May 2022 arXiv papers — page 92

Courtney Paquette, Elliot Paquette, Ben Adlam, Jeffrey Pennington

We develop a stochastic differential equation, called homogenized SGD, for analyzing the dynamics of stochastic gradient descent (SGD) on a high-dimensional random least squares problem with $\ell^2$-regularization. We show that homogenized SGD is the high-dimensional equivalence of SGD -- for any quadratic statistic (e.g., population risk with quadratic los

Sergey M. Zagorodnyuk

We study the operator $\mathcal{A}$ of multiplication by an independent variable in a matrix Sobolev space $W^2(M)$. In the cases of finite measures on $[a,b]$ with $(2\times 2)$ and $(3\times 3)$ real continuous matrix weights of full rank it is shown that the operator $\mathcal{A}$ is symmetrizable. Namely, there exist two symmetric operators $\mathcal{B}$

M. C. Diamantini, C. A. Trugenberger, V. M. Vinokur

Planar superconductors, thin films with thickness comparable to the superconducting coherence length, differ crucially from their bulk counterparts. The Coulomb interaction is logarithmic up to distances exceeding typical sample sizes and the Anderson-Higgs mechanism is ineffective to screen the resulting infrared divergences of the resulting (2+1)-dimension

Guilherme Maeda, Naoki Fukaya, Shin-ichi Maeda

Teleoperation is often limited by the ability of an operator to react and predict the behavior of the robot as it interacts with the environment. For example, to grasp small objects on a table, the teleoperator needs to predict the position of the fingertips before the fingers are closed to avoid them hitting the table. For that reason, we developed the F1 h

Lovisa Hagström, Richard Johansson

There are limitations in learning language from text alone. Therefore, recent focus has been on developing multimodal models. However, few benchmarks exist that can measure what language models learn about language from multimodal training. We hypothesize that training on a visual modality should improve on the visual commonsense knowledge in language models

Philipp Korell

We characterize the Gorensteinness of endomorphism rings of a fractional ideal on a curve singularity by stability of the ideal and a condition on its value semigroup ideal. Moreover, the Gorenstein algebroid curves with only Gorenstein integral extensions are classified.

Y. Q. Chai, M. Zhang, L. F. Wei

Sensitive detection of magnetic field is one of the open problem in metrology. Here, we propose an Mach-Zehnder atomic interferometry to sensitively detect the very weak local magnetic field, which is expelled by the superconductor (as the "testing magnet") due to the Meissner effect. The induced magnetic field gradient near the superconductor provides a cen

Xiaohong Fan, Yin Yang, Ke Chen, Jianping Zhang

Although existing deep learning compressed-sensing-based Magnetic Resonance Imaging (CS-MRI) methods have achieved considerably impressive performance, explainability and generalizability continue to be challenging for such methods since the transition from mathematical analysis to network design not always natural enough, often most of them are not flexible

Andrea M. Tonello, Nunzio A. Letizia

We are assisting at a growing interest in the development of learning architectures with application to digital communication systems. Herein, we consider the detection/decoding problem. We aim at developing an optimal neural architecture for such a task. The definition of the optimal criterion is a fundamental step. We propose to use the mutual information

Anssi Kanervisto, Tomi Kinnunen, Ville Hautamäki

Playing games with cheaters is not fun, and in a multi-billion-dollar video game industry with hundreds of millions of players, game developers aim to improve the security and, consequently, the user experience of their games by preventing cheating. Both traditional software-based methods and statistical systems have been successful in protecting against che

Chwas Ahmed, Amir Mafi, Mohammed Rafiq Namiq

We introduce a class of chordal graphs called ($d_1$,$d_2$,$\dots$,$d_q$)-trees. A graph belongs to this class if and only if its clique complex is sequentially Cohen-Macaulay, providing a complete classification of all sequentially Cohen-Macaulay co-chordal graphs. This class also yields a classification of bi-sequentially Cohen-Macaulay graphs. We study th

Jonathan Tremblay, Moustafa Meshry, Alex Evans, Jan Kautz

We present a large-scale synthetic dataset for novel view synthesis consisting of ~300k images rendered from nearly 2000 complex scenes using high-quality ray tracing at high resolution (1600 x 1600 pixels). The dataset is orders of magnitude larger than existing synthetic datasets for novel view synthesis, thus providing a large unified benchmark for both t

