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The intrinsic stable normal cone
We construct an analog of the intrinsic normal cone of Behrend-Fantechi in the equivariant motivic stable homotopy category over a base-scheme B and construct a fundament class in E-cohomology for any cohomology theory E in SH(B). For affine B, a perfect obstruction theory gives rise to a virtual fundamental class in...
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Globular cluster formation with multiple stellar populations from hierarchical star cluster complexes
Most old globular clusters (GCs) in the Galaxy are observed to have internal chemical abundance spreads in light elements. We discuss a new GC formation scenario based on hierarchical star formation within fractal molecular clouds. In the new scenario, a cluster of bound and unbound star clusters (`star cluster compl...
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Multiple Source Domain Adaptation with Adversarial Training of Neural Networks
While domain adaptation has been actively researched in recent years, most theoretical results and algorithms focus on the single-source-single-target adaptation setting. Naive application of such algorithms on multiple source domain adaptation problem may lead to suboptimal solutions. As a step toward bridging the g...
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OSSOS: V. Diffusion in the orbit of a high-perihelion distant Solar System object
We report the discovery of the minor planet 2013 SY$_{99}$, on an exceptionally distant, highly eccentric orbit. With a perihelion of 50.0 au, 2013 SY$_{99}$'s orbit has a semi-major axis of $730 \pm 40$ au, the largest known for a high-perihelion trans-Neptunian object (TNO), well beyond those of (90377) Sedna and 2...
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Solution of the Lindblad equation for spin helix states
Using Lindblad dynamics we study quantum spin systems with dissipative boundary dynamics that generate a stationary nonequilibrium state with a non-vanishing spin current that is locally conserved except at the boundaries. We demonstrate that with suitably chosen boundary target states one can solve the many-body Lin...
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Global bifurcation map of the homogeneus states in the Gray-Scott model
We study the spatially homogeneous time dependent solutions and their bifurcations of the Gray-Scott model. We find the global map of bifurcations by a combination of rigorous verification of the existence of Takens Bogdanov and a Bautin bifurcations, in the space of two parameters k and F. With the aid of numerical ...
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Stochastic Composite Least-Squares Regression with convergence rate O(1/n)
We consider the minimization of composite objective functions composed of the expectation of quadratic functions and an arbitrary convex function. We study the stochastic dual averaging algorithm with a constant step-size, showing that it leads to a convergence rate of O(1/n) without strong convexity assumptions. Thi...
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Fisher GAN
Generative Adversarial Networks (GANs) are powerful models for learning complex distributions. Stable training of GANs has been addressed in many recent works which explore different metrics between distributions. In this paper we introduce Fisher GAN which fits within the Integral Probability Metrics (IPM) framework...
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Language as a matrix product state
We propose a statistical model for natural language that begins by considering language as a monoid, then representing it in complex matrices with a compatible translation invariant probability measure. We interpret the probability measure as arising via the Born rule from a translation invariant matrix product state...
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On the application of Mattis-Bardeen theory in strongly disordered superconductors
The low energy optical conductivity of conventional superconductors is usually well described by Mattis-Bardeen (MB) theory which predicts the onset of absorption above an energy corresponding to twice the superconducing (SC) gap parameter Delta. Recent experiments on strongly disordered superconductors have challeng...
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Nanoscale Magnetic Imaging using Circularly Polarized High-Harmonic Radiation
This work demonstrates nanoscale magnetic imaging using bright circularly polarized high-harmonic radiation. We utilize the magneto-optical contrast of worm-like magnetic domains in a Co/Pd multilayer structure, obtaining quantitative amplitude and phase maps by lensless imaging. A diffraction-limited spatial resolut...
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Towards integrated superconducting detectors on lithium niobate waveguides
Superconducting detectors are now well-established tools for low-light optics, and in particular quantum optics, boasting high-efficiency, fast response and low noise. Similarly, lithium niobate is an important platform for integrated optics given its high second-order nonlinearity, used for high-speed electro-optic ...
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The Hilbert scheme of 11 points in A^3 is irreducible
We prove that the Hilbert scheme of 11 points on a smooth threefold is irreducible. In the course of the proof, we present several known and new techniques for producing curves on the Hilbert scheme.
