May 2022 arXiv papers — page 110

Mourad E. H. Ismail, Ruiming Zhang, Keru Zhou

We study two families of orthogonal polynomials. The first is a finite family related to the Askey-Wilson polynomials but the orthogonality is on the real line. A limiting case of this family is an infinite system of orthogonal polynomials whose moment problem is indeterminate. We provide several orthogonality measures for the infinite family and derive thei

Ruyu Yang

In recent years, machine learning methods have been used to assist scientists in scientific research. Human scientific theories are based on a series of concepts. How machine learns the concepts from experimental data will be an important first step. We propose a hybrid method to extract interpretable physical concepts through unsupervised machine learning.

Zeinab Kalantari, Sohrab Rahvar, Alaa Ibrahim

Gravitational lensing of gamma-ray bursts (GRBs) can provide an opportunity to probe the massive compact objects in the universe at different redshifts. We have discovered two consecutive pulses in the light curve of GRB 090717034, with the same temporal profile and different count rate, separated by a time interval, which is identified as gravitationally le

Xu Cao, Xiaoye Li, Liya Ma, Yi Huang

Movement and pose assessment of newborns lets experienced pediatricians predict neurodevelopmental disorders, allowing early intervention for related diseases. However, most of the newest AI approaches for human pose estimation methods focus on adults, lacking publicly benchmark for infant pose estimation. In this paper, we fill this gap by proposing infant

Jun-Yao Xu, Zheng-Zheng Li, Bao-Hua Sun, Yi-Fei Niu

The nuclear symmetry energy plays a key role in determining the equation of state (EoS) of dense, neutron-rich matter, which connects the atomic nuclei with the hot and dense matter in universe, thus has been the subject of intense investigations in laboratory experiments, astronomy observations and theories. Various probes have been proposed to constrain th

Nam-Jin Park, Seong-Ho Kwon, Yoo-Bin Bae, Byeong-Yeon Kim

This paper presents several conditions to determine strong sign controllability for diffusively-coupled undirected networks. The strong sign controllability is determined by the sign patterns (positive, negative, zero) of the edges. We first provide the necessary and sufficient conditions for strong sign controllability of basic components, such as path, cyc

S. Ganesamurthy, J. Jeyaranjan, R. Srimathi

In this paper, we consider the connected power domination number ($\gamma_{P, c}$) of three standard graph products. The exact value for $\gamma_{P, c}(G\circ H)$ is obtained for any two non-trivial graphs $G$ and $H.$ Further, tight upper bounds are proved for the connected power domination number of the Cartesian product of two graphs $G$ and $H.$ Conseque

Hossein Parineh, Nasser Mozayani

Protein Structure Prediction (PSP) is an unsolved problem in the field of computational biology. The problem of protein structure prediction is about predicting the native conformation of a protein, while its sequence of amino acids is known. Regarding processing limitations of current computer systems, all-atom simulations for proteins are typically unpract

Raymond Cheng

Traditional algebraic geometric invariants lose some of their potency in positive characteristic. For instance, smooth projective hypersurfaces may be covered by lines despite being of arbitrarily high degree. The purpose of this dissertation is to define a class of hypersurfaces that exhibits such classically unexpected properties, and to offer a perspectiv

Ahmad Esmaeili, Zahra Ghorrati, Eric Matson

Hyper-parameter Tuning is among the most critical stages in building machine learning solutions. This paper demonstrates how multi-agent systems can be utilized to develop a distributed technique for determining near-optimal values for any arbitrary set of hyper-parameters in a machine learning model. The proposed method employs a distributedly formed hierar

Ryo Takenaka

Let $\tilde{\mathfrak{g}}$ be the affine Lie algebra of type $A_{2l}^{(2)}$. The integrable highest weight $\tilde{\mathfrak{g}}$-module $L(k\Lambda_0)$ called the standard $\tilde{\mathfrak{g}}$-module is realized by a tensor product of the twisted module $V_L^T$ for the lattice vertex operator algebra $V_L$. By using such vertex algebraic construction, we

Yu-Ming Shang, Heyan Huang, Xin Sun, Wei Wei

Extracting relational triples from unstructured text is an essential task in natural language processing and knowledge graph construction. Existing approaches usually contain two fundamental steps: (1) finding the boundary positions of head and tail entities; (2) concatenating specific tokens to form triples. However, nearly all previous methods suffer from

