March 2020 arXiv papers — page 26

Yusuke Fujimoto, Fumiya Maeda, Asao Habe, Kouji Ohta

Recent galaxy observations show that star formation activity changes depending on galactic environments. In order to understand the diversity of galactic-scale star formation, it is crucial to understand the formation and evolution of giant molecular clouds in an extreme environment. We focus on observational evidence that bars in strongly barred galaxies la

T. Muñoz-Darias, M. Armas Padilla, F. Jiménez-Ibarra, G. Panizo-Espinar

We present the discovery of an optical accretion disk wind in the X-ray transient Swift J1858.6-0814. Our 90-spectrum data set, taken with the 10.4m GTC telescope over 8 different epochs and across five months, reveals the presence of conspicuous P-Cyg profiles in He I at 5876 Angs and Halpha. These features are detected throughout the entire campaign, albei

J. A. de Freitas Pacheco, Joseph Silk

Primordial black holes formed in an early post-inflation matter-dominated epoch during preheating provide a novel pathway for a source of the dark matter that utilizes known physics in combination with plausible speculations about the role of quantum gravity. Two cases are considered here: survival of Planck-scale relics and an early universe accretion scena

M. G. Aartsen, M. Ackermann, J. Adams, J. A. Aguilar

Pulsar wind nebulae (PWNe) are the main gamma-ray emitters in the Galactic plane. They are diffuse nebulae that emit nonthermal radiation. Pulsar winds, relativistic magnetized outflows from the central star, shocked in the ambient medium produce a multiwavelength emission from the radio through gamma rays. Although the leptonic scenario is able to explain m

Glenn Wagner, Dung X. Nguyen, Steven H. Simon

We apply the semi-classical quantum Boltzmann formalism for the computation of transport properties to multilayer graphene. We compute the electrical conductivity as well as the thermal conductivity and thermopower for Bernal-stacked multilayers with an even number of layers. We show that the window for hydrodynamic transport in multilayer graphene is simila

Yihong Chen, Yue Cao, Han Hu, Liwei Wang

How do humans recognize an object in a piece of video? Due to the deteriorated quality of single frame, it may be hard for people to identify an occluded object in this frame by just utilizing information within one image. We argue that there are two important cues for humans to recognize objects in videos: the global semantic information and the local local

C. Hansel, W. An, W. Mori, J. B. Rosenzweig

The plasma wakefield accelerator may accelerate particles to high energy in a future linear collider with unprecedented acceleration gradients, exceeding the GeV/m range. Beams for this application would have extremely high brightness and, subject to the intense plasma ion-derived focusing, they would achieve densities high enough to induce the plasma ions t

Hidetoshi Taya

We study massive charged particle production from the vacuum confined between two vibrating plates in the presence of a strong electric field. We analytically derive a formula for the production number based on the perturbation theory in the Furry picture, and show that the Schwinger mechanism by the strong electric field and the dynamical Casimir effect by

Bin Liu, Yue Cao, Yutong Lin, Qi Li

This paper introduces a negative margin loss to metric learning based few-shot learning methods. The negative margin loss significantly outperforms regular softmax loss, and achieves state-of-the-art accuracy on three standard few-shot classification benchmarks with few bells and whistles. These results are contrary to the common practice in the metric learn

Shuda Li, Kai Han, Theo W. Costain, Henry Howard-Jenkins

In this paper, we tackle the task of establishing dense visual correspondences between images containing objects of the same category. This is a challenging task due to large intra-class variations and a lack of dense pixel level annotations. We propose a convolutional neural network architecture, called adaptive neighbourhood consensus network (ANC-Net), th

Sarah Pratt, Mark Yatskar, Luca Weihs, Ali Farhadi

We introduce Grounded Situation Recognition (GSR), a task that requires producing structured semantic summaries of images describing: the primary activity, entities engaged in the activity with their roles (e.g. agent, tool), and bounding-box groundings of entities. GSR presents important technical challenges: identifying semantic saliency, categorizing and

R. Reyes, J. M. Rodriguez, J. M. Sigarreta, M. Villeta

Gromov hyperbolicity is an interesting geometric property, and so it is natural to study it in the context of geometric graphs. It measures the tree-likeness of a graph from a metric viewpoint. In particular, we are interested in circular-arc graphs, which is an important class of geometric intersection graphs. In this paper we give sharp bounds for the hype

