April 2020 arXiv papers — page 51

Haoxuan Jiang, Jianghui Ji, Liangliang Yu

In this work, we investigate the size, thermal inertia, surface roughness and geometric albedo of 10 Vesta family asteroids by using the Advanced Thermophysical Model (ATPM), based on the thermal infrared data acquired by mainly NASA's Wide-field Infrared Survey Explorer (WISE). Here we show that the average thermal inertia and geometric albedo of the invest

Marcel Bengs, Stephan Westermann, Nils Gessert, Dennis Eggert

Early detection of head and neck tumors is crucial for patient survival. Often, diagnoses are made based on endoscopic examination of the larynx followed by biopsy and histological analysis, leading to a high inter-observer variability due to subjective assessment. In this regard, early non-invasive diagnostics independent of the clinician would be a valuabl

Marek Cúth, Michal Doucha, Ondřej Kurka

We show that all the standard distances from metric geometry and functional analysis, such as Gromov-Hausdorff distance, Banach-Mazur distance, Kadets distance, Lipschitz distance, Net distance, and Hausdorff-Lipschitz distance have all the same complexity and are reducible to each other in a precisely defined way. This is done in terms of descriptive set th

Kartik Nagar, Prasita Mukherjee, Suresh Jagannathan

Geo-replicated systems provide a number of desirable properties such as globally low latency, high availability, scalability, and built-in fault tolerance. Unfortunately, programming correct applications on top of such systems has proven to be very challenging, in large part because of the weak consistency guarantees they offer. These complexities are exacer

Akari Asai, Hannaneh Hajishirzi

Many natural language questions require qualitative, quantitative or logical comparisons between two entities or events. This paper addresses the problem of improving the accuracy and consistency of responses to comparison questions by integrating logic rules and neural models. Our method leverages logical and linguistic knowledge to augment labeled training

Andrea Martinelli, John Lygeros

We address the problem of local flux redistribution in networked systems. The aim is to detect a suitable cluster which is able to locally adsorb a disturbance by means of an appropriate redistribution of control load among its nodes, such that no external node is affected. Traditional clustering measures are not suitable for our purpose, since they do not e

A. Celestino, K. Ebrahimi-Fard, F. Patras, D. Perales Anaya

Relations between moments and cumulants play a central role in both classical and non-commutative probability theory. The latter allows for several distinct families of cumulants corresponding to different types of independences: free, Boolean and monotone. Relations among those cumulants have been studied recently. In this work we focus on the problem of ex

Yonatan Bisk, Ari Holtzman, Jesse Thomason, Jacob Andreas

Language understanding research is held back by a failure to relate language to the physical world it describes and to the social interactions it facilitates. Despite the incredible effectiveness of language processing models to tackle tasks after being trained on text alone, successful linguistic communication relies on a shared experience of the world. It

Reinald Kim Amplayo, Mirella Lapata

The supervised training of high-capacity models on large datasets containing hundreds of thousands of document-summary pairs is critical to the recent success of deep learning techniques for abstractive summarization. Unfortunately, in most domains (other than news) such training data is not available and cannot be easily sourced. In this paper we enable the

Pavel Barkhayev

We study the minimum energy null-controllability problem for differential equations with point-wise delays. For the equations of both neutral and retarded type we reduce the problem of finding the optimal control to a Volterra integral equation and solve it explicitly. We prove that for any initial state and any controllability time the corresponding optimal

Ning Chen, Tong Li, Yongcheng Wu

We study the CP domain walls and the consequent gravitational waves induced by the spontaneous breaking of the CP symmetry in the complex singlet extension to the Standard Model. We impose the constraints from the unitarity, stability and the global minimal of the vacuum solutions on the model parameter space. The CP domain wall profiles and tensions are obt

Marc Verriere, David Regnier

The emergence of collective behaviors and the existence of large amplitude motions are both central features in the fields of nuclear structure and reactions. From a theoretical point of view, describing such phenomena requires increasing the complexity of the many-body wavefunction of the system to account for long-range correlations. One of the challenges,

Daniel Tubbenhauer, Paul Wedrich

In this note we compute the centers of the categories of tilting modules for G=SL2 in prime characteristic, of tilting modules for the corresponding quantum group at a complex root of unity, and of projective GgT-modules when g=1,2.

