arXiv subjects

Moritz Münchmeyer

Publications and source records attributed to Moritz Münchmeyer.

At least 37 records · Page 2Linked to original sources

arXiv2023

Inferring the Energy and Distance Distributions of Fast Radio Bursts using the First CHIME/FRB Catalog

Fast radio bursts (FRBs) are brief, energetic, extragalactic flashes of radio emission whose progenitors are largely unknown. Although studying the FRB population is essential for understanding how these astrophysical phenomena occur, such studies have been difficult to conduct without large numbers of FRBs and characterizable observational biases. Using the recently released catalog of 536 FRBs published by the Canadian Hydrogen Intensity Mapping Experiment/Fast Radio Burst (CHIME/FRB) collaboration, we present a study of the FRB population that also calibrates for selection effects. Assuming a Schechter luminosity function, we infer a characteristic energy cut-off of $E_\mathrm{char} =$ $2.38^{+5.35}_{-1.64} \times 10^{41}$ erg and a differential power-law index of $γ=$ $-1.3^{+0.7}_{-0.4}$. Simultaneously, we infer a volumetric rate of [$7.3^{+8.8}_{-3.8}$(stat.)$^{+2.0}_{-1.8}$(sys.)]$\times 10^4$ Gpc$^{-3}$ year$^{-1}$ above a pivot energy of 10$^{39}$ erg and below a scattering timescale of 10 ms at 600 MHz, and find we cannot significantly constrain the cosmic evolution of the FRB population with star formation rate. Modeling the host dispersion measure (DM) contribution as a log-normal distribution and assuming a total Galactic contribution of 80 pc cm$^{-3}$, we find a median value of $\mathrm{DM}_\mathrm{host} =$ $84^{+69}_{-49}$ pc cm$^{-3}$, comparable with values typically used in the literature. Proposed models for FRB progenitors should be consistent with the energetics and abundances of the full FRB population predicted by our results. Finally, we infer the redshift distribution of FRBs detected with CHIME, which will be tested with the localizations and redshifts enabled by the upcoming CHIME/FRB Outriggers project.

astro-ph.HE↗

arXiv2023

Probing Cosmological Particle Production and Pairwise Hotspots with Deep Neural Networks

Particles with masses much larger than the inflationary Hubble scale, $H_I$, can be pair-produced non-adiabatically during inflation. Due to their large masses, the produced particles modify the curvature perturbation around their locations. These localized perturbations eventually give rise to localized signatures on the Cosmic Microwave Background (CMB), in particular, pairwise hotspots (PHS). In this work, we show that Convolutional Neural Networks (CNN) provide a powerful tool for identifying PHS on the CMB. While for a given hotspot profile a traditional Matched Filter Analysis is known to be optimal, a Neural Network learns to effectively detect the large variety of shapes that can arise in realistic models of particle production. Considering an idealized situation where the dominant background to the PHS signal comes from the standard CMB fluctuations, we show that a CNN can isolate the PHS with $\mathcal{O}(10)\%$ efficiency even if the hotspot temperature is $\mathcal{O}(10)$ times smaller than the average CMB fluctuations. Overall, the CNN search is sensitive to heavy particle masses $M_0/H_I=\mathcal{O}(200)$, and constitutes one of the unique probes of very high energy particle physics.