Nirmit Sakre, Asao Habe, Alex R. Pettitt, Takashi Okamoto

We study the effects of the magnetic fields on the formation of massive, self-gravitationally bound cores (MBCs) in high-speed cloud-cloud collisions (CCCs). Extending our previous work (Sakre et al. 2021), we perform magnetohydrodynamic simulations following the high-speed (20 - 40 km s$^{-1}$) collisions between two magnetized (4 $\mu$G initially), turbule

Hengcan Shi, Munawar Hayat, Jianfei Cai

Effectively encoding multi-scale contextual information is crucial for accurate semantic segmentation. Existing transformer-based segmentation models combine features across scales without any selection, where features on sub-optimal scales may degrade segmentation outcomes. Leveraging from the inherent properties of Vision Transformers, we propose a simple

Tjark Miener, Daniel Nieto, Viviana Gammaldi, Daniel Kerszberg

We present the first branon dark matter (DM) search in the very high-energy gamma-ray band with observations of the dwarf spheroidal galaxy Segue~1 carried out by the Major Atmospheric Gamma Imaging Cherenkov (MAGIC) telescope system. Branons are new degrees of freedom that appear in flexible brane-world models corresponding to brane fluctuations. They behav

Xiaofeng Chen, Ying Gao

Redactable blockchains allow modifiers or voting committees with modification privileges to edit the data on the chain. Trapdoor holders in chameleon-based hash redactable blockchains can quickly compute hash collisions for arbitrary data, and without breaking the link of the hash-chain. However, chameleon-based hash redactable blockchain schemes have diffic

Tôru Sakai, Hiroki Nakano, Rito Furuchi, Kiyomi Okamoto

The magnetization process of the $S=1$ antiferromagnetic chain with the single-ion anisotropy $D$ and the biquadratic interaction is investigated using the numerical diagonalization. Both interactions stabilize the 2-magnon Tomonaga-Luttinger liquid (TLL) phase in the magnetization process. Based on several excitation gaps calculated by the numerical diagona

Okko Makkonen, Camilla Hollanti

In this paper, a general framework for linear secure distributed matrix multiplication (SDMM) is introduced. The model allows for a neat treatment of straggling and Byzantine servers via a star product interpretation as well as simplified security proofs. Known properties of star products also immediately yield a lower bound for the recovery threshold as wel

Jingshu Guo, Chaoyue Liu, Laiwen Yu, Hengtai Xiang

Two-dimensional materials (2DMs) meet the demand of broadband and low-cost photodetection on silicon for many applications. Currently, it is still very challenging to realize excellent silicon-2DM PDs. Here we demonstrate graphene-silicon-graphene waveguide PDs operating at the wavelength-bands of 1.55 {\mu}m and 2 {\mu}m, showing the potential for large-sca

Vicky Kouni, Yannis Panagakis

We present a new deep unfolding network for analysis-sparsity-based Compressed Sensing. The proposed network coined Decoding Network (DECONET) jointly learns a decoder that reconstructs vectors from their incomplete, noisy measurements and a redundant sparsifying analysis operator, which is shared across the layers of DECONET. Moreover, we formulate the hypo

H. Garcia-Tecocoatzi, A. Giachino, J. Li, A. Ramirez-Morales

The total decay widths of the charmed baryons are calculated by means of the $^3P_0$ model. Our calculations consider in the final states: the charmed baryon-(vector/pseudoscalar) meson pairs and the (octet/ decuplet) baryon-(pseudoscalar/vector) charmed meson pairs, within a constituent quark model. Furthermore, we calculate the masses of the charmed baryon

P. I. Dyadina

The question of the correspondence between the number of degrees of freedom and the number of polarization states in hybrid metric-Palatini f(R)-gravity is considered. It is shown that the scalar transverse breathing and longitudinal modes are a mixture of one polarization state. The speed of gravitational waves propagation in hybrid f(R)-gravity is calculat

K. Al Moulla, X. Dumusque, M. Cretignier, Y. Zhao

Context. To enable radial velocity (RV) precision on the order of ~0.1 m/s required for the detection of Earth-like exoplanets orbiting solar-type stars, the main obstacle lies in mitigating the impact of stellar activity. Aims. This study investigates the dependence of derived RVs with respect to the formation temperature of spectral line segments. Methods.