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Dynamically reconfigurable metal-semiconductor Yagi-Uda nanoantenna
We propose a novel type of tunable Yagi-Uda nanoantenna composed of metal-dielectric (Ag-Ge) core-shell nanoparticles. We show that, due to the combination of two types of resonances in each nanoparticle, such hybrid Yagi-Uda nanoantenna can operate in two different regimes. Besides the conventional nonresonant opera...
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Synthesis and In Situ Modification of Hierarchical SAPO-34 by PEG with Different Molecular Weights; Application in MTO Process
Modified structures of SAPO-34 were prepared using polyethylene glycol as the mesopores generating agent. The synthesized catalysts were applied in methanol-to-olefins (MTO) process. All modified synthesized catalysts were characterized via XRD, XRF, FESEM, FTIR, N2 adsorption-desorption techniques, and temperature-p...
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Support Feature Machines
Support Vector Machines (SVMs) with various kernels have played dominant role in machine learning for many years, finding numerous applications. Although they have many attractive features interpretation of their solutions is quite difficult, the use of a single kernel type may not be appropriate in all areas of the ...
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Voltage Control Using Eigen Value Decomposition of Fast Decoupled Load Flow Jacobian
Voltage deviations occur frequently in power systems. If the violation at some buses falls outside the prescribed range, it will be necessary to correct the problem by controlling reactive power resources. In this paper, an optimal algorithm is proposed to solve this problem by identifying the voltage buses, that wil...
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Convolutional neural networks for structured omics: OmicsCNN and the OmicsConv layer
Convolutional Neural Networks (CNNs) are a popular deep learning architecture widely applied in different domains, in particular in classifying over images, for which the concept of convolution with a filter comes naturally. Unfortunately, the requirement of a distance (or, at least, of a neighbourhood function) in t...
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Neural Network Multitask Learning for Traffic Flow Forecasting
Traditional neural network approaches for traffic flow forecasting are usually single task learning (STL) models, which do not take advantage of the information provided by related tasks. In contrast to STL, multitask learning (MTL) has the potential to improve generalization by transferring information in training s...
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A note on a new paradox in superluminal signalling
The Tolman paradox is well known as a base for demonstrating the causality violation by faster-than-light signals within special relativity. It is constructed using a two-way exchange of faster-than-light signals between two inertial observers who are in a relative motion receding one from another. Recently a one-way...
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The Compressed Overlap Index
For analysing text algorithms, for computing superstrings, or for testing random number generators, one needs to compute all overlaps between any pairs of words in a given set. The positions of overlaps of a word onto itself, or of two words, are needed to compute the absence probability of a word in a random text, o...
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An intuitive approach to the unified theory of spin-relaxation
Spin-relaxation is conventionally discussed using two different approaches for materials with and without inversion symmetry. The former is known as the Elliott-Yafet (EY) theory and for the latter the D'yakonov-Perel' (DP) theory applies, respectively. We discuss herein a simple and intuitive approach to demonstrate...
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Weighted Random Walk Sampling for Multi-Relational Recommendation
In the information overloaded web, personalized recommender systems are essential tools to help users find most relevant information. The most heavily-used recommendation frameworks assume user interactions that are characterized by a single relation. However, for many tasks, such as recommendation in social networks...
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Understanding the Twitter Usage of Humanities and Social Sciences Academic Journals
Scholarly communication has the scope to transcend the limitations of the physical world through social media extended coverage and shortened information paths. Accordingly, publishers have created profiles for their journals in Twitter to promote their publications and to initiate discussions with public. This paper...
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Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting
Machine learning algorithms, when applied to sensitive data, pose a distinct threat to privacy. A growing body of prior work demonstrates that models produced by these algorithms may leak specific private information in the training data to an attacker, either through the models' structure or their observable behavio...
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Nanoplatelets as material system between strong confinement and weak confinement
Recently, the fabrication of CdSe nanoplatelets became an important research topic. Nanoplatelets are often described as having a similar electronic structure as 2D dimensional quantum wells and are promoted as colloidal quantum wells with monolayer precision width. In this paper, we show, that nanoplatelets are not ...