Hong-Jian He, Yin-Zhe Ma, Jiaming Zheng

Self-interacting neutrinos that begin to free-stream at close to matter-radiation equality can reduce the physical size of photon sound horizon at last scattering surface. This mechanism can be the reason why standard $\Lambda$CDM cosmology sees a lower value of the Hubble constant than local measurements from distance ladder. We propose a new realization of

Chenxi Liu, Piotr Dollár, Kaiming He, Ross Girshick

Existing neural network architectures in computer vision -- whether designed by humans or by machines -- were typically found using both images and their associated labels. In this paper, we ask the question: can we find high-quality neural architectures using only images, but no human-annotated labels? To answer this question, we first define a new setup ca

Rajesh Singh, R. Adhikari

The outbreak of the novel coronavirus, COVID-19, has been declared a pandemic by the WHO. The structures of social contact critically determine the spread of the infection and, in the absence of vaccines, the control of these structures through large-scale social distancing measures appears to be the most effective means of mitigation. Here we use an age-str

Ezequiel Alvarez, Federico Lamagna, Manuel Szewc

The appearance of a new dangerous and contagious disease requires the development of a drug therapy faster than what is foreseen by usual mechanisms. Many drug therapy developments consist in investigating through different clinical trials the effects of different specific drug combinations by delivering it into a test group of ill patients, meanwhile a plac

T. Balcerzak, K. Szałowski, M. Jaščur

The Ising one-dimensional (1D) chain with spin $S=1/2$ and magnetoelastic interactions is studied with the lattice contribution included in the form of elastic interaction and thermal vibrations simultaneously taken into account. The magnetic energy term and the elastic (static) energy term based on the Morse potential are calculated exactly. The vibrational

Thomas Mannel, Kevin Olschewsky, K. Keri Vos

The mechanism of CP violation remains one of the puzzles in particle physics. Key to understanding this phenomenon are nonleptonic $B$ decays, especially multibody decays which exhibit large CP asymmetries in various regions of phase space. A full QCD-based theoretical description of these decays is still missing, requiring the use of models to fit the data.

Hamidreza Ehteram, Mohammad Ali Maddah-Ali, Mahtab Mirmohseni

The emerging applications of machine learning algorithms on mobile devices motivate us to offload the computation tasks of training a model or deploying a trained one to the cloud or at the edge of the network. One of the major challenges in this setup is to guarantee the privacy of the client data. Various methods have been proposed to protect privacy in th

Yanbin Deng, Changyu Huang, Yong-Chang Huang

We propose a new method for neutrino mass generation through a modified Higgs mechanism by introducing an additional tiny vacuum breaking to the charged Higgs field. With identical particle spectrum as standard electroweak model, this modified Higgs mechanism endows the lepton-Higgs Yukawa coupling Lagrangian with a modified lepton mass matrix. Inserting the

Marcin Gronowski, Adam M. Koza, Michał Tomza

Ultracold polar and magnetic ${}^{23}$Na${}^6$Li molecules in the rovibrational ground state of the lowest triplet $a^3\Sigma^+$ electronic state have been recently produced. Here, we calculate the electronic and rovibrational structure of these 14-electron molecules with spectroscopic accuracy ($<0.5\,$cm$^{-1}$) using state-of-the-art ab initio methods of

O. G. Miranda, D. K. Papoulias, G. Sanchez Garcia, O. Sanders

The CENNS-10 experiment of the COHERENT collaboration has recently reported the first detection of coherent-elastic neutrino-nucleus scattering (CEvNS) in liquid Argon with more than $3 \sigma$ significance. In this work, we exploit the new data in order to probe various interesting parameters which are of key importance to CEvNS within and beyond the Standa

Sarath Gopi, Sheetal Kalyani, Lajos Hanzo

Millimeter wave communication is eminently suitable for high-rate wireless systems, which may be beneficially amalgamated with intelligent reflecting surfaces (IRS), relying on beam-index modulation. Explicitly, we propose three different architectures based on IRSs for beam-index modulation in millimeter wave communication, which circumvent the line-of-sigh

Alessandro Iraci, Anna Vanden Wyngaerd

Inspired by [Qiu, Wilson 2019] and [D'Adderio, Iraci, Vanden Wyngaerd 2019 - Delta Square], we formulate a generalised Delta square conjecture (valley version). Furthermore, we use similar techniques as in [Haglund, Sergel 2019] to obtain a schedule formula for the combinatorics of our conjecture. We then use this formula to prove that the (generalised) vall

