arXiv subjects

James Farr

Publications and source records attributed to James Farr.

7 recordsLinked to original sources

arXiv2022

The Alcock-Paczy\'nski effect from Lyman-$\alpha$ forest correlations: Analysis validation with synthetic data

The three-dimensional distribution of the Ly$\alpha$ forest has been extensively used to constrain cosmology through measurements of the baryon acoustic oscillations (BAO) scale. However, more cosmological information could be extracted from the full shapes of the Ly$\alpha$ forest correlations through the Alcock-Paczy\'nski (AP) effect. In this work, we prepare for a cosmological analysis of the full shape of the Ly$\alpha$ forest correlations by studying synthetic data of the extended Baryon Oscillation Spectroscopic Survey (eBOSS). We use a set of one hundred eBOSS synthetic data sets in order to validate such an analysis. These mocks undergo the same analysis process as the real data. We perform a full-shape analysis on the mean of the correlation functions measured from the one hundred eBOSS realizations, and find that our model of the Ly$\alpha$ correlations performs well on current data sets. We show that we are able to obtain an unbiased full-shape measurement of $D_M/D_H(z_\mathrm{eff})$, where $D_M$ is the transverse comoving distance, $D_H$ is the Hubble distance, and $z_\mathrm{eff}$ is the effective redshift of the measurement. We test the fit over a range of scales, and decide to use a minimum separation of $r_\mathrm{min}=25\ h^{-1}\text{Mpc}$. We also study and discuss the impact of the main contaminants affecting Ly$\alpha$ forest correlations, and give recommendations on how to perform such analysis with real data. While the final eBOSS Ly$\alpha$ BAO analysis measured $D_M/D_H(z_\mathrm{eff}=2.33)$ with $4\%$ statistical precision, a full-shape fit of the same correlations could provide a $\sim2\%$ measurement.

astro-ph.CO↗

arXiv2022

The DESI Survey Validation: Results from Visual Inspection of the Quasar Survey Spectra

A key component of the Dark Energy Spectroscopic Instrument (DESI) survey validation (SV) is a detailed visual inspection (VI) of the optical spectroscopic data to quantify key survey metrics. In this paper we present results from VI of the quasar survey using deep coadded SV spectra. We show that the majority (~70%) of the main-survey targets are spectroscopically confirmed as quasars, with ~16% galaxies, ~6% stars, and ~8% low-quality spectra lacking reliable features. A non-negligible fraction of the quasars are misidentified by the standard spectroscopic pipeline but we show that the majority can be recovered using post-pipeline "afterburner" quasar-identification approaches. We combine these "afterburners" with our standard pipeline to create a modified pipeline to improve the overall quasar yield. At the depth of the main DESI survey both pipelines achieve a good-redshift purity (reliable redshifts measured within 3000 km/s) of ~99%; however, the modified pipeline recovers ~94% of the visually inspected quasars, as compared to ~86% from the standard pipeline. We demonstrate that both pipelines achieve an median redshift precision and accuracy of ~100 km/s and ~70 km/s, respectively. We constructed composite spectra to investigate why some quasars are missed by the standard spectroscopic pipeline and find that they are more host-galaxy dominated (i.e., distant analogs of "Seyfert galaxies") and/or dust reddened than the standard-pipeline quasars. We also show example spectra to demonstrate the overall diversity of the DESI quasar sample and provide strong-lensing candidates where two targets contribute to a single spectrum.

astro-ph.GA↗

arXiv2020

Optimal strategies for identifying quasars in DESI

As spectroscopic surveys continue to grow in size, the problem of classifying spectra targeted as quasars (QSOs) will need to move beyond its historical reliance on human experts. Instead, automatic classifiers will increasingly become the dominant classification method, leaving only small fractions of spectra to be visually inspected in ambiguous cases. In order to maximise classification accuracy, making best use of available classifiers will be of great importance, particularly when looking to identify and eliminate distinctive failure modes. In this work, we demonstrate that the machine learning-based classifier QuasarNET will be of use for future surveys such as the Dark Energy Spectroscopic Instrument (DESI), comparing its performance to the DESI pipeline classifier redrock. During the first of four passes across its footprint DESI will need to select high-$z$ ($z\geq2.1$) QSOs for reobservation, and so we first assess the classifiers' performance at identifying high-$z$ QSOs from single-exposure spectra. We then quantify the classifiers' abilities to construct QSO catalogues in both low- and high-$z$ bins, using coadded spectra to simulate end-of-survey data. For such tasks, QuasarNET is able to outperform redrock in its current form, identifying approximately 99% of high-$z$ QSOs from single exposures and producing QSO catalogues with sub-percent levels of contamination. By combining QuasarNET and redrock's outputs, we can further improve the classification strategies to identify up to 99.5% of high-$z$ QSOs from single exposures and reduce final QSO catalogue contamination to below 0.5%. These combined strategies address DESI's QSO classification needs effectively.

