arXiv subjects

Prakash Gaikwad

Publications and source records attributed to Prakash Gaikwad.

At least 19 recordsLinked to original sources

arXiv2026

Forecast for the detectability of patchy hydrogen reionization in WEAVE-QSO measurements of the Lyman-$α$ forest power spectrum at redshift $z \geq 4$

We present the first detailed forecasts for the detectability of patchy hydrogen reionization in the one-dimensional Ly$α$ forest power spectrum to be measured by the WEAVE-QSO survey. Using the Sherwood-relics reionization simulations and a WEAVE-QSO survey configuration, we generate mock spectra in four redshift bins, $z=4.0,4.2,4.4,$ and $4.6$, in which relic ionization and temperature fluctuations from patchy hydrogen reionization enhance the Ly$α$ forest power spectrum on large scales (i.e., at wavenumber $k\sim 10^{-3},\mathrm{s\,km^{-1}}$). Our Ly$α$ forest pipeline forecasts the power spectrum covariance by considering sample size, spectral resolution, noise subtraction, continuum placement, metal contamination, and damping wings from high-column density absorbers. Applying our covariance forecast within a Bayesian parameter inference framework, we find that the signature of patchy hydrogen reionization should be detectable at a significance of $\simeq 4.5σ$. The forthcoming WEAVE-QSO 1D power spectrum measurements should therefore be able to directly detect and characterize the large-scale relic imprint of patchy hydrogen reionization in the Ly$α$ forest power spectrum at $z\geq 4$.

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arXiv2026

Uncertainty-Aware Deep Learning for the Ly$α$ Forest: CNN-Based Absorber Detection and Characterization

The Ly$α$ forest is a powerful probe of the intergalactic medium and small-scale matter distribution, but deriving absorber properties traditionally requires computationally expensive Voigt-profile fitting. We present a convolutional neural network (CNN) that identifies and characterizes H I Ly$α$ absorbers directly from quasar spectra. The model is trained on synthetic spectra generated from the IllustrisTNG simulation and fitted with the VIPER Voigt-profile fitting code to provide training labels. The network simultaneously predicts absorber presence, column density ($N_{\rm HI}$), Doppler parameter ($b_{\rm HI}$), and line centroid. On simulated spectra, the CNN achieves an F1 score of $\sim$0.8, with mean absolute errors of $\sim$0.18 in $\log N_{\rm HI}$ and $\sim$0.10 in $\log b_{\rm HI}$. It accurately reproduces the H I column density distribution function (CDDF) and the $b_{\rm HI}$--$N_{\rm HI}$ relation, recovering CDDF slopes consistent with VIPER and a lower-envelope relation with an RMS difference of only 0.36 km s$^{-1}$. Applied to high-resolution UVES spectra, performance decreases to an F1 score of $\sim$0.5, with mean absolute errors of $\sim$0.34 in $\log N_{\rm HI}$ and $\sim$0.21 in $\log b_{\rm HI}$. Latent-space analysis reveals a significant domain shift between the simulated and observational spectra, contributing to the reduced performance. Nevertheless, the CNN preserves the observed CDDF and $b_{\rm HI}$--$N_{\rm HI}$ distributions, yielding CDDF slopes consistent with VIPER and a lower-envelope RMS difference of 2.96 km s$^{-1}$. Monte Carlo dropout is implemented during inference to quantify predictive uncertainties. Together with its computational efficiency, the method provides a scalable and uncertainty-aware framework for Ly$α$ forest analysis in upcoming spectroscopic surveys.

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arXiv2026

NISER-IUCAA New Simulations of JWST GAlaxies and Quasars(NINJA): Properties of galaxies at $5 \leq z \leq 10$