Arshyn Altybay, Michael Ruzhansky, Mohammed Elamine Sebih, Niyaz Tokmagambetov

We consider a space-fractional wave equation with a singular mass term depending on the position and prove that it is very weak well-posed. The uniqueness is proved in some appropriate sense. Moreover, we prove the consistency of the very weak solution with classical solutions when they exist. In order to study the behaviour of the very weak solution near th

L. Mandhour, F. Bouhadida

We show that under compressive uniaxial deformation of the three-band $\alpha-T_3$ lattice, the Dirac cones move toward each other, merge, and a gap opens, while the flat band remains unchanged. Consequently, the low-energy spectrum transitions from linear to quadratic dispersion, indicating the shift from massless to massive Dirac particles. Here, we theore

Linda Erlenhov, Francisco Gomes de Oliveira Neto, Martin Chukaleski, Samer Daknache

Test bots are automated testing tools that autonomously and periodically run a set of test cases that check whether the system under test meets the requirements set forth by the customer. The automation decreases the amount of time a development team spends on testing. As development projects become larger, it is important to focus on improving the test bots

Shuaidong Pan, Faner Lin, Jiebo Luo

Considering the fact that sports and politics interact in a very complex way, this interdisciplinary area remains largely untouched in data science research. Given the fact that huge fan bases exist for the major sports leagues such as NBA and NFL, it would be important for us to understand the hidden relationship between sports fans and their political pref

Guillaume St-Onge, Vincent Thibeault, Antoine Allard, Louis J. Dubé

Simple models of infectious diseases tend to assume random mixing of individuals, but real interactions are not random pairwise encounters: they occur within various types of gatherings such as workplaces, households, schools, and concerts, best described by a higher-order network structure. We model contagions on higher-order networks using group-based appr

Rami Ben-Ari, Mor Shpigel, Ophir Azulai, Udi Barzelay

Classification of new class entities requires collecting and annotating hundreds or thousands of samples that is often prohibitively costly. Few-shot learning suggests learning to classify new classes using just a few examples. Only a small number of studies address the challenge of few-shot learning on spatio-temporal patterns such as videos. In this paper,

Kathirvel Nallappan, Yang Cao, Guofu Xu, Hichem Guerboukha

In this work, we present an in-depth experimental and numerical study of the short-range THz communications links that use subwavelength dielectric fibers for information transmission and define main challenges and tradeoffs in the link implementation. Particularly, we use air or foam-cladded polypropylene-core subwavelength dielectric THz fibers of various

Z. H. Yao, B. Bonfond, D. Grodent, E. Chané

Although mass and energy in Jupiter's magnetosphere mostly come from the innermost Galilean moon Io's volcanic activities, solar wind perturbations can play crucial roles in releasing the magnetospheric energy and powering aurorae in Jupiter's polar regions. The systematic response of aurora to solar wind compression remains poorly understood. Here we report

Ismael Ayuso, Diego Sáez-Chillón Gómez

Extremal cosmological black holes are analysed in the framework of the most general second order scalar-tensor theory, the~so-called Horndeski gravity. Such~extremal black holes are a particular case of Schwarzschild-De Sitter black holes that arises when the black hole horizon and the cosmological one coincide. Such~metric is induced by a particular value o

J. L. F. Barbon, E. Rabinovici

We point out that negative specific heat at high energies is a characteristic feature of many TT-bar deformations, both in the original d = 2 case and in d = 1 quantum mechanical cousins. This note is a contribution to the memorial volume in honor of P. G. O. Freund.

Helmut Abels, Gerd Grubb

The fractional Laplacian $(-\Delta )^a$, $a\in(0,1)$, and its generalizations to variable-coefficient $2a$-order pseudodifferential operators $P$, are studied in $L_q$-Sobolev spaces of Bessel-potential type $H^s_q$. For a bounded open set $\Omega \subset \mathbb R^n$, consider the homogeneous Dirichlet problem: $Pu =f$ in $\Omega $, $u=0$ in $ \mathbb R^n\s

F. Matteucci, A. Vasini, V. Grisoni, M. Schultheis

We present results for the evolution of the abundances of heavy elements (O, Mg, Al, Si, K, Ca, Cr, Mn, Ni and Fe) in the inner Galactic regions ($R_{GC} < 4$kpc). We adopt a detailed chemical evolution model already tested for the Galactic bulge and compare the results with APOGEE data. We start with a set of yields from the literature which are considered

Debabrata Karmakar, Gershon Wolansky

We study the global in time existence and long time asymptotics of solutions to the parabolic-elliptic Patlak-Keller-Segel system for the multi-species populations in the whole Euclidean space $\mathbb{R}^2.$ We prove that at the borderline case of critical mass there exists a global {\it free energy solution} subject to initial data with finite entropy and

