December 2020 arXiv papers — page 6

Tara Boroushaki, Junshan Leng, Ian Clester, Alberto Rodriguez

We present the design, implementation, and evaluation of RF-Grasp, a robotic system that can grasp fully-occluded objects in unknown and unstructured environments. Unlike prior systems that are constrained by the line-of-sight perception of vision and infrared sensors, RF-Grasp employs RF (Radio Frequency) perception to identify and locate target objects thr

Markus Brueckner, Tomoo Kikuchi, George Vachadze

We estimate the relationship between GDP per capita growth and the growth rate of the national savings rate using a panel of 130 countries over the period 1960-2017. We find that GDP per capita growth increases (decreases) the growth rate of the national savings rate in poor countries (rich countries), and a higher credit-to-GDP ratio decreases the national

Claudio Gómez-Gonzáles, Jesse Wolfson

We present a list of problems in arithmetic topology posed at the June 2019 PIMS/NSF workshop on "Arithmetic Topology". Three problem sessions were hosted during the workshop in which participants proposed open questions to the audience and engaged in shared discussions from their own perspectives as working mathematicians across various fields of study. Par

Guozhi Dong, Hailong Guo, Zuoqiang Shi

This paper is dedicated to the development of numerical analysis for high-order methods solving partial differential equations on scattered point clouds. We build a novel geometric error analysis framework by estimating the error in the approximation of the Riemann metric tensor. The innovative framework serves as a fundamental tool for analyzing discontinuo

Hui Feng, Jundong Guo, Sam Shuzhi Ge

When sailing at sea, the smart ship will inevitably produce swaying motion due to the action of wind, wave and current, which makes the image collected by the visual sensor appear motion blur. This will have an adverse effect on the object detection algorithm based on the vision sensor, thereby affect the navigation safety of the smart ship. In order to remo

Oscar E. Martínez-Castiblanco, Primitivo B. Acosta-Humánez

In this paper, the origin of discrete dynamics is stated from a historical point of view, as well as its main ideas: fixed and periodic points, chaotic behaviour, bifurcations. This travel will begin with Poincar\'e's work and will finish with May's work, one of the most important scientific papers of 20th century. This paper is based on the M.Sc. thesis "Si

Leonid Positselski

We explain why the naive definition of a natural exact category structure on complete, separated topological vector spaces with linear topology fails. In particular, contrary to arXiv:0711.2527, the category of such topological vector spaces is not quasi-abelian. We present a corrected definition of exact category structure which works OK. Then we explain th

Yang Bai, Mrunal Korwar

Spherically symmetric magnetic and dyonic black holes with a magnetic charge $Q=2$ are studied in the Standard Model and general relativity. A magnetically charged black hole with mass below $9.3\times 10^{35}$ GeV has a "hairy" cloud of electroweak gauge and Higgs fields outside the event horizon with $1/m_W$ in size. An extremal magnetic black hole has a h

Weikui Ye, Zhaoyang Yin

In this paper, we consider the Cauchy problem for the Hunter-Saxton (HS) equation on the line. Firstly, we establish the local well-posedness for the integral form of the (HS) equation by constructing some special spaces $E^s_{p,r}$, which mix Lebesgue spaces and homogeneous Besov spaces. Then we present a global existence result and provide a sufficient con

Shih Yu Chang

This work prepares new probability bounds for sums of random, independent, Hermitian tensors. These probability bounds characterize large-deviation behavior of the extreme eigenvalue of the sums of random tensors. We extend Lapalace transform method and Lieb's concavity theorem from matrices to tensors, and apply these tools to generalize the classical bound

Hailan Ma, Daoyi Dong, Steven X. Ding, Chunlin Chen

Deep reinforcement learning has been recognized as an efficient technique to design optimal strategies for different complex systems without prior knowledge of the control landscape. To achieve a fast and precise control for quantum systems, we propose a novel deep reinforcement learning approach by constructing a curriculum consisting of a set of intermedia

Shao-Xia Chen, Bo Li, Tom Van Doorsselaere, Marcel Goossens

Given the recent interest in magnetohydrodynamic (MHD) waves in pores and sunspot umbrae, we examine the damping of slow surface kink modes (SSKMs) by modeling solar photospheric waveguides with a cylindrical inhomogeneity comprising a uniform interior, a uniform exterior, and a continuous transition layer (TL) in between. Performing an eigen-mode analysis i

