No Arabic abstract
Based on the theoretical description of Position-Position-Velocity(PPV) statistics in Lazarian & Pogosyan(2000), we introduce a new technique called the Velocity Decomposition Algorithm(VDA) in separating the PPV fluctuations arising from velocity and density fluctuations. Using MHD turbulence simulations, we demonstrate its promise in retrieving the velocity fluctuations from PPV cube in various physical conditions and its prospects in accurately tracing the magnetic field. We find that for localized clouds, the velocity fluctuations are most prominent at the wing part of the spectral line, and they dominate the density fluctuations. The same velocity dominance applies to extended HI regions undergoing galactic rotation. Our numerical experiment demonstrates that velocity channels arising from the cold phase of atomic hydrogen (HI) are still affected by velocity fluctuations at small scales. We apply the VDA to HI GALFA-DR2 data corresponding to the high-velocity cloud HVC186+19-114 and high latitude galactic diffuse HI data. Our study confirms the crucial role of velocity fluctuations in explaining why linear structures are observed within PPV cubes. We discuss the implications of VDA for both magnetic field studies and predicting polarized galactic emission that acts as the foreground for the Cosmic Microwave Background studies. Additionally, we address the controversy related to the filamentary nature of the HI channel maps and explain the importance of velocity fluctuations in the formation of structures in PPV data cubes. VDA will allow astronomers to obtain velocity fluctuations from almost every piece of spectroscopic PPV data and allow direct investigations of the turbulent velocity field in observations.
We present a new event trigger generator based on the Hilbert-Huang transform, named EtaGen ($eta$Gen). It decomposes a time-series data into several adaptive modes without imposing a priori bases on the data. The adaptive modes are used to find transients (excesses) in the background noises. A clustering algorithm is used to gather excesses corresponding to a single event and to reconstruct its waveform. The performance of EtaGen is evaluated by how many injections in the LIGO simulated data are found. EtaGen is viable as an event trigger generator when compared directly with the performance of Omicron, which is currently the best event trigger generator used in the LIGO Scientific Collaboration and Virgo Collaboration.
The knowledge of transitions between regular, laminar or chaotic behavior is essential to understand the underlying mechanisms behind complex systems. While several linear approaches are often insufficient to describe such processes, there are several nonlinear methods which however require rather long time observations. To overcome these difficulties, we propose measures of complexity based on vertical structures in recurrence plots and apply them to the logistic map as well as to heart rate variability data. For the logistic map these measures enable us not only to detect transitions between chaotic and periodic states, but also to identify laminar states, i.e. chaos-chaos transitions. The traditional recurrence quantification analysis fails to detect the latter transitions. Applying our new measures to the heart rate variability data, we are able to detect and quantify the laminar phases before a life-threatening cardiac arrhythmia occurs thereby facilitating a prediction of such an event. Our findings could be of importance for the therapy of malignant cardiac arrhythmias.
Identifying galaxy groups from redshift surveys of galaxies plays an important role in connecting galaxies with the underlying dark matter distribution. Current and future high-$z$ spectroscopic surveys, usually incomplete in redshift sampling, present both opportunities and challenges to identifying groups in the high-$z$ Universe. We develop a group finder that is based on incomplete redshift samples combined with photometric data, using a machine learning method to assign halo masses to identified groups. Test using realistic mock catalogs shows that $gtrsim 90%$ of true groups with halo masses $rm M_h gtrsim 10^{12} M_{odot}/h$ are successfully identified, and that the fraction of contaminants is smaller than $10%$. The standard deviation in the halo mass estimation is smaller than 0.25 dex at all masses. We apply our group finder to zCOSMOS-bright and describe basic properties of the group catalog obtained.
The energy cascade rate of turbulence can be measured with the structure function. In practice, the 3D velocity of the gas in molecular cloud is hard to measure, which makes the measurement of structure function difficult. In the case of thin molecular clouds perpendicular to the line of sight, the structure function $S^2_{ tt}$ can be measured with core velocity dispersion (CVD), ${rm CVD}^2=frac{1}{2}S^2_{ tt}$. This method was extended to the case when the thin molecular cloud is not perpendicular to the line of sight, with intersection angle $theta$, ${rm CVD}^2=frac{1}{2}S^2_{ tt}left(1-frac{1}{8}cos^2thetaright)R^{2/3}$, where $R$ can be expressed with elliptic integrals of the second kind $E(k,varphi)$ as $R=frac{2}{pi}E(costheta,frac{pi}{2})$.
Understanding the physics of how stars form is a highly-prioritized goal of modern Astrophysics, in part because star formation is linked to both galactic dynamics on large scales and to the formation of planets on small scales. It is well-known that stars form from the gravitational collapse of molecular clouds, which are in turn formed out of the turbulent interstellar medium. Star formation is highly inefficient, with one of the likely culprits being the regulation against gravitational collapse provided by magnetic fields. Measurement of the polarized emission from interstellar dust grains, which are partially aligned with the magnetic field, provides a key tool for understanding the role these fields play in the star formation process. Over the past decade, much progress has been made by the most recent generation of polarimeters operating over a range of wavelengths (from the far-infrared through the millimeter part of the spectrum) and over a range of angular resolutions (from less than an arcsecond through fractions of a degree). Future developments in instrument sensitivity for ground-based, airborne, and space-borne polarimeters operating over range of spatial scales are critical for enabling revolutionary steps forward in our understanding of the magnetized turbulence from which stars are formed.