Arbitrary Range Research Articles

Nonequilibrium master equationfor interacting Brownian particles in a deep-well periodic potential.

Employing a creation and annihilation operator formulation, we derive an approximate many-body master equationdescribing discrete hopping from the more general continuous description of Brownian motion on a deep-well nonequilibrium periodic potential. The many-body master equationdescribes interactions of arbitrary strength and range arising from a "top-hat" two-body interaction potential. We show that this master equationreduces to the well-known asymmetric simple exclusion process and the zero range process in certain regimes. We also use the creation and annihilation operator formalism to derive results for the steady-state drift and the number fluctuations in special cases, including the unexplored limit of weak interparticle interactions.

Nonlocality-induced surface localization in Bose-Einstein condensates of light

The ability to create and manipulate strongly correlated quantum many-body states is of central importance to the study of collective phenomena in several condensed-matter systems. In the last decades, a great amount of work has been focused on ultracold atoms in optical lattices, which provide a flexible platform to simulate peculiar phases of matter both for fermionic and bosonic particles. The recent experimental demonstration of Bose-Einstein condensation (BEC) of light in dye-filled microcavities has opened the intriguing possibility to build photonic simulators of solid-state systems, with potential advantages over their atomic counterpart. A distinctive feature of photon BEC is the thermo-optical nature of the effective photon-photon interaction, which is intrinsically nonlocal and can thus induce interactions of arbitrary range. This offers the opportunity to systematically study the collective behaviour of many-body systems with tunable interaction range. In this paper, we theoretically study the effect of nonlocal interactions in photon BEC. We first present numerical results of BEC in a double-well potential, and then extend our analysis to a short one-dimensional lattice with open boundaries. By resorting to a numerical procedure inspired by the Newton-Raphson method, we simulate the time-independent Gross-Pitaevskii equation and provide evidence of surface localization induced by nonlocality, where the condensate density is localized at the boundaries of the potential. Our work paves the way towards the realization of synthetic matter with photons, where the interplay between long-range interactions and low dimensionality can lead to the emergence of unexplored nontrivial collective phenomena.

Privacy-Preserving Keyword Similarity Search Over Encrypted Spatial Data in Cloud Computing

With the proliferation of cloud computing, data owners can outsource the spatial data from the Internet of Things devices to a cloud server to enjoy the pay-as-you-go storage resources and location-based services. However, the outsourced services may raise privacy concerns, since the cloud server may not be fully trusted for both data owners and search users. If the data owners and search users conventionally encrypt the spatial data and query requests, the efficiency and functionality of query processing are weakened. Most of the existing works only focus on spatial data search or keyword search and do not consider spatial keyword search over encrypted data. In this article, we first design a geometric range query (GRQ) scheme, which can generate an arbitrary geometric range to fit the search user’s desired spatial data while protecting location privacy. Furthermore, based on GRQ, we propose a multidimensional spatial keyword similarity search scheme with access control (MSSAC) by integrating the polynomial function and matrix transformation. Specifically, an access control strategy is defined by a role-based polynomial function, which is embedded in the vectors of indices and trapdoors to achieve efficient and lightweight access control. Moreover, MSSAC enables the cloud server to execute compute-then-compare operations for spatial keyword search in a privacy-preserving manner by leveraging techniques of randomizable permutation and matrix multiplication. The formal security analyses and extensive experiments demonstrate that GRQ and MSSAC preserve the privacy of data owners and search users while achieving efficient spatial keyword search.

The series of a four-node motif and coherent type-1 feed-forward loop can provide sensitive detection over arbitrary range of input signal, thereby explain Weber’s law in higher-order sensory processes, and compute logarithm

Weber’s law states that the ratio of the smallest perceptual change in an input signal and the background signal is constant. The law is observed across the perception of weight, light intensity, and sound intensity and pitch. To explain Weber’s law observed in steady-state responses, two models of perception have been proposed, namely the logarithmic and the linear model. This paper argues in favour of the linear model, which requires the sensory system to generate linear input–output relationship over several orders of magnitude. To this end, a four-node motif (FNM) is constructed from first principles whose series provides almost linear relationship between input signal and the output over arbitrary range of input signal. Mathematical analysis into the origin of this quasi-linear relationship shows that the series of coherent type-1 feed-forward loop (C1-FFL) is able to provide perfectly linear input–output relationship over arbitrary range of input signal. FNM also reproduces the neuronal data of numerosity detection study on the monkey. The series of FNM also provides a mechanism for sensitive detection over arbitrary range of input signal when the output has an upper limit. Further, the series of FNM provides a general basis for a class of bow-tie architecture where the number of receptors is much lower than the range of input signal and the “decoded output”. Besides (quasi-)linear input–output relationship, another example of this class of bow-tie architecture that the series of FNM is able to produce is absorption spectra of cone opsins of humans. Further, the series of FNM and C1-FFL, both, can compute logarithm over arbitrary range of input signal.

