scholarly journals Approximate decoherence free subspaces for distributed sensing

2021 ◽  
Author(s):  
Arne Hamann ◽  
Pavel Sekatski ◽  
Wolfgang Duer
Keyword(s):  
Spatial Dependence ◽  
Signal Strength ◽  
Distributed Sensing ◽  
Spatial Correlations ◽  
Noise Sources ◽  
Wide Applicability ◽  
Internal States ◽  
Equipotential Surfaces ◽  
The Cost ◽  
Decoherence Free Subspace

Abstract We consider the sensing of scalar valued fields with specific spatial dependence using a network of sensors, e.g. multiple atoms located at different positions within a trap. We show how to harness the spatial correlations to sense only a specific signal, and be insensitive to others at different positions or with unequal spatial dependence by constructing a decoherence-free subspace for noise sources at fixed, known positions. This can be extended to noise sources lying on certain surfaces, where we encounter a connection to mirror charges and equipotential surfaces in classical electrostatics. For general situations, we introduce the notion of an approximate decoherence-free subspace, where noise for all sources within some volume is significantly suppressed, at the cost of reducing the signal strength in a controlled way. We show that one can use this approach to maintain Heisenberg-scaling over long times and for a large number of sensors, despite the presence of multiple noise sources in large volumes. We introduce an efficient formalism to construct internal states and sensor configurations, and apply it to several examples to demonstrate the usefulness and wide applicability of our approach.

Propeller Cavitation Induced Hull Pressure Reduction by Air-Bubble Layer

2013 ◽  
Author(s):  
Jeung-Hoon Lee ◽  
Hyoung-Gil Park ◽  
Jin-Hak Kim ◽  
Kyung-Jun Lee ◽  
Jong-Soo Seo
Keyword(s):  
Acoustic Scattering ◽  
Destructive Interference ◽  
Primary Concern ◽  
Pressure Amplitude ◽  
Pressure Reduction ◽  
Noise Sources ◽  
Air Bubble ◽  
Excessive Consumption ◽  
Bubble Layer ◽  
The Cost

Cavitation generated by a marine propeller is a primary concern among the possible vibration- and noise- sources in commercial ships. By exploiting the compressibility of air, there have been many attempts to form an air-bubble layer underneath the stern-hull surface above the propeller, and consequently to isolate the cavity-induced pressure wave across the layer. However, it could not be popularly used because the cost was so expensive to deliver a huge amount of air for a sufficient isolation performance. In this work, full-scale ship measurements reveal that a significant reduction of pressure-amplitude is possible at the outside of an air-bubble layer, where the isolation effect is not involved. Moreover a hull-vibration reduction of approximately 75% was found to be achievable. Instead of excessive consumption of air, considerably small amount is necessary for a reduction of cavity-induced pressure amplitude, which can make the constitution of relevant system simple. Hence the purpose of this study is to provide a physical proof for such a beneficial phenomenon. By approximating the solution of acoustic scattering from a bubble, we find that phase-reversal reflection provoking a destructive interference is the main reason for a pressure reduction outside the layer.

scholarly journals UNIFORM ASYMPTOTIC NORMALITY IN STATIONARY AND UNIT ROOT AUTOREGRESSION

2011 ◽  
Vol 27 (6) ◽  
pp. 1117-1151 ◽  
Author(s):  
Chirok Han ◽  
Peter C. B. Phillips ◽  
Donggyu Sul
Keyword(s):  
Normal Distribution ◽  
Rate Of Convergence ◽  
Unit Root ◽  
Asymptotic Theory ◽  
Signal Strength ◽  
Rates Of Convergence ◽  
Moment Conditions ◽  
First Order ◽  
The Cost ◽  
Artificial Shrinkage

While differencing transformations can eliminate nonstationarity, they typically reduce signal strength and correspondingly reduce rates of convergence in unit root autoregressions. The present paper shows that aggregating moment conditions that are formulated in differences provides an orderly mechanism for preserving information and signal strength in autoregressions with some very desirable properties. In first order autoregression, a partially aggregated estimator based on moment conditions in differences is shown to have a limiting normal distribution that holds uniformly in the autoregressive coefficient ρ, including stationary and unit root cases. The rate of convergence is $\root \of n $ when $\left| \rho \right| < 1$ and the limit distribution is the same as the Gaussian maximum likelihood estimator (MLE), but when ρ = 1 the rate of convergence to the normal distribution is within a slowly varying factor of n. A fully aggregated estimator (FAE) is shown to have the same limit behavior in the stationary case and to have nonstandard limit distributions in unit root and near integrated cases, which reduce both the bias and the variance of the MLE. This result shows that it is possible to improve on the asymptotic behavior of the MLE without using an artificial shrinkage technique or otherwise accelerating convergence at unity at the cost of performance in the neighborhood of unity. Confidence intervals constructed from the FAE using local asymptotic theory around unity also lead to improvements over the MLE.

