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arxiv_dataset-106001812.02426
A Diamond-Photonics Platform Based on Silicon-Vacancy Centers in a Single Crystal Diamond Membrane and a Fiber-Cavity physics.app-ph physics.optics quant-ph We realize a potential platform for an efficient spin-photon interface, namely negatively-charged silicon-vacancy centers in a diamond membrane coupled to the mode of a fully-tunable, fiber-based, optical resonator. We demonstrate that introducing the thin ($\sim 200 \, \text{nm}$), single crystal diamond membrane into the mode of the resonator does not change the cavity properties, which is one of the crucial points for an efficient spin-photon interface. In particular, we observe constantly high Finesse values of up to $3000$ and a linear dispersion in the presence of the membrane. We observe cavity-coupled fluorescence froman ensemble of SiV$^{-}$ centers with an enhancement factor of $\sim 1.9$. Furthermore from our investigations we extract the ensemble absorption and extrapolate an absorption cross section of $(2.9 \, \pm \, 2) \, \cdot \, 10^{-12} \, \text{cm}^{2}$ for a single SiV$^{-}$ center, much higher than previously reported.
arxiv topic:physics.app-ph physics.optics quant-ph
arxiv_dataset-106011812.02526
Hilbert scheme of rational curves on a generic quintic threefold math.AG Let $X_0$ be a generic quintic threefold in projective space $\mathbf P^4$ over the complex numbers. For a fixed natural number $d$, let $R_d(X_0)$ be the open sub-scheme of the Hilbert scheme, parameterizing irreducible rational curves of degree $d$ on $X_0$. In this paper, we show that (1) $R_d(X_0)$ is smooth and of expected dimension, \par (2) Combining the Calabi-Yau condition on $X_0$, we further show that it consists of immersed rational curves. (3) Parts (1) and (2) imply a statement of Clemens' conjecture: if $C_0\in R_d(X_0)$ and $c_0:\mathbf P^1\to C_0$ is the normalization, the \par\hspace{1cc} normal sheaf is isomorphic to the vector bundle $$N_{c_0/X_0}\simeq \mathcal O_{\mathbf P^1}(-1)\oplus \mathcal O_{\mathbf P^1}(-1).$$
arxiv topic:math.AG
arxiv_dataset-106021812.02626
Guided Zoom: Questioning Network Evidence for Fine-grained Classification cs.CV We propose Guided Zoom, an approach that utilizes spatial grounding of a model's decision to make more informed predictions. It does so by making sure the model has "the right reasons" for a prediction, defined as reasons that are coherent with those used to make similar correct decisions at training time. The reason/evidence upon which a deep convolutional neural network makes a prediction is defined to be the spatial grounding, in the pixel space, for a specific class conditional probability in the model output. Guided Zoom examines how reasonable such evidence is for each of the top-k predicted classes, rather than solely trusting the top-1 prediction. We show that Guided Zoom improves the classification accuracy of a deep convolutional neural network model and obtains state-of-the-art results on three fine-grained classification benchmark datasets.
arxiv topic:cs.CV
arxiv_dataset-106031812.02726
Simulation of Stylized Facts in Agent-Based Computational Economic Market Models econ.GN econ.EM q-fin.EC q-fin.TR We study the qualitative and quantitative appearance of stylized facts in several agent-based computational economic market (ABCEM) models. We perform our simulations with the SABCEMM (Simulator for Agent-Based Computational Economic Market Models) tool recently introduced by the authors (Trimborn et al. 2019). Furthermore, we present novel ABCEM models created by recombining existing models and study them with respect to stylized facts as well. This can be efficiently performed by the SABCEMM tool thanks to its object-oriented software design. The code is available on GitHub (Trimborn et al. 2018), such that all results can be reproduced by the reader.
arxiv topic:econ.GN econ.EM q-fin.EC q-fin.TR
arxiv_dataset-106041812.02826
On the Gravitational Instabilities of Protoplanetary Disks astro-ph.EP The gravitational instabilities are important to the evolution of the disks and the planet formation in the disks. We calculate the evolution of the disks which form from the collapse of the molecular cloud cores. By changing the properties of the cloud cores and the hydrodynamical viscosity parameters, we explore their effects on the properties of the gravitational instabilities. We find that the disk is unstable when the angular velocity of the molecular cloud core is larger than a critical value. The time duration of the instability increases as the angular velocity of the core increases. The increase of the hydrodynamical viscosity parameter hardly affects the stability of the disk, but decreases the time duration of the critical state of the gravitational instability in the disk. The instability of the disks can happen at very early time of evolution of the disk, which is consistent with the observations.
arxiv topic:astro-ph.EP
arxiv_dataset-106051812.02926
Astrometric Interferometry astro-ph.IM Astrometry is a powerful technique in astrophysics to measure three-dimensional positions of stars and other astrophysical objects, including exoplanets and the gravitational influence they have on each other. Interferometric astrometry is presented here as just one in a suite of powerful astrometric techniques, which include space-based, seeing-limited and wide-angle adaptive optics techniques. Fundamental limits are discussed, demonstrating that even ground-based techniques have the capability for astrometry at the single micro-arcsecond level, should sufficiently sophisticated instrumentation be constructed for both the current generation of single telescopes and long-baseline optical interferometers.
arxiv topic:astro-ph.IM
arxiv_dataset-106061812.03026
A High-Order Scheme for Image Segmentation via a modified Level-Set method math.NA cs.CV cs.NA In this paper we propose a high-order accurate scheme for image segmentation based on the level-set method. In this approach, the curve evolution is described as the 0-level set of a representation function but we modify the velocity that drives the curve to the boundary of the object in order to obtain a new velocity with additional properties that are extremely useful to develop a more stable high-order approximation with a small additional cost. The approximation scheme proposed here is the first 2D version of an adaptive "filtered" scheme recently introduced and analyzed by the authors in 1D. This approach is interesting since the implementation of the filtered scheme is rather efficient and easy. The scheme combines two building blocks (a monotone scheme and a high-order scheme) via a filter function and smoothness indicators that allow to detect the regularity of the approximate solution adapting the scheme in an automatic way. Some numerical tests on synthetic and real images confirm the accuracy of the proposed method and the advantages given by the new velocity.
arxiv topic:math.NA cs.CV cs.NA
arxiv_dataset-106071812.03126
Polarization diversity phase modulator for measuring frequency-bin entanglement of a biphoton frequency comb in a depolarized channel quant-ph physics.optics Phase modulation has emerged as a technique to create and manipulate high-dimensional frequency-bin entanglement. A necessary step to extending this technique to depolarized channels, such as those in a quantum networking environment, is the ability to perform phase modulation independent of photon polarization. This also necessary to harness hypertanglement in the polarization and frequency degrees of freedom for operations like Bell state discrimination. However, practical phase modulators are generally sensitive to the polarization of light and this makes them unsuited to such applications. We overcome this limitation by implementing a polarization diversity scheme to measure frequency-bin entanglement in arbitrarily polarized photon pairs.
arxiv topic:quant-ph physics.optics
arxiv_dataset-106081812.03226
Towards Effective Exploration/Exploitation in Sequential Music Recommendation cs.IR Music streaming companies collectively serve billions of songs per day. Radio-based music services may intersperse audio advertisements among the songs as a means to generate revenue, much like traditional FM radio. Regardless of the monetization approach, the recommender system should decide when to play content that the listener is known to enjoy (exploit) and content that is novel to the listener (explore). Recommender systems that rely on this explore/exploit type framework have been deployed in a wide variety of applications such as movies, books, music, shopping and more. In this work, we investigate the impact of different ad/song sequences on listener behavior. In particular, we focus on the impact of exploring new song content for the listener given the previous sequence of ads and songs in the listener's session. Our results show that the prior sequence matters when considering song exploration and that this prior sequence has an impact on the listener's tendency to interrupt their current session.
arxiv topic:cs.IR
arxiv_dataset-106091812.03326
Analysis of A Spatially Inhomogeneous Stochastic Partial Differential Equation Epidemic Model math.DS This work proposes and analyzes a family of spatially inhomogeneous epidemic models. This is our first effort to use stochastic partial differential equations (SPDEs) to model epidemic dynamics with spatial variations and environmental noise. After setting up the problem, existence and uniqueness of solutions of the underlying SPDEs are examined. Then definitions of permanence and extinction are given. Certain sufficient conditions are provided for the permanence and extinction. Our hope is that this paper will open up windows for investigation of epidemic models from a new angle.
arxiv topic:math.DS
arxiv_dataset-106101812.03426
Real-Time Referring Expression Comprehension by Single-Stage Grounding Network cs.CV In this paper, we propose a novel end-to-end model, namely Single-Stage Grounding network (SSG), to localize the referent given a referring expression within an image. Different from previous multi-stage models which rely on object proposals or detected regions, our proposed model aims to comprehend a referring expression through one single stage without resorting to region proposals as well as the subsequent region-wise feature extraction. Specifically, a multimodal interactor is proposed to summarize the local region features regarding the referring expression attentively. Subsequently, a grounder is proposed to localize the referring expression within the given image directly. For further improving the localization accuracy, a guided attention mechanism is proposed to enforce the grounder to focus on the central region of the referent. Moreover, by exploiting and predicting visual attribute information, the grounder can further distinguish the referent objects within an image and thereby improve the model performance. Experiments on RefCOCO, RefCOCO+, and RefCOCOg datasets demonstrate that our proposed SSG without relying on any region proposals can achieve comparable performance with other advanced models. Furthermore, our SSG outperforms the previous models and achieves the state-of-art performance on the ReferItGame dataset. More importantly, our SSG is time efficient and can ground a referring expression in a 416*416 image from the RefCOCO dataset in 25ms (40 referents per second) on average with a Nvidia Tesla P40, accomplishing more than 9* speedups over the existing multi-stage models.
arxiv topic:cs.CV
arxiv_dataset-106111812.03526
Path Dependent Optimal Transport and Model Calibration on Exotic Derivatives math.PR math.OC q-fin.MF In this paper, we introduce and develop the theory of semimartingale optimal transport in a path dependent setting. Instead of the classical constraints on marginal distributions, we consider a general framework of path dependent constraints. Duality results are established, representing the solution in terms of path dependent partial differential equations (PPDEs). Moreover, we provide a dimension reduction result based on the new notion of "semifiltrations", which identifies appropriate Markovian state variables based on the constraints and the cost function. Our technique is then applied to the exact calibration of volatility models to the prices of general path dependent derivatives.
arxiv topic:math.PR math.OC q-fin.MF
arxiv_dataset-106121812.03626
EDF: Ensemble, Distill, and Fuse for Easy Video Labeling cs.CV We present a way to rapidly bootstrap object detection on unseen videos using minimal human annotations. We accomplish this by combining two complementary sources of knowledge (one generic and the other specific) using bounding box merging and model distillation. The first (generic) knowledge source is obtained from ensembling pre-trained object detectors using a novel bounding box merging and confidence reweighting scheme. We make the observation that model distillation with data augmentation can train a specialized detector that outperforms the noisy labels it was trained on, and train a Student Network on the ensemble detections that obtains higher mAP than the ensemble itself. The second (specialized) knowledge source comes from training a detector (which we call the Supervised Labeler) on a labeled subset of the video to generate detections on the unlabeled portion. We demonstrate on two popular vehicular datasets that these techniques work to emit bounding boxes for all vehicles in the frame with higher mean average precision (mAP) than any of the reference networks used, and that the combination of ensembled and human-labeled data produces object detections that outperform either alone.
arxiv topic:cs.CV
arxiv_dataset-106131812.03726
Stability preserving approximations of a semilinear hyperbolic gas transport model math.NA We consider the discretization of a semilinear damped wave equation arising, for instance, in the modeling of gas transport in pipeline networks. For time invariant boundary data, the solutions of the problem are shown to converge exponentially fast to steady states. We further prove that this decay behavior is inherited uniformly by a class of Galerkin approximations, including finite element, spectral, and structure preserving model reduction methods. These theoretical findings are illustrated by numerical tests.
