Redshift space three-point correlation function of IGM at z < 0.48. Issue 3 (15th November 2021) - Maitra, Soumak; Srianand, Raghunathan; Gaikwad, Prakash; Khandai, Nishikanta
ABSTRACT: Ly α forest decomposed into Voigt profile components allows us to study clustering properties of the intergalactic-medium and its dependence on various physical quantities. Here, we report the first detections of probability excess of low- z (i.e z < 0.48) Ly α absorber triplets over redshift-space scale of r ∥ ≤ 8 pMpc (Mpc in physical units) with maximum amplitude of 8.76^+1.96_-1.65 at a longitudinal separation of 1–2 pMpc. We measure non-zero three-point correlation (ζ = 4.76^+1.98_-1.67 ) only at this scale with reduced three-point correlation Q = 0.95^+0.39_-0.38 . The measured ζ shows an increasing trend with increasing minimum H i column density ( N H i ) threshold while Q does not show any N H i dependence. About 88 per cent of the triplets contributing to ζ (at z ≤ 0.2) have nearby galaxies (whose distribution is known to be complete for ∼0.1 L * at z < 0.1 and for ∼ L * at z ∼ 0.25 within 20 arcsec to the quasar sightlines) within velocity separation of 500 km s −1 and median impact parameter of 405 pkpc. The measured impact parameters are consistent with majority of the identified triplets not originating from individual galaxies but tracing the underlying galaxy distribution. Frequency of occurrence of Broad-Ly α absorbers ( b > 40 km s −1 ) in triplets (∼85 per cent) is factor ∼3 higher than that found among the full sample (∼32 per cent). Using four different cosmological simulations, we quantify the effect of peculiar velocities and feedback and show that most of the observed trends are broadly reproduced. However, ζ at small scales ( r ∥ < 1 pMpc) and its b -dependence found in simulations are inconsistent with observations. This could either be related to the failure of these simulations to reproduce the observed b and N H i distributions for N H i > 10 14 cm −2 self-consistently or to the wide spread of signal-to-noise ratio in the observed data.