October 2020 arXiv papers — page 33

Ye Wang, Cyrus Samii, Haoge Chang, P. M. Aronow

We consider design-based causal inference for spatial experiments in which treatments may have effects that bleed out and feed back in complex ways. Such spatial spillover effects violate the standard ``no interference'' assumption for standard causal inference methods. The complexity of spatial spillover effects also raises the risk of misspecification and

Youssef Mousaaid, Alistair Savage

We define the affinization of an arbitrary monoidal category $\mathcal{C}$, corresponding to the category of $\mathcal{C}$-diagrams on the cylinder. We also give an alternative characterization in terms of adjoining dot generators to $\mathcal{C}$. The affinization formalizes and unifies many constructions appearing in the literature. In particular, we descr

J. Borovicka, M. Setvak, H. Roesli, J. K. Kerkmann

One of the most energetic bolide events in recent decades was detected by the US Government sensors (USGS) over remote areas of the Bering Sea on December 18, 2018, 23:48 UT. No ground-based optical observations exist. Using the satellite imagery of the dust trail left behind by the bolide, we tried to reconstruct the bolide trajectory. In combination with t

O. O. Zdorevskyi, S. M. Perepelytsya

The structure of DNA double helix is stabilized by metal counterions condensed to a diffuse layer around the macromolecule. The dynamics of counterions in real conditions is governed by the electric fields from DNA and other biological macromolecules. In the present work the molecular dynamics study {was} performed for the system of DNA double helix with neu

Valery V. Smirnov, Margarita I. Zhilnikova1, Ekaterina V. Barmina, Georgy A. Shafeev

Laser fragmentation of Al nanoparticles in liquid isopropanol is experimentally studied. Nanoparticles are characterized by Transmission Electron Microscopy and measuring disk centrifuge. As the result, the size of Al nanoparticles is reduced from more than 100 nm down to 10 nm. These nanoparticles are considered as additives to liquid hydrocarbon fuels.

C. R. Jayanarayanan, T. S. S. R. K. Rao

In this article, we analyse the structure of finite dimensional subspaces of the set of points of strong subdifferentiability in a dual space. In a dual $L_1(\mu)$ space, such a subspace is in the discrete part of the Yoshida-Hewitt type decomposition. In this set up, any Banach space consisting of points of strong subdifferentiability is necessarily finite

Ryousei Takano, Kuniyasu Suzaki

A conventional data center that consists of monolithic-servers is confronted with limitations including lack of operational flexibility, low resource utilization, low maintainability, etc. Resource disaggregation is a promising solution to address the above issues. We propose a concept of disaggregated cloud data center architecture called Flow-in-Cloud (FiC

Shyam Das, Nayan Sarkar, Monimala Mondal, Farook Rahaman

We develop a new model for a spherically symmetric dark matter fluid sphere containing two regions: {\bf (i)} Isotropic inner region with constant density and {\bf (ii)} Anisotropic outer region. We solve the system of field equation by assuming a particular density profile along with a linear equation of state. The obtained solutions are well-behaved and ph

Artem Khyzha, Ori Lahav

We study the formal semantics of non-volatile memory in the x86-TSO architecture. We show that while the explicit persist operations in the recent model of Raad et al. from POPL'20 only enforce order between writes to the non-volatile memory, it is equivalent, in terms of reachable states, to a model whose explicit persist operations mandate that prior write

Andrei I. Pavlov, Mikhail N. Kiselev

We present a microscopic theory for quantum thermoelectric and heat transport in the Schwarzian regime of the Sachdev-Ye-Kitaev (SYK) model. As a charged fermion realization of the SYK model in nanostructures we assume a setup based on a quantum dot connected to the charge reservoirs through weak tunnel barriers. We analyze particle-hole symmetry breaking ef

Baocheng Zhang

Lorentz symmetry violation (LV) was recently proposed to be testable with a new method, in which the effect of the violation is described as a certain local interaction [R. Shaniv, et al, PRL 120, 103202 (2018)]. We revisit this LV effect in the paper and show that it is not only local, but it also represents a classical violation according to the recent qua

Weidong Mei, Rui Zhang

Intelligent reflecting surface (IRS) has been deemed as a transformative technology to achieve smart and reconfigurable environment for wireless communication. This letter studies a new IRS-aided communication system, where multiple IRSs assist in the communication between a multi-antenna base station (BS) and a remote single-antenna user by multi-hop signal

