March 2020 arXiv papers — page 93

Mustafa Polat, Hâldun Sevinçli, A. D. Güçlü

In this paper, we perform a systematic study on the electronic, magnetic, and transport properties of the hexagonal graphene quantum dots (GQDs) with armchair edges in the presence of a charged impurity using two different configurations: (1) a central Coulomb potential and (2) a positively charged carbon vacancy. The tight binding (TB) and the half-filled e

Hyeongmin Lee, Taeoh Kim, Hanbin Son, Sangwook Baek

In Convolutional Neural Network (CNN) based image processing, most of the studies propose networks that are optimized for a single-level (or a single-objective); thus, they underperform on other levels and must be retrained for delivery of optimal performance. Using multiple models to cover multiple levels involves very high computational costs. To solve the

Lijun Bo, Huafu Liao

This paper introduces a general class of Replicator-Mutator equations on a multi-dimensional fitness space. We establish a novel probabilistic representation of weak solutions of the equation by using the theory of Fockker-Planck-Kolmogorov (FPK) equations and a martingale extraction approach. The examples with closed-form probabilistic solutions for differe

Chong Wang, Shiquan Ren, Jian Liu

In this paper, based on the embedded homology groups of hypergraphs defined in \cite{h1}, we define the product of hypergraphs and prove the corresponding Künneth formula of hypergraphs which can be generalized to the Künneth formula for the embedded homology of graded subsets of chain complexes with coefficients in a principal ideal domain.

Shmuel Onn

We consider the problem of finding a subgraph of a given graph which maximizes a given function evaluated at its degree sequence. While the problem is intractable already for convex functions, we show that it can be solved in polynomial time for convex multi-criteria objectives. We next consider the problem with separable objectives, which is NP-hard already

Semin Xavier, Jose Mathew, S. Shankaranarayanan

We obtain an infinite number of exact static, Ricci-flat spherically symmetric vacuum solutions for a class of f(R) theories of gravity. We analytically derive two exact vacuum black-hole solutions for the same class of f(R) theories. The two black-hole solutions have the event-horizon at the same point; however, their asymptotic features are different. Our

C. Corda, F. Feleppa, F. Tamburini

Following Rosen's quantization rules, two of the Authors (CC and FF) recently described the Schwarzschild black hole (BH) formed after the gravitational collapse of a pressureless "star of dust" in terms of a "gravitational hydrogen atom". Here we generalize this approach to the gravitational collapse of a charged object, namely, to the g

Yangyao Chen, H. J. Mo, Cheng Li, Huiyuan Wang

We use a large $N$-body simulation to study the relation of the structural properties of dark matter halos to their assembly history and environment. The complexity of individual halo assembly histories can be well described by a small number of principal components (PCs), which, compared to formation times, provide a more complete description of halo assemb

Bo Jiang, Philippe Nain, Don Towsley

Consider a setting where Willie generates a Poisson stream of jobs and routes them to a single server that follows the first-in first-out discipline. Suppose there is an adversary Alice, who desires to receive service without being detected. We ask the question: what is the number of jobs that she can receive covertly, i.e. without being detected by Willie?

Bülent Karasözen

The human brain contains approximately $10^9$ neurons, each with approximately $10^3$ connections, synapses, with other neurons. Most sensory, cognitive and motor functions of our brains depend on the interaction of a large population of neurons. In recent years, many technologies are developed for recording large numbers of neurons either sequentially or si

Sungha Choi, Joanne T. Kim, Jaegul Choo

This paper exploits the intrinsic features of urban-scene images and proposes a general add-on module, called height-driven attention networks (HANet), for improving semantic segmentation for urban-scene images. It emphasizes informative features or classes selectively according to the vertical position of a pixel. The pixel-wise class distributions are sign

Shoya Ogawa, Takuma Matsumoto

We investigate the contribution of the $2^{+}_{2}$ resonance in $^6$He to observables via analysis of the $^6$He($p,p'$) reaction by using the continuum-discretized coupled channels method combined with the complex-scaling method. In this study, we obtain the $2^{+}_{2}$ state with the resonant energy 2.25 MeV and the decay width 3.75 MeV and analyse con

Biao Wang

In this note, we mainly show the analogue of one of Alladi's formulas over $\mathbb{Q}$ with respect to the Dirichlet convolutions involving the Möbius function $μ(n)$, which is related to the natural densities of sets of primes by recent work of Dawsey, Sweeting and Woo, and Kural et al. This would give us several new analogues. In particular, we get th