arxiv topic:math.NA
arxiv_dataset-106141812.03826
Examples of usage of nearfield acoustic holography methods for far field estimations: Part 1. CW signals eess.AS cs.SD physics.app-ph The paper is devoted to the usage of nearfield acoustic holography methods for estimating far field of the object. An experiment was carried out in anechoic chamber. First, acoustic filed was recorded in a plane that was close to source. This signals records were used to reconstruct the far field by computation routines. Second, the signal in the far field is measured and the results are compared. Several methods are tested and research on possible reduction of the microphone array size is carried out. The most significant reduction of the measurement facility complexity is usage a linear array in stead of the planar array that is made possible due to introduced computation routines
arxiv topic:eess.AS cs.SD physics.app-ph
arxiv_dataset-106151812.03926
Octahedron-Based Projections as Intermediate Representations for Computer Imaging: TOAST, TEA and More astro-ph.IM This paper defines and discusses a set of rectangular all-sky projections which have no singular points, notably the Tesselated Octahedral Adaptive Spherical Transformation (or TOAST) developed initially for the WorldWide Telescope (WWT). These have proven to be useful as intermediate representations for imaging data where the application transforms dynamically from a standardized internal format to a specific format (projection, scaling, orientation, etc.) requested by the user. TOAST is strongly related to the Hierarchical Triangular Mesh (HTM) pixelization and is particularly well adapted to the situations where one wishes to traverse a hierarchy of increasing resolution images. Since it can be recursively computed using a very simple algorithm it is particularly adaptable to use by graphical processing units.
arxiv topic:astro-ph.IM
arxiv_dataset-106161812.04026
A scenario for the Galactic cosmic rays between the knee and the second-knee astro-ph.HE We perform a fit to measurements of the cosmic ray spectrum and of the depth of shower maximum in the energy range between $10^{15}$~eV and $10^{18}$~eV. We consider a Galactic component that is a mixture of five representative nuclear species (H, He, N, Si and Fe), for which we adopt rigidity dependent broken power-law spectra, and we allow for an extragalactic component which becomes strongly suppressed for decreasing energies. The relative abundances of the Galactic components at $10^{15}$~eV are taken to be comparable to those determined by direct measurements at $10^{13}$~eV. The main features of the spectrum and of the composition are reproduced in these scenarios. The spectral knee results from the break of the H spectrum at $E_{\rm k}\simeq 3\times 10^{15}$~eV, although it is broaden by the comparable contribution from He which has a break at about $6\times 10^{15}$~eV. The low-energy ankle at $E_{\rm la}\simeq 2\times 10^{16}$~eV is associated to the strong suppression of the H and He Galactic components and the increasing relative contribution of the heavier ones, but the observed hardening of the spectrum at this energy turns out to result from the growing contribution of the extragalactic component. The second-knee at $E_{\rm sk}\simeq 26 E_{\rm k}\simeq 8\times 10^{16}$~eV is associated with the steepening of the Galactic Fe component. The transition to the regime in which the total cosmic ray flux is dominated by the extragalactic component takes place at an energy of about $10^{17}$~eV. The parameters of the fit depend on the hadronic model that is used to interpret the $X_{\rm max}$ measurements as well as on the specific $X_{\rm max}$ dataset that is considered in the fit. The impact of the possible existence of a maximum rigidity cutoff in the Galactic components is also discussed.
arxiv topic:astro-ph.HE
arxiv_dataset-106171812.04126
Governance in Adaptive Normative Multiagent Systems for the Internet of Smart Things: Challenges and Future Directions cs.SE The rapidly changing environments in which companies operate to support the Internet of Things (IoT) and Autonomous Vehicles is challenging traditional Multi agent System (MAS) approaches. The requirements of these highly dynamic environments gave rise to Adaptive Normative MAS approaches. At the same time, governance is an essential and challenging feature that still needs to be addressed in adaptive normative MAS. Indeed, governance of individual and societal agent behavior in Adaptive Normative MASs is still a vague concept that has not been properly investigated, modeled and implemented. However, governance is fundamental for solving problems involving MAS coordination, organizations and institutions. In this paper, we present our ongoing research towards understanding and improving governance in Adaptive Normative MASs. We also discuss challenges and future directions that will facilitate the development of domain specific smart IoT systems with governance features.
arxiv topic:cs.SE
arxiv_dataset-106181812.04226
Coherent Wave Propagation in Multi-Mode systems with Correlated Noise cond-mat.dis-nn cond-mat.mes-hall physics.optics Imperfections in multimode systems lead to mode-mixing and interferences between propagating modes. Such disorder is typically characterized by a finite correlation time (in quantum evolution) or correlation length (in paraxial evolution). We show that the long-scale dynamics of an initial excitation that spread in mode space can be tailored by the coherent dynamics on short-scale. In particular we unveil a universal crossover from exponential to power-law ballistic-like decay of the initial mode. Our results have applications to various wave physics frameworks, ranging from multimode fiber optics to quantum dots and quantum biology.
arxiv topic:cond-mat.dis-nn cond-mat.mes-hall physics.optics
arxiv_dataset-106191812.04326
Chevalley groups of polynomial rings over Dedekind domains math.KT math.GR Let R be a Dedekind domain, and let G be a simply connected Chevalley-Demazure group scheme of rank =>2. We prove that G(R[x_1,...,x_n])=G(R)E(R[x_1,...,x_n]) for any n=>1. This extends the corresponding results of A. Suslin and F. Grunewald, J. Mennicke, and L. Vaserstein for G=SL_n, Sp_2n. We also deduce some corollaries of the above result for regular rings R of higher dimension and discrete Hodge algebras over R.
arxiv topic:math.KT math.GR
arxiv_dataset-106201812.04426
PDE-Net 2.0: Learning PDEs from Data with A Numeric-Symbolic Hybrid Deep Network cs.LG cs.NA physics.comp-ph stat.ML Partial differential equations (PDEs) are commonly derived based on empirical observations. However, recent advances of technology enable us to collect and store massive amount of data, which offers new opportunities for data-driven discovery of PDEs. In this paper, we propose a new deep neural network, called PDE-Net 2.0, to discover (time-dependent) PDEs from observed dynamic data with minor prior knowledge on the underlying mechanism that drives the dynamics. The design of PDE-Net 2.0 is based on our earlier work \cite{Long2018PDE} where the original version of PDE-Net was proposed. PDE-Net 2.0 is a combination of numerical approximation of differential operators by convolutions and a symbolic multi-layer neural network for model recovery. Comparing with existing approaches, PDE-Net 2.0 has the most flexibility and expressive power by learning both differential operators and the nonlinear response function of the underlying PDE model. Numerical experiments show that the PDE-Net 2.0 has the potential to uncover the hidden PDE of the observed dynamics, and predict the dynamical behavior for a relatively long time, even in a noisy environment.
arxiv topic:cs.LG cs.NA physics.comp-ph stat.ML
arxiv_dataset-106211812.04526
Magnetically inspired explosive outflows from neutron-star mergers astro-ph.HE gr-qc Binary neutron-star mergers have long been associated with short-duration gamma-ray bursts (GRBs). This connection was confirmed with the first coincident detection of gravitational waves together with electromagnetic radiation from GW170817. The basic paradigm for short-duration GRBs includes an ultra-relativistic jet, but the low-luminosity prompt emission together with follow-up radio and X-ray observations have hinted that this picture may be different in the case of GW170817. In particular, it has been proposed that large amounts of the magnetic energy that is amplified after the merger, can be released when the remnant collapses to a black hole, giving rise to a quasi-spherical explosion impacting on the merger ejecta. Through numerical simulations we investigate this scenario for a range of viewing angles, injected energies and matter densities at the time of the collapse. Depending on the magnitude of the energy injection and the remnant density, we find two types of outflows: one with a narrow relativistic core and one with a wide-angle, but mildly relativistic outflow. Furthermore, very wide outflows are possible, but require energy releases in excess of 10^52 erg.
arxiv topic:astro-ph.HE gr-qc
arxiv_dataset-106221812.04626
Optical spectroscopy and demographics of redback millisecond pulsar binaries astro-ph.HE astro-ph.SR We present the first optical spectroscopy of five confirmed (or strong candidate) redback millisecond pulsar binaries, obtaining complete radial velocity curves for each companion star. The properties of these millisecond pulsar binaries with low-mass, hydrogen-rich companions are discussed in the context of the 14 confirmed and 10 candidate field redbacks. We find that the neutron stars in redbacks have a median mass of 1.78 +/- 0.09 M_sun with a dispersion of sigma = 0.21 +/- 0.09. Neutron stars with masses in excess of 2 M_sun are consistent with, but not firmly demanded by, current observations. Redback companions have median masses of 0.36 +/- 0.04 M_sun with a scatter of sigma = 0.15 +/- 0.04, and a tail possibly extending up to 0.7-0.9 M_sun. Candidate redbacks tend to have higher companion masses than confirmed redbacks, suggesting a possible selection bias against the detection of radio pulsations in these more massive candidate systems. The distribution of companion masses between redbacks and the less massive black widows continues to be strongly bimodal, which is an important constraint on evolutionary models for these systems. Among redbacks, the median efficiency of converting the pulsar spindown energy to gamma-ray luminosity is ~10%.
arxiv topic:astro-ph.HE astro-ph.SR
arxiv_dataset-106231812.04726
Polarisabilities from Compton Scattering on 3He nucl-th hep-ph This executive summary of recent theory progress in Compton scattering off 3He focuses on determining neutron polarisabilities; see ref. [2] and references therein for details and a better bibliography. Prepared for the Proceedings of the 22nd International Conference on Few-Body Problems in Physics, Caen 9-13 July 2018.
arxiv topic:nucl-th hep-ph
arxiv_dataset-106241812.04826
Spatial-Temporal Digital Image Correlation: A Unified Framework cs.CV A comprehensive and systematic framework for easily extending and implementing the subset-based spatial-temporal digital image correlation (DIC) algorithm is presented. The framework decouples the three main factors (i.e. shape function, correlation criterion, and optimization algorithm) involved in algorithm implementation of DIC and represents different algorithms in a uniform form. One can freely choose and combine the three factors to meet his own need, or freely add more parameters to extract analytic results. Subpixel translation and a simulated image series with different velocity characters are analyzed using different algorithms based on the proposed framework, confirming the merit of noise suppression and velocity compatibility. An application of mitigating air disturbance due to heat haze using spatial-temporal DIC is given to demonstrate the applicability of the framework.
arxiv topic:cs.CV
arxiv_dataset-106251812.04926
Ancient solutions for Andrews' hypersurface flow math.DG We construct the ancient solutions of the hypersurface flows in Euclidean spaces studied by B. Andrews in 1994. As time $t \rightarrow 0^-$ the solutions collapse to a round point where $0$ is the singular time. But as $t\rightarrow-\infty$ the solutions become more and more oval. Near the center the appropriately-rescaled pointed Cheeger-Gromov limits are round cylinder solutions $S^J \times \mathbb{R}^{n-J}$, $1 \leq J \leq n-1$. These results are the analog of the corresponding results in Ricci flow ($J=n-1$) and mean curvature flow.
arxiv topic:math.DG
arxiv_dataset-106261812.05026
A Fourier-based Picard-iteration approach for a class of McKean-Vlasov SDEs with L\'evy jumps math.PR We consider a class of L\'evy-driven stochastic differential equations (SDEs) with McKean-Vlasov (MK-V) interaction in the drift coefficient. It is assumed that the coefficient is bounded, affine in the state variable, and only measurable in the law of the solution. We study the equivalent functional fixed-point equation for the unknown time-dependent coefficients of the associated Markovian SDE. By proving a contraction property for the functional map in a suitable normed space, we infer existence and uniqueness results for the MK-V SDE, and derive a discretized Picard iteration scheme that approximates the law of the solution through its characteristic function. Numerical illustrations show the effectiveness of our method, which appears to be appropriate to handle the multi-dimensional setting.