Ozan Caglayan, Pranava Madhyastha, Lucia Specia

Automatic evaluation of language generation systems is a well-studied problem in Natural Language Processing. While novel metrics are proposed every year, a few popular metrics remain as the de facto metrics to evaluate tasks such as image captioning and machine translation, despite their known limitations. This is partly due to ease of use, and partly becau

O. O. Sobol, A. V. Lysenko, E. V. Gorbar, S. I. Vilchinskii

In order to describe magnetogenesis during inflation in the kinetic coupling model, we utilize a gradient expansion which is based on the fact that only long-wavelength (superhorizon) modes undergo amplification. For this purpose, we introduce a set of functions (bilinear combinations of electromagnetic fields with an arbitrary number of spatial curls) satis

Andrew James Bruce

We examine Lie (super)algebroids equipped with a homological section, i.e., an odd section that `self-commutes', we refer to such Lie algebroids as inner Q-algebroids: these provide natural examples of suitably "superised" Q-algebroids in the sense of Mehta. Such Lie algebroids are a natural generalisation of Q-manifolds and Lie superalgebras equipped with a

Naoki Takeuchi, Taiki Yamae, Hideo Suzuki, Nobuyuki Yoshikawa

Adiabatic quantum-flux-parametron (AQFP) circuits can operate with extremely small energy dissipation (~1 zJ per junction at 5 GHz) and high sensitivity (~1 {\mu}A) owing to adiabatic switching. Thus, AQFP logic is suitable to use as readout interfaces for cryogenic detectors, such as superconducting nanowire single-photon detectors (SSPDs). In order to exte

Linlin Hou, Ji Zhang, Ou Wu, Ting Yu

Literature analysis facilitates researchers to acquire a good understanding of the development of science and technology. The traditional literature analysis focuses largely on the literature metadata such as topics, authors, abstracts, keywords, references, etc., and little attention was paid to the main content of papers. In many scientific domains such as

Jia-Nan Guo, Xian-Ling Mao, Shu-Yang Lin, Wei Wei

Node classification in structural networks has been proven to be useful in many real world applications. With the development of network embedding, the performance of node classification has been greatly improved. However, nearly all the existing network embedding based methods are hard to capture the actual category features of a node because of the linearl

Marc Finzi, Ke Alexander Wang, Andrew Gordon Wilson

Reasoning about the physical world requires models that are endowed with the right inductive biases to learn the underlying dynamics. Recent works improve generalization for predicting trajectories by learning the Hamiltonian or Lagrangian of a system rather than the differential equations directly. While these methods encode the constraints of the systems u

S. D. Odintsov, V. K Oikonomou, F. P. Fronimos, K. V. Fasoulakos

In this work we shall demonstrate that it is possible to describe in a unified way a primordial bounce with the dark energy era, in the context of Gauss-Bonnet modified gravity. Particularly, the early time bounce has a nearly scale invariant power spectrum of primordial scalar curvature perturbations, while the dark energy era is a viable one, meaning that

Pablo Arrighi, Marios Christodoulou, Amélia Durbec

We provide a mathematically and conceptually robust notion of quantum superpositions of graphs. We argue that, crucially, quantum superpositions of graphs require node names for their correct alignment, which we demonstrate through a no-signalling argument. Nevertheless, node names are a fiducial construct, serving a similar purpose to the labelling of point

P. Lolur, M. Rahm, M. Skogh, L. García-Álvarez

We use the Variational Quantum Eigensolver (VQE) as implemented in the Qiskit software package to compute the ground state energy of small molecules derived from water, H$_2$O, and hydrogen cyanide, HCN. The work aims to benchmark algorithms for calculating the electronic structure and energy surfaces of molecules of relevance to prebiotic chemistry, beginni

C. Bougerol, E. Robin, E. Di Russo, E. Bellet-Amalric

Attaining low resistivity AlGaN layers is the keystone to improve the efficiency of light emitting devices in the ultraviolet spectral range. Here, we present a microstructural analysis of Ge-doped AlGaN samples with Al mole fraction from x=0 to 1, and nominal doping level in the range of 1E20 cm-3, together with the measurement of Ge concentration and its s

Ning Su, Qingbo Wang, Jinguo Hu, Xianghua Su

We consider the topological defects and spin structures of spin-1 Bose-Einstein condensates (BECs) with spin-orbit coupling (SOC) and dipole-dipole interaction (DDI) in a rotating harmonic plus quartic trap. The combined effects of SOC, DDI and rotation on the ground-state phases of the system are analyzed. Our results show that for fixed rotation frequency