Krishan Rana, Vibhavari Dasagi, Ben Talbot, Michael Milford

Learning-based approaches often outperform hand-coded algorithmic solutions for many problems in robotics. However, learning long-horizon tasks on real robot hardware can be intractable, and transferring a learned policy from simulation to reality is still extremely challenging. We present a novel approach to model-free reinforcement learning that can levera

John F. Raffensperger

Existing emissions trading system (ETS) designs inhibit emissions but do not constrain warming to any fxed level, preventing certainty of the global path of warming. Instead, they have the indirect objective of reducing emissions. They provide poor future price information. And they have high transaction costs for implementation, requiring treaties and laws.

Parth Thakkar, Senthilnathan Natarajan

Permissioned blockchains are becoming popular as data management systems in the enterprise setting. Compared to traditional distributed databases, blockchain platforms provide increased security guarantees but significantly lower performance. Further, these platforms are quite expensive to run for the low throughput they provide. The following are two ways t

Sian-Yao Huang, Wei-Ta Chu

We achieve very efficient deep learning model deployment that designs neural network architectures to fit different hardware constraints. Given a constraint, most neural architecture search (NAS) methods either sample a set of sub-networks according to a pre-trained accuracy predictor, or adopt the evolutionary algorithm to evolve specialized networks from t

Xiaoyu Zhang, Senthil Chandrasegaran, Kwan-Liu Ma

Current text visualization techniques typically provide overviews of document content and structure using intrinsic properties such as term frequencies, co-occurrences, and sentence structures. Such visualizations lack conceptual overviews incorporating domain-relevant knowledge, needed when examining documents such as research articles or technical reports.

Dimitrios Boursinos, Xenofon Koutsoukos

Cyber-physical systems (CPS) can benefit by the use of learning enabled components (LECs) such as deep neural networks (DNNs) for perception and decision making tasks. However, DNNs are typically non-transparent making reasoning about their predictions very difficult, and hence their application to safety-critical systems is very challenging. LECs could be i

Akira Masuoka, Taiki Shibata, Yuta Shimada

We generalize to the super context, the known fact that if an affine algebraic group $G$ over a commutative ring $k$ acts freely (in an appropriate sense) on an affine scheme $X$ over $k$, then the dur sheaf $X\tilde{\tilde{/}}G$ of $G$-orbits is an affine scheme in the following two cases: (I) $G$ is finite; (II) $k$ is a field, and $G$ is linearly reductiv

Katsuhiro Nakamura, Jasur Matrasulov, Yuki Izumida

The fast-forward (FF) scheme proposed by Masuda and Nakamura (\textit{Proc. R. Soc. A} \textbf{466}, 1135 (2010)) in the context of conservative quantum dynamics can reproduce a quasi-static dynamics in an arbitrarily short time. We apply the FF scheme to the classical stochastic Carnot-like heat engine which is driven by a Brownian particle coupled with a t

Shao-Kai Jian, Edwin Barnes, Sankar Das Sarma

The existence or not of Landau poles is one of the oldest open questions in non-asymptotic quantum field theories. We investigate the Landau pole issue in two condensed matter systems whose long-wavelength physics is described by appropriate quantum field theories: the critical quantum magnet and Dirac fermions in graphene with long-range Coulomb interaction

Teruki Hayakawa, Masateru Tsunoda, Koji Toda, Keitaro Nakasai

Various software fault prediction models and techniques for building algorithms have been proposed. Many studies have compared and evaluated them to identify the most effective ones. However, in most cases, such models and techniques do not have the best performance on every dataset. This is because there is diversity of software development datasets, and th

Nam N. Tran, Hemanshu R. Pota, Quang N. Tran, Jiankun Hu

The advent of smart power grid which plays a vital role in the upcoming smart city era is accompanied with the implementation of a monitoring tool, called state estimation. For the case of the unbalanced residential distribution grid, the state estimating operation which is conducted at a regional scale is considered as an application of the edge computing-b

Chao Fang, Amin Barzegar, Helmut G. Katzgraber

Known for their ability to identify hidden patterns in data, artificial neural networks are among the most powerful machine learning tools. Most notably, neural networks have played a central role in identifying states of matter and phase transitions across condensed matter physics. To date, most studies have focused on systems where different phases of matt

