arXiv subjects

Rupert A. C. Croft

Publications and source records attributed to Rupert A. C. Croft.

At least 37 records · Page 2Linked to original sources

arXiv2021

Deep Forest: Neural Network reconstruction of the Lyman-alpha forest

We explore the use of Deep Learning to infer physical quantities from the observable transmitted flux in the Lyman-alpha forest. We train a Neural Network using redshift z=3 outputs from cosmological hydrodynamic simulations and mock datasets constructed from them. We evaluate how well the trained network is able to reconstruct the optical depth for Lyman-alpha forest absorption from noisy and often saturated transmitted flux data. The Neural Network outperforms an alternative reconstruction method involving log inversion and spline interpolation by approximately a factor of 2 in the optical depth root mean square error. We find no significant dependence in the improvement on input data signal to noise, although the gain is greatest in high optical depth regions. The Lyman-alpha forest optical depth studied here serves as a simple, one dimensional, example but the use of Deep Learning and simulations to approach the inverse problem in cosmology could be extended to other physical quantities and higher dimensional data.

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arXiv2021

Observing the host galaxies of high-redshift quasars with JWST: predictions from the BlueTides simulation

The bright emission from high-redshift quasars completely conceals their host galaxies in the rest-frame ultraviolet/optical, with detection of the hosts in these wavelengths eluding even the Hubble Space Telescope (HST) using detailed point spread function (PSF) modelling techniques. In this study we produce mock images of a sample of z=7 quasars extracted from the BlueTides simulation, and apply Markov Chain Monte Carlo-based PSF modelling to determine the detectability of their host galaxies with the James Webb Space Telescope (JWST). While no statistically significant detections are made with HST, we predict that at the same wavelengths and exposure times JWST NIRCam imaging will detect ~50% of quasar host galaxies. We investigate various observational strategies, and find that NIRCam wide-band imaging in the long-wavelength filters results in the highest fraction of successful quasar host detections, detecting >80% of the hosts of bright quasars in exposure times of 5 ks. Exposure times of ~5 ks are required to detect the majority of host galaxies in the NIRCam wide-band filters, however even 10 ks exposures with MIRI result in <30% successful host detections. We find no significant trends between galaxy properties and their detectability. The PSF modelling can accurately recover the host magnitudes, radii, and spatial distribution of the larger-scale emission, when accounting for the central core being contaminated by residual quasar flux. Care should be made when interpreting the host properties measured using PSF modelling.

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arXiv2021

New Probes of Large Scale Structure

This is the second paper in a series where we propose a method of indirectly measuring large scale structure using information from small scale perturbations. The idea is to build a quadratic estimator from small scale modes that provides a map of structure on large scales. We demonstrated in the first paper that the quadratic estimator works well on a dark-matter-only N-body simulation at a snapshot of $z=0$. Here we generalize the theory to the case of a light cone halo catalog with a non-cubic region taken into consideration. We successfully apply the generalized version of the quadratic estimator to the light cone halo catalog based on an N-body simulation of volume $\sim15.03\,(h^{-1}\,\rm Gpc)^3$. The most distant point in the light cone is at a redshift of $1.42$, indicating the applicability of our method to next generation of galaxy surveys.

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arXiv2021

AI-assisted super-resolution cosmological simulations

Cosmological simulations of galaxy formation are limited by finite computational resources. We draw from the ongoing rapid advances in Artificial Intelligence (specifically Deep Learning) to address this problem. Neural networks have been developed to learn from high-resolution (HR) image data, and then make accurate super-resolution (SR) versions of different low-resolution (LR) images. We apply such techniques to LR cosmological N-body simulations, generating SR versions. Specifically, we are able to enhance the simulation resolution by generating 512 times more particles and predicting their displacements from the initial positions. Therefore our results can be viewed as new simulation realizations themselves rather than projections, e.g., to their density fields. Furthermore, the generation process is stochastic, enabling us to sample the small-scale modes conditioning on the large-scale environment. Our model learns from only 16 pairs of small-volume LR-HR simulations, and is then able to generate SR simulations that successfully reproduce the HR matter power spectrum to percent level up to $16\,h^{-1}\mathrm{Mpc}$, and the HR halo mass function to within $10 \%$ down to $10^{11} \, M_\odot$. We successfully deploy the model in a box 1000 times larger than the training simulation box, showing that high-resolution mock surveys can be generated rapidly. We conclude that AI assistance has the potential to revolutionize modeling of small-scale galaxy formation physics in large cosmological volumes.