Rooji Jinan, Ajay Badita, Tejas Bodas, Parimal Parag

Dispatching policies such as the join shortest queue (JSQ), join smallest work (JSW) and their power of two variants are used in load balancing systems where the instantaneous queue length or workload information at all queues or a subset of them can be queried. In situations where the dispatcher has an associated memory, one can minimize this query overhead

Prathamesh Saraf, R. N. Ponnalagu

This paper aims to design an optimal stability controller for a point to point trajectory tracking 3 degree of freedom articulated manipulator. The DH convention is used to obtain the forward and inverse kinematics of the manipulator. The manipulator dynamics are formulated using the Lagrange Euler method to obtain a nonlinear system. The complicated nonline

A. Neronov, D. Semikoz

Chiral dynamo converting asymmetry between right and left-handed leptons in the early universe into helical magnetic field has been proposed as a possible cosmological magnetogenesis scenario. We show that this mechanism is strongly affected by viscous damping of primordial plasma motions excited by the dynamo. This effect modifies the expected range of stre

A. Díaz, A. Zafra, E. Martínez-Pañeda, J. M. Alegre

There is a need for numerical models capable of predicting local accumulation of hydrogen near stress concentrators and crack tips to prevent and mitigate hydrogen assisted fracture in steels. The experimental characterisation of trapping parameters in metals, which is required for an accurate simulation of hydrogen transport, is usually performed through th

Tim Quatmann, Joost-Pieter Katoen

This paper presents an efficient procedure for multi-objective model checking of long-run average reward (aka: mean pay-off) and total reward objectives as well as their combination. We consider this for Markov automata, a compositional model that captures both traditional Markov decision processes (MDPs) as well as a continuous-time variant thereof. The cru

Joni Pajarinen, Jens Lundell, Ville Kyrki

Manipulating unknown objects in a cluttered environment is difficult because segmentation of the scene into objects, that is, object composition is uncertain. Due to this uncertainty, earlier work has concentrated on either identifying the "best" object composition and deciding on manipulation actions accordingly, or, tried to greedily gather information abo

Nacime Bouziani, Frédéric Nataf, Pierre-Henri Tournier

We consider sweeping domain decomposition preconditioners to solve the Helmholtz equation in the case of stripwise domain decomposition with or without overlaps. We unify their derivation and convergence studies by expressing them as Jacobi, Gauss-Seidel, and Symmetric Gauss-Seidel methods for different numbering of the unknowns. The proposed framework enabl

Yu Zhang, Xiusi Chen, Yu Meng, Jiawei Han

Categorizing documents into a given label hierarchy is intuitively appealing due to the ubiquity of hierarchical topic structures in massive text corpora. Although related studies have achieved satisfying performance in fully supervised hierarchical document classification, they usually require massive human-annotated training data and only utilize text info

I. A. Golovchanskiy, N. N. Abramov, V. S. Stolyarov, M. Weides

The critical step for future quantum industry demands realization of efficient information exchange between different-platform hybrid systems, including photonic and magnonic systems, that can harvest advantages of distinct platforms. The major restraining factor for the progress in certain hybrid systems is the fundamentally weak coupling parameter between

Gerrit E. Elsinga, Takashi Ishihara, J. C. R. Hunt

Extreme dissipation events in turbulent flows are rare, but they can be orders of magnitude stronger than the mean dissipation rate. Despite its importance in many small-scale physical processes, there is presently no accurate theory or model for predicting the extrema as a function of the Reynolds number. Here, we introduce a new model for the dissipation P

Wei Wang, Yimeng Chai, Tao Cui, Chuang Wang

In recent studies, Generative Adversarial Network (GAN) is one of the popular schemes to augment the image dataset. However, in our study we find the generator G in the GAN fails to generate numerical data in lower-dimensional spaces, and we address overfitting in the generation. By analyzing the Directed Graphical Model (DGM), we propose a theoretical restr

Tomohiro Nishiyama

The binary divergences that are divergences between probability measures defined on the same 2-point set have an interesting property. For the chi-squared divergence and the relative entropy, it is known that their binary divergence attain lower bounds with given means and variances, respectively. In this note, we show that the binary divergence of the squar

Hao Tang, Zhiao Huang, Jiayuan Gu, Bao-Liang Lu

Current graph neural networks (GNNs) lack generalizability with respect to scales (graph sizes, graph diameters, edge weights, etc..) when solving many graph analysis problems. Taking the perspective of synthesizing graph theory programs, we propose several extensions to address the issue. First, inspired by the dependency of the iteration number of common g

Markus Lazar, Jakob Leck

In this paper, we give the covariant formulation of second gradient electrodynamics, which is a generalized electrodynamics of second order including derivatives of higher order. The relativistic form of the field equations, the energy-momentum tensor and the Lorentz force density are presented. For an electric point charge, the generalized Lienard-Wiechert

