October 2022 arXiv papers — page 7

Tongyue He, Yiming Chen, Junxin Chen, Wei Wang

This paper presents a fused deep learning algorithm for ECG classification. It takes advantages of the combined convolutional and recurrent neural network for ECG classification, and the weight allocation capability of attention mechanism. The input ECG signals are firstly segmented and normalized, and then fed into the combined VGG and LSTM network for feat

Marco Drewes

We discuss the potential to observe lepton number violation (LNV) in displaced vertex searches for heavy neutral leptons (HNLs) at future lepton colliders. Even though a direct detection of LNV is impossible for the dominant production channel because lepton number is carried away by an unobservable neutrino, there are several signatures of LNV that can be s

Masaru Sugawara

In arXiv:0912.1346, four quantum dilogarithm identities containing infinitely many factors are proposed as wall-crossing formula for refined BPS invariant. We give algebraic proof of these identities using the formula for universal R-matrix of quantum affine algebra developed by K. Ito, which yields various product presentation of universal R-matrix by choos

Zhenwei An, Quzhe Huang, Cong Jiang, Yansong Feng

The charge prediction task aims to predict the charge for a case given its fact description. Recent models have already achieved impressive accuracy in this task, however, little is understood about the mechanisms they use to perform the judgment.For practical applications, a charge prediction model should conform to the certain legal theory in civil law cou

Pascal Heid

We will consider the damped Newton method for strongly monotone and Lipschitz continuous operator equations in a variational setting. We will provide a very accessible justification why the undamped Newton method performs better than its damped counterparts in a vicinity of a solution. Moreover, in the given setting, an adaptive step-size strategy will be pr

Wing-Fung Ku, Wan-Chi Siu, Xi Cheng, H. Anthony Chan

Have you ever thought that you can be an intelligent painter? This means that you can paint a picture with a few expected objects in mind, or with a desirable scene. This is different from normal inpainting approaches for which the location of specific objects cannot be determined. In this paper, we present an intelligent painter that generate a person's ima

Takehiro Ito, Yuni Iwamasa, Yusuke Kobayashi, Shun-ichi Maezawa

In 1973, Fisk proved that any $4$-coloring of a $3$-colorable triangulation of the $2$-sphere can be obtained from any $3$-coloring by a sequence of Kempe-changes. On the other hand, in the case where we are only allowed to recolor a single vertex in each step, which is a special case of a Kempe-change, there exists a $4$-coloring that cannot be obtained fro

Yuichiro Goto

Dlab and Ringel showed that algebras being quasi-hereditary in all orders for indices of primitive idempotents becomes hereditary. So, we are interested in for which orders a given quasi-hereditary algebra is again quasi-hereditary. As a matter of fact, we consider permutations of indices, and if the algebra with permuted indices is quasi-hereditary, then we

Stepan V. Nabol, Pavel S. Pankin, Dmitrii N. Maksimov, Ivan V. Timofeev

An anisotropic photonic crystal containing two anisotropic defect layers is considered. It is demonstrated that the system under can support a Fabry-Perot bound state in the continuum (FP-BIC). A fully analytic solution of the scattering problem as well as a condition for FP-BIC have been derived in the framework of the temporal coupled-mode theory.

Gunnar Þór Magnússon

We give a quick direct proof of Wu's theorem on the subadditivity of Hermitian metrics of negative holomorphic sectional curvature.

Enpei Zhang, Shuo Tang, Xiaowen Dong, Siheng Chen

Multi-agent learning has gained increasing attention to tackle distributed machine learning scenarios under constrictions of data exchanging. However, existing multi-agent learning models usually consider data fusion under fixed and compulsory collaborative relations among agents, which is not as flexible and autonomous as human collaboration. To fill this g

Tomislav Begušić, Geoffrey A. Blake

Two-dimensional spectroscopic techniques combining terahertz (THz), infrared (IR), and visible pulses offer a wealth of information about coupling among vibrational modes in molecular liquids, thus providing a promising probe of their local structure. However, the capabilities of these spectroscopies are still largely unexplored due to experimental limitatio

Wei Kang, Zengwei Yao, Fangjun Kuang, Liyong Guo

In streaming automatic speech recognition (ASR), it is desirable to reduce latency as much as possible while having minimum impact on recognition accuracy. Although a few existing methods are able to achieve this goal, they are difficult to implement due to their dependency on external alignments. In this paper, we propose a simple way to penalize symbol del

