March 2020 arXiv papers — page 131

Raed M. Shaiia

The different interpretations of quantum mechanics yield the same experimental results, which may give the impression that the question of what interpretation is the true one, is a philosophical question, not a scientific one. But in this paper, we will see that we can actually prove one interpretation, in particular, a version of the ensemble interpretation

Pedro Casas

The popularity of Artificial Intelligence (AI) -- and of Machine Learning (ML) as an approach to AI, has dramatically increased in the last few years, due to its outstanding performance in various domains, notably in image, audio, and natural language processing. In these domains, AI success-stories are boosting the applied field. When it comes to AI/ML for

Sebastian White, Arjan Heering

In this paper we illustrate techniques for digitized waveform signal processing of fast timing detectors. In the example discussed here, timing analysis of SiPM signals in the presence of high Dark Count Rates, a large data set of digitized waveforms is used to develop an optimal strategy relevant to the electronics front end design.

Ramy Amer, M. Majid Butt, Nicola Marchetti

Caching at mobile devices and leveraging device-to-device (D2D) communication are two promising approaches to support massive content delivery over wireless networks. Analysis of such D2D caching networks based on a physical interference model is usually carried out by assuming uniformly distributed devices. However, this approach does not capture the notion

Hayam Yassin, Eman R. Abo Elyazeed, Abdel Nasser Tawfik

The transverse momentum spectra of the well-identified produced particles, $π^+$, $π^-$, $K^+$, $K^-$, $p$, $\bar{p}$, $K_s^0$, $Λ$, $\barΛ$, $Ξ^-$, and $Ξ^+$ are analyzed in a statistical approach. From the partition function of grand-canonical ensemble, we propose a generic expression for the dependence of the generic chemical potential $μ$ on the rapidity

Oscar Fontanelli, Ricardo Mansilla

In this work we introduce a model based on master equations to describe the time evolution of the popularity of topics and hashtags on the Twitter social network. Specifically, we model the number of times a certain hashtag appears on the network as a function of time. In our model, the behavior of this quantity depends on the degree distribution of the netw

Kyle Sprague, Juan Carrasquilla, Steve Whitelam, Isaac Tamblyn

Transfer learning refers to the use of knowledge gained while solving a machine learning task and applying it to the solution of a closely related problem. Such an approach has enabled scientific breakthroughs in computer vision and natural language processing where the weights learned in state-of-the-art models can be used to initialize models for other tas

Juno V. Saraiva, Iran M. Braga, Victor F. Monteiro, F. Rafael M. Lima

In this article, we study a Radio Resource Allocation (RRA) that was formulated as a non-convex optimization problem whose main aim is to maximize the spectral efficiency subject to satisfaction guarantees in multiservice wireless systems. This problem has already been previously investigated in the literature and efficient heuristics have been proposed. How

Jack D. Kendall, Ross D. Pantone, Juan C. Nino

Analog crossbar architectures for accelerating neural network training and inference have made tremendous progress over the past several years. These architectures are ideal for dense layers with fewer than roughly a thousand neurons. However, for large sparse layers, crossbar architectures are highly inefficient. A new hardware architecture, dubbed the MN3

James Dallas, Michael P. Cole, Paramsothy Jayakumar, Tulga Ersal

In this work, a neural network based terramechanics model and terrain estimator are presented with an outlook for optimal control applications such as model predictive control. Recognizing the limitations of the state-of-the-art terramechanics models in terms of operating conditions, computational cost, and continuous differentiability for gradient-based opt

Borys Tymchenko, Philip Marchenko, Dmitry Spodarets

Diabetic retinopathy is one of the most threatening complications of diabetes that leads to permanent blindness if left untreated. One of the essential challenges is early detection, which is very important for treatment success. Unfortunately, the exact identification of the diabetic retinopathy stage is notoriously tricky and requires expert human interpre

Sergiy Borodachov

We study the problem of maximizing the minimal value over the sphere $S^{d-1}\subset \mathbb R^d$ of the potential generated by a configuration of $d+1$ points on $S^{d-1}$ (the maximal discrete polarization problem). The points interact via the potential given by a function $f$ of the Euclidean distance squared, where $f:[0,4]\to (-\infty,\infty]$ is contin

Carlos Paz-Soldan

The rapidly emerging technology of high-temperature superconductors (HTS) opens new opportunities for the development of non-planar non-insulated HTS magnets. This type of HTS magnet offers attractive features via its simplicity, robustness, and is well-suited for modest size steady-state applications such as a mid-scale stellarator. In non-planar coil appli