Maria Teresa Llano, Mark d'Inverno, Matthew Yee-King, Jon McCormack

Human collaboration with systems within the Computational Creativity (CC) field is often restricted to shallow interactions, where the creative processes, of systems and humans alike, are carried out in isolation, without any (or little) intervention from the user, and without any discussion about how the unfolding decisions are taking place. Fruitful co-cre

Wei Wang, Wei Zhang

Intelligent reflecting surface (IRS) is envisioned to change the paradigm of wireless communications from "adapting to wireless channels" to "changing wireless channels". However, current IRS configuration schemes, consisting of sub-channel estimation and passive beamforming in sequence, conform to the conventional model-based design philosophies and are dif

Toby Walsh

We propose an alternative to the Turing test that removes the inherent asymmetry between humans and machines in Turing's original imitation game. In this new test, both humans and machines judge each other. We argue that this makes the test more robust against simple deceptions. We also propose a small number of refinements to improve further the test. These

Abeer Al Ahmadieh, Cynthia Vinzant

In this paper we explore determinantal representations of multiaffine polynomials and consequences for the image of various spaces of matrices under the principal minor map. We show that a real multiaffine polynomial has a definite Hermitian determinantal representation if and only if all of its so-called Rayleigh differences factor as Hermitian squares and

Dan Barbasch, Jia-Jun Ma, Binyong Sun, Chen-Bo Zhu

Let $G$ be a real reductive group in Harish-Chandra's class. We derive some consequences of theory of coherent continuation representations to the counting of irreducible representations of $G$ with a given infinitesimal character and a given bound of the complex associated variety. When $G$ is a real classical group (including the real metaplectic group), w

Michael Carl Tschantz

The near universal condemnation of proxy discrimination hides a disagreement over what it is. This work surveys various notions of proxy and proxy discrimination found in prior work and represents them in a common framework. These notions variously turn on statistical dependencies, causal effects, and intentions. It discusses the limitations and uses of each

Mengshun Hu, Kui Jiang, Liang Liao, Jing Xiao

Spatial-Temporal Video Super-Resolution (ST-VSR) aims to generate super-resolved videos with higher resolution(HR) and higher frame rate (HFR). Quite intuitively, pioneering two-stage based methods complete ST-VSR by directly combining two sub-tasks: Spatial Video Super-Resolution (S-VSR) and Temporal Video Super-Resolution(T-VSR) but ignore the reciprocal r

Samuel Ewan Rannala, Andrea Meo, Sergiu Ruta, Wasan Pantasri

Micromagnetic modelling provides the ability to simulate large magnetic systems accurately without the computational cost limitation imposed by atomistic modelling. Through micromagnetic modelling it is possible to simulate systems consisting of thousands of grains over a time range of nanoseconds to years, depending upon the solver used. Here we present the

Hiroki Tanabe, Ellen H. Fukuda, Nobuo Yamashita

Convex-composite optimization, which minimizes an objective function represented by the sum of a differentiable function and a convex one, is widely used in machine learning and signal/image processing. Fast Iterative Shrinkage Thresholding Algorithm (FISTA) is a typical method for solving this problem and has a global convergence rate of $O(1 / k^2)$. Recen

Eduardo I. Guendelman, Zeeya Merali

String tension fundamentally determines the properties of strings; yet its value is often assigned arbitrarily, creating a fine-tuning problem. We describe a mechanism for dynamically generating string tension in a flat or almost flat spacetime, using the modified measures formalism, which in turn naturally generates a new type of stringy brane-world scenari

Xue-Chao Feng, Ke-Wei Wei

Based on the relations from the meson-meson mass mixing matrix, the mixing angles of isoscalar state have been re-evaluated via mass relations and latest experimental results. The results in the present work are compared with the values from different theoretical models, meanwhile, the quarkonia content of isoscalar state are presented. In order to check the

Xiaoni Zhang, Yuki Tsujikawa, Ikuma Tateishi, Masahito Niibe

We systematically investigated electronic evolutions of non-symmorphic borophene with chemical environments that were realized by the ion exchange method. Electronic structures can be characterized by the topological $Z_2$ invariant. Spectroscopic experiments and DFT calculations unveiled that a sheet of hydrogenated borophene (borophane) is the Dirac nodal

Jeong Hwan Lee, Myung Gyoon Lee, Jae Yeon Mun, Brian S. Cho

Jellyfish galaxies are an excellent tool to investigate the short-term effects of ram pressure stripping (RPS) on star formation in cluster environments. It has been thought that the star formation activity of jellyfish galaxies may depend on the host cluster properties, but previous studies have not yet found a clear correlation. In this study, we estimate