hep-ph↗

arXiv2023

The First CHIME/FRB Fast Radio Burst Catalog

We present a catalog of 536 fast radio bursts (FRBs) detected by the Canadian Hydrogen Intensity Mapping Experiment Fast Radio Burst (CHIME/FRB) Project between 400 and 800 MHz from 2018 July 25 to 2019 July 1, including 62 bursts from 18 previously reported repeating sources. The catalog represents the first large sample, including bursts from repeaters and non-repeaters, observed in a single survey with uniform selection effects. This facilitates comparative and absolute studies of the FRB population. We show that repeaters and apparent non-repeaters have sky locations and dispersion measures (DMs) that are consistent with being drawn from the same distribution. However, bursts from repeating sources differ from apparent non-repeaters in intrinsic temporal width and spectral bandwidth. Through injection of simulated events into our detection pipeline, we perform an absolute calibration of selection effects to account for systematic biases. We find evidence for a population of FRBs - comprising a large fraction of the overall population - with a scattering time at 600 MHz in excess of 10 ms, of which only a small fraction are observed by CHIME/FRB. We infer a power-law index for the cumulative fluence distribution of $α=-1.40\pm0.11(\textrm{stat.})^{+0.06}_{-0.09}(\textrm{sys.})$, consistent with the $-3/2$ expectation for a non-evolving population in Euclidean space. We find $α$ is steeper for high-DM events and shallower for low-DM events, which is what would be expected when DM is correlated with distance. We infer a sky rate of $[525\pm30(\textrm{stat.})^{+140}_{-130}({\textrm{sys.}})]/\textrm{sky}/\textrm{day}$ above a fluence of 5 Jy ms at 600 MHz, with scattering time at $600$ MHz under 10 ms, and DM above 100 pc cm$^{-3}$.

astro-ph.HE↗

arXiv2022

De-noising non-Gaussian fields in cosmology with normalizing flows

Fields in cosmology, such as the matter distribution, are observed by experiments up to experimental noise. The first step in cosmological data analysis is usually to de-noise the observed field using an analytic or simulation driven prior. On large enough scales, such fields are Gaussian, and the de-noising step is known as Wiener filtering. However, on smaller scales probed by upcoming experiments, a Gaussian prior is substantially sub-optimal because the true field distribution is very non-Gaussian. Using normalizing flows, it is possible to learn the non-Gaussian prior from simulations (or from more high-resolution observations), and use this knowledge to de-noise the data more effectively. We show that we can train a flow to represent the matter distribution of the universe, and evaluate how much signal-to-noise can be gained as a function of the experimental noise under idealized conditions. We also introduce a patching method to reconstruct fields on arbitrarily large images by dividing them up into small maps (where we reconstruct non-Gaussian features), and patching the small posterior maps together on large scales (where the field is Gaussian).

astro-ph.CO↗

arXiv2022

Snowmass Theory Frontier: Astrophysics and Cosmology

We summarize progress made in theoretical astrophysics and cosmology over the past decade and areas of interest for the coming decade. This Report is prepared as the TF09 "Astrophysics and Cosmology" topical group summary for the Theory Frontier as part of the Snowmass 2021 process.

hep-ph↗

arXiv2022

An Injection System for the CHIME/FRB Experiment

Dedicated surveys searching for Fast Radio Bursts (FRBs) are subject to selection effects which bias the observed population of events. Software injection systems are one method of correcting for these biases by injecting a mock population of synthetic FRBs directly into the realtime search pipeline. The injected population may then be used to map intrinsic burst properties onto an expected signal-to-noise ratio (SNR), so long as telescope characteristics such as the beam model and calibration factors are properly accounted for. This paper presents an injection system developed for the Canadian Hydrogen Intensity Mapping Experiment Fast Radio Burst project (CHIME/FRB). The system was tested to ensure high detection efficiency, and the pulse calibration method was verified. Using an injection population of ~85,000 synthetic FRBs, we found that the correlation between fluence and SNR for injected FRBs was consistent with that of CHIME/FRB detections in the first CHIME/FRB catalog. We also noted that the sensitivity of the telescope varied strongly as a function of the broadened burst width, but not as a function of the dispersion measure. We conclude that some of the machine-learning based Radio Frequency Interference (RFI) mitigation methods used by CHIME/FRB can be re-trained using injection data to increase sensitivity to wide events, and that planned upgrades to the presented injection system will allow for determining a more accurate CHIME/FRB selection function in the near future.