Lili Wang, Ji Liu, A. Stephen Morse

A simply structured distributed observer is described for estimating the state of a continuous-time, jointly observable, input-free, linear system whose sensed outputs are distributed across a time-varying network. It is explained how to design a gain $g$ in the observer so that their state estimation errors all converge exponentially fast to zero at a fixed

Bruce A. Cox, Christopher M. Smith, Timothy W. Breitbach, Jade F. Baker

Supply chains need to balance competing objectives; in addition to efficiency they need to be resilient to adversarial and environmental interference, and robust to uncertainties in long term demand. Significant research has been conducted designing efficient supply chains, and recent research has focused on resilient supply chain design. However, the integr

Erwann Delay

We adapt the Bartnik method to provide a Hilbert manifold structure for the space of solutions, without KID's, to the vacuum constraint equations on compact manifold of any dimension $\geq 3$. In the course, we prove that some fibers of the scalar curvature or the constraint operator are Hilbert submanifolds. We also study some operators and inequalities

Qian Chen, Wen Wang

The noetic end-to-end response selection challenge as one track in the 7th Dialog System Technology Challenges (DSTC7) aims to push the state of the art of utterance classification for real world goal-oriented dialog systems, for which participants need to select the correct next utterances from a set of candidates for the multi-turn context. This paper pres

Qi Yan, Xian'an Jin

Delta-matroid theory is often thought of as a generalization of topological graph theory. It is well-known that an orientable embedded graph is bipartite if and only if its Petrie dual is orientable. In this paper, we first introduce the concepts of Eulerian and bipartite delta-matroids and then extend the result from embedded graphs to arbitrary binary delt

Hirofumi Fujii, Kazuhiko Hara, Kohei Hayashi, Hidekazu Kakuno

We have investigated the status of the nuclear fuel assemblies in Unit-1 reactor of the Fukushima Daiichi Nuclear Power plant by the method called Cosmic Muon Radiography. In this study, muon tracking detectors were placed outside of the reactor building. We succeeded in identifying the inner structure of the reactor complex such as the reactor containment v

Priya Sundaresan, Jennifer Grannen, Brijen Thananjeyan, Ashwin Balakrishna

Robotic manipulation of deformable 1D objects such as ropes, cables, and hoses is challenging due to the lack of high-fidelity analytic models and large configuration spaces. Furthermore, learning end-to-end manipulation policies directly from images and physical interaction requires significant time on a robot and can fail to generalize across tasks. We add

P. V. Shibaev, O. Roslyak, E. Gullatt, J. Plumitallo

Novel liquid crystalline (LC) compositions are suggested and studied as elements of LC-nose. This allows for optical detection of several volatile organic compounds (VOCs). Ethanol, toluene, pyridine and acetic acid were detected by means of colorimetric and spectroscopic techniques during their diffusion inside chiral elements of LC-nose. Selectivity to dif

Jorge Benet, Pablo Llombart, Eduardo Sanz, Luis G. MacDowell

In this paper we study the structure of the ice/vapor interface in the neighborhood of the triple point for the TIP4P/2005 model. We probe the fluctuations of the ice/film and film/vapor surfaces that separate the liquid film from the coexisting bulk phases at basal, primary prismatic and secondary prismatic planes. The results are interpreted using a couple

Du Ran, Bin Zhang, Ye-Hong Chen, Zhi-Cheng Shi

We propose a scheme to control the evolution of a two-level quantum system in the strong coupling regime based on the idea of reverse-engineering. A coherent control field is designed to drive both closed and open two-level quantum systems along user predefined evolution trajectory without utilizing the rotating-wave approximation (RWA). As concrete examples

Ricard Durall, Margret Keuper, Janis Keuper

Generative convolutional deep neural networks, e.g. popular GAN architectures, are relying on convolution based up-sampling methods to produce non-scalar outputs like images or video sequences. In this paper, we show that common up-sampling methods, i.e. known as up-convolution or transposed convolution, are causing the inability of such models to reproduce

Davoud Mougouei, David M W Powers

Software Release Planning (SRP) is to find, for the software, a subset of the requirements with the highest value while respecting the budget. The value of a requirement however may, to various degrees, depend on selecting or ignoring other requirements. However, existing SRP models ignore either Value-Related Dependencies altogether or the strengths of thos