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arXiv2020

The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: Cosmological Implications from two Decades of Spectroscopic Surveys at the Apache Point observatory

We present the cosmological implications from final measurements of clustering using galaxies, quasars, and Ly$\alpha$ forests from the completed Sloan Digital Sky Survey (SDSS) lineage of experiments in large-scale structure. These experiments, composed of data from SDSS, SDSS-II, BOSS, and eBOSS, offer independent measurements of baryon acoustic oscillation (BAO) measurements of angular-diameter distances and Hubble distances relative to the sound horizon, $r_d$, from eight different samples and six measurements of the growth rate parameter, $f\sigma_8$, from redshift-space distortions (RSD). This composite sample is the most constraining of its kind and allows us to perform a comprehensive assessment of the cosmological model after two decades of dedicated spectroscopic observation. We show that the BAO data alone are able to rule out dark-energy-free models at more than eight standard deviations in an extension to the flat, $\Lambda$CDM model that allows for curvature. When combined with Planck Cosmic Microwave Background (CMB) measurements of temperature and polarization the BAO data provide nearly an order of magnitude improvement on curvature constraints. The RSD measurements indicate a growth rate that is consistent with predictions from Planck primary data and with General Relativity. When combining the results of SDSS BAO and RSD with external data, all multiple-parameter extensions remain consistent with a $\Lambda$CDM model. Regardless of cosmological model, the precision on $\Omega_\Lambda$, $H_0$, and $\sigma_8$, remains at roughly 1\%, showing changes of less than 0.6\% in the central values between models. The inverse distance ladder measurement under a o$w_0w_a$CDM yields $H_0= 68.20 \pm 0.81 \, \rm km\, s^{-1} Mpc^{-1}$, remaining in tension with several direct determination methods. (abridged)

astro-ph.CO↗

arXiv2020

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

We present a measurement of baryonic acoustic oscillations (BAO) from Lyman-$\alpha$ (Ly$\alpha$) 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$\alpha$ absorption. We measure the BAO scale both in the auto-correlation of Ly$\alpha$ 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 $1.5\sigma$ of the prediction of the flat-$\Lambda$CDM cosmology of Planck~(2016). The analysis code, \texttt{picca}, the catalog of the flux-transmission field measurements, and the $\Delta \chi^{2}$ surfaces are publicly available.

astro-ph.CO↗

arXiv2019

LyaCoLoRe: Synthetic Datasets for Current and Future Lyman-${\alpha}$ Forest BAO Surveys

The statistical power of Lyman-${\alpha}$ forest Baryon Acoustic Oscillation (BAO) measurements is set to increase significantly in the coming years as new instruments such as the Dark Energy Spectroscopic Instrument deliver progressively more constraining data. Generating mock datasets for such measurements will be important for validating analysis pipelines and evaluating the effects of systematics. With such studies in mind, we present LyaCoLoRe: a package for producing synthetic Lyman-${\alpha}$ forest survey datasets for BAO analyses. LyaCoLoRe transforms initial Gaussian random field skewers into skewers of transmitted flux fraction via a number of fast approximations. In this work we explain the methods of producing mock datasets used in LyaCoLoRe, and then measure correlation functions on a suite of realisations of such data. We demonstrate that we are able to recover the correct BAO signal, as well as large-scale bias parameters similar to literature values. Finally, we briefly describe methods to add further astrophysical effects to our skewers - high column density systems and metal absorbers - which act as potential complications for BAO analyses.

astro-ph.CO↗

arXiv2019

Baryon Acoustic Oscillations and the Hubble Constant: Past, Present and Future

We investigate constraints on the Hubble constant ($H_0$) using Baryon Acoustic Oscillations (BAO) and baryon density measurements from Big Bang Nucleosynthesis (BBN). We start by investigating the tension between galaxy BAO measurements and those using the Lyman-$\alpha$ forest, within a Bayesian framework. Using the latest results from eBOSS DR14 we find that the probability of this tension being statistical is $\simeq6.3\%$ assuming flat $\Lambda$CDM. We measure $H_0 = 67.6\pm1.1$ km s$^{-1}$ Mpc$^{-1}$, with a weak dependence on the BBN prior used, in agreement with results from Planck Cosmic Microwave Background (CMB) results and in strong tension with distance ladder results. Finally, we forecast the future of BAO $+$ BBN measurements of $H_0$, using the Dark Energy Spectroscopic Instrument (DESI). We find that the choice of BBN prior will have a significant impact when considering future BAO measurements from DESI.

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