January 2019 arXiv papers — page 36

Kieran Conboy, Noel Carroll

Based on 13 agile transformation cases over 15 years, this article identifies nine challenges associated with implementing SAFe, Scrum-at-Scale, Spotify, LeSS, Nexus, and other mixed or customised large-scale agile frameworks. These challenges should be considered by organizations aspiring to pursue a large-scale agile strategy. This article also provides re

Diego Perez-Liebana, Katja Hofmann, Sharada Prasanna Mohanty, Noboru Kuno

Learning in multi-agent scenarios is a fruitful research direction, but current approaches still show scalability problems in multiple games with general reward settings and different opponent types. The Multi-Agent Reinforcement Learning in Malm\"O (MARL\"O) competition is a new challenge that proposes research in this domain using multiple 3D games. The go

Sam Green, Craig M. Vineyard, Çetin Kaya Koç

Vision-based deep reinforcement learning (RL) typically obtains performance benefit by using high capacity and relatively large convolutional neural networks (CNN). However, a large network leads to higher inference costs (power, latency, silicon area, MAC count). Many inference optimizations have been developed for CNNs. Some optimization techniques offer t

Ryuji Takagi, Bartosz Regula

We establish an operational characterization of general convex resource theories -- describing the resource content of not only states, but also measurements and channels, both within quantum mechanics and in general probabilistic theories (GPTs) -- in the context of state and channel discrimination. We find that discrimination tasks provide a unified operat

Myoung-Gyun Suh, Christine Y. Wang, Cort Johnson, Kerry Vahala

Soliton microcombs offer the prospect of advanced optical metrology and timing systems in compact form factors. In these applications, pumping of microcombs directly from a semiconductor laser without amplification or triggering components is desirable for reduced power operation and to simplify system design. At the same time, low repetition rate microcombs

Alvaro E. Ulloa Cerna, Marios Pattichis, David P. vanMaanen, Linyuan Jing

The majority of biomedical studies use limited datasets that may not generalize over large heterogeneous datasets that have been collected over several decades. The current paper develops and validates several multimodal models that can predict 1-year mortality based on a massive clinical dataset. Our focus on predicting 1-year mortality can provide a sense

Marco Frasca

Using a technique devised by Bender, Milton and Savage, we derive the Dyson-Schwinger equations for quantum chromodynamics in differential form. We stop our analysis to the two-point functions. The 't~Hooft limit of color number going to infinity is derived showing how these equations can be cast into a treatable even if approximate form. It is seen how this

Zdzisław Brzeźniak, Nimit Rana

We prove the existence and the uniqueness of a local maximal solution to an $H^1$-critical stochastic wave equation with multiplicative noise on a smooth bounded domain $\mathcal{D} \subset \mathbb{R}^2$ with exponential nonlinearity. First, we derive the appropriate deterministic and stochastic Strichartz inequalities in suitable spaces and, then use them i

Andrew Douglas, Willem A. de Graaf

We describe an algorithm for classifying the closed subsets of a root system, up to conjugation by the associated Weyl group. Such a classification of an irreducible root system is closely related to the classification of the regular subalgebras, up to inner automorphism, of the corresponding simple Lie algebra. We implement our algorithm to classify the clo

Ilia Shumailov, Xitong Gao, Yiren Zhao, Robert Mullins

Convolutional Neural Networks (CNNs) are widely used to solve classification tasks in computer vision. However, they can be tricked into misclassifying specially crafted `adversarial' samples -- and samples built to trick one model often work alarmingly well against other models trained on the same task. In this paper we introduce Sitatapatra, a system desig

Daniel Goldstein, Sriram Ramaswamy, Bulbul Chakraborty

Inspired by experiments on dynamic extensile gels of biofilaments and motors, we propose a model of a network of linear springs with a kinetics consisting of growth at a prescribed rate, death after a lifetime drawn from a distribution, and birth at a randomly chosen node. The model captures features such as the build-up of self-stress, that are not easily i

Di Qi, Andrew J. Majda

A new strategy is presented to explain the creation and persistence of zonal flows widely observed in plasma edge turbulence. The core physics in the edge regime of the magnetic-fusion tokamaks can be described qualitatively by the one-state modified Hasegawa-Mima (MHM) model, which creates enhanced zonal flows and more physically relevant features in compar

Yixuan Tan, Xin Lei, Xingze Wang, Shanhui Fan

Visual object recognition is one of the most important perception functions for a wide range of intelligent machines. A conventional recognition process begins with forming a clear optical image of the object, followed by its computer analysis. In contrast, it is possible to carry out recognition without imaging by using coherent illumination and directly an