Liyong Guo, Xiaoyu Yang, Quandong Wang, Yuxiang Kong

Knowledge distillation(KD) is a common approach to improve model performance in automatic speech recognition (ASR), where a student model is trained to imitate the output behaviour of a teacher model. However, traditional KD methods suffer from teacher label storage issue, especially when the training corpora are large. Although on-the-fly teacher label gene

Kosuke Fujiwara, Sota Kitamura, Takahiro Morimoto

We study the nonlinear magnon spin current induced by an ac electric field under light irradiation in collinear antiferromagnets with broken inversion symmetry. For linearly polarized light, we find that a dc spin current appears through ``the magnon spin shift current" mechanism, which is driven by a spin polarization generation in the two magnon creation p

Koichi Miyazaki, Masato Murata, Tomoki Koriyama

Automatic speech recognition (ASR) systems developed in recent years have shown promising results with self-attention models (e.g., Transformer and Conformer), which are replacing conventional recurrent neural networks. Meanwhile, a structured state space model (S4) has been recently proposed, producing promising results for various long-sequence modeling ta

Sanaa Abaach, Zakaria Mzaouali, Morad El Baz

The long distance entanglement in finite size open Fermi-Hubbard chains, together with the end-to-end quantum teleportation are investigated. We show the peculiarity of the ground state of the Fermi-Hubbard model to support maximum long distance entanglement, which allows it to operate as a quantum resource for high fidelity long distance quantum teleportati

Dimitry Leites

1) In 1976, looking at simple finite-dimensional complex Lie superalgebras, J.~Bernstein and I, and independently M.~Duflo, observed that certain divergence-free vectorial Lie superalgebras have deformations with odd parameters and conjectured that other simple Lie superalgebras have no such deformations (unpublished). Here, I prove this conjecture and overv

Yulin Cai

We develop the intersection theory of non-archimedean analytic spaces and prove the projection formula and the GAGA principle. As an application, we naturally define the category of finite correspondences of analytic spaces.

Tengxiao Liu, Qipeng Guo, Xiangkun Hu, Yue Zhang

Interpreting the reasoning process from questions to answers poses a challenge in approaching explainable QA. A recently proposed structured reasoning format, entailment tree, manages to offer explicit logical deductions with entailment steps in a tree structure. To generate entailment trees, prior single pass sequence-to-sequence models lack visible interna

Xuan Bu, Liang-Jun Zhai, Shuai Yin

In this paper, we explore quantum criticality in the disordered Aubry-Andr\'{e} (AA) model. For the pure AA model, it is well-known that it hosts a critical point separating an extended phase and a localized insulator phase by tuning the strength of the quasiperiodic potential. Here we unearth that the disorder strength $\Delta$ contributes an independent re

Young-Moo Byun, Jejoong Yoo

Quasiparticle self-consistent many-body perturbation theory (MBPT) methods that update both eigenvalues and eigenvectors can calculate the excited-state properties of molecular systems without depending on the choice of starting points. However, those methods are computationally intensive even on modern multi-core central processing units (CPUs) and thus typ

Mohamedelmujtaba Altayeb, Abdelrahman M. Elamin, Hozaifa Ahmed, Eithar Elfatih Elfadil Ibrahim

The recent decade has seen an enormous rise in the popularity of deep learning and neural networks. These algorithms have broken many previous records and achieved remarkable results. Their outstanding performance has significantly sped up the progress of AI, and so far various milestones have been achieved earlier than expected. However, in the case of rela

Yan Li, Xingli Li, Jiasen Jin

We investigate the non-stationary phenomenon in a tripartite spin-1/2 system in the collision model (CM) framework. After introducing the dissipation through the system-environment collision for both Markovian and non-Markovian cases, we find the emergence of long-time oscillation in the dynamics of the system and the synchronization among subsystems. We con

Alexander Kamal, Roman Karasev

We show that the discrete versions of the systolic inequality that estimate the number of vertices of a simplicial complex from below have substantial applications to graphs, the one-dimensional simplicial complexes. Almost directly they provide good estimates for the number of vertices of a graph in terms of its chromatic number and the length of the smalle

Pengwei Yang, Amani Abusafia, Abdallah Lakhdari, Athman Bouguettaya

Crowdsourcing wireless energy services is a novel convenient alternative to charge IoT devices. We demonstrate peer-to-peer wireless energy services sharing between smartphones over a distance. Our demo leverages (1) a service-based technique to share energy services, (2) state-of-the-art power transfer technology over a distance, and (3) a mobile applicatio