George Egorov

Penkov with co-authors stdied several types of Lie algebra $\mathfrak{gl}(\infty)$. Completely different new types of super versions of $\mathfrak{gl}(\infty)$ are introduced in this paper: these are Lie superalgebras of supermatrices infinite in all directions with non-zero elements of each matrix occupying a region around the main diagonal bounded by certa

Yuhao Huang, Corey Keller

While many human imaging methodologies probe the structural and functional connectivity of the brain, techniques to investigate cortical networks in a causal and directional manner are critical but limited. The use of iEEG enables several approaches to directly characterize brain regions that are functionally connected and in some cases also establish direct

Nick E. Mavromatos

We discuss situations under which Lorentz symmetry is violated in effective gravitational field theories that arise in the low-energy limit of strings. In particular, we discuss spontaneous violation of the symmetry by the ground state of the system. In the flat space-time limit, the effective theory of the broken Lorentz Symmetry acquires a form that belong

Albert F. Rigosi

How aesthetically pleasing is your country's diffraction pattern? This work summarizes the calculated and experimental Fraunhofer diffraction patterns obtained from using apertures lithographically formed into shapes of national borders. Calculations are made based on the fast Fourier transform of the aperture images. The entropy of each of the 113 nations'

Afra Amini, Tiago Pimentel, Clara Meister, Ryan Cotterell

Probing has become a go-to methodology for interpreting and analyzing deep neural models in natural language processing. However, there is still a lack of understanding of the limitations and weaknesses of various types of probes. In this work, we suggest a strategy for input-level intervention on naturalistic sentences. Using our approach, we intervene on t

Suren Vasilyan, Thomas Fröhlich, Norbert Rogge

Design and operational performance of table-top measurement apparatus is presented towards direct Planck constant traceable high accuracy and high precision small forces and optical power measurements within SI unit system. An electromagnetic force compensation weighing balances, highly reflective mirrors and high-energy pulsed laser unit (static average pow

Hao Chen, Rongkai Shi, Diego Monteiro, Nilufar Baghaei

Virtual reality head-mounted displays (VR HMDs) have become a popular platform for gaming. However, simulator sickness (SS) is still an impediment to VR's wider adoption, particularly in gaming. It can induce strong discomfort and impair players' immersion, performance, and enjoyment. Researchers have explored techniques to mitigate SS. While these technique

Naoyuki Hirata

The trailing hemisphere of Dione is characterized by the Wispy Terrain, where it exhibits a hemispheric-scale network of extensional tectonic faults superposed on the moon's cratered surface. The faults likely reflect past endogenic activity and Dione's interior thermal history. Although fresh exposures of pristine scarps indicate that the timing of the faul

Jin Ho Go, Alina Sari, Jiaojiao Jiang, Shuiqiao Yang

The spread of fake news has caused great harm to society in recent years. So the quick detection of fake news has become an important task. Some current detection methods often model news articles and other related components as a static heterogeneous information network (HIN) and use expensive message-passing algorithms. However, in the real-world, quickly

Guang-Yao Zhou, Zhao-Huan Yu, Qiang Yuan, Hong-Hao Zhang

We attempt to interpret the cosmic-ray positron excess by injection from the nearby pulsar Geminga, assuming a two-zone diffusion scenario and an injection spectrum with a low energy cutoff. Since the high energy positrons and electrons from Geminga can induce $\gamma$ rays via inverse Compton scattering, we take into account the extended $\gamma$-ray observ

Kai Hou Yip, Quentin Changeat, Ahmed Al-Refaie, Ingo Waldmann

Current endeavours in exoplanet characterisation rely on atmospheric retrieval to quantify crucial physical properties of remote exoplanets from observations. However, the scalability and efficiency of the technique are under strain with increasing spectroscopic resolution and forward model complexity. The situation becomes more acute with the recent launch

Naoyuki Hirata, Hideaki Miyamoto

From recently-acquired, high-resolution images obtained by the Cassini spacecraft, we examine the patterns and spatial distributions of rayed craters on Dione. We identify 29 rayed craters with diameters larger than 2km on Dione's surface. The density of rayed craters and theoretical cratering rates indicate that the retention time for rays on Dione can be a

Jürgen Gauss, Simon Blaschke, Sophia Burger, Tommaso Nottoli

A rigorous analysis is carried out concerning the use of Cholesky decomposition (CD) of two-electron integrals in the case of quantum-chemical calculations with finite or perturbative magnetic fields and gauge-including atomic orbitals. We investigate in particular how permutational symmetry can be accounted for in such calculations and how this symmetry can

P. Marziani, A. del Olmo, C. A. Negrete, D. Dultzin

The identification of a virial broadening estimator in the quasar UV rest frame suitable for black hole mass computation at high redshift has become an important issue. We compare the HI Balmer H-beta line width to the ones of two intermediate ionization lines: the Aliii 1860 doublet and the Ciii] 1909 line, over a wide interval of redshift and luminosity (0