Guy Lapalme

This paper describes the design principles behind jsRealB (Version 4.0), a surface realizer written JavaScript for English or French sentences from a specification inspired by the constituent syntax formalism but for which a dependency-based input notation is also available. jsRealB can be used either within a web page or as a node.js module. We show that th

Mengqi Xu, W. Benjamin Rogers, Wylie W. Ahmed, Jennifer L. Ross

Enzymes have been shown to diffuse faster in the presence of their reactants. Recently, we revealed new insights into this process of enhanced diffusion using single-particle tracking (SPT) with total internal reflection fluorescence (TIRF) microscopy. We found that the mobility of individual enzymes was enhanced three fold in the presence of the substrate,

Huy Quoc Le, Dung Hoang Duong, Partha Sarathi Roy, Willy Susilo

A signcryption, which is an integration of a public key encryption and a digital signature, can provide confidentiality and authenticity simultaneously. Additionally, a signcryption associated with equality test allows a third party (e.g., a cloud server) to check whether or not two ciphertexts are encrypted from the same message without knowing the message.

Shivam Handa, Konstantinos Kallas, Nikos Vasilakis, Martin Rinard

We present a dataflow model for modelling parallel Unix shell pipelines. To accurately capture the semantics of complex Unix pipelines, the dataflow model is order-aware, i.e., the order in which a node in the dataflow graph consumes inputs from different edges plays a central role in the semantics of the computation and therefore in the resulting paralleliz

Olga Majewska, Ivan Vulić, Goran Glavaš, Edoardo M. Ponti

In parallel to their overwhelming success across NLP tasks, language ability of deep Transformer networks, pretrained via language modeling (LM) objectives has undergone extensive scrutiny. While probing revealed that these models encode a range of syntactic and semantic properties of a language, they are still prone to fall back on superficial cues and simp

Amir Hossein Afsharinejad, Chuanyi Ji, Robert Wilcox

Large-scale power failures are induced by nearly all natural disasters from hurricanes to wild fires. A fundamental problem is whether and how recovery guided by government policies is able to meet the challenge of a wide range of disruptions. Prior research on this problem is scant due to lack of sharing large-scale granular data at the operational energy g

Paul Grouchy, Shobhit Jain, Michael Liu, Kuhan Wang

With the growing amount of text in health data, there have been rapid advances in large pre-trained models that can be applied to a wide variety of biomedical tasks with minimal task-specific modifications. Emphasizing the cost of these models, which renders technical replication challenging, this paper summarizes experiments conducted in replicating BioBERT

Shuai Liu, Xinran Xu, Zhihao Yang, Xiaohan Zhao

Enhancer-promoter interactions (EPIs) regulate the expression of specific genes in cells, and EPIs are important for understanding gene regulation, cell differentiation and disease mechanisms. EPI identification through the wet experiments is costly and time-consuming, and computational methods are in demand. In this paper, we propose a deep neural network-b

Zhang XueGuang

Mrk142 has been known as the only outlier in R-L space (correlation between BLRs (broad line regions) radii and continuum luminosity) among the low redshift local reverberation mapped broad line AGNs (BLAGNs) with moderate accretion rates, due to its BLRs radius smaller than R-L expected value. Here, considering probable optical transient quasi-periodic osci

Damian Pascual, Beni Egressy, Florian Bolli, Roger Wattenhofer

Large pre-trained language models are capable of generating realistic text. However, controlling these models so that the generated text satisfies lexical constraints, i.e., contains specific words, is a challenging problem. Given that state-of-the-art language models are too large to be trained from scratch in a manageable time, it is desirable to control t

Lei Ding, Chaowei Hu, Erxi Feng, Chenyang Jiang

Two-dimensional van der Waals MnBi$_{2n}$Te$_{3n+1}$ (n = 1, 2, 3, 4) compounds have been recently found to be intrinsic magnetic topological insulators rendering quantum anomalous Hall effect and diverse topological states. Here, we summarize and compare the crystal and magnetic structures of this family, and discuss the effects of chemical composition on t

Yuto Hosaka, Shigeyuki Komura, David Andelman

We discuss the linear hydrodynamic response of a two-dimensional active chiral compressible fluid with odd viscosity. The viscosity coefficient represents broken time-reversal and parity symmetries in the 2D fluid and characterizes the deviation of the system from a passive fluid. Taking into account the hydrodynamic coupling to the underlying bulk fluid, we

Chiranjibi Sitaula, Sunil Aryal

Because the infection by Severe Acute Respiratory Syndrome Coronavirus 2 (COVID-19) causes the pneumonia-like effect in the lungs, the examination of chest x-rays can help to diagnose the diseases. For automatic analysis of images, they are represented in machines by a set of semantic features. Deep Learning (DL) models are widely used to extract features fr