Therese Biedl, Anna Lubiw, Owen Merkel

A $k$-colouring of a graph $G$ is an assignment of at most $k$ colours to the vertices of $G$ so that adjacent vertices are assigned different colours. The reconfiguration graph of the $k$-colourings, $\mathcal{R}_k(G)$, is the graph whose vertices are the $k$-colourings of $G$ and two colourings are joined by an edge in $\mathcal{R}_k(G)$ if they differ in

Zhaodong Chu, Chun-Yuan Wang, Jiamin Quan, Chenhui Zhang

The optoelectronic properties of atomically thin transition-metal dichalcogenides are strongly correlated with the presence of defects in the materials, which are not necessarily detrimental for certain applications. For instance, defects can lead to an enhanced photoconduction, a complicated process involving charge generation and recombination in the time

Mario Damiano, Renyu Hu

The high-contrast imaging technique is meant to provide insight into those planets orbiting several astronomical units from their host star. Space missions such as WFIRST, HabEx, and LUVOIR will measure reflected light spectra of cold gaseous and rocky planets. To interpret these observations we introduce ExoReL$^\Re$ (Exoplanetary Reflected Light Retrieval)

Igor Tsukerman

The paper examines local approximation errors of finite difference schemes in electromagnetic analysis. Despite a long history of the subject, several accuracy-related issues have been overlooked and/or remain controversial. For example, conflicting claims have been made in the literature about the order of Yee-like schemes in the vicinity of slanted or curv

Yongyang Cai, Kenneth Judd, Rong Xu

We apply numerical dynamic programming techniques to solve discrete-time multi-asset dynamic portfolio optimization problems with proportional transaction costs and shorting/borrowing constraints. Examples include problems with multiple assets, and many trading periods in a finite horizon problem. We also solve dynamic stochastic problems, with a portfolio i

Leonard Susskind

The quantum-Extended Church-Turing thesis is a principle of physics as well as computer science. It asserts that the laws of physics will prevent the construction of a machine that can efficiently determine the results of any calculation which cannot be done efficiently by a quantum Turing machine (or a universal quantum circuit). In this note I will argue t

Chris J. R. Lynch, Michael D. Smith

Most stars form in binaries, and both stars may grow by accreting material from a circumbinary disc onto their personal discs. We suspect that in many cases a wide molecular wind will envelope a collimated atomic jet emanating from close to an orbiting young star. This so-called Circumbinary Scenario is explored here in order to find common identifiable prop

Mouhyemen Khan, Akash Patel, Abhijit Chatterjee

A key challenge with controlling complex dynamical systems is to accurately model them. However, this requirement is very hard to satisfy in practice. Data-driven approaches such as Gaussian processes (GPs) have proved quite effective by employing regression based methods to capture the unmodeled dynamical effects. However, GPs scale cubically with data, and

Jonathan Crickmore, Ittoop Vergheese Puthoor, Berke Ricketti, Sarah Croke

Quantum state elimination measurements tell us what states a quantum system does not have. This is different from state discrimination, where one tries to determine what the state of a quantum system is, rather than what it is not. Apart from being of fundamental interest, quantum state elimination may find uses in quantum communication and quantum cryptogra

John Lesieutre

We construct some positive entropy automorphisms of rational surfaces with no periodic curves. The surfaces in question, which we term tri-Coble surfaces, are blow-ups of the projective plane at 12 points which have contractions down to three different Coble surfaces. The automorphisms arise as compositions of lifts of Bertini involutions from certain degree

Binxuan Huang, Kathleen M. Carley

An identity denotes the role an individual or a group plays in highly differentiated contemporary societies. In this paper, our goal is to classify Twitter users based on their role identities. We first collect a coarse-grained public figure dataset automatically, then manually label a more fine-grained identity dataset. We propose a hierarchical self-attent

Natalia Bondarenko

An inverse spectral problem is studied for the matrix Sturm-Liouville operator on a finite interval with the general self-adjoint boundary condition. We obtain a constructive solution based on the method of spectral mappings for the considered inverse problem. The nonlinear inverse problem is reduced to a linear equation in a special Banach space of infinite

Alejandro Parada-Mayorga, Luana Ruiz, Alejandro Ribeiro

Graph neural networks (GNNs) have been used effectively in different applications involving the processing of signals on irregular structures modeled by graphs. Relying on the use of shift-invariant graph filters, GNNs extend the operation of convolution to graphs. However, the operations of pooling and sampling are still not clearly defined and the approach

Eleonora Guerrini, Romain Lebreton, Ilaria Zappatore

In this work we present some results that allow to improve the decoding radius in solving polynomial linear systems with errors in the scenario where errors are additive and randomly distributed over a finite field. The decoding radius depends on some bounds on the solution that we want to recover, so their overestimation could significantly decrease our err

