Engineering topics

McDonald, Patrick

Publications and source records attributed to McDonald, Patrick.

7 records

DOE OSTI2024

The 3D Lyman- α forest power spectrum from eBOSS DR16

We measure the three-dimensional power spectrum (P3D) of the transmitted flux in the Lyman-α (Ly α) forest using the complete extended Baryon Oscillation Spectroscopic Survey data release 16 (eBOSS DR16). This sample consists of ~205 000 quasar spectra in the redshift range 2 ≤ z ≤ 4 at an effective redshift z = 2.334. We propose a pair-count spectral estimator in configuration space, weighting each pair by exp( i k ∙ r), for wave vector k and pixel pair separation r, effectively measuring the anisotropic power spectrum without the need for fast Fourier transforms. This accounts for the window matrix in a tractable way, avoiding artefacts found in Fourier-transform based power spectrum estimators due to the sparse sampling transverse to the line of sight of Ly α skewers. We extensively test our pipeline on two sets of mocks: (i) idealized Gaussian random fields with a sparse sampling of Ly α skewers, and (ii) log-normal LyaCoLoRe mocks including realistic noise levels, the eBOSS survey geometry and contaminants. On eBOSS DR16 data, the Kaiser formula with a non-linear correction term obtained from hydrodynamic simulations yields a good fit to the power spectrum data in the range $(0.02 ≤ k ≤ 0.35)$ h Mpc -1 at the 1–2σ level with a covariance matrix derived from LyaCoLoRe mocks. We demonstrate a promising new approach for full-shape cosmological analyses of Ly α forest data from cosmological surveys such as eBOSS, the currently observing Dark Energy Spectroscopic Instrument and future surveys such as the Prime Focus Spectrograph, WEAVE-QSO, and 4MOST.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Mitigating the noise of DESI mocks using analytic control variates

In order to address fundamental questions related to the expansion history of the Universe and its primordial nature with the next generation of galaxy experiments, we need to model reliably large-scale structure observables such as the correlation function and the power spectrum. Cosmological N-body simulations provide a reference through which we can test our models, but their output suffers from sample variance on large scales. Fortunately, this is the regime where accurate analytic approximations exist. To reduce the variance, which is key to making optimal use of these simulations, we can leverage the accuracy and precision of such analytic descriptions using Control Variates (CV). The power of control variates stems from utilizing inexpensive but highly correlated surrogates of the statistics one wishes to measure. The stronger the correlation between the surrogate and the statistic of interest, the larger the variance reduction delivered by the method. We apply two control variate formulations to mock catalogs generated in anticipation of upcoming data from the Dark Energy Spectroscopic Instrument (DESI) to test the robustness of its analysis pipeline. Our CV-reduced measurements offer a factor of 5-10 improvement in the measurement error compared with the raw measurements. We explore the relevant properties of the galaxy samples that dictate this reduction and comment on the improvements we find on some of the derived quantities relevant to Baryon Acoustic Oscillation (BAO) analysis.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

First detection of the BAO signal from early DESI data

We present the first detection of the baryon acoustic oscillations (BAOs) signal obtained using unblinded data collected during the initial 2 months of operations of the Stage-IV ground-based Dark Energy Spectroscopic Instrument (DESI). From a selected sample of 261 291 luminous red galaxies spanning the redshift interval 0.4 < z < 1.1 and covering 1651 square degrees with a 57.9 per cent completeness level, we report a ∼5σ level BAO detection and the measurement of the BAO location at a precision of 1.7 per cent. Using a bright galaxy sample of 109 523 galaxies in the redshift range 0.1 < z < 0.5, over 3677 square degrees with a 50.0 per cent completeness, we also detect the BAO feature at ∼3σ significance with a 2.6 per cent precision. These first BAO measurements represent an important milestone, acting as a quality control on the optimal performance of the complex robotically actuated, fibre-fed DESI spectrograph, as well as an early validation of the DESI spectroscopic pipeline and data management system. Based on these first promising results, we forecast that DESI is on target to achieve a high-significance BAO detection at sub-per cent precision with the completed 5-yr survey data, meeting the top-level science requirements on BAO measurements. This exquisite level of precision will set new standards in cosmology and confirm DESI as the most competitive BAO experiment for the remainder of this decade.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

