3D Power Spectrum Research Articles

A multiple x-ray-source array (MXA) system with a planar two-dimensional source distribution for digital breast tomosynthesis.

Digital breast tomosynthesis (DBT) has outpaced digital mammography in clinical adoption in the United States; however, substantial technological limitations remain to image quality in DBT, including undersampling from a one-dimensional (1D) scan geometry, x-ray source motion during acquisition, and patient motion artifacts from long exam times. A thermionic cathode x-ray system employing two-dimensional (2D, planar) multiple x-ray-source arrays (MXA) is proposed to improve DBT image quality. A 1D MXA, consisting of a linear array of thermionic cathodes was used to simulate a 2D MXA. The 1D MXA included 11 focal spots separated by a distance of =23mm. The 11 cathodes were paired with 11 molybdenum 50mm diameter anode disks, mounted on a rotating shaft within a single vacuum enclosure. Image quality was investigated as a function of MXA configuration by integrating the 1D MXA with a 200 × 250 mm2 flat panel detector at a source-to-detector distance of 630mm, resulting in a 20° tomographic arc. To simulate a 2D MXA, the detector (with phantom) was translated orthogonally to the linear array by a distance ( ) ranging from =0mm (conventional 1D) to =57mm. All sources operated at 30kV with 80mA and 4.5 mAs/pulse, yielding ∼100 mAs per DBT dataset. DBT reconstructions involved 22 projections and used filtered backprojection with a ramp and Hann apodization filter. Volumetric reconstructions for each source were weighted by sampling differences between sources, and averaged. Image quality was assessed in terms of contrast-to-noise ratio (CNR), background clutter noise and power spectrum, and slice sensitivity profile (SSP) using a set of physical phantoms, including: (i) contrast-detail signals coupled to spherical clutter (PMMA in air); (ii) an SSP phantom; (iii) a commercial "breast" phantom (CIRS BR3D, Sun Nuclear, Norfolk, VA); and (iv) bovine muscle. Background clutter noise amplitude reduced monotonically from the 1D MXA (σclutter=5.9 A.U., =0mm) and 2D MXA arrays with increasing , with statistical significance between the 1D MXA and 2D MXA with =57mm (σclutter=5.0 A.U., p<0.001). The contrast-detail/clutter phantom demonstrated CNR from the 2D MXA (δ=57mm) outperforming the 1D MXA in all combinations of contrast and detail. 2D power spectrum analysis of clutter demonstrated a pronounced Fourier domain null cone for the 1D MXA in the anterior field-of-view (away from the 1D MXA position), whereas the 2D MXA geometry (δ=57mm) did not exhibit the null cone. The SSP was 15%-50% narrower (FWHM) for the 2D versus the 1D geometry, across all reconstruction setups. The advantages of a 2D source geometry for DBT imaging were demonstrated quantitatively compared to a conventional 1D line of x-ray sources. The improvement in the 2D geometry was attributed both to improved Fourier domain sampling and reduced SSP. We conclude that 2D MXA sources have the potential to substantially improve DBT imaging in comparison to existing commercial DBT systems.

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

Abstract 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 (ik · 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 artifacts 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.

Direct Optimal Mapping Image Power Spectrum and its Window Functions

The key to detecting neutral hydrogen during the epoch of reionization (EoR) is to separate the cosmological signal from the dominating foreground radiation. We developed direct optimal mapping (DOM) to map interferometric visibilities; it contains only linear operations, with full knowledge of point spread functions from visibilities to images. Here, we demonstrate a fast Fourier transform-based image power spectrum and its window functions computed from the DOM images. We use noiseless simulation, based on the Hydrogen Epoch of Reionization Array Phase I configuration, to study the image power spectrum properties. The window functions show <10−11 of the integrated power leaks from the foreground-dominated region into the EoR window; the 2D and 1D power spectra also verify the separation between the foregrounds and the EoR.