Agrim Gupta, Cedric Girerd, Manideep Dunna, Qiming Zhang

Contact force is a natural way for humans to interact with the physical world around us. However, most of our interactions with the digital world are largely based on a simple binary sense of touch (contact or no contact). Similarly, when interacting with robots to perform complex tasks, such as surgery, richer force information that includes both magnitude

Yuchen Xie, Raghu Bollapragada, Richard Byrd, Jorge Nocedal

The motivation for this paper stems from the desire to develop an adaptive sampling method for solving constrained optimization problems in which the objective function is stochastic and the constraints are deterministic. The method proposed in this paper is a proximal gradient method that can also be applied to the composite optimization problem min f(x) +

José Vinícius de Miranda Cardoso, Jiaxi Ying, Daniel Perez Palomar

In the past two decades, the field of applied finance has tremendously benefited from graph theory. As a result, novel methods ranging from asset network estimation to hierarchical asset selection and portfolio allocation are now part of practitioners' toolboxes. In this paper, we investigate the fundamental problem of learning undirected graphical models un

Wei Li, Can Gao, Guocheng Niu, Xinyan Xiao

Existed pre-training methods either focus on single-modal tasks or multi-modal tasks, and cannot effectively adapt to each other. They can only utilize single-modal data (i.e. text or image) or limited multi-modal data (i.e. image-text pairs). In this work, we propose a unified-modal pre-training architecture, namely UNIMO, which can effectively adapt to bot

M. H. Rahman, S. M. Rifaat, S. N. Sadeek, M. Abrar

Ride-hailing system requires efficient management of dynamic demand and supply to ensure optimal service delivery, pricing strategies, and operational efficiency. Designing spatio-temporal forecasting models separately in a task-wise and city-wise manner to forecast demand and supply-demand gap in a ride-hailing system poses a burden for the expanding transp

Diana Kirk, Stephen G. MacDonell, Ewan Tempero

Many prescriptive approaches to developing software intensive systems have been advocated but each is based on assumptions about context. It has been found that practitioners do not follow prescribed methodologies, but rather select and adapt specific practices according to local needs. As researchers, we would like to be in a position to support such tailor

Talwinder Singh, Alphonse C. Sterling, Ronald L. Moore

SDO/AIA images the full solar disk in several EUV bands that are each sensitive to coronal plasma emissions of one or more specific temperatures. We observe that when isolated active regions (ARs) are on the disk, full-disk images in some of the coronal EUV channels show the outskirts of the AR as a dark moat surrounding the AR. Here we present seven specifi

Guangming Shi, Yong Xiao, Yingyu Li, Xuemei Xie

Existing communication systems are mainly built based on Shannon's information theory which deliberately ignores the semantic aspects of communication. The recent iteration of wireless technology, the so-called 5G and beyond, promises to support a plethora of services enabled by carefully tailored network capabilities based on the contents, requirements, as

Yang Zhang, Liqun Deng, Yasheng Wang

The front-end module in a typical Mandarin text-to-speech system (TTS) is composed of a long pipeline of text processing components, which requires extensive efforts to build and is prone to large accumulative model size and cascade errors. In this paper, a pre-trained language model (PLM) based model is proposed to simultaneously tackle the two most importa

Shilin Huang, Kenneth R. Brown

Fault-tolerant quantum error correction requires the measurement of error syndromes in a way that minimizes correlated errors on the quantum data. Steane and Shor ancilla are two well-known methods for fault-tolerant syndrome extraction. In this paper, we find a unifying construction that generates a family of ancilla blocks that interpolate between Shor and

W. T. Geng, Q. Zhan

Helium ions implanted into metals can evolve into ordered bubbles isomorphic to the host lattice. Long-range elastic interaction is generally believed to drive the formation of bubble superlattice, but little is known about the thermodynamics at the very initial stage. Our first-principles calculations demonstrate that in molybdenum, Friedel oscillations ind

Hairong Bai

In this paper, we consider the exponential Diophantine equation $a^{x}+b^{y}=c^{z},$ where $a, b, c$ be relatively prime positive integers such that $a^{2}+b^{2}=c^{r}, r\in Z^{+}, 2\mid r$ with $b$ even. That is $$a=\mid Re(m+n\sqrt{-1})^{r}\mid, b=\mid Im(m+n\sqrt{-1})^{r}\mid, c=m^{2}+n^{2},$$ where $m, n$ are positive integers with $m>n, m-n\equiv1(mod 2

Ivan C. Christov, Isanka Garli Hevage, Akif Ibraguimov, Rahnuma Islam

We employ a generalization of Einstein's random walk paradigm for diffusion to derive a class of multidimensional degenerate nonlinear parabolic equations in non-divergence form. Specifically, in these equations, the diffusion coefficient can depend on both the dependent variable and its gradient, and it vanishes when either one of the latter does. It is kno

Vaclav Zatloukal

We investigate the local (or occupation) time of a discrete-time random walk on a generic graph, and present a general method for calculating sample-path averages of local time functionals in terms of the resolvent of the transition matrix.