Hongyi Yu, Ziheng Zhou, Wang Yao

In binary compound 2D insulators/semiconductors such as hexagonal boron nitride (hBN), the different electron affinities of atoms can give rise to out-of-plane electric polarizations across inversion asymmetric van der Waals interface of near 0-degree twist angles. Here we show that at a general stacking order where sliding breaks the in-plane C3 rotational

S. M. Kuzenko, E. S. N. Raptakis, G. Tartaglino-Mazzucchelli

The superspace formalism for $\mathcal{N}=1$ supergravity in four dimensions is a powerful geometric setting to engineer off-shell supergravity-matter theories, including higher-derivative couplings. This review provides a unified description of the three superspace approaches to $\mathcal{N}=1$ conformal supergravity: (i) conformal superspace; (ii) $\mathsf

Yudong Lu, Jian Zhao, Youpeng Zhao, Wengang Zhou

Card game AI has always been a hot topic in the research of artificial intelligence. In recent years, complex card games such as Mahjong, DouDizhu and Texas Hold'em have been solved and the corresponding AI programs have reached the level of human experts. In this paper, we are devoted to developing an AI program for a more complex card game, GuanDan, whose

Gali Sheffi, Pedro Ramalhete, Erez Petrank

Multi-Version Concurrency Control (MVCC) is a common mechanism for achieving linearizable range queries in database systems and concurrent data-structures. The core idea is to keep previous versions of nodes to serve range queries, while still providing atomic reads and updates. Existing concurrent data-structure implementations, that support linearizable ra

Xuanpei Zhai, Wenshuang Li, Fengying Wei, Xuerong Mao

We establish a stochastic HIV/AIDS model for the individuals with protection awareness and reveal how the protection awareness plays its important role in the control of AIDS. We firstly show that there exists a global positive solution for the stochastic model. By constructing Lyapunov functions, the ergodic stationary distribution when $R_{0}^{s}>1$ and th

Wei Shi, Jindan Xu, Wei Xu, Marco Di Renzo

This correspondence investigates a reconfigurable intelligent surface (RIS)-assisted wireless communication system with security threats. The RIS is deployed to enhance the secrecy outage probability (SOP) of the data sent to a legitimate user. By deriving the distributions of the received signal-to-noise-ratios (SNRs) at the legitimate user and the eavesdro

Shuvam Chakraborty, Gregory Hellbourg, Maqsood Careem, Dola Saha

The growing need for electromagnetic spectrum to support the next generation (xG) communication networks increasingly generate unwanted radio frequency interference (RFI) in protected bands for radio astronomy. RFI is commonly mitigated at the Radio Telescope without any active collaboration with the interfering sources. In this work, we provide a method of

D. M. Polishchuk, M. Persson, M. M. Kulyk, G. Baglioni

Ferromagnetic/antiferromagnetic bilayers are interfaced with normal metal/ferromagnetic bilayers to form F*/AF/N/F valves. The N-spacer thickness is chosen such that it mediates strong indirect exchange (RKKY) between the outer magnetic layers, which varies in strength/direction depending on the N thickness and in direction on switching F. The system exhibit

Chang-Yin Ji, Wenze Lan, Peng Fu, Gang Wang

Topological photonics has received extensive attention from researchers because it provides brand new physical principles to manipulate light. Band topology of optical materials is characterized using the Berry phase defined by Bloch states. Until now, the criteria for experimentally probing the topological phase transition of band topology has always been r

Ricky X. F. Chen

There is a growing interest in studying the distribution of certain labels in products of permutations since the work of Stanley addressing a conjecture of B\'{o}na. This paper is concerned with a problem in that direction. Let $D$ be a permutation on the set $[n]=\{1,2,\ldots, n\}$ and $E\subset [n]$. Suppose the maximum possible number of cycles uncontamin

Xingchen Song, Di Wu, Binbin Zhang, Zhiyong Wu

The recently proposed Conformer architecture which combines convolution with attention to capture both local and global dependencies has become the \textit{de facto} backbone model for Automatic Speech Recognition~(ASR). Inherited from the Natural Language Processing (NLP) tasks, the architecture takes Layer Normalization~(LN) as a default normalization tech

Taisuke Ochi, Masahiro Kamada, Takamoto Yokosawa, Kozo Mukai

Edge engineering is important for both fundamental research and applications as the device size decreases to nanometer scale. This is especially the case for graphene because a graphene edge shows totally different electronic properties depending on the atomic structure and the termination. It has recently been shown that an atomically precise zigzag edge ca