Tiziano Schiavone, Giovanni Montani, Maria Giovanna Dainotti, Biagio De Simone

The mismatch between different independent measurements of the expansion rate of the Universe is known as the Hubble constant ($H_0$) tension, and it is a serious and pressing problem in cosmology. We investigate this tension considering the dataset from the Pantheon sample, a collection of 1048 Type Ia Supernovae (SNe Ia) with a redshift range $0<z<2.26$. W

Chang-Chun He, Shao-Gang Xu, Shao-Bin Qiu, Chao He

The first metallic glass of Au-Si alloy has been discovered for over half a century, but its atomic structure is still puzzling. Herein, Au 8 Si dodecahedrons with local five-fold symmetry are revealed as building blocks in Au-Si metallic glass, and the interconnection modes of Au 8 Si dodecahedrons determine the medium-range order. With dimensionality reduc

Patrick Härtl, Markus Leisegang, Matthias Bode

We present a detailed real-space spin-polarized scanning tunneling microscopy (SP-STM) study of the magnetic domain structure of Gd(0001) films epitaxially grown on W(110). To find optimal preparation conditions, the influence of the substrate temperature during deposition and of the post-growth annealing temperature was investigated. Our results show that t

Koray Kavaklı, Yuta Itoh, Hakan Urey, Kaan Akşit

This paper introduces a new multiplane CGH computation method to reconstruct artefact-free high-quality holograms with natural-looking defocus blur. Our method introduces a new targeting scheme and a new loss function. While the targeting scheme accounts for defocused parts of the scene at each depth plane, the new loss function analyzes focused and defocuse

C. Wetterich

Quantum gravity can determine the dependence of gauge couplings in a scalar field, which is related to possible fifth forces and time varying fundamental "constants". This prediction is based on the scaling solution of functional flow equations. For momenta below the field-dependent Planck mass the quantum scale invariant standard model emerges as an effecti

Xu Kaixin, Liu Liyang, Zhao Ziyuan, Zeng Zeng

Multi-label Learning on Image data has been widely exploited with deep learning models. However, supervised training on deep CNN models often cannot discover sufficient discriminative features for classification. As a result, numerous self-supervision methods are proposed to learn more robust image representations. However, most self-supervised approaches fo

Tôru Sakai, Kiyomi Okamoto, Hiroki Nakano, Rito Furuchi

The $S=1/2$ distorted diamond spin chain with the anisotropic ferromagnetic interaction is investigated using the numerical diagonalization and the level spectroscopy analysis. It is known that the system exhibits a plateau of the magnetization curve at the 1/3 of the saturation. The present study indicates that as the anisotropy is varied the quantum phase

Mingchuan Tian, Jizheng Liu

In order to improve the transmission effect of low-power communication signal of Internet of things and compress the enhancement time of low-power communication signal, this paper designs a low-power communication signal enhancement method of Internet of things based on nonlocal mean denoising. Firstly, the residual of one-dimensional communication layer is

N. Nadirashvili, G. Tephnadze, G. Tutberidze

In this paper, we investigate very general approximation kernels with special properties, called an approximate identity, and prove almost everywhere and norm convergence of these general methods, which consists of a class of summability methods and provide norm and a.e. convergence of these summability methods with respect to the trigonometric system. Inves

Chirag Ramesh Srivatsa, Chandra R. Murthy

Irregular repetition slotted aloha (IRSA) is a massive random access protocol in which users transmit several replicas of their packet over a frame to a base station. Existing studies have analyzed IRSA in the single-cell (SC) setup, which does not extend to the more practically relevant multi-cell (MC) setup due to the inter-cell interference. In this work,

Gill Barequet, Gil Ben-Shachar

We consider minimal-perimeter lattice animals, providing a set of conditions which are sufficient for a lattice to have the property that inflating all minimal-perimeter animals of a certain size yields (without repetitions) all minimal-perimeter animals of a new, larger size. We demonstrate this result on the two-dimensional square and hexagonal lattices. I

Sourav Majumder, Tanmoy Bera, Vibhor Singh

Hybrid devices based on the superconducting qubits have emerged as a promising platform for controlling the quantum states of macroscopic resonators. The nonlinearity added by a qubit can be a valuable resource for such control. Here we study a hybrid system consisting of a mechanical resonator longitudinally coupled to a transmon qubit. The qubit readout ca

Dmitrii Gavrilev, Nurlybek Amangeldiuly, Sergei Ivanov, Evgeny Burnaev

Prediction of protein-ligand (PL) binding affinity remains the key to drug discovery. Popular approaches in recent years involve graph neural networks (GNNs), which are used to learn the topology and geometry of PL complexes. However, GNNs are computationally heavy and have poor scalability to graph sizes. On the other hand, traditional machine learning (ML)