Yaotian Wang, Xiaohang Sun, Jason W. Fleischer

Recovering a signal from its Fourier intensity underlies many important applications, including lensless imaging and imaging through scattering media. Conventional algorithms for retrieving the phase suffer when noise is present but display global convergence when given clean data. Neural networks have been used to improve algorithm robustness, but efforts t

James Ren Hou Lee, Alexander Wong

A core challenge faced by the majority of individuals with Autism Spectrum Disorder (ASD) is an impaired ability to infer other people's emotions based on their facial expressions. With significant recent advances in machine learning, one potential approach to leveraging technology to assist such individuals to better recognize facial expressions and red

Thomas P. Darlington, Christian Carmesin, Matthias Florian, Emanuil Yanev

In monolayer transition metal dichalcogenides, quantum emitters are associated with localized strain that can be deterministically applied to create designer nano-arrays of single photon sources. Despite an overwhelming empirical correlation with local strain, the nanoscale interplay between strain, excitons, defects and local crystalline structure that give

Cory Stephenson, Jenelle Feather, Suchismita Padhy, Oguz Elibol

Encouraged by the success of deep neural networks on a variety of visual tasks, much theoretical and experimental work has been aimed at understanding and interpreting how vision networks operate. Meanwhile, deep neural networks have also achieved impressive performance in audio processing applications, both as sub-components of larger systems and as complet

Matt Roveto, Robert Mieth, Yury Dvorkin

The ability to make optimal decisions under uncertainty remains important across a variety of disciplines from portfolio management to power engineering. This generally implies applying some safety margins on uncertain parameters that may only be observable through a finite set of historical samples. Nevertheless, the optimized decisions must be resilient to

Hossen Teimoorinia, J. J. Kavelaars, Stephen Gwyn, Daniel Durand

We present a two-component Machine Learning (ML) based approach for classifying astronomical images by data-quality via an examination of sources detected in the images and image pixel values from representative sources within those images. The first component, which uses a clustering algorithm, creates a proper and small fraction of the image pixels to dete

Takami Sato, Junjie Shen, Ningfei Wang, Yunhan Jack Jia

Lane-Keeping Assistance System (LKAS) is convenient and widely available today, but also extremely security and safety critical. In this work, we design and implement the first systematic approach to attack real-world DNN-based LKASes. We identify dirty road patches as a novel and domain-specific threat model for practicality and stealthiness. We formulate t

Jeremy L. Smallwood, Alessia Franchini, Cheng Chen, Eric Becerril

We investigate the formation mechanism for the observed nearly polar aligned (perpendicular to the binary orbital plane) debris ring around the eccentric orbit binary 99 Herculis. An initially inclined nonpolar debris ring or disc will not remain flat and will not evolve to a polar configuration, due to the effects of differential nodal precession that alter

S. Saracino, S. Martocchia, N. Bastian, V. Kozhurina-Platais

Recent studies have revealed that the Multiple Populations (MPs) phenomenon does not occur only in ancient and massive Galactic globular clusters (GCs), but it is also observed in external galaxies, where GCs sample a wide age range with respect to the Milky Way. However, for a long time, it was unclear whether we were looking at the same phenomenon in diffe

Alexander Lopez, Rafael Molina

We propose an experimental realization of the Spin Hall effect in graphene by illuminating a graphene sheet on top of a substrate with circularly polarized monochromatic light. The substrate induces a controllable Rashba type spin-orbit coupling which breaks the spin-degeneracy of the Dirac cones but it is gapless. The circularly polarized light induces a ga

Yanjun Xu, Fiona A. Harrison, John A. Tomsick, Jeremy Hare

We present results from NuSTAR and XMM-Newton observations of the new black hole X-ray binary MAXI J1820+070 at low accretion rates (below 1% of the Eddington luminosity). We detect a narrow Fe K$α$ emission line, in contrast to the broad and asymmetric Fe K$α$ line profiles commonly present in black hole binaries at high accretion rates. The narrow line, wi

Chun Yu Tammy Huang, Fariborz Kargar, Topojit Debnath, Bishwajit Debnath

We report the results of Brillouin-Mandelstam spectroscopy and Mueller matrix spectroscopic ellipsometry of the nanoscale "pillar with the hat" periodic silicon structures, revealing intriguing phononic and photonic properties. It has been theoretically shown that periodic structures with properly tuned dimensions can act simultaneously as phononic a

