arXiv subjects

Solène Chabanier

Publications and source records attributed to Solène Chabanier.

17 recordsLinked to original sources

arXiv2025

Emulating the Lyman-Alpha forest 1D power spectrum from cosmological simulations: New models and constraints from the eBOSS measurement

We present the Lyssa suite of high-resolution cosmological simulations of the Lyman-$α$ forest designed for cosmological analyses. These 18 simulations have been run using the Nyx code with $4096^3$ hydrodynamical cells in a 120 Mpc ($\sim$ 81Mpc/h) comoving box and individually provide sub-percent level convergence of the Lyman-$α$ forest 1d flux power spectrum. We build a Gaussian process emulator for the Lyssa simulations in the lym1d likelihood framework to interpolate the power spectrum at arbitrary parameter values. We validate this emulator based on leave-one-out tests and based on the parameter constraints for simulations outside of the training set. We also perform comparisons with a previous emulator, showing a percent level accuracy and a good recovery of the expected cosmological parameters. Using this emulator we derive constraints on the linear matter power spectrum amplitude and slope parameters $A_{\mathrm{Ly}α}$ and $n_{\mathrm{Ly}α}$. While the best-fit Planck $Λ$CDM model has $A_{\mathrm{Ly}α}=8.79$ and $n_{\mathrm{Ly}α}=-2.363$, from DR14 eBOSS data we find that $A_{\mathrm{Ly}α}<7.6$ (95\% CI) and $n_{\mathrm{Ly}α}=-2.369 \pm 0.008$. The low value of $A_{\mathrm{Ly}α}$, in tension with Planck, is driven by the correlation of this parameter with the mean transmission of the Lyman-$α$ forest. This tension disappears when imposing a well-motivated external prior on this mean transmission, in which case we find $A_{\mathrm{Ly}α}=9.8\pm1.1$ in accordance with Planck.

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arXiv2024

The ACCEL$^2$ project: simulating Lyman-$α$ forest in large-volume hydrodynamical simulations

Cosmological information is usually extracted from the Lyman-$α$ forest correlations using only either large-scale information interpreted through linear theory or using small-scale information interpreted by means of expensive hydrodynamical simulations. A complete cosmological interpretation of the 3D correlations at all measurable scales is challenged by the need of more realistic models including the complex growth of non-linear small scales that can only be studied within large hydrodynamical simulations. Past work were often limited by the trade off between the simulated cosmological volume and the resolution of the low-density intergalactic medium from which the Lyman-$α$ signal originates. We conduct a suite of hydrodynamical simulations of the intergalactic medium, including one of the largest Lyman-$α$ simulations ever performed in terms of volume (640 $h^{-1}\mathrm{Mpc}$), alongside simulations in smaller volumes with resolutions up to 25 $h^{-1}\mathrm{kpc}$, which will be further improved to show resolution convergence in future studies. We compare the 3D Lyman-$α$ power spectra predicted by those simulations to different non-linear models. The inferred Lyman-$α$ bias and redshift space distortion (RSD) parameters, $b_α$ and $β_α$ are in remarkable agreement with those measured in SDSS and DESI data. We find that, contrary to intuition, the convergence of large-scale modes of the 3D Lyman-$α$ power spectra, which determines $β_α$, is primarily influenced by the resolution of the simulation box through mode coupling, rather than the box size itself. Finally, we study the BAO signal encoded in the 3D Lyman-$α$ power spectra. For the first time with a hydrodynamical simulation, we clearly detect the BAO signal, however we only marginally detect its damping, associated with the non-linear growth of the structures.

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arXiv2024

Measurement of the small-scale 3D Lyman-$α$ forest power spectrum

Small-scale correlations measured in the Lyman-$α$ (Ly$α$) forest encode information about the intergalactic medium and the primordial matter power spectrum. In this article, we present and implement a simple method to measure the 3-dimensional power spectrum, $P_{\rm 3D}$, of the Ly$α$ forest at wavenumbers $k$ corresponding to small, $\sim$ Mpc scales. In order to estimate $P_{\rm 3D}$ from sparsely and unevenly distributed data samples, we rely on averaging 1-dimensional Fourier Transforms, as previously carried out to estimate the 1-dimensional power spectrum of the Ly$α$ forest, $P_{\rm 1D}$. This methodology exhibits a very low computational cost. We confirm the validity of this approach through its application to Nyx cosmological hydrodynamical simulations. Subsequently, we apply our method to the eBOSS DR16 Ly$α$ forest sample, providing as a proof of principle, a first $P_{\rm 3D}$ measurement averaged over two redshift bins $z=2.2$ and $z=2.4$. This work highlights the potential for forthcoming $P_{\rm 3D}$ measurements, from upcoming large spectroscopic surveys, to untangle degeneracies in the cosmological interpretation of $P_{\rm 1D}$.