Robert Schaback

From March 23rd, the data for the recovered cases of COVID-19 are missing from the standard repository maintained by the Johns Hopkins University in collaboration with the WHO. But since data concerning recovered patients are extremely important for modelling the COVID-19 outbreak, a method for estimating the missing data is provided and tested. As a byprodu

Yuda Qiu, Zhangyang Xiong, Kai Han, Zhongyuan Wang

In this paper we examine the problem of inverse rendering of real face images. Existing methods decompose a face image into three components (albedo, normal, and illumination) by supervised training on synthetic face data. However, due to the domain gap between real and synthetic face images, a model trained on synthetic data often does not generalize well t

Ebrahim M. Kolahdouz, Amneet P. S. Bhalla, Lawrence N. Scotten, Brent A. Craven

This paper introduces a sharp interface method to simulate fluid-structure interaction (FSI) involving rigid bodies immersed in viscous incompressible fluids. The capabilities of this methodology are demonstrated for a range of benchmark test cases along with large-scale models of biomedical FSI. The numerical approach developed herein, which we refer to as

Kiana Ehsani, Shubham Tulsiani, Saurabh Gupta, Ali Farhadi

When we humans look at a video of human-object interaction, we can not only infer what is happening but we can even extract actionable information and imitate those interactions. On the other hand, current recognition or geometric approaches lack the physicality of action representation. In this paper, we take a step towards a more physical understanding of

Sotiris Skaperas, Lefteris Mamatas, Arsenia Chorti

Video content is responsible for more than 70% of the global IP traffic. Consequently, it is important for content delivery infrastructures to rapidly detect and respond to changes in content popularity dynamics. In this paper, we propose the employment of on-line change point (CP) analysis to implement real-time, autonomous and low-complexity video content

Markus Loecher

We attempt to give a unifying view of the various recent attempts to (i) improve the interpretability of tree-based models and (ii) debias the the default variable-importance measure in random Forests, Gini importance. In particular, we demonstrate a common thread among the out-of-bag based bias correction methods and their connection to local explanation fo

Fan Zhou, Xovee Xu, Ce Li, Goce Trajcevski

Quantifying and predicting the long-term impact of scientific writings or individual scholars has important implications for many policy decisions, such as funding proposal evaluation and identifying emerging research fields. In this work, we propose an approach based on Heterogeneous Dynamical Graph Neural Network (HDGNN) to explicitly model and predict the

Marcos Baptista Rios, Roberto J. López-Sastre, Fabian Caba Heilbron, Jan van Gemert

The Online Action Detection (OAD) problem needs to be revisited. Unlike traditional offline action detection approaches, where the evaluation metrics are clear and well established, in the OAD setting we find very few works and no consensus on the evaluation protocols to be used. In this work we propose to rethink the OAD scenario, clearly defining the probl

Qilei Chen, Ping Liu, Jing Ni, Yu Cao

Diabetic retinopathy (DR) is a primary cause of blindness in working-age people worldwide. About 3 to 4 million people with diabetes become blind because of DR every year. Diagnosis of DR through color fundus images is a common approach to mitigate such problem. However, DR diagnosis is a difficult and time consuming task, which requires experienced clinicia

Zachary Teed, Jia Deng

We introduce Recurrent All-Pairs Field Transforms (RAFT), a new deep network architecture for optical flow. RAFT extracts per-pixel features, builds multi-scale 4D correlation volumes for all pairs of pixels, and iteratively updates a flow field through a recurrent unit that performs lookups on the correlation volumes. RAFT achieves state-of-the-art performa

Moacir Aloisio, Silas L. Carvalho, César R. de Oliveira

It is shown that, Baire generically, the bound states of the Hamiltonian of the Hydrogen atom have spectral measures with exact $0$-lower and $1/3$-upper generalized fractal dimensions; the relation to (a weak form of) dynamical delocalization along orthonormal bases is also discussed. Such result is a consequence of the distribution of the Hamiltonian eigen

Yusuke Kimura

In this study, we analyze gauge groups in six-dimensional $N=1$ F-theory models. We construct elliptic Calabi-Yau 3-folds possessing various singularity types as double covers of "1/2 Calabi-Yau 3-folds", a class of rational elliptic 3-folds, by applying the method discussed in a previous study to classify the singularity types of the 1/2 Calabi-Yau 3-folds.