We present the NINJA suite of cosmological hydrodynamical simulations developed to investigate galaxy formation and evolution at $z \gtrsim 5$ in the era of JWST. Using our fiducial simulation, we explore a range of spectral synthesis prescriptions and dust attenuation models, demonstrating that suitably chosen parameters can reproduce the observed UV luminosity functions (UVLFs) over $5 \leq z \leq 10$. In all cases, the inferred dust-to-metal ratio evolves with redshift, although its normalization at fixed redshift varies by a factor of $\sim 7$, depending on the adopted dust--metallicity scaling and attenuation curve. These model variations introduce substantial scatter in predictions for the $B$-band luminosity function, the H$α$ luminosity function, the UV slope--UV magnitude relation, the stellar mass--Balmer ratio relation, and the relation between stellar and nebular colour excesses. Simultaneously reproducing these observables across multiple redshifts will therefore be essential for constraining dust models at high redshift with forthcoming observations. Observations of galaxies spanning a broad range of stellar masses with the Atacama Large Millimeter/submillimeter Array (ALMA) will provide particularly strong and independent constraints on dust properties. Our fiducial models underpredict the UV luminosity function at $z \geq 10$ relative to current observations, even when adopting a top-heavy IMF and neglecting dust attenuation. We find that galaxy properties are not fully converged at these redshifts in our simulation, indicating that higher-resolution simulations are required to robustly model galaxies at $z > 10$. We further emphasize that degeneracies between feedback prescriptions used in our simulation and dust properties must be carefully addressed when interpreting high-redshift observations and calibrating galaxy formation models.

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arXiv2026

An improved model for the effect of correlated Si-III absorption on the one-dimensional Lyman-$α$ forest power spectrum

We present an analysis of Si III absorption and its effect on the 1D Ly$α$ forest power spectrum using the Sherwood-Relics hydrodynamical simulation suite. In addition to oscillations from the Ly$α$--Si III cross correlation that are damped toward smaller scales, we find an enhancement in small-scale power that has been ignored in previous studies. We therefore develop a new analytical fitting function that captures two critical effects that have previously been neglected: distinct Ly$α$ and Si III line profiles, and a variable ratio for coeval Ly$α$ and Si III optical depths. In contrast to earlier work, we also predict amplitudes for the Si III power spectrum and Ly$α$--Si III cross power spectrum that decrease toward lower redshift due to the hardening metagalactic UV background spectrum at $z\lesssim 3.5$. The fitting function is validated by comparison against multiple simulated datasets at redshifts $2.2\leq z \leq 5.0$ and wavenumbers $k < 0.2\rm\,s\,km^{-1}$. Our model has little effect on existing warm dark matter constraints from the Ly$α$ forest when adopting a physically motivated prior on the silicon abundance. It will, however, be an essential consideration for future, high precision Ly$α$ forest power spectrum measurements.

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arXiv2025

Efficient Modelling of Lyman-α opacity fluctuations during late reionization epoch

The Lyman-$α$ forest opacity fluctuations observed from high-redshift quasar spectra have been proven to be extremely successful in order to probe the late phase of the reionization epoch. For ideal modeling of these opacity fluctuations, one of the main challenges is to satisfy the extremely high dynamic range requirements of the simulation box, resolving the Lyman-$α$ forest while probing the large cosmological scales. In this study, we adopt an efficient approach to model Lyman-$α$ opacity fluctuations in a coarse simulation volume, utilizing the semi-numerical reionization model SCRIPT (including inhomogeneous recombination and radiative feedback) integrated with a realistic photoionization background fluctuation generating model. Our model crucially incorporates ionization and temperature fluctuations, which are consistent with the reionization model. After calibrating our method with respect to high-resolution full hydrodynamic simulation, Nyx, we compared the models with available observational data at the redshift range, $z=5.0-6.1$. With a fiducial reionization model (reionization end at $z=5.8$), we demonstrated that the observed scatter in the effective optical depth can be matched reasonably well by tuning the free parameters of our model, i.e., the effective ionizing photon mean free path and mean photoionization rate. We further pursued an MCMC-based parameter space exploration, utilizing the available data to put constraints on the above free parameters. Our estimation prefers a slightly higher photoionization rate and slightly lower mean free path than the previous studies, which is also a consequence of temperature fluctuations. This study holds significant promise for efficiently extracting important physical information about the Epoch of Reionization, utilizing the wealth of available and upcoming observational data.