Cecilia Balocchi, Shane T. Jensen

Understanding the relationship between change in crime over time and the geography of urban areas is an important problem for urban planning. Accurate estimation of changing crime rates throughout a city would aid law enforcement as well as enable studies of the association between crime and the built environment. Bayesian modeling is a promising direction s

Krzysztof Rusek, José Suárez-Varela, Albert Mestres, Pere Barlet-Ros

Network modeling is a critical component for building self-driving Software-Defined Networks, particularly to find optimal routing schemes that meet the goals set by administrators. However, existing modeling techniques do not meet the requirements to provide accurate estimations of relevant performance metrics such as delay and jitter. In this paper we prop

Benedikt S. L. Fritz, Robert A. Manduca

We calculate measures of economic complexity for US metropolitan areas for the years 2007-2015 based on industry employment data. We show that the concept of economic complexity translates well from the cross-country to the regional setting, and is able to incorporate local as well as traded industries. The largest cities and the Northeast of the US have the

Raf Cluckers, Mircea Mustata

We show that if f is a nonzero, noninvertible function on a smooth complex variety X and J_f is the Jacobian ideal of f, then lct(f, J_f^2)>1 if and only if the hypersurface defined by f has rational singularities. Moreover, if this is not the case, then lct(f, J_f^2)=lct(f). We give two proofs, one relying on arc spaces and one that shows that the minimal e

Nick Bultinck, Shubhayu Chatterjee, Michael P. Zaletel

We use a lowest Landau level model to study the recent observation of an anomalous Hall effect in twisted bilayer graphene. This effective model is rooted in the occurrence of Chern bands which arise due to the coupling between the graphene device and its encapsulating substrate. Our model exhibits a phase transition from a spin-valley polarized insulator to

Alvaro Gomariz, Weiye Li, Ece Ozkan, Christine Tanner

Image-guided radiation therapy can benefit from accurate motion tracking by ultrasound imaging, in order to minimize treatment margins and radiate moving anatomical targets, e.g., due to breathing. One way to formulate this tracking problem is the automatic localization of given tracked anatomical landmarks throughout a temporal ultrasound sequence. For this

Pascal Marquet

It is important to be able to calculate the moist-air entropy of the atmosphere with precision. A potential temperature has already been defined from the third law of thermodynamics for this purpose. However, a doubt remains as to whether this entropy potential temperature can be represented with simple but accurate first- or second-order approximate formula

Kiranmoy Chatterjee, Diganta Mukherjee

Efficient estimation of population size from dependent dual-record system (DRS) remains a statistical challenge in capture-recapture type experiment. Owing to the nonidentifiability of the suitable Time-Behavioral Response Variation model (denoted as $M_{tb}$) under DRS, few methods are developed in Bayesian paradigm based on informative priors. Our contribu

Lyndon Koens, Wendong Wang, Metin Sitti, Eric Lauga

Control on microscopic scales depends critically on our ability to manipulate interactions with different physical fields. The creation of micro-machines therefore requires us to understand how multiple fields, such as surface capillary or electro-magnetic, can be used to produce predictable behaviour. Recently, a spinning micro-raft system was developed tha

David Balduzzi, Marta Garnelo, Yoram Bachrach, Wojciech M. Czarnecki

Zero-sum games such as chess and poker are, abstractly, functions that evaluate pairs of agents, for example labeling them `winner' and `loser'. If the game is approximately transitive, then self-play generates sequences of agents of increasing strength. However, nontransitive games, such as rock-paper-scissors, can exhibit strategic cycles, and there is no

Gabriel Fabricius, Alberto Maltz

The spread of an epidemic process is considered in the context of a spatial SIR stochastic model that includes a parameter $0\le p\le 1$ that assigns weights $p$ and $1- p$ to global and local infective contacts respectively. The model was previously studied by other authors in different contexts. In this work we characterized the behavior of the system arou

Alberto Riccardi, Dariusz Chruściński, Chiara Macchiavello

We address the problem of optimising entanglement witnesses when a limited fixed set of local measurements can be performed on a bipartite system, thus providing a procedure, feasible also for experiments, to detect entangled states using only the statistics of these local measurements. We completely characterize the class of entanglement witnesses of the fo

Matteo Fabbri, Guido Borghi, Fabio Lanzi, Roberto Vezzani

Can faces acquired by low-cost depth sensors be useful to catch some characteristic details of the face? Typically the answer is no. However, new deep architectures can generate RGB images from data acquired in a different modality, such as depth data. In this paper, we propose a new \textit{Deterministic Conditional GAN}, trained on annotated RGB-D face dat

