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arxiv_dataset-95001802.1046
Characteristics of type III radio bursts and solar S bursts astro-ph.SR The Sun is an active source of radio emission which is often associated with the acceleration of electrons arising from processes such as solar flares and coronal mass ejections (CMEs). At low radio frequencies (<100 MHz), numerous solar S bursts (where S stands for short) and storms of Type III radio bursts have been observed, that are not directly relates to flares and CMEs. Here, we expand our understanding on the spectral characteristic of these two different types of radio bursts based on observations from the Low Frequency Array (LOFAR). On 9 July 2013, over 3000 solar S bursts accompanied by over 800 Type III radio bursts were observed over a time period of ~8 hours. The characteristics of Type III radio bursts are consistent to previous studies, while S bursts show narrow bandwidths, durations and drift rates of about 1/2 the drift rate of Type III bursts. Type III bursts and solar S bursts occur in a region in the corona where plasma emission is the dominant emission mechanism as determined by data constrained density and magnetic field models.
arxiv topic:astro-ph.SR
arxiv_dataset-95011802.1056
Novelty Detection with GAN cs.CV The ability of a classifier to recognize unknown inputs is important for many classification-based systems. We discuss the problem of simultaneous classification and novelty detection, i.e. determining whether an input is from the known set of classes and from which specific class, or from an unknown domain and does not belong to any of the known classes. We propose a method based on the Generative Adversarial Networks (GAN) framework. We show that a multi-class discriminator trained with a generator that generates samples from a mixture of nominal and novel data distributions is the optimal novelty detector. We approximate that generator with a mixture generator trained with the Feature Matching loss and empirically show that the proposed method outperforms conventional methods for novelty detection. Our findings demonstrate a simple, yet powerful new application of the GAN framework for the task of novelty detection.
arxiv topic:cs.CV
arxiv_dataset-95021803.00067
Constrained Classification and Ranking via Quantiles cs.LG stat.ML In most machine learning applications, classification accuracy is not the primary metric of interest. Binary classifiers which face class imbalance are often evaluated by the $F_\beta$ score, area under the precision-recall curve, Precision at K, and more. The maximization of many of these metrics can be expressed as a constrained optimization problem, where the constraint is a function of the classifier's predictions. In this paper we propose a novel framework for learning with constraints that can be expressed as a predicted positive rate (or negative rate) on a subset of the training data. We explicitly model the threshold at which a classifier must operate to satisfy the constraint, yielding a surrogate loss function which avoids the complexity of constrained optimization. The method is model-agnostic and only marginally more expensive than minimization of the unconstrained loss. Experiments on a variety of benchmarks show competitive performance relative to existing baselines.
arxiv topic:cs.LG stat.ML
arxiv_dataset-95031803.00167
From Octopus to Dendrite - Semiflexible Polyelectrolyte Brush Condensates in Trivalent Counterion Solution cond-mat.soft physics.bio-ph Interplay between counterion-mediated interaction and stiffness inherent to polymer chain can bring substantial complexity to the morphology and dynamics of polyelectrolyte brush condensates. Trivalent counterions induce collapse of flexible polyelectrolyte brushes, over a certain range of grafting density, into octopus-like surface micelles; however, if individual chains are rigid enough, the ion-mediated local nematic ordering assembles the brush chains into fractal-like dendritic condensates whose relaxation dynamics is significantly slower than that in the surface micelles. Notably, the trivalent ions condensed in the dendritic condensates are highly mobile displaying quasi-one-dimensional diffusion in parallel along the dendritic branches. Our findings in this study are potentially of great significance to understanding the response of cellular organization such as chromosomes and charged polysaccharides on membranes to the change in ionic environment.
arxiv topic:cond-mat.soft physics.bio-ph
arxiv_dataset-95041803.00267
A fresh look at the Semiparametric Cram\'{e}r-Rao Bound eess.SP This paper aims at providing a fresh look at semiparametric estimation theory and, in particular, at the Semiparametric Cram\'{e}r-Rao Bound (SCRB). Semiparametric models are characterized by a finite-dimensional parameter vector of interest and by an infinite-dimensional nuisance function that is often related to an unspecified functional form of the density of the noise underlying the observations. We summarize the main motivations and the intuitive concepts about semiparametric models. Then we provide a new look at the classical estimation theory based on a geometrical Hilbert space-based approach. Finally, the semiparametric version of the Cram\'{e}r-Rao Bound for the estimation of the finite-dimensional vector of the parameters of interest is provided.
arxiv topic:eess.SP
arxiv_dataset-95051803.00367
A Benchmark Problem in Transportation Networks cs.SY In this note, we propose a case study of freeway traffic flow modeled as a hybrid system. We describe two general classes of networks that model flow along a freeway with merging onramps. The admission rate of traffic flow from each onramp is metered via a control input. Both classes of networks are easily scaled to accommodate arbitrary state dimension. The model is discrete-time and possesses piecewise-affine dynamics. Moreover, we present several control objectives that are especially relevant for traffic flow management. The proposed model is flexible and extensible and offers a benchmark for evaluating tools and techniques developed for hybrid systems.
arxiv topic:cs.SY
arxiv_dataset-95061803.00467
Negacyclic codes over the local ring $\mathbb{Z}_4[v]/\langle v^2+2v\rangle$ of oddly even length and their Gray images cs.IT math.IT Let $R=\mathbb{Z}_{4}[v]/\langle v^2+2v\rangle=\mathbb{Z}_{4}+v\mathbb{Z}_{4}$ ($v^2=2v$) and $n$ be an odd positive integer. Then $R$ is a local non-principal ideal ring of $16$ elements and there is a $\mathbb{Z}_{4}$-linear Gray map from $R$ onto $\mathbb{Z}_{4}^2$ which preserves Lee distance and orthogonality. First, a canonical form decomposition and the structure for any negacyclic code over $R$ of length $2n$ are presented. From this decomposition, a complete classification of all these codes is obtained. Then the cardinality and the dual code for each of these codes are given, and self-dual negacyclic codes over $R$ of length $2n$ are presented. Moreover, all $23\cdot(4^p+5\cdot 2^p+9)^{\frac{2^{p}-2}{p}}$ negacyclic codes over $R$ of length $2M_p$ and all $3\cdot(4^p+5\cdot 2^p+9)^{\frac{2^{p-1}-1}{p}}$ self-dual codes among them are presented precisely, where $M_p=2^p-1$ is a Mersenne prime. Finally, $36$ new and good self-dual $2$-quasi-twisted linear codes over $\mathbb{Z}_4$ with basic parameters $(28,2^{28}, d_L=8,d_E=12)$ and of type $2^{14}4^7$ and basic parameters $(28,2^{28}, d_L=6,d_E=12)$ and of type $2^{16}4^6$ which are Gray images of self-dual negacyclic codes over $R$ of length $14$ are listed.
arxiv topic:cs.IT math.IT
arxiv_dataset-95071803.00567
Computational Optimal Transport stat.ML Optimal transport (OT) theory can be informally described using the words of the French mathematician Gaspard Monge (1746-1818): A worker with a shovel in hand has to move a large pile of sand lying on a construction site. The goal of the worker is to erect with all that sand a target pile with a prescribed shape (for example, that of a giant sand castle). Naturally, the worker wishes to minimize her total effort, quantified for instance as the total distance or time spent carrying shovelfuls of sand. Mathematicians interested in OT cast that problem as that of comparing two probability distributions, two different piles of sand of the same volume. They consider all of the many possible ways to morph, transport or reshape the first pile into the second, and associate a "global" cost to every such transport, using the "local" consideration of how much it costs to move a grain of sand from one place to another. Recent years have witnessed the spread of OT in several fields, thanks to the emergence of approximate solvers that can scale to sizes and dimensions that are relevant to data sciences. Thanks to this newfound scalability, OT is being increasingly used to unlock various problems in imaging sciences (such as color or texture processing), computer vision and graphics (for shape manipulation) or machine learning (for regression, classification and density fitting). This short book reviews OT with a bias toward numerical methods and their applications in data sciences, and sheds lights on the theoretical properties of OT that make it particularly useful for some of these applications.
arxiv topic:stat.ML
arxiv_dataset-95081803.00667
Can cut generating functions be good and efficient? math.OC Making cut generating functions (CGFs) computationally viable is a central question in modern integer programming research. One would like to find CGFs that are simultaneously good, i.e., there are good guarantees for the cutting planes they generate, and efficient, meaning that the values of the CGFs can be computed cheaply (with procedures that have some hope of being implemented in current solvers). We investigate in this paper to what extent this balance can be struck. We propose a family of CGFs which, in a sense, achieves this harmony between good and efficient. In particular, we provide a parameterized family of $b+\Z^n$ free sets to derive CGFs from and show that our proposed CGFs give a good approximation of the closure given by CGFs obtained from all maximal $b+\Z^n$ free sets and their so-called trivial liftings, and simultaneously, show that these CGFs can be computed with explicit, efficient procedures. We provide a constructive framework to identify these sets as well as computing their trivial lifting. We follow it up with computational experiments to demonstrate this and to evaluate their practical use. Our proposed family of cuts seem to give some tangible improvement on randomly generated instances compared to GMI cuts; however, in MIPLIB 3.0 instances, and vertex cover and stable problems on random graph instances, their performance is poor.
arxiv topic:math.OC
arxiv_dataset-95091803.00767
Black Hole Space-time In Dark Matter Halo gr-qc astro-ph.CO astro-ph.HE For the first time, we obtain the analytical form of black hole space-time metric in dark matter halo for the stationary situation. Using the relation between the rotation velocity (in the equatorial plane) and the spherical symmetric space-time metric coefficient, we obtain the space-time metric for pure dark matter. By considering the dark matter halo in spherical symmetric space-time as part of the energy-momentum tensors in the Einstein field equation, we then obtain the spherical symmetric black hole solutions in dark matter halo. Utilizing Newman-Jains method, we further generalize spherical symmetric black holes to rotational black holes. As examples, we obtain the space-time metric of black holes surrounded by Cold Dark Matter and Scalar Field Dark Matter halos, respectively. Our main results regarding the interaction between black hole and dark matter halo are as follows: (i) For both dark matter models, the density profile always produces "cusp" phenomenon in small scale in the relativity situation; (ii) Dark matter halo makes the black hole horizon to increase but the ergosphere to decrease, while the magnitude is small; (iii) Dark matter does not change the singularity of black holes. These results are useful to study the interaction of black hole and dark matter halo in stationary situation. Particularly, the "cusp" produced in the $0\sim 1$ kpc scale would be observable in the Milky Way. Perspectives on future work regarding the applications of our results in astrophysics are also briefly discussed.
arxiv topic:gr-qc astro-ph.CO astro-ph.HE
arxiv_dataset-95101803.00867
Probing vorticity structure in heavy-ion collisions by local $\Lambda$ polarization nucl-th hep-ph We study the local structure of the vorticity field and the $\Lambda$ polarization in Au+Au collisions in the energy range $\sqrt{s_{\mathrm{NN}}}=7.7$--$200$ GeV and Pb+Pb collisions at $\sqrt{s_{\mathrm{NN}}}=2760$ GeV using A Multi-Phase Transport (AMPT) model. We focus on the vorticity field arising from the non-uniform expansion of the fireball, which gives the circular structure of the transverse vorticity $\boldsymbol{\omega}_{\perp}=(\omega_{x},\omega_{y})$ around the $z$ direction as well as the quadrupole pattern of the longitudinal vorticity $\omega_{z}$ in the transverse plane. As a consequence, the three components of the polarization vector $\mathbf{P}=(P_{x},P_{y},P_{z})$ for $\Lambda$ hyperons show harmonic behaviors as $\mathrm{sgn}(Y)\sin\phi_{p}$, $-\mathrm{sgn}(Y)\cos\phi_{p}$, and $-\sin(2\phi_{p})$, where $\phi_{p}$ and $Y$ are the azimuthal angle and rapidity in momentum space. These patterns of the local $\Lambda$ polarization are expected to be tested in future experiments.