Shantanu Sardar, Amit Kuber

For the representation-theoretic study of domestic string algebras, Schr\"{o}er introduced a version of hammocks that are bounded discrete linear orders. He introduced a finite combinatorial gadget called the bridge quiver, which we modified in the prequel of this paper to get a variation called the arch bridge quiver. Here we use it as a tool to provide an

Zihao Tang, Xinyi Wang, Lihaowen Zhu, Mariano Cabezas

Diffusion Weighted Imaging (DWI) is an advanced imaging technique commonly used in neuroscience and neurological clinical research through a Diffusion Tensor Imaging (DTI) model. Volumetric scalar metrics including fractional anisotropy, mean diffusivity, and axial diffusivity can be derived from the DTI model to summarise water diffusivity and other quantit

Valery G. Rousseau

Nikola Tesla is often presented by his adepts as the "unjustly forgotten genius", without who our current technology wouldn't exist. In this paper, we analyze some popular statements made by Tesla's adepts, mostly about inventions that they attribute to him, and determine whether they are myth or reality.

S. A. Kadam, Jackson Levi Said, B. Mishra

In this paper, we have explored the field equations of f(T, B) gravity as an extension of teleparallel gravity in an isotropic and homogeneous space time. In the basic formalism developed, the dynamical parameters are derived by incorporating the power law and exponential scale factor function. The models are showing accelerating behaviour and approaches to

Junqing Xu, Kejun Li, Uyen N. Huynh, Jinsong Huang

Spintronics in halide perovskites has drawn significant attention in recent years, due to highly tunable spin-orbit fields and intriguing interplay with lattice symmetry. Spin lifetime -- a key parameter that determines the applicability of materials for spintronics and spin-based quantum information applications -- has been extensively measured in halide pe

Feng Zhu, Jingjing Zhang, Xin Wang

A major bottleneck of distributed learning under parameter-server (PS) framework is communication cost due to frequent bidirectional transmissions between the PS and workers. To address this issue, local stochastic gradient descent (SGD) and worker selection have been exploited by reducing the communication frequency and the number of participating workers a

Sayan Goswami

Inspired by the inductive proof of LYM-inequality given by P. Frankl, we provide an inductive proof of the Bollob\'{a}s two family theorem.

Zixuan Geng, Maximilian Schleich, Dan Suciu

Sophisticated machine models are increasingly used for high-stakes decisions in everyday life. There is an urgent need to develop effective explanation techniques for such automated decisions. Rule-Based Explanations have been proposed for high-stake decisions like loan applications, because they increase the users' trust in the decision. However, rule-based

Hilal Asi, Karan Chadha, Gary Cheng, John Duchi

In non-private stochastic convex optimization, stochastic gradient methods converge much faster on interpolation problems -- problems where there exists a solution that simultaneously minimizes all of the sample losses -- than on non-interpolating ones; we show that generally similar improvements are impossible in the private setting. However, when the funct

Mohammad R. Garousi

Using the most general higher-derivative field redefinition for the closed spacetime manifolds, we show that the tree-level couplings of the metric, $B$-field and dilaton at orders $\alpha'^2$ and $\alpha'^3$ that have been recently found by the T-duality, can be written in a particular scheme in terms of the torsional Riemann curvature ${\cal R}$ and the to

Shin'ichirou Yoshida

Rotation may affect the occurrence of sustainable hydrogen burning in very low-mass stellar objects by the introduction of centrifugal force to the hydrostatic balance as well as by the appearance of rotational break-up of the objects (mass-shedding limit) for rapidly rotating cases. We numerically construct the models of rotating very low-mass stellar objec

Wanxing Chang, Ye Shi, Hoang Duong Tuan, Jingya Wang

Universal Domain Adaptation (UniDA) aims to transfer knowledge from a source domain to a target domain without any constraints on label sets. Since both domains may hold private classes, identifying target common samples for domain alignment is an essential issue in UniDA. Most existing methods require manually specified or hand-tuned threshold values to det

Jia Zhao, Yu Qiao

In this paper, we develop the bialgebra theory for Lie-Yamaguti algebras. For this purpose, we exploit two types of compatibility conditions: local cocycle condition and double construction. We define the classical Yang-Baxter equation in Lie-Yamaguti algebras and show that a solution to the classical Yang-Baxter equation corresponds to a relative Rota-Baxte