Peter J. Forrester, Anthony Mays

Considered are the large $N$, or large intensity, forms of the distribution of the length of the longest increasing subsequences for various models. Earlier work has established that after centring and scaling, the limit laws for these distributions relate to certain distribution functions at the hard edge known from random matrix theory. By analysing the ha

Ben Hutchinson, Negar Rostamzadeh, Christina Greer, Katherine Heller

Forming a reliable judgement of a machine learning (ML) model's appropriateness for an application ecosystem is critical for its responsible use, and requires considering a broad range of factors including harms, benefits, and responsibilities. In practice, however, evaluations of ML models frequently focus on only a narrow range of decontextualized predicti

Qin Tan, Wen-Di Guo, Yu-Xiao Liu

In this work, we investigate the quasinormal modes of a thick brane system. Considering the transverse-traceless tensor perturbation of the brane metric, we obtain the Schr\"odinger-like equation of the Kaluza-Klein modes of the tensor perturbation. Then we use the Wentzel-Kramers-Brillouin approximation and the asymptotic iteration method to solve this Schr

Kentarou Wada, Takeshi Kurosawa

We generalize the na\"ive estimator of a Poisson regression model with measurement errors as discussed in Kukush et al. [1]. The explanatory variable is not always normally distributed as they assume. In this study, we assume that the explanatory variable and measurement error are not limited to a normal distribution. We clarify the requirements for the exis

Yulia Klevtsova

The paper is concerned with a nonlinear system of partial differential equations with parameters and the random external force. This system describes the two-layer quasi-solenoidal Lorenz model for a baroclinic atmosphere on a rotating two-dimensional sphere. The stationary measures for the Markov semigroup defined by the solutions of the Cauchy problem for

Yuki Yamamoto

Let $F$ be a non-archimedean local field. For any irreducible representation $\pi$ of an inner form $G'=\mathrm{GL}_{m}(D)$ of $G=\mathrm{GL}_{N}(F)$, there exists an irredubile representation of a maximal compact open subgroup in $G'$ which is also a type for $\pi$. Then we can consider the problem whether these types are unique or not in some sense. If suc

Wucheng Zhang, Ilia Tutunnikov, Ilya Sh. Averbukh, Roman V. Krems

We consider a quantum system with a time-independent Hamiltonian parametrized by a set of unknown parameters $\alpha$. The system is prepared in a general quantum state by an evolution operator that depends on a set of unknown parameters $P$. After the preparation, the system evolves in time, and it is characterized by a time-dependent observable ${\cal O}(t

Hao Ren, Xiaojun Liang, Chunhua Yang, Zhiwen Chen

Thank you very much for the attention and concern of colleagues and scholars in this work. With the comments and guidance of experts, editors, and reviewers, this work has been accepted for publishing in the journal "Process Safety and Environmental Protection". The theme of this paper relies on the Spatial-temporal associations of numerous variables in the

Dimitris Stripelis, Umang Gupta, Hamza Saleem, Nikhil Dhinagar

The amount of biomedical data continues to grow rapidly. However, collecting data from multiple sites for joint analysis remains challenging due to security, privacy, and regulatory concerns. To overcome this challenge, we use Federated Learning, which enables distributed training of neural network models over multiple data sources without sharing data. Each

W. W. Wasserman, R. A. Harrison, G. I. Harris, A. Sawadsky

We demonstrate a hermetically sealed packaging system for integrated photonic devices at cryogenic temperatures with plug-and-play functionality. This approach provides the ability to encapsulate a controlled amount of gas into the optical package allowing helium to be used as a heat-exchange gas to thermalize photonic devices, or condensed into a superfluid

Shuhan Qi, Shuhao Zhang, Xiaohan Hou, Jiajia Zhang

Multi-agent reinforcement learning for incomplete information environments has attracted extensive attention from researchers. However, due to the slow sample collection and poor sample exploration, there are still some problems in multi-agent reinforcement learning, such as unstable model iteration and low training efficiency. Moreover, most of the existing

Kyosuke Nishibiro

Polycosecant numbers and polycotangent numbers are introduced as level two analogues of poly-Bernoulli numbers. It is shown that polycosecant numbers and polycotangent numbers satisfy many formulas similar to those of poly-Bernoulli numbers. However, there is much unknown about polycotangent numbers. For example, the zeta function interpolating them at non-p