The Negative Baryon Acoustic Oscillation Shift in the Lyα Forest from Cosmological Simulations

We present the first measurement of the Lyα forest baryon acoustic oscillations (BAO) shift parameter from cosmological simulations. In particular, we generate a suite of 1000 accurate effective field-level bias-based Lyα forest simulations of volume V=(1h−1Gpc)3 at z = 2, both in real and redshift space, calibrated upon two fixed-and-paired cosmological hydrodynamic simulations. To measure the BAO, we stack the 3D power spectra of the 1000 different realizations, compute the average, and use a model accounting for a proper smooth-peak component decomposition of the power spectrum, to fit it via an efficient Markov Chain Monte Carlo scheme estimating the covariance matrices directly from the simulations. We report the BAO shift parameters to be α=0.9969−0.0014+0.0014 and α=0.9905−0.0027+0.0027 in real and redshift space, respectively. We also measure the bias b lya and the BAO broadening parameter Σnl, finding blya=−0.1786−0.0001+0.0001 and Σnl=3.87−0.20+0.20 in real space, and blya=−0.073−0.004+0.005 and Σnl=6.55−0.22+0.23 in redshift space. Moreover, we measure the linear Kaiser factor βlya=1.39−0.18+0.24 from the isotropic redshift space fit. Overall, we find evidence for a negative shift of the BAO peak at the ∼2.2σ and ∼3.5σ levels in real and redshift space, respectively. This work sets new important theoretical constraints on the Lyα forest BAO scale and offers a potential solution to the tension emerging from previous observational analysis, in light of ongoing and upcoming Lyα forest spectroscopic surveys, such as DESI, the Prime Focus Spectrograph Survey, and WEAVE-QSO.

Impact of Self-shielding Minihalos on the Lyα Forest at High Redshift

Dense gas in minihalos with masses of 106−108 M ⊙ can shield themselves from reionization for ∼100 Myr after being exposed to the UV background. These self-shielded systems, often unresolved in cosmological simulations, can introduce strong absorption in quasar spectra. This paper is the first systematic study on the impact of these systems on the Lyα forest. We first derive the H i column density profile of photoevaporating minihalos by conducting 1D radiation–hydrodynamics simulations. We utilize these results to estimate the Lyα opacity from minihalos in a large-scale simulation that cannot resolve self-shielding. When the ionization rate of the background radiation is 0.03 × 10−12 s−1, as expected near the end of reionization at z ∼ 5.5, we find that the incidence rate of damped Lyα absorbers increases by a factor of ∼2−4 compared to at z = 4.5. The Lyα flux is, on average, suppressed by ∼3% of its mean due to minihalos. The absorption features enhance the 1D power spectrum up to ∼5% at k ∼ 0.1 h Mpc−1 (or 10−3 km−1 s), which is comparable to the enhancement caused by inhomogeneous reionization. The flux is particularly suppressed in the vicinity of large halos along the line-of-sight direction at separations of up to 10 h −1 Mpc at r ⊥ ≲ 2 h −1 Mpc. However, these effects become much smaller for higher ionizing rates (≳0.3 × 10−12 s−1) expected in the post-reionization Universe. Our findings highlight the need to consider minihalo absorption when interpreting the Lyα forest at z ≳ 5.5. Moreover, the sensitivity of these quantities to the ionizing background intensity can be exploited to constrain the intensity itself.

Wavelet-based statistics for enhanced 21cm EoR parameter constraints

We propose a new approach to improve the precision of astrophysical parameter constraints for the 21cm signal from the epoch of reionisation (EoR). Our method introduces new sets of summary statistics, hereafter ‘evolution compressed’ statistics, which quantify the spectral evolution of the 2D spatial statistics computed at fixed redshift. We defined such compressed statistics for power spectrum (PS), wavelet scattering transforms (WST), and wavelet moments (WM), which also characterise non-Gaussian features. To compare these different statistics, along with the 3D power spectrum, we estimated their Fisher information on three cosmological parameters from an ensemble of simulations of 21cm EoR data, both in noiseless and noisy scenarios using Square Kilometre Array (SKA) noise levels equivalent to 100 and 1000 h of observations. We also compare wavelet statistics, in particular WST, built from standard directional Morlet wavelets, as well as from a set of isotropic wavelets derived from the binning window function of the 2D power spectrum. For the noiseless case, the compressed wavelet statistics give constraints that are up to five times more precise than those obtained from the 3D isotropic power spectrum. At the same time, for 100 h SKA noise, from which it is difficult to extract non-Gaussian features, compressed wavelet statistics still give over 30% tighter constraints. We find that the wavelet statistics with wavelets derived from the power-spectrum binning window function provide the tightest constraints of all the statistics, with the WSTs seemingly performing better than the WMs, in particular when working with noisy data. The findings of this study demonstrate that evolution-compressed statistics extract more information than usual 3D isotropic power-spectra approaches and that our wavelet-based statistics can consistently outmatch power-spectrum-based statistics. When constructing such wavelet-based statistics, we also emphasise the need to choose a set of wavelets with an appropriate spectral resolution concerning the astrophysical process studied.