astro-ph.IM↗

arXiv2022

Robust Neural Network-Enhanced Estimation of Local Primordial Non-Gaussianity

When applied to the non-linear matter distribution of the universe, neural networks have been shown to be very statistically sensitive probes of cosmological parameters, such as the linear perturbation amplitude $σ_8$. However, when used as a "black box", neural networks are not robust to baryonic uncertainty. We propose a robust architecture for constraining primordial non-Gaussianity $f_{NL}$, by training a neural network to locally estimate $σ_8$, and correlating these local estimates with the large-scale density field. We apply our method to N-body simulations, and show that $σ(f_{NL})$ is 3.5 times better than the constraint obtained from a standard halo-based approach. We show that our method has the same robustness property as large-scale halo bias: baryonic physics can change the normalization of the estimated $f_{NL}$, but cannot change whether $f_{NL}$ is detected.

astro-ph.CO↗

arXiv2022

Snowmass2021 Cosmic Frontier: Cosmic Microwave Background Measurements White Paper

This is a solicited whitepaper for the Snowmass 2021 community planning exercise. The paper focuses on measurements and science with the Cosmic Microwave Background (CMB). The CMB is foundational to our understanding of modern physics and continues to be a powerful tool driving our understanding of cosmology and particle physics. In this paper, we outline the broad and unique impact of CMB science for the High Energy Cosmic Frontier in the upcoming decade. We also describe the progression of ground-based CMB experiments, which shows that the community is prepared to develop the key capabilities and facilities needed to achieve these transformative CMB measurements.

astro-ph.CO↗

arXiv2021

CHIME/FRB Catalog 1 results: statistical cross-correlations with large-scale structure

The CHIME/FRB Project has recently released its first catalog of fast radio bursts (FRBs), containing 492 unique sources. We present results from angular cross-correlations of CHIME/FRB sources with galaxy catalogs. We find a statistically significant ($p$-value $\sim 10^{-4}$, accounting for look-elsewhere factors) cross-correlation between CHIME FRBs and galaxies in the redshift range $0.3 \lesssim z \lesssim 0.5$, in three photometric galaxy surveys: WISE$\times$SCOS, DESI-BGS, and DESI-LRG. The level of cross-correlation is consistent with an order-one fraction of the CHIME FRBs being in the same dark matter halos as survey galaxies in this redshift range. We find statistical evidence for a population of FRBs with large host dispersion measure ($\sim 400$ pc cm$^{-3}$), and show that this can plausibly arise from gas in large halos ($M \sim 10^{14} M_\odot$), for FRBs near the halo center ($r \lesssim 100$ kpc). These results will improve in future CHIME/FRB catalogs, with more FRBs and better angular resolution.

astro-ph.CO↗

arXiv2021

Normalizing flows for random fields in cosmology

Normalizing flows are a powerful tool to create flexible probability distributions with a wide range of potential applications in cosmology. Here we are studying normalizing flows which represent cosmological observables at field level, rather than at the level of summary statistics such as the power spectrum. We evaluate the performance of different normalizing flows for both density estimation and sampling of near-Gaussian random fields, and check the quality of samples with different statistics such as power spectrum and bispectrum estimators. We explore aspects of these flows that are specific to cosmology, such as flowing from a physical prior distribution and evaluating the density estimation results in the analytically tractable correlated Gaussian case.

astro-ph.CO↗

arXiv2020

NDRIO White Paper: Envisioning Digital Research Infrastructure for the Simons Observatory

