arXiv subjects

Paul La Plante

Publications and source records attributed to Paul La Plante.

At least 37 records · Page 2Linked to original sources

arXiv2022

HERA Phase I Limits on the Cosmic 21-cm Signal: Constraints on Astrophysics and Cosmology During the Epoch of Reionization

Recently, the Hydrogen Epoch of Reionization Array (HERA) collaboration has produced the experiment's first upper limits on the power spectrum of 21-cm fluctuations at z~8 and 10. Here, we use several independent theoretical models to infer constraints on the intergalactic medium (IGM) and galaxies during the epoch of reionization (EoR) from these limits. We find that the IGM must have been heated above the adiabatic cooling threshold by z~8, independent of uncertainties about the IGM ionization state and the nature of the radio background. Combining HERA limits with galaxy and EoR observations constrains the spin temperature of the z~8 neutral IGM to 27 K < T_S < 630 K (2.3 K < T_S < 640 K) at 68% (95%) confidence. They therefore also place a lower bound on X-ray heating, a previously unconstrained aspects of early galaxies. For example, if the CMB dominates the z~8 radio background, the new HERA limits imply that the first galaxies produced X-rays more efficiently than local ones (with soft band X-ray luminosities per star formation rate constrained to L_X/SFR = { 10^40.2, 10^41.9 } erg/s/(M_sun/yr) at 68% confidence), consistent with expectations of X-ray binaries in low-metallicity environments. The z~10 limits require even earlier heating if dark-matter interactions (e.g., through millicharges) cool down the hydrogen gas. Using a model in which an extra radio background is produced by galaxies, we rule out (at 95% confidence) the combination of high radio and low X-ray luminosities of L_{r,ν}/SFR > 3.9 x 10^24 W/Hz/(M_sun/yr) and L_X/SFR<10^40 erg/s/(M_sun/yr). The new HERA upper limits neither support nor disfavor a cosmological interpretation of the recent EDGES detection. The analysis framework described here provides a foundation for the interpretation of future HERA results.

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arXiv2022

Direct Optimal Mapping for 21cm Cosmology: A Demonstration with the Hydrogen Epoch of Reionization Array

Motivated by the desire for wide-field images with well-defined statistical properties for 21cm cosmology, we implement an optimal mapping pipeline that computes a maximum likelihood estimator for the sky using the interferometric measurement equation. We demonstrate this direct optimal mapping with data from the Hydrogen Epoch of Reionization (HERA) Phase I observations. After validating the pipeline with simulated data, we develop a maximum likelihood figure-of-merit for comparing four sky models at 166MHz with a bandwidth of 100kHz. The HERA data agree with the GLEAM catalogs to <10%. After subtracting the GLEAM point sources, the HERA data discriminate between the different continuum sky models, providing most support for the model of Byrne et al. 2021. We report the computation cost for mapping the HERA Phase I data and project the computation for the HERA 320-antenna data; both are feasible with a modern server. The algorithm is broadly applicable to other interferometers and is valid for wide-field and non-coplanar arrays.

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arXiv2022

Probing helium reionization with kinetic Sunyaev Zel'dovich tomography

Reionization of helium is expected to occur at redshifts $z\sim3$ and have important consequences for quasar populations, galaxy formation, and the morphology of the intergalactic medium, but there is little known empirically about the process. Here we show that kinetic Sunyaev-Zeldovich (kSZ) tomography, based on the combination of CMB measurements and galaxy surveys, can be used to infer the primordial helium abundance as well as the time and duration of helium reionization. We find a high-significance detection at ${\sim10σ}$ can be expected from Vera Rubin Observatory and CMB-S4 in the near future. A more robust characterization of helium reionization will require next-generation experiments like MegaMapper (a proposed successor to DESI) and CMB-HD.