Zhao Han, Jordan Allspaw, Gregory LeMasurier, Jenna Parrillo

The FetchIt! Mobile Manipulation Challenge, held at the IEEE International Conference on Robots and Automation (ICRA) in May 2019, offered an environment with complex and integrated task sets, irregular objects, confined space, and machining, introducing new challenges in the mobile manipulation domain. Here we describe our efforts to address these challenge

Kamiar Rahnama Rad, Wenda Zhou, Arian Maleki

We study the problem of out-of-sample risk estimation in the high dimensional regime where both the sample size $n$ and number of features $p$ are large, and $n/p$ can be less than one. Extensive empirical evidence confirms the accuracy of leave-one-out cross validation (LO) for out-of-sample risk estimation. Yet, a unifying theoretical evaluation of the acc

Peter Plantinga, Deblin Bagchi, Eric Fosler-Lussier

While deep learning systems have gained significant ground in speech enhancement research, these systems have yet to make use of the full potential of deep learning systems to provide high-level feedback. In particular, phonetic feedback is rare in speech enhancement research even though it includes valuable top-down information. We use the technique of mimi

Xinzheng Zhang, Hang Su, Ce Zhang, Peter M. Atkinson

In this research, a novel robust change detection approach is presented for imbalanced multi-temporal synthetic aperture radar (SAR) image based on deep learning. Our main contribution is to develop a novel method for generating difference image and a parallel fuzzy c-means (FCM) clustering method. The main steps of our proposed approach are as follows: 1) I

Peter Plantinga, Eric Fosler-Lussier

Modern mispronunciation detection and diagnosis systems have seen significant gains in accuracy due to the introduction of deep learning. However, these systems have not been evaluated for the ability to be run in real-time, an important factor in applications that provide rapid feedback. In particular, the state-of-the-art uses bi-directional recurrent netw

Jie Liu, Jiawen Liu, Zhen Xie, Dong Li

How to accurately and efficiently label data on a mobile device is critical for the success of training machine learning models on mobile devices. Auto-labeling data on mobile devices is challenging, because data is usually incrementally generated and there is possibility of having unknown labels. Furthermore, the rich hardware heterogeneity on mobile device

Du Wei, Cheng Cheng, Zheng Zheng, Wu Hong

We estimate the stellar mass for a sample of low surface brightness galaxies (LSBGs) by fitting their multiband spectral energy distributions (SEDs) to the stellar population synthesis (SPS) model. The derived stellar masses (log M*/Msun) span from 7.1 to 11.1, with a mean of log M*/Msun=8.5, which is lower than that for normal galaxies. The stellar mass-to-

Shreyas Kousik, Bohao Zhang, Pengcheng Zhao, Ram Vasudevan

To move through the world, mobile robots typically use a receding-horizon strategy, wherein they execute an old plan while computing a new plan to incorporate new sensor information. A plan should be dynamically feasible, meaning it obeys constraints like the robot's dynamics and obstacle avoidance; it should have liveness, meaning the robot does not sto

Eric B. Isaacs, Shane Patel, Chris Wolverton

Quantitative predictions of the Li intercalation voltage and of the electronic properties of rechargeable battery cathode materials are a substantial challenge for first-principles theory due to the possibility of (1) strong correlations associated with localized transition metal $d$ electrons and (2) significant van der Waals (vdW) interactions in layered s

Eylon Persky, Hyeok Yoon, Yanwu Xie, Harold Y. Hwang

We study the effects of electrostatic gating on the lateral distribution of charge carriers in two dimensional devices, in a non-linear dielectric environment. We compute the charge distribution using the Thomas-Fermi approximation to model the electrostatics of the system. The electric field lines generated by the gate are focused at the edges of the device

Zepeng Huo, Arash PakBin, Xiaohan Chen, Nathan Hurley

Activity recognition in wearable computing faces two key challenges: i) activity characteristics may be context-dependent and change under different contexts or situations; ii) unknown contexts and activities may occur from time to time, requiring flexibility and adaptability of the algorithm. We develop a context-aware mixture of deep models termed the α-\b

AbdulAziz Al-Helali, Ben Liang, Nidal Nasser

Recently, Molecular Communication (MC) has been recognized as an enabling technology for nanonetworks where MC is envisioned to enable nanorobots to achieve sophisticated and complex tasks in the human body for promising medical applications. Many MC methods that can be applied in the human body have been proposed and modeled in the literature. However, none

