Forecasting constraints on the high-z IGM thermal state from the Lyman-α forest flux autocorrelation function

The autocorrelation function of the Lyman-α (Ly α) forest flux from high-z quasars probes the small-scale structure of the intergalactic medium (IGM). The thermal state of the IGM, determined by the physics of reionization, sets the small-scale power observed in the Ly α forest. To explore the sensi...

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Detalles Bibliográficos
Autores: Wolfson, Molly, Hennawi, Joseph F., Davies, Frederick B., Lukic, Zarija, Oñorbe Bernis, José
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2025
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/174966
Acceso en línea:https://hdl.handle.net/11441/174966
https://doi.org/10.1093/mnras/staf753
Access Level:acceso abierto
Palabra clave:Methods: statistical
Intergalactic medium
Quasars: absorption lines
Dark ages
Reionization
First stars
Descripción
Sumario:The autocorrelation function of the Lyman-α (Ly α) forest flux from high-z quasars probes the small-scale structure of the intergalactic medium (IGM). The thermal state of the IGM, determined by the physics of reionization, sets the small-scale power observed in the Ly α forest. To explore the sensitivity of the autocorrelation function to the IGM’s thermal state, we compute the autocorrelation function from a cosmological hydrodynamical simulation with an instantaneous reionization model and 135 post-processed thermal states. Using mock data sets of 20 quasars, we forecast constraints on T0 and γ , which characterize the post-processed IGM thermalstate, at 5.4 ≤ z ≤ 6. While this model simplifiesthe IGM’sthermalstate, itserves as a key firststep in assessing future observational prospects. We also perform an inference test on mocks and re-weight out posterior distributions to guarantee that they exhibit statistically correct behaviour. At z = 5.4, we find that an idealized data set constrains T0 to 59 per cent and γ to 16 per cent at the 1σ equivalent confidence level. To explore more realistic, non-instantaneous reionization scenarios, we analyse four models combining temperature and ultraviolet background (UVB) fluctuations at z = 5.8. We find that mock data generated from a model with both temperature and UVB fluctuations can rule out a model with only temperature fluctuations at the > 1σ level 73.9 per cent of the time.