October 2022 arXiv papers — page 123

Laszlo B. Kish

The original Deutsch-Jozsa (oDJ) problem is for an oracle (realized here as a database) of size N, where, according to their claim, the deterministic solution of the problem on a classical Turing computer requires O(N) computational complexity. They produced the famous Deutsch-Jozsa quantum algorithm that offered an exponential speedup over the classical com

Manuel Zeyen, Lukas Affolter, Marwan Abdou Ahmed, Thomas Graf

The Pound-Drever-Hall (PDH) technique is a popular method for stabilizing the frequency of a laser to a stable optical resonator or, vice versa, the length of a resonator to the frequency of a stable laser. We propose a refinement of the technique yielding an "infinite" dynamic (capture) range so that a resonator is correctly locked to the seed frequency, ev

Tey Berendschot

Inspired by the phase transition results for nonsingular Gaussian actions introduced in arXiv:1911.04272, we prove several phase transition results for nonsingular Bernoulli actions. For generalized Bernoulli actions arising from groups acting on trees, we are able to give a very precise description of their ergodic theoretical properties in terms of the Poi

Yuxiang Nie, Heyan Huang, Wei Wei, Xian-Ling Mao

Long document question answering is a challenging task due to its demands for complex reasoning over long text. Previous works usually take long documents as non-structured flat texts or only consider the local structure in long documents. However, these methods usually ignore the global structure of the long document, which is essential for long-range under

Junfei Wu, Weizhi Xu, Qiang Liu, Shu Wu

The prevalence and perniciousness of fake news have been a critical issue on the Internet, which stimulates the development of automatic fake news detection in turn. In this paper, we focus on evidence-based fake news detection, where several evidences are utilized to probe the veracity of news (i.e., a claim). Most previous methods first employ sequential m

Qihuang Zhong, Liang Ding, Li Shen, Peng Mi

Fine-tuning large pretrained language models on a limited training corpus usually suffers from poor generalization. Prior works show that the recently-proposed sharpness-aware minimization (SAM) optimization method can improve the model generalization. However, SAM adds a perturbation to each model parameter equally (but not all parameters contribute equally

Fredrik Ljungberg, Jonas Linder, Martin Enqvist, Kalevi Tervo

In this work, experiment design for marine vessels is explored. A dictionary-based approach is used, i.e., a systematic way of choosing the most informative combination of independent experiments out of a predefined set of candidates. This idea is quite general but is here tailored to an instrumental variable (IV) estimator with zero-mean instruments. This t

Oussama Boussif, Dan Assouline, Loubna Benabbou, Yoshua Bengio

The computational complexity of classical numerical methods for solving Partial Differential Equations (PDE) scales significantly as the resolution increases. As an important example, climate predictions require fine spatio-temporal resolutions to resolve all turbulent scales in the fluid simulations. This makes the task of accurately resolving these scales

Eduardo Arnold, Jamie Wynn, Sara Vicente, Guillermo Garcia-Hernando

Can we relocalize in a scene represented by a single reference image? Standard visual relocalization requires hundreds of images and scale calibration to build a scene-specific 3D map. In contrast, we propose Map-free Relocalization, i.e., using only one photo of a scene to enable instant, metric scaled relocalization. Existing datasets are not suitable to b

Zifeng Wang, Jimeng Sun

Accessing longitudinal multimodal Electronic Healthcare Records (EHRs) is challenging due to privacy concerns, which hinders the use of ML for healthcare applications. Synthetic EHRs generation bypasses the need to share sensitive real patient records. However, existing methods generate single-modal EHRs by unconditional generation or by longitudinal inferen

Robert Maxton, Yannick Meurice

The real time evolution of quantum field theory models can be calculated order by order in perturbation theory. For $\lambda \phi^4$ models, the perturbative series have a zero radius of convergence which in part motivated the design of digitized versions suitable for quantum computing. In agreement with general arguments suggesting that a large field cutoff

Anton Bakhtin, David J Wu, Adam Lerer, Jonathan Gray

No-press Diplomacy is a complex strategy game involving both cooperation and competition that has served as a benchmark for multi-agent AI research. While self-play reinforcement learning has resulted in numerous successes in purely adversarial games like chess, Go, and poker, self-play alone is insufficient for achieving optimal performance in domains invol

Nils Köpp, Iosif Petrakis

We incorporate strong negation in the theory of computable functionals TCF, a common extension of Plotkin's PCF and G\"{o}del's system $\mathbf{T}$, by defining simultaneously strong negation $A^{\mathbf{N}}$ of a formula $A$ and strong negation $P^{\mathbf{N}}$ of a predicate $P$ in TCF. As a special case of the latter, we get strong negation of an inductiv

Domenico Mattia Cinque, Claudio Battiloro, Paolo Di Lorenzo

The goal of this paper is to introduce pooling strategies for simplicial convolutional neural networks. Inspired by graph pooling methods, we introduce a general formulation for a simplicial pooling layer that performs: i) local aggregation of simplicial signals; ii) principled selection of sampling sets; iii) downsampling and simplicial topology adaptation.