German Rodikov, Nino Antulov-Fantulin

Volatility models of price fluctuations are well studied in the econometrics literature, with more than 50 years of theoretical and empirical findings. The recent advancements in neural networks (NN) in the deep learning field have naturally offered novel econometric modeling tools. However, there is still a lack of explainability and stylized knowledge abou

Ziyuan Zhao, Wenjing Lu, Zeng Zeng, Kaixin Xu

Label scarcity has been a long-standing issue for biomedical image segmentation, due to high annotation costs and professional requirements. Recently, active learning (AL) strategies strive to reduce annotation costs by querying a small portion of data for annotation, receiving much traction in the field of medical imaging. However, most of the existing AL m

Hikaru Fukuda, Kentaro Ueda, Yoshio Kaneko, Ryosuke Kurihara

When a conduction electron couples with a non-coplanar localized magnetic moment, the realspace Berry curvature is exerted to cause the geometrical Hall effect, which is not simply proportional to the magnetization. So far, it has been identified in the case mostly where the non-coplanar magnetic order is present on the sublattice of conduction electrons. He

Yihao Liu, Hengyuan Zhao, Jinjin Gu, Yu Qiao

Performance and generalization ability are two important aspects to evaluate the deep learning models. However, research on the generalization ability of Super-Resolution (SR) networks is currently absent. Assessing the generalization ability of deep models not only helps us to understand their intrinsic mechanisms, but also allows us to quantitatively measu

Sabah Al-Fedaghi

The design of complex man-made systems mostly involves a conceptual modeling phase; therefore, it is important to ensure an appropriate analysis method for these models. A key concept for such analysis is the development of a diagramming technique (e.g., UML) because diagrams can describe entities and processes and emphasize important aspects of the systems

Daqi Liu, Miroslaw Bober, Josef Kittler

Scene graph generation is a structured prediction task aiming to explicitly model objects and their relationships via constructing a visually-grounded scene graph for an input image. Currently, the message passing neural network based mean field variational Bayesian methodology is the ubiquitous solution for such a task, in which the variational inference ob

Om Prakash

We construct an infinite family of real cyclotomic fields with non-trivial class group. This result generalizes the result in [1] in the sense that our family includes theirs.

Ryan Sullivan, J. K. Terry, Benjamin Black, John P. Dickerson

Visualizing optimization landscapes has led to many fundamental insights in numeric optimization, and novel improvements to optimization techniques. However, visualizations of the objective that reinforcement learning optimizes (the "reward surface") have only ever been generated for a small number of narrow contexts. This work presents reward surfaces and r

Violeta Menéndez González, Andrew Gilbert, Graeme Phillipson, Stephen Jolly

In this work, we present an end-to-end network for stereo-consistent image inpainting with the objective of inpainting large missing regions behind objects. The proposed model consists of an edge-guided UNet-like network using Partial Convolutions. We enforce multi-view stereo consistency by introducing a disparity loss. More importantly, we develop a traini

Rima Alaifari, Francesca Bartolucci, Stefan Steinerberger, Matthias Wellershoff

Gabor phase retrieval is the problem of reconstructing a signal from only the magnitudes of its Gabor transform. Previous findings suggest a possible link between unique solvability of the discrete problem (recovery from measurements on a lattice) and stability of the continuous problem (recovery from measurements on an open subset of $\mathbb{R}^2$). In thi

San-Dong Guo, Wen-Qi Mu, Jia-Hao Wang, Yu-Xuan Yang

Strain is an effective method to tune the electronic properties of two-dimension (2D) materials, and can induce novel phase transition. Recently, 2D $\mathrm{MA_2Z_4}$ family materials are of interest because of their emerging topological, magnetic and superconducting properties. Here, we investigate the impact of strain effects ($a/a_0$:0.96$\sim$1.04) on t

Mark Sinzger-D'Angelo, Heinz Koeppl

The conditional intensity (CI) of a counting process $Y_t$ is based on the minimal knowledge $\mathcal{F}_t^Y$, i.e., on the observation of $Y_t$ alone. Prominently, the mutual information rate of a signal and its Poisson channel output is a difference functional between the CI and the intensity that has full knowledge about the input. While the CI of Markov