Gorka Muñoz-Gil, Giovanni Volpe, Miguel Angel Garcia-March, Ralf Metzler

The deviation from pure Brownian motion generally referred to as anomalous diffusion has received large attention in the scientific literature to describe many physical scenarios. Several methods, based on classical statistics and machine learning approaches, have been developed to characterize anomalous diffusion from experimental data, which are usually ac

Sean T. McQuade, Nathaniel J. Merrill, Benedetto Piccoli

This paper serves as a framework for designing advanced models for drug action on metabolism. Drug treatment may affect metabolism by either enhancing or inhibiting metabolic reactions comprising a metabolic network. We introduce the concept of \textit{metabolic graphs}, a generalization of hypergraphs having specialized features common to metabolic networks

Tilman Preuschoff, Malte Schlosser, Gerhard Birkl

We present a general analysis for determining the optimal modulation parameters for the modulation transfer spectroscopy scheme. The results are universally valid and can be applied to spectroscopy of any atomic species requiring only the knowledge of the effective linewidth $\Gamma_{eff}$. A signal with optimized slope and amplitude is predicted for a large

Miroslav Mitev, Arsenia Chorti, E. Veronica Belmega, Martin Reed

Wireless secret key generation (W-SKG) from shared randomness (e.g., from the wireless channel fading realizations), is a well established scheme that can be used for session key agreement. W-SKG approaches can be of particular interest in delay constrained wireless networks and notably in the context of ultra reliable low latency communications (URLLC) in b

Antoine Mahoro, Mirjana Pović, Petri Väisänen, Pheneas Nkundabakura

In this study, we analysed active galactic nuclei in the "green valley" by comparing active and non-active galaxies using data from the COSMOS field. We found that most of our X-ray detected active galactic nuclei with far-infrared emission have star formation rates higher than the ones of normal galaxies of the same stellar mass range.

Lucas Böttcher, Mingtao Xia, Tom Chou

Different ways of calculating mortality ratios during epidemics have yielded very different results, particularly during the current COVID-19 pandemic. We formulate both a survival probability model and an associated infection duration-dependent SIR model to define individual- and population-based estimates of dynamic mortality ratios. The key parameters tha

Simon Becker, Federica Gregorio, Delio Mugnolo

We analyze properties of semigroups generated by Schr\"odinger operators $-\Delta+V$ or polyharmonic operators $-(-\Delta)^m$, on metric graphs both on $L^p$-spaces and spaces of continuous functions. In the case of spatially constant potentials, we provide a semi-explicit formula for their kernel. Under an additional sub-exponential growth condition on the

B. Ananthanarayan, Samuel Friot, Shayan Ghosh

The three-loop QED mass-dependent contributions to the $g-2$ of each of the charged leptons with two internal closed fermion loops, sometimes called $A^{(6)}_3\left(\frac{m_1}{m_2}, \frac{m_1}{m_3}\right)$ in the $g-2$ literature, is revisited using the Mellin-Barnes (MB) representation technique. Results for the muon and $\tau$ lepton anomalous magnetic mom

Georg Grasegger, Jan Legerský

In this paper we present the SageMath package FlexRiLoG (short for flexible and rigid labelings of graphs). Based on recent results the software generates motions of graphs using special edge colorings. The package computes and illustrates the colorings and the motions. We present the structure and usage of the package.

Yong-Shang Long, Zheng-Meng Zhai, Li-Lei Han, Jie Kang

An urgent problem in controlling COVID-19 spreading is to understand the role of undocumented infection. We develop a five-state model for COVID-19, taking into account the unique features of the novel coronavirus, with key parameters determined by the government reports and mathematical optimization. Tests using data from China, South Korea, Italy, and Iran

Gustavo A. Nunez Segura, Sotiris Skaperas, Arsenia Chorti, Lefteris Mamatas

Software-defined networking (SDN) is a promising technology to overcome many challenges in wireless sensor networks (WSN), particularly with respect to flexibility and reuse. Conversely, the centralization and the planes' separation turn SDNs vulnerable to new security threats in the general context of distributed denial of service (DDoS) attacks. State-of-t

Vyacheslav N. Gorshkov, Vladimir V. Tereshchuk, Pooya Sareh

We have analyzed the expressed manifestation of the anisotropy of surface energy density in the dynamics of ultrathin nanowires, which break up into disjointed clusters when annealed below their melting temperature. The breakup process is studied for different temperatures and orientations of the nanowire axis relative to its internal crystal structure using