Theoretical concentration limit and maximum annual optical efficiency of static/low-concentration CPV for horizontal integration to vehicle bodies.

This study proposes an extended theoretical formula to characterize the relationship between the geometrical concentration ratio Cg and arbitrary incidence-angle range to objectively understand the theoretical limit performance of vehicle-integrated concentrator photovoltaics (VICPVs), i.e., static and low-concentration CPVs installed on a horizontal surface. Theoretical analysis revealed that the maximum annual optical efficiency (maximum annual solar energy yield) can be achieved by selectively collecting the sunlight incident only from a specific incidence-angle range of θ1-θ2 (θ1 ≠ 0°), regardless of the geographical location, which is associated with the angular distribution of the annual solar energy on the concentrator aperture. Moreover, the results of the solar concentrator design based on the obtained formula clarified that the annual optical efficiencies of the optical systems with aspheric lens or dielectric-filled crossed compound-parabolic-concentrator lens were 64-89% of the theoretical limit depending on the location for Cg = 3.5×. Nevertheless, the concentrator design can be further improved for practical applications.

Optimum Design of Multi-layered Micro-perforated Panel Sound Absorbers in Combination with Porous Materials in an Arbitrary Frequency Range

Optimum design of sound absorbers with optimum thickness and maximum sound absorption has always been an important issue to noise control. The purpose of this paper is an achievement of optimum design for micro-perforated panel (MPP) and its combination with a porous material and air gap to obtain maximum sound absorption with maximum overall thickness up to about 10 cm in the frequency range of (20-500 Hz), (500-2000 Hz) and (2000-10000 Hz). For this purpose, the genetic algorithm is proposed as an effective technique to solve the optimization problem. By using the precise theoretical models (i.e. simplified Allard's model and Atalla et al.’s model) to calculate the acoustic characteristics of each layer consisting of MPP, porous material, and airgap, we obtained more precise optimized structures. The transfer matrix method has been used to investigate the sound absorption of structures. To verify the operation of the programmed genetic algorithm, the results obtained from the optimization of the MPP absorber are compared with others that show the accuracy and efficiency of this method. After ensuring the accuracy of the proposed programmed genetic algorithm with more precise theoretical models to achieve the characteristics of each layer, new structures were obtained that have a much better sound absorption coefficient in the desired frequency range than the previous structures. The results show that the sound absorption coefficient can be reached to 0.67, 0.96, and 0.96 in the mentioned first, second, and third frequency range, respectively by optimum design parameter choosing of a composite structure.

Elementary Effects for Models with Dimensional Inputs of Arbitrary Type and Range: Scaling and Trajectory Generation

Elementary Effects for Models with Dimensional Inputs of Arbitrary Type and Range: Scaling and Trajectory Generation

A Frequency-Domain Spoofing Attack on FMCW Radars and Its Mitigation Technique Based on a Hybrid-Chirp Waveform

This article presents a novel spoofing device capable of injecting false target information into a frequency-modulated continuous-wave (FMCW) radar. The spoofing device uses a radio frequency (RF) single-sideband (SSB) mixer to introduce a frequency shift to the incoming RF signal transmitted by the victim radar and retransmits the modulated RF signal. The modulated RF signal resembles a false target. Upon down-conversion on the receiver chain of the victim radar, the modulated RF signal creates an illusion of a real target in the radar signal processing system. The frequency shift can be adjusted to vary the range of the spoofed target. The theory of the spoofing mechanism was developed, and a 5.8 GHz prototype was built for experimental validation. Experimental results demonstrate the ability of the proposed spoofing device to inject a false target at any arbitrary range. A hybrid-chirp FMCW approach was proposed and verified as a countermeasure to distinguish a real target from a spoofed target to mitigate the RF-spoofing attack.