Diluka Loku Galappaththige, Rajan Shrestha, Gayan Amarasuriya Aruma Baduge

The performance of simultaneous wireless information and power transfer (SWIPT) in downlink (DL) cell-free massive multiple-input multiple-output (MIMO) is investigated. Tight approximations to the DL harvested energy and the DL/uplink (UL) achievable rates are derived for two practical channel state information (CSI) cases by using a non-linear energy harve

Zhenzhen Li, Jian-Yun Nie, Benyou Wang, Pan Du

Distant supervision provides a means to create a large number of weakly labeled data at low cost for relation classification. However, the resulting labeled instances are very noisy, containing data with wrong labels. Many approaches have been proposed to select a subset of reliable instances for neural model training, but they still suffer from noisy labeli

Cyril Renevey, Aurélien Barrau, Killian Martineau, Selim Touati

Recent data suggest that the Universe could be positively curved. Combined with an inflationary stage, this might lead to a curvature bounce instead of the Big Bang. The background evolution is presented, as a function of the parameters controlling the cosmic evolution. The primordial tensor spectrum is also calculated and possible observational footprints o

Dongming Wei, Yogi Ahmad Erlangga, Gulzat Zhumakhanova

In this paper, finite element method is applied to Leland's model for numerical simulation of option pricing with transaction costs. Spatial finite element models based on P1 and/or P2 elements are formulated in combination with a Crank-Nicolson-type temporal scheme. The temporal scheme is implemented using the Rannacher approach. Examples with several sets

Zhesong Yu, Xingjian Du, Bilei Zhu, Zejun Ma

The rise of video-sharing platforms has attracted more and more people to shoot videos and upload them to the Internet. These videos mostly contain a carefully-edited background audio track, where serious speech change, pitch shifting and various types of audio effects may involve, and existing audio identification systems may fail to recognize the audio. To

Unnikrishnan Menon, Divyani Panda

Over the past decade, most of the metropolitan cities across the world have been witnessing a degrading trend in air quality index. Exhaust emission data observations show that promotion of public transport could be a potential way out of this gridlock. Due to environmental concerns, numerous public transport authorities harbor a great interest in introducin

Markus Dahlmanns, Johannes Lohmöller, Ina Berenice Fink, Jan Pennekamp

Due to increasing digitalization, formerly isolated industrial networks, e.g., for factory and process automation, move closer and closer to the Internet, mandating secure communication. However, securely setting up OPC UA, the prime candidate for secure industrial communication, is challenging due to a large variety of insecure options. To study whether Int

Hikaru Takeda, Touru Yamauchi, Masashi Takigawa, Hajime Ishikawa

We report results of magnetization and $^{31}$P NMR measurements under high pressure up to 6.4~GPa on RbMoOPO$_4$Cl, which is a frustrated square-lattice antiferromagnet with competing nearest-neighbor and next-nearest-neighbor interactions. Anomalies in the pressure dependences of the NMR shift and the transferred hyperfine coupling constants indicate a str

K. Paraschou

In this work, a part of the Research and Development effort of the PICOSEC detector is presented. The PICOSEC detector is a novel gas-filled detector, based on the Micromegas detector, which has been developed by the RD-51 PICOSEC collaboration. Instead of relying on traditional direct ionization, the PICOSEC detector takes advantage of the prompt timing cha

Yanping Liu, Yang Jiao, Qihui Fan, Guoqiang Li

Cell migration, which can be significantly affected by intracellular signaling pathways (ICSP) and extracellular matrix (ECM), plays a crucial role in many physiological and pathological processes. The efficiency of cell migration, which is typically modeled as a persistent random walk (PRW), depends on two critical motility parameters, i.e., migration speed

Wenhao Zhan

We consider the privacy problem of statistical estimation from distributed data, where users communicate to a central processor over a Gaussian multiple-access channel(MAC). To avoid the inevitable sacrifice of data utility for privacy in digital transmission schemes, we devise an over-the-air estimation strategy which utilizes the additive nature of MAC cha

Ben Knudsen

We prove that the ordered configuration spaces of planar graphs have the highest possible topological complexity generically, as predicted by a conjecture of Farber. Our argument establishes the same generic maximality for all higher topological complexities. We include some discussion of the non-planar case, demonstrating that the standard approach to the c