scholarly journals Exploring spatial dependence of cowpea-beans yield using global and local autocorrelation statistics in the Eastern Cariri region of Paraíba

2021 ◽  
Vol 51 (12) ◽  
Author(s):  
Antônia Silânia de Andrade ◽  
Madson Tavares Silva ◽  
Edivaldo Afonso de Oliveira Serrão ◽  
Vicente de Paulo Rodrigues da Silva ◽  
Enilson Palmeira Cavalcanti ◽  
...  
Keyword(s):  
Spatial Dependence ◽  
Likelihood Function ◽  
Spatial Models ◽  
Information Criterion ◽  
Likelihood Method ◽  
Spatial Correlations ◽  
Spatial Error ◽  
Multiple Regression Models ◽  
Harvest Data ◽  
Global And Local

ABSTRACT: This study evaluated the variability and characterizedthe spatial dependence between some soil attributes in the Eastern Cariri microregion of Paraíba,and analyzed the spatial correlations in order to identify the interactions between such attributes in cowpea bean(Vigna unguiculata L. Walp)production. Harvest data of the agricultural years of 2000-2017 in the Eastern Cariri microregion of Paraíba were analyzed. Parameters of the fitted models wereestimated using the Maximum Likelihood method and the performance of the models was evaluated based on coefficients of determination(R2), maximum log-likelihood function, and Schwarz’s Bayesian information criterion (BIC). Correlation and spatial autocorrelation between the cowpea productivity and agrometeorological elements was detected through the spatial analysis, using techniques such as the Moran’s index I. The study showed that, according to the performance indicators used, the spatial error model offered better results in relation to the classical multiple regression models and the self-regressive spatial models, indicating that the inclusion of spatial dependence in the models improves the estimate of productivity of cowpea in the microregion of Cariri Oriental da Paraíba.

scholarly journals The Impacts of Representing the Correlation of Errors in Radar Data Assimilation. Part I: Experiments with Simulated Background and Observation Estimates

2014 ◽  
Vol 142 (11) ◽  
pp. 3998-4016 ◽  
Author(s):  
Dominik Jacques ◽  
Isztar Zawadzki
Keyword(s):  
Data Assimilation ◽  
Cost Function ◽  
Radar Data ◽  
Spatial Correlations ◽  
Radar Observations ◽  
Lack Of Information ◽  
Data Thinning ◽  
The Cost ◽  
The Impact ◽  
Radar Data Assimilation

Abstract In radar data assimilation, statistically optimal analyses are sought by minimizing a cost function in which the variance and covariance of background and observation errors are correctly represented. Radar observations are particular in that they are often available at spatial resolution comparable to that of background estimates. Because of computational constraints and lack of information, it is impossible to perfectly represent the correlation of errors. In this study, the authors characterize the impact of such misrepresentations in an idealized framework where the spatial correlations of background and observation errors are each described by a homogeneous and isotropic exponential decay. Analyses obtained with perfect representation of correlations are compared to others obtained by neglecting correlations altogether. These two sets of analyses are examined from a theoretical and an experimental perspective. The authors show that if the spatial correlations of background and observation errors are similar, then neglecting the correlation of errors has a small impact on the quality of analyses. They suggest that the sampling noise, related to the precision with which analysis errors may be estimated, could be used as a criterion for determining when the correlations of errors may be omitted. Neglecting correlations altogether also yields better analyses than representing correlations for only one term in the cost function or through the use of data thinning. These results suggest that the computational costs of data assimilation could be reduced by neglecting the correlations of errors in areas where dense radar observations are available.

Methods of complex reduction of underwater noise of a marine object

2021 ◽  
pp. 28-34
Author(s):  
В.А. Пятакович ◽  
В.Ф. Рычкова ◽  
А.С. Шмаков
Keyword(s):  
Noise Reduction ◽  
Design Process ◽  
Underwater Noise ◽  
Noise Sources ◽  
The Cost