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arXiv2025

Measuring photo-ionization rate and mean free path of HeII ionizing photons at $2.5 \leq z \leq 3.6$: Evidence for late and rapid HeII reionization Part-II

We present measurements of the spatially averaged HeII photo-ionization rate ($\langle Γ_{\rm HeII} \rangle$), mean free path of HeII ionizing photons ($λ_{\rm mfp, HeII}$), and HeII fraction ($f_{\rm HeII}$) across seven redshift bins within the redshift range $2<z<4$. The measurements are obtained by comparing the observed effective optical depth distribution of HeII ($τ_{\rm eff, HeII}$) with models generated by post-processing of the Sherwood simulation suite using our code EXCITE. With EXCITE, we efficiently explore a large parameter space ($\sim 15000$ models) by varying $λ_{\rm mfp, HeII}$ and $\langle Γ_{\rm HeII} \rangle$. We employ Anderson-Darling test for the cumulative distribution of $τ_{\rm eff, HeII}$ to simultaneously measure $λ_{\rm mfp, HeII}$ and $\langle Γ_{\rm HeII} \rangle$. Our measurements account for possible observational and modeling uncertainties stemming mainly from the finite signal-to-noise ratio of the observed data and thermal parameter uncertainties. We find significant evolution, with the best-fit $\langle Γ_{\rm HeII} \rangle$ and $λ_{\rm mfp, HeII}$ decreasing by factors of $\sim 4.32$ and $ \sim 3.27$, respectively, from $z = 2.88$ to $z = 3.16$. Based on these measurements, we constrain the emissivity at the HeII ionization frequency ($ε_{228}$) and HeII ionizing photon emission rate ($\dot{n}$), finding consistency with results from galaxy and QSO surveys. Comparison of our measured parameters with widely used uniform UVB models supports a scenario where HeII reionization is not completed before $z\sim2.74$. Our measured evolution is complementary and in good agreement with recent measurements of thermal parameters of the IGM, suggesting a coherent picture of rather late and rapid HeII reionization.

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arXiv2025

The impact of faint AGN discovered by JWST on reionization

The relative contribution of emission from stellar sources and accretion onto supermassive black holes to reionization has been brought into focus again by the apparent high abundance of faint Active Galactic Nuclei (AGN) at $4\lesssim z\lesssim11$ uncovered by JWST. We investigate here the contribution of these faint AGN to hydrogen and the early stages of helium reionization using the GPU-based radiative transfer code ATON-HE by post-processing a cosmological hydrodynamical simulation from the sherwood-relics suite of simulations. We study four models: two galaxy-only late-end reionization models, a QSO-assisted and a QSO-only model. In the QSO-assisted model, 1% of the haloes host AGN, with AGN luminosities scaled to contribute 17% of the total hydrogen-ionizing emissivity. In the QSO-only model, quasars account for all the hydrogen-ionizing emissivity, with 10% of the haloes hosting AGN. The SED of AGN is assumed to be a power-law with $α=-1.7$ each with a 10 Myr lifetime. All models are calibrated to the observed mean Lyman-$α$ forest transmission at $5\lesssim z\lesssim6.2$. The QSO-assisted model requires an emissivity similar to the galaxy-only models and fits the observed distribution of the Lyman-$α$ optical depths well. The QSO-only model is inconsistent with the observed Lyman-$α$ optical depths distribution, and produces excessively high IGM temperatures at $z\lesssim 5$ due to an early onset of HeII reionization, unless the escape fraction of HeII-ionizing photons is assumed to be low. Our results suggest that a modest AGN contribution to reionization aligns with the Lyman-$α$ forest data, whereas an AGN dominated scenario is difficult to reconcile.

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arXiv2024

Percent-level timing of reionization: self-consistent, implicit-likelihood inference from XQR-30+ Ly$α$ forest data

The Lyman alpha (Lya) forest in the spectra of z>5 quasars provides a powerful probe of the late stages of the Epoch of Reionization (EoR). With the recent advent of exquisite datasets such as XQR-30, many models have struggled to reproduce the observed large-scale fluctuations in the Lya opacity. Here we introduce a Bayesian analysis framework that forward-models large-scale lightcones of IGM properties, and accounts for unresolved sub-structure in the Lya opacity by calibrating to higher-resolution hydrodynamic simulations. Our models directly connect physically-intuitive galaxy properties with the corresponding IGM evolution, without having to tune "effective" parameters or calibrate out the mean transmission. The forest data, in combination with UV luminosity functions and the CMB optical depth, are able to constrain global IGM properties at percent level precision in our fiducial model. Unlike many other works, we recover the forest observations without evoking a rapid drop in the ionizing emissivity from z~7 to 5.5, which we attribute to our sub-grid model for recombinations. In this fiducial model, reionization ends at $z=5.44\pm0.02$ and the EoR mid-point is at $z=7.7\pm0.1$. The ionizing escape fraction increases towards faint galaxies, showing a mild redshift evolution at fixed UV magnitude, Muv. Half of the ionizing photons are provided by galaxies fainter than Muv~-12, well below direct detection limits of optical/NIR instruments including JWST. We also show results from an alternative galaxy model that does not allow for a redshift evolution in the ionizing escape fraction. Despite being decisively disfavored by the Bayesian evidence, the posterior of this model is in qualitative agreement with that from our fiducial model. We caution however that our conclusions regarding the early stages of the EoR and which sources reionized the Universe are more model-dependent.

