اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدWavelet-based cross-correlation analysis of structure scaling in turbulent clouds
42
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
We propose a statistical tool to compare the scaling behaviour of turbulence in pairs of molecular cloud maps. Using artificial maps with well defined spatial properties, we calibrate the method and test its limitations to ultimately apply it to a set of observed maps. We develop the wavelet-based weighted cross-correlation (WWCC) method to study the relative contribution of structures of different sizes and their degree of correlation in two maps as a function of spatial scale, and the mutual displacement of structures in the molecular cloud maps. We test the WWCC for circular structures having a single prominent scale and fractal structures showing a self-similar behavior without prominent scales. Observational noise and a finite map size limit the scales where the cross-correlation coefficients and displacement vectors can be reliably measured. For fractal maps containing many structures on all scales, the limitation from the observational noise is negligible for signal-to-noise ratios >5. (abbrev). Application of the WWCC to the observed line maps of the giant molecular cloud G333 allows to add specific scale information to the results obtained earlier using the principle component analysis. It confirms the chemical and excitation similarity of $^{13}$CO and C$^{18}$O on all scales, but shows a deviation of HCN at scales of up to 7 (~7 pc). This can be interpreted as a chemical transition scale. The largest structures also show a systematic offset along the filament, probably due to a large-scale density gradient. The WWCC can compare correlated structures in different maps of molecular clouds identifying scales that represent structural changes such as chemical and phase transitions and prominent or enhanced dimensions.
قيم البحث
اقرأ أيضاً
Complex systems are composed of mutually interacting components and the output values of these components are usually long-range cross-correlated. We propose a method to characterize the joint multifractal nature of such long-range cross correlations
based on wavelet analysis, termed multifractal cross wavelet analysis (MFXWT). We assess the performance of the MFXWT method by performing extensive numerical experiments on the dual binomial measures with multifractal cross correlations and the bivariate fractional Brownian motions (bFBMs) with monofractal cross correlations. For binomial multifractal measures, the empirical joint multifractality of MFXWT is found to be in approximate agreement with the theoretical formula. For bFBMs, MFXWT may provide spurious multifractality because of the wide spanning range of the multifractal spectrum. We also apply the MFXWT method to stock market indexes and uncover intriguing joint multifractal nature in pairs of index returns and volatilities.
Sunquakes are one of the more distinct secondary phenomena related to solar flares, where energy deposition in the lower layers of the Suns atmosphere excites acoustic waves easily visible in Helioseismic and Magnetic Imager (HMI) dopplergrams. We ex
plore two possible sources of sunquakes in the context of the electron beam hypothesis: an instantaneous transfer of momentum and a gradual applied force due to flare eruption. We model the sunquake excitation and compare with five observed sunquake events using a cross-correlation analysis. We find that at least half the events studied are consistent with the electron beam hypothesis and estimate the energy required to excite the sunquakes to be within the range determined by previous studies.
Wavelet analysis of different solar activity indices, sunspot numbers, sunspot areas, flare index, magnetic fields, etc., allows us to investigate the time evolution of some specific features of the solar activity and the underlying dynamo mechanism.
The main aim of this work is the analysis of the time-frequency behavior of some magnetic strengtht indices currently taken at the Mt. Wilson Observatory 150-Foot Solar Tower. In particular, we analyzed both the long time series (Jan 19, 1970 - Jan 22, 2013) of the Magnetic Plage Strength Index (MPSI) values and of the Mt. Wilson Sunspot Index (MWSI) values, covering the descending phase of cycle 20, the full solar cycles 21-23 and the current part of the 24 solar cycle. This study is a further contribution to detect the changes in the multiscale quasiperiodic variations in the integrated magnetic solar activity with a comparison between past solar cycles and the current one, which is one of the weaker recorded in the past 100 years. Indeed, it is well known that an unusual and deep solar minimum occurred between solar cycles 23 and 24 and the time-frequency behavior of some magnetic strengtht indices can help to better interpret the responsible mechanisms.
Using self-gravitational hydrodynamical numerical simulations, we investigated the evolution of high-density turbulent molecular clouds swept by a colliding flow. The interaction of shock waves due to turbulence produces networks of thin filamentary
clouds with a sub-parsec width. The colliding flow accumulates the filamentary clouds into a sheet cloud and promotes active star formation for initially high-density clouds. Clouds with a colliding flow exhibit a finer filamentary network than clouds without a colliding flow. The probability distribution functions (PDFs) for the density and column density can be fitted by lognormal functions for clouds without colliding flow. When the initial turbulence is weak, the column density PDF has a power-law wing at high column densities. The colliding flow considerably deforms the PDF, such that the PDF exhibits a double peak. The stellar mass distributions reproduced here are consistent with the classical initial mass function with a power-law index of $-1.35$ when the initial clouds have a high density. The distribution of stellar velocities agrees with the gas velocity distribution, which can be fitted by Gaussian functions for clouds without colliding flow. For clouds with colliding flow, the velocity dispersion of gas tends to be larger than the stellar velocity dispersion. The signatures of colliding flows and turbulence appear in channel maps reconstructed from the simulation data. Clouds without colliding flow exhibit a cloud-scale velocity shear due to the turbulence. In contrast, clouds with colliding flow show a prominent anti-correlated distribution of thin filaments between the different velocity channels, suggesting collisions between the filamentary clouds.
We present a group-galaxy cross-correlation analysis using a group catalog produced from the 16,500 spectra from the optical zCOSMOS galaxy survey. Our aim is to perform a consistency test in the redshift range 0.2 < z < 0.8 between the clustering st
rength of the groups and mass estimates that are based on the richness of the groups. We measure the linear bias of the groups by means of a group-galaxy cross-correlation analysis and convert it into mass using the bias-mass relation for a given cosmology, checking the systematic errors using realistic group and galaxy mock catalogs. The measured bias for the zCOSMOS groups increases with group richness as expected by the theory of cosmic structure formation and yields masses that are reasonably consistent with the masses estimated from the richness directly, considering the scatter that is obtained from the 24 mock catalogs. An exception are the richest groups at high redshift (estimated to be more massive than 10^13.5 M_sun), for which the measured bias is significantly larger than for any of the 24 mock catalogs (corresponding to a 3-sigma effect), which is attributed to the extremely large structure that is present in the COSMOS field at z ~ 0.7. Our results are in general agreement with previous studies that reported unusually strong clustering in the COSMOS field.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