Naoyuki Hirata, Ren Ikeya

Asteroid (162173) Ryugu was the first spinning-top-shaped asteroid to be closely approached by a probe, the Hayabusa2 spacecraft, which sent numerous high-resolution images of Ryugu to the Earth and revealed the nature of this type of asteroid. One of the notable features of Ryugu is the equatorial ridge, which is considered the result of rapid spin in the p

Dessislava H. Kochloukova, Stefano Vidussi

We prove some conditions for the existence of higher dimensional algebraic fibering of group extensions. This leads to various corollaries on incoherence of groups and some geometric examples of algebraic fibers of type $F_n$ but not $FP_{n+1}$ of some groups including pure braid groups and families of poly-surface groups that are fundamental groups of compl

Mengqi He, Jing Zhang, Wenxin Yu

The success of fully supervised saliency detection models depends on a large number of pixel-wise labeling. In this paper, we work on bounding-box based weakly-supervised saliency detection to relieve the labeling effort. Given the bounding box annotation, we observe that pixels inside the bounding box may contain extensive labeling noise. However, as a larg

Zihua Guo, Chunyan Huang, Liang Song

In this note, we prove pointwise decay in time of solutions to the 3D energy-critical nonlinear Schr\"odinger equations assuming data in $L^1\cap H^3$. The main ingredients are the boundness of the Schr\"odinger propagators in Hardy space due to Miyachi \cite{Miyachi} and a fractional Leibniz rule in the Hardy space. We also extend the fractional chain rule

Heng Pan, Penglai Cui, Zhenyu li, Ru Jia

Deep learning has been used in a wide range of areas and made a huge breakthrough. With the ever-increasing model size and train-ing data volume, distributed deep learning emerges which utilizes a cluster to train a model in parallel. Unfortunately, the performance is often far from linear speedup due to the communication overhead between cluster nodes. To a

Yan Li, Gen Li, Kun Chen

In recent years microbiome studies have become increasingly prevalent and large-scale. Through high-throughput sequencing technologies and well-established analytical pipelines, relative abundance data of operational taxonomic units and their associated taxonomic structures are routinely produced. Since such data can be extremely sparse and high dimensional,

Kai Xiao, Xiang Zhou, Jaehyung Ju

The recent development of modular origami structures has ushered in a new era for active metamaterials with multiple degrees of freedom (multi-DOF). Notably, no systematic inverse design approach for volumetric modular origami structures has been reported. Moreover, very few topologies of modular origami have been studied for the design of active metamateria

Yilun Guan, Arthur Kosowsky

A claimed detection of cosmological tensor perturbations from inflation via B-mode polarization of the cosmic microwave background requires distinguishing other possible B-mode sources. One such potential source of confusion is primordial magnetic fields. For sufficiently low-amplitude B-mode signals, the microwave background temperature and polarization pow

Geoff Boeing, Carl Higgs, Shiqin Liu, Billie Giles-Corti

Benchmarking and monitoring urban design and transport features is critical to achieving local and international health and sustainability goals. However, most urban indicator frameworks use coarse spatial scales that only allow between-city comparisons or require expensive, technical, local spatial analyses for within-city comparisons. This study developed

Tatsumasa Suzuki

The pochette surgery, which was discovered by Iwase and Matsumoto, is a generalization of the Gluck surgery. In this paper we construct infinitely many embeddings of a pochette into the 4-sphere and prove that homotopy 4-spheres obtained from surgeries along these embedded pochettes are all diffeomorphic to the 4-sphere.

Naoto Dainobu

Let $p$ be an odd prime number and $f$ a modular form. We consider the $\mathbb{F}_p$-valued Galois representation $\bar{\rho}_f$ attached to $f$ and its twist $\bar{\rho}_{f, D}$ by the quadratic character $\chi_D$ corresponding to a quadratic discriminant $D$. We define $K_{f, D}$ to be the field corresponding to the kernel of $\bar{\rho}_{f, D}$. In this

Benjamin Proudfoot, Darin Ragozzine

Dozens of families of asteroids in the asteroid belt have similar orbits and compositions because they formed through a collision. However, the icy debris beyond the orbit of Neptune, called the Kuiper Belt, contains only one known family, the Haumea family. So far, no self-consistent explanation for the formation of the Haumea family can match all geophysic

Taotao Cai, Qi Lei, Quan Z. Sheng, Shuiqiao Yang

Influence Maximization (IM), which aims to select a set of users from a social network to maximize the expected number of influenced users, has recently received significant attention for mass communication and commercial marketing. Existing research efforts dedicated to the IM problem depend on a strong assumption: the selected seed users are willing to spr