Designing for Curves

Designing for Curves

An interplay between attraction and repulsion in infinite populations

We propose and study a model describing an infinite population of point entities arriving in and departing from X=mathbb {R}^d, dge 1. The already existing entities force each other to leave the population (repulsion) and attract the newcomers. The evolution of the population states is obtained by solving the corresponding Fokker-Planck equation. Without interactions, the evolution preserves states in which the probability p(n,Lambda ) of finding n points in a compact vessel Lambda subset X obeys the Poisson law. As we show, for pure attraction the decay of p(n,Lambda ) with nrightarrow +infty may be essentially slower. The main result is the statement that in the presence of repulsion—even of an arbitrary short range—the evolution preserves states in which the decay of p(n,Lambda ) is at most Poissonian. We also derive the corresponding kinetic equation, the numerical solutions of which can provide more detailed information on the interplay between attraction and repulsion. Further possibilities in studying the proposed model are also discussed.

Arbitrary free spectral range control of optical frequency combs based on an optical tapped delay line structure cascaded with a phase modulator

Arbitrary free spectral range control of optical frequency combs based on an optical tapped delay line structure cascaded with a phase modulator

Arpra: An Arbitrary Precision Range Analysis Library.

Motivated by the challenge of investigating the reproducibility of spiking neural network simulations, we have developed the Arpra library: an open source C library for arbitrary precision range analysis based on the mixed Interval Arithmetic (IA)/Affine Arithmetic (AA) method. Arpra builds on this method by implementing a novel mixed trimmed IA/AA, in which the error terms of AA ranges are minimised using information from IA ranges. Overhead rounding error is minimised by computing intermediate values as extended precision variables using the MPFR library. This optimisation is most useful in cases where the ratio of overhead error to range width is high. Three novel affine term reduction strategies improve memory efficiency by merging affine terms of lesser significance. We also investigate the viability of using mixed trimmed IA/AA and other AA methods for studying reproducibility in unstable spiking neural network simulations.

Location Privacy-Preserving Task Recommendation With Geometric Range Query in Mobile Crowdsensing

In mobile crowdsensing, location-based task recommendation requires each data requester to submit a task-related geometric range to crowdsensing service providers such that they can match suitable workers within this range. Generally, a trusted server (i.e., database owner) should be deployed to protect location privacy during the process, which is not desirable in practice. In this paper, we propose the location privacy-preserving task recommendation (PPTR) schemes with geometric range query in mobile crowdsensing without the trusted database owner. Specifically, we first propose a PPTR scheme with linear search complexity, named PPTR-L, based on a two-server model. By leveraging techniques of polynomial fitting and randomizable matrix multiplication, PPTR-L enables the service provider to find the workers located in the data requester’s arbitrary geometric query range without disclosing the sensitive location privacy. To further improve query efficiency, we design a novel data structure for task recommendation and propose PPTR-F to achieve faster-than-linear search complexity. Through security analysis, it is shown that our schemes can protect the confidentiality of workers’ locations and data requesters’ queries. Extensive experiments are performed to demonstrate that our schemes can achieve high computational efficiency in terms of geometric range query.

The Birkhoff-James orthogonality and norm attainment for multilinear maps

Very recently, motivated by the result of Bhatia and Šemrl which characterizes the Birkhoff-James orthogonality of operators on a finite dimensional Hilbert space in terms of norm attaining points, the Bhatia-Šemrl property was introduced. The main purpose of this article is to study the denseness of the set of multilinear maps with the Bhatia-Šemrl property which is contained in the set of norm attaining ones. Contrary to the most of previous results which were shown for operators on real Banach spaces, we prove the denseness for multilinear maps on some complex Banach spaces. We also show that the denseness of operators does not hold when the domain space is c0 for arbitrary range. Moreover, we find plenty of Banach spaces Y such that only the zero operator has the Bhatia-Šemrl property in the space of operators from c0 to Y.

Interacting hard-sphere fluids in an external field.

We present a method for studying equilibrium properties of interacting fluids in an arbitrary external field. The fluid is composed of monodisperse spherical particles with hard-core repulsion and additional interactions of arbitrary shape and limited range. Our method of analysis is exact in one dimension and provides demonstrably good approximations in higher dimensions. It can cope with homogeneous and inhomogeneous environments. We derive an equation for the pair distribution function. The solution, to be evaluated numerically, in general, or analytically for special cases, enters expressions for the entropy and free energy functionals. For some one-dimensional systems, our approach yields analytic solutions, reproducing available exact results from different approaches.

Non-local interactions in collective motion.

The collective motion of animal groups often exhibits velocity–velocity correlations between nearest neighbours, with the strongest velocity correlations observed at the shortest inter-animal spacings. This may have been a motivational factor in the development of models based primarily on short-ranged interactions. Here we ask whether such observations necessarily mean that the interactions are short-ranged. We develop a minimal model of collective motion capable of supporting interactions of arbitrary range and show that it represents a counterexample: the strongest velocity correlations emerge at the shortest distances, even when the interactions are explicitly non-local.