D. Kim, S. Jorgensen, J. Lee, J. Ahn

Whole-body control (WBC) is a generic task-oriented control method for feedback control of loco-manipulation behaviors in humanoid robots. The combination of WBC and model-based walking controllers has been widely utilized in various humanoid robots. However, to date, the WBC method has not been employed for unsupported passive-ankle dynamic locomotion. As s

Yuning Chen, Myles C. Silfies, Grzegorz Kowzan, Jose Miguel Bautista

We present a 100 MHz repetition rate Yb-fiber-laser-pumped synchronously pumped optical parametric oscillator (SPOPO) delivering tunable frequency combs covering almost the entire visible spectral range. By intracavity doubling both the signal and idler combs and using collinear residual pump light, nearly continuous tuning over the range of 420-700 nm is ac

Vincent Fortuin, Heiko Strathmann, Gunnar Rätsch

When fitting Bayesian machine learning models on scarce data, the main challenge is to obtain suitable prior knowledge and encode it into the model. Recent advances in meta-learning offer powerful methods for extracting such prior knowledge from data acquired in related tasks. When it comes to meta-learning in Gaussian process models, approaches in this sett

Federico Fulgeri, Matteo Fabbri, Stefano Alletto, Simone Calderara

When you see a person in a crowd, occluded by other persons, you miss visual information that can be used to recognize, re-identify or simply classify him or her. You can imagine its appearance given your experience, nothing more. Similarly, AI solutions can try to hallucinate missing information with specific deep learning architectures, suitably trained wi

Bryan Lim, Stefan Zohren, Stephen Roberts

Despite the recent popularity of deep generative state space models, few comparisons have been made between network architectures and the inference steps of the Bayesian filtering framework -- with most models simultaneously approximating both state transition and update steps with a single recurrent neural network (RNN). In this paper, we introduce the Recu

Russell J. Bowater

A substantial generalisation is put forward of the theory of subjective fiducial inference as it was outlined in earlier papers. In particular, this theory is extended to deal with cases where the data are discrete or categorical rather than continuous, and cases where there was important pre-data knowledge about some or all of the model parameters. The syst

A. Seo, A. V. Boris, G. Cristiani, H. -U. Habermeier

We report a spectral ellipsometry study of multilayers composed of superconducting YBa$_2$Cu$_3$O$_{6+\delta}$ (YBCO) and ferromagnetic La$_{0.7}$Ca$_{0.3}$MnO$_3$ in the spectral range of 0.7 - 6.5 eV. With increasing YBCO sublayer thickness, the optical spectral weight is enhanced at photon energies of 1.5 - 3.5 eV. The spectral weight enhancement is propo

Carlos Blanco, Dan Hooper, Pedro Machado

Results from the LSND and MiniBooNE experiments have been interpreted as evidence for a sterile neutrino with a mass near the electronvolt scale. Here we propose to test such a scenario by measuring the coherent elastic scattering rate of neutrinos from a pulsed spallation source. Coherent scattering is universal across all active neutrino flavors, and thus

Ohad Felsenstein, Idan Tal, Michal Ben-Shachar, Moshe Abeles

Multimodal behavior involves multiple processing stations distributed across distant brain regions, but our understanding of how such distributed processing is coordinated in the brain is limited. Here we take a decoding approach to this problem, aiming to quantify how temporal aspects of brain-wide neural activity may be used to infer specific multimodal be

Yaodong Li, Xiao Chen, Matthew P. A. Fisher

In this paper we continue to explore "hybrid" quantum circuit models in one-dimension with both unitary and measurement gates, focussing on the entanglement properties of wavefunction trajectories at long times, in the steady state. We simulate a large class of Clifford circuits, including models with or without randomness in the unitary gates, and with or w

Masazumi Honda

We study supersymmetric index of 4d $SU(N)$ $\mathcal{N}=4$ super Yang-Mills theory on $S^1 \times M_3$. We compute asymptotic behavior of the index in the limit of shrinking $S^1$ for arbitrary $N$ by a refinement of supersymmetric Cardy formula. The asymptotic behavior for the superconformal index case ($M_3 =S^3$) at large $N$ agrees with the Bekenstein-H

Y. Stein, R. -J. Dettmar, J. Irwin, R. Beck

We analyze the magnetic field geometry and the transport processes of the cosmic rays of the edge-on spiral starburst galaxy NGC 4666 from CHANG-ES radio continuum data in two frequencies; 6 GHz (C-band) and 1.5 GHz (L-band). Supplementary X-ray data are used to investigate the hot gas in NGC 4666. We determine the radio scale heights of total power emission