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Combined Thermal Control and GNC: An Enabling Technology for CubeSat Surface Probes and Small Robots
Advances in GNC, particularly from miniaturized control electronics, reaction-wheels and attitude determination sensors make it possible to design surface probes and small robots to perform surface exploration and science on low-gravity environments. These robots would use their reaction wheels to roll, hop and tumbl...
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Denoising Adversarial Autoencoders
Unsupervised learning is of growing interest because it unlocks the potential held in vast amounts of unlabelled data to learn useful representations for inference. Autoencoders, a form of generative model, may be trained by learning to reconstruct unlabelled input data from a latent representation space. More robust...
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Monodromy map for tropical Dolbeault cohomology
We define monodromy maps for tropical Dolbeault cohomology of algebraic varieties over non-Archimedean fields. We propose a conjecture of Hodge isomorphisms via monodromy maps, and provide some evidence.
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Randomness Evaluation with the Discrete Fourier Transform Test Based on Exact Analysis of the Reference Distribution
In this paper, we study the problems in the discrete Fourier transform (DFT) test included in NIST SP 800-22 released by the National Institute of Standards and Technology (NIST), which is a collection of tests for evaluating both physical and pseudo-random number generators for cryptographic applications. The most c...
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Analogies Explained: Towards Understanding Word Embeddings
Word embeddings generated by neural network methods such as word2vec (W2V) are well known to exhibit seemingly linear behaviour, e.g. the embeddings of analogy "woman is to queen as man is to king" approximately describe a parallelogram. This property is particularly intriguing since the embeddings are not trained to...
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Zero sum partition into sets of the same order and its applications
We will say that an Abelian group $\Gamma$ of order $n$ has the $m$-\emph{zero-sum-partition property} ($m$-\textit{ZSP-property}) if $m$ divides $n$, $m\geq 2$ and there is a partition of $\Gamma$ into pairwise disjoint subsets $A_1, A_2,\ldots , A_t$, such that $|A_i| = m$ and $\sum_{a\in A_i}a = g_0$ for $1 \leq i...
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Strongly Coupled Dark Energy with Warm dark matter vs. LCDM
Cosmologies including strongly Coupled (SC) Dark Energy (DE) and Warm dark matter (SCDEW) are based on a conformally invariant (CI) attractor solution modifying the early radiative expansion. Then, aside of radiation, a kinetic field $\Phi$ and a DM component account for a stationary fraction, $\sim 1\, \%$, of the t...
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Clausal Analysis of First-order Proof Schemata
Proof schemata are a variant of LK-proofs able to simulate various induction schemes in first-order logic by adding so called proof links to the standard first-order LK-calculus. Proof links allow proofs to reference proofs thus giving proof schemata a recursive structure. Unfortunately, applying reductive cut- elimi...
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Emotion Intensities in Tweets
This paper examines the task of detecting intensity of emotion from text. We create the first datasets of tweets annotated for anger, fear, joy, and sadness intensities. We use a technique called best--worst scaling (BWS) that improves annotation consistency and obtains reliable fine-grained scores. We show that emot...
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Modelling the descent of nitric oxide during the elevated stratopause event of January 2013
Using simulations with a whole-atmosphere chemistry-climate model nudged by meteorological analyses, global satellite observations of nitrogen oxide (NO) and water vapour by the Sub-Millimetre Radiometer instrument (SMR), of temperature by the Microwave Limb Sounder (MLS), as well as local radar observations, this st...
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Optimal Evidence Accumulation on Social Networks
A fundamental question in biology is how organisms integrate sensory and social evidence to make decisions. However, few models describe how both these streams of information can be combined to optimize choices. Here we develop a normative model for collective decision making in a network of agents performing a two-a...
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Efficient Data-Driven Geologic Feature Detection from Pre-stack Seismic Measurements using Randomized Machine-Learning Algorithm
Conventional seismic techniques for detecting the subsurface geologic features are challenged by limited data coverage, computational inefficiency, and subjective human factors. We developed a novel data-driven geological feature detection approach based on pre-stack seismic measurements. Our detection method employs...
