief propagation algorithm. Motivated by massive internet of things (IoT) networks and edge computing, we set the above problem in a clustered scenario, where the factor graph is divided into clusters and assigned for processin

Niki Baccile, Cédric Lorthioir, Abdoul Aziz Ba, Patrick Le Griel

Lipid nanotube-vesicle networks are important channels for intercellular communication and transport of matter. Experimentally observed in neighboring mammalian cells, but also reproduced in model membrane systems, a broad consensus exists on their formation and stability. Lipid membranes must be composed of at least two molecular components, each stabilizin

Tobias Mömke, Hang Zhou

We study the capacitated vehicle routing problem in graphic metrics (graphic CVRP). Our main contribution is a new lower bound on the cost of an optimal solution. For graphic metrics, this lower bound is tight and significantly stronger than the well-known bound for general metrics. The proof of the new lower bound is simple and combinatorial. Using this low

Amr Hendy, Mohamed Abdelghaffar, Mohamed Afify, Ahmed Y. Tawfik

This paper presents Domain-Specific Sub-network (DoSS). It uses a set of masks obtained through pruning to define a sub-network for each domain and finetunes the sub-network parameters on domain data. This performs very closely and drastically reduces the number of parameters compared to finetuning the whole network on each domain. Also a method to make mask

Stephanie Wallace, Martin Kartau, Tarun Kakkar, Chris Davis

Our growing ability to tailor healthcare to the needs of individuals has the potential to transform clinical treatment. However, the measurement of multiple biomarkers to inform clinical decisions requires rapid, effective, and affordable diagnostics. Chronic diseases and rapidly evolving pathogens in a larger population have also escalated the need for impr

Shuai Fan, Chen Lin, Haonan Li, Zhenghao Lin

Most existing pre-trained language representation models (PLMs) are sub-optimal in sentiment analysis tasks, as they capture the sentiment information from word-level while under-considering sentence-level information. In this paper, we propose SentiWSP, a novel Sentiment-aware pre-trained language model with combined Word-level and Sentence-level Pre-traini

Xiaoyu Fan, Kun Chen, Guosai Wang, Mingchun Zhuang

Due to the absence of a library for non-linear function evaluation, so-called general-purpose secure multi-party computation (MPC) are not as ''general'' as MPC programmers expect. Prior arts either naively reuse plaintext methods, resulting in suboptimal performance and even incorrect results, or handcraft ad hoc approximations for specific functions or pla

A. Almeida, C. J. A. P. Martins

We continue our exploration of the wiggly generalisation of the Velocity-Dependent One Scale Model for cosmic strings, through the study of its allowed asymptotic scaling solutions. We extend the work of a previous paper [Almeida $\&$ Martins, Phys. Rev. D 104 (2021) 043524] by considering the more comprehensive case of a time-varying coarse-graining scale f

Tomasz Cieślak, Boris Muha, Srđan Trifunović

Here we study a nonlinear thermoelasticity hyperbolic-parabolic system describing the balance of momentum and internal energy of a heat-conducting elastic body, preserving the positivity of temperature. So far, no global existence results in such a natural case were available. Our result is obtained by using thermodynamically justified variables which allow

Franz de Soete, Nicolas Passade-Boupat, Laurence Talini, François Lequeux

When a drop laden with solid particles and suspended in a liquid passes through a narrow pore, its interface experiences strong shear and elongation, and the raft of particles may accumulate toward the back of the drop. Using well controlled formulations of Pickering drops driven at set pressure, we determine the two conditions for which solid particles are

Jelica Vasiljević, Friedrich Feuerhake, Cédric Wemmert, Thomas Lampert

Virtual stain transfer is a promising area of research in Computational Pathology, which has a great potential to alleviate important limitations when applying deeplearningbased solutions such as lack of annotations and sensitivity to a domain shift. However, in the literature, the majority of virtual staining approaches are trained for a specific staining o

Rui Xue, Ze-Rui Wang, Wei-Jian Li

In the study of radiation mechanisms of AGNs' jets, hadronuclear (pp) interactions are commonly neglected, because the number density of cold protons in the jet is considered insufficient. Very recently, our previous work proves that pp interactions in the low TeV luminosity AGNs, which have potential to generate detectable very-high-energy (VHE) emission, c