Markus Linckelmann, Michael Livesey

We show that the Green correspondence induces an injective group homomorphism from the linear source Picard group $\mathcal{L}(B)$ of a block $B$ of a finite group algebra to the linear source Picard group $\mathcal{L}(C)$, where $C$ is the Brauer correspondent of $B$. This homomorphism maps the trivial source Picard group $\mathcal{T}(B)$ to the trivial sou

Takato Yasuno, Masazumi Amakata, Masahiro Okano

Recent years, typhoon damages has become social problem owing to climate change. In 9 September 2019, Typhoon Faxai passed on the Chiba in Japan, whose damages included with electric provision stop because of strong wind recorded on the maximum 45 meter per second. A large amount of tree fell down, and the neighbor electric poles also fell down at the same t

Xiao Liu, Sotirios A Tsaftaris

In the era of deep learning, aggregation of data from several sources is a common approach to ensuring data diversity. Let us consider a scenario where several providers contribute data to a consortium for the joint development of a classification model (hereafter the target model), but, now one of the providers decides to leave. This provider requests that

Victor H. Lutfalla

We give an explicit and effective construction for rhombus cut-and-project tilings with global n-fold rotational symmetry for any n. This construction is based on the dualization of regular n-fold multigrids. The main point is to prove the regularity of these multigrids, for this we use a result on trigonometric diophantine equations.

Bruno Courcelle

The ternary betweenness relation of a tree, B(x,y,z) expresses that y is on the unique path between x and z. This notion can be extended to order-theoretic trees defined as partial orders such that the set of nodes larger than any node is linearly ordered. In such generalized trees, the unique "path" between two nodes can have infinitely many nodes. We gener

Takato Yasuno

In medical image diagnosis, pathology image analysis using semantic segmentation becomes important for efficient screening as a field of digital pathology. The spatial augmentation is ordinary used for semantic segmentation. Tumor images under malignant are rare and to annotate the labels of nuclei region takes much time-consuming. We require an effective us

Hao Peng, Zhongzu Wu, Bo Zhang, Yongjun Chen

We present results from VLBI observations of continuum and OH line emission in IRAS 02524+2046 and also arcsecond-scale radio properties of this galaxy using VLA archive data. We found that there is no significant detection of radio continuum emission from VLBI observations. The arcsecond-scale radio images of this source show no clear extended emission, the

Ednilton S. de Oliveira

The changes a (negative) tidal charge causes at the phenomenon of superradiance which occurs around rotating black holes are investigated. This is made by computing the amplification factors of massless scalar waves being scattered by the black hole. It is shown that the increase of the tidal charge intensity leads to a considerable enhancement of energy ext

Marcel Bengs, Nils Gessert, Alexander Schlaefer

Forecasting motion of a specific target object is a common problem for surgical interventions, e.g. for localization of a target region, guidance for surgical interventions, or motion compensation. Optical coherence tomography (OCT) is an imaging modality with a high spatial and temporal resolution. Recently, deep learning methods have shown promising perfor

Gaëtan Hadjeres, Léopold Crestel

In this work, we propose a flexible method for generating variations of discrete sequences in which tokens can be grouped into basic units, like sentences in a text or bars in music. More precisely, given a template sequence, we aim at producing novel sequences sharing perceptible similarities with the original template without relying on any annotation; so

Luigi Bellomarini, Marco Benedetti, Andrea Gentili, Rosario Laurendi

In the COVID-19 outbreak, governments have applied progressive restrictions to production activities, permitting only those that are considered strategic or that provide essential services. This is particularly apparent in countries that have been stricken hard by the virus, with Italy being a major example. Yet we know that companies are not just isolated e

E. M. Koltsova, E. S. Kurkina, A. M. Vasetsky

To model the spread of COVID-19 coronavirus in Russian regions and in Moscow, a discrete logistic equation describing the increase in the number of cases is used. To check the adequacy of the mathematical model, the simulation results were compared with the spread of coronavirus in China, in a number of European and Asian countries, and the United States. Th

Allison Koenecke, Michael Powell, Ruoxuan Xiong, Zhu Shen

In severe viral pneumonia, including Coronavirus disease 2019 (COVID-19), the viral replication phase is often followed by hyperinflammation, which can lead to acute respiratory distress syndrome, multi-organ failure, and death. We previously demonstrated that alpha-1 adrenergic receptor ($\alpha_1$-AR) antagonists can prevent hyperinflammation and death in