Bozhou Chen, Kaixin Zhang, Longshen Ou, Chenmin Ba

Machine learning algorithms have made remarkable achievements in the field of artificial intelligence. However, most machine learning algorithms are sensitive to the hyper-parameters. Manually optimizing the hyper-parameters is a common method of hyper-parameter tuning. However, it is costly and empirically dependent. Automatic hyper-parameter optimization (

B. King, S. Tang

We investigate the phenomenology of nonlinear Compton scattering of polarised photons by unpolarised electrons in plane-wave backgrounds. The energy and angular spectra of polarised photons are calculated for linearly- and circularly-polarised pulses, monochromatic fields and constant crossed field backgrounds. When the field intensity is in the weakly nonli

Maude J. Blondin, Matthew Hale

Multi-agent optimization problems with many objective functions have drawn much interest over the past two decades. Many works on the subject minimize the sum of objective functions, which implicitly carries a decision about the problem formulation. Indeed, it represents a special case of a multi-objective problem, in which all objectives are prioritized equ

Johannes Ziegler, Dmitriy A. Kozlov, Nikolay N. Mikhailov, Sergey A. Dvoretsky

We review low and high field magnetotransport in 80 nm-thick strained HgTe, a material that belongs to the class of strong three-dimensional topological insulators. Utilizing a top gate, the Fermi level can be tuned from the valence band via the Dirac surface states into the conduction band and allows studying Landau quantization in situations where differen

Andrew Elvey Price

We address the problem of counting walks by winding angle on the Kreweras lattice, an oriented version of the triangular lattice. Our method uses a new decomposition of the lattice, which allows us to write functional equations characterising a generating function of walks counted by length, endpoint and winding angle. We then solve these functional equation

Shannon D. Dulz, Peter Plavchan, Justin R. Crepp, Christopher Stark

Planet yield calculations may be used to inform the target selection strategy and science operations of space observatories. Forthcoming and proposed NASA missions, such as the Wide-Field Infrared Survey Telescope (WFIRST), the Habitable Exoplanet Imaging Mission (HabEx), and the Large UV/Optical/IR Surveyor (LUVOIR), are expected to be equipped with sensiti

Stavros Akras, Denise R. Gonçalves, Gerardo Ramos-Larios, Isabel Aleman

Despite the many studies in the last decades, the low-ionisation structures (LISs) of planetary nebulae (PNe) still hold several mysteries. Recent imaging surveys have demonstrated that LISs are composed of molecular gas. Here we report H$_2$ emission in the LISs of NGC 7009 and NGC 6543 by means of very deep narrow-band H$_2$ images taken with NIRI@Gemini.

Ian Harrison, Michael L. Brown, Ben Tunbridge, Daniel B. Thomas

We describe the first results on weak gravitational lensing from the SuperCLASS survey: the first survey specifically designed to measure the weak lensing effect in radio-wavelength data, both alone and in cross-correlation with optical data. We analyse 1.53 square degrees of optical data from the Subaru telescope and 0.26 square degrees of radio data from t

Sinclaire M. Manning, Caitlin M. Casey, Chao-Ling Hung, Richard Battye

We present optical and near-infrared imaging covering a $\sim$1.53 deg$^2$ region in the Super-Cluster Assisted Shear Survey (SuperCLASS) field, which aims to make the first robust weak lensing measurement at radio wavelengths. We derive photometric redshifts for $\approx$176,000 sources down to $i^\prime_{\rm AB}\sim24$ and present photometric redshifts for

Richard A. Battye, Michael L. Brown, Caitlin M. Casey, Ian Harrison

The SuperCLuster Assisted Shear Survey (SuperCLASS) is a legacy programme using the e-MERLIN interferometric array. The aim is to observe the sky at L-band (1.4 GHz) to a r.m.s. of 7 uJy per beam over an area of ~1 square degree centred on the Abell 981 supercluster. The main scientific objectives of the project are: (i) to detect the effects of weak lensing

N. Hedrich, D. Rohner, M. Batzer, P. Maletinsky

Enhancing the measurement signal from solid state quantum sensors such as the nitrogen-vacancy (NV) center in diamond is an important problem for sensing and imaging of condensed matter systems. Here we engineer diamond scanning probes with a truncated parabolic profile that optimizes the photonic signal from single embedded NV centers, forming a high-sensit

Erik Parr, Patrick K. S. Vaudrevange, Martin Wimmer

MSSM-like string models from the compactification of the heterotic string on toroidal orbifolds (of the kind $T^6/P$) have distinct phenomenological properties, like the spectrum of vector-like exotics, the scale of supersymmetry breaking, and the existence of non-Abelian flavor symmetries. We show that these characteristics depend crucially on the choice of