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arXiv2022

Signatures of reionization feedback in the near-infrared background

The reionization of the intergalactic medium at redshifts $z\gtrsim 6$ is expected to have a lasting impact on galaxies residing in low-mass dark matter halos. Unable to accrete or retain gas photo-heated to temperatures $T \gtrsim 10^4$ K, the star formation histories of faint galaxies in the early Universe are expected to decline as they exhaust their gas supply, resulting in a turn-over in the galaxy luminosity function (LF) and a potential solution to the missing satellites problem in the local group. Unfortunately, there are several challenges to constraining `reionization feedback' empirically, most notably that galaxies in low-mass halos are intrinsically faint, and that there are other physical mechanisms capable of inducing a turn-over in the LF. In this work, we investigate a new signature of reionization feedback that is in principle distinct from other processes: as faint galaxies are quenched by reionization, their stellar populations passively age and grow redder while the brighter galaxies nearby continue to form stars at an increasing rate and so remain relatively blue. We find that this contrast, between quenched and un-quenched galaxies induces a scale and colour-dependent signature in the present-day near-infrared background comparable to the expected sensitivity of NASA's upcoming SPHEREx mission. Whereas models with pure mass suppression largely affect the signal at wavelengths $\lesssim 2 μ\rm{m}$, $\sim 5$%-level differences in the background persist out to $\sim 5 μ\rm{m}$ for reionization feedback models. Finally, the power spectra of intensity ratio maps exhibit larger variations, and may thus be a promising target for future analyses.

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arXiv2022

Automated Detection of Antenna Malfunctions in Large-N Interferometers: A Case Study with the Hydrogen Epoch of Reionization Array

We present a framework for identifying and flagging malfunctioning antennas in large radio interferometers. We outline two distinct categories of metrics designed to detect outliers along known failure modes of large arrays: cross-correlation metrics, based on all antenna pairs, and auto-correlation metrics, based solely on individual antennas. We define and motivate the statistical framework for all metrics used, and present tailored visualizations that aid us in clearly identifying new and existing systematics. We implement these techniques using data from 105 antennas in the Hydrogen Epoch of Reionization Array (HERA) as a case study. Finally, we provide a detailed algorithm for implementing these metrics as flagging tools on real data sets.

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arXiv2022

Understanding the Impact of Semi-numeric Reionization Models when using CNNs

Interpreting 21cm measurements from current and upcoming experiments like HERA and the SKA will provide new scientific insights and exciting implications for astrophysics and cosmology regarding the Epoch of Reionization (EoR). Several recent works have proposed using machine learning methods, such as convolutions neural networks (CNNs), to analyze images of reionization generated by these experiments since they could take full advantage of information contained in the image. Generally, these studies have used only a single semi-numeric method to generate the input 21cm data. In this work, we investigate the extent to which training CNNs for reionization applications depends on the underlying semi-numeric models. Working in the context of predicting CMB optical depth from 21cm images, we compare networks trained on similar datasets from 21cmfast and zreion, two widely used semi-numeric reionization methods. We show that neural networks trained on input data from only one model produce poor predictions on data from the other model. Satisfactory results are only achieved when both models are included in the training data. This finding has important implications for future analyses on observation data, and encourages the use of multiple models to produce images that capture the full complexity of the EoR.

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arXiv2022

Prospects for kSZ$^2$-Galaxy Cross-Correlations during Reionization

We explore a new approach for extracting reionization-era contributions to the kinetic Sunyaev-Zel'dovich (kSZ) effect. Our method utilizes the cross-power spectrum between filtered and squared maps of the cosmic microwave background (CMB) and photometric galaxy surveys during the Epoch of Reionization (EoR). This kSZ$^2$-galaxy cross-power spectrum statistic has been successfully detected at lower redshifts ($z \lesssim 1.5$). Here we extend this method to $z \gtrsim 6$ as a potential means to extract signatures of patchy reionization. We model the expected signal across multiple photometric redshift bins using semi-numeric simulations of the reionization process. In principle, the cross-correlation statistic robustly extracts reionization-era contributions to the kSZ signal, while its redshift evolution yields valuable information regarding the timing of reionization. Specifically, the model cross-correlation signal near $\ell \sim 1,000$ peaks during the early stages of the EoR, when about 20% of the volume of the universe is ionized. Detectible $\ell$ modes mainly reflect squeezed triangle configurations of the related bispectrum, quantifying correlations between the galaxy overdensity field on large scales and the smaller-scale kSZ power. We forecast the prospects for detecting this signal using future wide-field samples of Lyman-break galaxies from the Roman Space Telescope and next-generation CMB surveys including the Simons Observatory, CMB-S4, and CMB-HD. We find that a roughly 13$σ$ detection is possible for CMB-HD and Roman after summing over all $\ell$ modes. We discuss the possibilities for improving this approach and related statistics, with the aim of moving beyond simple detections to measure the scale and redshift dependence of the cross-correlation signals.