A. I. Dyachenko, S. A. Dyachenko, P. M. Lushnikov, V. E. Zakharov

A potential motion of ideal incompressible fluid with a free surface and infinite depth is considered in two-dimensional geometry. A time-dependent conformal mapping of the lower complex half-plane of the auxiliary complex variable $w$ into the area filled with fluid is performed with the real line of $w$ mapped into the free fluid's surface. The fluid dynam

Shinji Yamashita

We perform the Hamiltonian analysis of unimodular gravity in terms of the connection representation. The unimodular condition is imposed straightforwardly into the action with a Lagrange multiplier. After classifying constraints into first class and second class, the canonical quantization is carried out. We consider the difference of the corresponding physi

Gunnar A. Sigurdsson, Jean-Baptiste Alayrac, Aida Nematzadeh, Lucas Smaira

There are thousands of actively spoken languages on Earth, but a single visual world. Grounding in this visual world has the potential to bridge the gap between all these languages. Our goal is to use visual grounding to improve unsupervised word mapping between languages. The key idea is to establish a common visual representation between two languages by l

Sucheol Kim, Junil Choi, Jiho Song

This paper proposes hybrid beamforming designs for millimeter-wave (mmWave) multiple-input multiple-output (MIMO) backhaul systems equipped with uniform planar arrays (UPAs) of dual-polarization antennas at both the transmit and receive base stations. The proposed beamforming designs are to near-optimally solve optimization problems taking the dual-polarizat

Rui-Hua Xu, Xu Wang, J. H. Eberly

We extend our earlier "virtual detector" method [X. Wang, J. Tian, and J. H. Eberly, Phys. Rev. Lett. 110, 243001 (2013)], a hybrid quantum mechanical and classical trajectory method, to include phases in the classical trajectories. Effects of quantum interferences, lost in the earlier method, are restored. The obtained photoelectron momentum distributions a

Pierre A. Pantaleon, Tommaso Cea, Rory Brown, Niels R. Walet

The occurrence of superconducting and insulating phases is well-established in twisted graphene bilayers, and they have also been reported in other arrangements of graphene layers. We investigate three such arrangements: untwisted AB bilayer graphene on an hBN substrate, two graphene bilayers twisted with respect to each other, and a single ABC stacked graph

Brent Giggins, Georg A. Gottwald

The breeding method is a computationally cheap procedure to generate initial conditions for ensemble forecasting which project onto relevant synoptic growing modes. Ensembles of bred vectors, however, often lack diversity and align with the leading Lyapunov vector, which severely impacts their statistical reliability. In previous work we developed stochastic

Pierre-Emmanuel Jabin, Hsin-Yi Lin, Eitan Tadmor

We introduce a commutator method with multipliers to prove averaging lemmas, the regularizing effect for the velocity average of solutions for kinetic equations. This method requires only elementary techniques in Fourier analysis and shows a new range of assumptions that are sufficient for the velocity average to be in $L^2([0,T],H^{1/2}_x).$ This result not

Wei Chen

The low energy sector of 2D and 3D topological insulators (TIs) exhibits propagating edge states, which has speculated the existence of equilibrium edge currents or edge spin currents. We demonstrate that if the low energy sector of TIs is regularized in a straightforward manner into a square or cubic lattice, then the current from the edge states is in fact

Yue Zhao, Xiyang Hu, Cheng Cheng, Cong Wang

Outlier detection (OD) is a key machine learning (ML) task for identifying abnormal objects from general samples with numerous high-stake applications including fraud detection and intrusion detection. Due to the lack of ground truth labels, practitioners often have to build a large number of unsupervised, heterogeneous models (i.e., different algorithms wit

Roberto Buizza

The objective of this work is to predict the spread of COVID-19 starting from observed data, using a forecast method inspired by probabilistic weather prediction systems operational today. Results show that this method works well for China: on day 25 we could have predicted well the outcome for the next 35 days. The same method has been applied to Italy and

Nicholas Dwork, Jeremy W. Gordon, Shuyu Tang, Daniel O'Connor

Magnetic resonance imaging with hyperpolarized contrast agents can provide unprecedented \textit{in-vivo} measurements of metabolism, but yields images that are lower resolution than that achieved with proton anatomical imaging. In order to spatially localize the metabolic activity, the metabolic image must be interpolated to the size of the proton image. Th