Mark Fletcher, Sergei Nayakshin, Dimitris Stamatellos, Walter Dehnen

Gas clumps formed within massive gravitationally unstable circumstellar discs are potential seeds of gas giant planets, brown dwarfs and companion stars. Simulations show that competition between three processes -- migration, gas accretion and tidal disruption -- establishes what grows from a given seed. Here we investigate the robustness of numerical modell

Michael P. Howard, Antonia Statt, Felix Madutsa, Thomas M. Truskett

We present an algorithm for neighbor search in molecular simulations on graphics processing units (GPUs) based on bounding volume hierarchies (BVHs). The BVH is compressed into a low-precision, quantized representation to increase the BVH traversal speed compared to a previous implementation. We find that neighbor search using the quantized BVH is roughly tw

Yura Malitsky, Peter Ochs

The Conditional Gradient Method is generalized to a class of non-smooth non-convex optimization problems with many applications in machine learning. The proposed algorithm iterates by minimizing so-called model functions over the constraint set. Complemented with an Amijo line search procedure, we prove that subsequences converge to a stationary point. The a

Taushif Ahmed, Prasanna K. Dhani

The two-loop four-point amplitude of two massless SU(N) colored scalars and two color singlet operators with different virtuality described by a half-BPS and Konishi operators is calculated analytically in maximally supersymmetric Yang-Mills theory. We verify the ultraviolet behaviour of the unprotected composite operator and exponentiation of the infrared d

Matteo Basei, Haoyang Cao, Xin Guo

We consider a general class of nonzero-sum $N$-player stochastic games with impulse controls, where players control the underlying dynamics with discrete interventions. We adopt a verification approach and provide sufficient conditions for the Nash equilibria (NEs) of the game. We then consider the limit situation of $N \to \infty$, that is, a suitable mean-

Mathew Titus, Zach Gelbaum, James Watson

The use of critical slowing down as an early warning indicator for regime switching in observations from stochastic environments and noisy dynamical models has been widely studied and implemented in recent years. Some systems, however, have been shown to avoid critical slowing down prior to a transition between equilibria, e.g. (Ditlevsen and Johnsen, 2010).

Katarzyna Kapusta, Gerard Memmi, Matthieu Rambaud

This paper puts a new light on secure data storage inside distributed systems. Specifically, it revisits computational secret sharing in a situation where the encryption key is exposed to an attacker. It comes with several contributions: First, it defines a security model for encryption schemes, where we ask for additional resilience against exposure of the

Nicolò Cesa-Bianchi, Tommaso R. Cesari, Claire Monteleoni

We study an asynchronous online learning setting with a network of agents. At each time step, some of the agents are activated, requested to make a prediction, and pay the corresponding loss. The loss function is then revealed to these agents and also to their neighbors in the network. Our results characterize how much knowing the network structure affects t

Jose A. Carrillo, Katy Craig, Li Wang, Chaozhen Wei

Combining the classical theory of optimal transport with modern operator splitting techniques, we develop a new numerical method for nonlinear, nonlocal partial differential equations, arising in models of porous media, materials science, and biological swarming. Our method proceeds as follows: First, we discretize in time, either via the classical JKO schem

Nestor Armesto, Fabio Dominguez, Alex Kovner, Michael Lublinsky

We introduce the notion of the Color Glass Condensate (CGC) density matrix $\hat\rho$. This generalizes the concept of probability density for the distribution of the color charges in the hadronic wave function and is consistent with understanding the CGC as an effective theory after integration of part of the hadronic degrees of freedom. We derive the evolu

Asma Ben Abacha, Dina Demner-Fushman

One of the challenges in large-scale information retrieval (IR) is to develop fine-grained and domain-specific methods to answer natural language questions. Despite the availability of numerous sources and datasets for answer retrieval, Question Answering (QA) remains a challenging problem due to the difficulty of the question understanding and answer extrac

Mario Mastriani

During the last 25 years the scientific community has coexisted with the most fascinating protocol due to Quantum Physics: quantum teleportation (QTele), which would have been impossible if quantum entanglement, so questioned by Einstein, did not exist. In this work, a complete architecture for the teleportation of Computational Basis States (CBS) is present

Paul Fendley

I solve a quantum chain whose Hamiltonian is comprised solely of local four-fermi operators by constructing free-fermion raising and lowering operators. The free-fermion operators are both non-local and highly non-linear in the local fermions. This construction yields the complete spectrum of the Hamiltonian and an associated classical transfer matrix. The s