Rajkumar Santra, Balaram Dey, Subinit Roy, R. Palit

The $\gamma$-gated proton spectra measured in the reactions $^{64}$Ni($^{9}$Be, p2n)$^{70}$Ga and $^{64}$Ni($^{9}$Be, pn)$^{71}$Ga, have been utilized to obtain the nuclear level density (NLD) of $^{71}$Ga and $^{72}$Ga nuclei by using the statistical model (SM) calculations. It is seen that the $\gamma$-gated proton spectrum are reasonably explained by usin

Matthew Palmer

In Diophantine approximation, Vaaler's theorem was an important partial result towards the Duffin--Schaeffer conjecture, which was open for almost eighty years before it was recently proven by Koukoulopoulos and Maynard. A version of this result was previously proven to also hold in imaginary quadratic fields: in this paper, we establish a version of Vaaler'

Takuya Ishihara, Daisuke Kurisu

This study examines the problem of determining whether to treat individuals based on observed covariates. The most common decision rule is the conditional empirical success (CES) rule proposed by Manski (2004), which assigns individuals to treatments that yield the best experimental outcomes conditional on the observed covariates. Conversely, using shrinkage

Samuel K. Grunblatt, Nicholas Saunders, Ashley Chontos, Soichiro Hattori

The fate of planets around rapidly evolving stars is not well understood. Previous studies have suggested that relative to the main sequence population, planets transiting evolved stars ($P$ $<$ 100 d) tend to have more eccentric orbits. Here we present the discovery of TOI-4582 b, a 0.94 $\pm$ 0.12 R$_\mathrm{J}$, 0.53 $\pm$ 0.05 M$_\mathrm{J}$ planet orbit

Ivan Danilenko

The affine Grassmannian associated to a reductive group $\mathbf{G}$ is an affine analogue of the usual flag varieties. It is a rich source of Poisson varieties and their symplectic resolutions. These spaces are examples of conical symplectic resolutions dual to the Nakajima quiver varieties. In this work, we study their quantum connection. We use the stable

Reza Khanmohammadi, Sari Saba-Sadiya, Sina Esfandiarpour, Tuka Alhanai

In this paper, we present Mambanet: a hybrid neural network for predicting the outcomes of Basketball games. Contrary to other studies, which focus primarily on season games, this study investigates playoff games. MambaNet is a hybrid neural network architecture that processes a time series of teams' and players' game statistics and generates the probability

Amites Dasgupta

We obtain Azuma bounds for the probabilities of being away from the limit for a class of urn models. The method consists of relating the variables to certain linear combinations using eigenvectors of the replacement matrix, thus bringing in appropriate martingales. Some cases of repeated eigenvalues are also considered using Jordan vectors.

Chien-Peng Ho, Khee-Kyun Voo

The antiferromagnetism (AFM) and chiral-d wave superconductivity (SC) in a honeycomb lattice close to an antiferromagnetic (AF) Mott state at half band filling are studied with a t-J model and slave boson mean field theory. The order parameters and single particle dispersion relations at different band filling fractions are investigated. It is found that the

Lei Kou, Chuang Liu, Guo-wei Cai, Jia-ning Zhou

In this study, the open-circuit faults diagnosis and location issue of the neutral-point-clamped (NPC) inverters are analysed. A novel fault diagnosis approach based on knowledge driven and data driven was presented for the open-circuit faults in insulated-gate bipolar transistors (IGBTs) of NPC inverter, and Concordia transform (knowledge driven) and random

William Setterberg, Lindsay Glesener, Demoz Gebre Egziabher, John G. Sample

Solar flares are some of the most energetic events in the solar system and can be studied to investigate the physics of plasmas and stellar processes. One interesting aspect of solar flares is the presence of accelerated (nonthermal) particles, whose signatures appear in solar flare hard X-ray emissions. Debate has been ongoing since the early days of the sp

Yuta Takahashi, Kiwamu Watanabe

In characteristic $0$, the Campana-Peternell conjecture claims that the only smooth Fano variety with nef tangent bundle should be homogeneous. In this paper, we study the positive characteristic version of the Campana-Peternell conjecture. In particular, we give an affirmative answer for Fano $4$-folds with nef tangent bundle and Picard number greater than

Bhargav Annem, Sergey Khoperskov

At least one major merger is currently taking place in the MW. The Sgr dwarf spheroidal galaxy is being tidally destroyed while orbiting around the MW, whose close passages perturb the MW disc externally. In this work, using a series of hydrodynamical simulations, we investigate how massive dwarf galaxies on quasi-polar Sgr-like orbits impact the star format