Haibo Wang, Zaichen Zhang, Bingcheng Zhu, Jian Dang

Oriented to the point-to-multipoint free space optical communication (FSO) scenarios, this paper analyzes the micro-mirror array and phased array-type optical intelligent reflecting surface (OIRS) in terms of control mode, power efficiency, and beam splitting. We build the physical models of the two types of OIRSs. Based on the models, the closed form soluti

Hajar Emami, Qiong Liu, Ming Dong

While Positron emission tomography (PET) imaging has been widely used in diagnosis of number of diseases, it has costly acquisition process which involves radiation exposure to patients. However, magnetic resonance imaging (MRI) is a safer imaging modality that does not involve patient's exposure to radiation. Therefore, a need exists for an efficient and au

Haiming Yuan, Xian-Hui Ge

The "pole-skipping" phenomenon reflects that the retarded Green's function is not unique at a pole-skipping point in momentum space $(\omega,k)$. We explore the universality of the pole-skipping in different geometries. In holography, near horizon analysis of the bulk equation of motion is a simpler way to derive a pole-skipping point and we use this method

Samuel Roldán, Jose Luis Mora, Edward Becerra

In this paper it is shown how to construct a finite topological space $X$ for a given finitely presentable group $G$ such that $\pi_1(X)\cong G$. Our construction is not optimal in the sense that the cardinality of the space $X$ might not be the smallest possible. Our main result applies to a large class of interesting groups, including all finite groups.

Yo Sato

Radiative and electroweak penguin mediated decays of $B$ mesons are a great probe for physics beyond the Standard Model of particle physics. Furthermore, recently anomalies on exclusive $b \rightarrow s \ell^{+} \ell^{-}$ processes, which may imply lepton flavor universality violation, have been observed. Belle II experiment sheds light on the anomalies with

Michal P. Heller, Alexandre Serantes, Michał Spaliński, Viktor Svensson

We study the mechanisms setting the radius of convergence of hydrodynamic dispersion relations in kinetic theory in the relaxation time approximation. This introduces a qualitatively new feature with respect to holography: a nonhydrodynamic sector represented by a branch cut in the retarded Green's function. In contrast with existing holographic examples, we

James Van Yperen, Eduard Campillo-Funollet, Rebecca Inkpen, Anjum Memon

The mathematical interpretation of interventions for the mitigation of epidemics and pandemics in the literature often involves finding the optimal time to initiate an intervention and/or the use of infections to manage impact. Whilst these methods may work in theory, in order to implement they may require information which is likely not available whilst one

Shen Chen, Mingwei Zhang, Jiamin Cui, Wei Yao

Deep learning (DL) has brought about remarkable breakthrough in processing images, video and speech due to its efficacy in extracting highly abstract representation and learning very complex functions. However, there is seldom operating procedure reported on how to make it for real use cases. In this paper, we intend to address this problem by presenting a g

R. Bucik, S. M. Mulay, G. M. Mason, N. V. Nitta

3He-rich solar energetic particles (SEPs) are believed to be accelerated in solar flares or jets by a mechanism that depends on the ion charge-to-mass (Q/M) ratio. It implies that the flare plasma characteristics (e.g., temperature) may be effective in determining the elemental abundances of 3He-rich SEPs. This study examines the relation between the suprath

A. H. Reiman, N. Bertelli, P. T. Bonoli, N. J. Fisch

As tokamaks are designed and built with increasing levels of stored energy in the plasma, disruptions become increasingly dangerous. It has been reported that 95% of the disruptions in the Joint European Torus (JET) tokamak with the ITER-like wall are preceded by the growth of large locked islands, and these large islands are mostly produced by off-normal ev

Alexey Bondal, Ilya Zhdanovskiy

The paper is the survey of the modern results and applications of the theory of homotopes. The notion of a well-tempered element in an associative algebra is introduced and it is proven that the category of representations of the homotope constructed by a well-tempered element is the heart of a suitably glued t-structure. Hochschild and global dimensions of