arxiv topic:math.PR
arxiv_dataset-106271812.05126
A combinatorial duality between the weak and strong Bruhat orders math.CO In recent work, the authors used an order lowering operator $\nabla$, introduced by Stanley, to prove the strong Sperner property for the weak Bruhat order on the symmetric group. Hamaker, Pechenik, Speyer, and Weigandt interpreted $\nabla$ as a differential operator on Schubert polynomials and used this to prove a new identity for Schubert polynomials and a determinant conjecture of Stanley. In this paper we study a raising operator $\Delta$ for the \emph{strong} Bruhat order, which is in many ways dual to $\nabla$. We prove a Schubert identity dual to that of Hamaker et al. and derive formulas for counting weighted paths in the Hasse diagrams of the strong order which agree with path counting formulas for the weak order. We also show that powers of $\nabla$ and $\Delta$ have the same Smith normal forms, which we describe explicitly, answering a question of Stanley.
arxiv topic:math.CO
arxiv_dataset-106281812.05226
Observation of parity-time symmetry breaking in a single spin system quant-ph A fundamental axiom of quantum mechanics requires the Hamiltonians to be Hermitian which guarantees real eigen-energies and probability conservation. However, a class of non-Hermitian Hamiltonians with Parity-Time ($\mathcal{PT}$) symmetry can still display entirely real spectra. The Hermiticity requirement may be replaced by $\mathcal{PT}$ symmetry to develop an alternative formulation of quantum mechanics. A series of experiments have been carried out with classical systems including optics, electronics, microwaves, mechanics and acoustics. However, there are few experiments to investigate $\mathcal{PT}$ symmetric physics in quantum systems.Here we report the first observation of the $\mathcal{PT}$ symmetry breaking in a single spin system. We have developed a novel method to dilate a general $\mathcal{PT}$ symmetric Hamiltonian into a Hermitian one, which can be realized in a practical quantum system.Then the state evolutions under $\mathcal{PT}$ symmetric Hamiltonians, which range from $\mathcal{PT}$ symmetric unbroken to broken regions, have been experimentally observed with a single nitrogen-vacancy (NV) center in diamond. Due to the universality of the dilation method, our result opens a door for further exploiting and understanding the physical properties of $\mathcal{PT}$ symmetric Hamiltonian in quantum systems.
arxiv topic:quant-ph
arxiv_dataset-106291812.05326
Efficient quantum cluster algorithms for frustrated transverse field Ising antiferromagnets and Ising gauge theories cond-mat.str-el Working within the Stochastic Series Expansion (SSE) framework, we construct efficient quantum cluster algorithms for transverse field Ising antiferromagnets on the pyrochlore lattice and the planar pyrochlore lattice, for the fully frustrated square lattice Ising model in a transverse field (dual to the 2+1 dimensional odd Ising gauge theory), and for a transverse field Ising model with multi-spin interactions on the square lattice, which is dual to a 2+1 dimensional even Ising gauge theory (and reduces to the two dimensional quantum loop model in a certain limit). Our cluster algorithms use a microcanonical update procedure that generalizes and exploits the notion of "pre-marked motifs" introduced earlier in the context of a quantum cluster algorithm for triangular lattice transverse field Ising antiferromagnets. We demonstrate that the resulting algorithms are significantly more efficient than the standard link percolation based quantum cluster approach. We also introduce a new canonical update scheme that leads to a further improvement in measurement of some observables arising from its ability to make one-dimensional clusters in the "imaginary time" direction. Finally, we demonstrate that refinements in the choice of premarking strategies can lead to additional improvements in the efficiency of the microcanonical updates. As a first example of the physics that can be studied using these algorithmic developments, we obtain evidence for a power-law ordered intermediate-temperature phase associated with the two-step melting of long-range order in the fully frustrated square lattice transverse field Ising model.
arxiv topic:cond-mat.str-el
arxiv_dataset-106301812.05426
On the Noether Problem for torsion subgroups of tori math.AG We consider the Noether Problem for stable and retract rationality for the sequence of $d$-torsion subgroups $T[d]$ of a torus $T$, $d\geq 1$. We show that the answer to these questions only depends on $d\pmod{e(T)}$, where $e(T)$ is the period of the generic $T$-torsor. When $T$ is the norm one torus associated to a finite Galois extension, we find all $d$ such that the Noether Problem for retract rationality has a positive solution for $d$. We also give an application to the Grothendieck ring of stacks.
arxiv topic:math.AG
arxiv_dataset-106311812.05526
The spectrum of group-based Latin squares math.CO We construct sequencings for many groups that are a semi-direct product of an odd-order abelian group and a cyclic group of odd prime order. It follows from these constructions that there is a group-based complete Latin square of order $n$ if and only if $n \in \{ 1,2,4\}$ or there is a non-abelian group of order $n$.
arxiv topic:math.CO
arxiv_dataset-106321812.05626
Large Field Ranges from Aligned and Misaligned Winding hep-th We search for effective axions with super-Planckian decay constants in type IIB string models. We argue that such axions can be realised as long winding trajectories in complex-structure moduli space by an appropriate flux choice. Our main findings are: The simplest models with aligned winding in a 2-axion field space fail due to a general no-go theorem. However, equally simple models with misaligned winding, where the effective axion is not close to any of the fundamental axions, appear to work to the best of our present understanding. These models have large decay constants but no large monotonic regions in the potential, making them unsuitable for large-field inflation. We also show that our no-go theorem can be avoided by aligning three or more axions. We argue that, contrary to misaligned models, such models can have both large decay constants and large monotonic regions in the potential. Our results may be used to argue against the refined Swampland Distance Conjecture and strong forms of the axionic Weak Gravity Conjecture. It becomes apparent, however, that realising inflation is by far harder than just producing a light field with large periodicity.
arxiv topic:hep-th
arxiv_dataset-106331812.05726
Theoretical Evaluation of Electronic Density-of-states and Transport Effects on Field Emission from $n$-type Ultrananocrystalline Diamond Films cond-mat.mtrl-sci In the nitrogen-incorporated ultrananocrystalline diamond ((N)UNCD) films, representing an $n$-type highly conductive two-phase material comprised of $sp^3$ diamond grains and $sp^2$-rich graphitic grain boundaries, the current is carried by a high concentration of mobile electrons within the large-volume grain boundary networks. Fabricated in a simple thin-film planar form, (N)UNCD was found to be an efficient field emitter capable of emitting a significant amount of charge starting at the applied electric field as low as a few V/$\mu$m which makes it a promising material for designing electron sources. Despite the semimetallic conduction, field emission (FE) characteristics of this material demonstrate a strong deviation from the Fowler-Nordheim law in a high-current-density regime when (N)UNCD field emitters switch from a diode-like to resistor-like behavior. Such phenomenon resembles the current-density saturation effect in conventional semiconductors. In the present paper, we adapt the formalism developed for conventional semiconductors to study current-density saturation in (N)UNCD field emitters. We provide a comprehensive theoretical investigation of ($i$) the influence of partial penetration of the electric field into the material, ($ii$) transport effects (such as electric-field-dependent mobility), and ($iii$) features of a complex density-of-states structure (position and shape of $\pi-\pi^*$ bands, controlling the concentration of charge carriers) on the FE characteristics of (N)UNCD. We show that the formation of the current-density saturation plateau can be explained by the limited supply of electrons within the impurity $\pi-\pi^*$ bands and decreasing electron mobility in high electric field. Theoretical calculations are consistent with experiment.
arxiv topic:cond-mat.mtrl-sci
arxiv_dataset-106341812.05826
Stimulated plasmon polariton scattering cond-mat.mes-hall The plasmon and phonon polaritons of two-dimensional (2d) and van-der-Waals materials have recently gained substantial interest. Unfortunately, they are notoriously hard to observe in linear response because of their strong confinement, low frequency and longitudinal mode symmetry. Here, we propose a fundamentally new approach of harnessing nonlinear resonant scattering that we call stimulated plasmon polariton scattering (SPPS) in analogy to the opto-acoustic stimulated Brillouin scattering (SBS). We show that SPS allows to excite, amplify and detect 2d plasmon and phonon polaritons all across the THz-range while requiring only optical components in the near-IR or visible range. We present a coupled-mode theory framework for SPS and based on this find that SPS power gains exceed the very top gains observed in on-chip SBS by at least an order of magnitude. This opens exciting new possibilities to fundamental studies of 2d materials and will help closing the THz gap in spectrocopy and information technology.
arxiv topic:cond-mat.mes-hall
arxiv_dataset-106351812.05926
Addendum to: Kolmogorov complexity of sequences of random numbers generated in Bell's experiments (series of outcomes) quant-ph In the mentioned paper we presented results of the estimation of Kolmogorov complexity of sequences of random numbers generated in a famous Bell's experiment, aimed to study the security of QKD. We focused on series of time differences between successive detections of coincidences, and found that randomness cannot be taken for granted. It was then criticized that the theorems that demonstrate the randomness of series produced in Bell's experiments involve series of measurement outcomes, not of measurement times. Here we reply to this objection and present data of series of outcomes, showing that the conclusions in the mentioned paper are valid also in this case.
arxiv topic:quant-ph
arxiv_dataset-106361812.06026
Halo concentrations from extended Press-Schechter merger histories astro-ph.GA We apply the model relating halo concentration to formation history proposed by Ludlow et al. to merger trees generated using an algorithm based on excursion set theory. We find that while the model correctly predicts the median relation between halo concentration and mass, it underpredicts the scatter in concentration at fixed mass. Since the same model applied to N-body merger trees predicts the correct scatter, we postulate that the missing scatter is due to the lack of any environmental dependence in merger trees derived from excursion set theory. We show that a simple modification to the merger tree construction algorithm, which makes merger rates dependent on environment, can increase the scatter by the required amount, and simultaneously provide a qualitatively correct correlation between environment and formation epoch in the excursion set merger trees.
arxiv topic:astro-ph.GA
arxiv_dataset-106371812.06126
Probing neutron star structure via f-mode oscillations and damping in dynamical spacetime models gr-qc astro-ph.HE Gravitational wave and electromagnetic observations can provide new insights into the nature of matter at supra-nuclear densities inside neutron stars. Improvements in electromagnetic and gravitational wave sensing instruments continue to enhance the accuracy with which they can measure the masses, radii, and tidal deformability of neutron stars. These better measurements place tighter constraints on the equation of state of cold matter above nuclear density. In this article, we discuss a complementary approach to get insights into the structure of neutron stars by providing a model prediction for non-linear fundamental eigenmodes (f-modes) and their decay over time, which are thought to be induced by time-dependent tides in neutron star binaries. Building on pioneering studies that relate the properties of f-modes to the structure of neutron stars, we systematically study this link in the non-perturbative regime using models that utilize numerical relativity. Using a suite of fully relativistic numerical relativity simulations of oscillating TOV stars, we establish blueprints for the numerical accuracy needed to accurately compute the frequency and damping times of f-mode oscillations, which we expect to be a good guide for the requirements in the binary case. We show that the resulting f-mode frequencies match established results from linear perturbation theory, but the damping times within numerical errors depart from linear predictions. This work lays the foundation for upcoming studies aimed at a comparison of theoretical models of f-mode signatures in gravitational waves, and their uncertainties with actual gravitational wave data, searching for neutron star binaries on highly eccentric orbits, and probing neutron star structure at high densities.