Saeed Khaki, Hieu Pham, Ye Han, Andy Kuhl

Precise in-season corn grain yield estimates enable farmers to make real-time accurate harvest and grain marketing decisions minimizing possible losses of profitability. A well developed corn ear can have up to 800 kernels, but manually counting the kernels on an ear of corn is labor-intensive, time consuming and prone to human error. From an algorithmic per

Youcheng Wang, G. Bosse, H. P. Nair, N. J. Schreiber

SrRuO$_3$, a ferromagnet with an approximately 160\,K Curie temperature, exhibits a $T^2$ dependent dc resistivity below $\approx$ 30 K. Nevertheless, previous optical studies in the infrared and terahertz range show non-Drude dynamics at low temperatures which seem to contradict a Fermi-liquid picture with long-lived quasiparticles. In this work, we measure

Hoang-Son Do, Giang Le

In this paper, we extend some recent results of Guedj-Lu-Zeriahi about psh envelopes of bounded functions on bounded domains in $\mathbb{C}^n$. We also present a result on the regularity of psh envelopes.

Geoff French, Avital Oliver, Tim Salimans

Consistency regularization is a technique for semi-supervised learning that underlies a number of strong results for classification with few labeled data. It works by encouraging a learned model to be robust to perturbations on unlabeled data. Here, we present a novel mask-based augmentation method called CowMask. Using it to provide perturbations for semi-s

Tom Bachmann

We establish a kind of "degree zero Freudenthal Gm-suspension theorem" in motivic homotopy theory. From this we deduce results about the conservativity of the P^1-stabilization functor. In order to establish these results, we show how to compute certain pullbacks in the cohomology of a strictly homotopy invariant sheaf in terms of the Rost--Schmid complex. T

Samuel Deng, Sanjam Garg, Somesh Jha, Saeed Mahloujifar

Poisoning attacks have emerged as a significant security threat to machine learning algorithms. It has been demonstrated that adversaries who make small changes to the training set, such as adding specially crafted data points, can hurt the performance of the output model. Some of the stronger poisoning attacks require the full knowledge of the training data

V. Ferrer, I. Vainsencher

The space of holomorphic foliations of codimension one and degree $d\geq 2$ in $\mathbb{P}^n$ ($n\geq 3$) has an irreducible component whose general element can be written as a pullback $F^*\mathcal{F}$, where $\mathcal{F}$ is a general foliation of degree $d$ in $\mathbb{P}^2$ and $F:\mathbb{P}^n\dashrightarrow \mathbb{P}^2$ is a general rational linear map

Gabriel Berzunza, Cecilia Holmgren

We consider the model of random trees introduced by Devroye (1999), the so-called random split trees. The model encompasses many important randomized algorithms and data structures. We then perform supercritical Bernoulli bond-percolation on those trees and obtain a precise weak limit theorem for the sizes of the largest clusters. We also show that the appro

Ganesh Kumar M, Soman K. P, Gopalakrishnan E. A, Vijay Krishna Menon

In this paper, we have applied the logistic growth regression model and genetic algorithm to predict the number of coronavirus infected cases that can be expected in upcoming days in India and also estimated the final size and its peak time of the coronavirus epidemic in India.

Melvyn B. Nathanson

An open problem about finite geometric progressions in syndetic sets leads to a family of diophantine equations related to the commutativity of translation and multiplication by squares.

Sudipta Ghosh, Bhabani Prasad Chattopadhyay, Ram Mohan Roy, Jayanta Mukherjee

In recent years, coronary artery disease is escalating and is likely to assume an epidemic proportion by 2030. Currently the reliable methods for detection of coronary arterial lesions are either conventional coronary angiogram (CAG) or MDCT (Multiple Detector Computed Tomography) coronary angiogram. Conventional CAG is an invasive procedure. Conventional CA

Beth Ann Griffin, Megan S. Schuler, Elizabeth A. Stuart, Stephen Patrick

State-level policy evaluations commonly employ a difference-in-differences (DID) study design; yet within this framework, statistical model specification varies notably across studies. Motivated by applied state-level opioid policy evaluations, this simulation study compares statistical performance of multiple variations of two-way fixed effect models tradit

Dmitri Kuzmin, Manuel Quezada de Luna

In this work, we modify a continuous Galerkin discretization of a scalar hyperbolic conservation law using new algebraic correction procedures. Discrete entropy conditions are used to determine the minimal amount of entropy stabilization and constrain antidiffusive corrections of a property-preserving low-order scheme. The addition of a second-order entropy