Ajinkya Gawade, Aniket Sanap, Vishal Baviskar, Ryan Jahnige

Poor indoor air quality can contribute to the development of various chronic respiratory diseases such as asthma, heart disease, and lung cancer. Since air quality is extremely difficult for humans to detect though sensory processing, there is a need for efficient ventilation systems that can provide a healthier environment. In this paper, we have designed a

Yuhang Wu, Sunpreet S. Arora, Yanhong Wu, Hao Yang

Adversarial examples are input examples that are specifically crafted to deceive machine learning classifiers. State-of-the-art adversarial example detection methods characterize an input example as adversarial either by quantifying the magnitude of feature variations under multiple perturbations or by measuring its distance from estimated benign example dis

Gang Lu, Wenlong Sun, Hanyue Qiao, Yuanfeng Jin

In this paper, we introduce and investigate general 3-variable Jensen $\rho$-functional equation, and prove the Hyers-Ulam stability of the Jensen functional equations associated with the general 3-variable Jensen $\rho$-functional inequalities in complex Banach spaces.

Anne-Marie Aubert, Antonio Behn, Jorge Soto-Andrade

In this paper we introduce an intrinsic version of the classical induction of representations for a subgroup $H$ of a (finite) group $G$, called here {\em geometric induction}, which associates to any, not necessarily transitive, $G$-set $X$ and any representation of the action groupoid $A(G,X)$ associated to $G$ and $X$, a representation of the group $G$. W

Francesco Foggetti, Sergey Artyukhin

Competing magnetic exchange interactions often result in non-collinear magnetic states, such as spin spirals, which break the inversion symmetry and induce ferroelectric polarization. The resulting strong interactions between magnetic and dielectric degrees of freedom lead to a technologically important possibility to control magnetic order by electric field

David H. Lorenz, Boaz Rosenan

Management of information is an important aspect of every application. This includes, for example, protecting user data against breaches (like the one reported in the news about 50 million Facebook profiles being harvested for Cambridge Analytica), complying with data protection laws and regulations (like EU's new General Data Protection Regulation), coping

Sergio Cabello

We consider the problem of computing the \emph{distance-based representative skyline} in the plane, a problem introduced by Tao, Ding, Lin and Pei [Proc. 25th IEEE International Conference on Data Engineering (ICDE), 2009] and independently considered by Dupin, Nielsen and Talbi [Optimization and Learning - Third International Conference, OLA 2020] in the co

Chung Kao, Yue-Lin Sming Tsai, Gwo-Guang Wong

The cold dark matter (CDM) candidate with weakly interacting massive particles can successfully explain the observed dark matter relic density in cosmic scale and the large-scale structure of the Universe. However, a number of observations at the satellite galaxy scale seem to be inconsistent with CDM simulation. This is known as the small-scale problem of C

L. Podio, B. Tabone, C. Codella, F. Gueth

As a part of the CALYPSO large programme, we constrain the properties of protostellar jets and outflows in a sample of 21 Class 0 protostars with internal luminosities, Lint, from 0.035 to 47 Lsun. We analyse high angular resolution (~0.5"-1") IRAM PdBI observations in CO (2-1), SO ($5_6-4_5$), and SiO (5-4). CO (2-1), which probes outflowing gas, is detecte

Emad Barsoum, John Kender, Zicheng Liu

Human motion prediction and understanding is a challenging problem. Due to the complex dynamic of human motion and the non-deterministic aspect of future prediction. We propose a novel sequence-to-sequence model for human motion prediction and feature learning, trained with a modified version of generative adversarial network, with a custom loss function tha

Arnob Ghosh, Vaneet Aggarwal

We consider a multi-agent Markov strategic interaction over an infinite horizon where agents can be of multiple types. We model the strategic interaction as a mean-field game in the asymptotic limit when the number of agents of each type becomes infinite. Each agent has a private state; the state evolves depending on the distribution of the state of the agen

Lars Ohnemus, Lukas Ewecker, Ebubekir Asan, Stefan Roos

For advanced driver assistance systems, it is crucial to have information about oncoming vehicles as early as possible. At night, this task is especially difficult due to poor lighting conditions. For that, during nighttime, every vehicle uses headlamps to improve sight and therefore ensure safe driving. As humans, we intuitively assume oncoming vehicles bef