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arXiv2024

Signatures of warm dark matter in the cosmological density fields extracted using Machine Learning

We aim to construct a machine-learning approach that allows for a pixel-by-pixel reconstruction of the intergalactic medium (IGM) density field for various warm dark matter (WDM) models using the Lyman-alpha forest. With this regression machinery, we constrain the mass of a potential WDM particle from observed Lyman-alpha sightlines directly from the density field. We design and train a Bayesian neural network on the supervised regression task of recovering the optical depth-weighted density field $Δ_τ$ as well as its reconstruction uncertainty from the Lyman-alpha forest flux field. We utilise the Sherwood-Relics simulation suite at $4.1\leq z \leq 5.0$ as the main training and validation dataset. Leveraging the density field recovered by our neural network, we construct an inference pipeline to constrain the WDM particle masses based on the probability distribution function of the density fields. We find that our trained Bayesian neural network can accurately recover within a $1σ$ error $\geq 85\%$ of the density field pixels from a validation simulated dataset that encompasses multiple WDM and thermal models of the IGM. When predicting on Lyman-alpha skewers generated using the alternative hydrodynamical code Nyx not included in the training data, we find a $1σ$ accuracy rate $\geq 75\%$. We consider 2 samples of observed Lyman-alpha spectra from the UVES and GHOST instruments, at $z=4.4$ and $z=4.9$ respectively and fit the density fields recovered by our Bayesian neural network to constrain WDM masses. We find lower bounds on the WDM particle mass of $m_{\mathrm{WDM}} \geq 3.8$ KeV and $m_{\mathrm{WDM}} \geq 2.2$ KeV at $2σ$ confidence, respectively. We are able to match current state-of-the-art WDM particle mass constraints using up to 40 times less observational data than Markov Chain Monte Carlo techniques based on the Lyman-alpha forest power spectrum.

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arXiv2024

Damping wings in the Lyman-α forest: a model-independent measurement of the neutral fraction at 5.4<z<6.1

Recent observations have positioned the endpoint of the Epoch of Reionisation (EoR) at redshift $z \sim 5.3$. However, observations of the Lyman-$α$ forest have not yet been able to discern whether reionisation occurred slowly and late, with substantial neutral hydrogen persisting at redshift $\sim 6$, or rapidly and earlier, with the apparent late end driven by the fluctuating UV background. Gunn-Peterson (GP) absorption troughs are solid indicators that reionisation is not complete until $z=5.3$, but whether they contain significantly neutral gas has not yet been proven. We aim to answer this question by directly measuring, for the first time, the neutral hydrogen fraction ($x_\mathrm{HI}$) at the end of the EoR ($5 \lesssim z \lesssim 6$) in high-redshift quasars spectra. For high neutral fractions $x_\mathrm{HI}\gtrsim0.1$, GP troughs exhibit damping wing (DW) absorption extending over $1000$ km s$^{-1}$ beyond the troughs. While conclusively detected in Lyman-$α$ emission lines of quasars at $z\geq7$, DWs are challenging to observe in the general Lyman-$α$ forest due to absorption complexities and small-scale stochastic transmission features. We report the first successful identification of the stochastic DW signal adjacent to GP troughs at redshifts $z=5.6$ through careful stacking of the dark gaps in Lyman-$α$ forest. We use the signal to present a measurement of the corresponding global $x_\mathrm{HI}=0.19\pm0.07$ $(_{-0.16}^{+0.11})$ at $1σ$ $(2σ)$ at $z=5.6$ and a limit $x_\mathrm{HI}<0.44$ at $z=5.9$. The detection of this signal demonstrates the existence of substantially neutral islands near the conclusion of the EoR, unequivocally signaling a late-and-slow reionization scenario.