Liang Hu, Chengwei Wu, Wei Pan

In this paper, we consider the state estimation problem for nonlinear stochastic discrete-time systems. We combine Lyapunov's method in control theory and deep reinforcement learning to design the state estimator. We theoretically prove the convergence of the bounded estimate error solely using the data simulated from the model. An actor-critic reinforcement

Suzhen Han

A piece of a labelled graph $\Gamma$ defined by D. Gruber is a labelled path that embeds into $\Gamma$ in two essentially different ways. We prove that graphical $Gr'(\frac{1}{6})$ small cancellation groups whose associated pieces have uniformly bounded length are relative hyperbolic. In fact, we show that the Cayley graph of such group presentation is asymp

Ramachandran Anantharaman, Virendra Sule

This paper defines a linear representation for nonlinear maps $F:\mathbb{F}^n\rightarrow\mathbb{F}^n$ where $\mathbb{F}$ is a finite field, in terms of matrices over $\mathbb{F}$. This linear representation of the map $F$ associates a unique number $N$ and a unique matrix $M$ in $\mathbb{F}^{N\times N}$, called the Linear Complexity and the Linear Representa

Benjamin Estermann, Markus Marks, Mehmet Fatih Yanik

Disentanglement is at the forefront of unsupervised learning, as disentangled representations of data improve generalization, interpretability, and performance in downstream tasks. Current unsupervised approaches remain inapplicable for real-world datasets since they are highly variable in their performance and fail to reach levels of disentanglement of (sem

Kangda Zhi, Cunhua Pan, Hong Ren, Kezhi Wang

This paper considers an uplink reconfigurable intelligent surface (RIS)-aided massive multiple-input multiple-output (MIMO) system with statistical channel state information (CSI). The RIS is deployed to help conventional massive MIMO networks serve the users in the dead zone. We consider the Rician channel model and exploit the long-time statistical CSI to

R. Silvotti, V. Schaffenroth, U. Heber, R. H. Østensen

EPIC 216747137 is a new HW~Virginis system discovered by the Kepler spacecraft during its K2 "second life". Like the other HW Vir systems, EPIC 216747137 is a post-common-envelope eclipsing binary consisting of a hot subluminous star and a cool low-mass companion. The short orbital period of 3.87 hours produces a strong reflection effect from the secondary (

A. Valero

TileCal is the central hadronic calorimeter of the ATLAS experiment at the Large Hadron Collider (LHC). It is a sampling detector where scintillating tiles are embedded in steel absorber plates. The tiles are grouped forming cells, which are read-out on both sides by photomultiplier tubes (PMTs). The PMT digital samples are transmitted to the Read-Out Driver

Andrea Asperti, Stefano Dal Bianco

We provide a syllabification algorithm for the Divine Comedy using techniques from probabilistic and constraint programming. We particularly focus on the synalephe, addressed in terms of the "propensity" of a word to take part in a synalephe with adjacent words. We jointly provide an online vocabulary containing, for each word, information about its syllabif

Juhan Bae, Roger Grosse

Hyperparameter optimization of neural networks can be elegantly formulated as a bilevel optimization problem. While research on bilevel optimization of neural networks has been dominated by implicit differentiation and unrolling, hypernetworks such as Self-Tuning Networks (STNs) have recently gained traction due to their ability to amortize the optimization

Nils Kohl, Ulrich Rüde

We employ textbook multigrid efficiency (TME), as introduced by Achi Brandt, to construct an asymptotically optimal monolithic multigrid solver for the Stokes system. The geometric multigrid solver builds upon the concept of hierarchical hybrid grids (HHG), which is extended to higher-order finite-element discretizations, and a corresponding matrix-free impl

Arne Brataas, Bart van Wees, Olivier Klein, Gregoire de Loubens

Spin insulatronics covers efforts to generate, detect, control, and utilize high-fidelity pure spin currents and excitations inside magnetic insulators. Ultimately, the new findings may open doors for pure spin-based information and communication technologies. The aim is to replace moving charges with dynamical entities that utilize low-dissipation coherent

Bowen Yuan, Yu-Sheng Li, Pengrui Quan, Chih-Jen Lin

We study the problem of learning similarity by using nonlinear embedding models (e.g., neural networks) from all possible pairs. This problem is well-known for its difficulty of training with the extreme number of pairs. For the special case of using linear embeddings, many studies have addressed this issue of handling all pairs by considering certain loss f

F. Javier García de Abajo, Valerio Di Giulio

Free electron beams such as those employed in electron microscopes have evolved into powerful tools to investigate photonic nanostructures with an unrivaled combination of spatial and spectral precision through the analysis of electron energy losses and cathodoluminescence light emission. In combination with ultrafast optics, the emerging field of ultrafast

