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Giulio Fabbian

Publications and source records attributed to Giulio Fabbian.

At least 37 records · Page 2Linked to original sources

Quaia, the Gaia-unWISE Quasar Catalog: An All-Sky Spectroscopic Quasar Sample

We present a new, all-sky quasar catalog, Quaia, that samples the largest comoving volume of any existing spectroscopic quasar sample. The catalog draws on the 6,649,162 quasar candidates identified by the Gaia mission that have redshift estimates from the space observatory's low-resolution BP/RP spectra. This initial sample is highly homogeneous and complete, but has low purity, and 18% of even the bright ($G<20.0$) confirmed quasars have discrepant redshift estimates ($|Δz/(1+z)|>0.2$) compared to those from the Sloan Digital Sky Survey (SDSS). In this work, we combine the Gaia candidates with unWISE infrared data (based on the Wide-field Infrared Survey Explorer survey) to construct a catalog useful for cosmological and astrophysical quasar studies. We apply cuts based on proper motions and Gaia and unWISE colors, reducing the number of contaminants by $\sim$4$\times$. We improve the redshifts by training a $k$-nearest neighbors model on SDSS redshifts, and achieve estimates on the $G<20.0$ sample with only 6% (10%) catastrophic errors with $|Δz/(1+z)|>0.2$ ($0.1$), a reduction of $\sim$3$\times$ ($\sim$2$\times$) compared to the Gaia redshifts. The final catalog has 1,295,502 quasars with $G<20.5$, and 755,850 candidates in an even cleaner $G<20.0$ sample, with accompanying rigorous selection function models. We compare Quaia to existing quasar catalogs, showing that its large effective volume makes it a highly competitive sample for cosmological large-scale structure analyses. The catalog is publicly available at https://zenodo.org/records/10403370.

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CMB lensing reconstruction biases from masking extragalactic sources

Observed Cosmic Microwave Background (CMB) maps are contaminated by foregrounds, some of which are usually masked to perform cosmological analyses. If masks are correlated to the lensing signal, such as those removing extragalactic emissions located in matter overdensities, measurements over the unmasked sky may give biased estimates. We quantify the impact of these mask-induced biases for the reconstructed CMB lensing auto- and cross-correlation power spectra with external matter tracers. We show that they arise both from changes in the lensing power, and via modifications to the reconstruction power spectrum corrections, $N_L^{(0)}$, $N_L^{(1)}$ and $N_L^{(3/2)}$). For direct masking of the CMB lensing field, we derive simple analytic models of the masking effect and show that it is potentially large. We show that mask-induced biases are significantly reduced by optimal filtering of the CMB maps in the lensing reconstruction. We test the resulting lensing power spectrum biases on numerical simulations, masking radio sources, and peaks of thermal Sunyaev-Zeldovich (tSZ) and cosmic infrared background (CIB) emission. For the lensing auto spectrum, masking biases can only be measured with a statistical significance $\lesssim 3σ$ for future data sets. The same applies to the cross-correlation power spectra between CMB lensing and tSZ and CIB even though biases are larger (up to ~30%). We find that masking tSZ-selected galaxy clusters leads to the largest mask biases, potentially detectable with high significance. We find that the calibration of cluster masses using CMB lensing, in particular for objects at $z\lesssim 0.6$, might be significantly affected by mask biases for near-future observations if the lensing signal recovered inside the mask holes is used without further corrections. Conversely, mass calibration of high redshift objects will still deliver unbiased results.

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Constraints on axion-like polarization oscillations in the cosmic microwave background with POLARBEAR

Very light pseudoscalar fields, often referred to as axions, are compelling dark matter candidates and can potentially be detected through their coupling to the electromagnetic field. Recently a novel detection technique using the cosmic microwave background (CMB) was proposed, which relies on the fact that the axion field oscillates at a frequency equal to its mass in appropriate units, leading to a time-dependent birefringence. For appropriate oscillation periods this allows the axion field at the telescope to be detected via the induced sinusoidal oscillation of the CMB linear polarization. We search for this effect in two years of POLARBEAR data. We do not detect a signal, and place a median $95 \%$ upper limit of $0.65 ^\circ$ on the sinusoid amplitude for oscillation frequencies between $0.02\,\text{days}^{-1}$ and $0.45\,\text{days}^{-1}$, which corresponds to axion masses between $9.6 \times 10^{-22} \, \text{eV}$ and $2.2\times 10^{-20} \,\text{eV}$. Under the assumptions that 1) the axion constitutes all the dark matter and 2) the axion field amplitude is a Rayleigh-distributed stochastic variable, this translates to a limit on the axion-photon coupling $g_{ϕγ} < 2.4 \times 10^{-11} \,\text{GeV}^{-1} \times ({m_ϕ}/{10^{-21} \, \text{eV}})$.