В процессе проектирования к кораблю предъявляется целый ряд требований, удовлетворение которых обеспечивает необходимый уровень его эффективности. Основной целью разработки и обоснования оперативно-тактического задания на проектируемый корабль является определение круга задач, которые должен решать проектируемый корабль, т.е. определение его назначения и выработка на этой основе требований, определяющих как основное, так и дополнительное назначение корабля, и его тактико-технические элементы. В работе представлены проблемные вопросы комплексного применения средств обесшумливания являющиеся достаточно сложными и требующими взаимного согласования эффективности используемых средств исходя из интенсивности источников шума их частотных и фазовых характеристик, оптимизации масс и габаритов, а также стоимости акустической защиты. Представлена классификация методов и средств снижения уровней подводного шума, создаваемого корабельным оборудованием, рассмотрены основные средства снижения подводного шума корабля, обусловленные установкой механизмов и оборудования на виброизолирующую амортизацию и пути снижения модулированного шума корабельных механизмов. During the design process, a number of requirements are imposed on the ship, the satisfaction of which ensures the necessary level of its efficiency. The main purpose of the development and justification of the operational and tactical task for the projected ship is to determine the range of tasks that the projected ship should solve, i.e., determining its purpose and developing on this basis the requirements defining both the main and additional purpose of the ship, and its tactical and technical elements. The paper presents problematic issues of complex application of noise reduction means that are quite complex and require mutual coordination of the effectiveness of the means used based on the intensity of noise sources, their frequency and phase characteristics, optimization of masses and dimensions, as well as the cost of acoustic protection. The classification of methods and means of reducing the levels of underwater noise generated by shipboard equipment is presented, the main means are considered.

Lijphart, Lakatos, and Consociationalism

1997 ◽  
Vol 50 (1) ◽  
pp. 88-117 ◽  
Author(s):  
Ian S. Lustick
Keyword(s):  
Social Science ◽  
Comparative Politics ◽  
Research Program ◽  
Primary Response ◽  
The Political ◽  
Consociational Democracy ◽  
Wide Applicability ◽  
Research Programs ◽  
Democratic Stability ◽  
The Cost

Arend Lijphart's 1969 article on consociational democracy was a compelling critique of prevailing theories of democratic stability and the launching pad for one of the most widely regarded research programs in contemporary comparative politics. However, Lijphart and others who adopted consociational approaches encountered severe logical, theoretical, and empirical criticisms of their work. The success of the program and its apparent imperviousness to many of these attacks has been remarkable. Lijphart s primary response was to abandon standard norms of social science in favor of an “impressionistic” approach that protected the attractiveness and wide applicability of the theory at the cost of precision and scholarly rigor. The overall trajectory of the consociationalist research program is explained with reference to a shift from early- to late-Lakatosian commitments—from insisting on corroboration for one's theories through repeated encounters with evidence to a late-Lakatosian stance that expects the political and rhetorical skills of scholars operating on behalf of their research program to be more significant than evidence or theoretical coherence.

scholarly journals Adjusting spatial dependence of climate model outputs with cycle-consistent adversarial networks

2021 ◽  
Author(s):  
Bastien François ◽  
Soulivanh Thao ◽  
Mathieu Vrac
Keyword(s):  
Bias Correction ◽  
Spatial Dependence ◽  
Climate Model ◽  
Correction Method ◽  
Mapping Method ◽  
Dependence Structure ◽  
Spatial Correlations ◽  
Temperature And Precipitation ◽  
Climate Simulations ◽  
Spatial Correlation Structure

AbstractClimate model outputs are commonly corrected using statistical univariate bias correction methods. Most of the time, those 1d-corrections do not modify the ranks of the time series to be corrected. This implies that biases in the spatial or inter-variable dependences of the simulated variables are not adjusted. Hence, over the last few years, some multivariate bias correction (MBC) methods have been developed to account for inter-variable structures, inter-site ones, or both. As proof-of-concept, we propose to adapt a computer vision technique used for Image-to-Image translation tasks (CycleGAN) for the adjustment of spatial dependence structures of climate model projections. The proposed algorithm, named MBC-CycleGAN, aims to transfer simulated maps (seen as images) with inappropriate spatial dependence structure from climate model outputs to more realistic images with spatial properties similar to the observed ones. For evaluation purposes, the method is applied to adjust maps of temperature and precipitation from climate simulations through two cross-validation approaches. The first one is designed to assess two different post-processing schemes (Perfect Prognosis and Model Output Statistics). The second one assesses the influence of nonstationary properties of climate simulations on the performance of MBC-CycleGAN to adjust spatial dependences. Results are compared against a popular univariate bias correction method, a “quantile-mapping” method, which ignores inter-site dependencies in the correction procedure, and two state-of-the-art multivariate bias correction algorithms aiming to adjust spatial correlation structure. In comparison with these alternatives, the MBC-CycleGAN algorithm reasonably corrects spatial correlations of climate simulations for both temperature and precipitation, encouraging further research on the improvement of this approach for multivariate bias correction of climate model projections.

scholarly journals ANALYSIS OF THE EFFICIENCY OF ACOUSTIC SCREENS OF DIFFERENT DESIGNS

2021 ◽  
Vol 11 (3) ◽  
pp. 62-66
Author(s):  
Oleg G. ORLOV
Keyword(s):  
Single Layer ◽  
Vertical Axis ◽  
Metal Consumption ◽  
Noise Sources ◽  
Effective Protection ◽  
Sound Energy ◽  
Effi Ciency ◽  
Complete Absorption ◽  
Absorbing Material ◽  
The Cost