Leonardo Giani, Tamara M. Davis

If Dark Matter halos possess the gravitational equivalent of an intrinsic magnetic spin, a formal analogy exists between the low redshift behaviour of the Cosmic Web in a flat FLRW background, and a crystal of spins submerged in a thermal reservoir with temperature $T \propto H(t)$. We argue that, within the use of the Bianchi type IX geometry to describe th

Jun Shi, Enke Wang, Qian Wang

Recently, LHCb observed a double-charmed tetraquark candidate $T_{cc}^+$ and claimed its isospin to be zero due to the absence of $T_{cc}^{++}$. However, the absence of the $T_{cc}^{++}$ in LHCb may be due to their low production in $pp$ collisions, thus the isospin of $T_{cc}^+$ still needs to be clarified. We propose an efficient way to investigate the iso

G. Grissonnanche, O. Cyr-Choinière, J. Day, R. Liang

Electronic nematicity is the spontaneous loss of rotational symmetry in a metal, without breaking translational symmetry. In the cuprate superconductors, there is experimental evidence for nematicity, but its origin remains unclear. Here we investigate the onset of nematicity in the transport of charge by means of electric and thermoelectric measurements in

Alexander Olshanskii, Vladimir Shpilrain

The worst-case complexity of group-theoretic algorithms has been studied for a long time. Generic-case complexity, or complexity on random inputs, was introduced and studied relatively recently. In this paper, we address the average-case time complexity of the word problem in several classes of groups and show that it is often the case that the average-case

XMASS Collaboration, K. Abe, K. Hiraide, K. Ichimura

A search for the neutrinoless quadruple beta decay of $^{136}$Xe was conducted with the liquid-xenon detector XMASS-I using $\rm 327\; kg \times 800.0 \; days$ of the exposure. The pulse shape discrimination based on the scintillation decay time constant which distinguishes $\gamma$-rays including the signal and $\beta$-rays was used to enhance the search se

Jordan Erskine, Chris Lehnert

Many hierarchical reinforcement learning algorithms utilise a series of independent skills as a basis to solve tasks at a higher level of reasoning. These algorithms don't consider the value of using skills that are cooperative instead of independent. This paper proposes the Cooperative Consecutive Policies (CCP) method of enabling consecutive agents to coop

Nicolás Valenzuela

The fractional Laplacian has been strongly studied during past decades. In this paper we present a different approach for the associated Dirichlet problem, using recent deep learning techniques. In fact, intensively PDEs with a stochastic representation have been understood via neural networks, overcoming the so-called curse of dimensionality. Among these eq

Sungkweon Hong, Brian C. Williams

Stochastic sequential decision making often requires hierarchical structure in the problem where each high-level action should be further planned with primitive states and actions. In addition, many real-world applications require a plan that satisfies constraints on the secondary costs such as risk measure or fuel consumption. In this paper, we propose a hi

Jiachen Lian, Chunlei Zhang, Gopala Krishna Anumanchipalli, Dong Yu

Disentangling content and speaking style information is essential for zero-shot non-parallel voice conversion (VC). Our previous study investigated a novel framework with disentangled sequential variational autoencoder (DSVAE) as the backbone for information decomposition. We have demonstrated that simultaneous disentangling content embedding and speaker emb

Yongle Yu, Hailin Luo

We report a counter-intuitive self-heating effect of helium-4 superflow. This fundamentally unusual heating effect bears a phenomenological resemblance to the Peltier effect of electric current across two different conductors. It reveals that helium-4 superflow carries thermal energy and entropy, which is in contrast to the two-fluid model of superfluid heli

Robert Polski, Yiran Zhang, Yang Peng, Harpreet Singh Arora

Twisted bilayer graphene (TBG) near the magic twist angle of $\sim1.1^{o}$ exhibits a rich phase diagram. However, the interplay between different phases and their dependence on twist angle is still elusive. Here, we explore the stability of various TBG phases and demonstrate that superconductivity near filling of two electrons per moir\'e unit cell alongsid

Sooyoung Park, Meung Ho Seo, Ryun Ah Kim, D. Cho

We report our experiment on sideband cooling with two Raman transitions in a $\Lambda$ configuration that allows selective coherent population trapping (CPT) of the motional ground state. The cooling method is applied to $^{87}$Rb atoms in a circularly-polarized one-dimensional optical lattice. Owing to the vector polarizability, the vibration frequency of a