Baha Eddine Youcef Belmekki, Mohamed-Slim Alouini

Researchers are currently speculating about what the role of beyond fifth-generation (B5G) or sixth generation (6G) wireless systems will be. Several use cases and applications are proposed, ranging from enhanced mobile broadband communications and massive ultra-reliable low-latency Communication to holographic telepresence and tactile communications. One cr

Alexandre Saint, Anis Kacem, Kseniya Cherenkova, Konstantinos Papadopoulos

The SHApe Recovery from Partial textured 3D scans challenge, SHARP 2020, is the first edition of a challenge fostering and benchmarking methods for recovering complete textured 3D scans from raw incomplete data. SHARP 2020 is organised as a workshop in conjunction with ECCV 2020. There are two complementary challenges, the first one on 3D human scans, and th

Kazuhiro Sano, Yoshihiro Nitta, Yoshiaki Ōno

Using first-principles calculations, we examine the transition temperature $T_{\rm c}$ of superconductivity in sodium tungsten bronze ( Na$_x$WO$_3$, where $x$ is equal to or less than unity ). Although $T_{\rm c}$ is relatively low $T_{\rm c}( <\sim 3 {\rm K})$, it is interesting that its characteristic exponential dependence on $x$ has been experimentally

Federico Pichi, Maria Strazzullo, Francesco Ballarin, Gianluigi Rozza

This work deals with optimal control problems as a strategy to drive bifurcating solution of nonlinear parametrized partial differential equations towards a desired branch. Indeed, for these governing equations, multiple solution configurations can arise from the same parametric instance. We thus aim at describing how optimal control allows to change the sol

Harry Yserentant

Let $n>m$, and let $A$ be an $(m\times n)$-matrix of full rank. Then obviously the estimate $\|Ax\|\leq\|A\|\|x\|$ holds for the euclidean norm of $x$ and $Ax$ and the spectral norm as the assigned matrix norm. We study the sets of all $x$ for which, for fixed $\delta<1$, conversely $\|Ax\|\geq\delta\,\|A\|\|x\|$ holds. It turns out that these sets fill, in

Masahiro Kawasaki, Wakutaka Nakano, Hiromasa Nakatsuka, Eisuke Sonomoto

Ultra-Light Axion-like Particle (ULAP) is motivated as one of the solutions to the small scale problems in astrophysics. When such a scalar particle oscillates with an $\mathcal{O}(1)$ amplitude in a potential shallower than quadratic, it can form a localized dense object, oscillon. Because of its longevity due to the approximate conservation of the adiabati

Qi Li, Dianzi Liu, Zhenghua Qian

Data-driven quantitative defect reconstructions using ultrasonic guided waves has recently demonstrated great potential in the area of non-destructive testing. In this paper, we develop an efficient deep learning-based defect reconstruction framework, called NetInv, which recasts the inverse guided wave scattering problem as a data-driven supervised learning

N. Añez-López, G. Busquet, P. M. Koch, J. M. Girart

B-fields are predicted to play a role in the formation of filamentary structures and their fragmentation process. We aim at investigating the role of the B-field in the process of core fragmentation toward the hub-filament systems in the IRDC G14.2, which present different fragmentation level. We performed observations of the thermal dust polarization at 350

E. Strugovshchikov, A. Pishtshev, S. Karazhanov

Rare-earth metal oxyhydride compositions are currently attracting increasing attention to develop materials with unusual optical responses. Herein, using computer simulations of the electronic and optical properties, the optical responses of two stable yttrium oxyhydride compounds, Y4H10O and YHO, are studied for the visible light range. The emphasis is on m

Xuelian Cheng, Yiran Zhong, Mehrtash Harandi, Yuchao Dai

To reduce the human efforts in neural network design, Neural Architecture Search (NAS) has been applied with remarkable success to various high-level vision tasks such as classification and semantic segmentation. The underlying idea for the NAS algorithm is straightforward, namely, to enable the network the ability to choose among a set of operations (e.g.,

Zhiyuan Wu, Hong Qi, Yu Jiang, Minghao Zhao

Model compression becomes a recent trend due to the requirement of deploying neural networks on embedded and mobile devices. Hence, both accuracy and efficiency are of critical importance. To explore a balance between them, a knowledge distillation strategy is proposed for general visual representation learning. It utilizes our well-designed activation map a

Tom Eelbode, Jeroen Bertels, Maxim Berman, Dirk Vandermeulen

In many medical imaging and classical computer vision tasks, the Dice score and Jaccard index are used to evaluate the segmentation performance. Despite the existence and great empirical success of metric-sensitive losses, i.e. relaxations of these metrics such as soft Dice, soft Jaccard and Lovasz-Softmax, many researchers still use per-pixel losses, such a