Farhad Aghili

This paper presents a unified approach for inverse and direct dynamics of constrained multibody systems that can serve as a basis for analysis, simulation, and control. The main advantage of the formulation of the dynamic is that it does not require the constraint equations to be linearly independent. Thus, a simulation may proceed even in the presence of re

Won-Seok Choi, Dong-Sig Han, Hyundo Lee, Junseok Park

In Self-Supervised Learning (SSL), it is known that frequent occurrences of the collision in which target data and its negative samples share the same class can decrease performance. Especially in real-world data such as crawled data or robot-gathered observations, collisions may occur more often due to the duplicates in the data. To deal with this problem,

Gege Wen, Zongyi Li, Qirui Long, Kamyar Azizzadenesheli

Carbon capture and storage (CCS) plays an essential role in global decarbonization. Scaling up CCS deployment requires accurate and high-resolution modeling of the storage reservoir pressure buildup and the gaseous plume migration. However, such modeling is very challenging at scale due to the high computational costs of existing numerical methods. This chal

Haiyong Gu, Ying-nan Mao, Hao Sun, Kechen Wang

We utilize the lepton number violation signal process $p\, e^- \to \tau^+ jjj$ to search for heavy Majorana neutrinos at future proton-electron colliders. The LHeC (FCC-eh) is considered to run with an electron beam energy of 60 GeV, a proton beam energy of 7 (50) TeV and an integrated luminosity of 1 (3) ab$^{-1}$, and the electron beam is considered to be

Zhong Meng, Tongzhou Chen, Rohit Prabhavalkar, Yu Zhang

Text-only adaptation of a transducer model remains challenging for end-to-end speech recognition since the transducer has no clearly separated acoustic model (AM), language model (LM) or blank model. In this work, we propose a modular hybrid autoregressive transducer (MHAT) that has structurally separated label and blank decoders to predict label and blank d

Ou Na, Zecheng Zhang, Guang Lin

This paper proposes a replica exchange preconditioned Langevin diffusion discretized by the Crank-Nicolson scheme (repCNLD) to handle high-dimensional and multi-modal distribution problems. Sampling from high-dimensional and multi-modal distributions is a challenging question. The performance of many standard MCMC chains deteriorates as the dimension of para

Ruoyang Liu, Chenhan Wei, Yixiong Yang, Wenxun Wang

Data quantization is an effective method to accelerate neural network training and reduce power consumption. However, it is challenging to perform low-bit quantized training: the conventional equal-precision quantization will lead to either high accuracy loss or limited bit-width reduction, while existing mixed-precision methods offer high compression potent

Yu Guo, Zixuan Liu, Hao Tang, Xiao-Min Hu

Quantum theory allows information to flow through a single device in a coherent superposition of two opposite directions, resulting into situations where the input-output direction is indefinite. Here we introduce a theoretical method to witness input-output indefiniteness in a single quantum device, and we experimentally demonstrate it by constructing a pho

Nathan R. Sandford, David H. Weinberg, Daniel R. Weisz, Sal Wanying Fu

We present novel constraints on the underlying galaxy formation physics (e.g., mass loading factor, star formation history, metal retention) at $z\gtrsim7$ for the low-mass ($M_*\sim10^5$ M$_\odot$) Local Group ultra-faint dwarf galaxy (UFD) Eridanus {\sc II} (Eri II). Using a hierarchical Bayesian framework, we apply a one-zone chemical evolution model to E

Anton Chudaykin, Mikhail M. Ivanov

We present the effective-field theory (EFT)-based cosmological full-shape analysis of the anisotropic power spectrum of eBOSS quasars at the effective redshift $z_{\rm eff}=1.48$. We perform extensive tests of our pipeline on simulations, paying a particular attention to the modeling of observational systematics, such as redshift smearing, fiber collisions,

Ya Ju Fan, Jonathan E. Allen, Kevin S. McLoughlin, Da Shi

Neural Network (NN) models provide potential to speed up the drug discovery process and reduce its failure rates. The success of NN models require uncertainty quantification (UQ) as drug discovery explores chemical space beyond the training data distribution. Standard NN models do not provide uncertainty information. Methods that combine Bayesian models with

Ning Ning

Markov chain Monte Carlo (MCMC) algorithms have played a significant role in statistics, physics, machine learning and others, and they are the only known general and efficient approach for some high-dimensional problems. The random walk Metropolis (RWM) algorithm as the most classical MCMC algorithm, has had a great influence on the development and practice

