Related papers: Learning Reionization History from Quasars with Si…
This paper presents a novel framework for full-waveform seismic source inversion using simulation-based inference (SBI). Traditional probabilistic approaches often rely on simplifying assumptions about data errors, which we show can lead to…
Simulation-based inference (SBI) makes it possible to infer the parameters of a model from high-dimensional low-level features of the observed events. In this work we show how this method can be used to establish the presence of a weak…
One well-known way to constrain the hydrogen neutral fraction, x_H, of the high-redshift intergalactic medium (IGM) is through the shape of the red damping wing of the Lya absorption line. We examine this method's effectiveness in light of…
Observations of the early Universe suggest that reionization was complete by $z\sim6$, however, the exact history of this process is still unknown. One method for measuring the evolution of the neutral fraction throughout this epoch is via…
Bright, high redshift ($z>6$) QSOs are powerful probes of the ionisation state of the intervening intergalactic medium (IGM). The detection of Ly$\alpha$ damping wing absorption imprinted in the spectrum of high-z QSOs can provide strong…
The attenuation of Ly$\alpha$ photons by neutral hydrogen in the intergalactic medium (IGM) at $z\gtrsim5$ continues to be a powerful probe for studying the epoch of reionisation. Given a framework to estimate the intrinsic (true)…
Amortized simulation-based inference (SBI) methods train neural networks on simulated data to perform Bayesian inference. While this strategy avoids the need for tractable likelihoods, it often requires a large number of simulations and has…
Inferring the values and uncertainties of cosmological parameters in a cosmology model is of paramount importance for modern cosmic observations. In this paper, we use the simulation-based inference (SBI) approach to estimate cosmological…
Flagship near-future surveys targeting $10^8-10^9$ galaxies across cosmic time will soon reveal the processes of galaxy assembly in unprecedented resolution. This creates an immediate computational challenge on effective analyses of the…
Simulation-based inference (SBI) has emerged as a powerful tool for extracting cosmological information from galaxy surveys deep into the non-linear regime. Despite its great promise, its application is limited by the computational cost of…
The growing availability of large and complex datasets has increased interest in temporal stochastic processes that can capture stylized facts such as marginal skewness, non-Gaussian tails, long memory, and even non-Markovian dynamics.…
Spectroscopic analysis of Ly$\alpha$ damping wings of bright sources at $z>6$ is a promising way to measure the reionization history of the universe. However, the theoretical interpretation of the damping wings is challenging due to the…
The spectra of several high-redshift (z>6) quasars have shown evidence for a Gunn-Peterson (GP) damping wing, indicating a substantial mean neutral hydrogen fraction (x_HI > 0.03) in the z ~ 6 intergalactic medium (IGM). However, previous…
Simulation-based inference (SBI) enables cosmological parameter estimation when closed-form likelihoods or models are unavailable. However, SBI relies on machine learning for neural compression and density estimation. This requires large…
The spectra of high-redshift ($z\gtrsim 6$) quasars contain valuable information on the progression of the Epoch of Reionization (EoR). At redshifts $z<6$, the observed Lyman-series forest shows that the intergalactic medium (IGM) is nearly…
How much cosmological information can we reliably extract from existing and upcoming large-scale structure observations? Many summary statistics fall short in describing the non-Gaussian nature of the late-time Universe in comparison to…
We assess the impact of inhomogeneous reionization on detection of HII regions surrounding luminous high redshift quasars using planned low frequency radio telescopes. Our approach is to implement a semi-numerical scheme to calculate the…
Bayesian inference represents a principled way to incorporate Earth structure uncertainty in full-waveform moment tensor inversions, but traditional approaches generally require significant approximations that risk biasing the resulting…
Simulation-based inference (SBI) is emerging as a new statistical paradigm for addressing complex scientific inference problems. By leveraging the representational power of deep neural networks, SBI can extract the most informative…
Simulation-based inference (SBI) has become an important tool in cosmology for extracting additional information from observational data using simulations. However, all cosmological simulations are approximations of the actual universe, and…