Jack Ceroni, Torin F. Stetina, Maria Kieferova, Carlos Ortiz Marrero

The potential energy surface (PES) of molecules with respect to their nuclear positions is a primary tool in understanding chemical reactions from first principles. However, obtaining this information is complicated by the fact that sampling a large number of ground states over a high-dimensional PES can require a vast number of state preparations. In this w

Kevin Pratt

A multiplicative 3-matching in a group $G$ is a triple of sets $\{a_i\}, \{b_i\}, \{c_i\} \subset G$ such that $a_ib_jc_k = 1$ if and only if $i=j=k$. Here we record the fact that $\text{PSL}(2,p)$ has no multiplicative 3-matching of size greater than $O(p^{8/3})$, yet the slice rank of its group algebra's multiplication tensor is at least $\Omega(p^3)$ over

Alejandro H. Córsico, Murat Uzundag, S. O. Kepler, Leandro G. Althaus

The {\sl TESS} space mission has recently demonstrated its great potential to discover new pulsating white dwarf and pre-white dwarf stars, and to detect periodicities with high precision in already known white-dwarf pulsators. We report the discovery of two new pulsating He-rich atmosphere white dwarfs (DBVs) and present a detailed asteroseismological analy

B. Lefaucher, J. -B. Jager, V. Calvo, A. Durand

We report successful incorporation of an ensemble of G centers in silicon-on-insulator (SOI) microrings using ion implantation and conventional nanofabrication. The coupling between the emitters and the resonant modes of the microrings is studied using continuous-wave and time-resolved microphotoluminescence (PL) experiments. We observe the resonant modes of

Kaitlin Maile, Dennis G. Wilson, Patrick Forré

Incorporating equivariance to symmetry groups as a constraint during neural network training can improve performance and generalization for tasks exhibiting those symmetries, but such symmetries are often not perfectly nor explicitly present. This motivates algorithmically optimizing the architectural constraints imposed by equivariance. We propose the equiv

Giovanni Gallavotti

Viscosity, as a physical property of fluids, reflects an average effect over a chaotic microscopic motion described by Hamiltonian equations. It is proposed, as an example, that stationary states of an incompressible fluid subject to a constant force, can be described via several ensembles, in strict analogy with equilibrium Statistcal Mechanics.

Aida Abiad, Anuj Dawar, Octavio Zapata

Two graphs are cospectral if their respective adjacency matrices have the same multiset of eigenvalues, and generalized cospectral if they are cospectral and so are their complements. We study generalized cospectrality in relation to logical definability. We show that any pair of graphs that are elementary equivalent with respect to the three-variable counti

Odunayo Ogundepo, Xinyu Zhang, Jimmy Lin

Tokenization is a crucial step in information retrieval, especially for lexical matching algorithms, where the quality of indexable tokens directly impacts the effectiveness of a retrieval system. Since different languages have unique properties, the design of the tokenization algorithm is usually language-specific and requires at least some lingustic knowle

Tosin Adewumi, Sana Sabah Sabry, Nosheen Abid, Foteini Liwicki

We conduct relatively extensive investigations of automatic hate speech (HS) detection using different state-of-the-art (SoTA) baselines over 11 subtasks of 6 different datasets. Our motivation is to determine which of the recent SoTA models is best for automatic hate speech detection and what advantage methods like data augmentation and ensemble may have on

Xingyu Chen, Thomas H. Li, Ruonan Zhang, Ge Li

We present two versatile methods to generally enhance self-supervised monocular depth estimation (MDE) models. The high generalizability of our methods is achieved by solving the fundamental and ubiquitous problems in photometric loss function. In particular, from the perspective of spatial frequency, we first propose Ambiguity-Masking to suppress the incorr

Amir Jevnisek, Shai Avidan

The increasing popularity of facial manipulation (Deepfakes) and synthetic face creation raises the need to develop robust forgery detection solutions. Crucially, most work in this domain assume that the Deepfakes in the test set come from the same Deepfake algorithms that were used for training the network. This is not how things work in practice. Instead,