arxiv topic:nucl-th hep-ph
arxiv_dataset-95111803.00967
Active model learning and diverse action sampling for task and motion planning cs.RO cs.AI cs.LG stat.AP stat.ML The objective of this work is to augment the basic abilities of a robot by learning to use new sensorimotor primitives to enable the solution of complex long-horizon problems. Solving long-horizon problems in complex domains requires flexible generative planning that can combine primitive abilities in novel combinations to solve problems as they arise in the world. In order to plan to combine primitive actions, we must have models of the preconditions and effects of those actions: under what circumstances will executing this primitive achieve some particular effect in the world? We use, and develop novel improvements on, state-of-the-art methods for active learning and sampling. We use Gaussian process methods for learning the conditions of operator effectiveness from small numbers of expensive training examples collected by experimentation on a robot. We develop adaptive sampling methods for generating diverse elements of continuous sets (such as robot configurations and object poses) during planning for solving a new task, so that planning is as efficient as possible. We demonstrate these methods in an integrated system, combining newly learned models with an efficient continuous-space robot task and motion planner to learn to solve long horizon problems more efficiently than was previously possible.
arxiv topic:cs.RO cs.AI cs.LG stat.AP stat.ML
arxiv_dataset-95121803.01067
Improved Charge Transfer Multiplet Method to Simulate M- and L-Edge X-ray Absorption Spectra of Metal-Centered Excited States physics.chem-ph cond-mat.mtrl-sci Charge transfer multiplet (CTM) theory is a computationally undemanding and highly mature method for simulating the soft X-ray spectra of first-row transition metal complexes. However, CTM theory has seldom been applied to the simulation of excited state spectra. In this article, we extend the CTM4XAS software package to simulate M2,3- and L2,3-edge spectra of excited states of first-row transition metals and to interpret CTM eigenfunctions in terms of Russell-Saunders term symbols. We use these new programs to reinterpret the recently reported excited state M2,3-edge difference spectra of photogenerated ferrocenium cations and propose alternative assignments for the electronic state of the photogenerated ferrocenium cations supported by CTM theory simulations. We also use these new programs to model the L2,3-edge spectra of FeII compounds during nuclear relaxation following photoinduced spin crossover, and propose spectroscopic signatures for their vibrationally hot states
arxiv topic:physics.chem-ph cond-mat.mtrl-sci
arxiv_dataset-95131803.01167
Dissipative dynamics of an interacting spin system with collective damping quant-ph cond-mat.stat-mech The competition between Hamiltonian and Lindblad dynamics in quantum systems give rise to non-equillibrium phenomena with no counter part in conventional condensed matter physics. In this paper, we investigate this interplay of dynamics in infinite range Heisenberg model coupled to a non-Markovian bath and subjected to Lindblad dynamics due to spin flipping at a given site. The spin model is bosonized via Holstein-Primakoff transformations and is shown to be valid for narrow range of parameters in the thermodynamic limit. Using Schwinger-Keldysh technique, we derive mean field solution of the model and observe that the system breaks $\mathcal{Z}_2$-symmetry at the transition point. We calculate effective temperature that has linear dependence on the effective system-bath coupling, and is independent of the dissipation rate and cutoff frequency of the bath spectral density. Furthermore, we study the fluctuations over mean field and show that the dissipative spectrum is modified by ${\rm O}(\frac{1}{N})$ correction term which results change in various physically measurable quantities.
arxiv topic:quant-ph cond-mat.stat-mech
arxiv_dataset-95141803.01267
Laplacians on spheres math.RT Spheres can be written as homogeneous spaces $G/H$ for compact Lie groups in a small number of ways. In each case, the decomposition of $L^2(G/H)$ into irreducible representations of $G$ contains interesting information. We recall these decompositions, and see what they can reveal about the analogous problem for noncompact real forms of $G$ and $H$.
arxiv topic:math.RT
arxiv_dataset-95151803.01367
Wafer-scale fabrication and room-temperature experiments on graphene-based gates for quantum computation cond-mat.mes-hall quant-ph We have fabricated at wafer scale graphene-based configurations suitable for implementing at room temperature one-qubit quantum gates and a modified Deutsch-Jozsa algorithm. Our measurements confirmed the (quasi-)ballistic nature of charge carrier propagation through both types of devices, which have dimensions smaller than the room-temperature mean-free-path in graphene. As such, both graphene-based configurations were found to be suitable for quantum computation. These results are encouraging for demonstrating a miniaturized, room-temperature quantum computer based on graphene.
arxiv topic:cond-mat.mes-hall quant-ph
arxiv_dataset-95161803.01467
The Sequent Calculus Trainer with Automated Reasoning - Helping Students to Find Proofs cs.LO cs.CY The sequent calculus is a formalism for proving validity of statements formulated in First-Order Logic. It is routinely used in computer science modules on mathematical logic. Formal proofs in the sequent calculus are finite trees obtained by successively applying proof rules to formulas, thus simplifying them step-by-step. Students often struggle with the mathematical formalities and the level of abstraction that topics like formal logic and formal proofs involve. The difficulties can be categorised as syntactic or semantic. On the syntactic level, students need to understand what a correctly formed proof is, how rules can be applied (on paper for instance) without leaving the mathematical framework of the sequent calculus, and so on. Beyond this, on the semantic level, students need to acquire strategies that let them find the right proof. The Sequent Calculus Trainer is a tool that is designed to aid students in learning the techniques of proving given statements formally. In this paper we describe the didactical motivation behind the tool and the techniques used to address issues on the syntactic as well as on the semantic level.
arxiv topic:cs.LO cs.CY
arxiv_dataset-95171803.01567
Controlled Film Flow in Granulation of Metals for the Development of Amorphous Superhard and Functionally Unique New Materials physics.app-ph The problem of granulation is very bright by the granulated materials, as well as by their application. In the paper, some history of the granulation problem during over century and modern applications of the metallic granulates and amorphous materials are given at the beginning. Then the specific own granulation problem is presented, which has concern to the controlled liquid metal jet and film flows for a production of the uniform by size and form particles (granules) cooled with a high rate, to be amorphous or close to the amorphous materials. Such granules of the given size and form are needed for the new material science. The basics of developed theory of the controlled jet and film flow disintegration with further rapid cooling of the drops obtained after flow disintegration are presented together with the new patented granulation devices. The developed methods and devices can be used for production of the amorphous or close to amorphous granules in a wide range of the given sizes, with very narrow (plus-minus 50% deviation of size from the average one).
arxiv topic:physics.app-ph
arxiv_dataset-95181803.01667
The high voltage system for the novel MPGD-based photon detectors of COMPASS RICH-1 physics.ins-det hep-ex nucl-ex The architecture of the novel MPGD-based photon detectors of COMPASS RICH-1 consists in a large-size hybrid MPGD multilayer layout combining two layers of Thick-GEMs and a bulk resistive MICROMEGAS. Concerning biasing voltage, the Thick-GEMs are segmented in order to reduce the energy released in case of occasional discharges, while the MICROMEGAS anode is segmented in pads individually biased at positive voltage, while the micromesh is grounded. In total, there are ten different electrode types and more than 20000 electrodes supplied by more than 100 HV channels. Commercial power supply units are used. The original elements of the power supply system are the architecture of the voltage distribution net, the compensation, by voltage adjustment, of the effects of pressure and temperature variation affecting the detector gain and a sophisticated control software, which allows to protect the detectors against errors by the operator, to monitor and log voltages and current at 1 Hz rate and to automatically react to detector misbehaviors. The HV system and its performance are described in detail as well as the electrical stability of the detector during the operation at COMPASS.
arxiv topic:physics.ins-det hep-ex nucl-ex
arxiv_dataset-95191803.01767
Mutation and selection in bacteria: modelling and calibration q-bio.PE math.PR q-bio.QM Temporal evolution of a clonal bacterial population is modelled taking into account reversible mutation and selection mechanisms. For the mutation model, an efficient algorithm is proposed to verify whether experimental data can be explained by this model. The selection-mutation model has unobservable fitness parameters and, to estimate them, we use an Approximate Bayesian Computation (ABC) algorithm. The algorithms are illustrated using in vitro data for phase variable genes of Campylobacter jejuni.
arxiv topic:q-bio.PE math.PR q-bio.QM
arxiv_dataset-95201803.01867
Relativistic Quantum Optics: On the relativistic invariance of the light-matter interaction models quant-ph gr-qc hep-th In this note we discuss the invariance under general changes of reference frame of all the physical predictions of particle detector models in quantum field theory in general and, in particular, of those used in quantum optics to model atoms interacting with light. We find explicitly how the light-matter interaction Hamiltonians change under general coordinate transformations, and analyze the subtleties of the Hamiltonians commonly used to describe the light-matter interaction when relativistic motion is taken into account.
arxiv topic:quant-ph gr-qc hep-th
arxiv_dataset-95211803.01967
Learning Scene Gist with Convolutional Neural Networks to Improve Object Recognition cs.CV Advancements in convolutional neural networks (CNNs) have made significant strides toward achieving high performance levels on multiple object recognition tasks. While some approaches utilize information from the entire scene to propose regions of interest, the task of interpreting a particular region or object is still performed independently of other objects and features in the image. Here we demonstrate that a scene's 'gist' can significantly contribute to how well humans can recognize objects. These findings are consistent with the notion that humans foveate on an object and incorporate information from the periphery to aid in recognition. We use a biologically inspired two-part convolutional neural network ('GistNet') that models the fovea and periphery to provide a proof-of-principle demonstration that computational object recognition can significantly benefit from the gist of the scene as contextual information. Our model yields accuracy improvements of up to 50% in certain object categories when incorporating contextual gist, while only increasing the original model size by 5%. This proposed model mirrors our intuition about how the human visual system recognizes objects, suggesting specific biologically plausible constraints to improve machine vision and building initial steps towards the challenge of scene understanding.
arxiv topic:cs.CV
arxiv_dataset-95221803.02067
On cycles of pairing-friendly elliptic curves math.NT math.AG A cycle of elliptic curves is a list of elliptic curves over finite fields such that the number of points on one curve is equal to the size of the field of definition of the next, in a cyclic way. We study cycles of elliptic curves in which every curve is pairing-friendly. These have recently found notable applications in pairing-based cryptography, for instance in improving the scalability of distributed ledger technologies. We construct a new cycle of length 4 consisting of MNT curves, and characterize all the possibilities for cycles consisting of MNT curves. We rule out cycles of length 2 for particular choices of small embedding degrees. We show that long cycles cannot be constructed from families of curves with the same complex multiplication discriminant, and that cycles of composite order elliptic curves cannot exist. We show that there are no cycles consisting of curves from only the Freeman or Barreto--Naehrig families.
arxiv topic:math.NT math.AG
arxiv_dataset-95231803.02167
Dissipation induced $W$ state in a Rydberg-atom-cavity system quant-ph A dissipative scheme is proposed to prepare tripartite $W$ state in a Rydberg-atom-cavity system. It is an organic combination of quantum Zeno dynamics, Rydberg antiblockade and atomic spontaneous emission to turn the tripartite $W$ state into the unique steady state of the whole system. The robustness against the loss of cavity and the feasibility of the scheme are demonstrated thoroughly by the current experimental parameters, which leads to a high fidelity above $98\%$.
arxiv topic:quant-ph
arxiv_dataset-95241803.02267
An overview of $\Lambda_c$ decays hep-ph hep-ex The decays of the ground-state charmed baryon $\Lambda_c$ are now close to being completely mapped out. In this paper we discuss some remaining open questions, whose answers can help shed light on weak processes contributing to those decays, on calculations of such quantities as transition form factors in lattice QCD, and on missing decay modes such as $\Lambda_c \to \Lambda^* \ell^+ \nu_\ell$, where $\Lambda^*$ is an excited resonance. The discussion is in part a counterpart to a previous analysis of inclusive $D_s$ decays.
arxiv topic:hep-ph hep-ex
arxiv_dataset-95251803.02367
Evidence for a Variable Ultrafast Outflow in the Newly Discovered Ultraluminous Pulsar NGC 300 ULX-1 astro-ph.HE Ultraluminous pulsars are a definite proof that persistent super-Eddington accretion occurs in nature. They support the scenario according to which most Ultraluminous X-ray Sources (ULXs) are super-Eddington accretors of stellar mass rather than sub-Eddington intermediate mass black holes. An important prediction of theories of supercritical accretion is the existence of powerful outflows of moderately ionized gas at mildly relativistic speeds. In practice, the spectral resolution of X-ray gratings such as RGS onboard XMM-Newton is required to resolve their observational signatures in ULXs. Using RGS, outflows have been discovered in the spectra of 3 ULXs (none of which are currently known to be pulsars). Most recently, the fourth ultraluminous pulsar was discovered in NGC 300. Here we report detection of an ultrafast outflow (UFO) in the X-ray spectrum of the object, with a significance of more than 3{\sigma}, during one of the two simultaneous observations of the source by XMM-Newton and NuSTAR in December 2016. The outflow has a projected velocity of 65000 km/s (0.22c) and a high ionisation factor with a log value of 3.9. This is the first direct evidence for a UFO in a neutron star ULX and also the first time that this its evidence in a ULX spectrum is seen in both soft and hard X-ray data simultaneously. We find no evidence of the UFO during the other observation of the object, which could be explained by either clumpy nature of the absorber or a slight change in our viewing angle of the accretion flow.