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Metastable Modular Metastructures for On-Demand Reconfiguration of Band Structures and Non-Reciprocal Wave Propagation
We present a novel approach to achieve adaptable band structures and non-reciprocal wave propagation by exploring and exploiting the concept of metastable modular metastructures. Through studying the dynamics of wave propagation in a chain composed of finite metastable modules, we provide experimental and analysis re...
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Learning to Plan Chemical Syntheses
From medicines to materials, small organic molecules are indispensable for human well-being. To plan their syntheses, chemists employ a problem solving technique called retrosynthesis. In retrosynthesis, target molecules are recursively transformed into increasingly simpler precursor compounds until a set of readily ...
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Projective embedding of pairs and logarithmic K-stability
Let $\hat{L}$ be the projective completion of an ample line bundle $L$ over $D$, a smooth projective manifold. Hwang-Singer \cite{HwangS} have constructed complete CSCK metric on $\hat{L}\backslash D$. When the corresponding \kahler form is in the cohomology class of a rational divisor $A$ and when $L$ has negative C...
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Motion Switching with Sensory and Instruction Signals by designing Dynamical Systems using Deep Neural Network
To ensure that a robot is able to accomplish an extensive range of tasks, it is necessary to achieve a flexible combination of multiple behaviors. This is because the design of task motions suited to each situation would become increasingly difficult as the number of situations and the types of tasks performed by the...
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The evolution of magnetic fields in hot stars
Over the last decade, tremendous strides have been achieved in our understanding of magnetism in main sequence hot stars. In particular, the statistical occurrence of their surface magnetism has been established (~10%) and the field origin is now understood to be fossil. However, fundamental questions remain: how do ...
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Polynomial-Time Methods to Solve Unimodular Quadratic Programs With Performance Guarantees
We develop polynomial-time heuristic methods to solve unimodular quadratic programs (UQPs) approximately, which are known to be NP-hard. In the UQP framework, we maximize a quadratic function of a vector of complex variables with unit modulus. Several problems in active sensing and wireless communication applications...
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Can the Wild Bootstrap be Tamed into a General Analysis of Covariance Model?
It is well known that the F test is severly affected by heteroskedasticity in unbalanced analysis of covariance (ANCOVA) models. Currently available remedies for such a scenario are either based on heteroskedasticity-consistent covariance matrix estimation (HCCME) or bootstrap techniques. However, the HCCME approach ...
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Efficient K-Shot Learning with Regularized Deep Networks
Feature representations from pre-trained deep neural networks have been known to exhibit excellent generalization and utility across a variety of related tasks. Fine-tuning is by far the simplest and most widely used approach that seeks to exploit and adapt these feature representations to novel tasks with limited da...
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The cohomology ring of some Hopf algebras
Let p be a prime, and k be a field of characteristic p. We investigate the algebra structure and the structure of the cohomology ring for the connected Hopf algebras of dimension p^3, which appear in the classification obtained in [V.C. Nguyen, L.-H. Wang and X.-T. Wang, Classification of connected Hopf algebras of d...
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Eckart ro-vibrational Hamiltonians via the gateway Hamilton operator: theory and practice
Recently, a general expression for Eckart-frame Hamilton operators has been obtained by the gateway Hamiltonian method ({\it J. Chem. Phys.} {\bf 142}, 174107 (2015); {\it ibid.} {\bf 143}, 064104 (2015)). The kinetic energy operator in this general Hamiltonian is nearly identical with that of the Eckart-Watson opera...
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Optimal Timing to Trade Along a Randomized Brownian Bridge
This paper studies an optimal trading problem that incorporates the trader's market view on the terminal asset price distribution and uninformative noise embedded in the asset price dynamics. We model the underlying asset price evolution by an exponential randomized Brownian bridge (rBb) and consider various prior di...
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Inflationary Features and Shifts in Cosmological Parameters from Planck 2015 Data
We explore the relationship between features in the Planck 2015 temperature and polarization data, shifts in the cosmological parameters, and features from inflation. Residuals in the temperature data at low multipole $\ell$, which are responsible for the high $H_0\approx 70$ km s$^{-1}$Mpc$^{-1}$ and low $\sigma_8\O...