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arXiv2024

Damping Wing-Like Features in the Stacked Ly$α$ Forest: Potential Neutral Hydrogen Islands at $z<6$

Recent quasar absorption line observations suggest that reionization may end as late as $z \approx 5.3$. As a means to search for large neutral hydrogen islands at $z<6$, we revisit long dark gaps in the Ly$β$ forest in VLT/X-Shooter and Keck/ESI quasar spectra. We stack the Ly$α$ forest corresponding to both edges of these Ly$β$ dark gaps and identify a damping wing-like extended absorption profile. The average redshift of the stacked forest is $z=5.8$. By comparing these observations with reionization simulations, we infer that such a damping wing-like feature can be naturally explained if these gaps are at least partially created by neutral islands. Conversely, simulated dark gaps lacking neutral hydrogen struggle to replicate the observed damping wing features. Furthermore, this damping wing-like profile implies that the volume-averaged neutral hydrogen fraction must be $\langle x_{\rm HI} \rangle \geq 6.1 \pm 3.9\%$ at $z = 5.8$. Our results offer robust evidence that reionization extends below $z=6$.

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arXiv2024

FLAME: Fitting Ly$α$ Absorption lines using Machine learning

We introduce FLAME, a machine-learning algorithm designed to fit Voigt profiles to HI Lyman-alpha (Ly$α$) absorption lines using deep convolutional neural networks. FLAME integrates two algorithms: the first determines the number of components required to fit Ly$α$ absorption lines, and the second calculates the Doppler parameter $b$, the HI column density N$_{\rm HI}$, and the velocity separation of individual components. For the current version of FLAME, we trained it on low-redshift Ly$α$ forests observed with the far-ultraviolet gratings of the Cosmic Origin Spectrograph (COS) on board the Hubble Space Telescope (HST). Using these data, we trained FLAME on $\sim$ $10^6$ simulated Voigt profiles which we forward-modeled to mimic Ly$α$ absorption lines observed with HST-COS in order to classify lines as either single or double components and then determine Voigt profile-fitting parameters. FLAME shows impressive accuracy on the simulated data, identifying more than 98\% (90\%) of single (double) component lines. It determines $b$ values within $\approx \pm{8}~(15)$ km s$^{-1}$ and log $N_{\rm HI}/ {\rm cm}^2$ values within $\approx \pm 0.3~(0.8)$ for 90\% of the single (double) component lines. However, when applied to real data, FLAME's component classification accuracy drops by $\sim$ 10\%. Nevertheless, there is reasonable agreement between the $b$ and N$_{\rm HI}$ distributions obtained from traditional Voigt profile-fitting methods and FLAME's predictions. Our mock HST-COS data analysis, designed to emulate real data parameters, demonstrates that FLAME is able to achieve consistent accuracy comparable to its performance with simulated data. This finding suggests that the drop in FLAME's accuracy when used on real data primarily arises from the difficulty in replicating the full complexity of real data in the training sample.

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arXiv2024

Deep Learning the Intergalactic Medium using Lyman-alpha Forest at $ 4 \leq z \leq 5$

Unveiling the thermal history of the intergalactic medium (IGM) at $4 \leq z \leq 5$ holds the potential to reveal early onset HeII reionization or lingering thermal fluctuations from HI reionization. We set out to reconstruct the IGM gas properties along simulated Lyman-alpha forest data on pixel-by-pixel basis, employing deep Bayesian neural networks. Our approach leverages the Sherwood-Relics simulation suite, consisting of diverse thermal histories, to generate mock spectra. Our convolutional and residual networks with likelihood metric predicts the Ly$α$ optical depth-weighted density or temperature for each pixel in the Ly$α$ forest skewer. We find that our network can successfully reproduce IGM conditions with high fidelity across range of instrumental signal-to-noise. These predictions are subsequently translated into the temperature-density plane, facilitating the derivation of reliable constraints on thermal parameters. This allows us to estimate temperature at mean cosmic density, $T_{\rm 0}$ with one sigma confidence $δT_{\rm 0} \sim 1000{\rm K}$ using only one $20$Mpc/h sightline ($Δz\simeq 0.04$) with a typical reionization history. Existing studies utilize redshift pathlength comparable to $Δz\simeq 4$ for similar constraints. We can also provide more stringent constraints on the slope ($1σ$ confidence interval $δ{\rm γ} \lesssim 0.1$) of the IGM temperature-density relation as compared to other traditional approaches. We test the reconstruction on a single high signal-to-noise observed spectrum ($20$ Mpc/h segment), and recover thermal parameters consistent with current measurements. This machine learning approach has the potential to provide accurate yet robust measurements of IGM thermal history at the redshifts in question.