Christof Beierle, Marcus Brinkmann, Gregor Leander

All almost perfect nonlinear (APN) permutations that we know to date admit a special kind of linear self-equivalence, i.e., there exists a permutation $G$ in their CCZ-equivalence class and two linear permutations $A$ and $B$, such that $G \circ A = B \circ G$. After providing a survey on the known APN functions with a focus on the existence of self-equivale

Fabian Jaensch, Peter Jung

We consider a structured estimation problem where an observed matrix is assumed to be generated as an $s$-sparse linear combination of $N$ given $n\times n$ positive-semidefinite matrices. Recovering the unknown $N$-dimensional and $s$-sparse weights from noisy observations is an important problem in various fields of signal processing and also a relevant pr

Richard Clancy, Stephen Becker

In this paper we formulate and solve a robust least squares problem for a system of linear equations subject to quantization error in the data matrix. Ordinary least squares fails to consider uncertainty in the operator, modeling all noise in the observed signal. Total least squares accounts for uncertainty in the data matrix, but necessarily increases the c

L. McCuller, C. Whittle, D. Ganapathy, K. Komori

The first detection of gravitational waves by the Laser Interferometer Gravitational-wave Observatory (LIGO) in 2015 launched the era of gravitational wave astronomy. The quest for gravitational wave signals from objects that are fainter or farther away impels technological advances to realize ever more sensitive detectors. Since 2019, one advanced technique

Andrew Baker

Modern categories of spectra such as that of Elmendorf et al equipped with strictly symmetric monoidal smash products allows the introduction of symmetric monoids providing a new way to study highly coherent commutative ring spectra. These have categories of modules which are generalisations of the classical categories of spectra that correspond to modules o

Samuel Porritt

We study sums of Dirichlet characters over polynomials in $\mathbb{F}_q[t]$ with a prescribed number of irreducible factors. Our main results are explicit formulae for these sums in terms of zeros of Dirichlet L-functions. We also exhibit new phenomena concerning Chebyshev-type biases of such sums when the number of irreducible factors is very large.

Abel Castorena, Quentin Gendron

The main goal of this article is to compute the class of the divisor of $\overline{\mathcal{M}}_3$ obtained by taking the closure of the image of $\Omega\mathcal{M}_3(6;-2)$ by the forgetful map. This is done using Porteous formula and the theory of test curves. For this purpose, we study the locus of meromorphic differentials of the second kind, computing t

Mathieu Baillif

We gather in this note results and examples about collared or non-collared boundaries of non-metrisable manifolds. Almost everything is well known but a bit scattered in the literature, and some of it is apparently not published at all.

Patricia Cardoso, Jose Moura, Rui Marinheiro

The fast growth of Internet-connected embedded devices demands for new capabilities at the network edge. These new capabilities are local processing, efficient communications, and resource virtualization. The current work aims to address these capabilities by designing and deploying a new management proposal, which offers on-demand activation of offline Inte

Eric Barszcz

This paper introduces a polynomial blind algorithm that determines when two square matrices, $A$ and $B$, are permutation similar. The shifted and translated matrices $(A+\beta I+\gamma J)$ and $(B+\beta I+\gamma J)$ are used to color the vertices of two square, edge weighted, rook's graphs. Then the orbits are found by repeated symbolic squaring of the vert

H. M. Singer

The number of corona virus (COVID-19) infections grows worldwide. In order to create short term predictions to prepare for the extent of the global pandemic we analyze infection data from the top 25 affected countries. It is shown that all country-specific infection rates follow a power law growth behavior and the scaling exponents per country are calculated

Johannes Schemmel, Sebastian Billaudelle, Phillip Dauer, Johannes Weis

This paper presents the concepts behind the BrainScales (BSS) accelerated analog neuromorphic computing architecture. It describes the second-generation BrainScales-2 (BSS-2) version and its most recent in-silico realization, the HICANN-X Application Specific Integrated Circuit (ASIC), as it has been developed as part of the neuromorphic computing activities

Hua Sun

We consider a transmitter and $K$ receivers, each of which shares a key variable with the transmitter. Through a noiseless broadcast channel, the transmitter wishes to send a common message $W$ securely to $N$ out of the $K$ receivers while the remaining $K-N$ receivers learn no information about $W$. We are interested in the maximum message rate, i.e., the