Kathryn Volk, Renu Malhotra

We investigated the dynamical stability of high-multiplicity Kepler and K2 planetary systems. Our numerical simulations find instabilities in $\sim20\%$ of the cases on a wide range of timescales (up to $5\times10^9$ orbits) and over an unexpectedly wide range of initial dynamical spacings. To identify the triggers of long-term instability in multi-planet sy

Bartosz Piotrowski, Josef Urban

In this work, we develop a new learning-based method for selecting facts (premises) when proving new goals over large formal libraries. Unlike previous methods that choose sets of facts independently of each other by their rank, the new method uses the notion of \emph{state} that is updated each time a choice of a fact is made. Our stateful architecture is b

F. Lisi, G. Losquadro, A. Tortorelli, A. Ornatelli

The 5G-ALLSTAR project is aimed at integrating Terrestrial and Satellite Networks for satisfying the highly challenging and demanding requirements of the 5G use cases. The integration of the two networks is a key feature to assure the service continuity in challenging communication situations (e.g., emergency cases, marine, railway, etc.) by avoiding service

C. J. Pethick, Zhaowen Zhang, D. N. Kobyakov

We consider the elastic constants of phases with nonspherical nuclei, so-called pasta phases, predicted to occur in the inner crust of a neutron star. First, we treat perfectly ordered phases and give numerical estimates for lasagna and spaghetti when the pasta elements are spatially uniform: the results are in order-of-magnitude agreement with the numerical

Steph-Yves Louis, Yong Zhao, Alireza Nasiri, Xiran Wong

Machine learning (ML) methods have gained increasing popularity in exploring and developing new materials. More specifically, graph neural network (GNN) has been applied in predicting material properties. In this work, we develop a novel model, GATGNN, for predicting inorganic material properties based on graph neural networks composed of multiple graph-atte

Anthony Strock, Nicolas Rougier, Xavier Hinaut

We introduce a recurrent neural network model of working memory combining short-term and long-term components. e short-term component is modelled using a gated reservoir model that is trained to hold a value from an input stream when a gate signal is on. e long-term component is modelled using conceptors in order to store inner temporal patterns (that corres

Changyu Miao, Zhen Cao, Yik-Cheung Tam

Deep Semantic Matching is a crucial component in various natural language processing applications such as question and answering (QA), where an input query is compared to each candidate question in a QA corpus in terms of relevance. Measuring similarities between a query-question pair in an open domain scenario can be challenging due to diverse word tokens i

Haoran Zhang, Amy X. Lu, Mohamed Abdalla, Matthew McDermott

In this work, we examine the extent to which embeddings may encode marginalized populations differently, and how this may lead to a perpetuation of biases and worsened performance on clinical tasks. We pretrain deep embedding models (BERT) on medical notes from the MIMIC-III hospital dataset, and quantify potential disparities using two approaches. First, we

Sehun Chun, Chris Cantwell

As another critical implementation of moving frames for partial differential equations, this paper proposes a novel numerical scheme by aligning one of three orthogonal unit vectors at each grid point along the direction of a wave propagation to construct an organized set of frames, called a connection. This connection characterizes the geometry of wave prop

D. S. Agafontsev, V. E. Zakharov

We study numerically the integrable turbulence in the framework of the focusing one-dimensional nonlinear Schrodinger equation using a new method -- the "growing of turbulence". We add to the equation a weak controlled pumping term and start adiabatic evolution of turbulence from statistically homogeneous Gaussian noise. After reaching a certain leve

Heejong Park, Arvind Easwaran, Sidharta Andalam

Digital twin is a virtual replica of a real-world object that lives simultaneously with its physical counterpart. Since its first introduction in 2003 by Grieves, digital twin has gained momentum in a wide range of applications such as industrial manufacturing, automotive and artificial intelligence. However, many digital-twin-related approaches, found in in

Sohrab Hossain, Ahmed Abtahee, Imran Kashem, Mohammed Moshiul Hoque

A crime is a punishable offence that is harmful for an individual and his society. It is obvious to comprehend the patterns of criminal activity to prevent them. Research can help society to prevent and solve crime activates. Study shows that only 10 percent offenders commits 50 percent of the total offences. The enforcement team can respond faster if they h

Dragan Hajdukovic

Quantum vacuum and matter immersed in it interact through electromagnetic, strong and weak interactions. However, we have zero knowledge of the gravitational properties of the quantum vacuum. As an illustration of possible fundamental gravitational impact of the quantum vacuum, we study the gravitational field of an immersed point-like body. It is done under

Siwei Lyu

High quality fake videos and audios generated by AI-algorithms (the deep fakes) have started to challenge the status of videos and audios as definitive evidence of events. In this paper, we highlight a few of these challenges and discuss the research opportunities in this direction.