arxiv topic:gr-qc astro-ph.HE
arxiv_dataset-106381812.06226
A Survey of Privacy Infrastructures and Their Vulnerabilities cs.CR Over the last two decades, the scale and complexity of Anonymous networks and its associated technologies grows exponentially as privacy has become a major concern of individuals. Also, some cyber attackers make use of privacy infrastructures including botnets and Tor to do illegal activities like drug, contraband or DDoS attack. However, anonymous networks are not perfect, there are some methods could exploit the vulnerabilities and track user information. In this paper, we analyze few of privacy infrastructures and their vulnerabilities.
arxiv topic:cs.CR
arxiv_dataset-106391812.06326
Hypercomplex Generalizations of Gaussian-type Measures math.PR The article is devoted to a new type of measures which are hypercomplex generalizations of Gaussian-type measures. The considered such measures are related with solutions of high order hyperbolic PDEs and related Markov processes. Their characteristic functionals are investigated. Cylindrical distributions of these measures are studied.
arxiv topic:math.PR
arxiv_dataset-106401812.06426
Auto-tuning Neural Network Quantization Framework for Collaborative Inference Between the Cloud and Edge cs.DC cs.AI cs.CV cs.NE Recently, deep neural networks (DNNs) have been widely applied in mobile intelligent applications. The inference for the DNNs is usually performed in the cloud. However, it leads to a large overhead of transmitting data via wireless network. In this paper, we demonstrate the advantages of the cloud-edge collaborative inference with quantization. By analyzing the characteristics of layers in DNNs, an auto-tuning neural network quantization framework for collaborative inference is proposed. We study the effectiveness of mixed-precision collaborative inference of state-of-the-art DNNs by using ImageNet dataset. The experimental results show that our framework can generate reasonable network partitions and reduce the storage on mobile devices with trivial loss of accuracy.
arxiv topic:cs.DC cs.AI cs.CV cs.NE
arxiv_dataset-106411812.06526
Nonlinear Dynamics of Spherical Shells Buckling under Step Pressure cond-mat.soft nlin.PS Dynamic buckling is addressed for complete elastic spherical shells subject to a rapidly applied step in external pressure. Insights from the perspective of nonlinear dynamics reveal essential mathematical features of the buckling phenomena. To capture the strong buckling imperfection-sensitivity, initial geometric imperfections in the form of an axisymmetric dimple at each pole are introduced. Dynamic buckling under the step pressure is related to the quasi-static buckling pressure. Both loadings produce catastrophic collapse of the shell for conditions in which the pressure is prescribed. Damping plays an important role in dynamic buckling because of the time-dependent nonlinear interaction among modes, particularly the interaction between the spherically symmetric 'breathing' mode and the buckling mode. In this paper we argue that the precise frequency dependence of the damping does not matter as most of the damping happens at a single frequency (the breathing frequency). In general, there is not a unique step pressure threshold separating responses associated with buckling from those that do not buckle. Instead there exists a cascade of buckling thresholds, dependent on the damping and level of imperfection, separating pressures for which buckling occurs from those for which it does not occur. For shells with small and moderately small imperfections the dynamic step buckling pressure can be substantially below the quasi-static buckling pressure.
arxiv topic:cond-mat.soft nlin.PS
arxiv_dataset-106421812.06626
Designing Adversarially Resilient Classifiers using Resilient Feature Engineering cs.LG cs.CR stat.ML We provide a methodology, resilient feature engineering, for creating adversarially resilient classifiers. According to existing work, adversarial attacks identify weakly correlated or non-predictive features learned by the classifier during training and design the adversarial noise to utilize these features. Therefore, highly predictive features should be used first during classification in order to determine the set of possible output labels. Our methodology focuses the problem of designing resilient classifiers into a problem of designing resilient feature extractors for these highly predictive features. We provide two theorems, which support our methodology. The Serial Composition Resilience and Parallel Composition Resilience theorems show that the output of adversarially resilient feature extractors can be combined to create an equally resilient classifier. Based on our theoretical results, we outline the design of an adversarially resilient classifier.
arxiv topic:cs.LG cs.CR stat.ML
arxiv_dataset-106431812.06726
Machine Learning as a universal tool for quantitative investigations of phase transition cond-mat.stat-mech cond-mat.dis-nn hep-lat physics.comp-ph The problem of identifying the phase of a given system for a certain value of the temperature can be reformulated as a classification problem in Machine Learning. Taking as a prototype the Ising model and using the Support Vector Machine as a tool to classify Monte Carlo generated configurations, we show that the critical region of the system can be clearly identified and the symmetry that drives the transition can be reconstructed from the performance of the learning process. The role of the discrete symmetry of the system in obtaining this result is discussed. A finite size analysis of the learned Support Vector Machine decision function allows us to determine the critical temperature and critical exponents with a precision that is comparable to that of the most efficient numerical approaches relying on a known Hamiltonian description of the system. For the determination of the critical temperature and of the critical exponent connected with the divergence of the correlation length, other than the availability of a range of temperatures having information on both phases, the method we propose does not rest on any physical input on the system, and in particular is agnostic to its Hamiltonian, its symmetry properties and its order parameter. Hence, our investigation provides a first significant step in the direction of devising robust tools for quantitative analyses of phase transitions in cases in which an order parameter is not known.
arxiv topic:cond-mat.stat-mech cond-mat.dis-nn hep-lat physics.comp-ph
arxiv_dataset-106441812.06826
Minimax theorems in a fully non-convex setting math.OC math.FA In this paper, we establish two minimax theorems for functions $f:X\times I\to {\bf R}$, where $I$ is a real interval, without assuming that $f(x,\cdot)$ is quasi-concave. Also, some related applications are presented.
arxiv topic:math.OC math.FA
arxiv_dataset-106451812.06926
Imaging the Thermal and Kinematic Sunyaev-Zel'dovich Effect Signals in a Sample of Ten Massive Galaxy Clusters: Constraints on Internal Velocity Structures and Bulk Velocities astro-ph.CO We have imaged the Sunyaev-Zel'dovich (SZ) effect signals at 140 and 270 GHz towards ten galaxy clusters with Bolocam and AzTEC/ASTE. We also used Planck data to constrain the signal at large angular scales, Herschel-SPIRE images to subtract the brightest galaxies that comprise the cosmic infrared background (CIB), Chandra imaging to map the electron temperature $T_e$ of the intra-cluster medium (ICM), and HST imaging to derive models of each galaxy cluster's mass density. The galaxy clusters gravitationally lens the background CIB, which produced an on-average reduction in brightness towards the galaxy clusters' centers after the brightest galaxies were subtracted. We corrected for this deficit, which was between 5-25% of the 270 GHz SZ effect signal within $R_{2500}$. Using the SZ effect measurements, along with the X-ray constraint on $T_e$, we measured each galaxy cluster's average line of sight (LOS) velocity $v_z$ within $R_{2500}$, with a median per-cluster uncertainty of +-700 km/s. We found an ensemble-mean <$v_z$> of 430+-210 km/s, and an intrinsic cluster-to-cluster scatter $\sigma_{int}$ of 470+-340 km/s. We also obtained maps of $v_z$ over each galaxy cluster's face with an angular resolution of 70". All four galaxy clusters previously identified as having a merger oriented along the LOS showed an excess variance in these maps at a significance of 2-4$\sigma$, indicating an internal $v_z$ rms of $\gtrsim$1000 km/s. None of the six galaxy clusters previously identified as relaxed or plane of sky mergers showed any such excess variance.
arxiv topic:astro-ph.CO
arxiv_dataset-106461812.07026
State Leakage and Coordination with Causal State Knowledge at the Encoder cs.IT math.IT We revisit the problems of state masking and state amplification through the lens of empirical coordination. Specifically, we characterize the rate-equivocation-coordination trade-offs regions of a state-dependent channel in which the encoder has causal and strictly causal state knowledge. We also extend this characterization to the cases of two-sided state information and noisy channel feedback. Our approach is based on the notion of core of the receiver's knowledge, which we introduce to capture what the decoder can infer about all the signals involved in the model. Finally, we exploit the aforementioned results to solve a channel state estimation zero-sum game in which the encoder prevents the decoder to estimate the channel state accurately.
arxiv topic:cs.IT math.IT
arxiv_dataset-106471812.07126
BandNet: A Neural Network-based, Multi-Instrument Beatles-Style MIDI Music Composition Machine cs.SD cs.MM eess.AS In this paper, we propose a recurrent neural network (RNN)-based MIDI music composition machine that is able to learn musical knowledge from existing Beatles' songs and generate music in the style of the Beatles with little human intervention. In the learning stage, a sequence of stylistically uniform, multiple-channel music samples was modeled by a RNN. In the composition stage, a short clip of randomly-generated music was used as a seed for the RNN to start music score prediction. To form structured music, segments of generated music from different seeds were concatenated together. To improve the quality and structure of the generated music, we integrated music theory knowledge into the model, such as controlling the spacing of gaps in the vocal melody, normalizing the timing of chord changes, and requiring notes to be related to the song's key (C major, for example). This integration improved the quality of the generated music as verified by a professional composer. We also conducted a subjective listening test that showed our generated music was close to original music by the Beatles in terms of style similarity, professional quality, and interestingness. Generated music samples are at https://goo.gl/uaLXoB.
arxiv topic:cs.SD cs.MM eess.AS
arxiv_dataset-106481812.07226
Formation of Extremely Low-mass White Dwarfs in Double Degenerates astro-ph.SR Extremely low-mass white dwarfs (ELM WDs) are helium WDs with a mass less than $\sim$$0.3\rm\;M_\odot$. Most ELM WDs are found in double degenerates (DDs) in the ELM Survey led by Brown and Kilic. These systems are supposed to be significant gravitational-wave sources in the mHz frequency. In this paper, we firstly analyzed the observational characteristics of ELM WDs and found that there are two distinct groups in the ELM WD mass and orbital period plane, indicating two different formation scenarios of such objects, i.e. a stable Roche lobe overflow channel (RL channel) and common envelope ejection channel (CE channel). We then systematically investigated the formation of ELM WDs in DDs by a combination of detailed binary evolution calculation and binary population synthesis. Our study shows that the majority of ELM WDs with mass less than $0.22\rm\;M_\odot$ are formed from the RL channel. The most common progenitor mass in this way is in the range of $1.15-1.45\rm\;M_\odot$ and the resulting ELM WDs have a peak around $0.18\rm\;M_\odot$ when selection effects are taken into account, consistent with observations. The ELM WDs with a mass larger than $0.22\rm\;M_\odot$ are more likely to be from the CE channel and have a peak of ELM WD mass around $0.25\rm\;M_\odot$ which needs to be confirmed by future observations. By assuming a constant star formation rate of 2$\rm\;M_\odot yr^{-1}$ for a Milky Way-like galaxy, the birth rate and local density are $5\times10^{-4}\rm\;yr^{-1}$ and $1500\rm\;kpc^{-3}$, respectively, for DDs with an ELM WD mass less than $0.25\rm\;M_\odot$.
arxiv topic:astro-ph.SR
arxiv_dataset-106491812.07326
Longtime behavior and weak-strong uniqueness for a nonlocal porous media equation math.AP In this manuscript we consider a non-local porous medium equation with non-local diffusion effects given by a fractional heat operator \begin{equation*} \partial_t u = \mbox{div}(u\nabla p),\qquad \partial_t p = -(-\Delta)^s p + u^2, \end{equation*} in three space dimensions for $3/4\le s < 1$ and analyze the long time asymptotics. The proof is based on energy methods and leads to algebraic decay towards the stationary solution $u=0$ and $\nabla p=0$ in the $L^2(\mathbb{R}^3)$-norm. The decay rate depends on the exponent $s$. We also show weak-strong uniqueness of solutions and continuous dependence from the initial data. As a side product of our analysis we also show that existence of weak solutions, previously shown in [Caffarelli, Gualdani, Zamponi 2018] for $3/4\le s \le 1$, holds for $1/2 < s\le 1$ if we consider our problem in the torus.