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A Hierarchy of Normalizing Flows for Modelling the Galaxy-Halo Relationship

Using a large sample of galaxies taken from the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project, a suite of hydrodynamic simulations varying both cosmological and astrophysical parameters, we train a normalizing flow (NF) to map the probability of various galaxy and halo properties conditioned on astrophysical and cosmological parameters. By leveraging the learnt conditional relationships we can explore a wide range of interesting questions, whilst enabling simple marginalisation over nuisance parameters. We demonstrate how the model can be used as a generative model for arbitrary values of our conditional parameters; we generate halo masses and matched galaxy properties, and produce realisations of the halo mass function as well as a number of galaxy scaling relations and distribution functions. The model represents a unique and flexible approach to modelling the galaxy-halo relationship.

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CMB lensing reconstruction biases in cross-correlation with large-scale structure probes

The cross-correlation between cosmic microwave background (CMB) gravitational lensing and large-scale structure tracers will be an important cosmological probe in the coming years. Quadratic estimators provide a simple and powerful (if suboptimal) way to reconstruct the CMB lensing potential and are widely used. For Gaussian fields, the cross-correlation of a quadratic-estimator CMB lensing reconstruction with a tracer is exactly unbiased if the power spectra are known and consistent analytic lensing mode response functions are used. However, the bispectrum induced by non-linear large-scale structure growth and post-Born lensing can introduce an additional bias term ($N_L^{(3/2)}$) in the cross-correlation spectrum, similar to the $N_L^{(3/2)}$ bias in the auto-spectrum demonstrated in recent works. We give analytic flat-sky results for the cross-correlation bias using approximate models for the post-Born and large-scale structure cross-bispectra, and compare with N-body simulation results using ray-tracing techniques. We show that the bias can be at the 5-15\% level in all large-scale structure cross-correlations using small-scale CMB temperature lensing reconstruction, but is substantially reduced using polarization-based lensing estimators or simple foreground-projected temperature estimators. The relative magnitude of these effects is almost three times higher than in the CMB lensing auto-correlation, but is small enough that it can be modelled to sufficient precision using simple analytic models. We show that $N_L^{(3/2)}$ effects in cross-correlation will be detected with high significance when using data of future surveys and could affect systematic effects marginalization in cosmic shear measurements mimicking galaxy intrinsic alignment.

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Constraining cosmology with the Gaia-unWISE Quasar Catalog and CMB lensing: structure growth

We study the angular clustering of Quaia, a Gaia- and unWISE-based catalog of over a million quasars with an exceptionally well-defined selection function. With it, we derive cosmology constraints from the amplitude and growth of structure across cosmic time. We divide the sample into two redshift bins, centered at $z=1.0$ and $z=2.1$, and measure both overdensity auto-correlations and cross-correlations with maps of the Cosmic Microwave Background convergence measured by Planck. From these data, and including a prior from measurements of the baryon acoustic oscillations scale, we place constraints on the amplitude of the matter power spectrum $σ_8=0.766\pm 0.034$, and on the matter density parameter $Ω_m=0.343^{+0.017}_{-0.019}$. These measurements are in reasonable agreement with \planck at the $\sim$ 1.4$σ$ level, and are found to be robust with respect to observational and theoretical uncertainties. We find that our slightly lower value of $σ_8$ is driven by the higher-redshift sample, which favours a low amplitude of matter fluctuations. We present plausible arguments showing that this could be driven by contamination of the CMB lensing map by high-redshift extragalactic foregrounds, which should also affect other cross-correlations with tracers of large-scale structure beyond $z\sim1.5$. Our constraints are competitive with those from state-of-the-art 3$\times$2-point analyses, but arise from a range of scales and redshifts that is highly complementary to those covered by cosmic shear data and most galaxy clustering samples. This, coupled with the unprecedented combination of volume and redshift precision achieved by Quaia allows us to break the usual degeneracy between $Ω_m$ and $σ_8$.