Naoyuki Hirata, Noriyuki Namiki, Fumi Yoshida, Koji Matsumoto

Asteroid 162173 Ryugu is a rubble-pile asteroid, whose top-shape is compatible with models of deformation by spin up. Rims of major craters on Ryugu have an east-west asymmetric profile; their western crater rims are sharp and tall, while their eastern crater rims are rounded and low. Although there are various possible explanations, we theoretically assess

Ulrik Egede, Shohei Nishida, Mitesh Patel, Marie-Hélène Schune

In the past decade, electroweak penguin decays have provided a number of precision measurements, turning into one of the most competitive ways to search for New Physics that describe beyond the Standard Model phenomena. An overview of the measurements made at the $B$ factories and hadron colliders are given and the experimental methods are presented. Experim

Naoyuki Hirata, Ryo Suetsugu, Keiji Ohtsuki

Furrows are a concentric system of tectonic troughs, and are the oldest recognizable surface feature on Ganymede. We analyzed the distribution of furrows utilizing Voyager and Galileo images and found that furrows over Ganymede's surface are part of a global concentric circular structure. If this multi-ring structure is impact origin, this is the largest imp

Jiyang Ma, Shuoying Zhao, Xubiao Peng, Gaoshang Li

Biolasers show considerable potential in the biomedical field. Fluorescent protein (FP) is a type of biomaterial with good luminescence efficiency that can be used as the luminescent gain medium in biolasers. Due to the higher cell/tissue permeability, lower cell phototoxicity, and relatively less background fluorescence than other fluorescent proteins, the

Naoyuki Hirata, Ryuji Morishima, Keiji Ohtsuki, Akiko M. Nakamura

Spacecraft and ground-based observations show that the main rings of Saturn lack particles larger than 10 m. Tidal or collisional destruction of satellites/comets have been proposed as the origin of the main rings; however, Saturn's tide alone cannot grind km-sized fragments into submeter-sized particles because of the high mechanical strength of water ice a

Xiaoqin Zhang, Ziwei Huang, Jingjing Zheng, Shuo Wang

The task of grasp pattern recognition aims to derive the applicable grasp types of an object according to the visual information. Current state-of-the-art methods ignore category information of objects which is crucial for grasp pattern recognition. This paper presents a novel dual-branch convolutional neural network (DcnnGrasp) to achieve joint learning of

Suhas S. Jain, Parviz Moin

Accurate numerical modeling of compressible flows, particularly in the turbulent regime, requires a method that is non-dissipative and stable at high Reynolds ($Re$) numbers. For a compressible flow, it is known that discrete conservation of kinetic energy is not a sufficient condition for numerical stability, unlike in incompressible flows. In this study, w

Isaac Rudich, Quentin Cappart, Louis-Martin Rousseau

Decision diagrams are an increasingly important tool in cutting-edge solvers for discrete optimization. However, the field of decision diagrams is relatively new, and is still incorporating the library of techniques that conventional solvers have had decades to build. We drew inspiration from the warm-start technique used in conventional solvers to address o

Pramod Shukla

In this article we present a pheno-inspired classification for the divisor topologies of the favorable Calabi Yau (CY) threefolds with $1 \leq h^{1,1}(CY) \leq 5$ arising from the four-dimensional reflexive polytopes of the Kreuzer-Skarke database. Based on some empirical observations we conjecture that the topologies of the so-called coordinate divisors can

Jaime Roquero Gimenez, James Zou

Developing deep generative models that flexibly incorporate diverse measures of probability distance is an important area of research. Here we develop an unified mathematical framework of f-divergence generative model, f-GM, that incorporates both VAE and f-GAN, and enables tractable learning with general f-divergences. f-GM allows the experimenter to flexib

Kirill Shmilovich, Marc Stieffenhofer, Nicholas E. Charron, Moritz Hoffmann

Coarse-graining offers a means to extend the achievable time and length scales of molecular dynamics simulations beyond what is practically possible in the atomistic regime. Sampling molecular configurations of interest can be done efficiently using coarse-grained simulations, from which meaningful physicochemical information can be inferred if the correspon

Archit Sharma, Rehaan Ahmad, Chelsea Finn

While reinforcement learning (RL) provides a framework for learning through trial and error, translating RL algorithms into the real world has remained challenging. A major hurdle to real-world application arises from the development of algorithms in an episodic setting where the environment is reset after every trial, in contrast with the continual and non-

Son Hoang Dau, Quang Cao, Rinaldo Gagiano, Duy Huynh

A Batch Private Information Retrieval (batch-PIR) scheme allows a client to retrieve multiple data items from a database without revealing them to the storage server(s). Most existing approaches for batch-PIR are based on batch codes, in particular, probabilistic batch codes (PBC) (Angel et al. S&P'18), which incur large storage overheads. In this work, we s

Jianjun Jin, Shuan Tang, Xiaogao Feng

In this paper we introduce and study several new Hilbert-type operators acting between the weighted Fock spaces. We provide some sufficient and necessary conditions for the boundedness and compactness of certain Hilbert-type operators from one weighted Fock space to another.