arxiv topic:math.AP
arxiv_dataset-106501812.07426
Dark matter imprint on $^8$B neutrino spectrum hep-ph astro-ph.CO astro-ph.SR The next generation of solar neutrino detectors will provide a precision measure of the $^8$B electron-neutrino spectrum in the energy range from 1-15 MeV. Although the neutrino spectrum emitted by $^8$B $\beta$-decay reactions in the Sun's core is identical to the neutrino spectrum measured in the laboratory, due to vacuum and matter flavor oscillations, this spectrum will be very different from that measured on Earth by the different solar neutrino experiments. We study how the presence of dark matter (DM) in the Sun's core changes the shape of the $^8$B electron-neutrino spectrum. These modifications are caused by local variations of the electronic density and the $^8$B neutrino source, induced by local changes of the temperature, density and chemical composition. Particularly relevant are the shape changes at low and medium energy range $(E_\nu\le 10 {\; \rm MeV})$, for which the experimental noise level is expected to be quite small. If such a distortion in the $^8$B$\nu_e$ spectrum were to be observed, this would strongly hint in favor of the existence of DM in the Sun's core. The $^8$B electron-neutrino spectrum provides a complementary method to helioseismology and total neutrino fluxes for constraining the DM properties. In particular, we study the impact of light asymmetric DM on solar neutrino spectra. Accurate neutrino spectra measurements could help to determine whether light asymmetric DM exists in the Sun's core, since it has been recently advocated that this type of DM might resolve the solar abundance problem.
arxiv topic:hep-ph astro-ph.CO astro-ph.SR
arxiv_dataset-106511812.07526
Consistent Robust Adversarial Prediction for General Multiclass Classification stat.ML cs.LG We propose a robust adversarial prediction framework for general multiclass classification. Our method seeks predictive distributions that robustly optimize non-convex and non-continuous multiclass loss metrics against the worst-case conditional label distributions (the adversarial distributions) that (approximately) match the statistics of the training data. Although the optimized loss metrics are non-convex and non-continuous, the dual formulation of the framework is a convex optimization problem that can be recast as a risk minimization model with a prescribed convex surrogate loss we call the adversarial surrogate loss. We show that the adversarial surrogate losses fill an existing gap in surrogate loss construction for general multiclass classification problems, by simultaneously aligning better with the original multiclass loss, guaranteeing Fisher consistency, enabling a way to incorporate rich feature spaces via the kernel trick, and providing competitive performance in practice.
arxiv topic:stat.ML cs.LG
arxiv_dataset-106521812.07626
Universal Successor Features Approximators cs.LG cs.AI stat.ML The ability of a reinforcement learning (RL) agent to learn about many reward functions at the same time has many potential benefits, such as the decomposition of complex tasks into simpler ones, the exchange of information between tasks, and the reuse of skills. We focus on one aspect in particular, namely the ability to generalise to unseen tasks. Parametric generalisation relies on the interpolation power of a function approximator that is given the task description as input; one of its most common form are universal value function approximators (UVFAs). Another way to generalise to new tasks is to exploit structure in the RL problem itself. Generalised policy improvement (GPI) combines solutions of previous tasks into a policy for the unseen task; this relies on instantaneous policy evaluation of old policies under the new reward function, which is made possible through successor features (SFs). Our proposed universal successor features approximators (USFAs) combine the advantages of all of these, namely the scalability of UVFAs, the instant inference of SFs, and the strong generalisation of GPI. We discuss the challenges involved in training a USFA, its generalisation properties and demonstrate its practical benefits and transfer abilities on a large-scale domain in which the agent has to navigate in a first-person perspective three-dimensional environment.
arxiv topic:cs.LG cs.AI stat.ML
arxiv_dataset-106531812.07726
An endpoint weak-type estimate for multilinear Calder\'on-Zygmund operators math.CA The purpose of this article is to provide an alternative proof of the weak-type $\left(1,\ldots,1;\frac{1}{m}\right)$ estimate for $m$-multilinear Calder\'on-Zygmund operators on $\mathbb{R}^n$ first proved by Grafakos and Torres. Subsequent proofs in the bilinear setting have been given by Maldonado and Naibo and also by P\'erez and Torres. The proof given here is motivated by the proof of the weak-type $(1,1)$ estimate for Calder\'on-Zygmund operators in the nonhomogeneous setting by Nazarov, Treil, and Volberg.
arxiv topic:math.CA
arxiv_dataset-106541812.07826
Two-stage Combinatorial Optimization Problems under Risk cs.DS In this paper a class of combinatorial optimization problems is discussed. It is assumed that a solution can be constructed in two stages. The current first-stage costs are precisely known, while the future second-stage costs are only known to belong to an uncertainty set, which contains a finite number of scenarios with known probability distribution. A partial solution, chosen in the first stage, can be completed by performing an optimal recourse action, after the true second-stage scenario is revealed. A solution minimizing the Conditional Value at Risk (CVaR) measure is computed. Since expectation and maximum are boundary cases of CVaR, the model generalizes the traditional stochastic and robust two-stage approaches, previously discussed in the existing literature. In this paper some new negative and positive results are provided for basic combinatorial optimization problems such as the selection or network problems.
arxiv topic:cs.DS
arxiv_dataset-106551812.07926
Deep laser cooling and efficient magnetic compression of molecules physics.atom-ph We introduce a scheme for deep laser cooling of molecules based on robust dark states at zero velocity. By simulating this scheme, we show it to be a widely applicable method that can reach the recoil limit or below. We demonstrate and characterise the method experimentally, reaching a temperature of 5.4(7) $\mu$K. We solve a general problem of measuring low temperatures for large clouds by rotating the phase-space distribution and then directly imaging the complete velocity distribution. Using the same phase-space rotation method, we rapidly compress the cloud. Applying the cooling method a second time, we compress both the position and velocity distributions.
arxiv topic:physics.atom-ph
arxiv_dataset-106561812.08026
Near-optimal method for highly smooth convex optimization math.OC We propose a near-optimal method for highly smooth convex optimization. More precisely, in the oracle model where one obtains the $p^{th}$ order Taylor expansion of a function at the query point, we propose a method with rate of convergence $\tilde{O}(1/k^{\frac{ 3p +1}{2}})$ after $k$ queries to the oracle for any convex function whose $p^{th}$ order derivative is Lipschitz.
arxiv topic:math.OC
arxiv_dataset-106571812.08126
Generating Diverse and Meaningful Captions cs.CV cs.CL cs.LG Image Captioning is a task that requires models to acquire a multi-modal understanding of the world and to express this understanding in natural language text. While the state-of-the-art for this task has rapidly improved in terms of n-gram metrics, these models tend to output the same generic captions for similar images. In this work, we address this limitation and train a model that generates more diverse and specific captions through an unsupervised training approach that incorporates a learning signal from an Image Retrieval model. We summarize previous results and improve the state-of-the-art on caption diversity and novelty. We make our source code publicly available online.
arxiv topic:cs.CV cs.CL cs.LG
arxiv_dataset-106581812.08226
Towards Plan Transformations for Real-World Pick and Place Tasks cs.RO In this paper, we investigate the possibility of applying plan transformations to general manipulation plans in order to specialize them to the specific situation at hand. We present a framework for optimizing execution and achieving higher performance by autonomously transforming robot's behavior at runtime. We show that plans employed by robotic agents in real-world environments can be transformed, despite their control structures being very complex due to the specifics of acting in the real world. The evaluation is carried out on a plan of a PR2 robot performing pick and place tasks, to which we apply three example transformations, as well as on a large amount of experiments in a fast plan projection environment.
arxiv topic:cs.RO
arxiv_dataset-106591812.08326
Direct observation of corner states in second-order topological photonic crystal slabs cond-mat.mes-hall physics.class-ph Recently, higher-order topological phases that do not obey the usual bulk-edge correspondence principle have been introduced in electronic insulators and brought into classical systems, featuring with in-gap corner/hinge states. So far, second-order topological insulators have been realized in mechanical metamaterials, microwave circuit, topolectrical circuit and acoustic metamaterials. Here, using near-field scanning measurements, we show the direct observation of corner states in second-order topological photonic crystal (PC) slabs consisting of periodic dielectric rods on a perfect electric conductor (PEC). Based on the generalized two-dimensional (2D) Su-Schrieffer-Heeger (SSH) model, we show that the emergence of corner states roots in the nonzero edge dipolar polarization instead of the nonzero bulk quadrupole polarization. We demonstrate the topological transition of 2D Zak phases of PC slabs by tuning intra-cell distances between two neighboring rods. We also directly observe in-gap 1D edge states and 0D corner states in the microwave regime. Our work presents that the PC slab is a powerful platform to directly observe topological states, and paves the way to study higher-order photonic topological insulators.
arxiv topic:cond-mat.mes-hall physics.class-ph
arxiv_dataset-106601812.08426
Monochromatic composite right/left handedness achieved in the quantized composite right/left handed transmission line physics.optics The macro composite right/left handedness (CRLH) accompanies the positive/negative refraction index in the higher, microwave frequency bands in the composite right/left handed transmission line (CRLH-TL), respectively. In this paper, we adjust the refraction index of a quantized CRLH-TL via the squeezed parameters and the electronic components' parameters in the thermal squeezed state, and the refraction index shows the positive/negative jumping around the squeezed angle \(\varphi\)=\(\pi\) when it operates at a single frequency, and the similar result also arises while the refraction index is manipulated by the electronic components' parameters. The monochromatic CRLH achieved here breaks through the original definition in the macro CRLH-TL and provide a new implementation for the CRLH-TL.
arxiv topic:physics.optics
arxiv_dataset-106611812.08526
Equilibrium properties of the lattice system with SALR interaction potential on a square lattice: quasi-chemical approximation versus Monte Carlo simulation cond-mat.soft The lattice system with competing interactions that models biological objects (colloids, ensembles of protein molecules, etc.) is considered. This system is the lattice fluid on a square lattice with attractive interaction between nearest neighbours and repulsive interaction between next-next-nearest neighbours. The geometric order parameter is introduced for describing the ordered phases in this system. The critical value of the order parameter is estimated and the phase diagram of the system is constructed. The simple quasi-chemical approximation (QChA) is proposed for the system under consideration. The data of Monte Carlo simulation of equilibrium properties of the model are compared with the results of QChA. It is shown that QChA provides reasonable semiquantitative results for the systems studied and can be used as the basis for next order approximations.
arxiv topic:cond-mat.soft
arxiv_dataset-106621812.08626
Optimal Stopping under G-expectation math.PR We develop a theory of optimal stopping problems under G-expectation framework. We first define a new kind of random times, called G-stopping times, which is suitable for this problem. For the discrete time case with finite horizon, the value function is defined backwardly and we show that it is the smallest G-supermartingale dominating the payoff process and the optimal stopping time exists. Then we extend this result both to the infinite horizon and to the continuous time case. We also establish the relation between the value function and solution of reflected BSDE driven by G-Brownian motion.
arxiv topic:math.PR
arxiv_dataset-106631812.08726
Mathematical methods for resource-based type theories quant-ph With the wide range of quantum programming languages on offer now, efficient program verification and type checking for these languages presents a challenge -- especially when classical debugging techniques may affect the states in a quantum program. In this work, we make progress towards a program verification approach using the formalism of operational quantum mechanics and resource theories. We present a logical framework that captures two mathematical approaches to resource theory based on monoids (algebraic) and monoidal categories (categorical). We develop the syntax of this framework as an intuitionistic sequent calculus, and prove soundness and completeness of an algebraic and categorical semantics that recover these approaches. We also provide a cut-elimination theorem, normal form, and analogue of Lambek's lifting theorem for polynomial systems over the logics. Using these approaches along with the Curry-Howard-Lambek correspondence for programs, proofs and categories, this work lays the mathematical groundwork for a type checker for some resource theory based frameworks, with the possibility of extending it other quantum programming languages.