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A machine learning approach to mapping baryons onto dark matter haloes using the EAGLE and C-EAGLE simulations

High-resolution cosmological hydrodynamic simulations are currently limited to relatively small volumes due to their computational expense. However, much larger volumes are required to probe rare, overdense environments, and measure clustering statistics of the large scale structure. Typically, zoom simulations of individual regions are used to study rare environments, and semi-analytic models and halo occupation models applied to dark matter only (DMO) simulations are used to study the Universe in the large-volume regime. We propose a new approach, using a machine learning framework to explore the halo-galaxy relationship in the periodic EAGLE simulations, and zoom C-EAGLE simulations of galaxy clusters. We train a tree based machine learning method to predict the baryonic properties of galaxies based on their host dark matter halo properties. The trained model successfully reproduces a number of key distribution functions for an infinitesimal fraction of the computational cost of a full hydrodynamic simulation. By training on both periodic simulations as well as zooms of overdense environments, we learn the bias of galaxy evolution in differing environments. This allows us to apply the trained model to a larger DMO volume than would be possible if we only trained on a periodic simulation. We demonstrate this application using the $(800 \; \mathrm{Mpc})^3$ P-Millennium simulation, and present predictions for key baryonic distribution functions and clustering statistics from the EAGLE model in this large volume.

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DEMNUni: The imprint of massive neutrinos on the cross-correlation between cosmic voids and CMB lensing

Cosmic voids are a powerful probe of cosmology and are one of the core observables of upcoming galaxy surveys. The cross-correlations between voids and other large-scale structure tracers such as galaxy clustering and galaxy lensing have been shown to be very sensitive probes of cosmology and among the most promising to probe the nature of gravity and the neutrino mass. However, recent measurements of the void imprint on the lensed Cosmic Microwave Background (CMB) have been shown to be in tension with expectations based on LCDM simulations, hinting to a possibility of non-standard cosmological signatures due to massive neutrinos. In this work we use the DEMNUni cosmological simulations with massive neutrino cosmologies to study the neutrino impact on voids selected in photometric surveys, e.g. via Luminous Red Galaxies, as well as on the void- CMB lensing cross-correlation. We show how the void properties observed in this way (size function, profiles) are affected by the presence of massive neutrinos compared to the neutrino massless case, and show how these can vary as a function of the selection method of the void sample. We comment on the possibility for massive neutrinos to be the source of the aforementioned tension. Finally, we identify the most promising setup to detect signatures of massive neutrinos in the voids-CMB lensing cross-correlation and define a new quantity useful to distinguish among different neutrino masses by comparing future observations against predictions from simulations including massive neutrinos.

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CMB-S4: Forecasting Constraints on $f_\mathrm{NL}$ Through $μ$-distortion Anisotropy

Diffusion damping of the cosmic microwave background (CMB) power spectrum results from imperfect photon-baryon coupling in the pre-recombination plasma. At redshift $5 \times 10^4 < z < 2 \times 10^6$, the plasma acquires an effective chemical potential, and energy injections from acoustic damping in this era create $μ$-type spectral distortions of the CMB. These $μ$ distortions trace the underlying photon density fluctuations, probing the primordial power spectrum in short-wavelength modes $k_\mathrm{S}$ over the range $50 \ \mathrm{Mpc}^{-1} \lesssim k \lesssim 10^4 \ \mathrm{Mpc}^{-1}$. Small-scale power modulated by long-wavelength modes $k_\mathrm{L}$ from squeezed-limit non-Gaussianities introduces cross-correlations between CMB temperature anisotropies and $μ$ distortions. Under single-field inflation models, $μ\times T$ correlations measured from an observer in an inertial frame should vanish up to a factor of $(k_\mathrm{L}/k_\mathrm{S})^2 \ll 1$. Thus, any measurable correlation rules out single-field inflation models. We forecast how well the next-generation ground-based CMB experiment CMB-S4 will be able to constrain primordial squeezed-limit non-Gaussianity, parameterized by $f_\mathrm{NL}$, using measurements of $C_{\ell}^{μT}$ as well as $C_{\ell}^{μE}$ from CMB $E$ modes. Using current experimental specifications and foreground modeling, we expect $σ(f_\mathrm{NL}) \lesssim 1000$. This is roughly four times better than the current limit on $f_\mathrm{NL}$ using $μ\times T$ and $μ\times E$ correlations from Planck and is comparable to what is achievable with LiteBIRD, demonstrating the power of the CMB-S4 experiment. This measurement is at an effective scale of $k \simeq 740 \ \text{Mpc}^{-1}$ and is thus highly complementary to measurements at larger scales from primary CMB and large-scale structure.

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Planck ISW-lensing likelihood and the CMB temperature

We present a new Planck CMB lensing-CMB temperature cross-correlation likelihood that can be used to constrain cosmology via the Integrated Sachs-Wolfe (ISW) effect. CMB lensing is an excellent tracer of ISW, and we use the latest PR4 Planck data maps and lensing reconstruction to produce the first public Planck likelihood to constrain this signal. We demonstrate the likelihood by constraining the CMB background temperature from Planck data alone, where the ISW-lensing cross-correlation is a powerful way to break the geometric degeneracy, substantially improving constraints from the CMB and lensing power spectra alone.