Idris Badmus, Abdelquoddouss Laghrissi, Ari Pouttu

Network slicing is the means of logically isolating network capabilities from a one size fits all to a set of different slices where each slice is responsible for specific network requirements. In the same light, the micro-operator concept is targeted at local deployment of 5G for vertical specific services. When a network slice instance (NSI) is created acr

Felix Fiedler, Christoph Döpmann, Florian Tschorsch, Sergio Lucia

In the Tor network, anonymity is achieved through a multi-layered architecture, which comes at the cost of a complex network. Scheduling data in this network is a challenging task and the current approach shows to be incapable of avoiding network congestion and allocating fair data rates. We propose PredicTor, a distributed model predictive control approach,

Haruya Mizutani, Xiaohua Yao

Let \( H = (-\Delta)^m + V \) be a higher-order elliptic operator on \( L^2(\mathbb{R}^n) \), where \( V \) is a general bounded decaying potential. This paper focuses on the global Kato smoothing and Strichartz estimates for solutions to Schr\"odinger-type equation associated with \( H \). In particular, we first establish sharp global Kato smoothing estima

Marcel Bengs, Nils Gessert, Matthias Schlüter, Alexander Schlaefer

Purpose. Localizing structures and estimating the motion of a specific target region are common problems for navigation during surgical interventions. Optical coherence tomography (OCT) is an imaging modality with a high spatial and temporal resolution that has been used for intraoperative imaging and also for motion estimation, for example, in the context o

Francesco Restuccia, Tommaso Melodia

The unprecedented requirements of the Internet of Things (IoT) have made fine-grained optimization of spectrum resources an urgent necessity. Thus, designing techniques able to extract knowledge from the spectrum in real time and select the optimal spectrum access strategy accordingly has become more important than ever. Moreover, 5G and beyond (5GB) network

Costante Bellettini

We address the one-parameter minmax construction, via Allen--Cahn energy, that has recently lead to a new proof of the existence of a closed minimal hypersurface in an arbitrary compact Riemannian manifold $N^{n+1}$ with $n\geq 2$ (see Guaraco's 2018 work). We obtain the following multiplicity-$1$ result: if the Ricci curvature of $N$ is positive then the mi

Tanmoy Paul, Narayan Banerjee

In the present paper, we explore the possible effects of a second rank antisymmetric tensor field, known as Kalb-Ramond (KR) field, on cosmological particle production as well as on quantum entanglement for a massive scalar field propagating in a four dimensional FRW spacetime evolves through a symmetric bounce. For this purpose, the scalar field is consider

Marek Lassak

Similarly to the classic notion in $E^d$, a subset of a positive diameter below $\frac{\pi}{2}$ of a hemisphere of the sphere $S^d$ is called complete, provided adding any extra point increases its diameter. Complete sets are convex bodies on $S^d$. Our main theorem says that on $S^d$ complete bodies of diameter $\delta$ coincide with bodies of constant widt

Robert Voinescu, Jung-Shen B. Tai, Ivan I. Smalyukh

Three-dimensional topological solitons attract a great deal of interest in fields ranging from particle physics to cosmology but remain experimentally elusive in solid-state magnets. Here we numerically predict magnetic heliknotons, an embodiment of such nonzero-Hopf-index solitons localized in all spatial dimensions while embedded in a helical or conical ba

Haomiao Meng, Xingye Qiao

Inferring the heterogeneous treatment effect is a fundamental problem in the sciences and commercial applications. In this paper, we focus on estimating Conditional Average Treatment Effect (CATE), that is, the difference in the conditional mean outcome between treatments given covariates. Traditionally, Q-Learning based approaches rely on the estimation of

Franck Plunian, Rodion Stepanov, Mahendra Kumar Verma

In hydrodynamic and magnetohydrodynamic turbulence, expressions for the transfer rates rely on integrals over wavenumber triads $(\textbf{k,p,q})$ satisfying $\textbf{k+p+q=0}$. As an example $S_E^{uu}(\textbf{k|p,q})$ denotes the kinetic energy transfer rate to the mode $\textbf{k}$, from the two other modes in the triad, $\textbf{p}$ and $\textbf{q}$. As n

Tom Reichert, Paula Hillmann, Marcus Bleicher

The Ultra-relativistic Quantum Molecular Dynamics (UrQMD) transport approach is used to calculate $\Delta$(1232) yields in Ca+Ca, Ni+Ni and Au+Au collisions between 1 AGeV and 2 AGeV. We compare and validate two different methods to extract the yields of $\Delta$(1232) resonances in such low energy nuclear collisions: Firstly, the $\pi^-$ spectra at low $p_\