arxiv topic:quant-ph
arxiv_dataset-106641812.08826
Chaotic dynamics in a quantum Fermi-Pasta-Ulam problem cond-mat.dis-nn nlin.CD nlin.SI We investigate the emergence of chaotic dynamics in a quantum Fermi - Pasta - Ulam problem for anharmonic vibrations in atomic chains applying semi-quantitative analysis of resonant interactions complemented by exact diagonalization numerical studies. The crossover energy separating chaotic high energy phase and localized (integrable) low energy phase is estimated. It decreases inversely proportionally to the number of atoms until approaching the quantum regime where this dependence saturates. The chaotic behavior appears at lower energies in systems with free or fixed ends boundary conditions compared to periodic systems. The applications of the theory to realistic molecules are discussed.
arxiv topic:cond-mat.dis-nn nlin.CD nlin.SI
arxiv_dataset-106651812.08926
A controllable two-membrane-in-the-middle cavity optomechanical system physics.optics We report an optomechanical system with two dielectric membranes inside a Fabry-Perot cavity. The cavity resonant frequencies are measured in such a two-membrane-in-the-middle system, which show an interesting band-structure-like diagram. This system exhibits great controllability on the parameters of the system. The positions and angles of each membrane can be manipulated on demand by placing two membranes inside the cavity separately. The eigenfrequencies of the vibrational modes of the membranes can also be tuned individually with piezoelectricity. This scheme could be straightforwardly extended to multiple-membrane-in-the-middle systems, where more than two membranes are involved. Such a well controllable multiple membrane optomechanical system provides a promising platform for studying nonlinear and quantum dynamical phenomena in multimode optomechanics with distinct mechanical oscillators.
arxiv topic:physics.optics
arxiv_dataset-106661812.09026
Deep Reinforcement Learning for Real-Time Optimization in NB-IoT Networks cs.NI NarrowBand-Internet of Things (NB-IoT) is an emerging cellular-based technology that offers a range of flexible configurations for massive IoT radio access from groups of devices with heterogeneous requirements. A configuration specifies the amount of radio resource allocated to each group of devices for random access and for data transmission. Assuming no knowledge of the traffic statistics, there exists an important challenge in "how to determine the configuration that maximizes the long-term average number of served IoT devices at each Transmission Time Interval (TTI) in an online fashion". Given the complexity of searching for optimal configuration, we first develop real-time configuration selection based on the tabular Q-learning (tabular-Q), the Linear Approximation based Q-learning (LA-Q), and the Deep Neural Network based Q-learning (DQN) in the single-parameter single-group scenario. Our results show that the proposed reinforcement learning based approaches considerably outperform the conventional heuristic approaches based on load estimation (LE-URC) in terms of the number of served IoT devices. This result also indicates that LA-Q and DQN can be good alternatives for tabular-Q to achieve almost the same performance with much less training time. We further advance LA-Q and DQN via Actions Aggregation (AA-LA-Q and AA-DQN) and via Cooperative Multi-Agent learning (CMA-DQN) for the multi-parameter multi-group scenario, thereby solve the problem that Q-learning agents do not converge in high-dimensional configurations. In this scenario, the superiority of the proposed Q-learning approaches over the conventional LE-URC approach significantly improves with the increase of configuration dimensions, and the CMA-DQN approach outperforms the other approaches in both throughput and training efficiency.
arxiv topic:cs.NI
arxiv_dataset-106671812.09126
On the geometric and magnetic properties of the monomer, dimer and trimer of NiFe2O4 cond-mat.mtrl-sci cond-mat.mes-hall In this work, by employing Density Functional Theory, we compute and discuss some geometric and magnetic properties of the monomer, dimer and trimer of NiFe2 O4 . The calculations are performed at the UDFT/ B3LYP level of calculation, by employing the LANL2DZ effective pseudo potential. The results of the Mulliken spin densities and the spin polarization will be presented. Finally the outcome of the system density of states is considered.
arxiv topic:cond-mat.mtrl-sci cond-mat.mes-hall
arxiv_dataset-106681812.09226
Thermoelectric transport in two-dimensional topological insulator state based on HgTe quantum well cond-mat.mes-hall The thermoelectric response of HgTe quantum wells in the state of two-dimensional topological insulator (2D TI) has been studied experimentally. Ambipolar thermopower, typical for an electron-hole system, has been observed across the charge neutrality point, where the carrier type changes from electrons to holes according to the resistance measurements. The hole-type thermopower is much stronger than the electron-type one. The thermopower linearly increases with temperature. We present a theoretical model which accounts for both the edge and bulk contributions to the electrical conductivity and thermoelectric effect in a 2D TI, including the effects of edge to bulk leakage. The model, contrary to previous theoretical studies, demonstrates that the 2D TI is not expected to show anomalies of thermopower near the band conductivity threshold, which is consistent with our experimental results. Based on the experimental data and theoretical analysis, we conclude that the observed thermopower is mostly of the bulk origin, while the resistance is determined by both the edge and bulk transport.
arxiv topic:cond-mat.mes-hall
arxiv_dataset-106691812.09326
Proton decay matrix element on the lattice with physical pion mass hep-lat hep-ph Proton decay is one of possible signatures of baryon number violation, which has to exist to explain the baryon asymmetry and the existence of nuclear matter. Proton decays must be mediated through effective low-energy baryon number violating operators made of three quarks and a lepton. We calculate matrix elements of these operators between the proton and various meson final states using the direct method. We report on preliminary results of matrix element calculation done with the 2+1 dynamical flavor domain wall fermions at the physical point for the first time.
arxiv topic:hep-lat hep-ph
arxiv_dataset-106701812.09426
Coherence Temperature in the Diluted Periodic Anderson Model cond-mat.str-el cond-mat.dis-nn The Kondo and Periodic Anderson Model (PAM) are known to provide a microscopic picture of many of the fundamental properties of heavy fermion materials and, more generally, a variety of strong correlation phenomena in $4f$ and $5f$ systems. In this paper, we apply the Determinant Quantum Monte Carlo (DQMC) method to include disorder in the PAM, specifically the removal of a fraction $x$ of the localized orbitals. We determine the evolution of the coherence temperature $T^*$, where the local moments and conduction electrons become entwined in a heavy fermion fluid, with $x$ and with the hybridization $V$ between localized and conduction orbitals. We recover several of the principal observed trends in $T^*$ of doped heavy fermions, and also show that, within this theoretical framework, the calculated Nuclear Magnetic Resonance (NMR) relaxation rate tracks the experimentally measured behavior in pure and doped CeCoIn$_5$. Our results contribute to important issues in the interpretation of local probes of disordered, strongly correlated systems.
arxiv topic:cond-mat.str-el cond-mat.dis-nn
arxiv_dataset-106711812.09526
Functional Aggregate Queries with Additive Inequalities cs.DB cs.DS cs.IT cs.LG math.IT Motivated by fundamental applications in databases and relational machine learning, we formulate and study the problem of answering functional aggregate queries (FAQ) in which some of the input factors are defined by a collection of additive inequalities between variables. We refer to these queries as FAQ-AI for short. To answer FAQ-AI in the Boolean semiring, we define relaxed tree decompositions and relaxed submodular and fractional hypertree width parameters. We show that an extension of the InsideOut algorithm using Chazelle's geometric data structure for solving the semigroup range search problem can answer Boolean FAQ-AI in time given by these new width parameters. This new algorithm achieves lower complexity than known solutions for FAQ-AI. It also recovers some known results in database query answering. Our second contribution is a relaxation of the set of polymatroids that gives rise to the counting version of the submodular width, denoted by #subw. This new width is sandwiched between the submodular and the fractional hypertree widths. Any FAQ and FAQ-AI over one semiring can be answered in time proportional to #subw and respectively to the relaxed version of #subw. We present three applications of our FAQ-AI framework to relational machine learning: k-means clustering, training linear support vector machines, and training models using non-polynomial loss. These optimization problems can be solved over a database asymptotically faster than computing the join of the database relations.
arxiv topic:cs.DB cs.DS cs.IT cs.LG math.IT
arxiv_dataset-106721812.09626
Analysis of a SIRI epidemic model with distributed delay and relapse math.CA math.DS q-bio.PE We investigate the global behaviour of a SIRI epidemic model with distributed delay and relapse. From the theory of functional differential equations with delay, we prove that the solution of the system is unique, bounded, and positive, for all time. The basic reproduction number $R_{0}$ for the model is computed. By means of the direct Lyapunov method and LaSalle invariance principle, we prove that the disease free equilibrium is globally asymptotically stable when $R_{0} < 1$. Moreover, we show that there is a unique endemic equilibrium, which is globally asymptotically stable, when $R_{0} > 1$.
arxiv topic:math.CA math.DS q-bio.PE
arxiv_dataset-106731812.09726
Failure of the trilinear operator space Grothendieck theorem math.OA math.FA We give a counterexample to a trilinear version of the operator space Grothendieck theorem. In particular, we show that for trilinear forms on $\ell_\infty$, the ratio of the symmetrized completely bounded norm and the jointly completely bounded norm is in general unbounded, answering a question of Pisier. The proof is based on a non-commutative version of the generalized von Neumann inequality from additive combinatorics.
arxiv topic:math.OA math.FA
arxiv_dataset-106741812.09826
Fast configuration-interaction calculations for nobelium and ytterbium physics.atom-ph We calculate excitation energies for low states of nobelium, including states with open $5f$ subshell. An efficient version of the many-electron configuration-interaction method for treating the atom as a sixteen external electrons system has been developed and used. The method is tested on calculations for ytterbium which has external electron structure similar to nobelium. The results for nobelium are important for prediction of its spectrum and for interpretation of recent measurements. Ytterbium is mostly used to study the features of the method.
arxiv topic:physics.atom-ph
arxiv_dataset-106751812.09926
SNAS: Stochastic Neural Architecture Search cs.LG cs.AI stat.ML We propose Stochastic Neural Architecture Search (SNAS), an economical end-to-end solution to Neural Architecture Search (NAS) that trains neural operation parameters and architecture distribution parameters in same round of back-propagation, while maintaining the completeness and differentiability of the NAS pipeline. In this work, NAS is reformulated as an optimization problem on parameters of a joint distribution for the search space in a cell. To leverage the gradient information in generic differentiable loss for architecture search, a novel search gradient is proposed. We prove that this search gradient optimizes the same objective as reinforcement-learning-based NAS, but assigns credits to structural decisions more efficiently. This credit assignment is further augmented with locally decomposable reward to enforce a resource-efficient constraint. In experiments on CIFAR-10, SNAS takes less epochs to find a cell architecture with state-of-the-art accuracy than non-differentiable evolution-based and reinforcement-learning-based NAS, which is also transferable to ImageNet. It is also shown that child networks of SNAS can maintain the validation accuracy in searching, with which attention-based NAS requires parameter retraining to compete, exhibiting potentials to stride towards efficient NAS on big datasets. We have released our implementation at https://github.com/SNAS-Series/SNAS-Series.
arxiv topic:cs.LG cs.AI stat.ML
arxiv_dataset-106761812.10026
Induction, Coinduction, and Fixed Points: A Concise Comparative Survey cs.LO cs.PL math.CT In this survey article (which hitherto is an ongoing work-in-progress) we present the formulation of the induction and coinduction principles using the language and conventions of each of order theory, set theory, programming languages' type theory, first-order logic, and category theory, for the purpose of examining some of the similarities and, more significantly, the dissimilarities between these various mathematical disciplines, and hence shed some light on the precise relation between these disciplines. Towards that end, in this article we discuss plenty of related concepts, such as fixed points, pre-fixed points, post-fixed points, inductive sets and types, coinductive sets and types, algebras and coalgebras. We conclude the survey by hinting at the possibility of a more abstract and unified treatment that uses concepts from category theory such as monads and comonads.