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Tree based weighted learning for estimating individualized treatment rules with censored data
Estimating individualized treatment rules is a central task for personalized medicine. [zhao2012estimating] and [zhang2012robust] proposed outcome weighted learning to estimate individualized treatment rules directly through maximizing the expected outcome without modeling the response directly. In this paper, we ext...
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Fine-Tuning in the Context of Bayesian Theory Testing
Fine-tuning in physics and cosmology is often used as evidence that a theory is incomplete. For example, the parameters of the standard model of particle physics are "unnaturally" small (in various technical senses), which has driven much of the search for physics beyond the standard model. Of particular interest is ...
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Nuclear physics insights for new-physics searches using nuclei: Neutrinoless $ββ$ decay and dark matter direct detection
Experiments using nuclei to probe new physics beyond the Standard Model, such as neutrinoless $\beta\beta$ decay searches testing whether neutrinos are their own antiparticle, and direct detection experiments aiming to identify the nature of dark matter, require accurate nuclear physics input for optimizing their dis...
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On the (Statistical) Detection of Adversarial Examples
Machine Learning (ML) models are applied in a variety of tasks such as network intrusion detection or Malware classification. Yet, these models are vulnerable to a class of malicious inputs known as adversarial examples. These are slightly perturbed inputs that are classified incorrectly by the ML model. The mitigati...
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Search Rank Fraud De-Anonymization in Online Systems
We introduce the fraud de-anonymization problem, that goes beyond fraud detection, to unmask the human masterminds responsible for posting search rank fraud in online systems. We collect and study search rank fraud data from Upwork, and survey the capabilities and behaviors of 58 search rank fraudsters recruited from...
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Instabilities in Interacting Binary Stars
The types of instability in the interacting binary stars are reviewed. The project "Inter-Longitude Astronomy" is a series of smaller projects on concrete stars or groups of stars. It has no special funds, and is supported from resources and grants of participating organizations, when informal working groups are crea...
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Interaction blockade for bosons in an asymmetric double well
The interaction blockade phenomenon isolates the motion of a single quantum particle within a multi-particle system, in particular for coherent oscillations in and out of a region affected by the blockade mechanism. For identical quantum particles with Bose statistics, the presence of the other particles is still fel...
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SPIDER: CMB polarimetry from the edge of space
SPIDER is a balloon-borne instrument designed to map the polarization of the millimeter-wave sky at large angular scales. SPIDER targets the B-mode signature of primordial gravitational waves in the cosmic microwave background (CMB), with a focus on mapping a large sky area with high fidelity at multiple frequencies....
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Wind Shear and Turbulence on Titan : Huygens Analysis
Wind shear measured by Doppler tracking of the Huygens probe is evaluated, and found to be within the range anticipated by pre-flight assessments (namely less than two times the Brunt-Vaisala frequency). The strongest large-scale shear encountered was ~5 m/s/km, a level associated with 'Light' turbulence in terrestri...
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Composable security in relativistic quantum cryptography
Relativistic protocols have been proposed to overcome some impossibility results in classical and quantum cryptography. In such a setting, one takes the location of honest players into account, and uses the fact that information cannot travel faster than the speed of light to limit the abilities of dishonest agents. ...
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Tensor networks demonstrate the robustness of localization and symmetry protected topological phases
We prove that all eigenstates of many-body localized symmetry protected topological systems with time reversal symmetry have four-fold degenerate entanglement spectra in the thermodynamic limit. To that end, we employ unitary quantum circuits where the number of sites the gates act on grows linearly with the system s...
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Formation of Intermediate-Mass Black Holes through Runaway Collisions in the First Star Clusters
We study the formation of massive black holes in the first star clusters. We first locate star-forming gas clouds in proto-galactic haloes of $\gtrsim \!10^7\,{\rm M}_{\odot}$ in cosmological hydrodynamics simulations and use them to generate the initial conditions for star clusters with masses of $\sim \!10^5\,{\rm ...
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Mean Reverting Portfolios via Penalized OU-Likelihood Estimation
We study an optimization-based approach to con- struct a mean-reverting portfolio of assets. Our objectives are threefold: (1) design a portfolio that is well-represented by an Ornstein-Uhlenbeck process with parameters estimated by maximum likelihood, (2) select portfolios with desirable characteristics of high mean...