Markus Rabus, Régis Lachaume, Andrés Jordán, Rafael Brahm

We report on 13 new high-precision measurements of stellar diameters for low-mass dwarfs obtained by means of near-infrared long-baseline interferometry with PIONIER at the Very Large Telescope Interferometer. Together with accurate parallaxes from Gaia DR2, these measurements provide precise estimates for their linear radii, effective temperatures, masses,

Samayra Straal, Joeri van Leeuwen

Pinpointing a pulsar in its parent supernova remnant (SNR) or resulting pulsar wind nebula (PWN) is key for understanding its formation history, and the pulsar wind mechanism. Yet, only about half the SNRs and PWNe appear associated with a pulsar. We aim to find the pulsars in a sample of eight known and new SNRs and PWNe. Using the LOFAR radio telescope at

Natália S. Móller, Alberto L. de Paula, Cristhiano Duarte, Raphael C. Drumond

When the reduced state of a many-body quantum system is independent of its remaining parts, we say it shows what has become known by shielding property. Under some assumptions, equilibrium states of quantum transverse Ising models do manifest such phenomenon. Namely, imagine a many-body quantum system described by a lattice in the presence of an external mag

J. Méndez-Abreu, S. F. Sánchez, A. de Lorenzo-Cáceres

Galaxies are complex systems made up of different structural components such as bulges, discs, and bars. Understanding galaxy evolution requires unveiling, independently, their history of stellar mass and metallicity assembly. We introduce C2D, a new algorithm to perform spectro-photometric multi-component decompositions of integral field spectroscopy (IFS)

Andi Hektor, Andrzej Hryczuk, Kristjan Kannike

We reconsider complex scalar singlet dark matter stabilised by a $\mathbb{Z}_{3}$ symmetry. We refine the stability bounds on the potential and use constraints from unitarity on scattering at finite energy to place a stronger lower limit on the direct detection cross section. In addition, we improve the treatment of the thermal freeze-out by including the ev

R. Allart, V. Bourrier, C. Lovis, D. Ehrenreich

Probing the evaporation of exoplanet atmospheres is key to understanding the formation and evolution of exoplanetary systems. The main tracer of evaporation in the UV is the Lyman-alpha transition, which can reveal extended exospheres. Recently, NIR metastable helium triplet (1.08 microns) revealed extended thermospheres in several exoplanets, opening a new

T. J. L. de Boer, M. Gieles, E. Balbinot, V. Henault-Brunet

Using data from Gaia DR2, we study the radial number density profiles of the Galactic globular cluster sample. Proper motions are used for accurate membership selection, especially crucial in the cluster outskirts. Due to the severe crowding in the centres, the Gaia data is supplemented by literature data from HST and surface brightness measurements, where a

Arne L. Grimsmo, Joshua Combes, Ben Q. Baragiola

Bosonic rotation codes, introduced here, are a broad class of bosonic error-correcting codes based on phase-space rotation symmetry. We present a universal quantum computing scheme applicable to a subset of this class--number-phase codes--which includes the well-known cat and binomial codes, among many others. The entangling gate in our scheme is code-agnost

Lucas Lombriser

An additional variation of the Einstein-Hilbert action with respect to the Planck mass provides a constraint on the average Ricci scalar that prevents vacuum energy from gravitating. Consideration of the evolution of the inhomogeneous matter distribution in the Universe with evaluation of the averaging constraint on disconnected matter cells that ultimately

Amartya Mitra, Michael Mulligan

We study theoretically the magnetoresistance oscillations near a half-filled lowest Landau level ($\nu = 1/2$) that result from the presence of a periodic one-dimensional electrostatic potential. We use the Dirac composite fermion theory of Son [Phys. Rev. X 5 031027 (2015)], where the $\nu=1/2$ state is described by a $(2+1)$-dimensional theory of quantum e

Jacob C. Bridgeman, Daniel Barter

A domain wall structure consists of a planar graph with faces labeled by fusion categories/topological phases. Edges are labeled by bimodules/domain walls. When the vertices are labeled by point defects we get a compound defect. We present an algorithm, called the domain wall structure algorithm, for computing the compound defect. We apply this algorithm to

Ignacio Martin-Navarro, Aaron J. Romanowsky, Jean P. Brodie, Anna Ferre-Mateu

Ultra diffuse galaxies are a population of extended galaxies but with relatively low luminosities. The origin of these objects remains unclear, largely due to the observational challenges of the low surface brightness Universe. We present here a detailed stellar population analysis of a relatively isolated UDG, DGSAT I, based on spectroscopic data from the K