Omri Lesser, Gal Shavit, Yuval Oreg

We show that a one-dimensional topological superconductor can be realized in carbon nanotubes, using a relatively small magnetic field. Our analysis relies on the intrinsic curvature-enhanced spin-orbit coupling of the nanotubes, as well as on the orbital effect of a magnetic flux threaded through the nanotube. Tuning experimental parameters, we show that a

Jenifer S. Millard, Stephen A. Eales, M. W. L. Smith, H. L. Gomez

We investigate the evolution of the gas mass fraction for galaxies in the COSMOS field using submillimetre emission from dust at 850$μ$m. We use stacking methodologies on the 850$μ$m S2COSMOS map to derive the gas mass fraction of galaxies out to high redshifts, 0 <= $z$ <= 5, for galaxies with stellar masses of $10^{9.5} < M_* (\rm M_{\odot}) < 10^{11.75}$.

C. J. Nixon, J. E. Pringle

In order to provide an explanation for the unexpected radial brightness distribution of the steady accretion discs seen in nova-like variables, Nixon & Pringle (2019) proposed that the accretion energy is redistributed outwards by means of strong, magnetically driven, surface flows. In this paper we note that the &#34;powerful, rotating disc winds&#34; obser

Anshu Gupta, Kim-Vy Tran, Jonathan Cohn, Leo Y. Alcorn

We use K-band spectroscopic data from the Multi-Object Spectroscopic Emission Line (MOSEL) survey to analyze the kinematic properties of galaxies at z>3. Our sample consists of 34 galaxies at 3.0<zspec<3.8 between 9.0<log(M_star)<11.0. We find that galaxies with log(M_star) > 10.2 at z > 3 have 56 +/- 21 km/s lower integrated velocity dispersion compared to

Philipp Eitner, Maria Bergemann, Camilla Juul Hansen, Gabriele Cescutti

The abundance ratios of manganese to iron in late-type stars across a wide metallicity range place tight constraints on the astrophysical production sites of Fe-group elements. In this work, we investigate the chemical evolution of Mn in the Milky Way galaxy using high-resolution spectroscopic observations of stars in the Galactic disc and halo stars, as wel

Evgeni Grishin, Uri Malamud, Hagai B. Perets, Oliver Wandel

Following its flyby and first imaging the Pluto-Charon binary, the New Horizons spacecraft visited the Kuiper-Belt-Object (KBO) (486958) 2014 MU69 (Arrokoth). Imaging showed MU69 to be a contact-binary, made of two individual lobes connected by a narrow neck, rotating at low spin period (15.92 h), and having high obliquity (~98 deg), similar to other KBO con

Jens Bayer, David Münch, Michael Arens

Living in a complex world like ours makes it unacceptable that a practical implementation of a machine learning system assumes a closed world. Therefore, it is necessary for such a learning-based system in a real world environment, to be aware of its own capabilities and limits and to be able to distinguish between confident and unconfident results of the in

Charis Mesaritakis, Marialena Akriotou, Dimitris Syvridis

We present a photonic system that exploits the speckle generated by the interaction of a laser source and a semitransparent scattering medium, in our case a large-core optical fiber, as a physical root of trust for cryptographic applications, while the same configuration can act as a high-rate machine learning paradigm.

Ferdinand Gleixner, Naveen Kumar

Electronic parametric instabilities of an ultrarelativistic circularly polarized laser pulse propagating in underdense plasmas are studied by numerically solving the dispersion relation which includes the effect of the radiation reaction force in laser-driven plasma dynamics. Emphasis is placed on studying the different modes in the laser-plasma system and i

V. G. Dubrovsky, A. V. Topovsky

We constructed the new classes of exact multi-lump solutions of KP-1 and KP-2 versions of KP equations with integrable boundary condition $u_{y}\big|_{y=0}=0$ by the use of $\overline\partial$-dressing method of Zakharov and Manakov and derived general determinant formula for such solutions. We demonstrated how reality and boundary conditions for the field $

V. G. Dubrovsky, A. V. Topovsky

New classes of exact multi-soliton solutions of KP-1 and KP-2 versions of Kadomtsev-Petviashvili equation with integrable boundary condition $u_{y}\big|_{y=0}=0$ by the use of $\overline\partial$-dressing method of Zakharov and Manakov are constructed in the paper. General determinant formula in convenient form for such solutions is derived. It is shown how