Influence of sources with a spectral peak in the detection of Cosmic Dawn and Epoch of Reionization

ABSTRACT Foreground removal is one of the biggest challenges in the detection of the Cosmic Dawn (CD) and Epoch of Reionization (EoR). Various foreground subtraction techniques have been developed based on the spectral smoothness of foregrounds. However, the sources with a spectral peak (SP) at megahertz may break down the spectral smoothness at low frequencies (&amp;lt;1000 MHz). In this paper, we cross-match the GaLactic and Extragalactic All-sky Murchison Widefield Array (GLEAM) extragalactic source catalogue with three other radio source catalogues, covering the frequency range 72 MHz–1.4 GHz, to search for sources with spectral turnover. 4423 sources from the GLEAM catalogue are identified as SP sources, representing ≈3.2 per cent of the GLEAM radio source population. We utilize the properties of SP source candidates obtained from real observations to establish simulations and test the impact of SP sources on the extraction of CD/EoR signals. We statistically compare the differences introduced by SP sources in the residuals after removing the foregrounds with three methods, which are polynomial fitting, principal component analysis, and fast independent component analysis. Our results indicate that the presence of SP sources in the foregrounds has a negligible influence on extracting the CD/EoR signal. After foreground subtraction, the contribution from SP sources to the total power in the two-dimensional power spectrum within the EoR window is approximately 3–4 orders of magnitude lower than the CD/EoR signal.

Flat-sky angular power spectra revisited

We revisit the flat-sky approximation for evaluating the angular power spectra of projected random fields by retaining information about the correlations along the line of sight. For the case of projections with broad, overlapping radial window functions, these line-of-sight correlations are suppressed and are ignored in the commonly adopted Limber approximation. However, retaining the correlations is important for narrow window functions or unequal-time spectra but introduces significant computational difficulties due to the highly oscillatory nature of the integrands involved. We deal with the integral over line-of-sight wave-modes in the flat-sky approximation analytically, using the FFTlog expansion of the 3D power spectrum. This results in an efficient computational method, which is a substantial improvement compared to any full-sky approaches. We apply our results to galaxy clustering (with and without redshift-space distortions), CMB lensing and galaxy lensing observables in a flat ΛCDM universe. In the case of galaxy clustering, we find excellent agreement with the full-sky results on large (percent-level agreement) and intermediate or small (subpercent agreement) scales, dramatically out-performing the Limber approximation for both wide and narrow window functions, and in equal- and unequal-time cases. In the cases of lensing, we show on the full-sky that the angular power spectrum of the lensing convergence can be very well approximated by projecting the 3D Laplacian (rather than the correct angular Laplacian) of the gravitational potential, even on large scales. Combining this approximation with our flat-sky techniques provides an efficient and accurate evaluation of the CMB lensing angular power spectrum on all scales. We further analyse the clustering and lensing angular power spectra by isolating the projection effects due to the observable- and survey-specific window functions, separating them from the effects due to integration along the line of sight and unequal-time mixing in the 3D power spectrum. All of the angular power spectrum results presented in this paper are obtained using a Python code implementation, which we make publicly available.