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arXiv2023

The Dark Energy Spectroscopic Instrument: One-dimensional power spectrum from first Lyman-$α$ forest samples with Fast Fourier Transform

We present the one-dimensional Lyman-$α$ forest power spectrum measurement using the first data provided by the Dark Energy Spectroscopic Instrument (DESI). The data sample comprises $26,330$ quasar spectra, at redshift $z > 2.1$, contained in the DESI Early Data Release and the first two months of the main survey. We employ a Fast Fourier Transform (FFT) estimator and compare the resulting power spectrum to an alternative likelihood-based method in a companion paper. We investigate methodological and instrumental contaminants associated to the new DESI instrument, applying techniques similar to previous Sloan Digital Sky Survey (SDSS) measurements. We use synthetic data based on log-normal approximation to validate and correct our measurement. We compare our resulting power spectrum with previous SDSS and high-resolution measurements. With relatively small number statistics, we successfully perform the FFT measurement, which is already competitive in terms of the scale range. At the end of the DESI survey, we expect a five times larger Lyman-$α$ forest sample than SDSS, providing an unprecedented precise one-dimensional power spectrum measurement.

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arXiv2023

Planting a Lyman alpha forest on AbacusSummit

The full-shape correlations of the Lyman alpha (Ly$α$) forest contain a wealth of cosmological information through the Alcock-Paczyński effect. However, these measurements are challenging to model without robustly testing and verifying the theoretical framework used for analyzing them. Here, we leverage the accuracy and volume of the $N$-body simulation suite \textsc{AbacusSummit} to generate high-resolution Ly$α$ skewers and quasi-stellar object (QSO) catalogs. One of the main goals of our mocks is to aid in the full-shape Ly$α$ analysis planned by the Dark Energy Spectroscopic Instrument (DESI) team. We provide optical depth skewers for six of the fiducial cosmology base-resolution simulations ($L_{\rm box} = 2\,h^{-1}{\rm Gpc}$, $N = 6912^3$) at $z = 2.5$. We adopt a simple recipe based on the Fluctuating Gunn-Peterson Approximation (FGPA) for constructing these skewers from the matter density in an $N$-body simulation and calibrate it against the 1D and 3D Ly$α$ power spectra extracted from the hydrodynamical simulation IllustrisTNG (TNG; $L_{\rm box} = 205\,h^{-1}{\rm Mpc}$, $N = 2500^3$). As an important application, we study the non-linear broadening of the baryon acoustic oscillation (BAO) peak and show the cross-correlation between DESI-like QSOs and our Ly$α$ forest skewers. We find differences on small scales between the Kaiser approximation prediction and our mock measurements of the Ly$α$$\times$QSO cross-correlation, which would be important to account for in upcoming analyses. The \textsc{AbacusSummit} Ly$α$ forest mocks open up the possibility for improved modelling of cross correlations between Ly$α$ and cosmic microwave background (CMB) lensing and Ly$α$ and QSOs, and for forecasts of the 3-point Ly$α$ correlation function. Our catalogues and skewers are publicly available on Globus.

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arXiv2022

Target Selection and Validation of DESI Quasars

The Dark Energy Spectroscopic Instrument (DESI) survey will measure large-scale structures using quasars as direct tracers of dark matter in the redshift range 0.9 2.1. We present several methods to select candidate quasars for DESI, using input photometric imaging in three optical bands (g, r, z) from the DESI Legacy Imaging Surveys and two infrared bands (W1, W2) from the Wide-field Infrared Explorer (WISE). These methods were extensively tested during the Survey Validation of DESI. In this paper, we report on the results obtained with the different methods and present the selection we optimized for the DESI main survey. The final quasar target selection is based on a Random Forest algorithm and selects quasars in the magnitude range 16.5 99% purity for a nominal effective exposure time of ~1000s. With a 310 per sq. deg. target density, the main selection allows DESI to select more than 200 QSOs per sq. deg. (including 60 quasars with z>2.1), exceeding the project requirements by 20%. The redshift distribution of the selected quasars is in excellent agreement with quasar luminosity function predictions.