R. Prasad, Avinash Kr. Yadav, Anil Kumar Yadav

In this paper, we investigate a transitioning model of Bianchi type V universe in Brans-Dicke theory of gravitation. The derived model not only validates Mach's principle but also describes the present acceleration of the universe. In this paper, our aim is to constrain an exact Bianchi type V universe in Brans - Dicke gravity. For this sake, firstly we

David Ojika, Bhavesh Patel, G. Anthony Reina, Trent Boyer

Using medical imaging as case-study, we demonstrate how Intel-optimized TensorFlow on an x86-based server equipped with 2nd Generation Intel Xeon Scalable Processors with large system memory allows for the training of memory-intensive AI/deep-learning models in a scale-up server configuration. We believe our work represents the first training of a deep neura

Xiaozhe Gu, Arvind Easwaran

Many existing studies on mixed-criticality (MC) scheduling assume that low-criticality budgets for high-criticality applications are known apriori. These budgets are primarily used as guidance to determine when the scheduler should switch the system mode from low to high. Based on this key observation, in this paper we propose a dynamic MC scheduling model u

Stefan Lenz, Harald Binder

The best way to calculate statistics from medical data is to use the data of individual patients. In some settings, this data is difficult to obtain due to privacy restrictions. In Germany, for example, it is not possible to pool routine data from different hospitals for research purposes without the consent of the patients. The DataSHIELD software provides

Soyeun Jung, Zhao Yang, Kevin Zumbrun

For strong detonation waves of the inviscid Majda model, spectral stability was established by Jung and Yao for waves with step-type ignition functions, by a proof based largely on explicit knowledge of wave profiles. In the present work, we extend their stability results to strong detonation waves with more general ignition functions where explicit profiles

Fortunato Tito Arecchi

Physics deals with Newtonian particles described by position q and momentum p. The precision of the simultaneous measurement of q and p is limited by the uncertainty relation ruled by Planck's constant. From the uncertainty relation all quantum consequences emerge, including entanglement. On the other hand, Homoclinic Chaos (HC) , that consists of sequen

Saul Johnson

If we wish to compromise some password-protected system as an attacker (i.e. a member of the red team), we have a large number of popular and actively-maintained tools to choose from in helping us to realise our goal. Password hash cracking hardware and software, online guessing tools, exploit frameworks, and a wealth of tools for helping us to perform recon

Bingqing Yu, Jacopo Tagliabue, Ciro Greco, Federico Bianchi

We address the problem of personalizing query completion in a digital commerce setting, in which the bounce rate is typically high and recurring users are rare. We focus on in-session personalization and improve a standard noisy channel model by injecting dense vectors computed from product images at query time. We argue that image-based personalization disp

Proma Mondal, Aniruddha Chakraborty

We propose a new method for finding the exact analytical solution in Laplace domain for the problem where the probability density of a random walker in a piece-wise linear potential in presence of a rectangular sink of arbitrary width and height. The motion of the random walker is modelled by using Smoluchowski equation. For our model we have derived exact a

Edson D. Leonel, Celia Mayumi Kuwana, Makoto Yoshida, Juliano Antonio de Oliveira

The scaling invariance for chaotic orbits near a transition from unlimited to limited diffusion in a dissipative standard mapping is explained via the analytical solution of the diffusion equation. It gives the probability of observing a particle with a specific action at a given time. We show the diffusion coefficient varies slowly with the time and is resp

Xiaochen Fan, Chaocan Xiang, Chao Chen, Panlong Yang

With the rapid development of smart cities, smart buildings are generating a massive amount of building sensing data by the equipped sensors. Indeed, building sensing data provides a promising way to enrich a series of data-demanding and cost-expensive urban mobile applications. In this paper, we study how to reuse building sensing data to predict traffic vo