Weiyan Shi, Yu Li, Saurav Sahay, Zhou Yu

Persuasion dialogue systems reflect the machine's ability to make strategic moves beyond verbal communication, and therefore differentiate themselves from task-oriented or open-domain dialogue systems and have their own unique values. However, the repetition and inconsistency problems still persist in dialogue response generation and could substantially impa

Blanca Belsa, Kasra Amini, Xinyao Liu, Aurelien Sanchez

Visualizing molecular transformations in real-time requires a structural retrieval method with {\AA}ngstr\"om spatial and femtosecond temporal atomic resolution. Imaging of hydrogen-containing molecules additionally requires an imaging method that is sensitive to the atomic positions of hydrogen nuclei, with most methods possessing relatively low sensitivity

Joseph Klobusicky

We construct Markov processes for modeling the rupture of edges in a two-dimensional foam. We first describe a network model for tracking topological information of foam networks with a state space of combinatorial embeddings. Through a mean-field rule for randomly selecting neighboring cells of a rupturing edge, we consider a simplified version of the netwo

Stephen Tian, Suraj Nair, Frederik Ebert, Sudeep Dasari

A generalist robot must be able to complete a variety of tasks in its environment. One appealing way to specify each task is in terms of a goal observation. However, learning goal-reaching policies with reinforcement learning remains a challenging problem, particularly when hand-engineered reward functions are not available. Learned dynamics models are a pro

Masaki Tsukamoto, Mitsunobu Tsutaya, Masahiko Yoshinaga

Given an action of a finite group $G$, we can define its index. The $G$-index roughly measures a size of the given $G$-space. We explore connections between the $G$-index theory and topological dynamics. For a fixed-point free dynamical system, we study the $\mathbb{Z}_p$-index of the set of $p$-periodic points. We find that its growth is at most linear in $

Javier López Prol, Wolf-Peter Schill

The transformation of the electricity sector is a main element of the transition to a decarbonized economy. Conventional generators powered by fossil fuels have to be replaced by variable renewable energy (VRE) sources in combination with electricity storage and other options for providing temporal flexibility. We discuss the market dynamics of increasing VR

Baris Gecer, Jiankang Deng, Stefanos Zafeiriou

The last few years have witnessed the great success of non-linear generative models in synthesizing high-quality photorealistic face images. Many recent 3D facial texture reconstruction and pose manipulation from a single image approaches still rely on large and clean face datasets to train image-to-image Generative Adversarial Networks (GANs). Yet the colle

Federico W. Pasini

For a prime knot group, the classifying space for the family of the subgroups generated by the meridians can be seen as an abstract analogue of the ambient manifold in which the knot lives. An explicit model of this ambient classifying space is constructed as a branched covering space of the 3-sphere branched over the knot; more general branched covering spa

Marcos Oliveira

Crime rates per capita are used virtually everywhere to rank and compare cities. However, their usage relies on a strong linear assumption that crime increases at the same pace as the number of people in a region. In this paper, we demonstrate that using per capita rates to rank cities can produce substantially different rankings from rankings adjusted for p

Billy Ferguson, Brad Ross

We propose a sensitivity analysis for Synthetic Control (SC) treatment effect estimates to interrogate the assumption that the SC method is well-specified, namely that choosing weights to minimize pre-treatment prediction error yields accurate predictions of counterfactual post-treatment outcomes. Our data-driven procedure recovers the set of treatment effec

Tobias Ekholm, Vivek Shende

We determine the skein-valued Gromov-Witten partition function for a single toric Lagrangian brane in $\mathbb{C}^3$ or the resolved conifold. We first show geometrically they must satisfy a certain skein-theoretic recursion, and then solve this equation. The recursion is a skein-valued quantization of the equation of the mirror curve. The solution is the ex

Martin Mariusz Lester

We present a case study on using program verification tools, specifically model-checkers for C programs, to solve simple interactive fiction games from around 1980. Off-the-shelf model-checking tools are unable to handle the games in their original form. In order to work around this, we apply a series of program transformations that do not change the behavio

Kay Schwieger, Stefan Wagner

Given a free action of a compact Lie group $G$ on a unital C*-algebra $\mathcal{A}$ and a spectral triple on the corresponding fixed point algebra $\mathcal{A}^G$, we present a systematic and in-depth construction of a spectral triple on $\mathcal{A}$ that is build upon the geometry of $\mathcal{A}^G$ and $G$. We compare our construction with a selection of

Yuan Shi, Hong Qin, Nathaniel J. Fisch

In strong electromagnetic fields, unique plasma phenomena and applications emerge, whose description requires recently developed theories and simulations [Y. Shi, Ph.D. thesis, Princeton University (2018)]. In the classical regime, to quantify effects of strong magnetic fields on three-wave interactions, a convenient formula is derived by solving the fluid m

Mikko Kiviranta

We have designed and fabricated an integrated two-stage SQUID amplifier, requiring only one bias line and one flux setpoint line. From the biasing viewpoint the two stages are connected in series while from the signal propagation viewpoint the stages are cascaded. A proof-of principle demonstration at T = 4.2 K is presented.