Field-level Lyman-α forest modeling in redshift space via augmented nonlocal Fluctuating Gunn-Peterson Approximation

Context. Devising fast and accurate methods of predicting the Lyman-α forest at the field level, avoiding the computational burden of running large-volume cosmological hydrodynamic simulations, is of fundamental importance to quickly generate the massive set of simulations needed by the state-of-the-art galaxy and Lyα forest spectroscopic surveys. Aims. We present an improved analytical model to predict the Lyα forest at the field level in redshift space from the dark matter field, expanding upon the widely used Fluctuating Gunn-Peterson Approximation (FGPA). Instead of assuming a unique universal relation over the whole considered cosmic volume, we introduce a dependence on the cosmic web environment (knots, filaments, sheets, and voids) in the model, thereby effectively accounting for nonlocal bias. Furthermore, we include a detailed treatment of velocity bias in the redshift space distortion modeling, allowing the velocity bias to be cosmic-web-dependent. Methods. We first mapped the dark matter field from real to redshift space through a particle-based relation including velocity bias, depending on the cosmic web classification of the dark matter field in real space. We then formalized an appropriate functional form for our model, building upon the traditional FGPA and including a cutoff and a boosting factor mimicking a threshold and inverse-threshold bias effect, respectively, with model parameters depending on the cosmic web classification in redshift space. Eventually, we fit the coefficients of the model via an efficient Markov chain Monte Carlo scheme. Results. We find evidence for a significant difference between the same model parameters in different environments, suggesting that for the investigated setup the simple standard FGPA is not able to adequately predict the Lyα forest in the different cosmic web regimes. We reproduce the summary statistics of the reference cosmological hydrodynamic simulation that we use for comparison, yielding an accurate mean transmitted flux, probability distribution function, 3D power spectrum, and bispectrum. In particular, we achieve maximum deviation and average deviation accuracy in the Lyα forest 3D power spectrum of ∼3% and ∼0.1% up to k ∼ 0.4 h Mpc−1, and ∼5% and ∼1.8% up to k ∼ 1.4 h Mpc−1. Conclusions. Our new model outperforms previous analytical efforts to predict the Lyα forest at the field level in all the probed summary statistics, and has the potential to become instrumental in the generation of fast accurate mocks for covariance matrices estimation in the context of current and forthcoming Lyα forest surveys.

Improvement to the Epoch of Reionisation power spectrum using simulations with the Central Redundant Array Mega-tile (CRAM)

Abstract Detection of the 21 cm signal from the Epoch of Reionisation (EoR) ( $z \sim 6 - 10$ ) amidst the dominant foregrounds, which are 3–4 orders of magnitude greater than the weak cosmological signal, is a challenging task for the existing 21 cm experiments. The detection is further challenged by the large Field of View (FoV) of the instrument used for observation, as it becomes necessary to excise foregrounds present within the FoV to make a successful detection. In response to the challenges faced, in our previous work, we developed and installed a new instrument – the Central Redundant Array Mega-tile (CRAM) – and integrated it within the MWA Phase II configuration. It is a larger antenna tile configuration ( $8\times 8$ dipoles) with a smaller FoV at every frequency under consideration and has multiple sidelobes of reduced response when compared with the existing Murchison Widefield Array (MWA) tiles. In this paper, we aim to demonstrate through power spectrum simulations that using the larger tile, such as the CRAM, can reduce the impact of bright radio foregrounds near the field edge. For the pedagogical approach aimed with this work, we developed a power spectrum pipeline to estimate the cylindrically averaged power spectrum. The power spectrum is estimated for MWA-MWA baselines and CRAM-MWA baselines using analytical beams, simulated diffuse sky maps and a semi-numerical 21 cm signal. Employing a drift scanning strategy, we estimate 1D and 2D power spectra for a series of two-minute observations spanning 24 hrs using the diffuse sky maps. Our simulations predict a power reduction at the edge of the EoR wedge. The reduction in foreground power is confirmed with the Fisher analysis of the expected signal-to-noise ratio (SNR) improvement, which reports a higher SNR with the power estimations from CRAM baselines when compared with the regular MWA baselines. The reduced power obtained with the CRAM baselines is consistent with the fact that the larger tile configuration has reduced the impact of foregrounds from near the horizon.