Alexander Steinicke, Markus Penz, Bine Penz

The Secret Santa ritual, where in a group of people every member presents a gift to a randomly assigned partner, poses a combinatorial problem when considering the probabilities involved in the formation of pairs, where two persons exchange gifts mutually. We give different possible derivations for such probabilities by counting fixed-point-free permutations

Henri Kauhanen

The Fundamental Theorem of Language Change (Yang, 2000) implies the impossibility of stable variation in the Variational Learning framework, but only in the special case where two, and not more, grammatical variants compete. Introducing the notion of an advantage matrix, I generalize Variational Learning to situations where the learner receives input generat

Riccardo Fazio, Alessandra Jannelli

This paper deals with a non-standard finite difference scheme defined on a quasi-uniform mesh for approximate solutions of the MHD boundary layer flow of an incompressible fluid past a flat plate for a wide range of the magnetic parameter. The obtained numerical results are compared with those available in the literature. We show how to improve the obtained

Tsai-Jung Chen, Ying-Ji Hong

Automotive engineers want to reduce the noise generated by the vibrations of rubber wiper on the windshield of an automobile. To understand the vibrations of wiper noise, certain spring-mass models were presented by some specialists, over the past few years, to simulate the vibrations of rubber wiper on windshield. In this article, we will give precise mathe

Hisashi Hayakawa, Yusuke Ebihara

This section shows an overview of a recent development of the studies on great space weather events in history. Its discussion starts from the Carrington event and compare its intensity with the extreme storms within the coverage of the regular magnetic measurements. Extending its analyses back beyond their onset, this section shows several case studies of e

Davoud Mougouei, David M W Powers

Software requirements selection aims to find an optimal subset of the requirements with the highest value while respecting the project constraints. But the value of a requirement may depend on the presence or absence of other requirements in the optimal subset. Such Value Dependencies, however, are imprecise and hard to capture. In this paper, we propose a m

Ning An, Liuqi Jin, Huitong Ding, Jiaoyun Yang

While a large body of research has formally identified apolipoprotein E (APOE) as a major genetic risk marker for Alzheimer disease, accumulating evidence supports the notion that other risk markers may exist. The traditional Alzheimer-specific signature analysis methods, however, have not been able to make full use of rich protein expression data, especiall

David A. Green, Patrick Elwood

Here we report observations of a recent giant radio flare from Cygnus X-3 in 2020 February, made with the Arcminute MicroKelvin Imager.

Suat Gumussoy, Hitay Ozbay

In this note we consider a class of linear time invariant systems with infinitely many unstable modes. By using the parameterization of all stabilizing controllers and a data transformation, we show that H-infinity controllers for such systems can be computed using the techniques developed earlier for infinite dimensional plants with finitely many unstable m

Denise Cocchiarella, Stefano Scali, Salvatore Ribisi, Bianca Nardi

The achievement of quantum supremacy boosted the need for a robust medium of quantum information. In this task, higher-dimensional qudits show remarkable noise tolerance and enhanced security for quantum key distribution applications. However, to exploit the advantages of such states, we need a thorough characterisation of their entanglement. Here, we propos

Spyridon Papastergiou, Haralambos Mouratidis, Eleni-Maria Kalogeraki

This paper aims to enhance the security and resilience of Critical Information Infrastructures (CIIs) by providing a dynamic collaborative, warning and response system (CyberSANE system) supporting and guiding security officers and operators (e.g. Incident Response professionals) to recognize, identify, dynamically analyse, forecast, treat and respond to the

Yiqing Xu, Yi Lin, Alexander Nielsen, Ian Hendry

With demonstrated applications ranging from metrology to telecommunications, soliton microresonator frequency combs have emerged over the past decade as a remarkable new technology. However, standard implementations only allow for the generation of combs whose repetition rate is tied close to the fundamental resonator free-spectral range (FSR), offering litt

Abdelatif Elkachkouri, Allal Ghanmi, Ali Hafoud

We investigate the quaternionic extension of the fractional Fourier transform on the real half-line leading to fractional Hankel transform. This will be handled à la Bargmann by means of hyperholomorphic second Bargmann transform for the slice Bergman space of second kind. Basic properties are derived including inversion formula and Plancherel identity.