Observations of the cosmic microwave background (CMB) are an incredibly fertile source of information for studying the origins and evolution of the Universe. Canadian digital research infrastructure (DRI) has played a key role in reducing ever-larger quantities of raw data into maps of the CMB suitable for scientific analysis, as exemplified by the many scientific results produced by the Atacama Cosmology Telescope (ACT) over the past decade. The Simons Observatory (SO), due to start observing in 2023, will be able to measure the CMB with about an order of magnitude more sensitivity than ACT and other current telescopes. In this White Paper we outline how Canadian DRI under the New Digital Research Infrastructure Organization (NDRIO) could build upon the legacy of ACT and play a pivotal role in processing SO data, helping to produce data products that will be central to the cosmology community for years to come. We include estimates of DRI resources required for this work to indicate what kind of advanced research computing (ARC) would best support an SO-like project. Finally, we comment on how ARC allocations could be structured for large collaborations like SO and propose a research data management (RDM) system that makes public data releases available not only for download but also for direct analysis on Canadian DRI.

astro-ph.IM↗

arXiv2020

CMB-HD: Astro2020 RFI Response

CMB-HD is a proposed ultra-deep (0.5 uk-arcmin), high-resolution (15 arcseconds) millimeter-wave survey over half the sky that would answer many outstanding questions in both fundamental physics of the Universe and astrophysics. This survey would be delivered in 7.5 years of observing 20,000 square degrees, using two new 30-meter-class off-axis cross-Dragone telescopes to be located at Cerro Toco in the Atacama Desert. Each telescope would field 800,000 detectors (200,000 pixels), for a total of 1.6 million detectors.

astro-ph.CO↗

arXiv2019

Higher N-point function data analysis techniques for heavy particle production and WMAP results

We explore data analysis techniques for signatures from heavy particle production during inflation. Heavy particules can be produced by time dependent masses and couplings, which are ubiquitous in string theory. These localized excitations induce curvature perturbations with non-zero correlation functions at all orders. In particular, Flauger et. al. 2016 has shown that the signal-to-noise as a function of the order $N$ of the correlation function can peak for $N$ of order $\mathcal{O}(1)$ to $\mathcal{O}(100)$ for an interesting space of models. As previous non-Gaussianity analyses have focused on $N=\{3,4\}$, in principle this provides an unexplored data analysis window with new discovery potential. We derive estimators for arbitrary $N$-point functions in this model and discuss their properties and covariances. To lowest order, the heavy particle production phenomenology reduces to a classical Poisson process, which can be implemented as a search for spherically symmetric profiles in the curvature perturbations. We explicitly show how to recover this result from the $N$-point functions and their estimators. Our focus in this paper is on method development, but we provide an initial data analysis using WMAP data, which illustrates the particularities of higher $N$-point function searches.

astro-ph.CO↗

arXiv2019

Inflation and Early Dark Energy with a Stage II Hydrogen Intensity Mapping Experiment

This white paper envisions a revolutionary post-DESI, post-LSST dark energy program based on intensity mapping of the redshifted 21cm emission line from neutral hydrogen at radio frequencies. The proposed intensity mapping survey has the unique capability to quadruple the volume of the Universe surveyed by optical programs, provide a percent-level measurement of the expansion history to $z \sim 6$, open a window to explore physics beyond the concordance $Λ$CDM model, and to significantly improve the precision on standard cosmological parameters. In addition, characterization of dark energy and new physics will be powerfully enhanced by cross-correlations with optical surveys and cosmic microwave background measurements. The rich dataset obtained by the proposed intensity mapping instrument will be simultaneously useful in exploring the time-domain physics of fast radio transients and pulsars, potentially in live "multi-messenger" coincidence with other observatories. The core dark energy/inflation science advances enabled by this program are the following: (i) Measure the expansion history of the universe over $z=0.3-6$ with a single instrument, extending the range deep into the pre-acceleration era, providing an unexplored window for new physics; (ii) Measure the growth rate of structure in the universe over the same redshift range; (iii) Observe, or constrain, the presence of inflationary relics in the primordial power spectrum, improving existing constraints by an order of magnitude; (iv) Observe, or constrain, primordial non-Gaussianity with unprecedented precision, improving constraints on several key numbers by an order of magnitude. Detailed mapping of the enormous, and still largely unexplored, volume of cosmic space will thus provide unprecedented information on fundamental questions of the vacuum energy and early-universe physics.