Manoj Reddy Dareddy, Zijun Xue, Nicholas Lin, Junghoo Cho

Next-item prediction is a a popular problem in the recommender systems domain. As the name suggests, the task is to recommend subsequent items that a user would be interested in given contextual information and historical interaction data. In our paper, we model a general notion of context via a sequence of item interactions. We model the next item predictio

Eric Dolores-Cuenca, Jose L. Mendoza-Cortes

We explore the operad of finite posets and its algebras. We use order polytopes to investigate the combinatorial properties of zeta values. By generalizing a family of zeta value identities, we demonstrate the applicability of this approach. In addition, we offer new proofs of some of Ramanujan's results on the properties of Eulerian numbers, interpreting hi

Angel Yanguas-Gil, Jeffrey W. Elam

In this work we explore the application of deep neural networks to the optimization of atomic layer deposition processes based on thickness values obtained at different points of an ALD reactor. We introduce a dataset designed to train neural networks to predict saturation times based on the dose time and thickness values measured at different points of the

Sumit Goel

We study the design of effort-maximizing grading schemes between agents with private abilities. Assuming agents derive value from the information their grade reveals about their ability, we find that more informative grading schemes induce more competitive contests. In the contest framework, we investigate the effect of manipulating individual prizes and inc

Otavio Braga, Olivier Siohan

Under noisy conditions, automatic speech recognition (ASR) can greatly benefit from the addition of visual signals coming from a video of the speaker's face. However, when multiple candidate speakers are visible this traditionally requires solving a separate problem, namely active speaker detection (ASD), which entails selecting at each moment in time which

Akhil Rao, Francesca Letizia

Launch behaviors are a key determinant of the orbital environment. Physical and economic forces such as fragmentations and changing launch costs, or policies like post-mission disposal (PMD) compliance requirements, will alter the relative attractiveness of different orbits and lead operators to adjust their launch behaviors. However, integrating models of a

A. Vinokurov, K. Atapin, O. P. Bordoloi, A. Sarkisyan

We present the results of 8 epochs of simultaneous UV and X-ray observations of the highly variable ultraluminous X-ray source (ULX) Holmberg II X-1 with AstroSat -- Indian multiwavelength space satellite. During the entire observation period from late 2016 to early 2020, Holmberg II X-1 showed a moderate X-ray luminosity of $8\times10^{39}$ erg/s and a hard

Matt Jaffe, Lukas Palm, Claire Baum, Lavanya Taneja

Optical cavities have found widespread use in interfacing to quantum emitters. Concerns about backreflection and resulting loss, however, have largely prevented the placement of optics such as lenses or modulators within high-finesse cavities. In this work, we demonstrate a million-fold suppression of backreflections from lenses within a twisted optical cavi

Jiabao Gao, Caijun Zhong, Geoffrey Ye Li, Joseph B. Soriaga

Hybrid analog-digital (HAD) architecture is widely adopted in practical millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems to reduce hardware cost and energy consumption. However, channel estimation in the context of HAD is challenging due to only limited radio frequency (RF) chains at transceivers. Although various compressive se

Christian Vorwerk, Francesco Sottile, Claudia Draxl

We present a formalism for the resonant inelastic x-ray scattering (RIXS) cross section. The resulting compact expression in terms of polarizability matrix elements, particularly lends itself to the implementation in an all-electron many-body perturbation theory (MBPT) framework, which is realized in the full-potential package exciting. With the carbon K edg

Olivia Meredith Bitter, Dan Hooper

Observations of the TeV halos associated with nearby pulsars indicate that these objects inject significant fluxes of very high-energy electron-positrons pairs into the interstellar medium (ISM), thereby likely providing the dominant contribution to the cosmic-ray positron flux. In this paper, we use the cosmic-ray positron fraction as measured by the AMS-02