Hanwei Xu, Yujun Chen, Yulun Du, Nan Shao

Prompt-based techniques have demostrated great potential for improving the few-shot generalization of pretrained language models. However, their performance heavily relies on the manual design of prompts and thus requires a lot of human efforts. In this paper, we introduce Genetic Prompt Search (GPS) to improve few-shot learning with prompts, which utilizes

Jia Li, Ge Li, Zhuo Li, Zhi Jin

Developers often perform repetitive code editing activities for various reasons (e.g., code refactoring) during software development. Pre-trained code editing models have achieved the state-of-the-art (SOTA) results. Pre-trained models are first pre-trained with pre-training tasks and fine-tuned with the code editing task. Existing pre-training tasks mainly

Litian Li, Zheng Yang, Ronggang Wang

Benefit from flexible network designs and end-to-end joint optimization approach, learned image compression (LIC) has demonstrated excellent coding performance and practical feasibility in recent years. However, existing compression models suffer from serious multi-generation loss, which always occurs during image editing and transcoding. During the process

Yixiao Gao, Junyang Ge, Shengzhi Sun, Xiang Shen

Creating nonradiating dark modes is key to achieving high-Q resonance in dielectric open cavities. The concept of photonic bound states in the continuum (BIC) offers an efficient method to suppress radiative loss through symmetry engineering. Structural reflection symmetry (RS) has been widely utilized to construct BICs in asymmetric metasurfaces. In this pa

Ramin Ayanzadeh, Narges Alavisamani, Poulami Das, Moinuddin Qureshi

Quantum Approximate Optimization Algorithm (QAOA) is one of the leading candidates for demonstrating the quantum advantage using near-term quantum computers. Unfortunately, high device error rates limit us from reliably running QAOA circuits for problems with more than a few qubits. In QAOA, the problem graph is translated into a quantum circuit such that ev

Dhananjay Thiruvady, Su Nguyen, Yuan Sun, Fatemeh Shiri

Transporting ore from mines to ports is of significant interest in mining supply chains. These operations are commonly associated with growing costs and a lack of resources. Large mining companies are interested in optimally allocating their resources to reduce operational costs. This problem has been previously investigated in the literature as resource con

Vanya Bannihatti Kumar

Grammar Error Correction(GEC) mainly relies on the availability of high quality of large amount of synthetic parallel data of grammatically correct and erroneous sentence pairs. The quality of the synthetic data is evaluated on how well the GEC system performs when pre-trained using it. But this does not provide much insight into what are the necessary facto

Frederic Latour, Oscar Perdomo

The Clifford group is the set of gates generated by controlled-Z gates, the phase gate and the Hadamard gate. We will say that a n-qubit state is a Clifford state if it can be prepared using Clifford gates. These states are known as the stabilizer states and they arise in quantum error correction. In this paper we study the set of all 5-qubit Clifford states

A. M. Michalik, F. Marsiglio

Resonant transmission occurs when constructive interference results in the complete passage of an incoming wave through an array of barriers. In this paper we explore such a scenario with one dimensional models. We adopt wave packets with finite width to illustrate the deterioration of resonance with decreasing wave packet width, and suggest an approximate w

Han-Yi Wang, Wei-Yong Zhang, Zhi-Yuan Yao, Ying Liu

Gauge theory and thermalization are both foundations of physics and nowadays are both topics of essential importance for modern quantum science and technology. Simulating lattice gauge theories (LGTs) realized recently with ultracold atoms provides a unique opportunity for carrying out a correlated study of gauge theory and thermalization in the same setting

Cui-Xian Guo, Shu Chen, Kun Ding, Haiping Hu

Defective spectral degeneracy, known as exceptional point (EP), lies at the heart of various intriguing phenomena in optics, acoustics, and other nonconservative systems. Despite extensive studies in the past two decades, the \textit{collective} behaviors (e.g., annihilation, coalescence, braiding, etc.) involving multiple exceptional points or lines and the

Yugo Fujimoto, Kei Nakagawa, Kentaro Imajo, Kentaro Minami

Machine learning is an increasingly popular tool with some success in predicting stock prices. One promising method is the Trader-Company~(TC) method, which takes into account the dynamism of the stock market and has both high predictive power and interpretability. Machine learning-based stock prediction methods including the TC method have been concentratin