arxiv topic:astro-ph.HE
arxiv_dataset-95261803.02467
A $q$-analogue for Euler's evaluations of the Riemann zeta function math.NT We provide a $q$-analogue of Euler's formula for $\zeta(2k)$ for $k\in\mathbb{Z}^+$. Our main results are stated in Theorems 3.1 and 3.2 below. The result generalizes a recent result of Z.W. Sun who obtained $q$-analogues of $\zeta(2)=\pi^2/6$ and $\zeta(4)=\pi^4/90$.
arxiv topic:math.NT
arxiv_dataset-95271803.02567
On two-spectra inverse problems math.SP math-ph math.CA math.FA math.MP We consider a two-spectra inverse problem for the one-dimensional Schr\"{o}dinger equation with boundary conditions containing rational Herglotz--Nevanlinna functions of the eigenvalue parameter and provide a complete solution of this problem.
arxiv topic:math.SP math-ph math.CA math.FA math.MP
arxiv_dataset-95281803.02667
A limit theorem for the six-length of random functional graphs with a fixed degree sequence math.CO We obtain results on the limiting distribution of the six-length of a random functional graph, also called a functional digraph or random mapping, with given in-degree sequence. The six-length of a vertex $v\in V$ is defined from the associated mapping, $f:V\to V$, to be the maximum $i\in V$ such that the elements $v, f(v), \ldots, f^{i-1}(v)$ are all distinct. This has relevance to the study of algorithms for integer factorisation.
arxiv topic:math.CO
arxiv_dataset-95291803.02767
Babenko's equation for periodic gravity waves on water of finite depth: derivation and numerical solution math.AP math-ph math.MP The nonlinear two-dimensional problem, describing periodic steady waves on water of finite depth is considered in the absence of surface tension. It is reduced to a single pseudo-differential operator equation (Babenko's equation), which is investigated analytically and numerically. This equation has the same form as the equation for waves on infinitely deep water; the latter had been proposed by Babenko and studied in detail by Buffoni, Dancer and Toland. Instead of the $2 \pi$-periodic Hilbert transform $\mathcal{C}$ used in the equation for deep water, the equation obtained here contains a certain operator $\mathcal{B}_r$, which is the sum of $\mathcal{C}$ and a compact operator whose dependence on the parameter involves on the depth of water. Numerical computations are based on an equivalent form of Babenko's equation derived by virtue of the spectral decomposition of the operator $\mathcal{B}_r \D / \D t$. Bifurcation curves and wave profiles of the extreme form are obtained numerically.
arxiv topic:math.AP math-ph math.MP
arxiv_dataset-95301803.02867
Phase transitions for a model with uncountable spin space on the Cayley tree: the general case math.PR In this paper we complete the analysis of a statistical mechanics model on Cayley trees of any degree, started in [EsHaRo12,EsRo10,BoEsRo13,JaKuBo14,Bo17]. The potential is of nearest-neighbor type and the local state space is compact but uncountable. Based on the system parameters we prove existence of a critical value $\theta_{\rm c}$ such that for $\theta\le \theta_{\rm c}$ there is a unique translation-invariant splitting Gibbs measure. For $\theta_{\rm c}<\theta$ there is a phase transition with exactly three translation-invariant splitting Gibbs measures. The proof rests on an analysis of fixed points of an associated non-linear Hammerstein integral operator for the boundary laws.
arxiv topic:math.PR
arxiv_dataset-95311803.02967
Decomposition of Nonlinear Dynamical Networks via Comparison Systems math.DS math.OC In analysis and control of large-scale nonlinear dynamical systems, a distributed approach is often an attractive option due to its computational tractability and usually low communication requirements. Success of the distributed control design relies on the separability of the network into weakly interacting subsystems such that minimal information exchange between subsystems is sufficient to achieve satisfactory control performance. While distributed analysis and control design for dynamical network have been well studied, decomposition of nonlinear networks into weakly interacting subsystems has not received as much attention. In this article we propose a vector Lyapunov functions based approach to quantify the energy-flow in a dynamical network via a model of a comparison system. Introducing a notion of power and energy flow in a dynamical network, we use sum-of-squares programming tools to partition polynomial networks into weakly interacting subsystems. Examples are provided to illustrate the proposed method of decomposition.
arxiv topic:math.DS math.OC
arxiv_dataset-95321803.03067
Compositional Attention Networks for Machine Reasoning cs.AI We present the MAC network, a novel fully differentiable neural network architecture, designed to facilitate explicit and expressive reasoning. MAC moves away from monolithic black-box neural architectures towards a design that encourages both transparency and versatility. The model approaches problems by decomposing them into a series of attention-based reasoning steps, each performed by a novel recurrent Memory, Attention, and Composition (MAC) cell that maintains a separation between control and memory. By stringing the cells together and imposing structural constraints that regulate their interaction, MAC effectively learns to perform iterative reasoning processes that are directly inferred from the data in an end-to-end approach. We demonstrate the model's strength, robustness and interpretability on the challenging CLEVR dataset for visual reasoning, achieving a new state-of-the-art 98.9% accuracy, halving the error rate of the previous best model. More importantly, we show that the model is computationally-efficient and data-efficient, in particular requiring 5x less data than existing models to achieve strong results.
arxiv topic:cs.AI
arxiv_dataset-95331803.03167
Physical explanation of the universal "inverse-3rd-power-of-separation" law found numerically for the electrostatic interaction between two protruding nanostructures cond-mat.mes-hall Two conducting nanostructures on a conducting base-plate, and with a common applied electrostatic field, interact because their electrons are a common electron-thermodynamic system. Except at small separations, the interaction reduces the apex field enhancement factor (FEF) of each nanostructure, by means of "charge blunting". A parameter of interest is the fractional reduction (-d) of the apex FEF, as compared with the apex FEF for the same emitter when standing alone on the base-plate. For systems of two or a few identical post-like emitters, or regular arrays of such emitters, details have been investigated by methods based on numerical solution of Laplace's equation, and by using line-charge models. For post separations c comparable with post height h, several authors have shown that the variation of (-d) with c is well described by formulae having exponential or quasi-exponential form. By contrast, explorations of the two-emitter situation using the "floating-sphere-at-emitter-plane potential" (FSEPP) model have predicted that, for large c-values, (-d) falls off as 1/c*c*c. Numerical Laplace-type simulations carried out by de Assis and Dall'Agnol (arXiv:1711.00601v2) have confirmed this limiting dependence for six different situations involving pairs of protruding nanostructures; hence they suggest it as an universal law. By using the FSEPP model for the central structure, and by adopting a "first moments" representation for the distant structure, this letter shows that a clear physical reason can be given for this numerically discovered general limiting (1/c*c*c) dependence. An implication is that the quasi-exponential formula found useful for c comparable with h is simply a good fitting formula. A second implication is that the FSEPP model, which currently is used mainly in nanoscience, may have much wider applicability to electrostatic phenomena.
arxiv topic:cond-mat.mes-hall
arxiv_dataset-95341803.03267
Resonating valence bonds and spinon pairing in the Dicke model quant-ph cond-mat.supr-con Resonating valence bond (RVB) states are a class of entangled quantum many body wavefunctions with great significance in condensed matter physics. We propose a scheme to synthesize a family of RVB states using a cavity QED setup with two-level atoms (with states $\vert 0 \rangle$ and $\vert 1 \rangle$) coupled to a common photon mode. In the lossy cavity limit, starting with an initial state of $M$ atoms excited and $N$ atoms in the ground state, we show that this setup can be configured as a Stern Gerlach experiment. A measurement of photon emission collapses the wavefunction of atoms onto an RVB state composed of resonating long-ranged singlets of the form $\frac{1}{\sqrt{2}}[\vert 0 1 \rangle - \vert 1 0 \rangle]$. Each emitted photon reduces the number of singlets by unity, replacing it with a pair of lone spins or `spinons'. As spinons are formed coherently in pairs, they are analogous to Cooper pairs in a superconductor. To simulate pair fluctuations, we propose a protocol in which photons are allowed to escape the cavity undetected. This leads to a mixed quantum state with a fluctuating number of spinon pairs -- an inchoate superconductor. Remarkably, in the limit of large system sizes, this protocol reveals an underlying quantum phase transition. Upon tuning the initial spin polarization ($M-N$), the emission exhibits a continuous transition from a dark state to a bright state. This is reflected in the spinon pair number distribution which can be tuned from sub-poissonian to super-poissonian regimes. This opens an exciting route to simulate RVB states and superconductivity.
arxiv topic:quant-ph cond-mat.supr-con
arxiv_dataset-95351803.03367
NeuroStorm: Accelerating Brain Science Discovery in the Cloud q-bio.OT Neuroscientists are now able to acquire data at staggering rates across spatiotemporal scales. However, our ability to capitalize on existing datasets, tools, and intellectual capacities is hampered by technical challenges. The key barriers to accelerating scientific discovery correspond to the FAIR data principles: findability, global access to data, software interoperability, and reproducibility/re-usability. We conducted a hackathon dedicated to making strides in those steps. This manuscript is a technical report summarizing these achievements, and we hope serves as an example of the effectiveness of focused, deliberate hackathons towards the advancement of our quickly-evolving field.
arxiv topic:q-bio.OT
arxiv_dataset-95361803.03467
RippleNet: Propagating User Preferences on the Knowledge Graph for Recommender Systems cs.IR cs.LG stat.ML To address the sparsity and cold start problem of collaborative filtering, researchers usually make use of side information, such as social networks or item attributes, to improve recommendation performance. This paper considers the knowledge graph as the source of side information. To address the limitations of existing embedding-based and path-based methods for knowledge-graph-aware recommendation, we propose Ripple Network, an end-to-end framework that naturally incorporates the knowledge graph into recommender systems. Similar to actual ripples propagating on the surface of water, Ripple Network stimulates the propagation of user preferences over the set of knowledge entities by automatically and iteratively extending a user's potential interests along links in the knowledge graph. The multiple "ripples" activated by a user's historically clicked items are thus superposed to form the preference distribution of the user with respect to a candidate item, which could be used for predicting the final clicking probability. Through extensive experiments on real-world datasets, we demonstrate that Ripple Network achieves substantial gains in a variety of scenarios, including movie, book and news recommendation, over several state-of-the-art baselines.
arxiv topic:cs.IR cs.LG stat.ML
arxiv_dataset-95371803.03567
Review of Blockchain Technology and its Expectations: Case of the Energy Sector cs.CY This article suggests that the worldwide relevance of blockchain technology is motivated by the changes that it is expected to cause in: (i) the way that business is organised and (ii) regulated, as well as (iii) by the way that it changes the role of individuals within a society. The article presents an overview of the features of blockchain technology. It then takes a closer look into the developments within the energy sector across the world to gain a preliminary indication of whether the stated expectations are coming to reality. As a result of this review, we remain cautiously optimistic that blockchain technology could deliver the expected impact.
arxiv topic:cs.CY
arxiv_dataset-95381803.03667
Co-occurrence of the Benford-like and Zipf Laws Arising from the Texts Representing Human and Artificial Languages cs.CL physics.soc-ph stat.OT We demonstrate that large texts, representing human (English, Russian, Ukrainian) and artificial (C++, Java) languages, display quantitative patterns characterized by the Benford-like and Zipf laws. The frequency of a word following the Zipf law is inversely proportional to its rank, whereas the total numbers of a certain word appearing in the text generate the uneven Benford-like distribution of leading numbers. Excluding the most popular words essentially improves the correlation of actual textual data with the Zipfian distribution, whereas the Benford distribution of leading numbers (arising from the overall amount of a certain word) is insensitive to the same elimination procedure. The calculated values of the moduli of slopes of double logarithmical plots for artificial languages (C++, Java) are markedly larger than those for human ones.