Power spectrum estimation methods on intracluster medium surface brightness fluctuations

Accurate estimation of galaxy cluster masses is a central problem in cosmology. Turbulence is believed to introduce significant deviations from the hydrostatic mass estimates. Estimation of turbulence properties is complicated by projection of the 3D cluster onto the 2D plane of the sky, and is commonly done in the form of indirect probes from fluctuations in the X-ray surface brightness and Sunyaev-Zeldovich effect maps. In this paper, we address this problem using simulations. We examine different methods for estimating the power spectrum on 2D projected fluctuation data, emulating data projected onto a 2D plane of the sky, and comparing them to the original, expected 3D power spectrum. Noise can contaminate the power spectrum of ICM observations, so we also briefly compare a few methods of reducing noise in the images for better spectral estimation.

Planting a Lyman alpha forest on AbacusSummit

ABSTRACT 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 analysing them. Here, we leverage the accuracy and volume of the N-body simulation suite AbacusSummit to generate high-resolution Ly α skewers and quasi-stellar object (QSO) catalogues. 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 = 69123) 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 = 25003). 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 × QSO cross-correlation, which would be important to account for in upcoming analyses. The 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 via the National Energy Research Scientific Computing Center (NERSC) (full link under the section ‘Data Availability’).

Studying the multifrequency angular power spectrum of the cosmic dawn 21-cm signal

ABSTRACT The light-cone (LC) anisotropy arises due to cosmic evolution of the cosmic dawn (CD) 21-cm signal along the line-of-sight (LoS) axis of the observation volume. The LC effect makes the signal statistically non-ergodic along the LoS axis. The multifrequency angular power spectrum (MAPS) provides an unbiased alternative to the popular three-dimensional (3D) power spectrum as it does not assume statistical ergodicity along every direction in the signal volume. Unlike the 3D power spectrum which mixes the cosmic evolution of the 21-cm signal along the LoS k modes, MAPS keeps the evolution information disentangled. Here, we first study the impact of different underlying physical processes during CD on the behaviour of the 21-cm MAPS using simulations of various different scenarios and models. We also make error predictions in 21-cm MAPS measurements considering only the system noise and cosmic variance for mock observations of Hydrogen Epoch of Reionization Array (HERA), NenuFAR, and SKA-Low. We find that 100 h of HERA observations will be able to measure 21-cm MAPS at ≥3σ for ℓ ≲ 1000 with $0.1\, {\rm MHz}$ channel-width. The better sensitivity of SKA-Low allows reaching this sensitivity up to ℓ ≲ 3000. Note that due to the difference in the frequency coverage of the various experiments, the CD–epoch of reionization model considered for NenuFAR is different than those used for the HERA and SKA-Low predictions. Considering NenuFAR with the new model, measurements ≥2σ are possible only for ℓ ≲ 600 with $0.2\, {\rm MHz}$ channel-width and for a 10 times longer observation time of tobs = 1000 h. However, for the range 300 ≲ ℓ ≲ 600 and tobs = 1000 h more than 3σ measurements are still possible for NenuFAR when combining consecutive frequency channels within a 5 MHz band.

A deep dive: Chandra observations of the NGC 4839 group falling into the Coma cluster

ABSTRACT Cosmological simulations of structure formation predict that galaxy clusters continue to grow and evolve through ongoing mergers with group-scale systems. During these merging events, the ram pressure applied by the intracluster medium acts to strip the gas from the infalling groups, forming large tails of stripped gas, which eventually become part of the main cluster. In this work, we present a detailed analysis of our new deep Chandra observations of the NGC 4839 group falling into the nearby Coma cluster, providing a unique opportunity to explore the way galaxy clusters in the local Universe continue to grow. Our analysis reveals a cold front feature at the leading head of the group, preceded by a bow shock of hot gas in front with a Mach number of ∼1.5. The power spectrum of surface brightness fluctuations in the tail shows that the slope gets less steep as the distance from the leading head increases, changing from $-2.35_{-0.06}^{+0.07}$ at the inner part of the tail to $-1.37_{-0.07}^{+0.09}$ at the outermost part of the tail. These values are shallower than the slope of the Kolmogorov 2D power spectrum, indicating that thermal conduction is being suppressed throughout the tail, enabling long-lived small-scale turbulence, which would typically be washed out if thermal conduction was not inhibited. The characteristic amplitude of surface brightness fluctuations in the tail suggests a mild level of turbulence with a Mach number in the range of 0.1–0.5, agreeing with that found for the infalling group in Abell 2142.