Emilio Musso, Filippo Salis

The lower-order cr-invariant variational problem for Legendrian curves in the 3-sphere is studied and its Euler-Lagrange equations are deduced. Closed critical curves are investigated. Closed critical curves with non-constant cr-curvature are characterized. We prove that their cr-equivalence classes are in one-to-one correspondence with the rational points o

Suat Gumussoy, Hitay Ozbay

The skew Toeplitz approach is one of the well developed methods to design H-infinity controllers for infinite dimensional systems. In order to be able to use this method the plant needs to be factorized in some special manner. This paper investigates the largest class of SISO time delay systems for which the special factorizations required by the skew Toepli

S. Amoroso, P. Azzurri, J. Bendavid, E. Bothmann

This Report summarizes the proceedings of the 2019 Les Houches workshop on Physics at TeV Colliders. Session 1 dealt with (I) new developments for high precision Standard Model calculations, (II) the sensitivity of parton distribution functions to the experimental inputs, (III) new developments in jet substructure techniques and a detailed examination of glu

Luis Linan, Étienne Pariat, Guillaume Aulanier, Kostas Moraitis

Based on a decomposition of the magnetic field into potential and nonpotential components, magnetic energy and relative helicity can both also be decomposed into two quantities: potential and free energies, and volume-threading and current-carrying helicities. In this study, we perform a coupled analysis of their behaviors in a set of parametric 3D magnetohy

Bapi Chatterjee, Sathya Peri, Muktikanta Sa

Graph algorithms enormously contribute to the domains such as blockchains, social networks, biological networks, telecommunication networks, and several others. The ever-increasing demand of data-volume, as well as speed of such applications, have essentially transported these applications from their comfort zone: static setting, to a challenging territory o

Alfons Geser, Dieter Hofbauer, Johannes Waldmann

We over-approximate reachability sets in string rewriting by languages defined by admissible factors, called tiles. A sparse set of tiles contains only those that are reachable in derivations, and is constructed by completing an automaton. Using the partial algebra defined by a sparse tiling for semantic labelling, we obtain a transformational method for pro

Ryan LaRose, Brian Coyle

Data representation is crucial for the success of machine learning models. In the context of quantum machine learning with near-term quantum computers, equally important considerations of how to efficiently input (encode) data and effectively deal with noise arise. In this work, we study data encodings for binary quantum classification and investigate their

Paolo Antonelli, Michele Dolce, Pierangelo Marcati

In this paper, we investigate linear stability properties of the 2D isentropic compressible Euler equations linearized around a shear flow given by a monotone profile, close to the Couette flow, with constant density, in the domain $\mathbb{T}\times \mathbb{R}$. We begin by directly investigating the Couette shear flow, where we characterize the linear growt

J. Blümlein, A. Maier, P. Marquard, G. Schäfer

We calculate the motion of binary mass systems in gravity up to the fourth post--Newtonian order. We use momentum expansions within an effective field theory approach based on Feynman amplitudes in harmonic coordinates by applying dimensional regularization. We construct the canonical transformations to ADM coordinates and to effective one body theory (EOB)

M. Zeynali Azim, M. A. Jabraeil Jamali, B. Anari, S. Alikhani

In this paper, we introduce a new method which we call it MZ-method, for dividing a natural number $x$ by two and then we use graph as a model to show MZ-algorithm. Applying (recursively) $k$-times of the MZ-method for the number $x$, produces a graph with unique structure that is denoted by $G_k(x)$. We investigate the structure of $G_k(x)$. Also from the n

Harry Schmidt

We give a short proof of Manin-Mumford in the multiplicative group based on the pigeon-hole principle and the so-called structure theorem for anomalous subvarieties. The arguments appear to be new and perhaps applicable in other situations.

Jason N. Byrd, Stephen E. Masters, Douglas S. Burns, Victor F. Lotrich

The task of developing high performing parallel software must be made easier and more cost effective in order to fully exploit existing and emerging large scale computer systems for the advancement of science. The Super Instruction Architecture is a parallel programming platform geared towards applications that need to manage large amounts of data stored in

S. M. A. Tabatabaee, N. Sadooghi

By combining the Wigner function formalism of relativistic quantum kinetic theory with fundamental equations of relativistic magnetohydrodynamics (MHD), we present a novel approach to determine the proper time evolution of the temperature and other thermodynamic quantities in a uniformly expanding hot, magnetized, and weakly interacting plasma. The aim is to

Francesca Arici, Francesco Galuppi, Tatiana Gateva-Ivanova

We study Veronese and Segre morphisms between non-commutative projective spaces. We compute finite reduced Gröbner bases for their kernels, and we compare them with their analogues in the commutative case.