Yujia Xue, Ian G. Davison, David A. Boas, Lei Tian

Fluorescence imaging is indispensable to biology and neuroscience. The need for large-scale imaging in freely behaving animals has further driven the development in miniaturized microscopes (miniscopes). However, conventional microscopes / miniscopes are inherently constrained by their limited space-bandwidth-product, shallow depth-of-field, and the inabilit

Veronica Hernandez, Domingo Pestana, Jose M. Rodriguez

To compute the hyperbolicity constant is an almost intractable problem, thus it is natural to try to bound it in terms of some parameters of the graph. Let $\mathcal{G}(g,c,n)$ be the set of graphs $G$ with girth $g(G)=g$, circumference $c(G)=c$, and $n$ vertices; and let $\mathcal{H}(g,c,m)$ be the set of graphs with girth $g$, circumference $c$, and $m$ ed

Ricardo Bianconi

We present here a preliminary version of a translation with comments of Georg Mohr's book "Euclides Danicus", where the first proof of Mohr-Mascheroni Theorem appeared in 1672, 125 years before Mascheroni's book.

Shantanu Gupta, Zachary C. Lipton, David Childers

Given a causal graph, the do-calculus can express treatment effects as functionals of the observational joint distribution that can be estimated empirically. Sometimes the do-calculus identifies multiple valid formulae, prompting us to compare the statistical properties of the corresponding estimators. For example, the backdoor formula applies when all confo

Yannik Löhr, Daniel Wolf, Clemens Pollerberg, Alexander Hörsting

We present the design, implementation and experimental validation of a supervisory predictive control approach for an electrical heating system featuring a phase change slurry as heat storage and transfer medium. The controller optimizes the energy flows that are used as set points for the heat generation and energy distribution components. The optimization

Indrajit Sen, Antony Valentini

This is the first of two papers which attempt to comprehensively analyse superdeterministic hidden-variables models of Bell correlations. We first give an overview of superdeterminism and discuss various criticisms of it raised in the literature. We argue that the most common criticism, the violation of `free-will', is incorrect. We take up Bell's intuitive

Zhenyu Tang, Wei Zhao, Xingzhi Xie, Zheng Zhong

Background: Chest computed tomography (CT) is recognized as an important tool for COVID-19 severity assessment. As the number of affected patients increase rapidly, manual severity assessment becomes a labor-intensive task, and may lead to delayed treatment. Purpose: Using machine learning method to realize automatic severity assessment (non-severe or severe

A. Antognini, N. J. Ayres, I. Belosevic, V. Bondar

We demonstrate efficient transverse compression of a 12.5 MeV/c muon beam stopped in a helium gas target featuring a vertical density gradient and crossed electric and magnetic fields. The muon stop distribution extending vertically over 14 mm was reduced to a 0.25 mm size (RMS) within 3.5 $\mu$s. The simulation including cross sections for low-energy $\mu^+

Johannes Dahlke, Kristina Bogner, Matthias Mueller, Thomas Berger

In recent years, many scholars praised the seemingly endless possibilities of using machine learning (ML) techniques in and for agent-based simulation models (ABM). To get a more comprehensive understanding of these possibilities, we conduct a systematic literature review (SLR) and classify the literature on the application of ML in and for ABM according to

Barbara Opozda

We begin the study of completeness of affine connections, especially those on statistical manifolds as well as on affine hypersurfaces. We collect basic facts, prove new theorems and provide examples with remarkable properties.

Thomas Goossens, Bert Geelen, Andy Lambrechts, Chris Van Hoof

Vignetting in camera lenses is generally seen as something to avoid. For spectral cameras with thin-film interference filters, however, we argue that vignetting can be an advantage. When illuminated by focused light, the bandwidth of interference filters increases with the chief-ray angle, causing position-dependent smoothing of the spectra. We show that vig

Joon Son Chung, Jaesung Huh, Seongkyu Mun, Minjae Lee

The objective of this paper is 'open-set' speaker recognition of unseen speakers, where ideal embeddings should be able to condense information into a compact utterance-level representation that has small intra-speaker and large inter-speaker distance. A popular belief in speaker recognition is that networks trained with classification objectives outperform

Karolina Sedziak-Kacprowicz, Artur Czerwinski, Piotr Kolenderski

We present a method for measuring quantum states encoded in the temporal modes of photons. The basis for the multilevel quantum states is defined by the use of modes propagating in a dispersive medium, which is a fiber in this case. The propagation and time-resolved single photon detection allow us to define a positive-operator valued measure (POVM). The POV