Influence of Pitch on Surface Dose Distribution and Image Noise of Computed Tomography Scans.

This study evaluated the effect of pitch on 256-slice helical computed tomography (CT) scans. Cylindrical water phantoms (CWP) were measured using axial and helical scans with various pitch values. The surface dose distributions of CWP were measured, and reconstructed images were obtained using filtered back-projection (FBP) and iterative model reconstruction (IMR). The image noise in each reconstructed image was decomposed into a baseline component and another component that varied along the z-axis. The baseline component of the image noise was highest at the center of the reconstructed image and decreased toward the edges. The normalized 2D power spectra for each pitch were almost identically distributed. Furthermore, the ratios of the 2D power spectra for IMR and FBP at different pitch values were obtained. The magnitudes of the components varying along the z-axis were smallest at the center of the reconstructed image and increased toward the edge. The ratios of the 3D power spectra on the fx axis for IMR and FBP at different pitch values were obtained. The results showed that the effect of the pitch was related to the component that varied along the z-axis. Furthermore, the pitch had a smaller effect on IMR than on FBP.

Why and when to expect Gaussian error distributions in epoch of reionization 21-cm power spectrum measurements

ABSTRACTWe explore error distributions in Epoch of Reionization 21-cm power spectrum estimators using a combination of mathematical analysis and numerical simulations. We provide closed-form solutions for the error distributions of individual bins in 3d-power spectra for two estimators currently in use in the field, which we designate as ‘straight-square’ and ‘cross-multiply’ estimators. We then demonstrate when the corresponding spherically binned power spectra should (and should not) have Gaussian error distributions, which requires appealing to non-standard statements of the central limit theorem. This has important implications for how upper limits are reported, as well as how cosmological inferences are performed based on power spectrum measurements. Specifically, assuming a Gaussian error distribution can over- or underestimate the upper limit depending on the type of estimator and produces overly compact likelihood functions for the power spectrum.

Separating the memory of reionisation from cosmology in the Lyα forest power spectrum at the post-reionisation era

ABSTRACTIt has been recently shown that the astrophysics of reionisation can be extracted from the Lyα forest power spectrum by marginalizing the memory of reionisation over cosmological information. This impact of cosmic reionisation on the Lyα forest power spectrum can survive cosmological time-scales because cosmic reionisation, which is inhomogeneous, and subsequent shocks from denser regions can heat the gas in low-density regions to ∼3 × 104 K and compress it to mean-density. Current approach of marginalization over the memory of reionisation, however, is not only model-dependent, based on the assumption of a specific reionisation model, but also computationally expensive. Here, we propose a simple analytical template for the impact of cosmic reionisation, thereby treating it as a broad-band systematic to be marginalized over for Bayesian inference of cosmological information from the Lyα forest in a model-independent manner. This template performs remarkably well with an error of $\le 6~{{\ \rm per\ cent}}$ at large scales k ≈ 0.19 Mpc−1, where the effect of the memory of reionisation is important, and reproduces the broad-band effect of the memory of reionisation in the Lyα forest correlation function, as well as the expected bias of cosmological parameters due to this systematic. The template can successfully recover the morphology of forecast errors in cosmological parameter space as expected when assuming a specific reionisation model for marginalization purposes, with a slight overestimation of tens of per cent for the forecast errors on the cosmological parameters. We further propose a similar template for this systematic on the Lyα forest 1D power spectrum.