Haoyue Wang, Haihao Lu, Rahul Mazumder

The Frank-Wolfe (FW) method is a popular algorithm for solving large-scale convex optimization problems appearing in structured statistical learning. However, the traditional Frank-Wolfe method can only be applied when the feasible region is bounded, which limits its applicability in practice. Motivated by two applications in statistical learning, the $\ell_

Weidi Wang, Alireza V. Amirkhizi

Exceptional points (EPs) are complex singularities of parametric linear operators where two or more eigenvalues and eigenvectors coalesce. EPs are attracting increasing interest in mechanical metamaterials due to their strong potentials for wave filtering, cloaking, and sensing applications. This work studies the band topology and scattering behaviors near E

Yirui Wang, Kang Zheng, Chi-Tung Chang, Xiao-Yun Zhou

Exploiting available medical records to train high performance computer-aided diagnosis (CAD) models via the semi-supervised learning (SSL) setting is emerging to tackle the prohibitively high labor costs involved in large-scale medical image annotations. Despite the extensive attentions received on SSL, previous methods failed to 1) account for the low dise

Ashkan Yousefi Zadeh, Meysam Shahbazy

Nowadays it is inevitable to use intelligent systems to improve the performance and optimization of different components of devices or factories. Furthermore, it's so essential to have appropriate predictions to make better decisions in businesses, medical studies, and engineering studies, etc. One of the newest and most widely used of these methods is a fie

Daniele Bartoli, Giacomo Micheli, Giovanni Zini, Ferdinando Zullo

In this paper we prove that the property of being scattered for a $\mathbb{F}_q$-linearized polynomial of small $q$-degree over a finite field $\mathbb{F}_{q^n}$ is unstable, in the sense that, whenever the corresponding linear set has at least one point of weight larger than one, the polynomial is far from being scattered. To this aim, we define and investi

Peter Borg, Carl Feghali

A set of sets is called a family. Two families $\mathcal{A}$ and $\mathcal{B}$ of sets are said to be cross-intersecting if each member of $\mathcal{A}$ intersects each member of $\mathcal{B}$. For any two integers $n$ and $k$ with $1 \leq k \leq n$, let ${[n] \choose \leq k}$ denote the family of subsets of $[n] = \{1, \dots, n\}$ that have at most $k$ elem

Peng Xu, Dhruv Kumar, Wei Yang, Wenjie Zi

It is a common belief that training deep transformers from scratch requires large datasets. Consequently, for small datasets, people usually use shallow and simple additional layers on top of pre-trained models during fine-tuning. This work shows that this does not always need to be the case: with proper initialization and optimization, the benefits of very

J. I. Katz

The activity of the repeating FRB 20180916B is periodically modulated with a period of 16.3 days, and FRB 121102 may be similarly modulated with a period of about 160 days. In some models of this modulation the period derivative is insensitive to the uncertain parameters; these models can be tested by measurement of or bounds on the derivative. In other mode

Lynn Wahab, Ezzat Chebaro, Jad Ismail, Amir Nasrelddine

Climate change is an impending disaster which is of pressing concern more and more every year. Countless efforts have been made to study the long-term effects of climate change on agriculture, land resources, and biodiversity. Studies involving marine life, however, are less prevalent in the literature. Our research studies the available data on the populati

Jacob Turton, David Vinson, Robert Elliott Smith

Models based on the transformer architecture, such as BERT, have marked a crucial step forward in the field of Natural Language Processing. Importantly, they allow the creation of word embeddings that capture important semantic information about words in context. However, as single entities, these embeddings are difficult to interpret and the models used to

Mohamed Ghoneim, Can Kozçaz, Kerem Kurşun, Yegor Zenkevich

Supersymmetric gauge theories of certain class possess a large hidden nonperturbative symmetry described by the Ding-Iohara-Miki (DIM) algebra which can be used to compute their partition functions and correlators very efficiently. We lift the DIM-algebraic approach developed to study holomorphic blocks of 3d linear quiver gauge theories one dimension higher

Mohsen Toorani, Christian Gehrmann

The central role of the certificate authority (CA) in traditional public key infrastructure (PKI) makes it fragile and prone to compromises and operational failures. Maintaining CAs and revocation lists is demanding especially in loosely-connected and large systems. Log-based PKIs have been proposed as a remedy but they do not solve the problem effectively.