Sean D. Brittain, Joan R. Najita, Ruobing Dong, Zhaohuan Zhu

The high occurrence rates of spiral arms and large central clearings in protoplanetary disks, if interpreted as signposts of giant planets, indicate that gas giants form commonly as companions to young stars ($<$ few Myr) at orbital separations of 10--300\,au. However, attempts to directly image this giant planet population as companions to more mature stars

Sven Schewe

This paper discusses the hardness of finding minimal good-for-games (GFG) Buchi, Co-Buchi, and parity automata with state based acceptance. The problem appears to sit between finding small deterministic and finding small nondeterministic automata, where minimality is NP-complete and PSPACE-complete, respectively. However, recent work of Radi and Kupferman ha

Xian Gao

We make a full classification of scalar monomials built of the Riemann curvature tensor up to the quadratic order and of the covariant derivatives of the scalar field up to the third order. From the point of view of the effective field theory, the third or even higher order covariant derivatives of the scalar field are of the same order as the higher curvatu

Jose Moura, David Hutchison

Cyber-Physical Systems (CPSs) are increasingly important in critical areas of our society such as intelligent power grids, next generation mobile devices, and smart buildings. CPS operation has characteristics including considerable heterogeneity, variable dynamics, and high complexity. These systems have also scarce resources in order to satisfy their entir

A. Pitanti, T. Makkonen, M. F. Colombano, S. Zanotto

A strong trend for quantum based technologies and applications follows the avenue of combining different platforms to exploit their complementary technological and functional advantages. Micro and nano-mechanical devices are particularly suitable for hybrid integration due to the easiness of fabrication at multi-scales and their pervasive coupling with elect

S. H. Shekh, V. R. Chirde

In this paper, we have investigated some features of anisotropic accelerating Bianchi type-I cosmological model in the presence of two non-interacting fluids, i.e. one usual string and other dark energy fluid towards the gravitational field equations for the linear form of $f(T)$ gravity, where \textit{T }be the torsion. To achieve a physically realistic sol

Jianyuan Deng, Zhibo Yang, Yao Li, Dimitris Samaras

Naloxone, an opioid antagonist, has been widely used to save lives from opioid overdose, a leading cause for death in the opioid epidemic. However, naloxone has short brain retention ability, which limits its therapeutic efficacy. Developing better opioid antagonists is critical in combating the opioid epidemic.Instead of exhaustively searching in a huge che

Y. Ouyang, P. F. Chen, S. Q. Fan, B. Li

Solar filaments are dark structures on the solar disk, with an elongated spine and several barbs extending out from the spine. When appearing above the solar limb, a filament is called a prominence, with several feet extending down to the solar surface. It was generally thought that filament barbs are simply the prominence feet veering away from the spine an

Benjamin Isac Fargion, Daniele Fargion, Pier Giorgio De Sanctis Lucentini, Emanuele Habib

The CoVid-19 is spreading pandemically all over the world. A rapid defeat of the pandemic requires carrying out on the population a mass screening, able to separate positive from negative cases. Such a cleaning will free a flow of productive population. The current rate and cost of testing, performed with the common PCR (polymerase chain reaction) method and

Asmaa Abbas, Mohammed M. Abdelsamea, Mohamed Medhat Gaber

Chest X-ray is the first imaging technique that plays an important role in the diagnosis of COVID-19 disease. Due to the high availability of large-scale annotated image datasets, great success has been achieved using convolutional neural networks (CNNs) for image recognition and classification. However, due to the limited availability of annotated medical i

Aris Filos-Ratsikas, Alexandros Hollender, Katerina Sotiraki, Manolis Zampetakis

The classes PPA-$p$ have attracted attention lately, because they are the main candidates for capturing the complexity of Necklace Splitting with $p$ thieves, for prime $p$. However, these classes were not known to have complete problems of a topological nature, which impedes any progress towards settling the complexity of the Necklace Splitting problem. On

Francesco Mainardi

In this tutorial survey we recall the basic properties of the special function of the Mittag-Leffler and Wright type that are known to be relevant in processes dealt with the fractional calculus. We outline the major applications of these functions. For the Mittag-Leffler functions we analyze the Abel integral equation of the second kind and the fractional r

Juening Jin, Yahong Rosa Zheng, Wen Chen, Chengshan Xiao

This paper investigates the hybrid precoding design for millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems with finite-alphabet inputs. The precoding problem is a joint optimization of analog and digital precoders, and we treat it as a matrix factorization problem with power and constant modulus constraints. Our work presents three main c