A non-parametric estimation approach in the investigation of spectral statistics

被引:7
|
作者
Jafarizadeh, M. A. [1 ,2 ]
Fouladi, N. [3 ]
Sabri, H. [3 ]
Maleki, B. R. [3 ]
机构
[1] Univ Tabriz, Dept Theoret Phys & Astrophys, Tabriz 51664, Iran
[2] Res Inst Fundamental Sci, Tabriz 51664, Iran
[3] Univ Tabriz, Dept Nucl Phys, Tabriz 51664, Iran
关键词
Kernel density estimation (KDE); Nearest neighbor spacing distribution (NNSD); Kullback-Leibler divergence (KLD) measure; Interacting boson model (IBM); DENSITY-ESTIMATION; QUANTUM CHAOS; SPACINGS; NUMBER;
D O I
10.1007/s12648-013-0311-7
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
We have used kernel density estimation (KDE) technique to analyze the spectral statistics of nuclear systems with emphasis on the nearest neighbor spacing distribution. The deviations to regular and chaotic dynamics are described by closer distances to Poisson and Wigner limits, respectively which have calculated via Kullback-Leibler divergence measure. The level statistics of nuclei provide empirical evidences for three dynamical symmetry limits of interacting boson model, considering oblate and prolate nuclei. The predictions of KDE technique suggest a considerable reduction in the uncertainties of chaocity degrees and also more regular dynamics in comparison with other estimation methods for considered systems.
引用
收藏
页码:919 / 927
页数:9
相关论文
共 50 条
  • [31] Adaptive weighted non-parametric background model for efficient video coding
    Chakraborty, Subrata
    Paul, Manoranjan
    Murshed, Manzur
    Ali, Mortuza
    NEUROCOMPUTING, 2017, 226 : 35 - 45
  • [32] Beta-Binomial stick-breaking non-parametric prior
    Gil-Leyva, Maria F.
    Mena, Ramses H.
    Nicoleris, Theodoros
    ELECTRONIC JOURNAL OF STATISTICS, 2020, 14 (01): : 1479 - 1507
  • [33] Novel hybrid object-based non-parametric clustering approach for grouping similar objects in specific visual domains
    Kuru, Kaya
    Khan, Wasiq
    APPLIED SOFT COMPUTING, 2018, 62 : 667 - 701
  • [34] Medical image segmentation based on non-parametric mixture models with spatial information
    Song, Yu-Qing
    Liu, Zhe
    Chen, Jian-Mei
    Zhu, Feng
    Xie, Cong-Hua
    SIGNAL IMAGE AND VIDEO PROCESSING, 2012, 6 (04) : 569 - 578
  • [35] Non-parametric calibration of multiple related radiocarbon determinations and their calendar age summarisation
    Heaton, Timothy J.
    JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS, 2022, 71 (05) : 1918 - 1956
  • [36] TARGET DETECTION EXPERIMENTS WITH A NON-PARAMETRIC DETECTOR ON A NEW HYPERSPECTRAL DATA SET
    Matteoli, Stefania
    Diani, Marco
    Corsini, Giovanni
    2017 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2017, : 1328 - 1331
  • [37] Optimal convergence rates in non-parametric regression with fractional time series errors
    Feng, Yuanhua
    Beran, Jan
    JOURNAL OF TIME SERIES ANALYSIS, 2013, 34 (01) : 30 - 39
  • [38] Brain waves analysis via a non-parametric Bayesian mixture of autoregressive kernels
    Granados-Garcia, Guilllermo
    Fiecas, Mark
    Babak, Shahbaba
    Fortin, Norbert J.
    Ombao, Hernando
    COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2022, 174
  • [39] A kernelized non-parametric classifier based on feature ranking in anisotropic Gaussian kernel
    Sheikhpour, Razieh
    Sarram, Mehdi Agha
    Chahooki, Mohammad Ali Zare
    Sheikhpour, Robab
    NEUROCOMPUTING, 2017, 267 : 545 - 555
  • [40] AN EFFICIENT VIDEO CODING TECHNIQUE USING A NOVEL NON-PARAMETRIC BACKGROUND MODEL
    Chakraborty, Subrata
    Paul, Manoranjan
    Murshed, Manzur
    Ali, Mortuza
    2014 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO WORKSHOPS (ICMEW), 2014,