Ilya Sklyar, Anna Piunova, Christian Osendorfer

Streaming recognition and segmentation of multi-party conversations with overlapping speech is crucial for the next generation of voice assistant applications. In this work we address its challenges discovered in the previous work on multi-turn recurrent neural network transducer (MT-RNN-T) with a novel approach, separator-transducer-segmenter (STS), that en

Vijay Korthikanti, Jared Casper, Sangkug Lym, Lawrence McAfee

Training large transformer models is one of the most important computational challenges of modern AI. In this paper, we show how to significantly accelerate training of large transformer models by reducing activation recomputation. Activation recomputation is commonly used to work around memory capacity constraints. Rather than storing activations for backpr

Artur Grigorev, Adriana-Simona Mihaita, Seunghyeon Lee, Fang Chen

Predicting the duration of traffic incidents is a challenging task due to the stochastic nature of events. The ability to accurately predict how long accidents will last can provide significant benefits to both end-users in their route choice and traffic operation managers in handling of non-recurrent traffic congestion. This paper presents a novel bi-level

Valentina Beorchia, Rosa M. Miró-Roig

This note is motivated by the Question 16 of http://cubics.wikidot.com: Which configurations of 15 points in the projective 3-space arise as eigenpoints of a cubic surface? We prove that a general eigenscheme in the projective n-space is the complete intersection of two suitable smooth determinantal curves on a smooth determinantal surface. Moreover, we prov

Pierre-Louis Giscard, Mohammadali Foroozandeh

A general approach is presented that offers exact analytical solutions for the time-evolution of quantum spin systems during parametric waveforms of arbitrary functions of time. The proposed method utilises the \emph{path-sum} method that relies on the algebraic and combinatorial properties of walks on graphs. A full mathematical treatment of the proposed fo

Son T. Ly, Bai Lin, Hung Q. Vo, Dragan Maric

Reliable large-scale cell detection and segmentation is the fundamental first step to understanding biological processes in the brain. The ability to phenotype cells at scale can accelerate preclinical drug evaluation and system-level brain histology studies. The impressive advances in deep learning offer a practical solution to cell image detection and segm

S. Halder, K. Mukherjee, S. I. Mistakidis, S. Das

We investigate the quench dynamics of quasi-one and two dimensional dipolar Bose-Einstein condensates (dBEC) of $^{164}$Dy atoms under the influence of a fast rotating magnetic field. The magnetic field thus controls both the magnitude and sign of the dipolar potential. We account for quantum fluctuations, critical to formation of exotic quantum droplet and

Han-Yin Huang, Cynthia C. S. Liem

Artificial intelligence literature suggests that minority and fragile communities in society can be negatively impacted by machine learning algorithms due to inherent biases in the design process, which lead to socially exclusive decisions and policies. Faced with similar challenges in dealing with an increasingly diversified audience, the museum sector has

Kádmo de S. Laxa

We consider a finite system of interacting point processes with memory of variable length modeling a finite but large network of spiking neurons with two different leakage mechanisms. Associated to each neuron there are two point processes, describing its successive spiking and leakage times. For each neuron, the rate of the spiking point process is an expon

Alexis Toumi, Giovanni de Felice, Richie Yeung

DisCoPy (Distributional Compositional Python) is an open source toolbox for computing with string diagrams and functors. In particular, the diagram data structure allows to encode various kinds of quantum processes, with functors for classical simulation and optimisation, as well as compilation and evaluation on quantum hardware. This includes the ZX calculu

Nicholas J. Curtis, Kyle E. Niemeyer, Chih-Jen Sung

The high cost of chemistry integration is a significant computational bottleneck for realistic reactive-flow simulations using operator splitting. Here we present a methodology to accelerate the solution of the chemical kinetic ordinary differential equations using single-instruction, multiple-data vector processing on CPUs using the OpenCL framework. First,

W. Jayani Jayasuriya, Tejas Chandrashekhar Mulky, Kyle E. Niemeyer

Smoldering combustion plays a key role in wildfires in forests, grasslands, and peatlands due to its common occurrence in porous fuels like peat and duff. As a consequence, understanding smoldering behavior in these fuels is crucial. Such fuels are generally composed of cellulose, hemicellulose, and lignin. Here we present an updated computational model for

Linh Huynh, Jacob G. Scott, Peter J. Thomas

Density dependence is important in the ecology and evolution of microbial and cancer cells. Typically, we can only measure net growth rates, but the underlying density-dependent mechanisms that give rise to the observed dynamics can manifest in birth processes, death processes, or both. Therefore, we utilize the mean and variance of cell number fluctuations