arxiv topic:cs.CL physics.soc-ph stat.OT
arxiv_dataset-95391803.03767
Multi-Agent Submodular Optimization cs.DS Recent years have seen many algorithmic advances in the area of submodular optimization: (SO) $\min/\max~f(S): S \in \mathcal{F}$, where $\mathcal{F}$ is a given family of feasible sets over a ground set $V$ and $f:2^V \rightarrow \mathbb{R}$ is submodular. This progress has been coupled with a wealth of new applications for these models. Our focus is on a more general class of \emph{multi-agent submodular optimization} (MASO) which was introduced by Goel et al. in the minimization setting: $\min \sum_i f_i(S_i): S_1 \uplus S_2 \uplus \cdots \uplus S_k \in \mathcal{F}$. Here we use $\uplus$ to denote disjoint union and hence this model is attractive where resources are being allocated across $k$ agents, each with its own submodular cost function $f_i()$. In this paper we explore the extent to which the approximability of the multi-agent problems are linked to their single-agent {\em primitives}, referred to informally as the {\em multi-agent gap}. We present different reductions that transform a multi-agent problem into a single-agent one. For maximization we show that (MASO) admits an $O(\alpha)$-approximation whenever (SO) admits an $\alpha$-approximation over the multilinear formulation, and thus substantially expanding the family of tractable models. We also discuss several family classes (such as spanning trees, matroids, and $p$-systems) that have a provable multi-agent gap of 1. In the minimization setting we show that (MASO) has an $O(\alpha \cdot \min \{k, \log^2 (n)\})$-approximation whenever (SO) admits an $\alpha$-approximation over the convex formulation. In addition, we discuss the class of "bounded blocker" families where there is a provably tight O$(\log n)$ gap between (MASO) and (SO).
arxiv topic:cs.DS
arxiv_dataset-95401803.03867
Attosecond electronic recollision as field detector physics.optics We demonstrate the complete reconstruction of the electric field of visible-infrared pulses with energy as low as a few tens of nanojoules. The technique allows for the reconstruction of the instantaneous electric field vector direction and magnitude, thus giving access to the characterisation of pulses with an arbitrary time-dependent polarisation state. The technique combines extreme ultraviolet interferometry with the generation of isolated attosecond pulses.
arxiv topic:physics.optics
arxiv_dataset-95411803.03967
A multi-wavelength study of the evolution of Early-Type Galaxies in Groups: the ultraviolet view astro-ph.GA ABRIDGED- The UV-optical color magnitude diagram (CMD) of rich galaxy groups is characterised by a well developed Red Sequence (RS), a Blue Cloud (BC) and the so-called Green Valley (GV). Loose, less evolved groups of galaxies likely not virialized yet may lack a well defined RS. This is actually explained in the framework of galaxy evolution. We are focussing on understanding galaxy migration towards the RS, checking for signatures of such a transition in their photometric and morphological properties. We report on the UV properties of a sample of ETGs galaxies inhabiting the RS. The analysis of their structures, as derived by fitting a Sersic law to their UV luminosity profiles, suggests the presence of an underlying disk. This is the hallmark of dissipation processes that still must have a role in the evolution of this class of galaxies. SPH simulations with chemo-photometric implementations able to match the global properties of our targets are used to derive their evolutionary paths through UV-optical CDM, providing some fundamental information such as the crossing time through the GV, which depends on their luminosity. The transition from the BC to the RS takes several Gyrs, being about 3-5 Gyr for the the brightest galaxies and more long for fainter ones, if it occurs. The photometric study of nearby galaxy structures in UV is seriously hampered by either the limited FoV of the cameras (e.g in HST) or by the low spatial resolution of the images (e.g in the GALEX). Current missions equipped with telescopes and cameras sensitive to UV wavelengths, such as Swift-UVOT and Astrosat-UVIT, provide a relatively large FoV and better resolution than the GALEX. More powerful UV instruments (size, resolution and FoV) are obviously bound to yield fundamental advances in the accuracy and depth of the surface photometry and in the characterisation of the galaxy environment.
arxiv topic:astro-ph.GA
arxiv_dataset-95421803.04067
Valley-selective exciton bistability in a suspended monolayer semiconductor cond-mat.mes-hall We demonstrate robust power- and wavelength-dependent optical bistability in fully suspended monolayers of WSe2 near the exciton resonance. Bistability has been achieved under continuous-wave optical excitation at an intensity level of 10^3 W/cm^2. The observed bistability is originated from a photo-thermal mechanism, which provides both optical nonlinearity and passive feedback, two essential elements for optical bistability. Under a finite magnetic field, the exciton bistability becomes helicity dependent, which enables repeatable switching of light purely by its polarization.
arxiv topic:cond-mat.mes-hall
arxiv_dataset-95431803.04167
Methods for Classically Simulating Noisy Networked Quantum Architectures quant-ph As research on building scalable quantum computers advances, it is important to be able to certify their correctness. Due to the exponential hardness of classically simulating quantum computation, straight-forward verification through classical simulation fails. However, we can classically simulate small scale quantum computations and hence we are able to test that devices behave as expected in this domain. This constitutes the first step towards obtaining confidence in the anticipated quantum-advantage when we extend to scales which can no longer be simulated. Realistic devices have restrictions due to their architecture and limitations due to physical imperfections and noise. Here we extend the usual ideal simulations by considering those effects. We provide a general methodology for constructing realistic simulations emulating the physical system which will both provide a benchmark for realistic devices, and guide experimental research in the quest for quantum-advantage. We exemplify our methodology by simulating a networked architecture and corresponding noise-model; in particular that of the device developed in the Networked Quantum Information Technologies Hub (NQIT). For our simulations we use, with suitable modification, the classical simulator of of Bravyi and Gosset. The specific problems considered belong to the class of Instantaneous Quantum Polynomial-time (IQP) problems, a class believed to be hard for classical computing devices, and to be a promising candidate for the first demonstration of quantum-advantage. We first consider a subclass of IQP, defined by Bermejo-Vega et al, involving two-dimensional dynamical quantum simulators, before moving to more general instances of IQP, but which are still restricted to the architecture of NQIT.
arxiv topic:quant-ph
arxiv_dataset-95441803.04267
Gravitational collapse and structure formation in an expanding universe with dark energy physics.pop-ph astro-ph.CO gr-qc Observations show that the expansion of the Universe is accelerating. This requires that the dominant constituent of matter in the Universe has some unusual properties like negative pressure. This exotic component has been given the name dark energy. We work with the simplest model of dark energy, the cosmological constant introduced by Einstein. We study the evolution of spherical over-densities in such a model and show that there is a minimum over-density required for collapse: perturbations with a smaller amplitude do not collapse. This threshold is interesting as even perturbations with a positive over-density and negative energy do not collapse in finite time. Further, we show that perturbations with an amplitude larger than, but comparable to the threshold value, take a very long time to collapse. We compare the solutions with the case when dark energy is absent.
arxiv topic:physics.pop-ph astro-ph.CO gr-qc
arxiv_dataset-95451803.04367
Graded Holonomic D-modules on Monomial Curves math.RT math.RA In this paper, we study the holonomic $D$-modules when $D$ is the ring of $k$-linear differential operators on $A = k[\Gamma]$, the coordinate ring of an affine monomial curve over the complex numbers $k = \mathbb C$. In particular, we consider the graded case, and classify the simple graded $D$-modules and compute their extensions. The classification over the first Weyl algebra $D = A_1(k)$ is obtained as a special case.
arxiv topic:math.RT math.RA
arxiv_dataset-95461803.04467
Witnessing Planetary Systems in the Making with the Next Generation Very Large Array astro-ph.EP The discovery of thousands of exoplanets over the last couple of decades has shown that the birth of planets is a very efficient process in nature. Theories invoke a multitude of mechanisms to describe the assembly of planets in the disks around pre-main-sequence stars, but observational constraints have been sparse on account of insufficient sensitivity and resolution. Understanding how planets form and interact with their parental disk is crucial also to illuminate the main characteristics of a large portion of the full population of planets that is inaccessible to current and near-future observations. This White Paper describes some of the main issues for our current understanding of the formation and evolution of planets, and the critical contribution expected in this field by the Next Generation Very Large Array.
arxiv topic:astro-ph.EP
arxiv_dataset-95471803.04567
Convolutional Neural Networks and Language Embeddings for End-to-End Dialect Recognition cs.SD eess.AS Dialect identification (DID) is a special case of general language identification (LID), but a more challenging problem due to the linguistic similarity between dialects. In this paper, we propose an end-to-end DID system and a Siamese neural network to extract language embeddings. We use both acoustic and linguistic features for the DID task on the Arabic dialectal speech dataset: Multi-Genre Broadcast 3 (MGB-3). The end-to-end DID system was trained using three kinds of acoustic features: Mel-Frequency Cepstral Coefficients (MFCCs), log Mel-scale Filter Bank energies (FBANK) and spectrogram energies. We also investigated a dataset augmentation approach to achieve robust performance with limited data resources. Our linguistic feature research focused on learning similarities and dissimilarities between dialects using the Siamese network, so that we can reduce feature dimensionality as well as improve DID performance. The best system using a single feature set achieves 73% accuracy, while a fusion system using multiple features yields 78% on the MGB-3 dialect test set consisting of 5 dialects. The experimental results indicate that FBANK features achieve slightly better results than MFCCs. Dataset augmentation via speed perturbation appears to add significant robustness to the system. Although the Siamese network with language embeddings did not achieve as good a result as the end-to-end DID system, the two approaches had good synergy when combined together in a fused system.
arxiv topic:cs.SD eess.AS
arxiv_dataset-95481803.04667
Dynamic Vision Sensors for Human Activity Recognition cs.CV Unlike conventional cameras which capture video at a fixed frame rate, Dynamic Vision Sensors (DVS) record only changes in pixel intensity values. The output of DVS is simply a stream of discrete ON/OFF events based on the polarity of change in its pixel values. DVS has many attractive features such as low power consumption, high temporal resolution, high dynamic range and fewer storage requirements. All these make DVS a very promising camera for potential applications in wearable platforms where power consumption is a major concern. In this paper, we explore the feasibility of using DVS for Human Activity Recognition (HAR). We propose to use the various slices (such as $x-y$, $x-t$, and $y-t$) of the DVS video as a feature map for HAR and denote them as Motion Maps. We show that fusing motion maps with Motion Boundary Histogram (MBH) give good performance on the benchmark DVS dataset as well as on a real DVS gesture dataset collected by us. Interestingly, the performance of DVS is comparable to that of conventional videos although DVS captures only sparse motion information.
arxiv topic:cs.CV
arxiv_dataset-95491803.04767
SU(3) Quantum Spin Ladders as a Regularization of the CP(2) Model at Non-Zero Density: From Classical to Quantum Simulation hep-lat cond-mat.str-el quant-ph Quantum simulations would be highly desirable in order to investigate the finite density physics of QCD. $(1+1)$-d $\mathbb{C}P(N-1)$ quantum field theories are toy models that share many important features of QCD: they are asymptotically free, have a non-perturbatively generated massgap, as well as $\theta$-vacua. $SU(N)$ quantum spin ladders provide an unconventional regularization of $\mathbb{C}P(N-1)$ models that is well-suited for quantum simulation with ultracold alkaline-earth atoms in an optical lattice. In order to validate future quantum simulation experiments of $\mathbb{C}P(2)$ models at finite density, here we use quantum Monte Carlo simulations on classical computers to investigate $SU(3)$ quantum spin ladders at non-zero chemical potential. This reveals a rich phase structure, with single- or double-species Bose-Einstein "condensates", with or without ferromagnetic order.
arxiv topic:hep-lat cond-mat.str-el quant-ph
arxiv_dataset-95501803.04867
Extreme field-sensitivity of the magnetic tunneling in Fe-doped Li$_3$N cond-mat.mtrl-sci cond-mat.mes-hall cond-mat.str-el The magnetic properties of dilute Li$_2$(Li$_{1-x}$Fe$_x$)N with $x \sim 0.001$ are dominated by the spin of single, isolated Fe atoms. Below $T = 10$ K the spin-relaxation times become temperature-independent indicating a crossover from thermal excitations to the quantum tunneling regime. We report on a strong increase of the spin-flip probability in $\textit{transverse}$ magnetic fields that proves the resonant character of this tunneling process. $\textit{Longitudinal}$ fields, on the other hand, lift the ground-state degeneracy and destroy the tunneling condition. An increase of the relaxation time by four orders of magnitude in applied fields of only a few milliTesla reveals exceptionally sharp tunneling resonances. Li$_2$(Li$_{1-x}$Fe$_x$)N represents a comparatively simple and clean model system that opens the possibility to study quantum tunneling of the magnetization at liquid helium temperatures.