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arXiv2021

A Real Time Processing System for Big Data in Astronomy: Applications to HERA

As current- and next-generation astronomical instruments come online, they will generate an unprecedented deluge of data. Analyzing these data in real time presents unique conceptual and computational challenges, and their long-term storage and archiving is scientifically essential for generating reliable, reproducible results. We present here the real-time processing (RTP) system for the Hydrogen Epoch of Reionization Array (HERA), a radio interferometer endeavoring to provide the first detection of the highly redshifted 21 cm signal from Cosmic Dawn and the Epoch of Reionization by an interferometer. The RTP system consists of analysis routines run on raw data shortly after they are acquired, such as calibration and detection of radio-frequency interference (RFI) events. RTP works closely with the Librarian, the HERA data storage and transfer manager which automatically ingests data and transfers copies to other clusters for post-processing analysis. Both the RTP system and the Librarian are public and open source software, which allows for them to be modified for use in other scientific collaborations. When fully constructed, HERA is projected to generate over 50 terabytes (TB) of data each night, and the RTP system enables the successful scientific analysis of these data.

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arXiv2021

First Results from HERA Phase I: Upper Limits on the Epoch of Reionization 21 cm Power Spectrum

We report upper-limits on the Epoch of Reionization (EoR) 21 cm power spectrum at redshifts 7.9 and 10.4 with 18 nights of data ($\sim36$ hours of integration) from Phase I of the Hydrogen Epoch of Reionization Array (HERA). The Phase I data show evidence for systematics that can be largely suppressed with systematic models down to a dynamic range of $\sim10^9$ with respect to the peak foreground power. This yields a 95% confidence upper limit on the 21 cm power spectrum of $Δ^2_{21} \le (30.76)^2\ {\rm mK}^2$ at $k=0.192\ h\ {\rm Mpc}^{-1}$ at $z=7.9$, and also $Δ^2_{21} \le (95.74)^2\ {\rm mK}^2$ at $k=0.256\ h\ {\rm Mpc}^{-1}$ at $z=10.4$. At $z=7.9$, these limits are the most sensitive to-date by over an order of magnitude. While we find evidence for residual systematics at low line-of-sight Fourier $k_\parallel$ modes, at high $k_\parallel$ modes we find our data to be largely consistent with thermal noise, an indicator that the system could benefit from deeper integrations. The observed systematics could be due to radio frequency interference, cable sub-reflections, or residual instrumental cross-coupling, and warrant further study. This analysis emphasizes algorithms that have minimal inherent signal loss, although we do perform a careful accounting in a companion paper of the small forms of loss or bias associated with the pipeline. Overall, these results are a promising first step in the development of a tuned, instrument-specific analysis pipeline for HERA, particularly as Phase II construction is completed en route to reaching the full sensitivity of the experiment.

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arXiv2021

Effects of model incompleteness on the drift-scan calibration of radio telescopes

Precision calibration poses challenges to experiments probing the redshifted 21-cm signal of neutral hydrogen from the Cosmic Dawn and Epoch of Reionization (z~30-6). In both interferometric and global signal experiments, systematic calibration is the leading source of error. Though many aspects of calibration have been studied, the overlap between the two types of instruments has received less attention. We investigate the sky based calibration of total power measurements with a HERA dish and an EDGES style antenna to understand the role of auto-correlations in the calibration of an interferometer and the role of sky in calibrating a total power instrument. Using simulations we study various scenarios such as time variable gain, incomplete sky calibration model, and primary beam model. We find that temporal gain drifts, sky model incompleteness, and beam inaccuracies cause biases in the receiver gain amplitude and the receiver temperature estimates. In some cases, these biases mix spectral structure between beam and sky resulting in spectrally variable gain errors. Applying the calibration method to the HERA and EDGES data, we find good agreement with calibration via the more standard methods. Although instrumental gains are consistent with beam and sky errors similar in scale to those simulated, the receiver temperatures show significant deviations from expected values. While we show that it is possible to partially mitigate biases due to model inaccuracies by incorporating a time-dependent gain model in calibration, the resulting errors on calibration products are larger and more correlated. Completely addressing these biases will require more accurate sky and primary beam models.