Connor J. McClellan, Eilam Yalon, Kirby K. H. Smithe, Saurabh V. Suryavanshi

Semiconductors require stable doping for applications in transistors, optoelectronics, and thermoelectrics. However, this has been challenging for two-dimensional (2D) materials, where existing approaches are either incompatible with conventional semiconductor processing or introduce time-dependent, hysteretic behavior. Here we show that low temperature (< 2

Christopher Potts, Zhengxuan Wu, Atticus Geiger, Douwe Kiela

We introduce DynaSent ('Dynamic Sentiment'), a new English-language benchmark task for ternary (positive/negative/neutral) sentiment analysis. DynaSent combines naturally occurring sentences with sentences created using the open-source Dynabench Platform, which facilities human-and-model-in-the-loop dataset creation. DynaSent has a total of 121,634 sentences

Fateme Mahdikhanysarvejahany, Daniel N. Meade, Christine Muccianti, Bekele H. Badada

MoSe2-WSe2 heterostructures host strongly bound interlayer excitons (IXs) which exhibit bright photoluminescence (PL) when the twist-angle is near 0{\deg} or 60{\deg}. Over the past several years, there have been numerous reports on the optical response of these heterostructures but no unifying model to understand the dynamics of IXs and their temperature de

Ilya B. Shapirovsky

We consider the operation of sum on Kripke frames, where a family of frames-summands is indexed by elements of another frame. In many cases, the modal logic of sums inherits the finite model property and decidability from the modal logic of summands. In this paper we show that, under a general condition, the satisfiability problem on sums is polynomial space

Dominic J. Williamson, Clement Delcamp, Frank Verstraete, Norbert Schuch

We construct a tensor network representation of the 3d toric code ground state that is stable to a generating set of uniform local tensor perturbations, including those that do not map to local operators on the physical Hilbert space. The stability is established by mapping the phase diagram of the perturbed tensor network to that of the 3d Ising gauge theor

J. Guo, G. Yumnam, A. Dahal, Y. Chen

Geometrically frustrated materials, such as spin ice or kagome lattice, are known to exhibit exotic Hall effect phenomena due to spin chirality. We explore Hall effect mechanism in an artificial honeycomb spin ice of Nd--Sn element using Hall probe and polarized neutron reflectivity measurements. In an interesting observation, a strong enhancement in Hall si

Dmitry E. Pelinovsky

It is shown how to compute the instability rates for the double-periodic solutions to the cubic NLS (nonlinear Schrodinger) equation by using the Lax linear equations. The wave function modulus of the double-periodic solutions is periodic both in space and time coordinates; such solutions generalize the standing waves which have the time-independent and spac

Loic Peter, Marcel Tella-Amo, Dzhoshkun Ismail Shakir, Jan Deprest

Video mosaicking requires the registration of overlapping frames located at distant timepoints in the sequence to ensure global consistency of the reconstructed scene. However, fully automated registration of such long-range pairs is (i) challenging when the registration of images itself is difficult; and (ii) computationally expensive for long sequences due

Patrick Franz, Thorsten Berger, Ibrahim Fayaz, Sarah Nadi

Highly configurable systems are highly complex systems, with the Linux kernel arguably being one of the most well-known ones. Since 2007, it has been a frequent target of the research community, conducting empirical studies and building dedicated methods and tools for analyzing, configuring, testing, optimizing, and maintaining the kernel in the light of its

R. M. de Oliveira, Samuraí Brito, L. R. da Silva, Constantino Tsallis

Boltzmann-Gibbs statistical mechanics applies satisfactorily to a plethora of systems. It fails however for complex systems generically involving strong space-time entanglement. Its generalization based on nonadditive $q$-entropies adequately handles a wide class of such systems. We show here that scale-invariant networks belong to this class. We numerically

Bernardo M. O. Fraga, Ulisses Barres de Almeida, Clecio R. Bom, Carlos H. Brandt

Blazars are among the most studied sources in high-energy astrophysics as they form the largest fraction of extragalactic gamma-ray sources and are considered prime candidates for being the counterparts of high-energy astrophysical neutrinos. Their reliable identification amid the many faint radio sources is a crucial step for multi-messenger counterpart ass