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arXiv2024

A modified lognormal approximation of the Lyman-$α$ forest: comparison with full hydrodynamic simulations at $2\leq z\leq 2.7$

Observations of the Lyman-$α$ forest in distant quasar spectra with upcoming surveys are expected to provide significantly larger and higher-quality datasets. To interpret these datasets, it is imperative to develop efficient simulations. One such approach is based on the assumption that baryonic densities in the intergalactic medium (IGM) follow a lognormal distribution. We extend our earlier work to assess the robustness of the lognormal model of the Lyman-$α$ forest in recovering the parameters characterizing IGM state, namely, the mean-density IGM temperature ($T_0$), the slope of the temperature-density relation ($γ$), and the hydrogen photoionization rate ($Γ_{12}$), by comparing with high-resolution Sherwood SPH simulations across the redshift range $2 \leq z \leq 2.7$. These parameters are estimated through a Markov Chain Monte Carlo technique, using the mean and power spectrum of the transmitted flux. We find that the usual lognormal distribution of IGM densities cannot recover the parameters of the SPH simulations. This limitation arises from the fact that the SPH baryonic density distribution cannot be described by a simple lognormal form. To address this, we extend the model by scaling the linear density contrast by a parameter $ν$. While the resulting baryonic density is still lognormal, the additional parameter gives us extra freedom in setting the variance of density fluctuations. With this extension, values of $T_0$ and $γ$ implied in the SPH simulations are recovered at $\sim 1-σ$ ($\lesssim$ 10%) of the median (best-fit) values for most redshifts bins. However, this extended lognormal model cannot recover $Γ_{12}$ reliably, with the best-fit value discrepant by $\gtrsim 3-σ$ for $z > 2.2$. Despite this limitation in the recovery of $Γ_{12}$, we argue that the model remains useful for constraining cosmological parameters.

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arXiv2024

Unveiling Dark Matter free-streaming at the smallest scales with high redshift Lyman-alpha forest

This study introduces novel constraints on the free-streaming of thermal relic warm dark matter (WDM) from Lyman-$α$ forest flux power spectra. Our analysis utilises a high-resolution, high-redshift sample of quasar spectra observed using the HIRES and UVES spectrographs ($z=4.2-5.0$). We employ a Bayesian inference framework and a simulation-based likelihood that encompasses various parameters including the free-streaming of dark matter, cosmological parameters, the thermal history of the intergalactic medium, and inhomogeneous reionization, to establish lower limits on the mass of a thermal relic WDM particle of $5.7\;\mathrm{keV}$ (at 95\% C.L.). This result surpasses previous limits from the Lyman-$α$ forest through reduction of the measured uncertainties due to a larger statistical sample and by measuring clustering to smaller scales ($k_{\rm max}=0.2\;\mathrm{km^{-1}\,s}$). The approximately two-fold improvement due to the expanded statistical sample suggests that the effectiveness of Lyman-$α$ forest constraints on WDM models at high redshifts are limited by the availability of high-quality quasar spectra. Restricting the analysis to comparable scales and thermal history priors as in prior studies ($k_{\rm max}<0.1\;\mathrm{km^{-1}\,s}$) lowers the bound on the WDM mass to $4.1\;\mathrm{keV}$. As the precision of the measurements increases, it becomes crucial to examine the instrumental and modelling systematics. On the modelling front, we argue that the impact of the thermal history uncertainty on the WDM particle mass constraint has diminished due to improved independent observations. At the smallest scales, the primary source of modeling systematic arises from the structure in the peculiar velocity of the intergalactic medium and inhomogeneous reionization.

