scholarly journals The spin–temperature dependence of the 21-cm–LAE cross-correlation

2020 ◽  
Vol 496 (1) ◽  
pp. 581-589
Author(s):  
Caroline Heneka ◽  
Andrei Mesinger
Keyword(s):  
Correlation Function ◽  
Cross Correlation ◽  
Cross Correlation Function ◽  
H Ii Regions ◽  
Spin Temperature ◽  
Common Assumption ◽  
Cold Spots ◽  
The Common ◽  
The Mean ◽  
The Cross

ABSTRACT Cross-correlating 21 cm with known cosmic signals will be invaluable proof of the cosmic origin of the first 21-cm detections. As some of the widest fields available, comprising thousands of sources with reasonably known redshifts, narrow-band Lyman-α emitter (LAE) surveys are an obvious choice for such cross-correlation. Here, we revisit the 21-cm–LAE cross-correlation, relaxing the common assumption of reionization occurring in a pre-heated intergalactic medium (IGM). Using specifications from the Square Kilometre Array and the Subaru Hyper Supreme-Cam, we present new forecasts of the 21-cm–LAE cross-correlation function at z ∼ 7. We sample a broad parameter space of the mean IGM neutral fraction and spin temperature, ($\bar{x}_{\rm H\,{\small I}}$, $\bar{T}_{\rm S}$). The sign of the cross-correlation roughly follows the sign of the 21-cm signal: Ionized regions that surround LAEs correspond to relative hot spots in the 21-cm signal when the neutral IGM is colder than the CMB, and relative cold spots when the neutral IGM is hotter than the CMB. The amplitude of the cross-correlation function generally increases with increasing $\bar{x}_{\rm H\,{\small I}}$, following the increasing bias of the cosmic H ii regions. As is the case for 21 cm, the strongest cross signal occurs when the IGM is colder than the CMB, providing a large contrast between the neutral regions and the ionized regions, which host LAEs. We also vary the topology of reionization and the epoch of X-ray heating. The cross-correlation during the first half of reionization is sensitive to these topologies, and could thus be used to constrain them.

scholarly journals Measuring precise radial velocities and cross-correlation function line-profile variations using a Skew Normal density

2019 ◽  
Vol 622 ◽  
pp. A131 ◽  
Author(s):  
U. Simola ◽  
X. Dumusque ◽  
J. Cisewski-Kehe
Keyword(s):  
Correlation Function ◽  
Cross Correlation ◽  
Cross Correlation Function ◽  
Normal Density ◽  
Inverse Slope ◽  
Stellar Activity ◽  
New Model ◽  
The Mean ◽  
The Asymmetry ◽  
Skew Normal

Context. Stellar activity is one of the primary limitations to the detection of low-mass exoplanets using the radial-velocity (RV) technique. Stellar activity can be probed by measuring time-dependent variations in the shape of the cross-correlation function (CCF). It is therefore critical to measure with high-precision these shape variations to decorrelate the signal of an exoplanet from spurious RV signals caused by stellar activity. Aims. We propose to estimate the variations in shape of the CCF by fitting a Skew Normal (SN) density which, unlike the commonly employed Normal density, includes a Skewness parameter to capture the asymmetry of the CCF induced by stellar activity and the convective blueshift. Methods. We compared the performances of the proposed method to the commonly employed Normal density using both simulations and real observations with different levels of activity and signal-to-noise ratios. Results. When considering real observations, the correlation between the RV and the asymmetry of the CCF and between the RV and the width of the CCF are stronger when using the parameters estimated with the SN density rather than those obtained with the commonly employed Normal density. In particular, the strongest correlations have been obtained when using the mean of the SN as an estimate for the RV. This suggests that the CCF parameters estimated using a SN density are more sensitive to stellar activity, which can be helpful when estimating stellar rotational periods and when characterizing stellar activity signals. Using the proposed SN approach, the uncertainties estimated on the RV defined as the median of the SN are on average 10% smaller than the uncertainties calculated on the mean of the Normal. The uncertainties estimated on the asymmetry parameter of the SN are on average 15% smaller than the uncertainties measured on the Bisector Inverse Slope Span (BIS SPAN), which is the commonly used parameter to evaluate the asymmetry of the CCF. We also propose a new model to account for stellar activity when fitting a planetary signal to RV data. Based on simple simulations, we were able to demonstrate that this new model improves the planetary detection limits by 12% compared to the model commonly used to account for stellar activity. Conclusions. The SN density is a better model than the Normal density for characterizing the CCF since the correlations used to probe stellar activity are stronger and the uncertainties of the RV estimate and the asymmetry of the CCF are both smaller.

Simultaneous Measurement of Temperature and Velocity Using µPIV

2006 ◽  
Author(s):  
Pramod Chamarthy ◽  
Steven T. Wereley ◽  
Suresh V. Garimella
Keyword(s):  
Brownian Motion ◽  
Correlation Function ◽  
Cross Correlation ◽  
Cross Correlation Function ◽  
Motion Information ◽  
Peak Broadening ◽  
Constant Temperature Water Bath ◽  
Gravity Driven ◽  
The Cross ◽  
Gravity Driven Flow

In μPIV, for a uniform velocity field the displacement of the cross-correlation function gives the velocity of the fluid and the broadening of the peak-width represents the amount of Brownian motion present. In the presence of a linear or a parabolic shear, the shape of the cross-correlation function would have both the Brownian motion information as well as the velocity distribution information. In the present work, the broadening of the cross-correlation function caused by the velocity gradient was subtracted from the total peak broadening in order to isolate the Brownian motion information and thus infer temperature. To the authors' knowledge, this technique has not been applied to measure the temperature of a moving fluid. The experiments were conducted in a gravity driven flow through a tube surrounded by a constant temperature water bath.

Damage Detection Based on the Cross Correlation Function Amplitude Vector and its Application to the ASCE Benchmark Structure

2007 ◽  
Vol 353-358 ◽  
pp. 2317-2320 ◽  
Author(s):  
Zhe Feng Yu ◽  
Zhi Chun Yang
Keyword(s):  
Correlation Function ◽  
Damage Detection ◽  
Structural Damage ◽  
Cross Correlation ◽  
Relative Difference ◽  
Random Excitation ◽  
Cross Correlation Function ◽  
Vibration Responses ◽  
Specific Frequency ◽  
The Cross

A new method for structural damage detection based on the Cross Correlation Function Amplitude Vector (CorV) of the measured vibration responses is presented. Under a stationary random excitation with a specific frequency spectrum, the CorV of the structure only depends on the frequency response function matrix of the structure, so the normalized CorV has a specific shape. Thus the damage can be detected and located with the correlativity and the relative difference between CorVs of the intact and damaged structures. With the benchmark problem sponsored by ASCE Task Group on Structural Health Monitoring, the CorV is proved an effective approach to detecting the damage in structures subject to random excitations.

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