Mohammad Abudayah, Omar Alomari, Omar AbuGhneim

Let $X$ be bipartite mixed graph and for a unit complex number $\alpha$, $H_\alpha$ be its $\alpha$-hermitian adjacency matrix. If $X$ has a unique perfect matching, then $H_\alpha$ has a hermitian inverse $H_\alpha^{-1}$. In this paper we give a full description of the entries of $H_\alpha^{-1}$ in terms of the paths between the vertices. Furthermore, for $

Alessandro Ferrari, Anna Rogantini Picco

This paper empirically evaluates whether adopting a common currency has changed the level of consumption smoothing of euro area member states. We construct a counterfactual dataset of macroeconomic variables through the synthetic control method. We then use the output variance decomposition of Asdrubali, Sorensen and Yosha (1996) on both the actual and the s

Naoyuki Hirata, Hiroshi Kimura, Keiji Ohtsukia

Spokes in Saturn's rings are radially-extended structures consisting of dust grains. Although spacecraft and space telescope observations have revealed various detailed features of the spokes and their time variation, their formation mechanism is still under debate. Previous models examined charging mechanisms to attempt at explaining dust release from cm-si

Nikita S. Pavlov, Kirill S. Pervakov, Igor A. Nekrasov

The electronic structure, magnetism and Fermi surface of a hole self-doped potential iron-based superconductor KCa$_2$Fe$_4$As$_4$O$_2$ (12442) were studied by a first-principes DFT/GGA approach. The projection onto Wannier functions basis is proposed to calculate directly the self-doping value. In particular for KCa$_2$Fe$_4$As$_4$O$_2$ it is 0.75 hole on F

Nasser Ghadiri, Rasoul Samani, Fahime Shahrokh

With the availability of voice-enabled devices such as smart phones, mental health disorders could be detected and treated earlier, particularly post-pandemic. The current methods involve extracting features directly from audio signals. In this paper, two methods are used to enrich voice analysis for depression detection: graph transformation of voice signal

Tôru Sakai, Takaharu Yamada, Ryosuke Nakanishi, Rito Furuchi

The $S=2$ quantum spin chain with the single-ion anisotropy $D$ and the biquadratic exchange interaction $J_{\rm BQ}$ is investigated using the numerical diagonalization of finite-size clusters and the level spectroscopy analysis. It is found that the intermediate-$D$ phase corresponding to the symmetry protected topological (SPT) phase appears in a wide reg

Xuda Ding, Han Wang, Jianping He, Cailian Chen

In this paper we consider estimating the system parameters and designing stable observer for unknown noisy linear time-invariant (LTI) systems. We propose a Support Vector Regression (SVR) based estimator to provide adjustable asymmetric error interval for estimations. This estimator is capable to trade-off bias-variance of the estimation error by tuning par

Tongyu Wang, Peng Yi, Jie Chen

This work studies Nash equilibrium seeking for a class of stochastic aggregative games, where each player has an expectation-valued objective function depending on its local strategy and the aggregate of all players' strategies. We propose a distributed algorithm with operator extrapolation, in which each player maintains an estimate of this aggregate by exc

Jinke Li, Xiao He, Yang Wen, Yuan Gao

As a rising task, panoptic segmentation is faced with challenges in both semantic segmentation and instance segmentation. However, in terms of speed and accuracy, existing LiDAR methods in the field are still limited. In this paper, we propose a fast and high-performance LiDAR-based framework, referred to as Panoptic-PHNet, with three attractive aspects: 1)

Alfredo Mirandola, S. Molinelli, G. Vilches Freixas, M. Donetti

Purpose: To describe the dosimetric commissioning and quality assurance (QA) of the actively scanned proton and carbon ion beams at the Italian National Center for Oncological Hadrontherapy. Methods: The laterally integrated depth-dose-distributions (IDDs) were acquired with the PTW Peakfinder, a variable depth water column, equipped with two Bragg peak ioni

Rajarshi Roy, Jonathan Raiman, Neel Kant, Ilyas Elkin

In this work, we present a reinforcement learning (RL) based approach to designing parallel prefix circuits such as adders or priority encoders that are fundamental to high-performance digital design. Unlike prior methods, our approach designs solutions tabula rasa purely through learning with synthesis in the loop. We design a grid-based state-action repres

Zhengjun Wang, Albin Hedse, Edoardo Amarotti, Nils Lenngren

Advances in ultrafast spectroscopy can provide access to dynamics involving nontrivial quantum correlations and their evolutions. In coherent 2D spectroscopy, the oscillatory time dependence of a signal is a signature of such quantum dynamics. Here we study such beating signals in electronic coherent 2D spectroscopy of CdSe quantum dots (CdSe QDs) at 77 K. T