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From Data to Software to Science with the Rubin Observatory LSST

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) dataset will dramatically alter our understanding of the Universe, from the origins of the Solar System to the nature of dark matter and dark energy. Much of this research will depend on the existence of robust, tested, and scalable algorithms, software, and services. Identifying and developing such tools ahead of time has the potential to significantly accelerate the delivery of early science from LSST. Developing these collaboratively, and making them broadly available, can enable more inclusive and equitable collaboration on LSST science. To facilitate such opportunities, a community workshop entitled "From Data to Software to Science with the Rubin Observatory LSST" was organized by the LSST Interdisciplinary Network for Collaboration and Computing (LINCC) and partners, and held at the Flatiron Institute in New York, March 28-30th 2022. The workshop included over 50 in-person attendees invited from over 300 applications. It identified seven key software areas of need: (i) scalable cross-matching and distributed joining of catalogs, (ii) robust photometric redshift determination, (iii) software for determination of selection functions, (iv) frameworks for scalable time-series analyses, (v) services for image access and reprocessing at scale, (vi) object image access (cutouts) and analysis at scale, and (vii) scalable job execution systems. This white paper summarizes the discussions of this workshop. It considers the motivating science use cases, identified cross-cutting algorithms, software, and services, their high-level technical specifications, and the principles of inclusive collaborations needed to develop them. We provide it as a useful roadmap of needs, as well as to spur action and collaboration between groups and individuals looking to develop reusable software for early LSST science.

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The Simons Observatory: Constraining inflationary gravitational waves with multi-tracer B-mode delensing

We introduce and validate a delensing framework for the Simons Observatory (SO), which will be used to improve constraints on inflationary gravitational waves (IGWs) by reducing the lensing noise in measurements of the $B$-modes in CMB polarization. SO will initially observe CMB by using three small aperture telescopes and one large-aperture telescope. While polarization maps from small-aperture telescopes will be used to constrain IGWs, the internal CMB lensing maps used to delens will be reconstructed from data from the large-aperture telescope. Since lensing maps obtained from the SO data will be noise-dominated on sub-degree scales, the SO lensing framework constructs a template for lensing-induced $B$-modes by combining internal CMB lensing maps with maps of the cosmic infrared background from Planck as well as galaxy density maps from the LSST survey. We construct a likelihood for constraining the tensor-to-scalar ratio $r$ that contains auto- and cross-spectra between observed $B$-modes and the lensing $B$-mode template. We test our delensing analysis pipeline on map-based simulations containing survey non-idealities, but that, for this initial exploration, does not include contamination from Galactic and extragalactic foregrounds. We find that the SO survey masking and inhomogeneous and atmospheric noise have very little impact on the delensing performance, and the $r$ constraint becomes $σ(r)\approx 0.0015$ which is close to that obtained from the idealized forecasts in the absence of the Galactic foreground and is nearly a factor of two tighter than without delensing. We also find that uncertainties in the external large-scale structure tracers used in our multi-tracer delensing pipeline lead to bias much smaller than the $1\,σ$ statistical uncertainties.

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CMB spectral distortions revisited: a new take on $μ$ distortions and primordial non-Gaussianities from FIRAS data

Deviations from the blackbody spectral energy distribution of the CMB are a precise probe of physical processes active both in the early universe (such as those connected to particle decays and inflation) and at later times (e.g. reionization and astrophysical emissions). Limited progress has been made in the characterization of these spectral distortions after the pioneering measurements of the FIRAS instrument on the COBE satellite in the early 1990s, which mainly targeted the measurement of their average amplitude across the sky. Since at present no follow-up mission is scheduled to update the FIRAS measurement, in this work we re-analyze the FIRAS data and produce a map of $μ$-type spectral distortion across the sky. We provide an updated constraint on the $μ$ distortion monopole $|\langleμ\rangle|<47\times 10^{-6}$ at 95\% confidence level that sharpens the previous FIRAS estimate by a factor of $\sim 2$. We also constrain primordial non-Gaussianities of curvature perturbations on scales $10\lesssim k\lesssim 5\times 10^4$ through the cross-correlation of $μ$ distortion anisotropies with CMB temperature and, for the first time, the full set of polarization anisotropies from the Planck satellite. We obtain upper limits on $f_{\rm NL}\lesssim 3.6 \times 10^6$ and on its running $n_{\rm NL}\lesssim 1.4$ that are limited by the FIRAS sensitivity but robust against galactic and extragalactic foreground contaminations. We revisit previous similar analyses based on data of the Planck satellite and show that, despite their significantly lower noise, they yield similar or worse results to ours once all the instrumental and astrophysical uncertainties are properly accounted for. Our work is the first to self-consistently analyze data from a spectrometer and demonstrate the power of such instrument to carry out this kind of science case with reduced systematic uncertainties.