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When the cookie meets the blockchain: Privacy risks of web payments via cryptocurrencies
We show how third-party web trackers can deanonymize users of cryptocurrencies. We present two distinct but complementary attacks. On most shopping websites, third party trackers receive information about user purchases for purposes of advertising and analytics. We show that, if the user pays using a cryptocurrency, ...
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Performance Evaluation of Container-based Virtualization for High Performance Computing Environments
Virtualization technologies have evolved along with the development of computational environments since virtualization offered needed features at that time such as isolation, accountability, resource allocation, resource fair sharing and so on. Novel processor technologies bring to commodity computers the possibility...
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An integral formula for the $Q$-prime curvature in 3-dimensional CR geometry
We give an integral formula for the total $Q^\prime$-curvature of a three-dimensional CR manifold with positive CR Yamabe constant and nonnegative Paneitz operator. Our derivation includes a relationship between the Green's functions of the CR Laplacian and the $P^\prime$-operator.
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Intelligent Device Discovery in the Internet of Things - Enabling the Robot Society
The Internet of Things (IoT) is continuously growing to connect billions of smart devices anywhere and anytime in an Internet-like structure, which enables a variety of applications, services and interactions between human and objects. In the future, the smart devices are supposed to be able to autonomously discover ...
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Super-blockers and the effect of network structure on information cascades
Modelling information cascades over online social networks is important in fields from marketing to civil unrest prediction, however the underlying network structure strongly affects the probability and nature of such cascades. Even with simple cascade dynamics the probability of large cascades are almost entirely di...
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Super-Gaussian, super-diffusive transport of multi-mode active matter
Living cells exhibit multi-mode transport that switches between an active, self-propelled motion and a seemingly passive, random motion. Cellular decision-making over transport mode switching is a stochastic process that depends on the dynamics of the intracellular chemical network regulating the cell migration proce...
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Height functions for motives
We define various height functions for motives over number fields. We compare these height functions with classical height functions on algebraic varieties, and also with analogous height functions for variations of Hodge structures on curves over C. These comparisons provide new questions on motives over number fiel...
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On the dimension effect of regularized linear discriminant analysis
This paper studies the dimension effect of the linear discriminant analysis (LDA) and the regularized linear discriminant analysis (RLDA) classifiers for large dimensional data where the observation dimension $p$ is of the same order as the sample size $n$. More specifically, built on properties of the Wishart distri...
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Plasma Wake Accelerators: Introduction and Historical Overview
Fundamental questions on the nature of matter and energy have found answers thanks to the use of particle accelerators. Societal applications, such as cancer treatment or cancer imaging, illustrate the impact of accelerators in our current life. Today, accelerators use metallic cavities that sustain electricfields wi...
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$R$-triviality of some exceptional groups
The main aim of this paper is to prove $R$-triviality for simple, simply connected algebraic groups with Tits index $E_{8,2}^{78}$ or $E_{7,1}^{78}$, defined over a field $k$ of arbitrary characteristic. Let $G$ be such a group. We prove that there exists a quadratic extension $K$ of $k$ such that $G$ is $R$-trivial ...
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Aperture synthesis imaging of the carbon AGB star R Sculptoris: Detection of a complex structure and a dominating spot on the stellar disk
We present near-infrared interferometry of the carbon-rich asymptotic giant branch (AGB) star R Sculptoris. The visibility data indicate a broadly circular resolved stellar disk with a complex substructure. The observed AMBER squared visibility values show drops at the positions of CO and CN bands, indicating that th...
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Intrinsically Sparse Long Short-Term Memory Networks
Long Short-Term Memory (LSTM) has achieved state-of-the-art performances on a wide range of tasks. Its outstanding performance is guaranteed by the long-term memory ability which matches the sequential data perfectly and the gating structure controlling the information flow. However, LSTMs are prone to be memory-band...