Julien Assuied, Yérali Gandica

Several studies have used Wikipedia (WP) data-set to analyse worldwide human preferences by languages. However, those studies could suffer from bias related to exceptional social circumstances. Any massive event promoting the exceptional edition of WP can be defined as a source of bias. In this article, we follow a procedure for detecting outliers. Our study

Zijie Zeng, Jing Lin, Weike Pan, Zhong Ming

The common item-based collaborative filtering framework becomes a typical recommendation method when equipped with a certain item-to-item similarity measurement. On one hand, we realize that a well-designed similarity measurement is the key to providing satisfactory recommendation services. On the other hand, similarity measurements designed for sequential r

Hu Zhang, Bei Deng, Wei-Chao Wang, Xing-Qiang Shi

Polar metals based on binary and ternary compounds have been demonstrated in literature. Here, we propose a design principle for ferroelectric-like elemental polar metals and relate it to real materials. The design principle is that, to be an elemental polar metal, atoms should occupy at least two inequivalent Wyckoff positions in a crystal with a polar spac

Stephany Rajeh, Marinette Savonnet, Eric Leclercq, Hocine Cherifi

Influential nodes play a critical role in boosting or curbing spreading phenomena in complex networks. Numerous centrality measures have been proposed for identifying and ranking the nodes according to their importance. Classical centrality measures rely on various local or global properties of the nodes. They do not take into account the network community s

Pietro Menotti

We give the proof of the real analyticity of the accessory parameters in Liouville field theory as a function of the position of the sources in the case in which in addition to elliptic sources, parabolic sources are present. The method is a non trivial extension of the elliptic case as it requires in an intermediate step the introduction of a regulator. The

Wei-Rui Chen, Muhammad Abdul-Mageed

Machine translation (MT) involving Indigenous languages, including those possibly endangered, is challenging due to lack of sufficient parallel data. We describe an approach exploiting bilingual and multilingual pretrained MT models in a transfer learning setting to translate from Spanish to ten South American Indigenous languages. Our models set new SOTA on

Long H. Pham, Jun Sun

Neural networks have achieved state-of-the-art performance in solving many problems, including many applications in safety/security-critical systems. Researchers also discovered multiple security issues associated with neural networks. One of them is backdoor attacks, i.e., a neural network may be embedded with a backdoor such that a target output is almost

Muxin Liu, Chang Liu, Yi-Ming Hu, Lijing Shao

Gravitational waves (GWs) originated from mergers of stellar-mass binary black holes (SBBHs) are considered as dark sirens in cosmology since they usually do not have electromagnetic counterparts. In order to study cosmos with these events, we not only need the luminosity distances extracted from GW signals, but also require the redshift information of sourc

Quanjun Wang, Yuxuan Zhang, Yue Zheng, Zhoumingyang Zhu

We perform a theoretical investigation of the clamped laser intensity inside the filament plasma as a function of gas pressure with external focusing. Unlike the clamped intensity under the selffocusing condition, which is independent on the gas pressure, the clamped intensity with external focusing decreases with the gas pressure. Our findings can explain t

Dongyoung Go, Gwanghee Kim, Jina Park, Junyong Park

The item response model in latent space (LSIRM; Jeon et al., 2021) uncovers unobserved interactions between respondents and items in the item response data by embedding both in a shared latent metric space. The R package lsirm12pl implements Bayesian estimation of the LSIRM and its extensions for various response types, base model specifications, and missing

Ma-Cheng Yang, Cong-Feng Qiao

A family of skew information quantities is obtained, in which the well-known Wigner-Yanase skew information and quantum Fisher information stand as special cases. A transparent proof of convexity of the generalized skew information is given, implying a simple proof of the Wigner-Yanase-Dyson conjecture. We find in this work an exact skew information inequali

Chae Eun Lee, Hyelim Park, Yeong-Gil Shin, Minyoung Chung

Semi-supervised learning for medical image segmentation is an important area of research for alleviating the huge cost associated with the construction of reliable large-scale annotations in the medical domain. Recent semi-supervised approaches have demonstrated promising results by employing consistency regularization, pseudo-labeling techniques, and advers

Zhaoxi Zhang, Leo Yu Zhang, Xufei Zheng, Bilal Hussain Abbasi

The usage of deep learning is being escalated in many applications. Due to its outstanding performance, it is being used in a variety of security and privacy-sensitive areas in addition to conventional applications. One of the key aspects of deep learning efficacy is to have abundant data. This trait leads to the usage of data which can be highly sensitive a