Trung Trinh, Samuel Kaski, Markus Heinonen

We introduce implicit Bayesian neural networks, a simple and scalable approach for uncertainty representation in deep learning. Standard Bayesian approach to deep learning requires the impractical inference of the posterior distribution over millions of parameters. Instead, we propose to induce a distribution that captures the uncertainty over neural network

Dörte Kreher, Cassandra Milbradt

We study a microscopic limit order book model, in which the order dynamics depend on the current best bid and ask price and the current volume density functions, simultaneously, and derive its macroscopic high-frequency dynamics. As opposed to the existing literature on scaling limits for limit order book models, we include price changes which do not scale w

Moritz Flaschel, Siddhant Kumar, Laura De Lorenzis

We propose a new approach for data-driven automated discovery of isotropic hyperelastic constitutive laws. The approach is unsupervised, i.e., it requires no stress data but only displacement and global force data, which are realistically available through mechanical testing and digital image correlation techniques; it delivers interpretable models, i.e., mo

Seyed Ali Hosseini Mansoori, Alireza Talebian, Hassan Firouzjahi

We study inflationary solution in an extension of mimetic gravity with the higher derivative interactions coupled to gravity. Because of the higher derivative interactions, the setup is free from the ghost and gradient instabilities while it hosts a number of novel properties. The dispersion relation of scalar perturbations develops quartic momentum correcti

Kenji Kobayashi, Yuri Nakao

With the widespread adoption of machine learning in the real world, the impact of the discriminatory bias has attracted attention. In recent years, various methods to mitigate the bias have been proposed. However, most of them have not considered intersectional bias, which brings unfair situations where people belonging to specific subgroups of a protected g

Mohammad Tasnimul Haque, Juuso Manninen, David Vitali, Pertti Hakonen

We propose a scheme for enhancing the optomechanical coupling between microwave and mechanical resonators by up to seven orders of magnitude to the ultrastrong coupling limit in a circuit optomechanical setting. The tripartite system considered here consists of a Josephson junction Cooper-pair box that mediates the coupling between the microwave cavity and t

Koichi Hattori, Hidetoshi Taya, Shinsuke Yoshida

We study di-lepton production from a single photon in the presence of a strong constant magnetic field. By the use of the Ritus-basis formalism, we analytically evaluate the photon--to--di-lepton conversion vertex with fully taking into account the non-perturbative interactions between the produced fermions and the strong magnetic field. We show that the di-

Anirudh Singhal, Subham Pirojiwala, Nikhil Karamchandani

Motivated by the mode estimation problem of an unknown multivariate probability density function, we study the problem of identifying the point with the minimum k-th nearest neighbor distance for a given dataset of n points. We study the case where the pairwise distances are apriori unknown, but we have access to an oracle which we can query to get noisy inf

Yuhai Song, Zhong Cao, Kailun Wu, Ziang Yan

The idea of unfolding iterative algorithms as deep neural networks has been widely applied in solving sparse coding problems, providing both solid theoretical analysis in convergence rate and superior empirical performance. However, for sparse nonlinear regression problems, a similar idea is rarely exploited due to the complexity of nonlinearity. In this wor

Jungin Lee

In this paper we improve the upper bound of the number $N_{K, n}(X)$ of degree $n$ extensions of a number field $K$ with absolute discriminant bounded by $X$. This is achieved by giving a short $\mathcal{O}_K$-basis of an order of an extension $L$ of $K$. Our result generalizes the best known upper bound on $N_{\mathbb{Q}, n}(X)$ by Lemke Oliver and Thorne t

Xiaojian Du, Sören Schlichting

We solve a leading-order QCD kinetic theory with light quarks and gluon degrees of freedom to study the non-equilibrium dynamics of the quark-gluon plasma (QGP). By including both elastic and inelastic scatterings for quarks and gluon, the model is proficient to describe kinetic and chemical equilibration of the QGP, and thus connects the initial (semi-) har

J. Ferretti, J. Kotila, R. I. Magaña Vsevolodovna, E. Santopinto

The structure of odd-$A$ $^{(115,117)}$Rh and $^{(115,117)}$Pd isotopes is studied by means of the neutron-proton Interacting Boson-Fermion Model (IBFM-2). $J^P = \frac{1}{2}^+$ quantum number assignment for the $^{(115,117)}$Pd ground-states is critically discussed and the predicted energy levels are compared to the existing experimental data. The resulting