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Inferencing into the void: problems with implicit populations Comments on `Empirical software engineering experts on the use of students and professionals in experiments'
I welcome the contribution from Falessi et al. [1] hereafter referred to as F++ , and the ensuing debate. Experimentation is an important tool within empirical software engineering, so how we select participants is clearly a relevant question. Moreover as F++ point out, the question is considerably more nuanced than ...
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NoScope: Optimizing Neural Network Queries over Video at Scale
Recent advances in computer vision-in the form of deep neural networks-have made it possible to query increasing volumes of video data with high accuracy. However, neural network inference is computationally expensive at scale: applying a state-of-the-art object detector in real time (i.e., 30+ frames per second) to ...
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TensorQuant - A Simulation Toolbox for Deep Neural Network Quantization
Recent research implies that training and inference of deep neural networks (DNN) can be computed with low precision numerical representations of the training/test data, weights and gradients without a general loss in accuracy. The benefit of such compact representations is twofold: they allow a significant reduction...
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Information-geometrical characterization of statistical models which are statistically equivalent to probability simplexes
The probability simplex is the set of all probability distributions on a finite set and is the most fundamental object in the finite probability theory. In this paper we give a characterization of statistical models on finite sets which are statistically equivalent to probability simplexes in terms of $\alpha$-famili...
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The Network Nullspace Property for Compressed Sensing of Big Data over Networks
We present a novel condition, which we term the net- work nullspace property, which ensures accurate recovery of graph signals representing massive network-structured datasets from few signal values. The network nullspace property couples the cluster structure of the underlying network-structure with the geometry of ...
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On physically redundant and irrelevant features when applying Lie-group symmetry analysis to hydrodynamic stability analysis
Every linear system of partial differential equations (PDEs) admits a scaling symmetry in its dependent variables. In conjunction with other admitted symmetries of linear type, the associated invariant solution condition poses a linear eigenvalue problem. If this problem is structured such that the spectral theorem a...
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Transforming Musical Signals through a Genre Classifying Convolutional Neural Network
Convolutional neural networks (CNNs) have been successfully applied on both discriminative and generative modeling for music-related tasks. For a particular task, the trained CNN contains information representing the decision making or the abstracting process. One can hope to manipulate existing music based on this '...
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AMTnet: Action-Micro-Tube Regression by End-to-end Trainable Deep Architecture
Dominant approaches to action detection can only provide sub-optimal solutions to the problem, as they rely on seeking frame-level detections, to later compose them into "action tubes" in a post-processing step. With this paper we radically depart from current practice, and take a first step towards the design and im...
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Adaptive Estimation in Structured Factor Models with Applications to Overlapping Clustering
This work introduces a novel estimation method, called LOVE, of the entries and structure of a loading matrix A in a sparse latent factor model X = AZ + E, for an observable random vector X in Rp, with correlated unobservable factors Z \in RK, with K unknown, and independent noise E. Each row of A is scaled and spars...
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Asymptotic profile of solutions for some wave equations with very strong structural damping
We consider the Cauchy problem in R^n for some types of damped wave equations. We derive asymptotic profiles of solutions with weighted L^{1,1}(R^n) initial data by employing a simple method introduced by the first author. The obtained results will include regularity loss type estimates, which are essentially new in ...
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Spontaneous generation of fractional vortex-antivortex pairs at single edges of high-Tc superconductors
Unconventional d-wave superconductors with pair-breaking edges are predicted to have ground states with spontaneously broken time-reversal and translational symmetries. We use the quasiclassical theory of superconductivity to demonstrate that such phases can exist at any single pair-breaking facet. This implies that ...
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A Survey of Neuromorphic Computing and Neural Networks in Hardware
Neuromorphic computing has come to refer to a variety of brain-inspired computers, devices, and models that contrast the pervasive von Neumann computer architecture. This biologically inspired approach has created highly connected synthetic neurons and synapses that can be used to model neuroscience theories as well ...
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Junctions of refined Wilson lines and one-parameter deformation of quantum groups
We study junctions of Wilson lines in refined SU(N) Chern-Simons theory and their local relations. We focus on junctions of Wilson lines in antisymmetric and symmetric powers of the fundamental representation and propose a set of local relations which realize one-parameter deformations of quantum groups $\dot{U}_{q}(...