Jingya Zang, Cuiyun Gao, Yupan Chen, Ruifeng Xu

Reviews of songs play an important role in online music service platforms. Prior research shows that users can make quicker and more informed decisions when presented with meaningful song reviews. However, reviews of music songs are generally long in length and most of them are non-informative for users. It is difficult for users to efficiently grasp meaning

Zhe Zhang, Minghao Song, Xiaobiao Huang

Accelerator performance often deteriorates with time during a long period of operation due to secular changes in the machine components or the surrounding environment. In many cases some tuning knobs are effective in compensating the performance drifts and optimization methods can be used to find the ideal machine setting. However, such intervention usually

Jiexing Qi, Jingyao Tang, Ziwei He, Xiangpeng Wan

Relational structures such as schema linking and schema encoding have been validated as a key component to qualitatively translating natural language into SQL queries. However, introducing these structural relations comes with prices: they often result in a specialized model structure, which largely prohibits using large pretrained models in text-to-SQL. To

Sonia K. Murthy, Kyle Lo, Daniel King, Chandra Bhagavatula

Systems that can automatically define unfamiliar terms hold the promise of improving the accessibility of scientific texts, especially for readers who may lack prerequisite background knowledge. However, current systems assume a single "best" description per concept, which fails to account for the many potentially useful ways a concept can be described. We p

Jie Zhao, Jiangtao Su, Xu Yang, Hui Li

We report on high resolution observations of recurrent fan-like jets by the Goode Solar telescope (GST) in multi-wavelengths inside a sunspot group. The dynamics behaviour of the jets is derived from the Ha line profiles. Quantitative values for one well-identified event have been obtained showing a maximum projected velocity of 42 km s^-1 and a Doppler shif

Samer Alashhab, Antonio Javier Gallego, Miguel Ángel Lozano

This paper proposes an interactive system for mobile devices controlled by hand gestures aimed at helping people with visual impairments. This system allows the user to interact with the device by making simple static and dynamic hand gestures. Each gesture triggers a different action in the system, such as object recognition, scene description or image scal

Xiaoyu Ma, Jinlong Lei, Peng Yi, Jie Chen

This paper aims to design a distributed coordination algorithm for solving a multi-agent decision problem with a hierarchical structure. The primary goal is to search the Nash equilibrium of a noncooperative game such that each player has no incentive to deviate from the equilibrium under its private objective. Meanwhile, the agents can coordinate to optimiz

Yang Ni, Danny Abraham, Mariam Issa, Yeseong Kim

Reinforcement Learning (RL) has opened up new opportunities to enhance existing smart systems that generally include a complex decision-making process. However, modern RL algorithms, e.g., Deep Q-Networks (DQN), are based on deep neural networks, resulting in high computational costs. In this paper, we propose QHD, an off-policy value-based Hyperdimensional

Yifan Jia, Michael M. Wolf

The vast majority of quantum states and unitaries have circuit complexity exponential in the number of qubits. In a similar vein, most of them also have exponential minimum description length, which makes it difficult to pinpoint examples of exponential complexity. In this work, we construct examples of constant description length but exponential circuit com

H. Tabuchi, Y. Matsuzaki, N. Furuya, Y. Nakano

Nitrogen vacancy (NV) centers in diamond are promising systems for realizing sensitive temperature sensors. Pulsed optically detected magnetic resonance (Pulsed-ODMR) is one of the ways to measure the temperature using NV centers. However, Pulsed-ODMR requires careful calibration and strict time synchronization to control the microwave pulse, which complicat

Yunseok Jang, Ruben Villegas, Jimei Yang, Duygu Ceylan

There have been remarkable successes in computer vision with deep learning. While such breakthroughs show robust performance, there have still been many challenges in learning in-depth knowledge, like occlusion or predicting physical interactions. Although some recent works show the potential of 3D data in serving such context, it is unclear how we efficient

Patricio Peralta-Braz, Mehrisadat Makki Alamdari, Rafael O. Ruiz, Elena Atroshchenko

Piezoelectric Energy Harvesters (PEHs) are typically employed to provide additional source of energy for a sensing system. However, studies show that a PEH can be also used as a sensor to acquire information about the source of vibration by analysing the produced voltage signal. This opens a possibility to create Simultaneous Energy Harvesting and Sensing (S

Bo Fang, M. Yusuf Özkaya, Ang Li, Ümit V. Çatalyürek

Early but promising results in quantum computing have been enabled by the concurrent development of quantum algorithms, devices, and materials. Classical simulation of quantum programs has enabled the design and analysis of algorithms and implementation strategies targeting current and anticipated quantum device architectures. In this paper, we present a gra