Michael Kellman, Kevin Zhang, Jon Tamir, Emrah Bostan

Critical aspects of computational imaging systems, such as experimental design and image priors, can be optimized through deep networks formed by the unrolled iterations of classical model-based reconstructions (termed physics-based networks). However, for real-world large-scale inverse problems, computing gradients via backpropagation is infeasible due to m

Eric Schneider, Marcus Poulton, Archie Drake, Leanne Smith

Multi-Robot Task Allocation (MRTA) is the problem of distributing a set of tasks to a team of robots with the objective of optimising some criteria, such as minimising the amount of time or energy spent to complete all the tasks or maximising the efficiency of the team's joint activity. The exploration of MRTA methods is typically restricted to laborator

Mehmet Mert Şahin, Hüseyin Arslan

This paper introduces a novel non-orthogonal multiple access (NOMA) concept named waveform-domain NOMA, which proposes the coexistence of different waveforms in the same resource element (RE). Regarding the demands of each user equipments (UEs), appropriate waveforms are assigned intelligently and decoded at the receiver side properly. Since the performance

Gia Dvali

We establish that unitarity of scattering amplitudes imposes universal entropy bounds. The maximal entropy of a self-sustained quantum field object of radius R is equal to its surface area and at the same time to the inverse running coupling evaluated at the scale R. The saturation of these entropy bounds is in one-to-one correspondence with the non-perturba

Yuta Sakai, Vincent Y. F. Tan

This study considers the unconditional smooth Rényi entropy, the smooth conditional Rényi entropy proposed by Kuzuoka [\emph{IEEE Trans.\ Inf.\ Theory}, vol.~66, no.~3, pp.~1674--1690, 2020], and a new quantity which we term the conditional smooth Rényi entropy. In particular, we examine asymptotic expansions of these entropies when the underlying source wit

Johannes Bund, Matthias Függer, Christoph Lenzen, Moti Medina

Consider an arbitrary network of communicating modules on a chip, each requiring a local signal telling it when to execute a computational step. There are three common solutions to generating such a local clock signal: (i) by deriving it from a single, central clock source, (ii) by local, free-running oscillators, or (iii) by handshaking between neighboring

Oytun Ulutan, A S M Iftekhar, B. S. Manjunath

Comprehensive visual understanding requires detection frameworks that can effectively learn and utilize object interactions while analyzing objects individually. This is the main objective in Human-Object Interaction (HOI) detection task. In particular, relative spatial reasoning and structural connections between objects are essential cues for analyzing int

Mahroo Shiranzaei, Jonas Fransson, Annica M. Black-Schaffer, Fariborz Parhizgar

We theoretically investigate the exchange interaction between magnetic impurities in ultrathin Bi$_2$Se$_3$ topological insulator films by taking into account the low-energy states produced by the impurities. We find that the locally induced impurity resonances strongly influence the exchange interaction between magnetic moments. In particular, we find a non

David F. Anderson, Ayman Badawi

In this paper, we introduce the concept of n-semiprimary ideals, n-powerful ideals, and n-powerful semiprimary ideals of commutative rings. We study these concepts and relate them to several generalizations of pseudo-valuation domains.

Simon Niklaus, Feng Liu

Differentiable image sampling in the form of backward warping has seen broad adoption in tasks like depth estimation and optical flow prediction. In contrast, how to perform forward warping has seen less attention, partly due to additional challenges such as resolving the conflict of mapping multiple pixels to the same target location in a differentiable way

Matthias Laschke, Alarith Uhde, Marc Hassenzahl

Work is a rich source of meaning. However, beyond organizational changes, most approaches in the research field of Meaningful Work neglected the power of work-related technology to increase meaning. Using two cases as examples, this paper proposes a wellbeing-driven approach to the design of work-related technology. Despite the positive results of our cases,

Holger Klapperich, Alarith Uhde, Marc Hassenzahl

Nowadays, automation not only dominates industry but becomes more and more a part of our private, everyday lives. Following the notion of increased convenience and more time for the "important things in life", automation relieves us from many daily household chores - robots vacuum floors and automated coffeemakers produce supposedly barista-quality c

R. N. P. Maia, C. M. Silva da Conceição

An analytical method to compute the LDOS energy spectrum and stationary states for finite size doped monatomic chains modelled by an effective one-dimensional tight-binding hamiltonian is presented. It is based on the formal solution of linear second order recurrence relations. We also study the LDOS energy spectrum of some doped monatomic chains applying a