Ajit C. Balram, Karsten Flensberg, Jens Paaske, Mark S. Rudner

Two-dimensional topological insulators (TIs) host gapless helical edge states that are predicted to support a quantized two-terminal conductance. Quantization is protected by time-reversal symmetry, which forbids elastic backscattering. Paradoxically, the current-carrying state itself breaks the time-reversal symmetry that protects it. Here we show that the

C. S. Anderson, S. P. O'Sullivan, G. H. Heald, T. Hodgson

We investigate the previously proposed possibility that multi-epoch broadband polarimetry could act as a complement or limited proxy for VLBI observations of blazars, in that the number of polarised emission components in the jet, and some of their properties and those of the foreground environment, might be inferred from the object's time-varying 1D Faraday

Seung-Joo Lee, Wolfgang Lerche, Timo Weigand

We analyse the Weak Gravity Conjecture for chiral four-dimensional F-theory compactifications with N=1 supersymmetry. Extending our previous work on nearly tensionless heterotic strings in six dimensions, we show that under certain assumptions a tower of asymptotically massless states arises in the limit of vanishing coupling of a U(1) gauge symmetry coupled

David Liptai, Daniel J. Price

We present a method for general relativistic smoothed particle hydrodynamics (GRSPH), based on an entropy-conservative form of the general relativistic hydrodynamic equations for a perfect fluid. We aim to replace approximate treatments of general relativity in current SPH simulations of tidal disruption events and accretion discs. We develop an improved sho

Svea Hernandez, Søren Larsen, Alessandra Aloisi, Danielle A. Berg

Stellar populations are powerful tools for investigating the evolution of extragalactic environments. We present the first UV integrated-light spectroscopic observations for 15 young star clusters in the starburst M83 with a special focus on metallicity measurements. The data were obtained with the Cosmic Origins Spectrograph (COS) onboard the Hubble Space T

William J. Fischer, Emily Safron, S. Thomas Megeath

Outbursts due to dramatic increases in the mass accretion rate are the most extreme type of variability in young stellar objects. We searched for outbursts among 319 protostars in the Orion molecular clouds by comparing 3.6, 4.5, and 24 micron photometry from the Spitzer Space Telescope to 3.4, 4.6, and 22 micron photometry from the Wide-field Infrared Surve

Benjamin J. Brown, Dominic J. Williamson

Fracton topological phases have a large number of materialized symmetries that enforce a rigid structure on their excitations. Remarkably, we find that the symmetries of a quantum error-correcting code based on a fracton phase enable us to design decoding algorithms. Here we propose and implement decoding algorithms for the three-dimensional X-cube model. In

Qi-Bo Zeng, Yan-Bin Yang, Yong Xu

Topological phases have recently witnessed a rapid progress in non-Hermitian systems. Here we study a one-dimensional non-Hermitian Aubry-Andr\'e-Harper model with imaginary periodic or quasiperiodic modulations. We demonstrate that the non-Hermitian off-diagonal AAH models can host zero-energy modes at the edges. In contrast to the Hermitian case, the zero-

Alexis Nikolakopoulos, Natalie Jachowicz, Nils Van Dessel, Kajetan Niewczas

Differences between $\nu_e$ and $\nu_{\mu}$ quasielastic cross sections are essential in neutrino oscillation analyses and CP violation searches for experiments such as DUNE and T2HK. The ratio of these is however poorly known experimentally and for certain kinematic regions theoretical models give contradictory answers. We use two independent mean-field bas

Kanwar Bharat Singh, Saied Taheri

Tire mounted sensors are emerging as a promising technology, capable of providing information about important tire states. This paper presents a survey of the state-of-the-art in the field of smart tire technology, with a special focus on the different signal processing techniques proposed by researchers to estimate the tire load and slip angle using tire mo

C. Dalfó, M. A. Fiol

It is well known that, in general, part of the spectrum of a graph can be obtained from the adjacency matrix of its quotient graph given by a regular partition. In this paper, we propose a method to obtain all the spectrum, and also the local spectra, of a graph $\Gamma$ from the quotient matrices of some of its regular partitions. As examples, it is shown h

Vicente Leyton-Ortega, Alejandro Perdomo-Ortiz, Oscar Perdomo

Although the performance of hybrid quantum-classical algorithms is highly dependent on the selection of the classical optimizer and the circuit ansatz, a robust and thorough assessment on-hardware of such features has been missing to date. From the optimizer perspective, the primary challenge lies in the solver's stochastic nature, and their significant vari