arxiv topic:cs.LO cs.PL math.CT
arxiv_dataset-106771812.10126
Multifaceted nonlinear dynamics in $\mathcal{PT}$-symmetric coupled Li\'{e}nard oscillators nlin.CD We propose a generalized parity-time ($\mathcal{PT}$) -symmetric Li\'enard oscillator with two different orders of nonlinear position-dependent dissipation. We study the stability of the stationary states by using the eigenvalues of Jacobian and evaluate the stability threshold thereafter. In the first order nonlinear damping model, we discover that the temporal evolution of both gain and lossy oscillators attains a complete convergence towards the stable stationary state leading to the emergence of oscillation and amplitude deaths. Also, the system displays a remarkable manifestation of transient chaos in the lossy oscillator while the gain counterpart exhibits blow-up dynamics for certain choice of initial conditions and control parameters. Employing an external driving force on the loss oscillator, we find that the blow-up dynamics can be controlled and a pure aperiodic state is achievable. On the other hand, the second order nonlinear damping model yields a completely different dynamics on contrary to the first order where the former reveals a conventional quasi-periodic route to chaos upon decreasing the natural frequency of both gain and loss oscillators. An electronic circuit scheme for the experimental realization of the proposed system has also been put forward.
arxiv topic:nlin.CD
arxiv_dataset-106781812.10226
Geometric construction of Heisenberg-Weil representations for finite unitary groups and Howe correspondences math.RT math.NT We give a geometric construction of the Heisenberg-Weil representation of a finite unitary group by the middle \'{e}tale cohomology of an algebraic variety over a finite field, whose rational points give a unitary Heisenberg group. Using also a Frobenius action, we give a geometric realization of the Howe correspondence for $(\mathit{Sp}_{2n},O_2^-)$ over any finite field including characteristic two. As an application, we show that unipotency is preserved under the Howe correspondence.
arxiv topic:math.RT math.NT
arxiv_dataset-106791812.10326
Equivalent Choice Functions and Stable Mechanisms econ.TH We study conditions for the existence of stable and group-strategy-proof mechanisms in a many-to-one matching model with contracts if students' preferences are monotone in contract terms. We show that "equivalence", properly defined, to a choice profile under which contracts are substitutes and the law of aggregate holds is a necessary and sufficient condition for the existence of a stable and group-strategy-proof mechanism. Our result can be interpreted as a (weak) embedding result for choice functions under which contracts are observable substitutes and the observable law of aggregate demand holds.
arxiv topic:econ.TH
arxiv_dataset-106801812.10426
Stochastic Trust Region Inexact Newton Method for Large-scale Machine Learning cs.LG stat.ML Nowadays stochastic approximation methods are one of the major research direction to deal with the large-scale machine learning problems. From stochastic first order methods, now the focus is shifting to stochastic second order methods due to their faster convergence and availability of computing resources. In this paper, we have proposed a novel Stochastic Trust RegiOn Inexact Newton method, called as STRON, to solve large-scale learning problems which uses conjugate gradient (CG) to inexactly solve trust region subproblem. The method uses progressive subsampling in the calculation of gradient and Hessian values to take the advantage of both, stochastic and full-batch regimes. We have extended STRON using existing variance reduction techniques to deal with the noisy gradients and using preconditioned conjugate gradient (PCG) as subproblem solver, and empirically proved that they do not work as expected, for the large-scale learning problems. Finally, our empirical results prove efficacy of the proposed method against existing methods with bench marked datasets.
arxiv topic:cs.LG stat.ML
arxiv_dataset-106811812.10526
Cosmological constant problem: deflation during inflation gr-qc hep-th We argue that the discrepancy between the Planck mass scale and the observed value of the cosmological constant can be largely attenuated if those quantities are understood as a result of effective, and thus scale-dependent, couplings. We exemplify this mechanism for the early inflationary epoch of the universe by solving the corresponding effective gap equations, subject to an energy condition. Several non-trivial checks and extensions are discussed. A comparison of our results to the renormalization group flow, obtained within the asymptotic safety program reveals a stunning agreement.
arxiv topic:gr-qc hep-th
arxiv_dataset-106821812.10626
The Tensor Theory of Connections math.GM This paper extends the univariate Theory of Connections, introduced in (Mortari,2017), to the multivariate case on rectangular domains with detailed attention to the bivariate case. In particular, it generalizes the bivariate Coons surface, introduced by (Coons,1984), by providing analytical expressions, called "constrained expressions," representing all possible surfaces with assigned boundary constraints in terms of functions and arbitrary-order derivatives. In two dimensions, these expressions, which contain a freely chosen function, g(x,y), satisfy all constraints no matter what the g(x,y) is. The boundary constraints considered in this article are Dirichlet, Neumann, and any combinations of them. Although the focus of this article is on two-dimensional spaces, the final section introduces the "Tensor Theory of Connections," validated by mathematical proof. This represents the multivariate extension of the Theory of Connections subject to arbitrary-order derivative constraints in rectangular domains. The main task of this paper is to provide an analytical procedure to obtain constrained expressions in any space that can be used to transform constrained problems into unconstrained problems. This theory is proposed mainly to better solve PDEs and stochastic differential equations.
arxiv topic:math.GM
arxiv_dataset-106831812.10726
The simplicial volume of mapping tori of 3-manifolds math.GT math.AT math.GR We prove that any mapping torus of a closed 3-manifold has zero simplicial volume. When the fiber is a prime 3-manifold, classification results can be applied to show vanishing of the simplicial volume, however the case of reducible fibers is by far more subtle. We thus analyse the possible self-homeomorphisms of reducible 3-manifolds, and use this analysis to produce an explicit representative of the fundamental class of the corresponding mapping tori. To this end, we introduce a new technique for understanding self-homeomorphisms of connected sums in arbitrary dimensions on the level of classifying spaces and for computing the simplicial volume. In particular, we extend our computations to mapping tori of certain connected sums in higher dimensions. Our main result completes the picture for the vanishing of the simplicial volume of fiber bundles in dimension four. Moreover, we deduce that dimension four together with the trivial case of dimension two are the only dimensions where all mapping tori have vanishing simplicial volume. As a group theoretic consequence, we derive an alternative proof of the fact that the fundamental group $G$ of a mapping torus of a 3-manifold $M$ is Gromov hyperbolic if and only if $M$ is virtually a connected sum $\# S^2\times S^1$ and $G$ does not contain $\mathbb{Z}^2$.
arxiv topic:math.GT math.AT math.GR
arxiv_dataset-106841812.10826
Bohm-Bell type experiments: Classical probability approach to (no-)signaling and applications to quantum physics and psychology quant-ph math-ph math.MP math.PR We consider the problem of representation of quantum states and observables in the framework of classical probability theory (Kolmogorov's measure-theoretic axiomatics, 1933). Our aim is to show that, in spite of the common opinion, correlations of observables $A_1, A_2$ and $B_1,B_2$ involved in the experiments of the Bohm-Bell type can be expressed as correlations of classical random variables $a_1, a_2$ and $b_1, b_2.$ The crucial point is that correlations $\langle A_i, B_j \rangle$ should be treated as conditional on the selection of the pairs $(i, j).$ The setting selection procedure is based on two random generators $R_A$ and $R_B.$ They are also considered as observables, supplementary to the "basic observables" $A_1, A_2$ and $B_1, B_2.$ These observables are absent in the standard description, e.g., in the scheme for derivation of the CHSH-inequality. We represent them by classical random variables $r_a$ and $r_b.$ Following the recent works of Dzhafarov and collaborators, we apply our conditional correlation approach to characterize (no-)signaling in the classical probabilistic framework. Consideration the Bohm-Bell experimental scheme in the presence of signaling is important for applications outside quantum mechanics, e.g., in psychology and social science.
arxiv topic:quant-ph math-ph math.MP math.PR
arxiv_dataset-106851812.10926
HUOPM: High Utility Occupancy Pattern Mining cs.DB Mining useful patterns from varied types of databases is an important research topic, which has many real-life applications. Most studies have considered the frequency as sole interestingness measure for identifying high quality patterns. However, each object is different in nature. The relative importance of objects is not equal, in terms of criteria such as the utility, risk, or interest. Besides, another limitation of frequent patterns is that they generally have a low occupancy, i.e., they often represent small sets of items in transactions containing many items, and thus may not be truly representative of these transactions. To extract high quality patterns in real life applications, this paper extends the occupancy measure to also assess the utility of patterns in transaction databases. We propose an efficient algorithm named High Utility Occupancy Pattern Mining (HUOPM). It considers user preferences in terms of frequency, utility, and occupancy. A novel Frequency-Utility tree (FU-tree) and two compact data structures, called the utility-occupancy list and FU-table, are designed to provide global and partial downward closure properties for pruning the search space. The proposed method can efficiently discover the complete set of high quality patterns without candidate generation. Extensive experiments have been conducted on several datasets to evaluate the effectiveness and efficiency of the proposed algorithm. Results show that the derived patterns are intelligible, reasonable and acceptable, and that HUOPM with its pruning strategies outperforms the state-of-the-art algorithm, in terms of runtime and search space, respectively.
arxiv topic:cs.DB
arxiv_dataset-106861812.11026
Hybrid Wasserstein Distance and Fast Distribution Clustering stat.ME We define a modified Wasserstein distance for distribution clustering which inherits many of the properties of the Wasserstein distance but which can be estimated easily and computed quickly. The modified distance is the sum of two terms. The first term --- which has a closed form --- measures the location-scale differences between the distributions. The second term is an approximation that measures the remaining distance after accounting for location-scale differences. We consider several forms of approximation with our main emphasis being a tangent space approximation that can be estimated using nonparametric regression. We evaluate the strengths and weaknesses of this approach on simulated and real examples.
arxiv topic:stat.ME
arxiv_dataset-106871812.11126
Spontaneous localization in self-focusing of ultrashort light pulses physics.optics This is a summary directed to PhD students of the research work conducted on the problem of the production of "light bullets", or multidimensional wave packets that propagate without distortion in unbounded, homogeneous, nonlinear media, and on the actual nature of the self-localized light wave packets spontaneously generated in self-focusing experiments with ultrashort pulses.
arxiv topic:physics.optics
arxiv_dataset-106881812.11226
Fast Training Algorithms for Deep Convolutional Fuzzy Systems with Application to Stock Index Prediction q-fin.ST cs.LG A deep convolutional fuzzy system (DCFS) on a high-dimensional input space is a multi-layer connection of many low-dimensional fuzzy systems, where the input variables to the low-dimensional fuzzy systems are selected through a moving window across the input spaces of the layers. To design the DCFS based on input-output data pairs, we propose a bottom-up layer-by-layer scheme. Specifically, by viewing each of the first-layer fuzzy systems as a weak estimator of the output based only on a very small portion of the input variables, we design these fuzzy systems using the WM Method. After the first-layer fuzzy systems are designed, we pass the data through the first layer to form a new data set and design the second-layer fuzzy systems based on this new data set in the same way as designing the first-layer fuzzy systems. Repeating this process layer-by-layer we design the whole DCFS. We also propose a DCFS with parameter sharing to save memory and computation. We apply the DCFS models to predict a synthetic chaotic plus random time-series and the real Hang Seng Index of the Hong Kong stock market.