Yu Wei Tan, Nicholas Chua, Nathan Biette, Anand Bhojan

Real-time depth of field in game cinematics tends to approximate the semi-transparent silhouettes of out-of-focus objects through post-processing techniques. We leverage ray tracing hardware acceleration and spatio-temporal reconstruction to improve the realism of such semi-transparent regions through hybrid rendering, while maintaining interactive frame rat

Sarah Tammen, Lingxian Zhang

In this paper, we prove a complex version of the incidence estimate of Guth, Solomon and Wang for tubes obeying certain strong spacing conditions, and we use one of our new estimates to resolve a discretized variant of Falconer's distance set problem in $\mathbb{C}^2$.

Ahmet Can Mert, Aikata, Sunmin Kwon, Youngsam Shin

Homomorphic encryption (HE) enables computation on encrypted data, and hence it has a great potential in privacy-preserving outsourcing of computations to the cloud. Hardware acceleration of HE is crucial as software implementations are very slow. In this paper, we present design methodologies for building a programmable hardware accelerator for speeding up

Noah Lebowitz-Lockard, Victor Souza

Refining an estimate of Croot, Dobbs, Friedlander, Hetzel and Pappalardi, we show that for all $k \geq 2$, the number of integers $1 \leq a \leq n$ such that the equation $a/n = 1/m_1 + \dotsc + 1/m_k$ has a solution in positive integers $m_1, \dotsc, m_k$ is bounded above by $n^{1 - 1/2^{k-2} + o(1)}$ as $n$ goes to infinity. The proof is elementary.

Tim Dockhorn, Arash Vahdat, Karsten Kreis

Denoising diffusion models (DDMs) have emerged as a powerful class of generative models. A forward diffusion process slowly perturbs the data, while a deep model learns to gradually denoise. Synthesis amounts to solving a differential equation (DE) defined by the learnt model. Solving the DE requires slow iterative solvers for high-quality generation. In thi

Michael G. Jabbour, Jonatan Bohr Brask

We derive a simple sufficient criterion for the locality of correlations obtained from given measurements on a Gaussian quantum state. The criterion is based on the construction of a local-hidden-variable model which works by passing part of the inherent Gaussian noise of the state onto the measurements. We illustrate our result in the setting of displaced p

Sam Jeralds, Shrawan Kumar

Kostant asked the following question: Let $\mathfrak{g}$ be a simple Lie algebra over the complex numbers. Let $\lambda$ be a dominant integral weight. Then, $V(\lambda)$ is a component of $V(\rho)\otimes V(\rho)$ if and only if $\lambda \leq 2 \rho$ under the usual Bruhat-Chevalley order on the set of weights. In an earlier work with R. Chirivi and A. Maffe

Shinkyu Park

We investigate a multi-agent decision problem in population games where each agent in a population makes a decision on strategy selection and revision to engage in repeated games with others. The strategy revision is subject to time delays which represent the time it takes for an agent revising its strategy needs to spend before it can adopt a new strategy a

Zhuosheng Zhang, Hai Zhao, Ming Zhou

Discriminative pre-trained language models (PrLMs) can be generalized as denoising auto-encoders that work with two procedures, ennoising and denoising. First, an ennoising process corrupts texts with arbitrary noising functions to construct training instances. Then, a denoising language model is trained to restore the corrupted tokens. Existing studies have

Ilya Soloveychik, Ilya Lyubomirsky, Xin Wang, Sudeep Bhoja

The amounts of data that need to be transmitted, processed, and stored by the modern deep neural networks have reached truly enormous volumes in the last few years calling for the invention of new paradigms both in hardware and software development. One of the most promising and rapidly advancing frontiers here is the creation of new numerical formats. In th

Wei Li, Chen-Rui Wei

We study the L\"{u}roth problem for partial differential fields. The main result is the following partial differential analog of generalized L\"{u}roth's theorem: Let $\mathcal{F}$ be a differential field of characteristic 0 with $m$ derivation operators, $\textbf{u}=u_1,\ldots,u_n$ a set of differential indeterminates over $\mathcal{F}$. We prove that an in

Henry Booth, Wanli Ma, Oktay Karakus

Combining multi-spectral satellite data and machine learning has been suggested as a method for monitoring plastic pollutants in the ocean environment. Recent studies have made theoretical progress regarding the identification of marine plastic via machine learning. However, no study has assessed the application of these methods for mapping and monitoring ma