astro-ph.CO↗

arXiv2019

Packed Ultra-wideband Mapping Array (PUMA): A Radio Telescope for Cosmology and Transients

PUMA is a proposal for an ultra-wideband, low-resolution and transit interferometric radio telescope operating at $200-1100\,\mathrm{MHz}$. Its design is driven by six science goals which span three science themes: the physics of dark energy (measuring the expansion history and growth of the universe up to $z=6$), the physics of inflation (constraining primordial non-Gaussianity and primordial features) and the transient radio sky (detecting one million fast radio bursts and following up SKA-discovered pulsars). We propose two array configurations composed of hexagonally close-packed 6m dish arrangements with 50% fill factor. The initial 5,000 element 'petite array' is scientifically compelling, and can act as a demonstrator and a stepping stone to the full 32,000 element 'full array'. Viewed as a 21cm intensity mapping telescope, the program has the noise equivalent of a traditional spectroscopic galaxy survey comprised of 0.6 and 2.5 billion galaxies at a comoving wavenumber of $k=0.5\,h\mathrm{Mpc}^{-1}$ spanning the redshift range $z = 0.3 - 6$ for the petite and full configurations, respectively. At redshifts beyond $z=2$, the 21cm technique is a uniquely powerful way of mapping the universe, while the low-redshift range will allow for numerous cross-correlations with existing and upcoming surveys. This program is enabled by the development of ultra-wideband radio feeds, cost-effective dish construction methods, commodity radio-frequency electronics driven by the telecommunication industry and the emergence of sufficient computing power to facilitate real-time signal processing that exploits the full potential of massive radio arrays. The project has an estimated construction cost of 55 and 330 million FY19 USD for the petite and full array configurations. Including R&D, design, operations and science analysis, the cost rises to 125 and 600 million FY19 USD, respectively.

astro-ph.IM↗

arXiv2019

Research and Development for HI Intensity Mapping

Development of the hardware, data analysis, and simulation techniques for large compact radio arrays dedicated to mapping the 21 cm line of neutral hydrogen gas has proven to be more difficult than imagined twenty years ago when such telescopes were first proposed. Despite tremendous technical and methodological advances, there are several outstanding questions on how to optimally calibrate and analyze such data. On the positive side, it has become clear that the outstanding issues are purely technical in nature and can be solved with sufficient development activity. Such activity will enable science across redshifts, from early galaxy evolution in the pre-reionization era to dark energy evolution at low redshift.

astro-ph.IM↗

arXiv2019

Fast Wiener filtering of CMB maps with Neural Networks

We show how a neural network can be trained to Wiener filter masked CMB maps to high accuracy. We propose an innovative neural network architecture, the WienerNet, which guarantees linearity in the data map. Our method does not require Wiener filtered training data, but rather learns Wiener filtering from tailored loss functions which are mathematically guaranteed to be minimized by the exact solution. Once trained, the neural network Wiener filter is extremely fast, about a factor of 1000 faster than the standard conjugate gradient method. Wiener filtering is the computational bottleneck in many optimal CMB analyses, including power spectrum estimation, lensing and non-Gaussianities, and our method could potentially be used to speed them up by orders of magnitude with minimal loss of optimality. The method should also be useful to analyze other statistical fields in cosmology.

astro-ph.CO↗

arXiv2018

Transverse Velocities with the Moving Lens Effect

Gravitational potentials which change in time induce fluctuations in the observed cosmic microwave background (CMB) temperature. Cosmological structure moving transverse to our line of sight provides a specific example known as the moving lens effect. Here we explore how the observed CMB temperature fluctuations combined with the observed matter over-density can be used to infer the transverse velocity of cosmological structure on large scales. We show that near-future CMB surveys and galaxy surveys will have the statistical power to make a first detection of the moving lens effect, and we discuss applications for the reconstructed transverse velocity.

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