Rafael Ponte

The goal of this article is to study minimal surfaces in $\mathbb{M}^2 \times \mathbb{R}$ having finite total curvature, where $\mathbb{M}^2$ is a Hadamard manifold. The main result gives a formula to compute the total curvature in terms of topological, geometrical and conformal data of the minimal surface. In particular, we prove the total curvature is an i

Viktor Yanush, Dmitry Kropotov

We consider the problem of sampling from posterior distributions for Bayesian models where some parameters are restricted to be orthogonal matrices. Such matrices are sometimes used in neural networks models for reasons of regularization and stabilization of training procedures, and also can parameterize matrices of bounded rank, positive-definite matrices a

Shumon Koga, Delphine Bresch-Pietri, Miroslav Krstic

This paper presents a control design for the one-phase Stefan problem under actuator delay via a backstepping method. The Stefan problem represents a liquid-solid phase change phenomenon which describes the time evolution of a material's temperature profile and the interface position. The actuator delay is modeled by a first-order hyperbolic partial differen

Gerd Röpke

The Mott effect describes the dissolution of bound states in a dense partially ionized plasma. It happens when the ionization potential depression, owing to effects of correlation and degeneracy, compensates the binding energy of the bound state. At high densities and moderate temperatures, the Pauli blocking becomes important and influences significantly th

Xingyi Zhou, Jiacheng Zhuo, Philipp Krähenbühl

With the advent of deep learning, object detection drifted from a bottom-up to a top-down recognition problem. State of the art algorithms enumerate a near-exhaustive list of object locations and classify each into: object or not. In this paper, we show that bottom-up approaches still perform competitively. We detect four extreme points (top-most, left-most,

Ani Nersisyan, Stefano Poletto, Nasser Alidoust, Riccardo Manenti

Enabling applications for solid state quantum technology will require systematically reducing noise, particularly dissipation, in these systems. Yet, when multiple decay channels are present in a system with similar weight, resolution to distinguish relatively small changes is necessary to infer improvements to noise levels. For superconducting qubits, uncon

Jaeyoung Park, Giovanni Lapenta, Diego Gonzalez-Herrero, Nicholas Krall

In the Earth magnetosphere, sunspots and magnetic cusp fusion devices, the boundary between the plasma and the magnetic field is marked by a diamagnetic current layer with a rapid change in plasma pressure and magnetic field strength. First principles numerical simulations were conducted to investigate this boundary layer with a spatial resolution beyond ele

The Pierre Auger Collaboration, A. Aab, P. Abreu, M. Aglietta

The determination of the primary energy of extensive air showers using the fluorescence detection technique requires an estimation of the energy carried away by particles that do not deposit all their energy in the atmosphere. This estimation is typically made using Monte Carlo simulations and thus depends on the assumed primary particle mass and on model pr

B. Müller, M. Karrer, F. Limberger, M. Becker

By scanning with a $30\, \mathrm{keV}$ focused He ion beam (He-FIB) across YBa$_2$Cu$_3$O$_7$ (YBCO) thin film microbridges, we create Josephson barriers with critical current density $j_\mathrm{c}$ adjustable by irradiation dose $D$. The dependence $j_\mathrm{c} (D)$ yields an exponential decay. At $4.2\, \mathrm{K}$, a transition from flux-flow to Josephso

Theodore Erler, Carlo Maccaferri, Ruggero Noris

Motivated by the appearance of associativity anomalies in the context of superstring field theory, we give a generalized solution built from boundary condition changing operators which can be associated to a generic tachyon vacuum in the $KBc$ subalgebra of the Okawa form. We articulate sufficient conditions on the choice of tachyon vacuum to ensure that amb

Ulrike Riess

We approach non-divisorial base loci of big and nef line bundles on irreducible symplectic varieties. While for K3 surfaces, only divisorial base loci can occur, nothing was known about the behaviour of non-divisorial base loci for more general irreducible symplectic varieties. We determine the base loci of all big and nef line bundles on the Hilbert scheme

Michal Mackiewicz, Hans Jakob Rivertz, Graham D. Finlayson

In this paper, we propose two methods of calculating theoretically maximal metamer mismatch volumes. Unlike prior art techniques, our methods do not make any assumptions on the shape of spectra on the boundary of the mismatch volumes. Both methods utilize a spherical sampling approach, but they calculate mismatch volumes in two different ways. The first meth

Yipeng Li, Xinglin Zhao, Navamita Ray, Xiangmin Jiao

High-order surface reconstruction is an important technique for CAD-free, mesh-based geometric and physical modeling, and for high-order numerical methods for solving partial differential equations (PDEs) in engineering applications. In this paper, we introduce a novel method for accurate and robust reconstructions of piecewise smooth surfaces from a triangu