Inpainting Hydrodynamical Maps with Deep Learning

From 1000 hydrodynamic simulations of the CAMELS project, each with a different value of the cosmological and astrophysical parameters, we generate 15,000 gas temperature maps. We use a state-of-the-art deep convolutional neural network to recover missing data from those maps. We mimic the missing data by applying regular and irregular binary masks that cover either 15% or 30% of the area. We quantify the reliability of our results using two summary statistics: (1) the distance between the probability density functions, estimated using the Kolmogorov–Smirnov (K-S) test, and (2) the 2D power spectrum. We find an excellent agreement between the model prediction and the unmasked maps when using the power spectrum: better than 1% for k < 20 h Mpc−1 for any irregular mask. For regular masks, we observe a systematic offset of ∼5% when covering 15% of the maps, while the results become unreliable when 30% of the data is missing. The observed K-S test p-values favor the null hypothesis that the reconstructed and the ground-truth maps are drawn from the same underlying distribution when irregular masks are used. For regular-shaped masks, on the other hand, we find a strong evidence that the two distributions do not match each other. Finally, we use the model, trained on gas temperature maps, to inpaint maps from fields not used during model training. We find that, visually, our model is able to reconstruct the missing pixels from the maps of those fields with great accuracy, although its performance using summary statistics depends strongly on the considered field.

The information content of projected galaxy fields

ABSTRACT The power spectrum of the non-linearly evolved large-scale mass distribution recovers only a minority of the information available on the mass fluctuation amplitude. We investigate the recovery of this information in 2D ‘slabs’ of the mass distribution averaged over ≈100 h−1 Mpc along the line of sight, as might be obtained from photometric redshift surveys. We demonstrate a Hamiltonian Monte Carlo method to reconstruct the non-Gaussian mass distribution in slabs, under the assumption that the projected field is a point-transformed Gaussian random field, Poisson-sampled by galaxies. When applied to the Quijote N-body suite at z = 0.5 and at a transverse resolution of 2 h−1 Mpc, the method recovers ∼30 times more information than the 2D power spectrum in the well-sampled limit, recovering the Gaussian limit on information. At a more realistic galaxy sampling density of 0.01 h3 Mpc−3, shot noise reduces the information gain to a factor of 5 improvement over the power spectrum at resolutions of 4 h−1 Mpc or smaller.

Extraction and Reconstruction of Arbitrary 3D Frequency Features from the Potassium Dihydrogen Phosphate Surfaces Machined by Different Cutting Parameters.

To comprehensively analyze the effect of cutting parameters on the 3D surface topography of machined potassium dihydrogen phosphate crystals, 2D power spectrum density and continuous wavelet transform are used to extract and reconstruct the arbitrary actual 3D frequency features of machined potassium dihydrogen phosphate crystal surfaces. The 2D power spectrum density method is used to quantitatively describe the 3D surface topography of machined potassium dihydrogen phosphate crystals. The continuous wavelet transform method is applied to extract and reconstruct 3D topographies of arbitrary actual spatial frequency features in machined surfaces. The main spatial frequency features fx of the machined surfaces are 0.0056 μm-1, 0.0112 μm-1, and 0.0277 μm-1 with the cutting depth from 3 μm to 9 μm. With the feed rate changing from 8μm/r to 18 μm/r, the main spatial frequency features fx are 0.0056 μm-1-0.0277 μm-1. With the spindle speed from 1300 r/min to 1500 r/min, the main spatial frequency features fx are same as the main spatial frequency features of the cutting depths. The results indicate that the variation of cutting parameters affects the main spatial frequency features on the 3D surface topography. The amplitudes of the spatial middle-frequency features are increased with the increasing of cutting depth and spindle speed. The spatial low-frequency features are mainly affected via the feed rate. The spatial high-frequency features are related to the measurement noise and material properties of potassium dihydrogen phosphate. The distributional directions of the frequency features in the reconstructed 3D surface topography are consistent with the distribution directions of actual frequency features in the original surface topography. The reconstructed topographies of the spatial frequency features with maximum power spectrum density are the most similar to the original 3D surfaces. In this machining, the best 3D surface topography of the machined KDP crystals is obtained with a cutting depth ap = 3 μm, feed rate f = 8 μm/r and a spindle speed n = 1400 r/min.