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arXiv2021

The importance of galaxy formation histories in models of reionization

Upcoming galaxy surveys and 21-cm experiments targeting high redshifts $z\gtrsim 6$ are highly complementary probes of galaxy formation and reionization. However, in order to expedite the large volume simulations relevant for 21-cm observations, many models of galaxies within reionization codes are entirely subgrid and/or rely on halo abundances only. In this work, we explore the extent to which resolving and modeling individual galaxy formation histories affects predictions both for the galaxy populations detectable by upcoming surveys and the signatures of reionization accessible to upcoming 21-cm experiments. We find that a common approach, in which galaxy luminosity is assumed to be a function of halo mass only, is biased with respect to models in which galaxy properties are evolved through time via semi-analytic modeling and thus reflective of the diversity of assembly histories that naturally arise in $N$-body simulations. The diversity of galaxy formation histories also results in scenarios in which the brightest galaxies do \textit{not} always reside in the centers of large ionized regions, as there are often relatively low-mass halos undergoing dramatic, but short-term, growth. This has clear implications for attempts to detect or validate the 21-cm background via cross correlation. Finally, we show that a hybrid approach -- in which only halos hosting galaxies bright enough to be detected in surveys are modeled in detail, with the rest modeled as an unresolved field of halos with abundance related to large-scale overdensity -- is a viable way to generate large-volume `simulations` well-suited to wide-area surveys and current-generation 21-cm experiments targeting relatively large $k \lesssim 1 \ h \ \text{Mpc}^{-1}$ scales.

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arXiv2021

Methods of Error Estimation for Delay Power Spectra in $21\,\textrm{cm}$ Cosmology

Precise measurements of the 21 cm power spectrum are crucial for understanding the physical processes of hydrogen reionization. Currently, this probe is being pursued by low-frequency radio interferometer arrays. As these experiments come closer to making a first detection of the signal, error estimation will play an increasingly important role in setting robust measurements. Using the delay power spectrum approach, we have produced a critical examination of different ways that one can estimate error bars on the power spectrum. We do this through a synthesis of analytic work, simulations of toy models, and tests on small amounts of real data. We find that, although computed independently, the different error bar methodologies are in good agreement with each other in the noise-dominated regime of the power spectrum. For our preferred methodology, the predicted probability distribution function is consistent with the empirical noise power distributions from both simulated and real data. This diagnosis is mainly in support of the forthcoming HERA upper limit, and also is expected to be more generally applicable.

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arXiv2021

Validation of the HERA Phase I Epoch of Reionization 21 cm Power Spectrum Software Pipeline

We describe the validation of the HERA Phase I software pipeline by a series of modular tests, building up to an end-to-end simulation. The philosophy of this approach is to validate the software and algorithms used in the Phase I upper limit analysis on wholly synthetic data satisfying the assumptions of that analysis, not addressing whether the actual data meet these assumptions. We discuss the organization of this validation approach, the specific modular tests performed, and the construction of the end-to-end simulations. We explicitly discuss the limitations in scope of the current simulation effort. With mock visibility data generated from a known analytic power spectrum and a wide range of realistic instrumental effects and foregrounds, we demonstrate that the current pipeline produces power spectrum estimates that are consistent with known analytic inputs to within thermal noise levels (at the 2 sigma level) for k > 0.2 h/Mpc for both bands and fields considered. Our input spectrum is intentionally amplified to enable a strong `detection' at k ~0.2 h/Mpc -- at the level of ~25 sigma -- with foregrounds dominating on larger scales, and thermal noise dominating at smaller scales. Our pipeline is able to detect this amplified input signal after suppressing foregrounds with a dynamic range (foreground to noise ratio) of > 10^7. Our validation test suite uncovered several sources of scale-independent signal loss throughout the pipeline, whose amplitude is well-characterized and accounted for in the final estimates. We conclude with a discussion of the steps required for the next round of data analysis.