E. Sánchez, A. Bañón Navarro, F. Wilms, M. Borchardt

In this work, a comparison of the global gyrokinetic codes EUTERPE and GENE-3D in stellarator configurations of LHD and W7-X is carried out. In linear simulations with adiabatic electrons, excellent agreement is found in the mode numbers, growth rate and frequency, mode structure, and spatial localization of the most unstable mode in LHD. In W7-X, the depend

Ahmed Syed, Brian Chase, Philip Varghese, Sana Begum

There are many stages in the LLRF and RF system development process for any new accelerator that can take advantage of hardware emulation of the high-power RF system and RF cavities. LLRF development, bench testing, control system development and testing of installed systems must happen well before SRF cavities are available for test. The PIP-II Linac has th

Z. Schumacher, S. A. Sato, S. Neb, A. Niedermayr

The coupling of light to electrical charge carriers in semiconductors is the foundation of many technological applications. Attosecond transient absorption spectroscopy measures simultaneously how excited electrons and the vacancies they leave behind dynamically react to the applied optical fields. In compound semiconductors, these dynamics can be probed via

Bruno Laburthe-Tolra, Ziyad Amodjee, Benjamin Pasquiou, Martin Robert-de-Saint-Vincent

We propose a minimalistic model to account for the main properties of a continuous superradiant laser, in which a beam of atoms crosses the mode of a high-finesse Fabry-Perot cavity, and collectively emits light into the cavity mode. We focus on the case of weak single atom - cavity cooperativity, and highlight the relevant regime where decoherence due to th

Pavel Suma, Giorgos Tolias

Deep metric learning for vision is trained by optimizing a representation network to map (non-)matching image pairs to (non-)similar representations. During testing, which typically corresponds to image retrieval, both database and query examples are processed by the same network to obtain the representation used for similarity estimation and ranking. In thi

Yang Liu, Jan Hannig, Alexander C Murph

Post-data statistical inference concerns making probability statements about model parameters conditional on observed data. When a priori knowledge about parameters is available, post-data inference can be conveniently made from Bayesian posteriors. In the absence of prior information, we may still rely on objective Bayes or generalized fiducial inference (G

Mengping Yang, Zhe Wang, Ziqiu Chi, Yanbing Zhang

Training GANs under limited data often leads to discriminator overfitting and memorization issues, causing divergent training. Existing approaches mitigate the overfitting by employing data augmentations, model regularization, or attention mechanisms. However, they ignore the frequency bias of GANs and take poor consideration towards frequency information, e

Frédéric Le Roux, Maxime Wolff

Recently Bowden, Hensel and Webb defined the fine curve graph for surfaces, extending the notion of curve graphs for the study of homeomorphism or diffeomorphism groups of surfaces. Later Long, Margalit, Pham, Verberne and Yao proved that for a closed surface of genus $g\geqslant 2$, the automorphism group of the fine graph is naturally isomorphic to the hom

Juan M. Miramont, François Auger, Marcelo A. Colominas, Nils Laurent

The zeros of the spectrogram have proven to be a relevant feature to describe the time-frequency structure of a signal, originated by the destructive interference between components in the time-frequency plane. In this work, a classification of these zeros in three types is introduced, based on the nature of the components that interfere to produce them. Ech

Åke Andersson, Luca Schio, Robert Richter, Michele Alagia

Gas phase C$_{70}$ molecules have been ionized with single photons of energies between 16 eV and 70 eV and the electron spectra measured with velocity map imaging in coincidence with the ions. The doubly ionized and unfragmented species was present at photon energies of 22 eV and up, and triply charged ions from 55 eV. The low kinetic energy parts of the spe

Laura Cabello Piqueras, Anders Søgaard

Pretrained multilingual language models can help bridge the digital language divide, enabling high-quality NLP models for lower resourced languages. Studies of multilingual models have so far focused on performance, consistency, and cross-lingual generalisation. However, with their wide-spread application in the wild and downstream societal impact, it is imp

Charles-Antoine Guérin, Virginie Capelle, Jean-Michel Hartmann

We use radiances collected from space by the Infrared Atmospheric Sounder Interferometer (IASI) when looking down at ocean surfaces during the day to remotely determine the probability distribution of wave slopes. This is achieved by using about 300 channels between 3.6 and 4.0 $\mu$m and a physically-based approach which properly takes the contribution of t

J. Hyam Rubinstein, Benjamin I. P. Rubinstein

The sample compressibility of concept classes plays an important role in learning theory, as a sufficient condition for PAC learnability, and more recently as an avenue for robust generalisation in adaptive data analysis. Whether compression schemes of size $O(d)$ must necessarily exist for all classes of VC dimension $d$ is unknown, but conjectured to be tr

Xiaolong Fan, Maoguo Gong, Yue Wu, Mingyang Zhang

The empirical studies of Graph Neural Networks (GNNs) broadly take the original node feature and adjacency relationship as singleview input, ignoring the rich information of multiple graph views. To circumvent this issue, the multiview graph analysis framework has been developed to fuse graph information across views. How to model and integrate shared (i.e.