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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.

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The Simons Observatory: a new open-source power spectrum pipeline applied to the Planck legacy data

We present a reproduction of the Planck 2018 angular power spectra at $\ell > 30$, and associated covariance matrices, for intensity and polarization maps at 100, 143 and 217 GHz. This uses a new, publicly available, pipeline that is part of the PSpipe package. As a test case we use the same input maps, ancillary products, and analysis choices as in the Planck 2018 analysis, and find that we can reproduce the spectra to 0.1$σ$ precision, and the covariance matrices to 10%. We show that cosmological parameters estimated from our re-derived products agree with the public Planck products to 0.1$σ$, providing an independent cross-check of the Planck team's analysis. Going forward, the publicly-available code can be easily adapted to use alternative input maps, data selections and analysis choices, for future optimal analysis of Planck data with new ground-based Cosmic Microwave Background data.

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The Simons Observatory: Galactic Science Goals and Forecasts

Observing in six frequency bands from 27 to 280 GHz over a large sky area, the Simons Observatory (SO) is poised to address many questions in Galactic astrophysics in addition to its principal cosmological goals. In this work, we provide quantitative forecasts on astrophysical parameters of interest for a range of Galactic science cases. We find that SO can: constrain the frequency spectrum of polarized dust emission at a level of $Δβ_d \lesssim 0.01$ and thus test models of dust composition that predict that $β_d$ in polarization differs from that measured in total intensity; measure the correlation coefficient between polarized dust and synchrotron emission with a factor of two greater precision than current constraints; exclude the non-existence of exo-Oort clouds at roughly 2.9$σ$ if the true fraction is similar to the detection rate of giant planets; map more than 850 molecular clouds with at least 50 independent polarization measurements at 1 pc resolution; detect or place upper limits on the polarization fractions of CO(2-1) emission and anomalous microwave emission at the 0.1% level in select regions; and measure the correlation coefficient between optical starlight polarization and microwave polarized dust emission in $1^\circ$ patches for all lines of sight with $N_{\rm H} \gtrsim 2\times10^{20}$ cm$^{-2}$. The goals and forecasts outlined here provide a roadmap for other microwave polarization experiments to expand their scientific scope via Milky Way astrophysics.

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BoloCalc: a sensitivity calculator for the design of Simons Observatory

The Simons Observatory (SO) is an upcoming experiment that will study temperature and polarization fluctuations in the cosmic microwave background (CMB) from the Atacama Desert in Chile. SO will field both a large aperture telescope (LAT) and an array of small aperture telescopes (SATs) that will observe in six bands with center frequencies spanning from 27 to 270~GHz. Key considerations during the SO design phase are vast, including the number of cameras per telescope, focal plane magnification and pixel density, in-band optical power and camera throughput, detector parameter tolerances, and scan strategy optimization. To inform the SO design in a rapid, organized, and traceable manner, we have created a Python-based sensitivity calculator with several state-of-the-art features, including detector-to-detector optical white-noise correlations, a handling of simulated and measured bandpasses, and propagation of low-level parameter uncertainties to uncertainty in on-sky noise performance. We discuss the mathematics of the sensitivity calculation, the calculator's object-oriented structure and key features, how it has informed the design of SO, and how it can enhance instrument design in the broader CMB community, particularly for CMB-S4.

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Instrumental systematics biases in CMB lensing reconstruction: a simulation-based assessment

Weak gravitational lensing of the cosmic microwave background (CMB) is an important cosmological tool that allows us to learn about the structure, composition and evolution of the Universe. Upcoming CMB experiments, such as the Simons Observatory (SO), will provide high-resolution and low-noise CMB measurements. We consider the impact of instrumental systematics on the corresponding high-precision lensing reconstruction power spectrum measurements. We simulate CMB temperature and polarization maps for an SO-like instrument and potential scanning strategy, and explore systematics relating to beam asymmetries and offsets, boresight pointing, polarization angle, gain drifts, gain calibration and electric crosstalk. Our analysis shows that the majority of the biases induced by the systematics we modeled are below a detection level of $\sim 0.6σ$. We discuss potential mitigation techniques to further reduce the impact of the more significant systematics, and pave the way for future lensing-related systematics analyses.

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