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arXiv2021

Extracting the Optical Depth to Reionization $τ$ from 21 cm Data Using Machine Learning Techniques

Upcoming measurements of the high-redshift 21 cm signal from the Epoch of Reionization (EoR) are a promising probe of the astrophysics of the first galaxies and of cosmological parameters. In particular, the optical depth $τ$ to the last scattering surface of the cosmic microwave background (CMB) should be tightly constrained by direct measurements of the neutral hydrogen state at high redshift. A robust measurement of $τ$ from 21 cm data would help eliminate it as a nuisance parameter from CMB estimates of cosmological parameters. Previous proposals for extracting $τ$ from future 21 cm datasets have typically used the 21 cm power spectra generated by semi-numerical models to reconstruct the reionization history. We present here a different approach which uses convolution neural networks (CNNs) trained on mock images of the 21 cm EoR signal to extract $τ$. We construct a CNN that improves upon on previously proposed architectures, and perform an automated hyperparameter optimization. We show that well-trained CNNs are able to accurately predict $τ$, even when removing Fourier modes that are expected to be corrupted by bright foreground contamination of the 21 cm signal. Typical random errors for an optimized network are less than $3.06\%$, with biases factors of several smaller. While preliminary, this approach could yield constraints on $τ$ that improve upon sample-variance limited measurements of the low-$\ell$ EE observations of the CMB, making this approach a valuable complement to more traditional methods of inferring $τ$.

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arXiv2021

The Role of Machine Learning in the Next Decade of Cosmology

In recent years, machine learning (ML) methods have remarkably improved how cosmologists can interpret data. The next decade will bring new opportunities for data-driven cosmological discovery, but will also present new challenges for adopting ML methodologies and understanding the results. ML could transform our field, but this transformation will require the astronomy community to both foster and promote interdisciplinary research endeavors.

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arXiv2020

Redundant-Baseline Calibration of the Hydrogen Epoch of Reionization Array

In 21 cm cosmology, precision calibration is key to the separation of the neutral hydrogen signal from very bright but spectrally-smooth astrophysical foregrounds. The Hydrogen Epoch of Reionization Array (HERA), an interferometer specialized for 21 cm cosmology and now under construction in South Africa, was designed to be largely calibrated using the self-consistency of repeated measurements of the same interferometric modes. This technique, known as "redundant-baseline calibration" resolves most of the internal degrees of freedom in the calibration problem. It assumes, however, on antenna elements with identical primary beams placed precisely on a redundant grid. In this work, we review the detailed implementation of the algorithms enabling redundant-baseline calibration and report results with HERA data. We quantify the effects of real-world non-redundancy and how they compare to the idealized scenario in which redundant measurements differ only in their noise realizations. Finally, we study how non-redundancy can produce spurious temporal structure in our calibration solutions--both in data and in simulations--and present strategies for mitigating that structure.

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arXiv2020

DAYENU: A Simple Filter of Smooth Foregrounds for Intensity Mapping Power Spectra

We introduce DAYENU, a linear, spectral filter for HI intensity mapping that achieves the desirable foreground mitigation and error minimization properties of inverse co-variance weighting with minimal modeling of the underlying data. Beyond 21 cm power-spectrum estimation, our filter is suitable for any analysis where high dynamic-range removal of spectrally smooth foregrounds in irregularly (or regularly) sampled data is required, something required by many other intensity mapping techniques. Our filtering matrix is diagonalized by Discrete Prolate Spheroidal Sequences which are an optimal basis to model band-limited foregrounds in 21 cm intensity mapping experiments in the sense that they maximally concentrate power within a finite region of Fourier space. We show that DAYENU enables the access of large-scale line-of-sight modes that are inaccessible to tapered DFT estimators. Since these modes have the largest SNRs, DAYENU significantly increases the sensitivity of 21 cm analyses over tapered Fourier transforms. Slight modifications allow us to use DAYENU as a linear replacement for iterative delay CLEANing (DAYENUREST). We refer readers to the Code section at the end of this paper for links to examples and code.

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arXiv2020

Developing a Real Time Processing System for HERA

The Hydrogen Epoch of Reionization Array (HERA) is a radio telescope in the Karoo desert of South Africa endeavoring to observe Cosmic Dawn and the Epoch of Reionization. When fully constructed, it will consist of 350 antennas and generate over 60 terabytes (TB) of data each night. In order to keep pace with the relatively large rate of data, we have developed the real-time processing (RTP) system for HERA. The RTP is responsible for inspecting data for acceptable levels of quality and flagging unusable data, as well as providing an initial calibration solution. The RTP system consists of the pipeline management system, called the hera_opm package, and the data management system, called the librarian. Though the systems have been developed in the context of analyzing HERA data, they feature public and open source software, and have been designed to be adapted and used in other contexts as necessary.

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