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arXiv2020

Direct geometrical measurement of the Hubble constant from galaxy parallax: predictions for the Vera C. Rubin Observatory and Nancy Grace Roman Space Telescope

We investigate the possibility that a statistical detection of the galaxy parallax shift due to the Earth's motion with respect to the CMB frame (cosmic secular parallax) could be made by the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) or by the Nancy Grace Roman Space Telescope (NGRST), and used to measure the Hubble constant. We make mock galaxy surveys which extend to redshift z=0.06 from a large N-body simulation, and include astrometric errors from the LSST and NGRST science requirements, redshift errors and peculiar velocities. We include spectroscopic redshifts for the brightest galaxies (r < 18) in the fiducial case. We use these catalogues to make measurements of parallax versus redshift,for various assumed survey parameters and analysis techniques. We find that in order to make a competitive measurement it will be necessary to model and correct for the peculiar velocity component of galaxy proper motions. It will also be necessary to push astrometry of extended sources into a new regime, and combine information from the different elements of resolved galaxies. In an appendix we describe some simple tests of galaxy image registration which yield relatively promising results. For our fiducial survey parameters, we predict an rms error on the direct geometrical measurement of H0 of 2.8% for LSST and 0.8% for NGRST.

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arXiv2020

On the possibility of Baryon Acoustic Oscillation measurements at redshift $z>7.6$ with the Roman Space Telescope

The Nancy Grace Roman Space Telescope (RST), with its field of view and high sensitivity will make surveys of cosmological large-scale structure possible at high redshifts. We investigate the possibility of detecting Baryon Acoustic Oscillations (BAO) at redshifts $z>7.6$ for use as a standard ruler. We use data from the hydrodynamic simulation \textsc{BlueTides} in conjunction with the gigaparsec-scale Outer Rim simulation and a model for patchy reionization to create mock RST High Latitude Survey grism data for Lyman-alpha emission line selected galaxies at redshifts $z=7.4$ to $z=10$, covering 2280 square degrees. We measure the monopoles of galaxies in the mock catalogues and fit the BAO features. We find that for a line flux of $L = 7\times 10^{-17} \ {\rm erg/s/cm}^{2}$, the $5 σ$ detection limit for the current design, the BAO feature is partially detectable (measured in three out of four survey quadrants analysed independently). The resulting root mean square error on the angular diameter distance to $z=7.7$ is 7.9$\%$. If we improve the detection sensitivity by a factor of two (i.e. $L = 3.5\times 10^{-17} \ {\rm erg/s/cm}^{2}$), the distance error reduces to $1.4\%$. We caution that many more factors are yet to be modelled, including dust obscuration, the damping wing due to the intergalactic medium, and low redshift interlopers. If these issues do not strongly affect the results, or different observational techniques (such as use of multiple lines) can mitigate them, RST or similar instruments may be able to constrain the angular diameter distance to the high redshift Universe.

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arXiv2020

The host galaxies of z=7 quasars: predictions from the BlueTides simulation

We examine the properties of the host galaxies of $z=7$ quasars using the large volume, cosmological hydrodynamical simulation BlueTides. We find that the 10 most massive black holes and the 191 quasars in the simulation (with $M_{\textrm{UV,AGN}} 10^{6.5}M_\odot$ black hole, indicating that minor mergers play at least some role in growing black holes in the early Universe.