arxiv topic:cond-mat.mtrl-sci cond-mat.mes-hall cond-mat.str-el
arxiv_dataset-95511803.04967
Recurrent Neural Network Attention Mechanisms for Interpretable System Log Anomaly Detection cs.LG cs.NE stat.ML Deep learning has recently demonstrated state-of-the art performance on key tasks related to the maintenance of computer systems, such as intrusion detection, denial of service attack detection, hardware and software system failures, and malware detection. In these contexts, model interpretability is vital for administrator and analyst to trust and act on the automated analysis of machine learning models. Deep learning methods have been criticized as black box oracles which allow limited insight into decision factors. In this work we seek to "bridge the gap" between the impressive performance of deep learning models and the need for interpretable model introspection. To this end we present recurrent neural network (RNN) language models augmented with attention for anomaly detection in system logs. Our methods are generally applicable to any computer system and logging source. By incorporating attention variants into our RNN language models we create opportunities for model introspection and analysis without sacrificing state-of-the art performance. We demonstrate model performance and illustrate model interpretability on an intrusion detection task using the Los Alamos National Laboratory (LANL) cyber security dataset, reporting upward of 0.99 area under the receiver operator characteristic curve despite being trained only on a single day's worth of data.
arxiv topic:cs.LG cs.NE stat.ML
arxiv_dataset-95521803.05067
Applications of Psychological Science for Actionable Analytics cs.SE Actionable analytics are those that humans can understand, and operationalize. What kind of data mining models generate such actionable analytics? According to psychological scientists, humans understand models that most match their own internal models, which they characterize as lists of "heuristic" (i.e., lists of very succinct rules). One such heuristic rule generator is the Fast-and-Frugal Trees (FFT) preferred by psychological scientists. Despite their successful use in many applied domains, FFTs have not been applied in software analytics. Accordingly, this paper assesses FFTs for software analytics. We find that FFTs are remarkably effective. Their models are very succinct (5 lines or less describing a binary decision tree). These succinct models outperform state-of-the-art defect prediction algorithms defined by Ghortra et al. at ICSE'15. Also, when we restrict training data to operational attributes (i.e., those attributes that are frequently changed by developers), FFTs perform much better than standard learners. Our conclusions are two-fold. Firstly, there is much that software analytics community could learn from psychological science. Secondly, proponents of complex methods should always baseline those methods against simpler alternatives. For example, FFTs could be used as a standard baseline learner against which other software analytics tools are compared.
arxiv topic:cs.SE
arxiv_dataset-95531803.05167
A generalization of the steepest-edge rule and its number of simplex iterations for a nondegenerate LP math.OC In this paper, we propose a $p$-norm rule, which is a generalization of the steepest-edge rule, as a pivoting rule for the simplex method. For a nondegenerate linear programming problem, we show upper bounds for the number of iterations of the simplex method with the steepest-edge and $p$-norm rules. One of the upper bounds is given by a function of the number of variables, that of constraints, and the minimum and maximum positive elements in all basic feasible solutions.
arxiv topic:math.OC
arxiv_dataset-95541803.05267
$P_{c}$-like pentaquarks in hidden strange sector hep-ph nucl-th Analogous to the work of hidden charm molecular pentaquarks, we study possible hidden strange molecular pentaquarks composed of $\Sigma$ (or $\Sigma^{*}$) and $K$ (or $K^{*}$) in the framework of quark delocalization color screening model. Our results suggest that the $\Sigma K$, $\Sigma K^{*}$ and $\Sigma^{*} K^{*}$ with $IJ^{P}=\frac{1}{2}\frac{1}{2}^{-}$ and $\Sigma K^{*}$, $\Sigma^{*} K$ and $\Sigma^{*} K^{*}$ with $IJ^{P}=\frac{1}{2}\frac{3}{2}^{-}$ are all resonance states by coupling the open channels. The molecular pentaquark $\Sigma^{*} K$ with quantum numbers $IJ^{P}=\frac{1}{2}\frac{3}{2}^{-}$ can be seen as a strange partner of the LHCb $P_{c}(4380)$ state, and it can be identified as the nucleon resonance $N^{*}(1875)$ listed in PDG. The $\Sigma K^{*}$ with quantum numbers $IJ^{P}=\frac{1}{2}\frac{3}{2}^{-}$ can be identified as the $N^{*}(2100)$, which was experimentally observed in the $\phi$ photo-production.
arxiv topic:hep-ph nucl-th
arxiv_dataset-95551803.05367
Integrating UML with Service Refinement for Requirements Modeling and Analysis cs.SE Unified Modeling Language (UML) is the de facto standard for requirements modeling and system design. UML as a visual language can tremendously help customers, project managers, and developers to specify the requirements of a target system. However, UML lacks the ability to specify the requirements precisely such as the contracts of the system operation, and verify the consistency and refinement of the requirements. These disadvantages result in that the potential faults of software are hard to be discovered in the early stage of software development process, and then requiring more efforts in software testing to find the bugs. Service refinement is a formal method, which could be a supplement to enhance the UML. In this paper, we show how to integrate UML with service refinement to specify requirements, and verify the consistency and refinements of the requirements through a case study of online shopping system. Particularly, requirements are modeled through UML diagrams, which includes a) use case diagram, b) system sequence diagrams and c) conceptual class diagram. Service refinement enhances the requirements model by introducing the contracts. Furthermore, the consistency and refinements of requirement model can be verified through service refinement. Our approach demonstrates integrating UML with service refinement can require fewer efforts to achieve the consistency requirements than only using UML for requirement modeling.
arxiv topic:cs.SE
arxiv_dataset-95561803.05467
The phase-separation mechanism of a binary mixture in a ring trimer cond-mat.quant-gas We show that, depending on the ratio between the inter- and the intra-species interactions, a binary mixture trapped in a three-well potential with periodic boundary conditions exhibits three macroscopic ground-state configurations which differ in the degree of mixing. Accordingly, the corresponding quantum states feature either delocalization or a Schr\"odinger cat-like structure. The two-step phase separation occurring in the system, which is smoothed by the activation of tunnelling processes, is confirmed by the analysis of the energy spectrum that collapses and rearranges at the two critical points. In such points, we show that also Entanglement Entropy, a quantity borrowed from quantum-information theory, features singularities, thus demonstrating its ability to witness the double mixining-demixing phase transition. The developed analysis, which is of interest to both the experimental and theoretical communities, opens the door to the study of the demixing mechanism in complex lattice geometries.
arxiv topic:cond-mat.quant-gas
arxiv_dataset-95571803.05567
Achieving Human Parity on Automatic Chinese to English News Translation cs.CL Machine translation has made rapid advances in recent years. Millions of people are using it today in online translation systems and mobile applications in order to communicate across language barriers. The question naturally arises whether such systems can approach or achieve parity with human translations. In this paper, we first address the problem of how to define and accurately measure human parity in translation. We then describe Microsoft's machine translation system and measure the quality of its translations on the widely used WMT 2017 news translation task from Chinese to English. We find that our latest neural machine translation system has reached a new state-of-the-art, and that the translation quality is at human parity when compared to professional human translations. We also find that it significantly exceeds the quality of crowd-sourced non-professional translations.
arxiv topic:cs.CL
arxiv_dataset-95581803.05667
A Study of Recent Contributions on Information Extraction cs.IR cs.CL This paper reports on modern approaches in Information Extraction (IE) and its two main sub-tasks of Named Entity Recognition (NER) and Relation Extraction (RE). Basic concepts and the most recent approaches in this area are reviewed, which mainly include Machine Learning (ML) based approaches and the more recent trend to Deep Learning (DL) based methods.
arxiv topic:cs.IR cs.CL
arxiv_dataset-95591803.05767
Multiplicity Dependence of Charged Particle, $\phi$ Meson and Multi-strange Particle Productions in p+p Collisions at $\sqrt{\rm s}$ = 200 GeV with PYTHIA Simulation hep-ph nucl-th We report the multiplicity dependence of charged particle productions for $\pi^{\pm}$, $K^{\pm}$, $p$, $\overline{p}$ and $\phi$ meson at $|y| < 1.0$ in p+p collisions at $\sqrt{\rm s}$ = 200 GeV with $\rm PYTHIA$ simulation. The impact of parton multiple interactions and gluon contributions is studied and found to be possible sources of the particle yields splitting as a function of $p_T$ with respect to multiplicity. No obvious particle species dependence for the splitting is observed. The multiplicity dependence on ratios of $K^-/\pi^-$, $K^+/\pi^+$, $\overline{p}/\pi^-$, $p/\pi^+$ and $\Lambda/K^{0}_{s}$ in mid-rapidity in p+p collisions is found following the similar tendency as that in Au+Au collisions at $\sqrt{s_{NN}}$ = 200 GeV from RHIC, which heralds the similar underlying initial production mechanisms despite the differences in the initial colliding systems.
arxiv topic:hep-ph nucl-th
arxiv_dataset-95601803.05867
Capturing Structure Implicitly from Time-Series having Limited Data stat.ML cs.LG Scientific fields such as insider-threat detection and highway-safety planning often lack sufficient amounts of time-series data to estimate statistical models for the purpose of scientific discovery. Moreover, the available limited data are quite noisy. This presents a major challenge when estimating time-series models that are robust to overfitting and have well-calibrated uncertainty estimates. Most of the current literature in these fields involve visualizing the time-series for noticeable structure and hard coding them into pre-specified parametric functions. This approach is associated with two limitations. First, given that such trends may not be easily noticeable in small data, it is difficult to explicitly incorporate expressive structure into the models during formulation. Second, it is difficult to know $\textit{a priori}$ the most appropriate functional form to use. To address these limitations, a nonparametric Bayesian approach was proposed to implicitly capture hidden structure from time series having limited data. The proposed model, a Gaussian process with a spectral mixture kernel, precludes the need to pre-specify a functional form and hard code trends, is robust to overfitting and has well-calibrated uncertainty estimates.
arxiv topic:stat.ML cs.LG
arxiv_dataset-95611803.05967
Earth: Atmospheric Evolution of a Habitable Planet astro-ph.EP Our present-day atmosphere is often used as an analog for potentially habitable exoplanets, but Earth's atmosphere has changed dramatically throughout its 4.5 billion year history. For example, molecular oxygen is abundant in the atmosphere today but was absent on the early Earth. Meanwhile, the physical and chemical evolution of Earth's atmosphere has also resulted in major swings in surface temperature, at times resulting in extreme glaciation or warm greenhouse climates. Despite this dynamic and occasionally dramatic history, the Earth has been persistently habitable--and, in fact, inhabited--for roughly 4 billion years. Understanding Earth's momentous changes and its enduring habitability is essential as a guide to the diversity of habitable planetary environments that may exist beyond our solar system and for ultimately recognizing spectroscopic fingerprints of life elsewhere in the Universe. Here, we review long-term trends in the composition of Earth's atmosphere as it relates to both planetary habitability and inhabitation. We focus on gases that may serve as habitability markers (CO2, N2) or biosignatures (CH4, O2), especially as related to the redox evolution of the atmosphere and the coupled evolution of Earth's climate system. We emphasize that in the search for Earth-like planets we must be mindful that the example provided by the modern atmosphere merely represents a single snapshot of Earth's long-term evolution. In exploring the many former states of our own planet, we emphasize Earth's atmospheric evolution during the Archean, Proterozoic, and Phanerozoic eons, but we conclude with a brief discussion of potential atmospheric trajectories into the distant future, many millions to billions of years from now. All of these 'Alternative Earth' scenarios provide insight to the potential diversity of Earth-like, habitable, and inhabited worlds.
arxiv topic:astro-ph.EP
arxiv_dataset-95621803.06067
Dynamic-structured Semantic Propagation Network cs.CV Semantic concept hierarchy is still under-explored for semantic segmentation due to the inefficiency and complicated optimization of incorporating structural inference into dense prediction. This lack of modeling semantic correlations also makes prior works must tune highly-specified models for each task due to the label discrepancy across datasets. It severely limits the generalization capability of segmentation models for open set concept vocabulary and annotation utilization. In this paper, we propose a Dynamic-Structured Semantic Propagation Network (DSSPN) that builds a semantic neuron graph by explicitly incorporating the semantic concept hierarchy into network construction. Each neuron represents the instantiated module for recognizing a specific type of entity such as a super-class (e.g. food) or a specific concept (e.g. pizza). During training, DSSPN performs the dynamic-structured neuron computation graph by only activating a sub-graph of neurons for each image in a principled way. A dense semantic-enhanced neural block is proposed to propagate the learned knowledge of all ancestor neurons into each fine-grained child neuron for feature evolving. Another merit of such semantic explainable structure is the ability of learning a unified model concurrently on diverse datasets by selectively activating different neuron sub-graphs for each annotation at each step. Extensive experiments on four public semantic segmentation datasets (i.e. ADE20K, COCO-Stuff, Cityscape and Mapillary) demonstrate the superiority of our DSSPN over state-of-the-art segmentation models. Moreoever, we demonstrate a universal segmentation model that is jointly trained on diverse datasets can surpass the performance of the common fine-tuning scheme for exploiting multiple domain knowledge.