David Ehrenreich, Christophe Lovis, Romain Allart, María Rosa Zapatero Osorio

Ultra-hot giant exoplanets receive thousands of times Earth's insolation. Their high-temperature atmospheres (>2,000 K) are ideal laboratories for studying extreme planetary climates and chemistry. Daysides are predicted to be cloud-free, dominated by atomic species and substantially hotter than nightsides. Atoms are expected to recombine into molecules

Tomáš Musil

Artificial neural networks are a state-of-the-art solution for many problems in natural language processing. What can we learn about language and meaning from the way artificial neural networks represent it? Word representations obtained from the Skip-gram variant of the word2vec model exhibit interesting semantic properties. This is usually explained by ref

I Gede Arjana, Imara Lima Fernandes, Jonathan Chico, Samir Lounis

Magnetic skyrmions are prime candidates as information carriers for spintronic devices due to their topological nature and nanometric size. However, unavoidable inhomogeneities inherent to any material leads to pinning or repulsion of skyrmions that, in analogy to biology concepts, define the phenotype of the skyrmion-defect interaction, generating complexit

Carlos Guillermo Bornancini, Diego García Lambas

We analyse different photometric and spectroscopic properties of active galactic nuclei (AGNs) and quasars (QSOs) selected by their mid-IR power-law and X-ray emission from the COSMOS survey. We use a set of star-forming galaxies as a control sample to compare with the results. We have considered samples of obscured (HR > -0.2) and unobscured (HR < -0.2) sou

Tong Bai, Cunhua Pan, Hong Ren, Yansha Deng

Wireless powered mobile edge computing (WP-MEC) has been recognized as a promising technique to provide both enhanced computational capability and sustainable energy supply to massive low-power wireless devices. However, its energy consumption becomes substantial, when the transmission link used for wireless energy transfer (WET) and for computation offloadi

Jesús López-Fidalgo, Mariano Amo-Salas

In this paper, the tools provided by the theory of Optimal Experimental Design are applied to a nonlinear calibration model. This is motivated by the need of estimating radiation doses using radiochromic films for radiotherapy purposes. The calibration model is in this case nonlinear and the explanatory variable cannot be worked out explicitly from the model

J. S. Ben-Benjamin, L. Cohen

We present a new approach for obtaining quantum quasi-probability distributions, $P(α,β)$, for two arbitrary operators, $\mathbf{a}$ and $\mathbf{b}$, where $α$ and $β$ are the corresponding c-variables. We show that the quantum expectation value of an arbitrary operator can always be expressed as a phase space integral over $α$ and $β$, where the integrand

Chengyao Li, Jason Ku, Steven L. Waslander

Accurate and reliable 3D object detection is vital to safe autonomous driving. Despite recent developments, the performance gap between stereo-based methods and LiDAR-based methods is still considerable. Accurate depth estimation is crucial to the performance of stereo-based 3D object detection methods, particularly for those pixels associated with objects i

J. S. Ben-Benjamin

In 1932, Fermi presented a two-atom model for determining whether quantum mechanics is consistent with causality, and concluded that indeed it is. In the late 1960&#39;s, Shirokov and others found that Fermi&#39;s approximations may not have been sound, and when corrected, Fermi&#39;s model shows non-causal behavior. We show that if instead of time-dependent

Manon Costa, Christèle Etchegaray, Sepideh Mirrahimi

We study a parabolic Lotka-Volterra type equation that describes the evolution of a population structured by a phenotypic trait, under the effects of mutations and competition for resources modelled by a nonlocal feedback. The limit of small mutations is characterized by a Hamilton-Jacobi equation with constraint that describes the concentration of the popul

Waseem Abbas, Mudassir Shabbir, Hassan Jaleel, Xenofon Koutsoukos

In this paper, we consider a network of agents with Laplacian dynamics, and study the problem of improving network robustness by adding a maximum number of edges within the network while preserving a lower bound on its strong structural controllability (SSC) at the same time. Edge augmentation increases network&#39;s robustness to noise and structural change

Thomas Gerard, Christopher Parsonson, Zacharaya Shabka, Polina Bayvel

We propose a time-multiplexed DS-DBR/SOA-gated system to deliver low-power fast tuning across S-/C-/L-bands. Sub-ns switching is demonstrated, supporting 122$\times$50 GHz channels over 6.05 THz using AI techniques.