Andrea Guzmán-Mesa, Daniel Kitzmann, Chloe Fisher, Adam J. Burgasser

Warm Neptunes offer a rich opportunity for understanding exo-atmospheric chemistry. With the upcoming James Webb Space Telescope (JWST), there is a need to elucidate the balance between investments in telescope time versus scientific yield. We use the supervised machine learning method of the random forest to perform an information content analysis on a 11-p

H. E. S. S. Collaboration, :, H. Abdalla, R. Adam

The detection of the first electromagnetic counterpart to the binary neutron star (BNS) merger remnant GW170817 established the connection between short $\gamma$-ray bursts and BNS mergers. It also confirmed the forging of heavy elements in the ejecta (a so-called kilonova) via the r-process nucleosynthesis. The appearance of non-thermal radio and X-ray emis

Neda Ghafourian, Mahmood Roshan, Shahram Abbassi

The evolution of disk galaxies in modified gravity is studied by using high-resolution N-body simulations. More specifically, we use the weak field limit of two modified gravity theories, i.e., nonlocal gravity (NLG) and scalar-tensor-vector gravity known as MOG, and ignore the existence of dark matter halo. On the other hand, we construct the same models in

Julien Sedro, Hans Henrik Rugh

We consider cocycles obtained by composing sequences of transfer operators with positive weights, associated with uniformly expanding maps (possibly having countably many branches) and depending upon parameters. Assuming $C^k$ regularity with respect to coordinates and parameters, we show that when the sequence is picked within a certain uniform family the t

Goro Kobayashi, Tatsuki Kuribayashi, Sho Yokoi, Kentaro Inui

Attention is a key component of Transformers, which have recently achieved considerable success in natural language processing. Hence, attention is being extensively studied to investigate various linguistic capabilities of Transformers, focusing on analyzing the parallels between attention weights and specific linguistic phenomena. This paper shows that att

Luc Villandré, Jean-François Plante, Thierry Duchesne, Patrick Brown

Large spatiotemporal datasets are a challenge for conventional Bayesian models because of the cubic computational complexity of the algorithms for obtaining the Cholesky decomposition of the covariance matrix in the multivariate normal density. Moreover, standard numerical algorithms for posterior estimation, such as Markov Chain Monte Carlo (MCMC), are intr

Shohei Hisada, Taichi Murayama, Kota Tsubouchi, Sumio Fujita

[Background] Two clusters of coronavirus disease 2019 (COVID-19) were confirmed in Hokkaido, Japan in February 2020. To capture the clusters, this study employs Web search query logs and user location information from smartphones. [Material and Methods] First, we anonymously identified smartphone users who used a Web search engine (Yahoo! JAPAN Search) for t

Kaiyu Zheng, Stefanie Tellex

In this paper, we present pomdp_py, a general purpose Partially Observable Markov Decision Process (POMDP) library written in Python and Cython. Existing POMDP libraries often hinder accessibility and efficient prototyping due to the underlying programming language or interfaces, and require extra complexity in software toolchain to integrate with robotics s

Nikhil Mehta, Kevin J Liang, Vinay K Verma, Lawrence Carin

Naively trained neural networks tend to experience catastrophic forgetting in sequential task settings, where data from previous tasks are unavailable. A number of methods, using various model expansion strategies, have been proposed recently as possible solutions. However, determining how much to expand the model is left to the practitioner, and often a con

Caroline Heneka, Andrei Mesinger

Cross-correlating 21cm with known cosmic signals will be invaluable proof of the cosmic origin of the first 21cm detections. As some of the widest fields available, comprising thousands of sources with reasonably known redshifts, narrow-band Lyman alpha emitter (LAE) surveys are an obvious choice for such cross-correlation. Here we revisit the 21cm -- LAE cr

Chenxu Li, Olivier Scaillet, Yiwen Shen

We develop a novel five-component decomposition of optimal dynamic portfolio choice, which reveals the simultaneous impacts from market incompleteness and wealth-dependent utilities. Under the HARA utility and a nonrandom interest rate, we can explicitly solve for the optimal policy as a combination of a bond holding scheme and the corresponding simpler CRRA

Ilaria Carleo, Davide Gandolfi, Oscar Barragán, John H. Livingston

We report the discovery of a warm Neptune and a hot sub-Neptune transiting TOI-421 (BD-14 1137, TIC 94986319), a bright (V=9.9) G9 dwarf star in a visual binary system observed by the TESS space mission in Sectors 5 and 6. We performed ground-based follow-up observations -- comprised of LCOGT transit photometry, NIRC2 adaptive optics imaging, and FIES, CORAL

