Search results for "Gaussian function"
showing 10 items of 21 documents
Randomized Rx For Target Detection
2018
This work tackles the target detection problem through the well-known global RX method. The RX method models the clutter as a multivariate Gaussian distribution, and has been extended to nonlinear distributions using kernel methods. While the kernel RX can cope with complex clutters, it requires a considerable amount of computational resources as the number of clutter pixels gets larger. Here we propose random Fourier features to approximate the Gaussian kernel in kernel RX and consequently our development keep the accuracy of the nonlinearity while reducing the computational cost which is now controlled by an hyperparameter. Results over both synthetic and real-world image target detection…
Coexistence of unlimited bipartite and genuine multipartite entanglement: Promiscuous quantum correlations arising from discrete to continuous-variab…
2006
Quantum mechanics imposes 'monogamy' constraints on the sharing of entanglement. We show that, despite these limitations, entanglement can be fully 'promiscuous', i.e. simultaneously present in unlimited two-body and many-body forms in states living in an infinite-dimensional Hilbert space. Monogamy just bounds the divergence rate of the various entanglement contributions. This is demonstrated in simple families of N-mode (N >= 4) Gaussian states of light fields or atomic ensembles, which therefore enable infinitely more freedom in the distribution of information, as opposed to systems of individual qubits. Such a finding is of importance for the quantification, understanding and potenti…
Probabilistic quantum clustering
2020
Abstract Quantum Clustering is a powerful method to detect clusters with complex shapes. However, it is very sensitive to a length parameter that controls the shape of the Gaussian kernel associated with a wave function, which is employed in the Schrodinger equation with the role of a density estimator. In addition, linking data points into clusters requires local estimates of covariance which requires further parameters. This paper proposes a Bayesian framework that provides an objective measure of goodness-of-fit to the data, to optimise the adjustable parameters. This also quantifies the probabilities of cluster membership, thus partitioning the data into a specific number of clusters, w…
Distributed learning automata for solving a classification task
2016
In this paper, we propose a novel classifier in two-dimensional feature spaces based on the theory of Learning Automata (LA). The essence of our scheme is to search for a separator in the feature space by imposing a LA based random walk in a grid system. To each node in the gird we attach an LA, whose actions are the choice of the edges forming the separator. The walk is self-enclosing, i.e, a new random walk is started whenever the walker returns to starting node forming a closed classification path yielding a many edged polygon. In our approach, the different LA attached at the different nodes search for a polygon that best encircles and separates each class. Based on the obtained polygon…
Time-on-Task in Children with ADHD: An ex-Gaussian Analysis
2013
AbstractAlthough it is widely known that high intra-individual variability (IIV) is a key characteristic of attention deficit/hyperactivity disorder (ADHD), a detailed exploration of the IIV pattern during the time course of a cognitive task has never been carried out. In this study, 30 children with ADHD and 30 controls, were administered the Conners’ Continuous Performance Task (CPT-II). The across-block individual performance of the groups was analyzed using an ex-Gaussian approach, which enabled a clearer understanding of how individual response times (RTs) fluctuate during a task in comparison with conventional measures of central tendency. While the conventional measures showed a sign…
Polynomial approximation of non-Gaussian unitaries by counting one photon at a time
2017
In quantum computation with continous-variable systems, quantum advantage can only be achieved if some non-Gaussian resource is available. Yet, non-Gaussian unitary evolutions and measurements suited for computation are challenging to realize in the lab. We propose and analyze two methods to apply a polynomial approximation of any unitary operator diagonal in the amplitude quadrature representation, including non-Gaussian operators, to an unknown input state. Our protocols use as a primary non-Gaussian resource a single-photon counter. We use the fidelity of the transformation with the target one on Fock and coherent states to assess the quality of the approximate gate.
The structural relaxation of molten sodium disilicate
2002
We use molecular dynamics computer simulations to study the relaxation dynamics of Na2O-2(SiO2) in its molten, highly viscous state. We find that at low temperatures the incoherent intermediate scattering function for Na relaxes about 100 times faster than the one of the Si and O atoms. In contrast to this all coherent functions relax on the same time scale if the wave-vector is around 1AA^-1. This anomalous relaxation dynamics is traced back to the channel-like structure for the Na atoms that have been found for this system. We find that the relaxation dynamics for Si and O as well as the time dependence of the coherent functions for Na can be rationalized well by means of mode-coupling th…
Über eine eichung eines 7.5 × 7.5 cm - NaJ(Tl) - Vollkristalls zur absolutzählung flächenförmiger präparate
1966
Abstract The photopeak efficiency and the peak-to-total ratio for a 7.5 × 7.5 cm solid NaI(Tl)-crystal are determined in the range of 0.145–1.33 MeV. The disintegration rates of the disc sources used are known by 4 πβ -and 4 πβ - γ -coincidence measurements. The effect of the disc diameter and the distance source-crystal on the photopeak efficiency is studied thoroughly. The data obtained are compared with those of other authors. The evaluation of the photopeak area is performed in a frequency diagram, a special type of probability scale, in which both parts of the Gaussian curve are represented by straight lines. Hence, corrections for the Compton overlap, bremsstrahlung and background can…
Non-Markovianity of Gaussian Channels
2015
We introduce a necessary and sufficient criterion for the non-Markovianity of Gaussian quantum dynamical maps based on the violation of divisibility. The criterion is derived by defining a general vectorial representation of the covariance matrix which is then exploited to determine the condition for the complete positivity of partial maps associated to arbitrary time intervals. Such construction does not rely on the Choi-Jamiolkowski representation and does not require optimization over states.
Probability Distribution of the Residence Times in Periodically Fluctuating Metastable Systems
1998
We investigate experimentally and numerically the probability distribution of the residence times in periodically fluctuating metastable systems. The experiments are performed in a physical metastable system which is the series of a biasing resistor with a tunnel diode in parallel to a capacitor. The numerical simulations are performed in an overdamped model system with a time-dependent potential. We investigate both the cases where the system is deterministically overall-stable and overall-unstable. In the overall-unstable regime, the experimental and the numerically investigated systems show noise enhanced stability in the presence of a finite amount of noise. The determined P(T) is mult…