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arXiv2022

Modeling the Lyman-$α$ forest with Eulerian and SPH hydrodynamical methods

We compare two state-of-the-art numerical codes to study the overall accuracy in modeling the intergalactic medium and reproducing Lyman-$α$ forest observables for DESI and high-resolution data sets. The codes employ different approaches to solving both gravity and modeling the gas hydrodynamics. The first code, Nyx, solves the Poisson equation using the Particle-Mesh (PM) method and the Euler equations using a finite volume method. The second code, \CRKHACC, uses a Tree-PM method to solve for gravity, and an improved Lagrangian smoothed particle hydrodynamics (SPH) technique, where fluid elements are modeled with particles, to treat the intergalactic gas. We compare the convergence behavior of the codes in flux statistics as well as the degree to which the codes agree in the converged limit. We find good agreement overall with differences being less than observational uncertainties, and a particularly notable $\lesssim$1\% agreement in the 1D flux power spectrum. This agreement was achieved by applying a tessellation methodology for reconstructing the density in \CRKHACC instead of using an SPH kernel as is standard practice. We show that use of the SPH kernel can lead to significant and unnecessary biases in flux statistics; this is especially prominent at high redshifts, $z \sim 5$, as the Lyman-$α$ forest mostly comes from lower-density regions which are intrinsically poorly sampled by SPH particles.

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arXiv2022

Deep Learning of DESI Mock Spectra to Find Damped Lyα Systems

We have updated and applied a convolutional neural network (CNN) machine learning model to discover and characterize damped Ly$α$ systems (DLAs) based on Dark Energy Spectroscopic Instrument (DESI) mock spectra. We have optimized the training process and constructed a CNN model that yields a DLA classification accuracy above 99$\%$ for spectra which have signal-to-noise (S/N) above 5 per pixel. Classification accuracy is the rate of correct classifications. This accuracy remains above 97$\%$ for lower signal-to-noise (S/N) $\approx1$ spectra. This CNN model provides estimations for redshift and HI column density with standard deviations of 0.002 and 0.17 dex for spectra with S/N above 3 per pixel. Also, this DLA finder is able to identify overlapping DLAs and sub-DLAs. Further, the impact of different DLA catalogs on the measurement of Baryon Acoustic Oscillation (BAO) is investigated. The cosmological fitting parameter result for BAO has less than $0.61\%$ difference compared to analysis of the mock results with perfect knowledge of DLAs. This difference is lower than the statistical error for the first year estimated from the mock spectra: above $1.7\%$. We also compared the performance of CNN and Gaussian Process (GP) model. Our improved CNN model has moderately 14$\%$ higher purity and 7$\%$ higher completeness than an older version of GP code, for S/N $>$ 3. Both codes provide good DLA redshift estimates, but the GP produces a better column density estimate by $24\%$ less standard deviation. A credible DLA catalog for DESI main survey can be provided by combining these two algorithms.

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arXiv2021

The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: The Damped Lyman-$α$ systems Catalog

We present the characteristics of the Damped Lyman-$α$ (DLA) systems found in the data release DR16 of the extended Baryon Oscillation Spectroscopic Survey (eBOSS) of the Sloan Digital Sky Survey (SDSS). DLAs were identified using the convolutional neural network (CNN) of~\cite{Parks2018}. A total of 117,458 absorber candidates were found with $2 \leq \zdla \leq 5.5$ and $19.7 \leq \lognhi \leq 22$, including 57,136 DLA candidates with $\lognhi \geq 20.3$. Mock quasar spectra were used to estimate DLA detection efficiency and the purity of the resulting catalog. Restricting the quasar sample to bright forests, i.e. those with mean forest fluxes $\meanflux>2\times\fluxunit$, the completeness and purity are greater than 90\% for DLAs with column densities in the range $20.1\leq \lognhi \leq 22$.

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arXiv2020

The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: Baryon acoustic oscillations with Lyman-$α$ forests

We present a measurement of baryonic acoustic oscillations (BAO) from Lyman-$α$ (Ly$α$) absorption and quasars at an effective redshift $z=2.33$ using the complete extended Baryonic Oscillation Spectroscopic Survey (eBOSS). The sixteenth and final eBOSS data release (SDSS DR16) contains all data from eBOSS and its predecessor, the Baryonic Oscillation Spectroscopic Survey (BOSS), providing $210,005$ quasars with $z_{q}>2.10$ that are used to measure Ly$α$ absorption. We measure the BAO scale both in the auto-correlation of Ly$α$ absorption and in its cross correlation with $341,468$ quasars with redshift $z_{q}>1.77$. Apart from the statistical gain from new quasars and deeper observations, the main improvements over previous work come from more accurate modeling of physical and instrumental correlations and the use of new sets of mock data. Combining the BAO measurement from the auto- and cross-correlation yields the constraints of the two ratios $D_{H}(z=2.33)/r_{d} = 8.99 \pm 0.19$ and $D_{M}(z=2.33)/r_{d} = 37.5 \pm 1.1$, where the error bars are statistical. These results are within $1.5σ$ of the prediction of the flat-$Λ$CDM cosmology of Planck~(2016). The analysis code, \texttt{picca}, the catalog of the flux-transmission field measurements, and the $Δχ^{2}$ surfaces are publicly available.