Sergei Nayakshin, Takashi Tsukagoshi, Cassandra Hall, Allona Vazan

Dark rings with bright rims are the indirect signposts of planets embedded in protoplanetary discs. In a recent first, an azimuthally elongated AU-scale blob, possibly a planet, was resolved with ALMA in TW Hya. The blob is at the edge of a cliff-like rollover in the dust disc rather than inside a dark ring. Here we build time-dependent models of TW Hya disc

Felix Rech, Kai Huang

From the prevention of natural disasters such as landslide and avalanches, to the enhancement of energy efficiencies in chemical and civil engineering industries, understanding the collective dynamics of granular materials is a fundamental question that are closely related to our daily lives. Using a recently developed multi-static radar system operating at

Chengyi Wang, Yu Wu, Shujie Liu, Ming Zhou

End-to-end speech translation poses a heavy burden on the encoder, because it has to transcribe, understand, and learn cross-lingual semantics simultaneously. To obtain a powerful encoder, traditional methods pre-train it on ASR data to capture speech features. However, we argue that pre-training the encoder only through simple speech recognition is not enou

Oskar Gustafsson, Mattias Villani, Pär Stockhammar

Bayesian models often involve a small set of hyperparameters determined by maximizing the marginal likelihood. Bayesian optimization is a popular iterative method where a Gaussian process posterior of the underlying function is sequentially updated by new function evaluations. An acquisition strategy uses this posterior distribution to decide where to place

Libo Qin, Xiao Xu, Wanxiang Che, Ting Liu

In real-world scenarios, users usually have multiple intents in the same utterance. Unfortunately, most spoken language understanding (SLU) models either mainly focused on the single intent scenario, or simply incorporated an overall intent context vector for all tokens, ignoring the fine-grained multiple intents information integration for token-level slot

J. Collens, K. Pusuluri, A. Kelly, D. Knapper

We disclose the generality of the intrinsic mechanisms underlying multistability in reciprocally inhibitory 3-cell circuits composed of simplified, low-dimensional models of oscillatory neurons, as opposed to those of a detailed Hodgkin- Huxley type . The computational reduction to return maps for the phase-lags between neurons reveals a rich multiplicity of

Zhonghao Zhang, Yipeng Liu, Jiani Liu, Fei Wen

Most compressive sensing (CS) reconstruction methods can be divided into two categories, i.e. model-based methods and classical deep network methods. By unfolding the iterative optimization algorithm for model-based methods onto networks, deep unfolding methods have the good interpretation of model-based methods and the high speed of classical deep network m

Laurens Versluis, Alexandru Iosup

Workflows are prevalent in today's computing infrastructures. The workflow model support various different domains, from machine learning to finance and from astronomy to chemistry. Different Quality-of-Service (QoS) requirements and other desires of both users and providers makes workflow scheduling a tough problem, especially since resource providers need

Raghavendra Selvan, Erik B Dam

With the increasing adoption of machine learning tools like neural networks across several domains, interesting connections and comparisons to concepts from other domains are coming to light. In this work, we focus on the class of Tensor Networks, which has been a work horse for physicists in the last two decades to analyse quantum many-body systems. Buildin

Shuxi Zeng, Fan Li, Rui Wang, Fan Li

Chance imbalance in baseline characteristics is common in randomized clinical trials. Regression adjustment such as the analysis of covariance (ANCOVA) is often used to account for imbalance and increase precision of the treatment effect estimate. An objective alternative is through inverse probability weighting (IPW) of the propensity scores. Although IPW a

Hiroya Nakao, Igor Mezić

We provide an overview of the Koopman operator analysis for a class of partial differential equations describing relaxation of the field variable to a stable stationary state. We introduce Koopman eigenfunctionals of the system and use the notion of conjugacy to develop spectral expansion of the Koopman operator. For linear systems such as the diffusion equa

C. Geng, D. Dickinson, H. R. Wilson

Microtearing modes have been widely reported as a tearing parity electron temperature gradient driven plasma instability, which leads to fine scale tearing of the magnetic flux surfaces thereby resulting in reconnection of magnetic field lines and formation of magnetic islands. In slab geometry it has previously been shown that the drive mechanism requires a

