Three- and two-point spatial correlations of intergalactic medium at z ∼ 2 using projected quasar triplets

Abstract

We present analysis of two-and three-point correlation functions of Lyα forest (at 2 ≤ z ≤ 2.5) using X-Shooter spectra of three background quasar triplets probing transverse separations of 0.5-1.6 pMpc. We present statistics based on transmitted flux and clouds identified using Voigt profile fitting. We show that the observed two-, three-point correlation functions and reduced three-point correlation (i.e Q) are well reproduced by our simulations. We assign probabilities for realising all the observed correlation properties simultaneously using our simulations. Our simulations suggest an increase in correlation amplitudes and Q with increasing N HI . We roughly see this trend in the observations too. We identify a concurrent gap of 17Å (i.e 14.2 h −1 cMpc, one of the longest reported) wide in one of the triplets. Such gap is realised only in 14.2% of our simulated sightlines and most of the time belongs to a void in the matter distribution. In the second triplet, we detect DLAs along all three sightlines (with spatial separations 0.64 to 1.6 pMpc) within a narrow redshift interval (i.e ∆z = 0.088). Detection of a foreground quasar (∼ 1 pMpc from the triplet sightlines) and excess partial Lyman Limit systems around these DLAs suggest that we may be probing a large over-dense region. We also report positive C iv-C iv correlations up to ∼ 500 kms −1 only in the longitudinal direction. Additionally, we conclude a positive C iv-Lyα correlations for higher N HI thresholds up to a scale of ∼ 1000 kms −1 both in transverse and longitudinal directions.

Probing the thermal state of the intergalactic medium at z > 5 with the transmission spikes in high-resolution Ly α forest spectra

“…In Appendix B we use such rescaling to show how the three flux statistics we consider here depend on thermal parameters T0 and γ and the photo-ionization rate, and demonstrate that it is the width distribution of the transmission spikes which is most sensitive to the thermal state of the gas. We further show that, for the reionization and thermal history models we consider in this work, the spike statistics are only very weakly affected by pressure (Jeans) smoothing at the typical gas densities probed by the Lyα transmission spikes (Gnedin & Hui 1998;Theuns et al 2000;Peeples et al 2010;Kulkarni et al 2015;Lukić et al 2015;Nasir et al 2016;Maitra et al 2019;Wu et al 2019). We use the spike width distribution to obtain an estimate of the best fit values and uncertainty for the thermal parameters 8 .…”

“…The FPS is a measure of the clustering of the pixels in transmission spikes. One can also study the two point correlation of spikes (see e.g., Maitra et al 2019). However, due to the limited number of observed QSOs and the smaller number of spikes detected per sightline, the two point correlation function of spikes is rather noisy.…”

A consistent and robust measurement of the thermal state of the IGM at 2 ≤ z ≤ 4 from a large sample of Ly α forest spectra: evidence for late and rapid He ii reionization

“…The increase in temperature of the IGM due to He ii reionization has the following main effects on the H i Lyα forest (i) broadening of the absorption features (Schaye et al 2000;Lidz et al 2010;Becker et al 2011), (ii) decrease in neutral fraction due to the temperature dependence of the recombination rate (Rauch et al 1997 and (iii) pressure smoothing of the density and flux fields (Gnedin & Hui 1998;Peeples et al 2010;Kulkarni et al 2015;Lukić et al 2015;Rorai et al 2017a;Maitra et al 2019). Since increasing the temperature of the IGM leads to smoothing of the flux, the Lyα forest statistics used in the past for measuring thermal parameters are based on either extracting small scale features or measuring the broadening of the absorption lines.…”

“…cite has been shown to reproduce the results of full hydrosimulations to well within 10 percent accuracy (Gaikwad et al 2018). viper runs on parallel architectures and allows us to perform a Voigt profile analysis for large samples of observed and simulated spectra consistently (see Maitra et al 2019Maitra et al , 2020, for a clustering analysis using Voigt profile components). Thanks to these two codes, we are in a position to measure the physical parameters of the IGM from Lyα forest data by simultaneously using the different statistics mentioned above.…”

A hierarchical field-level inference approach to reconstruction from sparse Lyman-α forest data

“…At present, major analyses of the Ly-α forest focus only on the analysis of the matter power spectrum (e.g. Croft et al 1998;Seljak et al 2006;Viel et al 2006;Bird et al 2011;Slosar et al 2011;Busca et al 2013;Palanque-Delabrouille et al 2015;Rossi et al 2015;Nasir et al 2016;Yèche et al 2017;Rossi 2017;Bautista et al 2017;Boera et al 2019;Blomqvist et al 2019;Maitra et al 2019). However, these approaches ignore significant amounts of information contained in the higher-order statistics of the matter density field as generated by non-linear gravitational dynamics in the late time universe (He et al 2018).…”