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arXiv2020

Reconstructing the Gravitational Lensing Potential from the Lyman-$α$ Forest

We demonstrate a method for reconstructing the weak lensing potential from the Lyman-$α$ forest data. We derive an optimal estimator for the lensing potential on the sky based on the correlation between pixels in real space. This method effectively deals with irregularly spaced data, holes in the survey, missing data and inhomogeneous noise. We demonstrate an implementation of the method with simulated spectra and weak lensing. It is shown that with a source density of $>\sim 0.5$ per square arcminutes and $\sim 200$ pixels in each spectrum ($λ/ Δλ= 1300$) the lensing potential can be reconstructed with high fidelity if the relative absorption in the spectral pixels is signal dominated. When noise dominates the measurement of the absorption in each pixel the noise in the lensing potential is higher, but for reasonable numbers of sources and noise levels and a high fidelity map the lensing potential is obtainable. The lensing estimator could also be applied to lensing of the Cosmic Microwave Background (CMB), 21 cm intensity mapping (IM) or any case in which the correlation function of the source can be accurately estimated.

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arXiv2020

Large Scale Structure Reconstruction with Short-Wavelength Modes

Large scale density modes are difficult to measure because they are sensitive to systematic observational errors in galaxy surveys, but we can study them indirectly by observing their impact on small scale perturbations. Cosmological perturbation theory predicts that second-order density inhomogeneities are a convolution of a short- and a long-wavelength mode. This arises physically because small scale structures grow at different rates depending on the large scale environment in which they reside. This induces an off-diagonal term in the two-point statistics in Fourier space that we use as the basis for a quadratic estimator for the large scale field. We demonstrate that this quadratic estimator works well on an N-body simulation of size (2.5 h^{-1} Gpc)^3. In particular, the quadratic estimator successfully reconstructs the long-wavelength modes using only small-scale information. This opens up novel opportunities to study structure on the largest observable scales.

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arXiv2020

Trend Filtering -- I. A Modern Statistical Tool for Time-Domain Astronomy and Astronomical Spectroscopy

The problem of denoising a one-dimensional signal possessing varying degrees of smoothness is ubiquitous in time-domain astronomy and astronomical spectroscopy. For example, in the time domain, an astronomical object may exhibit a smoothly varying intensity that is occasionally interrupted by abrupt dips or spikes. Likewise, in the spectroscopic setting, a noiseless spectrum typically contains intervals of relative smoothness mixed with localized higher frequency components such as emission peaks and absorption lines. In this work, we present trend filtering, a modern nonparametric statistical tool that yields significant improvements in this broad problem space of denoising $spatially$ $heterogeneous$ signals. When the underlying signal is spatially heterogeneous, trend filtering is superior to any statistical estimator that is a linear combination of the observed data---including kernel smoothers, LOESS, smoothing splines, Gaussian process regression, and many other popular methods. Furthermore, the trend filtering estimate can be computed with practical and scalable efficiency via a specialized convex optimization algorithm, e.g. handling sample sizes of $n\gtrsim10^7$ within a few minutes. In a companion paper, we explicitly demonstrate the broad utility of trend filtering to observational astronomy by carrying out a diverse set of spectroscopic and time-domain analyses.

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arXiv2020

Trend Filtering -- II. Denoising Astronomical Signals with Varying Degrees of Smoothness

Trend filtering---first introduced into the astronomical literature in Paper I of this series---is a state-of-the-art statistical tool for denoising one-dimensional signals that possess varying degrees of smoothness. In this work, we demonstrate the broad utility of trend filtering to observational astronomy by discussing how it can contribute to a variety of spectroscopic and time-domain studies. The observations we discuss are (1) the Lyman-$α$ forest of quasar spectra; (2) more general spectroscopy of quasars, galaxies, and stars; (3) stellar light curves with planetary transits; (4) eclipsing binary light curves; and (5) supernova light curves. We study the Lyman-$α$ forest in the greatest detail---using trend filtering to map the large-scale structure of the intergalactic medium along quasar-observer lines of sight. The remaining studies share broad themes of: (1) estimating observable parameters of light curves and spectra; and (2) constructing observational spectral/light-curve templates. We also briefly discuss the utility of trend filtering as a tool for one-dimensional data reduction and compression.

