PRIYA: a new suite of Lyman-α forest simulations for cosmology

Bird, Simeon; Fernandez, Martin; Ho, Ming-Feng; Qezlou, Mahdi; Monadi, Reza; Ni, Yueying; Chen, Nianyi; Croft, Rupert; Di Matteo, Tiziana

doi:10.1088/1475-7516/2023/10/037

Cited by 5 publications

(1 citation statement)

References 125 publications

(198 reference statements)

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“…The properties of the forest are sensitive to the thermal and ionization state of the intergalactic medium (IGM) and also to the underlying cosmological model. Hence it has been extensively used to constrain dark matter [5][6][7][8][9][10][11][12][13][14], cosmological [15][16][17][18][19][20][21] and astrophysical parameters [22][23][24][25]. With large surveys such as ongoing DESI [26][27][28][29][30] and upcoming WEAVE [31,32], it will become possible to access a large number of QSO spectra, making it important to construct theoretical models and simulations which can be used for interpreting the data.…”

Section: Introductionmentioning

confidence: 99%

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

Arya,

Roy Choudhury,

Paranjape

et al. 2024

J. Cosmol. Astropart. Phys.

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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 (Γ12), by comparing with high-resolution Sherwood SPH simulations across the redshift range 2 ≤ z ≤ 2.7. These parameters are estimated through a Markov Chain Monte Carlo (MCMC) 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 ∼ 1 - σ (≲ 10%) of the median (best-fit) values for most redshifts bins. However, this extended lognormal model cannot recover Γ12 reliably, with the best-fit value discrepant by ≳ 3 - σ for z > 2.2. Despite this limitation in the recovery of Γ12, whose origins we explain, we argue that the model remains useful for constraining cosmological parameters.

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Section: Introductionmentioning

confidence: 99%

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

Arya,

Roy Choudhury,

Paranjape

et al. 2024

J. Cosmol. Astropart. Phys.

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Cosmological constraints from the eBOSS Lyman-α forest using the PRIYA simulations

Fernandez,

Bird,

2024

J. Cosmol. Astropart. Phys.

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We present new cosmological parameter constraints from the eBOSS Lyman-α forest survey. We use a new theoretical model and likelihood based on the PRIYA simulation suite. PRIYA is the first suite to resolve the Lyman-α forest in a (120 Mpc/h)3 volume, using a multi-fidelity emulation technique. We use PRIYA to predict Lyman-α forest observables with ≲ 1% interpolation error over an 11 dimensional (9 simulated, 2 in post-processing) parameter space. We identify an internal tension within the flux power spectrum data. Once the discrepant data is removed, we find the primeval scalar spectral index measured at a pivot scale of k 0 = 0.78 Mpc-1 to be nP = 1.009+0.027 -0.018 at 68% confidence. This measurement from the Lyman-α forest flux power spectrum alone is in reasonable agreement with Planck, and in tension with earlier eBOSS analyses. The amplitude of matter fluctuations is σ 8 = 0.733+0.026 -0.029 at 68% confidence, in agreement with Dark Energy Survey weak lensing measurements and other small-scale structure probes and in tension with CMB measurements from Planck and ACT. The effective optical depth to Lyman-α photons from our pipeline is in good agreement with earlier high resolution measurements. We find a linear power at z = 3 and k = 0.009 s/km of Δ2 L = 0.302+0.024 -0.027 with a slope n eff = -2.264+0.026 -0.018. Our flux power spectrum only chains prefer a low level of heating during helium reionization. When we add IGM temperature data we find nP = 0.983 ± 0.020 and σ 8 = 0.703+0.023 -0.027. Our chains prefer an early and long helium reionization event, as suggested by measurements from the helium Lyman-α forest. In the near future we will use our pipeline to infer cosmological parameters from the DESI Lyman-α data.

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Modelling post-reionization H i distributions in fuzzy dark matter cosmologies using conditional normalizing flows

Dome,

Azhar,

Fialkov

2023

Monthly Notices of the Royal Astronomical Society

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Upcoming 21-cm intensity mapping experiments like the Square Kilometer Array (SKA) hold significant potential to constrain the properties of dark matter. In this work, we model neutral hydrogen (H i) distributions using high-resolution hydrodynamical N-body simulations of both cold dark matter (CDM) and fuzzy dark matter (FDM) cosmologies in the post-reionization redshift range of z = 3.42−4.94. We show that the H i abundance decreases in FDM-like cosmologies. Extreme FDM models with m ∼ 10−22 eV are at odds with a range of measurements. Due to the increased halo bias, the H i bias increases, paralleled by the damped Lyman-α (DLA) bias which we infer from the cross-section of DLAs. The distribution of the latter in extreme FDM models has a high median at the low-mass end, which can be traced to the high column density of cosmic filaments. FDM models exhibit a very similar abundance of DLAs compared to CDM while sub-DLAs are already less abundant. We study the prospects of detecting the brightest H i peaks with SKA1-Low at z = 4.94, indicating moderate signal-to-noise ratios (SNRs) at angular resolution θA = 2 arcmin with a rapidly declining SNR for lower values of θA. After training the conditional normalizing flow network HIGlow on 2D H i maps, we interpolate its latent space of axion masses to predict the peak flux for a new, synthetic FDM cosmology, finding good agreement with expectations. This work thus underscores the potential of normalizing flows in capturing complex, non-linear structures within H i maps, offering a versatile tool for conditional sample generation and prediction tasks.

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PRIYA: a new suite of Lyman-α forest simulations for cosmology

Cited by 5 publications

References 125 publications

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

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

Cosmological constraints from the eBOSS Lyman-α forest using the PRIYA simulations

Modelling post-reionization H i distributions in fuzzy dark matter cosmologies using conditional normalizing flows

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