Open AccessPower spectrum and intermittency of the transmitted flux from the Lyman α absorption spectra of quasi‐stellar objects
Author(s) -
Jamkhedkar Priya,
Feng LongLong,
Zheng Wei,
Kirkman David,
Tytler David,
Fang LiZhi
Publication year - 2003
Publication title -
monthly notices of the royal astronomical society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.058
H-Index - 383
eISSN - 1365-2966
pISSN - 0035-8711
DOI - 10.1046/j.1365-8711.2003.06662.x
Subject(s) - physics , intermittency , spectral density , statistical physics , gaussian , flux (metallurgy) , limit (mathematics) , field (mathematics) , computational physics , cosmic variance , astrophysics , statistics , mathematical analysis , redshift , galaxy , mathematics , quantum mechanics , meteorology , turbulence , materials science , pure mathematics , metallurgy
Using a set of 28 high‐resolution, high signal‐to‐noise ratio quasi‐stellar object Lyα absorption spectra, we investigate the non‐Gaussian features of the transmitted flux fluctuations and their effect upon the power spectrum of this field. We find that the spatial distribution of the local power of the transmitted flux on scales k ≥ 0.05 s km −1 is highly spiky or intermittent. The probability distribution functions of the local power are long‐tailed. The power on small scales is dominated by small probability events, and consequently, the uncertainty in the power spectrum of the transmitted flux field is generally large. This uncertainty arises owing to the slow convergence of an intermittent field to a Gaussian limit required by the central limit theorem (CLT). To reduce this uncertainty, it is common to estimate the error of the power spectrum by selecting subsamples with an ‘optimal’ size. We show that this conventional method actually does not calculate the variance of the original intermittent field but of a Gaussian field. Based on the analysis of intermittency, we propose an algorithm to calculate the error. It is based on a bootstrap resampling among all independent local power modes. This estimation does not require any extra parameter such as the size of the subsamples and is sensitive to the intermittency of the fields. This method effectively reduces the uncertainty in the power spectrum when the number of independent modes matches the condition for CLT convergence.