Mohannad Abu-romoh, Nelson Costa, Antonio Napoli, João Pedro

A convolutional neural network is proposed to mitigate fiber transmission effects, achieving a five-fold reduction in trainable parameters compared to alternative equalizers, and 3.5 dB improvement in MSE compared to DBP with comparable complexity.

Keisuke Fujii

I show a nontrivial functional giving a conservation quantity in the collisional energy cascade of dissipative Maxwell gases: a fractional-calculus extension of the mean energy. The conservation of this quantity directly leads the power-law energy tail that is stationary during the temporal evolution. In the thermal limit, this quantity naturally reduces to

Ioannis Kontogiannis

Solar flares and coronal mass ejections (CMEs) cause immediate and adverse effects on the interplanetary space and geospace. The deeper understanding of the mechanisms that produce them and the construction of efficient prediction schemes are of paramount importance. The source regions of flares and CMEs exhibit some common morphological characteristics asso

José Roberto Nascimento, Marcos Tadeu O. Pimenta, João R. Santos Júnior

In this paper we prove the existence of a signed ground state solution in the mountain pass level for a class of asymptotically linear elliptic problems, even when the nonlinearity is just continuous in the second variable. The (strongly) resonant and non-resonant cases are discussed. A multiplicity result is also proved when $f$ is odd with respect to the s

Gourav Datta, Zeyu Liu, Zihan Yin, Linyu Sun

In order to deploy current computer vision (CV) models on resource-constrained low-power devices, recent works have proposed in-sensor and in-pixel computing approaches that try to partly/fully bypass the image signal processor (ISP) and yield significant bandwidth reduction between the image sensor and the CV processing unit by downsampling the activation m

Shi-Yu Li, Yun-Long Li, Tianmeng Zhang, Jozsef Vinko

The 2-m aperture Chinese Space Station Telescope (CSST), which observes at wavelengths ranging from 255 to 1000 nm, is expected to start science operations in 2024. An ultra-deep field observation program covering approximately 10 square degrees is proposed with supernovae (SNe) and other transients as one of its primary science drivers. This paper presents

Julien Carron

I describe a method to estimate response matrices of Cosmic Microwave Background (CMB) lensing power spectra estimators to the true sky power under realistic conditions. Applicable to all lensing reconstruction pipelines based on quadratic estimators (QE), it uses a small number of Gaussian CMB Monte-Carlos and specially designed QE's in order to obtain suff

Arrasy Rahman, Ignacio Carlucho, Niklas Höpner, Stefano V. Albrecht

Open ad hoc teamwork is the problem of training a single agent to efficiently collaborate with an unknown group of teammates whose composition may change over time. A variable team composition creates challenges for the agent, such as the requirement to adapt to new team dynamics and dealing with changing state vector sizes. These challenges are aggravated i

Mohit Garg, Suneel Sarswat

We use formal methods to specify, design, and monitor continuous double auctions, which are widely used to match buyers and sellers at exchanges of foreign currencies, stocks, and commodities. We identify three natural properties of such auctions and formally prove that these properties completely determine the input-output relationship. We then formally ver

Olivier Jeunen, Ciarán M. Gilligan-Lee, Rishabh Mehrotra, Mounia Lalmas

The ability to answer causal questions is crucial in many domains, as causal inference allows one to understand the impact of interventions. In many applications, only a single intervention is possible at a given time. However, in some important areas, multiple interventions are concurrently applied. Disentangling the effects of single interventions from joi

Giordano Cotti

In this paper, we address the integration problem of the isomonodromic system of quantum differential equations ($qDE$s) associated with the quantum cohomology of $\mathbb P^1$-bundles on Fano varieties. It is shown that bases of solutions of the $qDE$ of the total space of the $\mathbb P^1$-bundle can be reconstructed from the datum of bases of solutions of

Christian Herglotz, Werner Robitza, Matthias Kränzler, André Kaup

In the past decade, we have witnessed an enormous growth in the demand for online video services. Recent studies estimate that nowadays, more than 1% of the global greenhouse gas emissions can be attributed to the production and use of devices performing online video tasks. As such, research on the true power consumption of devices and their energy efficienc