Sabrina S. Hong, Alexander T. Papageorge, Prasahnt Sivarajah, Genya Crossman

In state-of-the-art quantum computing platforms, including superconducting qubits and trapped ions, imperfections in the 2-qubit entangling gates are the dominant contributions of error to system-wide performance. Recently, a novel 2-qubit parametric gate was proposed and demonstrated with superconducting transmon qubits. This gate is activated through RF mo

F. Gómez-Cubillo, S. Villullas

Wavelet frames for $L^2({\mathbb R})$ can be characterized by means of spectral techniques. This work uses spectral formulas to determine all the tight wavelet frames for $L^2({\mathbb R})$ with a fixed finite number of generators of minimal support. The method associates wavelet frames of this type with certain inner operator-valued functions in Hardy space

Zur Izhakian

This paper lays out a foundation for a theory of supertropical algebraic geometry, relying on commutative $\nu$-algebra. To this end, the paper introduces $\mathfrak{q}$-congruences, carried over $\nu$-semirings, whose distinguished ghost and tangible clusters allow both quotienting and localization. Utilizing these clusters, $\mathfrak{g}$-prime, $\mathfrak

B. Barrios, A. Quaas

We will consider the nonlocal H\'enon equation $$(-\Delta)^s u= |x|^{\alpha} u^{p},\quad \mathbb{R}^{N},$$ where $(-\Delta)^s$ is the fractional Laplacian operator with $0<s<1$, $-2s<\alpha$, $p>1$ and $N>2s$. We prove a nonexistence result for positive solutions in the optimal range of the nonlinearity, that is, when $$1<p<p^*_{\alpha, s}:=\frac{N+2\alpha+2

Yang-Ting Chien

In the first talk I discuss the usefulness of jet grooming for testing jet quenching mechanisms, and I present a calculation of soft-drop jet mass distribution in proton-proton and heavy ion collisions. In the second talk I discuss the comprehensive studies of quark and gluon jet substructure as a way to search for qualitatively new jet modification signatur

Thomas Löhr, Carlo Camilloni, Massimiliano Bonomi, Michele Vendruscolo

Accurate protein structural ensembles can be determined with metainference, a Bayesian inference method that integrates experimental information with prior knowledge of the system and deals with all sources of uncertainty and errors as well as with system heterogeneity. Furthermore, metainference can be implemented using the metadynamics approach, which enab

Goran Radanovic, Rati Devidze, David C. Parkes, Adish Singla

We consider a two-agent MDP framework where agents repeatedly solve a task in a collaborative setting. We study the problem of designing a learning algorithm for the first agent (A1) that facilitates a successful collaboration even in cases when the second agent (A2) is adapting its policy in an unknown way. The key challenge in our setting is that the first

Andrea Bianchi

We consider the Birman-Hilden inclusion $\varphi\colon\mathfrak{Br}_{2g+1}\to\Gamma_{g,1}$ of the braid group into the mapping class group of an orientable surface with boundary, and prove that $\varphi$ is stably trivial in homology with twisted coefficients in the symplectic representation $H_1(\Sigma_{g,1})$ of the mapping class group; this generalises a

Tobias Ekholm, Vivek Shende

We study 1-parameter families of holomorphic curves with Lagrangian boundary in Calabi-Yau 3-folds. We show that the expected codimension one phenomena can be organized to match the HOMFLYPT skein relations from quantum topology. It follows that counting holomorphic curves by the class of their boundaries in the skein module of the Lagrangian gives a deforma

Suman Kumar Sahoo, Manmohan Vashisth

In this article, we study the unique determination of convection term and the time-dependent density coefficient appearing in a convection-diffusion equation from partial Dirichlet to Neumann map measured on boundary.

Dipjyoti Paul, Md Sahidullah, Goutam Saha

Voice-based biometric systems are highly prone to spoofing attacks. Recently, various countermeasures have been developed for detecting different kinds of attacks such as replay, speech synthesis (SS) and voice conversion (VC). Most of the existing studies are conducted with a specific training set defined by the evaluation protocol. However, for realistic s

F. Gómez-Cubillo, S. Villullas

This work characterizes (dyadic) wavelet frames for $L^2({\mathbb R})$ by means of spectral techniques. These techniques use decomposability properties of the frame operator in spectral representations associated to the dilation operator. The approach is closely related to usual Fourier domain fiberization techniques, dual Gramian analysis and extension prin