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arXiv2019

Towards Machine-assisted Meta-Studies: The Hubble Constant

We present an approach for automatic extraction of measured values from the astrophysical literature, using the Hubble constant for our pilot study. Our rules-based model -- a classical technique in natural language processing -- has successfully extracted 298 measurements of the Hubble constant, with uncertainties, from the 208,541 available arXiv astrophysics papers. We have also created an artificial neural network classifier to identify papers in arXiv which report novel measurements. From the analysis of our results we find that reporting measurements with uncertainties and the correct units is critical information when distinguishing novel measurements in free text. Our results correctly highlight the current tension for measurements of the Hubble constant and recover the $3.5σ$ discrepancy -- demonstrating that the tool presented in this paper is useful for meta-studies of astrophysical measurements from a large number of publications.

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arXiv2019

QSO obscuration at high redshift ($z \gtrsim 7$): Predictions from the BlueTides simulation

High-$z$ AGNs hosted in gas rich galaxies are expected to grow through significantly obscured accretion phases. This may limit or bias their observability. In this work, we use \textsc{BlueTides}, a large volume cosmological simulation of galaxy formation to examine quasar obscuration for the highest-redshift ($z \geq 7$) supermassive black holes residing in the center of galaxies. We find that for the bright quasars, most of the high column density gas ($>90\%$) resides in the innermost regions of the host galaxy, (typically within $< 10$ ckpc), while the gas in the outskirts is a minor contributor to the $N_\mathrm H$. The brightest quasars can have large angular variations in galactic obscuration, over 2 orders of magnitude, where the lines of sight with the lowest obscuration are those formed via strong gas outflows driven by AGN feedback. We find that for the overall AGN population, the mean $N_\mathrm H$ is generally larger for high luminosity and BH mass, while the $N_\mathrm H$ distribution is significantly broadened, developing a low $N_\mathrm H $ wing due to the angular variations driven by the AGN outflows/feedback. The obscured fraction P($N_{\rm H} > 10^{23} {\rm cm}^{-2}$) typically range from 0.6 to 1.0 for increasing $L_{X}$ (with $L_X > 10^{43} \rm{ergs/s}$), with no clear trend of redshift evolution. With respect to the galaxy host property, we find a linear relation between $N_{\rm H}$, $M_*$ and $M_{\rm H_2}$ with $\log N_{\rm H} = (0.24 \pm 0.03) \log M_{*} + (20.7 \pm 0.3)$ and $\log N_{\rm H} = (0.47 \pm 0.03) \log M_{\rm H_2} + (18.4 \pm 0.3)$. The dust optical depth in the UV band $τ_{\mathrm UV}$ has tight positive correlation with $N_{\rm H}$. Our dust extincted UVLF is about 1.5 dex lower than the intrinsic UVLF, implying that more than 99\% of the $z \sim 7$ AGNs are heavily dust extincted and therefore would be missed by the UV band observation.

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arXiv2019

Inflation and Dark Energy from spectroscopy at $z > 2$

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 $z < 1$, 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. The large cosmological volume at $2 < z < 5$, together with the ability to efficiently target high-$z$ galaxies with known techniques, enables large gains in the study of Inflation and Dark Energy. A future spectroscopic survey can test the Gaussianity of the initial conditions up to a factor of ~50 better than our current bounds, crossing the crucial theoretical threshold of $σ(f_{NL}^{\rm local})$ of order unity that separates single field and multi-field models. Simultaneously, it can measure the fraction of Dark Energy at the percent level up to $z = 5$, thus serving as an unprecedented test of the standard model and opening up a tremendous discovery space.

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arXiv2019

Dark Matter Science in the Era of LSST

Astrophysical observations currently provide the only robust, empirical measurements of dark matter. In the coming decade, astrophysical observations will guide other experimental efforts, while simultaneously probing unique regions of dark matter parameter space. This white paper summarizes astrophysical observations that can constrain the fundamental physics of dark matter in the era of LSST. We describe how astrophysical observations will inform our understanding of the fundamental properties of dark matter, such as particle mass, self-interaction strength, non-gravitational interactions with the Standard Model, and compact object abundances. Additionally, we highlight theoretical work and experimental/observational facilities that will complement LSST to strengthen our understanding of the fundamental characteristics of dark matter.