arxiv topic:cs.CV
arxiv_dataset-95631803.06167
Semantic Segmentation of Pathological Lung Tissue with Dilated Fully Convolutional Networks cs.CV Early and accurate diagnosis of interstitial lung diseases (ILDs) is crucial for making treatment decisions, but can be challenging even for experienced radiologists. The diagnostic procedure is based on the detection and recognition of the different ILD pathologies in thoracic CT scans, yet their manifestation often appears similar. In this study, we propose the use of a deep purely convolutional neural network for the semantic segmentation of ILD patterns, as the basic component of a computer aided diagnosis (CAD) system for ILDs. The proposed CNN, which consists of convolutional layers with dilated filters, takes as input a lung CT image of arbitrary size and outputs the corresponding label map. We trained and tested the network on a dataset of 172 sparsely annotated CT scans, within a cross-validation scheme. The training was performed in an end-to-end and semi-supervised fashion, utilizing both labeled and non-labeled image regions. The experimental results show significant performance improvement with respect to the state of the art.
arxiv topic:cs.CV
arxiv_dataset-95641803.06267
Consistent sets of lines with no colorful incidence cs.CG cs.CV math.CO We consider incidences among colored sets of lines in $\mathbb{R}^d$ and examine whether the existence of certain concurrences between lines of $k$ colors force the existence of at least one concurrence between lines of $k+1$ colors. This question is relevant for problems in 3D reconstruction in computer vision.
arxiv topic:cs.CG cs.CV math.CO
arxiv_dataset-95651803.06367
The supernova remnant population in the very-high-energy sky: prospects for CTA astro-ph.HE The detection of very-high-energy gamma rays from supernova remnant shells testifies of the acceleration of particles at strong shocks. Many aspects of the particle acceleration remain however unclear. The study of individual objects is very helpful, but the study of the entire population of SNRs detected in this range and its characteristics can also bring valuable science. Using Monte-Carlo simulations, the population of shells bright in the TeV and multi-TeV range can be simulated. The results of these simulations aim at being compared with observations of in struments operating in these ranges, such as the Cherenkov Telescope Array (CTA). Our results suggest that CTA should be able to effectively constrain the slope of particles accelerated at SNRs and the electron-to-proton ratio.
arxiv topic:astro-ph.HE
arxiv_dataset-95661803.06467
Optimizing Information Freshness in Wireless Networks under General Interference Constraints cs.IT cs.NI math.IT Age of information (AoI) is a recently proposed metric for measuring information freshness. AoI measures the time that elapsed since the last received update was generated. We consider the problem of minimizing average and peak AoI in a wireless networks, consisting of a set of source-destination links, under general interference constraints. When fresh information is always available for transmission, we show that a stationary scheduling policy is peak age optimal. We also prove that this policy achieves average age that is within a factor of two of the optimal average age. In the case where fresh information is not always available, and packet/information generation rate has to be controlled along with scheduling links for transmission, we prove an important separation principle: the optimal scheduling policy can be designed assuming fresh information, and independently, the packet generation rate control can be done by ignoring interference. Peak and average AoI for discrete time G/Ber/1 queue is analyzed for the first time, which may be of independent interest.
arxiv topic:cs.IT cs.NI math.IT
arxiv_dataset-95671803.06567
A Dual Approach to Scalable Verification of Deep Networks cs.LG stat.ML This paper addresses the problem of formally verifying desirable properties of neural networks, i.e., obtaining provable guarantees that neural networks satisfy specifications relating their inputs and outputs (robustness to bounded norm adversarial perturbations, for example). Most previous work on this topic was limited in its applicability by the size of the network, network architecture and the complexity of properties to be verified. In contrast, our framework applies to a general class of activation functions and specifications on neural network inputs and outputs. We formulate verification as an optimization problem (seeking to find the largest violation of the specification) and solve a Lagrangian relaxation of the optimization problem to obtain an upper bound on the worst case violation of the specification being verified. Our approach is anytime i.e. it can be stopped at any time and a valid bound on the maximum violation can be obtained. We develop specialized verification algorithms with provable tightness guarantees under special assumptions and demonstrate the practical significance of our general verification approach on a variety of verification tasks.
arxiv topic:cs.LG stat.ML
arxiv_dataset-95681803.06667
Subleading-power corrections to the radiative leptonic $B \to \gamma \ell \nu$ decay in QCD hep-ph hep-ex hep-lat Applying the method of light-cone sum rules with photon distribution amplitudes, we compute the subleading-power correction to the radiative leptonic $B \to \gamma \ell \nu$ decay, at next-to-leading order in QCD for the twist-two contribution and at leading order in $\alpha_s$ for the higher-twist contributions, induced by the hadronic component of the collinear photon. The leading-twist hadronic photon effect turns out to preserve the symmetry relation between the two $B \to \gamma$ form factors due to the helicity conservation, however, the higher-twist hadronic photon corrections can yield symmetry-breaking effect already at tree level in QCD. Using the conformal expansion of photon distribution amplitudes with the non-perturbative parameters estimated from QCD sum rules, the twist-two hadronic photon contribution can give rise to approximately 30\% correction to the leading-power "direct photon" effect computed from the perturbative QCD factorization approach. In contrast, the subleading-power corrections from the higher-twist two-particle and three-particle photon distribution amplitudes are estimated to be of ${\cal O} (3 \sim 5\%)$ with the light-cone sum rule approach. We further predict the partial branching fractions of $B \to \gamma \ell \nu $ with a photon-energy cut $E_{\gamma} \geq E_{\rm cut}$, which are of interest for determining the inverse moment of the leading-twist $B$-meson distribution amplitude thanks to the forthcoming high-luminosity Belle II experiment at KEK.
arxiv topic:hep-ph hep-ex hep-lat
arxiv_dataset-95691803.06767
Generation and detection of non-Gaussian phonon-added coherent states in optomechanical systems quant-ph cond-mat.mes-hall physics.optics Adding excitations on a coherent state provides an effective way to observe nonclassical properties of radiation fields. Here we describe and analyse how to apply this concept to the motional state of a mechanical oscillator and present a full scheme to prepare non-Gaussian {\it phonon}-added coherent states of the mechanical motion in cavity optomechanics. We first generate a mechanical coherent state using electromagnetically induced transparency. We then add a single phonon onto the coherent state via optomechanical parametric down-conversion combined with single photon detection. We validate this single-phonon-added coherent state by using a red-detuned beam and reading out the state of the optical output field. This approach allows us to verify nonclassical properties of the phonon state, such as sub-Poissonian character and quadrature squeezing. We further show that our scheme can be directly implemented using existing devices, and is generic in nature and hence applicable to a variety of systems in opto- and electromechanics.
arxiv topic:quant-ph cond-mat.mes-hall physics.optics
arxiv_dataset-95701803.06867
Cloud Infrastructure Provenance Collection and Management to Reproduce Scientific Workflow Execution cs.DC The emergence of Cloud computing provides a new computing paradigm for scientific workflow execution. It provides dynamic, on-demand and scalable resources that enable the processing of complex workflow-based experiments. With the ever growing size of the experimental data and increasingly complex processing workflows, the need for reproducibility has also become essential. Provenance has been thought of a mechanism to verify a workflow and to provide workflow reproducibility. One of the obstacles in reproducing an experiment execution is the lack of information about the execution infrastructure in the collected provenance. This information becomes critical in the context of Cloud in which resources are provisioned on-demand and by specifying resource configurations. Therefore, a mechanism is required that enables capturing of infrastructure information along with the provenance of workflows executing on the Cloud to facilitate the re-creation of execution environment on the Cloud. This paper presents a framework, ReCAP, along with the proposed mapping approaches that aid in capturing the Cloud-aware provenance information and help in re-provisioning the execution resource on the Cloud with similar configurations. Experimental evaluation has shown the impact of different resource configurations on the workflow execution performance, therefore justifies the need for collecting such provenance information in the context of Cloud. The evaluation has also demonstrated that the proposed mapping approaches can capture Cloud information in various Cloud usage scenarios without causing performance overhead and can also enable the re-provisioning of resources on Cloud. Experiments were conducted using workflows from different scientific domains such as astronomy and neuroscience to demonstrate the applicability of this research for different workflows.
arxiv topic:cs.DC
arxiv_dataset-95711803.06967
Phenomenology of coupled non linear oscillators nlin.CD A recently introduced model of coupled non linear oscillators in a ring is revisited in terms of its information processing capabilities. The use of Lempel-Ziv based entropic measures allows to study thoroughly the complex patterns appearing in the system for different values of the control parameters. Such behaviors, resembling cellular automata, have been characterized both spatially and temporally. Information distance is used to study the stability of the system to perturbations in the initial conditions and in the control parameters. The latter is not an issue in cellular automata theory, where the rules form a numerable set, contrary to the continuous nature of the parameter space in the system studied in this contribution. The variation in the density of the digits, as a function of time is also studied. Local transitions in the control parameter space are also discussed.
arxiv topic:nlin.CD
arxiv_dataset-95721803.07067
Setting up a Reinforcement Learning Task with a Real-World Robot cs.LG cs.AI cs.RO stat.ML Reinforcement learning is a promising approach to developing hard-to-engineer adaptive solutions for complex and diverse robotic tasks. However, learning with real-world robots is often unreliable and difficult, which resulted in their low adoption in reinforcement learning research. This difficulty is worsened by the lack of guidelines for setting up learning tasks with robots. In this work, we develop a learning task with a UR5 robotic arm to bring to light some key elements of a task setup and study their contributions to the challenges with robots. We find that learning performance can be highly sensitive to the setup, and thus oversights and omissions in setup details can make effective learning, reproducibility, and fair comparison hard. Our study suggests some mitigating steps to help future experimenters avoid difficulties and pitfalls. We show that highly reliable and repeatable experiments can be performed in our setup, indicating the possibility of reinforcement learning research extensively based on real-world robots.
arxiv topic:cs.LG cs.AI cs.RO stat.ML
arxiv_dataset-95731803.07167
Soft Pomerons and the Forward LHC Data hep-ph hep-ex Recent data from LHC13 by the TOTEM Collaboration on $\sigma_{tot}$ and $\rho$ have indicated disagreement with all the Pomeron model predictions by the COMPETE Collaboration (2002). On the other hand, as recently demonstrated by Martynov and Nicolescu (MN), the new $\sigma_{tot}$ datum and the unexpected decrease in the $\rho$ value are well described by the maximal Odderon dominance at the highest energies. Here, we discuss the applicability of Pomeron dominance through fits to the \textit{most complete set} of forward data from $pp$ and $\bar{p}p$ scattering. We consider an analytic parametrization for $\sigma_{tot}(s)$ consisting of non-degenerated Regge trajectories for even and odd amplitudes (as in the MN analysis) and two Pomeron components associated with double and triple poles in the complex angular momentum plane. The $\rho$ parameter is analytically determined by means of dispersion relations. We carry out fits to $pp$ and $\bar{p}p$ data on $\sigma_{tot}$ and $\rho$ in the interval 5 GeV - 13 TeV (as in the MN analysis). Two novel aspects of our analysis are: (1) the dataset comprises all the accelerator data below 7 TeV and we consider \textit{three independent ensembles} by adding: either only the TOTEM data (as in the MN analysis), or only the ATLAS data, or both sets; (2) in the data reductions to each ensemble, uncertainty regions are evaluated through error propagation from the fit parameters, with 90 \% CL. We argument that, within the uncertainties, this analytic model corresponding to soft Pomeron dominance, does not seem to be excluded by the \textit{complete} set of experimental data presently available.