Wei Luo, Junyi Ji, Jinlian Lu, Xiuwen Zhang

Two-dimensional (2D) band crossing semimetals (BCSMs) could be used to build a range of novel nanoscale devices such as superlenses and transistors. We find that symmorphic symmetry can protect a new type of robust 2D BCSMs, unlike the previously proposed 2D essential BCSMs protected by non-symmorphic symmetry [Young et al., Phys. Rev. Lett. 115, 126803 (201

Mohammad Taghi Dabiri, Mohsen Rezaee, Imran Shafique Ansari

The channel modeling of unnamed aerial vehicle (UAV)-based free-space optical (FSO) links with nonzero boresight pointing error is the subject of this paper. In particular, utilizing log-normal turbulence model, we propose a novel closed-form statistical channel model for UAV-based FSO links that takes into account the effect of nonzero boresight pointing er

Yanhe Huang, George Petroulakis, Frank Sottile, Igor Zelenko

A typical linear projection of the Grassmannian in its Plucker embedding is injective, unless its image is a projective space. A notable exception are self-adjoint linear projections, which have even degree. We consider linear projections of Gr_3(C^6) with low-dimensional centers of projection. When the center has dimension less than five, we show that the p

Ming Du, Chris Jacobsen

Electron and x-ray microscopes allow one to image the entire, unlabeled structure of hydrated materials at a resolution well beyond what visible light microscopes can achieve. However, both approaches involve ionizing radiation, so that radiation damage must be considered as one of the limits to imaging. Drawing upon earlier work, we describe here a unified

Shenghan Wang, Yipeng Liu, Lanlan Feng, Ce Zhu

Robust tensor principal component analysis (RTPCA) can separate the low-rank component and sparse component from multidimensional data, which has been used successfully in several image applications. Its performance varies with different kinds of tensor decompositions, and the tensor singular value decomposition (t-SVD) is a popularly selected one. The stand

J. E. Ramírez, C. Pajares

In string percolation model, the study of colliding systems at high energies is based on a continuum percolation theory in two dimensions where the number of strings distributed in the surface of interest is strongly determined by the size and the energy of the colliding particles. It is also expected that the surface where the disks are lying be finite, def

Yifei Liu, Chao Chen, Xi Zhang, Sihong Xie

Probabilistic graphical models, such as Markov random fields (MRF), exploit dependencies among random variables to model a rich family of joint probability distributions. Sophisticated inference algorithms, such as belief propagation (BP), can effectively compute the marginal posteriors. Nonetheless, it is still difficult to interpret the inference outcomes

Yuwang Hu, Jiefeng Liu, Yunhe Sheng

In this paper, first we study infinitesimal deformations of a Lie algebra with a representation and introduce the notion of a Nijenhuis pair, which gives a trivial deformation of a Lie algebra with a representation. Then we introduce the notion of a Kupershmidt-(dual-)Nijenhuis structure on a Lie algebra with a representation, which is a generalization of th

Jan-Hendrik Storm, Oliver Kieler, Rainer Körber

We recently demonstrated a 1$^{\textrm{st}}$-order axial gradiometer SQUID system, which is operated in a liquid He dewar with negligible noise contribution. The achieved close to SQUID-limited measured coupled energy sensitivity $\varepsilon_{c}$ of $\sim 30\,h$ corresponds to a white field noise below 180~aT~Hz${^{-1/2}}$. In order to further improve the S

Maximilian Kloock, Patrick Scheffe, Janis Maczijewski, Alexandru Kampmann

This paper introduces our Cyber-Physical Mobility Lab (CPM Lab). It is an open-source development environment for networked and autonomous vehicles with focus on networked decision-making, trajectory planning, and control. The CPM Lab hosts 20 physical model-scale vehicles ({\mu}Cars) which we can seamlessly extend by unlimited simulated vehicles. The code a

Denis Bonheure, Giovanni P. Galdi, Filippo Gazzola

Fluid flows around an obstacle generate vortices which, in turn, generate lift forces on the obstacle. Therefore, even in a perfectly symmetric framework equilibrium positions may be asymmetric. We show that this is not the case for a Poiseuille flow in an unbounded 2D channel, at least for small Reynolds number and flow rate. We consider both the cases of v

Payam Karisani, Joyce C. Ho, Eugene Agichtein

Mining social media content for tasks such as detecting personal experiences or events, suffer from lexical sparsity, insufficient training data, and inventive lexicons. To reduce the burden of creating extensive labeled data and improve classification performance, we propose to perform these tasks in two steps: 1. Decomposing the task into domain-specific s