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arXiv2019

Gravitational redshift profiles of MaNGA BCGs

The gravitational potential well of an $M>10^{13}$ $M_\odot$ galaxy will lead to a gravitational redshift differential of order 1 km/s between the galaxy core and its outskirts. Current surveys of massive galaxies with spatially resolved spectroscopy have reached a size which makes feasible attempts to detect gravitational redshifts within galaxies. We use spectra from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) experiment to attempt a measurement of the averaged stellar redshift profile of large elliptical galaxies. We find that systematic effects (possibly related to charge transfer or wavelength calibration accuracy) make the standard MaNGA data pipeline unsuitable for measuring the relevant sub km/s wavelength shifts. We therefore develop a cross-correlation technique to mitigate these effects, but caution that we are working beyond the design accuracy of the MaNGA experiment. With a sample of $272$ galaxies in halos with $\log (M/M_\odot)>13$, we attempt a measurement of the gravitational redshift profile, achieving $1 σ$ errors of size $\sim 0.5$ km/s, but are unable to make a significant detection of the signal. Even without a detection, our measurement can be used to limit the dark matter mass within the half light radius of elliptical galaxies to $1.2$ times the stellar mass, at the 68% confidence level. We also perform weighting scheme tests and split sample tests, and address target selection issues and other relativistic effects, including the transverse Doppler effect and relativistic beaming of stars. Future detections could lead to new constraints on the galaxy mass distribution that are different from kinematic and lensing determinations and open a window on galaxy properties and tests of gravity.

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arXiv2019

Effects of baryons on the gravitational redshift profile of ΛCDM halos

Gravitational redshifts and other relativistic effects are beginning to be studied in the context of galaxy clustering. Distortions consistent with those expected in General Relativity have been measured in galaxy cluster redshift profiles by Wojtak et al. and others and in the the cross-correlation function of galaxy populations by Alam et al. On scales below ~20 Mpc/$h$ simulations have shown that gravitational redshift dominates over other effects. However, this signal is related to the shape and depth of gravitational potentials, and therefore the matter density in galaxies and galaxy clusters that is responsible for them. We investigate the effects of baryonic physics on the gravitational redshift profiles of massive (group and cluster-sized) halos. We compare the profiles of different components in halos taken from the MassiveBlack-II cosmological hydrodynamic simulation and a dark matter-only version of the same simulation. We find that inclusion of baryons, cooling, star formation and feedback significantly alters the relevant inner density profiles. These baryonic effects lead to overall increases in both gravitational redshifts and the transverse relativistic Doppler effects by up to ~50% for group size halos. We show how modified Navarro Frenk White halo profiles can be used to parametrize these differences, and provide relevant halo profile fits.

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arXiv2018

Intensity mapping with SDSS/BOSS Lyman-alpha emission, quasars and their Lyman-alpha forest

We investigate the large-scale structure of Lyman-alpha emission intensity in the Universe at redshifts z=2-3.5 using cross-correlation techniques. Our Lya emission samples are spectra of BOSS Luminous Red Galaxies from Data Release 12 with the best fit model galaxies subtracted. We cross-correlate the residual flux in these spectra with BOSS quasars, and detect a positive signal on scales 1-15 Mpc/h. We identify and remove a source of contamination not previously accounted for, due to the effects of quasar clustering on cross-fibre light. Corrected, our quasar-Lya emission cross-correlation is 50 % lower than that seen by Croft et al. for DR10, but still significant. Because only 3% of space is within 15 Mpc/h of a quasar, the result does not fully explore the global large-scale structure of Lya emission. To do this, we cross-correlate with the Lya forest. We find no signal in this case. The 95% upper limit on the global Lya mean surface brightness from Lya emission-Lya forest cross-correlation is mu < 1.2x10^-22 erg/s/cm^2/A/arcsec^2 This null result rules out the scenario where the observed quasar-Lya emission cross-correlation is primarily due to the large scale structure of star forming galaxies, Taken in combination, our results suggest that Lya emitting galaxies contribute, but quasars dominate within 15 Mpc/h. A simple model for Lya emission from quasars based on hydrodynamic simulations reproduces both the observed forest-Lya emission and quasar-Lya emission signals. The latter is also consistent with extrapolation of observations of fluorescent emission from smaller scales r < 1 Mpc.

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