arxiv topic:hep-ph hep-ex
arxiv_dataset-95741803.07267
Does the chiral magnetic effect change the dynamic universality class in QCD? hep-ph cond-mat.mes-hall cond-mat.stat-mech nucl-th In QCD matter under an external magnetic field, the chiral magnetic effect (CME) leads to the collective gapless mode called the chiral magnetic wave (CMW). Since dynamic universality class generally depends on low-energy gapless modes, it is nontrivial whether the CME and the resulting CMW change that of the second-order chiral phase transition in QCD. To address this question, we study the critical dynamics near the chiral phase transition in massless two-flavor QCD under an external magnetic field. By performing the dynamic renormalization-group analysis within the epsilon expansion, we find that the presence of the CME changes the dynamic universality class to that of model A. We also show that the transport coefficient of the CME is not renormalized by the critical fluctuations of the order parameter.
arxiv topic:hep-ph cond-mat.mes-hall cond-mat.stat-mech nucl-th
arxiv_dataset-95751803.07367
Muon anomalies and the $SU(5)$ Yukawa relations hep-ph We show that, within the framework of $SU(5)$ Grand Unified Theories (GUTs), multiple vector-like families at the GUT scale which transform under a gauged $U(1)'$ (under which the three chiral families are neutral) can result in a single vector-like family at low energies which can induce non-universal and flavourful $Z'$ couplings, which can account for the B physics anomalies in $R_{K^{(*)}}$. In such theories, we show that the same muon couplings which explain $R_{K^{(*)}}$ also correct the Yukawa relation $Y_e=Y_d^T$ in the muon sector without the need for higher Higgs representations. To illustrate the mechanism, we construct a concrete a model based on $SU(5)\times A_4 \times Z_3\times Z_7$ with two vector-like families at the GUT scale, and two right-handed neutrinos, leading to a successful fit to quark and lepton (including neutrino) masses, mixing angles and CP phases, where the constraints from lepton flavour violation require $Y_e$ to be diagonal.
arxiv topic:hep-ph
arxiv_dataset-95761803.07467
Laser Cooling at Resonance cond-mat.quant-gas physics.atom-ph We show experimentally that 3-D laser cooling of lithium atoms is achieved when the laser light is tuned exactly to resonance with the atomic transition. For a theoretical description of this surprising phenomenon we resolve to a full model which takes into account both the entire atomic structure and the laser light polarization. Here we build such a model for $^7$Li atoms cooled on the $D_{2}$-line in a $\sigma^+-\sigma^-$ laser configuration. We take all 24 Zeeman sub-levels into account and obtain good agreement with the experimental data. Moreover, by means of Monte-Carlo simulations we show that coherent processes play an important role in showing consistency between the theory and the experimental results.
arxiv topic:cond-mat.quant-gas physics.atom-ph
arxiv_dataset-95771803.07567
Umbral Moonshine and String Duality hep-th By studying 2d string compactifications with half-maximal supersymmetry in a variety of duality frames, we find a natural physical setting for understanding Umbral moonshine. Near points in moduli space with enhanced gauge symmetry, we find that the Umbral symmetry groups arise as symmetries of the theory. In one duality frame -- a flux compactification on $T^4/Z_2\times T^4$ -- the 24-dimensional permutation representations of the Umbral groups act on D1-branes strung between a set of NS5-branes. The presence of these NS5-branes is used to explain the Umbral moonshine decompositions of the K3 twining genera, and in particular of the K3 elliptic genus. The fundamental string in this frame is dual to the type IIA string on K3$\times T^4$ and to a compactified heterotic little string theory. The latter provides an interesting example of a little string theory, as the string-scale geometry transverse to the 5-brane plays an important role in its construction.
arxiv topic:hep-th
arxiv_dataset-95781803.07667
Edgeworth expansions for weakly dependent random variables math.PR math.DS We discuss sufficient conditions that guarantee the existence of asymptotic expansions for the Central Limit Theorem for weakly dependent random variables including observations arising from sufficiently chaotic dynamical systems like piece-wise expanding maps, and strongly ergodic Markov chains. We primarily use spectral techniques to obtain the results.
arxiv topic:math.PR math.DS
arxiv_dataset-95791803.07767
Composite fermion Hall conductivity and the half-filled Landau level cond-mat.str-el We consider the Hall conductivity of composite fermions in the theory of Halperin, Lee, and Read (HLR). We present a fully quantum mechanical numerical calculation that shows, under suitable conditions, the HLR theory exhibits a particle-hole symmetric dc electrical Hall response in the presence of quenched disorder. Remarkably, this response of the HLR theory remains robust even when the disorder range is of the order of the Fermi wavelength. We find that deviations from particle-hole symmetric response can appear in the ac Hall conductivity at frequencies sufficiently large compared to the inverse system size. Our results agree with a recent semi-classical analysis by Wang et al., Phys. Rev. X 7, 031029 (2017) and complement the arguments based on the fully quantum-mechanical model by Kumar et al., Phys. Rev. B 98, 11505 (2018). These results provide further evidence that the HLR theory is compatible with an emergent particle-hole symmetry.
arxiv topic:cond-mat.str-el
arxiv_dataset-95801803.07867
Transit Photometry as an Exoplanet Discovery Method astro-ph.EP Photometry with the transit method has arguably been the most successful exoplanet discovery method to date. A short overview about the rise of that method to its present status is given. The method's strength is the rich set of parameters that can be obtained from transiting planets, in particular in combination with radial velocity observations; the basic principles of these parameters are given, with explicit formulations for the transit detection probability and the times of transit epochs in comparison to radial velocity epochs. The transit method has however also drawbacks, which are the low probability of properly aligned planet systems and the presence of astrophysical phenomena that may mimic transits and give rise to false detection positives. In the second part, we outline the main factors that determine the design of transit surveys, such as the size of the survey sample, the temporal coverage, the photometric precision, the sample brightness and the methods to extract transit events from observed light curves. Lastly, an overview over past, current, and future transit surveys is given. For these surveys we indicate their basic instrument configuration and their planet catch, including the ranges of planet sizes and stellar magnitudes that were encountered. Current and future transit detection experiments concentrate primarily on bright or special targets, and we expect that the transit method remains a principal driver of exoplanet science, through new discoveries to be made and through the development of new generations of instruments.
arxiv topic:astro-ph.EP
arxiv_dataset-95811803.07967
Long-wavelength phonons in the crystalline and pasta phases of neutron-star crusts nucl-th astro-ph.HE We study the long-wavelength excitations of the inner crust of neutron stars, considering three phases: cubic crystal at low densities, rods and plates near the core-crust transition. To describe the phonons, we write an effective Lagrangian density in terms of the coarse-grained phase of the neutron superfluid gap and of the average displacement field of the clusters. The kinetic energy, including the entrainment of the neutron gas by the clusters, is obtained within a superfluid hydrodynamics approach. The potential energy is determined from a model where clusters and neutron gas are considered in phase coexistence, augmented by the elasticity of the lattice due to Coulomb and surface effects. All three phases show strong anisotropy, i.e., angle dependence of the phonon velocities. Consequences for the specific heat at low temperature are discussed.
arxiv topic:nucl-th astro-ph.HE
arxiv_dataset-95821803.08067
A Review of Situation Awareness Assessment Approaches in Aviation Environments cs.HC Situation awareness (SA) is an important constituent in human information processing and essential in pilots' decision-making processes. Acquiring and maintaining appropriate levels of SA is critical in aviation environments as it affects all decisions and actions taking place in flights and air traffic control. This paper provides an overview of recent measurement models and approaches to establishing and enhancing SA in aviation environments. Many aspects of SA are examined including the classification of SA techniques into six categories, and different theoretical SA models from individual, to shared or team, and to distributed or system levels. Quantitative and qualitative perspectives pertaining to SA methods and issues of SA for unmanned vehicles are also addressed. Furthermore, future research directions regarding SA assessment approaches are raised to deal with shortcomings of the existing state-of-the-art methods in the literature.
arxiv topic:cs.HC
arxiv_dataset-95831803.08167
A Staggered Explicit-Implicit Finite Element Formulation for Electroactive Polymers physics.comp-ph Electroactive polymers such as dielectric elastomers (DEs) have attracted significant attention in recent years. Computational techniques to solve the coupled electromechanical system of equations for this class of materials have universally centered around fully coupled monolithic formulations, which while generating good accuracy requires significant computational expense. However, this has significantly hindered the ability to solve large scale, fully three-dimensional problems involving complex deformations and electromechanical instabilities of DEs. In this work, we provide theoretical basis for the effectiveness and accuracy of staggered explicit-implicit finite element formulations for this class of electromechanically coupled materials, and elicit the simplicity of the resulting staggered formulation. We demonstrate the stability and accuracy of the staggered approach by solving complex electromechanically coupled problems involving electroactive polymers, where we focus on problems involving electromechanical instabilities such as creasing, wrinkling, and bursting drops. In all examples, essentially identical results to the fully monolithic solution are obtained, showing the accuracy of the staggered approach at a significantly reduced computational cost.
arxiv topic:physics.comp-ph
arxiv_dataset-95841803.08267
Cross-infrastructure holistic experiment design for cyber-physical energy system validation cs.SY Strong digitalization and shifting from unidirectional to bidirectional topology have transformed the electrical grid into a cyber-physical energy system, i.e. smart grid, with strong interdependency among various domains. It is mandatory to develop a comprehensive and holistic validation approach for such large scale system. However, a single research infrastructure may not have sufficient expertise and equipment for such test, without huge or eventually unfeasible investment. In this paper, we propose another adequate approach: connecting existing and established infrastructures with complementary specialization and facilities into a cross-infrastructure holistic experiment. The proposition enables testing of CPES assessment research in near real-world scenario without significant investment while efficiently exploiting the existing infrastructures. Hybrid cloud based architecture is considered as the support for such setup and the design of cross-infrastructure experiment is also covered.
arxiv topic:cs.SY
arxiv_dataset-95851803.08367
Gradient Descent Quantizes ReLU Network Features stat.ML cs.LG Deep neural networks are often trained in the over-parametrized regime (i.e. with far more parameters than training examples), and understanding why the training converges to solutions that generalize remains an open problem. Several studies have highlighted the fact that the training procedure, i.e. mini-batch Stochastic Gradient Descent (SGD) leads to solutions that have specific properties in the loss landscape. However, even with plain Gradient Descent (GD) the solutions found in the over-parametrized regime are pretty good and this phenomenon is poorly understood. We propose an analysis of this behavior for feedforward networks with a ReLU activation function under the assumption of small initialization and learning rate and uncover a quantization effect: The weight vectors tend to concentrate at a small number of directions determined by the input data. As a consequence, we show that for given input data there are only finitely many, "simple" functions that can be obtained, independent of the network size. This puts these functions in analogy to linear interpolations (for given input data there are finitely many triangulations, which each determine a function by linear interpolation). We ask whether this analogy extends to the generalization properties - while the usual distribution-independent generalization property does not hold, it could be that for e.g. smooth functions with bounded second derivative an approximation property holds which could "explain" generalization of networks (of unbounded size) to unseen inputs.
arxiv topic:stat.ML cs.LG
arxiv_dataset-95861803.08467
BSD-GAN: Branched Generative Adversarial Network for Scale-Disentangled Representation Learning and Image Synthesis cs.CV We introduce BSD-GAN, a novel multi-branch and scale-disentangled training method which enables unconditional Generative Adversarial Networks (GANs) to learn image representations at multiple scales, benefiting a wide range of generation and editing tasks. The key feature of BSD-GAN is that it is trained in multiple branches, progressively covering both the breadth and depth of the network, as resolutions of the training images increase to reveal finer-scale features. Specifically, each noise vector, as input to the generator network of BSD-GAN, is deliberately split into several sub-vectors, each corresponding to, and is trained to learn, image representations at a particular scale. During training, we progressively "de-freeze" the sub-vectors, one at a time, as a new set of higher-resolution images is employed for training and more network layers are added. A consequence of such an explicit sub-vector designation is that we can directly manipulate and even combine latent (sub-vector) codes which model different feature scales.Extensive experiments demonstrate the effectiveness of our training method in scale-disentangled learning of image representations and synthesis of novel image contents, without any extra labels and without compromising quality of the synthesized high-resolution images. We further demonstrate several image generation and manipulation applications enabled or improved by BSD-GAN. Source codes are available at https://github.com/duxingren14/BSD-GAN.