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arXiv2020

The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: Large-scale Structure Catalogs for Cosmological Analysis

We present large-scale structure catalogs from the completed extended Baryon Oscillation Spectroscopic Survey (eBOSS). Derived from Sloan Digital Sky Survey (SDSS) -IV Data Release 16 (DR16), these catalogs provide the data samples, corrected for observational systematics, and random positions sampling the survey selection function. Combined, they allow large-scale clustering measurements suitable for testing cosmological models. We describe the methods used to create these catalogs for the eBOSS DR16 Luminous Red Galaxy (LRG) and Quasar samples. The quasar catalog contains 343,708 redshifts with $0.8 < z < 2.2$ over 4,808\,deg$^2$. We combine 174,816 eBOSS LRG redshifts over 4,242\,deg$^2$ in the redshift interval $0.6 < z < 1.0$ with SDSS-III BOSS LRGs in the same redshift range to produce a combined sample of 377,458 galaxy redshifts distributed over 9,493\,deg$^2$. Improved algorithms for estimating redshifts allow that 98 per cent of LRG observations result in a successful redshift, with less than one per cent catastrophic failures ($Δz > 1000$ ${\rm km~s}^{-1}$). For quasars, these rates are 95 and 2 per cent (with $Δz > 3000$ ${\rm km~s}^{-1}$). We apply corrections for trends between the number densities of our samples and the properties of the imaging and spectroscopic data. For example, the quasar catalog obtains a $χ^2$/DoF$= 776/10$ for a null test against imaging depth before corrections and a $χ^2$/DoF$=6/8$ after. The catalogs, combined with careful consideration of the details of their construction found here-in, allow companion papers to present cosmological results with negligible impact from observational systematic uncertainties.

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arXiv2020

The Sloan Digital Sky Survey Quasar Catalog: Sixteenth Data Release

We present the final Sloan Digital Sky Survey IV (SDSS-IV) quasar catalog from Data Release 16 of the extended Baryon Oscillation Spectroscopic Survey (eBOSS). This catalog comprises the largest selection of spectroscopically confirmed quasars to date. The full catalog includes two sub-catalogs: a "superset" of all SDSS-IV/eBOSS objects targeted as quasars containing 1,440,615 observations and a quasar-only catalog containing 750,414 quasars, including 225,082 new quasars appearing in an SDSS data release for the first time, as well as known quasars from SDSS-I/II/III. We present automated identification and redshift information for these quasars alongside data from visual inspections for 320,161 spectra. The quasar-only catalog is estimated to be 99.8% complete with 0.3% to 1.3% contamination. Automated and visual inspection redshifts are supplemented by redshifts derived via principal component analysis and emission lines. We include emission line redshifts for H$α$, H$β$, Mg II, C III], C IV, and Ly$α$. Identification and key characteristics generated by automated algorithms are presented for 99,856 Broad Absorption Line quasars and 35,686 Damped Lyman Alpha quasars. In addition to SDSS photometric data, we also present multi-wavelength data for quasars from GALEX, UKIDSS, WISE, FIRST, ROSAT/2RXS, XMM-Newton, and Gaia. Calibrated digital optical spectra for these quasars can be obtained from the SDSS Science Archive Server.

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arXiv2020

Formation of compact galaxies in the Extreme-Horizon simulation

We present the Extreme-Horizon (EH) cosmological simulation: EH models galaxy formation with stellar and AGN feedback and uses a very high resolution in the intergalactic and circumgalactic medium. The high resolution in low-density regions results in smaller-size massive galaxies at redshift $z=2$, in better agreement with observations compared to other simulations. This results from the improved modeling of cold gas flows accreting onto galaxies. Besides, the EH simulation forms a population of particularly compact galaxies with stellar masses of $10^{10-11}$\,M$_\sun$ that are reminiscent of observed ultracompact galaxies at $z\simeq2$. These objects form mainly through repeated major mergers of low-mass progenitors, independently of baryonic feedback mechanisms. This formation process can be missed in simulations using a too low resolution in low-density intergalactic regions.