arxiv topic:q-fin.ST cs.LG
arxiv_dataset-106891812.11326
QoS-aware Full-duplex Concurrent Scheduling for Millimeter Wave Wireless Backhaul Networks cs.NI The development of self-interference (SI) cancelation technology makes full-duplex (FD) communication possible. Considering the quality of service (QoS) of flows in small cells densely deployed scenario with limited time slot (TS) resources, this paper introduces the FD communication into the concurrent scheduling problem of millimeter-wave (mmWave) wireless backhaul network. We propose a QoS-aware FD concurrent scheduling algorithm to maximize the number of flows with their QoS requirements satisfied. Based on the contention graph, the algorithm makes full use of the FD condition. Both residual self-interference (RSI) and multi-user interference (MUI) are considered. Besides, it also fully considers the QoS requirements of flows and ensures the flows can be transmitted at high rates. Extensive simulations at 60GHz demonstrate that with high SI cancelation level and appropriate contention threshold, the proposed FD algorithm can achieve superior performance in terms of the number of flows with their QoS requirements satisfied and the system throughput compared with other stateof-of-the-art schemes.
arxiv topic:cs.NI
arxiv_dataset-106901812.11426
Performance and Moli`ere radius measurements using a compact prototype of LumiCal in an electron test beam physics.ins-det A new design of a detector plane of sub-millimetre thickness for an electromagnetic sampling calorimeter is presented. It is intended to be used in the luminometers LumiCal and BeamCal in future linear $e^+e^-$ collider experiments. The detector planes were produced utilising novel connectivity scheme technologies. They were installed in a compact prototype of the calorimeter and tested at DESY with an electron beam of energy 1-5 GeV. The performance of a prototype of a compact LumiCal comprising eight detector planes was studied. The effective Moli`ere radius at 5 GeV was determined to be (8.1 +/- 0.1 (stat) +/- 0.3 (syst)) mm, a value well reproduced by the Monte Carlo (MC) simulation (8.4 +/- 0.1) mm. The dependence of the effective Moli`ere radius on the electron energy in the range 1-5 GeV was also studied. Good agreement was obtained between data and MC simulation.
arxiv topic:physics.ins-det
arxiv_dataset-106911812.11526
Improving forecasting accuracy of time series data using a new ARIMA-ANN hybrid method and empirical mode decomposition cs.LG stat.ML Many applications in different domains produce large amount of time series data. Making accurate forecasting is critical for many decision makers. Various time series forecasting methods exist which use linear and nonlinear models separately or combination of both. Studies show that combining of linear and nonlinear models can be effective to improve forecasting performance. However, some assumptions that those existing methods make, might restrict their performance in certain situations. We provide a new Autoregressive Integrated Moving Average (ARIMA)-Artificial Neural Network(ANN) hybrid method that work in a more general framework. Experimental results show that strategies for decomposing the original data and for combining linear and nonlinear models throughout the hybridization process are key factors in the forecasting performance of the methods. By using appropriate strategies, our hybrid method can be an effective way to improve forecasting accuracy obtained by traditional hybrid methods and also either of the individual methods used separately.
arxiv topic:cs.LG stat.ML
arxiv_dataset-106921812.11626
Unfolding quantum master equation into a system of real-valued equations: computationally effective expansion over the basis of $SU(N)$ generators quant-ph Dynamics of an open $N$-state quantum system is typically modeled with a Markovian master equation describing the evolution of the system's density operator. By using generators of $SU(N)$ group as a basis, the density operator can be transformed into a real-valued 'Bloch vector'. The Lindbladian, a super-operator which serves a generator of the evolution, %in the master equation, can be expanded over the same basis and recast in the form of a real matrix. Together, these expansions result is a non-homogeneous system of $N^2-1$ real-valued linear differential equations for the Bloch vector. Now one can, e.g., implement a high-performance parallel simplex algorithm to find a solution of this system which guarantees exact preservation of the norm and Hermiticity of the density matrix. However, when performed in a straightforward way, the expansion turns to be an operation of the time complexity $\mathcal{O}(N^{10})$. The complexity can be reduced when the number of dissipative operators is independent of $N$, which is often the case for physically meaningful models. Here we present an algorithm to transform quantum master equation into a system of real-valued differential equations and propagate it forward in time. By using a scalable model, we evaluate computational efficiency of the algorithm and demonstrate that it is possible to handle the model system with $N = 10^3$ states on a single node of a computer cluster.
arxiv topic:quant-ph
arxiv_dataset-106931812.11726
Three-partition Hodge integrals and the topological vertex math-ph hep-th math.AG math.MP math.QA nlin.SI A conjecture on the relation between the cubic Hodge integrals and the topological vertex in topological string theory is resolved. A central role is played by the notion of generalized shift symmetries in a fermionic realization of the two-dimensional quantum torus algebra. These algebraic relations of operators in the fermionic Fock space are used to convert generating functions of the cubic Hodge integrals and the topological vertex to each other. As a byproduct, the generating function of the cubic Hodge integrals at special values of the parameters therein is shown to be a tau function of the generalized KdV (aka Gelfand-Dickey) hierarchies.
arxiv topic:math-ph hep-th math.AG math.MP math.QA nlin.SI
arxiv_dataset-106941812.11826
UAV Base Station Location Optimization for Next Generation Wireless Networks: Overview and Future Research Directions cs.NI Unmanned aerial vehicles mounted base stations (UAV-BSs) are expected to become one of the significant components of the Next Generation Wireless Networks (NGWNs). Rapid deployment, mobility, higher chances of unobstructed propagation path, and flexibility features of UAV-BSs have attracted significant attention. Despite, potentially, high gains brought by UAV-BSs in NGWNs, many challenges are also introduced by them. Optimal location assignment to UAV-BSs, arguably, is the most widely investigated problem in the literature on UAV-BSs in NGWNs. This paper presents a comprehensive survey of the literature on the location optimization of UAV-BSs in NGWNs. A generic optimization framework through a universal Mixed Integer Non-Linear Programming (MINLP) formulation is constructed and the specifications of its constituents are elaborated. The generic problem is classified into a novel taxonomy. Due to the highly challenging nature of the optimization problem a range of solutions are adopted in the literature which are also covered under the aforementioned classification. Furthermore, future research directions on UAV-BS location optimization in 5G and beyond non-terrestrial aerial communication systems are discussed.
arxiv topic:cs.NI
arxiv_dataset-106951812.11926
On the maximal function associated to the spherical means on the Heisenberg group math.CA In this paper we deal with lacunary and full versions of the spherical maximal function on the Heisenberg group $\mathbb{H}^n$, for $n\ge 2$. By suitable adaptation of an approach developed by M. Lacey in the Euclidean case, we obtain sparse bounds for these maximal functions, which lead to new unweighted and weighted estimates. In particular, we deduce the $L^p$ boundedness, for $1<p<\infty$, of the lacunary maximal function associated to the spherical means on the Heisenberg group. In order to prove the sparse bounds, we establish $ L^p-L^q $ estimates for local (single scale) variants of the spherical means.
arxiv topic:math.CA
arxiv_dataset-106961901.00053
Spanning 2-Forests and Resistance Distance in 2-Connected Graphs math.CO A spanning 2-forest separating vertices $u$ and $v$ of an undirected connected graph is a spanning forest with 2 components such that $u$ and $v$ are in distinct components. Aside from their combinatorial significance, spanning 2-forests have an important application to the calculation of resistance distance or effective resistance. The resistance distance between vertices $u$ and $v$ in a graph representing an electrical circuit with unit resistance on each edge is the number of spanning 2-forests separating $u$ and $v$ divided by the number of spanning trees in the graph. There are also well-known matrix theoretic methods for calculating resistance distance, but the way in which the structure of the underlying graph determines resistance distance via these methods is not well understood. For any connected graph $G$ with a 2-separator separating vertices $u$ and $v$, we show that the number of spanning trees and spanning 2-forests separating $u$ and $v$ can be expressed in terms of these same quantities for the smaller separated graphs, which makes computation significantly more tractable. An important special case is the preservation of the number of spanning 2-forests if $u$ and $v$ are in the same smaller graph. In this paper we demonstrate that this method of calculating resistance distance is more suitable for certain structured families of graphs than the more standard methods. We apply our results to count the number of spanning 2-forests and calculate the resistance distance in a family of Sierpinski triangles and in the family of linear 2-trees with a single bend.
arxiv topic:math.CO
arxiv_dataset-106971901.00153
Occupation time statistics of a gas of interacting diffusing particles cond-mat.stat-mech The time which a diffusing particle spends in a certain region of space is known as the occupation time, or the residence time. Recently the joint occupation time statistics of an ensemble of non-interacting particles was addressed using the single-particle statistics. Here we employ the Macroscopic Fluctuation Theory (MFT) to study the occupation time statistics of many \emph{interacting} particles. We find that interactions can significantly change the statistics and, in some models, even cause a singularity of the large-deviation function describing these statistics. This singularity can be interpreted as a dynamical phase transition. We also point out to a close relation between the MFT description of the occupation-time statistics of non-interacting particles and the level 2 large deviation formalism which describes the occupation-time statistics of a single particle.
arxiv topic:cond-mat.stat-mech
arxiv_dataset-106981901.00253
Skyrmion Tubes as Magnonic Waveguides cond-mat.mes-hall cond-mat.mtrl-sci Various latest experiments have proven the theoretical prediction that domain walls in planar magnetic structures can channel spin waves as outstanding magnonic waveguides, establishing a superb platform for building magnonic devices. Recently, three-dimensional nanomagnetism has been boosted up and become a significant branch of magnetism, because three-dimensional magnetic structures expose a lot of emerging physics hidden behind planar ones and will inevitably provide broader room for device engineering. Skyrmions and antiSkyrmions, as natural three-dimensional magnetic configurations, are not considered yet in the context of spin-wave channeling and steering. Here, we show that skyrmion tubes can act as nonplanar magnonic waveguides if excited suitably. An isolated skyrmion tube in a magnetic nanoprism induces spatially separate internal and edge channels of spin waves; the internal channel has a narrower energy gap, compared to the edge channel, and accordingly can transmit signals at lower frequencies. Additionally, we verify that those spin-wave beams along magnetic nanoprism are restricted to the regions of potential wells. Transmission of spin-wave signals in such waveguides results from the coherent propagation of locally driven eigenmodes of skyrmions, i.e., the breathing and rotational modes. Finally, we find that spin waves along the internal channels are less susceptible to magnetic field than those along the edge channels. Our work will open a new arena for spin-wave manipulation and help bridge skyrmionics and magnonics.
arxiv topic:cond-mat.mes-hall cond-mat.mtrl-sci
arxiv_dataset-106991901.00353
Dilution with Digital Microfluidic Biochips: How Unbalanced Splits Corrupt Target-Concentration cs.ET Sample preparation is an indispensable component of almost all biochemical protocols, and it involves, among others, making dilutions and mixtures of fluids in certain ratios. Recent microfluidic technologies offer suitable platforms for automating dilutions on-chip, and typically on a digital microfluidic biochip (DMFB), a sequence of (1:1) mix-split operations is performed on fluid droplets to achieve the target concentration factor (CF) of a sample. An (1:1) mixing model ideally comprises mixing of two unit-volume droplets followed by a (balanced) splitting into two unit-volume daughter-droplets. However, a major source of error in fluidic operations is due to unbalanced splitting, where two unequal-volume droplets are produced following a split. Such volumetric split-errors occurring in different mix-split steps of the reaction path often cause a significant drift in the target-CF of the sample, the precision of which cannot be compromised in life-critical assays. In order to circumvent this problem, several error-recovery or error-tolerant techniques have been proposed recently for DMFBs. Unfortunately, the impact of such fluidic errors on a target-CF and the dynamics of their behavior have not yet been rigorously analyzed. In this work, we investigate the effect of multiple volumetric split-errors on various target-CFs during sample preparation. We also perform a detailed analysis of the worst-case scenario, i.e., the condition when the error in a target-CF is maximized. This analysis may lead to the development of new techniques for error-tolerant sample preparation with DMFBs without using any sensing operation.
arxiv topic:cs.ET