Samuel A. Stein, Ying Mao, James Ang, Ang Li

Quantum Machine Learning continues to be a highly active area of interest within Quantum Computing. Many of these approaches have adapted classical approaches to the quantum settings, such as QuantumFlow, etc. We push forward this trend and demonstrate an adaption of the Classical Convolutional Neural Networks to quantum systems - namely QuCNN. QuCNN is a pa

Ruibo Chen, Wei Li, Zhiyuan Zhang, Ruihan Bao

Volume prediction is one of the fundamental objectives in the Fintech area, which is helpful for many downstream tasks, e.g., algorithmic trading. Previous methods mostly learn a universal model for different stocks. However, this kind of practice omits the specific characteristics of individual stocks by applying the same set of parameters for different sto

Nama Premsai

Low cost and low thermal budget based spin-coated sol-gel Alumina was explored as a dielectric/passivation layer for GFET. Post thermal annealing, the crack was observed in sol-gel Alumina layer exactly above the graphene channel. The possible mechanism of crack could be graphene lateral restoring movement due to (i) Thermal Expansion Coefficient (TEC) diffe

Shreeharshini Dharanesh Murthy, Lawrence Doolittle, Charlie Xu, Bo Hong

Any cavity controller for a distributed system needs a Phase Reference Line (PRL) signal from which to define phases of a cavity field measurement. The LCLS-II PRL system at SLAC provides bidirectional (forward and reverse) phase references at 1300 MHz to each rack of the LLRF system. The PRL controller embedded with the Master Oscillator (MO) locks the aver

Wojciech Prazuch, Aleksandra Suwalska, Marek Socha, Joanna Tobiasz

Due to the large accumulation of patients requiring hospitalization, the COVID-19 pandemic disease caused a high overload of health systems, even in developed countries. Deep learning techniques based on medical imaging data can help in the faster detection of COVID-19 cases and monitoring of disease progression. Regardless of the numerous proposed solutions

Wenbo Du, Tao Tan, Haijun Zhang, Xianbin Cao

Consider a processor having access only to meta-data consisting of the timings of data packets and acknowledgment (ACK) packets from all nodes in a network. The meta-data report the source node of each packet, but not the destination nodes or the contents of the packets. The goal of the processor is to infer the network topology based solely on such informat

Zi Wang, Huaibo Huang, Aihua Zheng, Chenglong Li

Occluded person re-identification (Re-ID), the task of searching for the same person's images in occluded environments, has attracted lots of attention in the past decades. Recent approaches concentrate on improving performance on occluded data by data/feature augmentation or using extra models to predict occlusions. However, they ignore the imbalance proble

Dongwei Sun, Zhuolin Gao

Image segmentation is a historic and significant computer vision task. With the help of deep learning techniques, image semantic segmentation has made great progresses. Over recent years, based on guidance of attention mechanism compared with CNN which overcomes the problems of lacking of interaction between different channels, and effective capturing and ag

Tingting Wu, Wenna Wu, Ying Yang, Feng-Lei Fan

The Retinex model is one of the most representative and effective methods for low-light image enhancement. However, the Retinex model does not explicitly tackle the noise problem, and shows unsatisfactory enhancing results. In recent years, due to the excellent performance, deep learning models have been widely used in low-light image enhancement. However, t

X. F. Shen, A. Pukhov, O. N. Rosmej, N. E. Andreev

Understanding the interaction of kilojoule, picosecond laser pulse with long-scale length preplasma or homogeneous near critical density (NCD) plasma is crucial for guiding experiments at national short-pulse laser facilities. Using full three-dimensional particle-in-cell simulations, we demonstrate that in this regime, cross-filament stochastic acceleration

Jianwei Mei

It is easy to reason that gravity might be the effect of a fluid in disguise, as it will naturally arise in emergent gravity models where gravity is due to the effect of some fundamental particles, with the latter expected to behave collectively like a fluid at the macroscopic scale. We call this the fluid/gravity equivalence. The key difficulty with the flu

Ankit Gangwal, Aakash Jain, Mauro Conti

Electric vehicles (EVs) represent the long-term green substitute for traditional fuel-based vehicles. To encourage EV adoption, the trust of the end-users must be assured. In this work, we focus on a recently emerging privacy threat of profiling and identifying EVs via the analog electrical data exchanged during the EV charging process. The core focus of our