Florian Köpf, Sean Kille, Jairo Inga, Sören Hohmann

While many theoretical works concerning Adaptive Dynamic Programming (ADP) have been proposed, application results are scarce. Therefore, we design an ADP-based optimal trajectory tracking controller and apply it to a large-scale ball-on-plate system. Our proposed method incorporates an approximated reference trajectory instead of using setpoint tracking and

Iurii Timrov, Francesco Aquilante, Luca Binci, Matteo Cococcioni

We present a derivation of the exact expression for Pulay forces in density-functional theory calculations augmented with extended Hubbard functionals, and arising from the use of orthogonalized atomic orbitals as projectors for the Hubbard manifold. The derivative of the inverse square root of the orbital overlap matrix is obtained as a closed-form solution

Zhipeng Ding, Marc Niethammer

Multi-atlas segmentation (MAS) is a popular image segmentation technique for medical images. In this work, we improve the performance of MAS by correcting registration errors before label fusion. Specifically, we use a volumetric displacement field to refine registrations based on image anatomical appearance and predicted labels. We show the influence of the

Kai Ploeger, Michael Lutter, Jan Peters

Robots that can learn in the physical world will be important to en-able robots to escape their stiff and pre-programmed movements. For dynamic high-acceleration tasks, such as juggling, learning in the real-world is particularly challenging as one must push the limits of the robot and its actuation without harming the system, amplifying the necessity of sam

A. Jakovac, D. Berenyi, P. Posfay

This paper is about the meaning of understanding in scientific and in artificial intelligent systems. We give a mathematical definition of the understanding, where, contrary to the common wisdom, we define the probability space on the input set, and we treat the transformation made by an intelligent actor not as a loss of information, but instead a reorganiz

Baisakh, Rakesh Mohanty

The design and analysis of efficient algorithms with the knowledge of current and past inputs is a non-trivial and challenging research area in computer science. In many practical applications the future inputs are not available to the algorithm at any instance of time. So the algorithm has to make decisions based on a sequence of inputs that are in order an

Nhan Thanh Nguyen, Kyungchun Lee, Huaiyu Dai

Although the sphere decoder (SD) is a powerful detector for multiple-input multiple-output (MIMO) systems, it has become computationally prohibitive in massive MIMO systems, where a large number of antennas are employed. To overcome this challenge, we propose fast deep learning (DL)-aided SD (FDL-SD) and fast DL-aided $K$-best SD (KSD, FDL-KSD) algorithms. T

Johannes Münch

The fate of matter forming a black hole is still an open problem, although models of quantum gravity corrected black holes are available. In loop quantum gravity (LQG) models were presented, which resolve the classical singularity in the centre of the black hole by means of a black-to-white hole transition, but neglect the collapse process. The situation is

Giang L. D. Nguyen, Willy Susilo, Dung Hoang Duong, Huy Quoc Le

Identity-based encryption with equality test supporting flexible authorization (IBEET-FA) allows the equality test of underlying messages of two ciphertexts while strengthens privacy protection by allowing users (identities) to control the comparison of their ciphertexts with others. IBEET by itself has a wide range of useful applicable domain such as keywor

Moritz Schneider, Jens Lang

Peer methods are a comprehensive class of time integrators offering numerous degrees of freedom in their coefficient matrices that can be used to ensure advantageous properties, e.g. A-stability or super-convergence. In this paper, we show that implicit-explicit (IMEX) Peer methods are well-balanced and asymptotic preserving by construction without additiona

Yong Joon Song, Dong Jin Ji, Hye In Seo, Gyu Bum Han

Various methods have been developed to analyze the association between organisms and their genomic sequences. Among them, sequence alignment is the most frequently used for comparative analysis of biological genomes. However, the traditional sequence alignment method is considerably complicated in proportion to the sequences' length, and it is significantly

Vasiliki Stergiopoulou, José Henrique de Morais Goulart, Sébastien Schaub, Luca Calatroni

Super-resolution light microscopy overcomes the physical barriers due to light diffraction, allowing for the observation of otherwise indistinguishable subcellular entities. However, the specific acquisition conditions required by state-of-the-art super-resolution methods to achieve adequate spatio-temporal resolution are often very challenging. Exploiting m

Thomas Bird, Friso H. Kingma, David Barber

Deep generative models provide a powerful set of tools to understand real-world data. But as these models improve, they increase in size and complexity, so their computational cost in memory and execution time grows. Using binary weights in neural networks is one method which has shown promise in reducing this cost. However, whether binary neural networks ca