O. M. Boyarkin, I. O. Boyarkina

Opportunity of the solar flares (SF's) prediction observing the solar neutrino fluxes is investigated. In three neutrino generations the evolution of the neutrino flux traveling the coupled sunspots (CS's) which are the SF source is considered. It is assumed that the neutrinos possess both the dipole magnetic moment and the anapole moment while the magnetic

Shintarou Yanagida

We discuss the gluing construction of class $\mathcal{S}$ chiral algebras in derived setting. The gluing construction in non-derived setting was introduced by Arakawa to construct a family of vertex algebras of which the associated varieties give genus zero Moore-Tachikawa symplectic varieties. Motivated by the higher genus case, we introduce a dg vertex alg

John Cremona, Filip Najman

By reformulating and extending results of Elkies, we prove some results on $\mathbb Q$-curves over number fields of odd degree. We show that, over such fields, the only prime isogeny degrees~$\ell$ which an elliptic curve without CM may have are those degrees which are already possible over~$\mathbb Q$ itself (in particular, $\ell\le37$), and we show the exi

Chiranjib Saha, Harpreet S. Dhillon

In this letter, we characterize the distribution of the number of users associated with the typical base station (BS), termed the typical cell load, in a cellular network where the BSs are distributed as a homogeneous Poisson point process (PPP) and the users are distributed as an independent Poisson cluster process (PCP). In this setting, we derive the exac

Paul H. Frampton

Among particle theory candidates for the dark matter constituents. axions and WIMPs are the most popular. In this talk we discuss these then focus on our preferred astrophysical candidate, the Primordial Intermediate Mass Black Holes in the acronym $DM=PIMBHs$. The earliest experimental confirmation may come from microlensing of the Magellanic Clouds at the

Yuming Shang, Heyan Huang, Xin Sun, Xianling Mao

Relation ties, defined as the correlation and mutual exclusion between different relations, are critical for distant supervised relation extraction. Existing approaches model this property by greedily learning local dependencies. However, they are essentially limited by failing to capture the global topology structure of relation ties. As a result, they may

Alexander Bors

Let $G$ be a group. A function $G\rightarrow G$ of the form $x\mapsto x^{\alpha}g$ for a fixed automorphism $\alpha$ of $G$ and a fixed $g\in G$ is called an affine map of $G$. In this paper, we study finite groups $G$ with an affine map of large order. More precisely, we show that if $G$ admits an affine map of order larger than $\frac{1}{2}|G|$, then $G$ i

Fabian Ritter, Sebastian Hack

Achieving peak performance in a computer system requires optimizations in every layer of the system, be it hardware or software. A detailed understanding of the underlying hardware, and especially the processor, is crucial to optimize software. One key criterion for the performance of a processor is its ability to exploit instruction-level parallelism. This

Shurun Wang, Shiqi Wang, Wenhan Yang, Xinfeng Zhang

It plays a fundamental role to compactly represent the visual information towards the optimization of the ultimate utility in myriad visual data centered applications. With numerous approaches proposed to efficiently compress the texture and visual features serving human visual perception and machine intelligence respectively, much less work has been dedicat

Chunxiuzi Liu, Fengyang Sun, Qingrui Ni, Lin Wang

Classical benchmark problems utilize multiple transformation techniques to increase optimization difficulty, e.g., shift for anti centering effect and rotation for anti dimension sensitivity. Despite testing the transformation invariance, however, such operations do not really change the landscape's "shape", but rather than change the "view point". For insta

Tomohiro Abe

We study the effect of the early kinetic decoupling in a model of fermionic dark matter (DM) that interacts with the standard model particles only by exchanging the Higgs boson. There are two DM-Higgs couplings, namely CP-conserving and CP-violating couplings. If the mass of the DM is slightly below half of the Higgs boson mass, then the couplings are suppre

Emanuele Papini, Antonio Cicone, Mirko Piersanti, Luca Franci

Turbulent space and astrophysical plasmas exhibit a complex dynamics, which involves nonlinear coupling across different temporal and spatial scales. There is growing evidence that impulsive events, such as magnetic reconnection instabilities, lead to a spatially localized enhancement of energy dissipation, thus speeding up the energy transfer at small scale

Elton P. Hsu, Cheng Ouyang

We prove a geometric extension of L\'evy's occupation time arcsine law near a hypersurface on a Riemannian manifold. The deviation from the classic arcsine law is of the order of the square-root of the time horizon and is expressed explicitly in terms of the mean curvature of the hypersurface and the local time of the underlying standard Brownian motion.