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arXiv2020

The impact of AGN feedback on the 1D power spectra from the Ly$α$ forest using the Horizon-AGN suite of simulations

The Lyman-$α$ forest is a powerful probe for cosmology, but it is also strongly impacted by galaxy evolution and baryonic processes such as Active Galactic Nuclei (AGN) feedback, which can redistribute mass and energy on large scales. We constrain the signatures of AGN feedback on the 1D power spectrum of the Lyman-$α$ forest using a series of eight hydro-cosmological simulations performed with the Adaptative Mesh Refinement code RAMSES. This series starts from the Horizon-AGN simulation and varies the sub-grid parameters for AGN feeding, feedback and stochasticity. These simulations cover the whole plausible range of feedback and feeding parameters according to the resulting galaxy properties. AGNs globally suppress the Lyman-$α$ power at all scales. On large scales, the energy injection and ionization dominate over the supply of gas mass from AGN-driven galactic winds, thus suppressing power. On small scales, faster cooling of denser gas mitigates the suppression. This effect increases with decreasing redshift. We provide lower and upper limits of this signature at nine redshifts between $z=4.25$ and $z=2.0$, making it possible to account for it at post-processing stage in future work given that running simulations without AGN feedback can save considerable amounts of computing resources. Ignoring AGN feedback in cosmological inference analyses leads to strong biases with 2\% shift on $σ_8$ and 1\% shift on $n_s$, which represents twice the standards deviation of the current constraints on $n_s$.

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arXiv2020

Hints, neutrino bounds and WDM constraints from SDSS DR14 Lyman-$α$ and Planck full-survey data

The Ly-$α$ forest 1D flux power spectrum is a powerful probe of several cosmological parameters. Assuming a $Λ$CDM cosmology including massive neutrinos, we find that the latest SDSS DR14 BOSS and eBOSS Ly-$α$ forest data is in very good agreement with current weak lensing constraints on $(Ω_m, σ_8)$ and has the same small level of tension with Planck. We did not identify a systematic effect in the data analysis that could explain this small tension, but we show that it can be reduced in extended cosmological models where the spectral index is not the same on the very different times and scales probed by CMB and Ly-$α$ data. A particular case is that of a $Λ$CDM model including a running of the spectral index on top of massive neutrinos. With combined Ly-$α$ and Planck data, we find a slight (3$σ$) preference for negative running, $α_s= -0.010 \pm 0.004$ (68% CL). Neutrino mass bounds are found to be robust against different assumptions. In the $Λ$CDM model with running, we find $\sum m_ν<0.11$ eV at the 95% confidence level for combined Ly-$α$ and Planck (temperature and polarisation) data, or $\sum m_ν< 0.09$ eV when adding CMB lensing and BAO data. We further provide strong and nearly model-independent bounds on the mass of thermal warm dark matter. For a conservative configuration consisting of SDSS data restricted to $z<4.5$ combined with XQ-100 \lya data, we find $m_X > 5.3\;\mathrm{keV}$ (95\%CL).

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arXiv2019

Matter power spectrum: from Ly$α$ forest to CMB scales

We present a new compilation of inferences of the linear 3D matter power spectrum at redshift $z\,{=}\,0$ from a variety of probes spanning several orders of magnitude in physical scale and in cosmic history. We develop a new lower-noise method for performing this inference from the latest Ly$α$ forest 1D power spectrum data. We also include cosmic microwave background (CMB) temperature and polarization power spectra and lensing reconstruction data, the cosmic shear two-point correlation function, and the clustering of luminous red galaxies. We provide a Dockerized Jupyter notebook housing the fairly complex dependencies for producing the plot of these data, with the hope that groups in the future can help add to it. Overall, we find qualitative agreement between the independent measurements considered here and the standard $Λ$CDM cosmological model fit to the {\it Planck} data

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arXiv2019

The one-dimensional power spectrum from the SDSS DR14 Ly$α$ forests

We present a measurement of the 1D Ly$α$ forest flux power spectrum, using the complete Baryon Oscillation Spectroscopic Survey (BOSS) and first extended-BOSS (eBOSS) quasars at $z_{\rm qso}>2.1$, corresponding to the fourteenth data release (DR14) of the Sloan Digital Sky Survey (SDSS). Our results cover thirteen bins in redshift from $z_{\rm Lyα}=2.2$ to 4.6, and scales up to $k=0.02\rm \,(km/s)^{-1}$. From a parent sample of 180,413 visually inspected spectra, we selected the 43,751 quasars with the best quality; this data set improves the previous result from the ninth data release (DR9), both in statistical precision (achieving a reduction by a factor of two) and in redshift coverage. We also present a thorough investigation of identified sources of systematic uncertainties that affect the measurement. The resulting 1D power spectrum of this work is in excellent agreement with the one from the BOSS DR9 data.

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