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arXiv2023

Constraints on the Evolution of the Ionizing Background and Ionizing Photon Mean Free Path at the End of Reionization

The variations in Ly$α$ forest opacity observed at $z>5.3$ between lines of sight to different background quasars are too strong to be caused by fluctuations in the density field alone. The leading hypothesis for the cause of this excess variance is a late, ongoing reionization process at redshifts below six. Another model proposes strong ionizing background fluctuations coupled to a short, spatially varying mean free path of ionizing photons, without explicitly invoking incomplete reionization. With recent observations suggesting a short mean free path at $z\sim6$, and a dramatic improvement in $z>5$ Ly$α$ forest data quality, we revisit this latter possibility. Here we apply the likelihood-free inference technique of approximate Bayesian computation to jointly constrain the hydrogen photoionization rate $Γ_{\rm HI}$ and the mean free path of ionizing photons $λ_{\rm mfp}$ from the effective optical depth distributions at $z=5.0$-$6.1$ from XQR-30. We find that the observations are well-described by fluctuating mean free path models with average mean free paths that are consistent with the steep trend implied by independent measurements at $z\sim5$-$6$, with a concomitant rapid evolution of the photoionization rate.

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arXiv2023

Measuring the photo-ionization rate, neutral fraction and mean free path of HI ionizing photons at $4.9 \leq z \leq 6.0$ from a large sample of XShooter and ESI spectra

We measure the mean free path ($λ_{\rm mfp,HI}$), photo-ionization rate ($\langle Γ_{\rm HI} \rangle$) and neutral fraction ($\langle f_{\rm HI} \rangle$) of hydrogen in 12 redshift bins at $4.85<z<6.05$ from a large sample of moderate resolution XShooter and ESI QSO absorption spectra. The fluctuations in ionizing radiation field are modeled by post-processing simulations from the Sherwood suite using our new code "EXtended reionization based on the Code for Ionization and Temperature Evolution" (EX-CITE). EX-CITE uses efficient Octree summation for computing intergalactic medium attenuation and can generate large number of high resolution $Γ_{\rm HI}$ fluctuation models. Our simulation with EX-CITE shows remarkable agreement with simulations performed with the radiative transfer code Aton and can recover the simulated parameters within $1σ$ uncertainty. We measure the three parameters by forward-modeling the Ly$α$ forest and comparing the effective optical depth ($τ_{\rm eff, HI}$) distribution in simulations and observations. The final uncertainties in our measured parameters account for the uncertainties due to thermal parameters, modeling parameters, observational systematics and cosmic variance. Our best fit parameters show significant evolution with redshift such that $λ_{\rm mfp,HI}$ and $\langle f_{\rm HI} \rangle$ decreases and increases by a factor $\sim 6$ and $\sim 10^{4}$, respectively from $z \sim 5$ to $z \sim 6$. By comparing our $λ_{\rm mfp,HI}$, $\langle Γ_{\rm HI} \rangle$ and $\langle f_{\rm HI} \rangle$ evolution with that in state-of-the-art Aton radiative transfer simulations and the Thesan and CoDa-III simulations, we find that our best fit parameter evolution is consistent with a model in which reionization completes by $z \sim 5.2$.

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arXiv2023

Probing Ultra-late Reionization: Direct Measurements of the Mean Free Path over $5<z<6$

The mean free path of ionizing photons, $λ_{\rm mfp}$, is a critical parameter for modeling the intergalactic medium (IGM) both during and after reionization. We present direct measurements of $λ_{\rm mfp}$ from QSO spectra over the redshift range $5<z<6$, including the first measurements at $z\simeq5.3$ and 5.6. Our sample includes data from the XQR-30 VLT large program, as well as new Keck/ESI observations of QSOs near $z \sim 5.5$, for which we also acquire new [C II] 158$μ$m redshifts with ALMA. By measuring the Lyman continuum transmission profile in stacked QSO spectra, we find $λ_{\rm mfp} = 9.33_{-1.80}^{+2.06}$, $5.40_{-1.40}^{+1.47}$, $3.31_{-1.34}^{+2.74}$, and $0.81_{-0.48}^{+0.73}$ pMpc at $z=5.08$, 5.31, 5.65, and 5.93, respectively. Our results demonstrate that $λ_{\rm mfp}$ increases steadily and rapidly with time over $5<z<6$. Notably, we find that $λ_{\rm mfp}$ deviates significantly from predictions based on a fully ionized and relaxed IGM as late as $z=5.3$. By comparing our results to model predictions and indirect $λ_{\rm mfp}$ constraints based on IGM Ly$α$ opacity, we find that the $λ_{\rm mfp}$ evolution is consistent with scenarios wherein the IGM is still undergoing reionization and/or retains large fluctuations in the ionizing UV background well below redshift six.

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