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Online estimation of the asymptotic variance for averaged stochastic gradient algorithms
Stochastic gradient algorithms are more and more studied since they can deal efficiently and online with large samples in high dimensional spaces. In this paper, we first establish a Central Limit Theorem for these estimates as well as for their averaged version in general Hilbert spaces. Moreover, since having the a...
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The response of the terrestrial bow shock and magnetopause of the long term decline in solar polar fields
The location of the terrestrial magnetopause (MP) and it's subsolar stand-off distance depends not only on the solar wind dynamic pressure and the interplanetary magnetic field (IMF), both of which play a crucial role in determining it's shape, but also on the nature of the processes involved in the interaction betwe...
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Superconductivity of barium-VI synthesized via compression at low temperatures
Using a membrane-driven diamond anvil cell and both ac magnetic susceptibility and electrical resistivity measurements, we have characterized the superconducting phase diagram of elemental barium to pressures as high as 65 GPa. We have determined the superconducting properties of the recently discovered Ba-VI crystal...
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Self-Supervised Damage-Avoiding Manipulation Strategy Optimization via Mental Simulation
Everyday robotics are challenged to deal with autonomous product handling in applications like logistics or retail, possibly causing damage on the items during manipulation. Traditionally, most approaches try to minimize physical interaction with goods. However, we propose to take into account any unintended motion o...
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Adversarial Deep Learning for Robust Detection of Binary Encoded Malware
Malware is constantly adapting in order to avoid detection. Model based malware detectors, such as SVM and neural networks, are vulnerable to so-called adversarial examples which are modest changes to detectable malware that allows the resulting malware to evade detection. Continuous-valued methods that are robust to...
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Simple closed curves, finite covers of surfaces, and power subgroups of Out(F_n)
We construct examples of finite covers of punctured surfaces where the first rational homology is not spanned by lifts of simple closed curves. More generally, for any set $\mathcal{O} \subset F_n$ which is contained in the union of finitely many $Aut(F_n)$-orbits, we construct finite-index normal subgroups of $F_n$ ...
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Hard Mixtures of Experts for Large Scale Weakly Supervised Vision
Training convolutional networks (CNN's) that fit on a single GPU with minibatch stochastic gradient descent has become effective in practice. However, there is still no effective method for training large CNN's that do not fit in the memory of a few GPU cards, or for parallelizing CNN training. In this work we show t...
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Single-hole GPR reflection imaging of solute transport in a granitic aquifer
Identifying transport pathways in fractured rock is extremely challenging as flow is often organized in a few fractures that occupy a very small portion of the rock volume. We demonstrate that saline tracer experiments combined with single-hole ground penetrating radar (GPR) reflection imaging can be used to monitor ...
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Episodic Torque-Luminosity Correlations and Anticorrelations of GX 1+4
We analyse archival CGRO-BATSE X-ray flux and spin frequency measurements of GX 1+4 over a time span of 3000 days. We systematically search for time dependent variations of torque luminosity correlation. Our preliminary results indicate that the correlation shifts from being positive to negative on time scales of few...
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Applications of Fractional Calculus to Newtonian Mechanics
We investigate some basic applications of Fractional Calculus (FC) to Newtonian mechanics. After a brief review of FC, we consider a possible generalization of Newton's second law of motion and apply it to the case of a body subject to a constant force. In our second application of FC to Newtonian gravity, we conside...
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Radial Surface Density Profiles of Gas and Dust in the Debris Disk around 49 Ceti
We present ~0.4 resolution images of CO(3-2) and associated continuum emission from the gas-bearing debris disk around the nearby A star 49 Ceti, observed with the Atacama Large Millimeter/Submillimeter Array (ALMA). We analyze the ALMA visibilities in tandem with the broad-band spectral energy distribution to measur...
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Spontaneously broken translational symmetry at edges of high-temperature superconductors: thermodynamics in magnetic field
We investigate equilibrium properties, including structure of the order parameter, superflow patterns, and thermodynamics of low-temperature surface phases of layered d_{x^2-y^2}-wave superconductors in magnetic field. At zero external magnetic field, time-reversal symmetry and continuous translational symmetry along...
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