arxiv topic:cs.CV
arxiv_dataset-95871803.08567
Property FW, differentiable structures, and smoothability of singular actions math.DS math.GR math.GT We provide a smoothening criterion for group actions on manifolds by singular diffeomorphisms. We prove that if a countable group $\Gamma$ has the fixed point property FW for walls (e.g. if it has property (T)), every aperiodic action of $\Gamma$ by diffeomorphisms that are of class $C^r$ with countably many singularities is conjugate to an action by true diffeomorphisms of class $C^r$ on a homeomorphic (possibly non-diffeomorphic) manifold. As applications, we show that Navas's result for actions of Kazhdan groups on the circle, as well as the recent solutions to Zimmer's conjecture, generalise to aperiodic actions by diffeomorphisms with countably many singularities.
arxiv topic:math.DS math.GR math.GT
arxiv_dataset-95881803.08667
On efficient global optimization via universal Kriging surrogate models stat.ML In this paper, we investigate the capability of the universal Kriging (UK) model for single-objective global optimization applied within an efficient global optimization (EGO) framework. We implemented this combined UK-EGO framework and studied four variants of the UK methods, that is, a UK with a first-order polynomial, a UK with a second-order polynomial, a blind Kriging (BK) implementation from the ooDACE toolbox, and a polynomial-chaos Kriging (PCK) implementation. The UK-EGO framework with automatic trend function selection derived from the BK and PCK models works by building a UK surrogate model and then performing optimizations via expected improvement criteria on the Kriging model with the lowest leave-one-out cross-validation error. Next, we studied and compared the UK-EGO variants and standard EGO using five synthetic test functions and one aerodynamic problem. Our results show that the proper choice for the trend function through automatic feature selection can improve the optimization performance of UK-EGO relative to EGO. From our results, we found that PCK-EGO was the best variant, as it had more robust performance as compared to the rest of the UK-EGO schemes; however, total-order expansion should be used to generate the candidate trend function set for high-dimensional problems. Note that, for some test functions, the UK with predetermined polynomial trend functions performed better than that of BK and PCK, indicating that the use of automatic trend function selection does not always lead to the best quality solutions. We also found that although some variants of UK are not as globally accurate as the ordinary Kriging (OK), they can still identify better-optimized solutions due to the addition of the trend function, which helps the optimizer locate the global optimum.
arxiv topic:stat.ML
arxiv_dataset-95891803.08767
A conservation law with spatially localized sublinear damping math.AP math.OC We consider a general conservation law on the circle, in the presence of a sublinear damping. If the damping acts on the whole circle, then the solution becomes identically zero in finite time, following the same mechanism as the corresponding ordinary differential equation. When the damping acts only locally in space, we show a dichotomy: if the flux function is not zero at the origin, then the transport mechanism causes the extinction of the solution in finite time, as in the first case. On the other hand, if zero is a non-degenerate critical point of the flux function, then the solution becomes extinct in finite time only inside the damping zone, decays algebraically uniformly in space, and we exhibit a boundary layer, shrinking with time, around the damping zone. Numerical illustrations show how similar phenomena may be expected for other equations.
arxiv topic:math.AP math.OC
arxiv_dataset-95901803.08867
Testing demand responsive shared transport services via agent-based simulations cs.MA physics.soc-ph Demand Responsive Shared Transport DRST services take advantage of Information and Communication Technologies ICT, to provide on demand transport services booking in real time a ride on a shared vehicle. In this paper, an agent-based model ABM is presented to test different the feasibility of different service configurations in a real context. First results show the impact of route choice strategy on the system performance.
arxiv topic:cs.MA physics.soc-ph
arxiv_dataset-95911803.08967
Automatic phase calibration for RF cavities using beam-loading signals physics.acc-ph Precise calibration of the cavity phase signals is necessary for the operation of any particle accelerator. For many systems this requires human in the loop adjustments based on measurements of the beam parameters downstream. Some recent work has developed a scheme for the calibration of the cavity phase using beam measurements and beam-loading however this scheme is still a multi-step process that requires heavy automation or human in the loop. In this paper we analyze a new scheme that uses only RF signals reacting to beam-loading to calculate the phase of the beam relative to the cavity. This technique could be used in slow control loops to provide real-time adjustment of the cavity phase calibration without human intervention thereby increasing the stability and reliability of the accelerator.
arxiv topic:physics.acc-ph
arxiv_dataset-95921803.09067
Gravity model explained by the radiation model on a population landscape physics.soc-ph Understanding the mechanisms behind human mobility patterns is crucial to improve our ability to optimize and predict traffic flows. Two representative mobility models, i.e., radiation and gravity models, have been extensively compared to each other against various empirical data sets, while their fundamental relation is far from being fully understood. In order to study such a relation, we first model the heterogeneous population landscape by generating a fractal geometry of sites and then by assigning to each site a population independently drawn from a power-law distribution. Then the radiation model on this population landscape, which we call the radiation-on-landscape (RoL) model, is compared to the gravity model to derive the distance exponent in the gravity model in terms of the properties of the population landscape, which is confirmed by the numerical simulations. Consequently, we provide a possible explanation for the origin of the distance exponent in terms of the properties of the heterogeneous population landscape, enabling us to better understand mobility patterns constrained by the travel distance.
arxiv topic:physics.soc-ph
arxiv_dataset-95931803.09167
3D Reconstruction & Assessment Framework based on affordable 2D Lidar cs.RO Lidar is extensively used in the industry and mass-market. Due to its measurement accuracy and insensitivity to illumination compared to cameras, It is applied onto a broad range of applications, like geodetic engineering, self driving cars or virtual reality. But the 3D Lidar with multi-beam is very expensive, and the massive measurements data can not be fully leveraged on some constrained platforms. The purpose of this paper is to explore the possibility of using cheap 2D Lidar off-the-shelf, to preform complex 3D Reconstruction, moreover, the generated 3D map quality is evaluated by our proposed metrics at the end. The 3D map is constructed in two ways, one way in which the scan is performed at known positions with an external rotary axis at another plane. The other way, in which the 2D Lidar for mapping and another 2D Lidar for localization are placed on a trolley, the trolley is pushed on the ground arbitrarily. The generated maps by different approaches are converted to octomaps uniformly before the evaluation. The similarity and difference between two maps will be evaluated by the proposed metrics thoroughly. The whole mapping system is composed of several modular components. A 3D bracket was made for assembling of the Lidar with a long range, the driver and the motor together. A cover platform made for the IMU and 2D Lidar with a shorter range but high accuracy. The software is stacked up in different ROS packages.
arxiv topic:cs.RO
arxiv_dataset-95941803.09267
Frobenius Degenerations of Preprojective Algebras math.RA math.RT math.SG In this paper, we study a preprojective algebra for quivers decorated with $k$-algebras and bimodules, which generalizes work of Gabriel for ordinary quivers, work of Dlab and Ringel for $k$-species, and recent work of de Thanhoffer de V\"olcsey and Presotto, which has recently appeared from a different perspective in work of K\"ulshammer. As for undecorated quivers, we show that its moduli space of representations recovers the Hamiltonian reduction of the cotangent bundle over the space of representations of the decorated quiver. These algebras yield degenerations of ordinary preprojective algebras, by folding the quiver and then degenerating the decorations. We prove that these degenerations are flat in the Dynkin case, and conjecture, based on computer results, that this extends to arbitrary decorated quivers.
arxiv topic:math.RA math.RT math.SG
arxiv_dataset-95951803.09367
Opposition diagrams for automorphisms of small spherical buildings math.CO An automorphism $\theta$ of a spherical building $\Delta$ is called \textit{capped} if it satisfies the following property: if there exist both type $J_1$ and $J_2$ simplices of $\Delta$ mapped onto opposite simplices by $\theta$ then there exists a type $J_1\cup J_2$ simplex of $\Delta$ mapped onto an opposite simplex by $\theta$. In previous work we showed that if $\Delta$ is a thick irreducible spherical building of rank at least $3$ with no Fano plane residues then every automorphism of $\Delta$ is capped. In the present work we consider the spherical buildings with Fano plane residues (the \textit{small buildings}). We show that uncapped automorphisms exist in these buildings and develop an enhanced notion of "opposition diagrams" to capture the structure of these automorphisms. Moreover we provide applications to the theory of "domesticity" in spherical buildings, including the complete classification of domestic automorphisms of small buildings of types $\mathsf{F}_4$ and $\mathsf{E}_6$.
arxiv topic:math.CO
arxiv_dataset-95961803.09467
A Switch to the Concern of User: Importance Coefficient in Utility Distribution and Message Importance Measure cs.IT math.IT math.PR math.ST stat.TH This paper mainly focuses on the utilization frequency in receiving end of communication systems, which shows the inclination of the user about different symbols. When the average number of use is limited, a specific utility distribution is proposed on the best effort in term of fairness, which is also the closest one to occurring probability in the relative entropy. Similar to a switch, its parameter can be selected to make it satisfy different users' requirements: negative parameter means the user focus on high-probability events and positive parameter means the user is interested in small-probability events. In fact, the utility distribution is a measure of message importance in essence. It illustrates the meaning of message importance measure (MIM), and extend it to the general case by selecting the parameter. Numerical results show that this utility distribution characterizes the message importance like MIM and its parameter determines the concern of users.
arxiv topic:cs.IT math.IT math.PR math.ST stat.TH
arxiv_dataset-95971803.09567
The Arches cluster revisited: I. Data presentation and stellar census astro-ph.SR astro-ph.GA Located within the central region of the Galaxy, the Arches cluster appears to be one of the youngest, densest and most massive stellar aggregates within the Milky Way. As such it has the potential to be a uniquely instructive laboratory for the study of star formation in extreme environments and the physics of very massive stars. In order to determine the fundamental physical properties of both cluster and constituent stars, we provide and analyse new HST+VLT near-IR datasets. Stacking multiple epochs of spectroscopy results in the deepest view of the cluster ever obtained, allowing us to to identify candidate giant and main sequence stars for the first time. All cluster members are found to be WNLh or O stars, with the smooth and continuous progression in spectral morphologies from O super-/hypergiants through to the WNLh cohort implying a direct evolutionary connection. Importantly no H-free Wolf-Rayets are found, while no products of binary interaction/mass-transfer may be unambiguously identified, despite the presence of massive binaries within the Arches. We infer a main sequence turn-off around O4-5V, corresponding to ~30-38Msun, while the eclipsing binary F2 implies current masses of ~80Msun and ~60Msun for the WNLh and O hypergiant cohorts, respectively. A cluster age of ~2-3Myr is suggested by the location of the main-sequence turn-off. While the absence of H-free Wolf-Rayets argues against the prior occurrence of SNe, such an age does accommodate such events for exceptionally massive stars. Future progress requires quantitative analysis of cluster members combined with additional spectroscopic observations to better constrain the binary population; nevertheless it is already abundantly clear that the Arches offers an unprecedented insight into the formation, evolution and death of the most massive stars Nature allows to form in the local universe (Abridged).
arxiv topic:astro-ph.SR astro-ph.GA
arxiv_dataset-95981803.09667
Spin subdiffusion in disordered Hubbard chain cond-mat.str-el cond-mat.quant-gas We derive and study the effective spin model that explains the anomalous spin dynamics in the one-dimensional Hubbard model with strong potential disorder. Assuming that charges are localized, we show that spins are delocalized and their subdiffusive transport originates from a singular random distribution of spin exchange interactions. The exponent relevant for the subdiffusion is determined by the Anderson localization length and the density of electrons. While the analytical derivations are valid for low particle density, numerical results for the full model reveal a qualitative agreement up to half-filling.
arxiv topic:cond-mat.str-el cond-mat.quant-gas
arxiv_dataset-95991803.09767
Unifying Dark Matter and Dark Energy with non-Canonical Scalars gr-qc astro-ph.CO hep-ph hep-th Non-canonical scalar fields with the Lagrangian ${\cal L} = X^\alpha - V(\phi)$, possess the attractive property that the speed of sound, $c_s^{2} = (2\,\alpha - 1)^{-1}$, can be exceedingly small for large values of $\alpha$. This allows a non-canonical field to cluster and behave like warm/cold dark matter on small scales. We demonstrate that simple potentials including $V = V_0\coth^2{\phi}$ and a Starobinsky-type potential can unify dark matter and dark energy. Cascading dark energy, in which the potential cascades to lower values in a series of discrete steps, can also work as a unified model. In all of these models the kinetic term $X^\alpha$ plays the role of dark matter, while the potential term $V(\phi)$ plays the role of dark energy.
arxiv topic:gr-qc astro-ph.CO hep-ph hep-th