Forest without Trees is still Fruitful: Constraints on the thermal state of the neutral IGM at $z\approx5.6$ with the 21-cm forest power spectrum

Abstract

Neutral regions of the intergalactic medium (IGM) during the Epoch of Reionization (EoR) remain largely unexplored due to the limitations of existing probes. Owing to discoveries of numerous high-redshift radio-bright sources, the 21-cm forest, a series of absorption features imprinted by the neutral IGM in the spectra of such sources, now offers an attractive probe of the thermal and ionization state of the predominantly neutral IGM at $z\gtrsim5.5$. We analyse archival upgraded Giant Metrewave Radio Telescope (uGMRT) observations of J352-15, the brightest known radio-loud quasar in the EoR ($z=5.82$), to measure the one-dimensional (1D) power spectrum of the 21-cm forest. By comparing the observed power spectrum with forward-modelled synthetic spectra generated from cosmological simulations spanning a wide range of ionization and X-ray pre-heating scenarios, we perform Bayesian inference even in the absence of a statistical detection. We also present an independent Murchison Widefield Array measurement, although its lower sensitivity prevents competitive constraints. Using uGMRT, we achieve a sensitivity of $3.62\,\rm mJy\,beam^{-1}$ per $6.1\,\rm kHz$ channel. While we do not detect the 21-cm forest statistically, the null detection jointly constrains the mean neutral hydrogen fraction, $\langle x_{\rm HI}\rangle$, and the mean temperature of the neutral IGM, $\langle T_{\rm HI}\rangle$. At the $68\%$ credible level, our analysis disfavours cold and substantially neutral IGM models at $z\approx5.6$, including models with $\langle T_{\rm HI}\rangle \lesssim 27\,\rm K$ for $\langle x_{\rm HI}\rangle=0.1$. These limits probe parameter space allowed by existing Ly$\alpha$ and 21-cm observations, indicating substantial pre-heating of the neutral IGM above the adiabatic cooling floor. This demonstrates that the 21-cm forest has entered the regime of observationally informative statistics.