Various sources of noise in cities and ways to combat them are considered. The effi ciency of two types of acoustic screens is analyzed: single-layer and two-and three-layer. The positive and negative characteristics of various designs of existing acoustic screens are listed. A fundamentally new design of the acoustic screen is described: the panels have a ridge profi le, they are located along the vertical axis of the frame with a step at which the panels above the located ridge cover the top of the lower ridge, the outer surfaces of the panels and their end parts are made of a material that has sound-refl ecting properties, and the inner surfaces of the panels are made of sound-absorbing material. Such an acoustic screen is devoid of the disadvantages inherent in acoustic screens of other structures and is more effi cient. The considered invention allows due to the use of the ridge shape of acoustic panels: prevent the refl ection of sound energy in the direction of noise sources (a small part will be directed upwards); provide almost complete absorption of sound energy as it passes through the channels formed by the ridge panels; provide the same effective protection against noise sources located on both sides of the screen; prevent the formation of snow and ice crust on sound-absorbing surfaces, which ensures the constant eff ectiveness of the screen in diff erent seasons of the year; reduce metal consumption, which will reduce the weight of the structure without reducing its effi ciency and reduce the cost of acoustic screens.

scholarly journals Adjusting spatial dependence of climate model outputs with Cycle-Consistent Adversarial Networks

2021 ◽  
Author(s):  
Bastien François ◽  
Soulivanh Thao ◽  
Mathieu Vrac
Keyword(s):  
Bias Correction ◽  
Spatial Dependence ◽  
Climate Model ◽  
Correction Method ◽  
Mapping Method ◽  
Dependence Structure ◽  
Spatial Correlations ◽  
Temperature And Precipitation ◽  
Climate Simulations ◽  
Spatial Correlation Structure

Abstract Climate model outputs are commonly corrected using statistical univariate bias correction methods. Most of the time, those 1d-corrections do not modify the ranks of the time series to be corrected. This implies that biases in the spatial or inter-variable dependences of the simulated variables are not adjusted. Hence, over the last few years, some multivariate bias correction (MBC) methods have been developed to account for inter-variable structures, inter-site ones, or both. As proof-of-concept, we propose to adapt a computer vision technique used for Image-to-Image translation tasks (CycleGAN) for the adjustment of spatial dependence structures of climate model projections. The proposed algorithm, named MBC-CycleGAN, aims to transfer simulated maps (seen as images) with inappropriate spatial dependence structure from climate model outputs to more realistic images with spatial properties similar to the observed ones. For evaluation purposes, the method is applied to adjust maps of temperature and precipitation from climate simulations through two cross-validation approaches. The first one is designed to assess two different post-processing schemes (Perfect Prognosis and Model Output Statistics). The second one assesses the influence of nonstationary properties of climate simulations on the performance of MBC-CycleGAN to adjust spatial dependences. Results are compared against a popular univariate bias correction method, a ``quantile-mapping'' method, which ignores inter-site dependencies in the correction procedure, and two state-of-the-art multivariate bias correction algorithms aiming to adjust spatial correlation structure. In comparison with these alternatives, the MBC-CycleGAN algorithm reasonably corrects spatial correlations of climate simulations for both temperature and precipitation, encouraging further research on the improvement of this approach for multivariate bias correction of climate model projections.

Quantum key distribution: defeating collective noise without reducing efficiency

2014 ◽  
Vol 14 (9&10) ◽  
pp. 845-856
Author(s):  
Song Lin ◽  
Gong-De Guo ◽  
Fei Gao ◽  
Xiao-Fen Liu
Keyword(s):  
Quantum Key Distribution ◽  
Quantum Communication ◽  
Transmission Rate ◽  
Key Distribution ◽  
Collective Noise ◽  
Bb84 Protocol ◽  
Communication Efficiency ◽  
Valid Solution ◽  
The Cost ◽  
Decoherence Free Subspace

Decoherence-free subspace (DFS) is a valid solution to realize quantum communication over a collective noise channel, and has been widely studied. Generally speaking, replacing a qubit with a DFS state will cause the reduction of communication efficiency. However, in this letter, it is shown that some kinds of noises may not lower the transmission rate of quantum key distribution. To illustrate it, we propose two quantum key distribution protocols based on Bell states. Here, two nonorthogonal and unbiased sets in a DFS are constructed by linear combination of particles at different positions. Since $n-1$ classical bits are distributed by using $2n$ qubits in our protocols, the transmission rate is close to that of noiseless BB84 protocol. Furthermore, when considering the cost of transmitting classical bits, the efficiencies of these protocols are even higher than that of BB84 protocol.

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