Markus Banagl

We consider transfer maps on ordinary homology, bordism of singular spaces and homology with coefficients in Ranicki's symmetric L-spectrum, associated to block bundles with closed oriented PL manifold fiber and compact polyhedral base. We prove that if the base polyhedron is a Witt space, for example a pure-dimensional compact complex algebraic variety, the

Marc Jourdan, Rémy Degenne

A Top Two sampling rule for bandit identification is a method which selects the next arm to sample from among two candidate arms, a leader and a challenger. Due to their simplicity and good empirical performance, they have received increased attention in recent years. However, for fixed-confidence best arm identification, theoretical guarantees for Top Two m

Sabrina H. Streipert, Gail S. K. Wolkowicz

The next-iterate operators and corresponding next-iterate root-sets and root-curves associated with the nullclines of a planar discrete map are introduced. How to augment standard phase portraits that include the nullclines and the direction field, by including the signs of the root-operators associated with their nullclines, thus producing an augmented phas

Shreeharshini Dharanesh Murthy, Lawrence Doolittle, Andrew Benwell

The goal of a LLRF system is to control an actual RF cavity with beam. While digital simulations have a place, having an analog circuit to stand in for the cavity can be tremendously helpful in validating hardware+firmware+software under development. A wide range of cavity emulators have been developed in collaboration with SLAC, and LBNL. Cavity emulators a

Renato M. A. Dantas, Henry F. Legg, Stefano Bosco, Daniel Loss

We investigate non-linear transport signatures stemming from linear and cubic spin-orbit interactions in one- and two-dimensional systems. The analytical zero-temperature response to external fields is complemented by finite temperature numerical analysis, establishing a way to distinguish between linear and cubic spin-orbit interactions. We also propose a p

Qingyun Deng, Zhen Zhong, Mao Ye, Wensen Zhang

Lithosphere is an outer rigid part of the terrestrial body, usually consisting of the crust and part of the mantle. Characterizing the physical properties of the lithosphere is critical in investigating its evolution. By modeling mass-related loads within the lithosphere, physical parameters such as the elastic thickness of the lithosphere can be inferred fr

Rafaela F. S. Penacchio, Maurício B. Estradiote, Sérgio L. Morelhão, Celso I. Fornari

Combinations of advanced X-ray sources and zero-noise detector of enormous dynamic range have significantly increased the opportunity of mapping the reciprocal space of crystal lattices. It is particularly important in the design of new devices based on epitaxial thin films. In this work, we present a simple approach to the three-dimensional geometry involve

Joao Paulo Pinheiro, C. A. de S. Pires

The minimal scalar sector of the 3-3-1 model is composed by the SU(3)$_L$ triplet scalars $\eta$, $\rho$, $\chi$ and its potential allows the trilinear term $\frac{f}{\sqrt{2}}\chi \eta \rho$. Since $f$ is an energy scale associated to the explicit violation of Peccei-Quinn global symmetry, it is natural to consider in what energy scale such symmetry is brok

Rabin Adhikari, Safal Thapaliya, Nirajan Basnet, Samip Poudel

Billions of people across the globe have been using social media platforms in their local languages to voice their opinions about the various topics related to the COVID-19 pandemic. Several organizations, including the World Health Organization, have developed automated social media analysis tools that classify COVID-19-related tweets into various topics. H

Jiří Dvořák, Tomáš Mrkvička

Determining the relevant spatial covariates is one of the most important problems in the analysis of point patterns. Parametric methods may lead to incorrect conclusions, especially when the model of interactions between points is wrong. Therefore, we propose a fully nonparametric approach to testing significance of a covariate, taking into account the possi

Bin Li, Yixuan Weng, Bin Sun, Shutao Li

We introduce a new task, named video corpus visual answer localization (VCVAL), which aims to locate the visual answer in a large collection of untrimmed instructional videos using a natural language question. This task requires a range of skills - the interaction between vision and language, video retrieval, passage comprehension, and visual answer localiza

Hadi Abdine, Moussa Kamal Eddine, Michalis Vazirgiannis, Davide Buscaldi

Word sense induction (WSI) is a difficult problem in natural language processing that involves the unsupervised automatic detection of a word's senses (i.e. meanings). Recent work achieves significant results on the WSI task by pre-training a language model that can exclusively disambiguate word senses, whereas others employ previously pre-trained language m

Yasushi Suto, Shin Sasaki, Masataka Aizawa, Kotaro Fujisawa

We develop a general framework to compute photometric variations induced by the oblique rotation of a star with an axisymmetric inhomogeneous surface. We apply the framework to compute lightcurves of white dwarfs adopting two simple models of their surface inhomogeneity. Depending on the surface model and the location of the observer, the resulting lightcurv