Maritime Target Localization From Bistatic Range Measurements in Space-Based Passive Radar

In this article, localization of a maritime target using a passive multistatic radar system, consisting of a single receiver and a number of satellites as its transmitters, is investigated. The set of communication satellites and also the global navigation satellite system (GNSS), including GPS, Glonass, and Galileo, are employed as illuminators of opportunity. In the receiver, the reflected signals from the target along with the direct signal from the satellites are employed to extract a set of bistatic range measurements. Leveraging these measurements and the satellite’s position information, a novel localization method considering zero height of maritime target and appropriate combination of the measurement signals is presented. The proposed method is efficient for localization of maritime targets in cases with arbitrary bistatic range accuracy. The results of numerical simulations confirm the efficiency of the proposed method and its superior performance in comparison with the state-of-the-art methods.

Design of Parallel Sorting System Using Discrete-Time Neural Circuit Model

A parallel sorting system based on discrete-time K-Winners-Take-All (KWTA) neural circuit (NC) model is designed. The system is described by a set of difference equations and by step functions. The KWTA NC model of discrete-time is given by difference equation and by step functions. Corresponding functional block-diagrams of the system are presented. The upper limit on the number of iterations required to achieve a convergence of the sorting process to the steady state is defined. The system does not need a knowledge of range of input data change. In order to use the system, the minimal difference between the inputs should be known. The system is suitable for processing unknown inputs of finite values located in arbitrary unknown finite range. The system is characterized by arbitrary finite resolution of inputs, high speed, moderate computational complexity and complexity of software implementation. The results of computer simulations illustrating efficiency of the system are provided.

A Model for Improving Guesses of Future Soccer League Game Results

In this paper we propose a model for predicting future soccer game results by using information about the results of past league games. First, from regressions we extracted the prediction confidence interval for the goal difference between the winner and the loser in each game. Second, we created an arbitrary range around zero and defined criteria for forecasting a win, a tie or a loss according to the location of the confidence interval relative to the arbitrary range we defined. Third, we gradually changed the edges of the arbitrary range and repeated the second step. Among all the arbitrary ranges, we chose the one that best predicted the match results. We found that the best arbitrary range accurately predicts 52% of the match results. Finally, we upgraded the model by allowing double chance betting, which offers gamblers five possible betting options: home team wins (1), home team wins or game ends in a tie (1 and X), away team wins (2), away team wins or game ends in a tie (2 and X), game ends in a tie (X). When double chance betting was allowed, the model accurately predicted 77% of the match results.

Gauge dependence of the perturbative QCD predictions under the momentum-space subtraction scheme * * Supported by Graduate Research and Innovation Foundation of Chongqing, China (CYB19065, ydstd1912), the National Natural Science Foundation of China (11625520, 11947406, 11905056), the China Postdoctoral Science Foundation (2019M663432) and the Chongqing Special Postdoctoral Science Foundation (XmT2019055)

The momentum-space subtraction (MOM) scheme is one of the most frequently used renormalization schemes in perturbative QCD (pQCD) theory. In this paper, we discuss in detail the gauge dependence of the pQCD predictions obtained under the MOM scheme. Conventionally, a renormalization scale ambiguity exists for the fixed-order pQCD predictions; this assigns an arbitrary range and error for the fixed-order pQCD prediction and makes the discussions on the issue of the gauge dependence much more involved. The principle of maximum conformality (PMC) adopts the renormalization group equation to determine the magnitude of the coupling constant; hence, it determines the effective momentum flow of the process, which is independent of the choice of renormalization scale. Thus, no renormalization scale ambiguity exists in PMC predictions. To focus our attention on the MOM scheme's gauge dependence, we first apply the PMC to deal with the pQCD series. As an explicit example, we adopt the Higgs boson decay width up to its five-loop QCD contribution, to demonstrate the behavior of the gauge dependence before and after applying the PMC. Interaction vertices are chosen to define five different MOM schemes: mMOM, MOMh, MOMq, MOMg, and MOMgg. Under these MOM schemes, we obtain , , , , and ; here, the central values correspond to the Landau gauge with the gauge parameter , the first errors correspond to , and the second ones arise through taking . The uncertainty of the Higgs mass causes an extra error of (or ) keV for all the aforementioned MOM schemes. It is found that the Higgs decay width depends very weakly on the choice of MOM scheme, which is consistent with renormalization group invariance. It is found that the gauge dependence of under the scheme is less than ±1%, which is the smallest gauge dependence among all the aforementioned MOM schemes.