An emulator for the Lyman-α forest in beyond-ΛCDM cosmologies

Interpreting observations of the Lyman-α forest flux power spectrum requires interpolation between a small number of expensive simulations. We present a Gaussian process emulator modelling the 1D flux power spectrum as a function of the amplitude and slope of the small-scale linear matter power spectrum, and the state of the intergalactic medium at the epoch of interest (2 < z < 4). This parameterisation enables the prediction of the flux power spectrum in extended cosmological models that are not explicitly included in the training set, eliminating the need to construct bespoke emulators for a number of extensions to ΛCDM. Our emulator is appropriate for cosmologies in which the linear matter power spectrum is described to percent level accuracy by just an amplitude and slope across the epoch of interest, and in the regime probed by eBOSS/DESI data. We demonstrate this for massive neutrino cosmologies, where the emulator is able to predict the flux power spectrum in a Σm ν = 0.3 eV neutrino cosmology to sub-percent accuracy, without including massive neutrinos in the training simulations. Further parameters would be required to describe models with sharp features in the linear power, such as warm or light axion dark matter. This work will facilitate the combination of upcoming DESI data with observations of the cosmic microwave background, to obtain constraints on neutrino mass and other extensions to ΛCDM cosmology.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Massive neutrinos and degeneracies in Lyman-alpha forest simulations

Using a suite of hydrodynamical simulations with cold dark matter, baryons, and neutrinos, we present a detailed study of the effect of massive neutrinos on the 1-D and 3-D flux power spectra of the Lyman-α (Lyα) forest. The presence of massive neutrinos in cosmology induces a scale- and time-dependent suppression of structure formation that is strongest on small scales. Measuring this suppression is a key method for inferring neutrino masses from cosmological data, and is one of the main goals of ongoing and future surveys like eBOSS, DES, LSST, Euclid or DESI . The clustering in the Lyα forest traces the quasi-linear power at late times and on small scales. In combination with observations of the cosmic microwave background, the forest therefore provides some of the tightest constraints on the sum of the neutrino masses. However there is a well-known degeneracy between Σmν and the amplitude of perturbations in the linear matter power spectrum. We study the corresponding degeneracy in the 1-D flux power spectrum of the Lyα forest, and for the first time also study this degeneracy in the 3-D flux power spectrum. We show that the non-linear effects of massive neutrinos on the Lyα forest, beyond the effect of linear power amplitude suppression, are negligible, and this degeneracy persists in the Lyα forest observables to a high precision. Here, we discuss the implications of this degeneracy for choosing parametrisations of the Lyα forest for cosmological analysis.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Inflation and Dark Energy from spectroscopy at $\mathcal{z} > 2$

The expansion of the Universe is understood to have accelerated during two epochs: in its very first moments during a period of Inflation and much more recently, at $\mathcal{z} < 1$, when Dark Energy is hypothesized to drive cosmic acceleration. The undiscovered mechanisms behind these two epochs represent some of the most important open problems in fundamental physics. Most of the processes involved during Inflation impact observations on the very largest spatial scales. Traditionally, these have been accessed through observations of the Cosmic Microwave Background (CMB). While very powerful, the CMB originates from a 2D surface and the finite number of modes that it contains will largely be measured by experiments over the next decade. Observations of large 3D volumes with large-scale structure (LSS) access similar scales and will dramatically increase the number of available modes. For example, LSS observations in the range $2 \lesssim z \lesssim 5$ can more than triple the volume surveyed at $z \lesssim 2$, and, together with the sufficiently high galaxy number in this interval, strongly motivates a future spectroscopic survey that exploits this opportunity. In addition, tomography allows mapping the growth of structure with redshift, which provides robust constraints on Dark Energy and neutrino masses while relaxing restrictive assumptions such as a power-law primordial power spectrum. Finally, cross-correlation with external tracers, such as CMB lensing, Intensity Mapping or the Lyman-$\alpha$ forest, immunises the constraints to the systematics that make measurement challenging and further improves the precision through ‘sample variance cancellation’ and degeneracy breaking.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2020

Data Assimilation Enhancements to Air Force Weather’s Land Information System

The United States Air Force (USAF) has a proud and storied tradition of enabling significant advancements in the area of characterizing and modeling land state information. 557th Weather Wing (557 WW; DoD’s Executive Agent for Land Information) provides routine geospatial intelligence information to warfighters, planners, and decision makers at all echelons and services of the U.S. military, government and intelligence community. 557 WW and its predecessors have been home to the DoD’s only operational regional and global land data analysis systems since January 1958. As a trusted partner since 2005, Air Force Weather (AFW) has relied on the Hydrological Sciences Laboratory at NASA/GSFC to lead the interagency scientific collaboration known as the Land Information System (LIS). LIS is an advanced software framework for high performance land surface modeling and data assimilation of geospatial intelligence (GEOINT) information.

Wegiel, Jerry↗