Yiming Ma

Recent sophisticated CNN-based algorithms have demonstrated their extraordinary ability to automate counting crowds from images, thanks to their structures which are designed to address the issue of various head scales. However, these complicated architectures also increase computational complexity enormously, making real-time estimation implausible. Thus, i

G. F. Paraschos, V. Mpisketzis, J. -Y. Kim, G. Witzel

Total intensity variability light curves offer a unique insight into the ongoing debate about the launching mechanism of jets. For this work, we utilise the availability of radio and $\gamma$-ray light curves over a few decades of the radio source 3C 84 (NGC 1275). We calculate the multiband time lags between the flares identified in the light curves via dis

Gaoqing Cao

Recalling the expectation of an extremely strong primordial magnetic field $H$, we recheck transitions among the phases of chiral symmetry restoration ($\chi SR$), chiral symmetry breaking ($\chi SB$), and pion superfluidity ($\pi SF$)in the QCD epoch of the early Universe. For homogeneous phases in a finite $H$, a sensible scheme is adopted to determine the

Gayoung An, Donghyun Lee

We study high-velocity tails of some homogeneous Boltzmann equations on $v \in \mathbb{R}_{v}^d$. First, we consider spatially homogeneous inelastic Boltzmann equation with noncutoff collision kernel, in the case of moderately soft potentials. We also study spatially homogeneous mixture Boltzmann equations : for both noncutoff collision kernel with moderatel

Won Young Choi, Isabel C. Arango, Van Tuong Pham, Diogo C. Vaz

One of the major obstacles to realizing spintronic devices such as MESO logic devices is the small signal magnitude used for magnetization readout, making it important to find materials with high spin-to-charge conversion efficiency. Although intermixing at the junction of two materials is a widely occurring phenomenon, its influence on material characteriza

Anees Al-Najjar, Nageswara S. V. Rao, Ramanan Sankaran, Maxim Ziatdinov

Advanced electron microscopy workflows require an ecosystem of microscope instruments and computing systems possibly located at different sites to conduct remotely steered and automated experiments. Current workflow executions involve manual operations for steering and measurement tasks, which are typically performed from control workstations co-located with

Kazuya Tsubokura, Fumiya Kishi, Kotomi Narita, Takuya Takeda

This paper describes the dialog robot system designed by Team Irisapu for the preliminary round of the Dialogue Robot Competition 2022 (DRC2022). Our objective was to design a hospitable travel agent robot. The system we developed was ranked 8th out of 13 systems in the preliminary round of the competition, but our robot received high marks for its naturalne

Alessio Gravina, Davide Bacciu, Claudio Gallicchio

Deep Graph Networks (DGNs) currently dominate the research landscape of learning from graphs, due to their efficiency and ability to implement an adaptive message-passing scheme between the nodes. However, DGNs are typically limited in their ability to propagate and preserve long-term dependencies between nodes, i.e., they suffer from the over-squashing phen

Masaya Tashiro, Ashif Aminulloh Fathnan, Yuta Sugiura, Akira Uchiyama

We present metasurface-inspired maintenance-free IoT tags that can be characterised not only by frequency-domain profiles but also by time-domain profiles. In particular, time-domain characterisation is made possible by implementing the waveform-selective mechanisms of recently developed circuit-based metasurfaces that behave differently, even at the same fr

Christoffer Fyllgraf Christensen, Fengwen Wang, Ole Sigmund

Much work has been done in topology optimization of multiscale structures for maximum stiffness or minimum compliance design. Such approaches date back to the original homogenization-based work by Bends{\o}e and Kikuchi from 1988, which lately has been revived due to advances in manufacturing methods like additive manufacturing. Orthotropic microstructures l

Wenbiao Li, Pan Tang, Zhengfan Wu, Weixue Lu

Embedding-based retrieval (EBR) is a technique to use embeddings to represent query and document, and then convert the retrieval problem into a nearest neighbor search problem in the embedding space. Some previous works have mainly focused on representing the web page with a single embedding, but in real web search scenarios, it is difficult to represent all

Hanyuan Hang

In this paper, we propose an ensemble learning algorithm named \textit{bagged $k$-distance for mode-based clustering} (\textit{BDMBC}) by putting forward a new measurement called the \textit{probability of localized level sets} (\textit{PLLS}), which enables us to find all clusters for varying densities with a global threshold. On the theoretical side, we sh