Daniel Gratzer, Jonathan Sterling, Carlo Angiuli, Thierry Coquand

We present a new way to control the unfolding of definitions in dependent type theory. Traditionally, proof assistants require users to fix whether each definition will or will not be unfolded in the remainder of a development; unfolding definitions is often necessary in order to reason about them, but an excess of unfolding can result in brittle proofs and

Yante Li, Yang Liu, KhÁnh Nguyen, Henglin Shi

Collaborative learning is an educational approach that enhances learning through shared goals and working together. Interaction and regulation are two essential factors related to the success of collaborative learning. Since the information from various modalities can reflect the quality of collaboration, a new multimodal dataset with cognitive and emotional

Victor Krutyanskiy, Marco Canteri, Martin Meraner, James Bate

A quantum repeater node is presented based on trapped ions that act as single photon emitters, quantum memories and an elementary quantum processor. The node's ability to establish entanglement across two 25 km-long optical fibers independently, then to swap that entanglement efficiently to extend it over both fibers, is demonstrated. The resultant entanglem

Y. T. Tefera, D. Mazzanti, S. Anastasi, D. G. Caldwell

Virtual Reality (VR) interfaces are increasingly used as remote visualization media in telerobotics. Remote environments captured through RGB-D cameras and visualized using VR interfaces can enhance operators' situational awareness and sense of presence. However, this approach has strict requirements for the speed, throughput, and quality of the visualized 3

M. Vadai, H. Damerau, M. Giovannozzi, A. Huschauer

For the future intensity increase of the fixed-target beams in the CERN accelerator complex, a barrier-bucket scheme has been developed to reduce the beam loss during the 5-turn extraction from the PS towards the SPS, the so-called Multi-Turn Extraction. The low-level RF system must synchronise the barrier phase with the PS extraction and SPS injection kicke

ATLAS Collaboration

This paper reports a search for Higgs boson pair ($hh$) production in association with a vector boson ($W$ or $Z$) using 139 $fb^{-1}$ of proton-proton collision data at $\sqrt{s}=$ 13 TeV recorded with the ATLAS detector at the Large Hadron Collider. The search is performed in final states in which the vector boson decays leptonically ($W\to\ell\nu, Z\to\el

Jean-Noel Mettler, Sascha P. Quanz, Ravit Helled, Stephanie L. Olson

We assess the dependence of Earth's disk-integrated mid-infrared thermal emission spectrum on observation geometries and investigate which and how spectral features are impacted by seasonality on Earth. We compiled an exclusive dataset containing 2690 disk-integrated thermal emission spectra for four different full-disk observing geometries (North & South Po

Martin A. Guest

This article, intended for a general mathematical audience, is an informal review of some of the many interesting links which have developed between quantum cohomology and "classical" mathematics. It is based on a talk given at the Autumn Meeting of the Mathematical Society of Japan in September 2021.

Kihyun Kim

We consider the long time dynamics for the self-dual Chern-Simons-Schr\"odinger equation (CSS) within equivariant symmetry. (CSS) is a self-dual $L^{2}$-critical equation having pseudoconformal invariance and solitons. In this paper, we show that any $m$-equivariant, $m\geq1$, $H^{3}$ finite-time blow-up solution to (CSS) is a pseudoconformal blow-up solutio

Ramesh Doddaiah, Prathyush Parvatharaju, Elke Rundensteiner, Thomas Hartvigsen

Explainability helps users trust deep learning solutions for time series classification. However, existing explainability methods for multi-class time series classifiers focus on one class at a time, ignoring relationships between the classes. Instead, when a classifier is choosing between many classes, an effective explanation must show what sets the chosen

Jeppe Sinkbæk Thomsen, Karsten Brogaard, Torben Arentoft, Ditte Slumstrup

Asteroseismic scaling relations can provide high-precision measurements of mass and radius for red giant (RG) stars displaying solar-like oscillations. Their accuracy can be validated and potentially improved using independent and accurate observations of mass, radius, effective temperature and metallicity. We seek to achieve this using long period SB2 eclip

Daejin Jo, Sungwoong Kim, Daniel Wontae Nam, Taehwan Kwon

Episodic count has been widely used to design a simple yet effective intrinsic motivation for reinforcement learning with a sparse reward. However, the use of episodic count in a high-dimensional state space as well as over a long episode time requires a thorough state compression and fast hashing, which hinders rigorous exploitation of it in such hard and c