Jia Li, Zhuo Li, Huangzhao Zhang, Ge Li

In the software engineering community, deep learning (DL) has recently been applied to many source code processing tasks. Due to the poor interpretability of DL models, their security vulnerabilities require scrutiny. Recently, researchers have identified an emergent security threat, namely poison attack. The attackers aim to inject insidious backdoors into

Thy Nguyen, Anamay Chaturvedi, Huy Lê Nguyen

We consider the problem of clustering in the learning-augmented setting, where we are given a data set in $d$-dimensional Euclidean space, and a label for each data point given by an oracle indicating what subsets of points should be clustered together. This setting captures situations where we have access to some auxiliary information about the data set rel

Kun Wei, Long Zhou, Ziqiang Zhang, Liping Chen

Direct speech-to-speech translation (S2ST) is an attractive research topic with many advantages compared to cascaded S2ST. However, direct S2ST suffers from the data scarcity problem because the corpora from speech of the source language to speech of the target language are very rare. To address this issue, we propose in this paper a Speech2S model, which is

Kyungmin Kim

In a recent search (Kim et al. 2022), we looked for microlensing signature in gravitational waves from spectrograms of the binary black hole events in the first and second gravitational-wave transient catalogs. For the search, we have implemented a deep learning-based method (Kim et al. 2021) and figured out that one event, GW190707 093326, out of forty-six

Abdul Muneem, Junya Yoshida, Hiroyuki Ekawa, Masahiro Hino

Neutron imaging is a non-destructive inspection technique with a wide range of applications. One of the important aspects concerning neutron imaging is achieving micrometer-scale spatial resolution. Developing a neutron detector with a high resolution is a challenging task. Neutron detectors, based on fine-grained nuclear emulsion, may be suitable for high r

Yi Chen, Zheng Chang, Geyong Min, Shiwen Mao

IoT devices recently are utilized to detect the state transition in the surrounding environment and then transmit the status updates to the base station for future system operations. To satisfy the stringent timeliness requirement of the status updates for the accurate system control, age of information (AoI) is introduced to quantify the freshness of the se

Joseph Kraisler, Wei Li, Kui Ren, John C. Schotland

This work considers the propagation of high-frequency waves in highly-scattering media where physical absorption of a nonlinear nature occurs. Using the classical tools of the Wigner transform and multiscale analysis, we derive semilinear radiative transport models for the phase-space intensity and the diffusive limits of such transport models. As an applica

Haoran Ji, Yanan Li, Yi Liu, Xiang Ding

The infinite-layer nickelates, isostructural to the high-Tc superconductor cuprates, have risen as a promising platform to host unconventional superconductivity and stimulated growing interests in the condensed matter community. Despite numerous researches, the superconducting pairing symmetry of the nickelate superconductors, the fundamental characteristic

Mitchell Schneider, Muhammed Zuboraj, Valery Dolgashev, John J Lewellen

We report the results of high gradient testing of two single cell off axis coupled standing wave accelerating structures. Two brazed standing wave side coupled structures with the same geometry were tested one made of pure copper Cu and one made of a copper silver CuAg alloy with silver concentration of 0.08 percent. A peak surface electric field of 450 MV p

Peter Kagey

We discuss efficient methods for unranking derangements and m\'enage permutations. That is, we will provide an algorithm to efficiently extract the $k$-th earliest such permutation under the lexicographic ordering. We will show that this problem can be reduced to the problem of computing the number of restricted permutations with a given prefix, and then we

Hangfeng He, Weijie J. Su

While deep learning has enabled significant advances in many areas of science, its black-box nature hinders architecture design for future artificial intelligence applications and interpretation for high-stakes decision makings. We addressed this issue by studying the fundamental question of how deep neural networks process data in the intermediate layers. O

Takao Komatsu

Let $a_1,a_2,\dots,a_k$ be positive integers with $\gcd(a_1,a_2,\dots,a_k)=1$. Frobenius number is the largest positive integer that is NOT representable in terms of $a_1,a_2,\dots,a_k$. When $k\ge 3$, there is no explicit formula in general, but some formulae may exist for special sequences $a_1,a_2,\dots,a_k$, including, those forming arithmetic progressio

Apurba Bera, Nissim Kanekar, Jayaram N. Chengalur, Jasjeet S. Bagla

The neutral atomic hydrogen (HI) mass function (HIMF) describes the distribution of the HI content of galaxies at any epoch; its evolution provides an important probe of models of galaxy formation and evolution. Here, we report Giant Metrewave Radio Telescope HI 21cm spectroscopy of blue star-forming galaxies at $z\approx0.20-0.42$ in the Extended Groth Stri