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Camille Avestruz

Publications and source records attributed to Camille Avestruz.

At least 37 records · Page 2Linked to original sources

Cosmic Reionization on Computers: Statistical Properties of the Distributions of Mean Opacities

Quasar absorption lines provide a unique window to the relationship between galaxies and the intergalactic medium during the Epoch of Reionization. In particular, high redshift quasars enable measurements of the neutral hydrogen content of the universe. However, the limited sample size of observed quasar spectra, particularly at the highest redshifts, hampers our ability to fully characterize the intergalactic medium during this epoch from observations alone. In this work, we characterize the distributions of mean opacities of the intergalactic medium in simulations from the Cosmic Reionization on Computers (CROC) project. We find that the distribution of mean opacities along sightlines follows a non-trivial distribution that cannot be easily approximated by a known distribution. When comparing the cumulative distribution function of mean opacities measurements in subsamples of sample sizes similar to observational measurements from the literature, we find consistency between CROC and observations at redshifts $z\lesssim 5.7$. However, at higher redshifts ($z\gtrsim5.7$), the cumulative distribution function of mean opacities from CROC is notably narrower than those from observed quasar sightlines implying that observations probe a systematically more opaque intergalactic medium at higher redshifts than the intergalactic medium in CROC boxes at these same redshifts. This is consistent with previous analyses that indicate that the universe is reionized too early in CROC simulations.

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The Blending ToolKit: A simulation framework for evaluation of galaxy detection and deblending

We present an open source Python library for simulating overlapping (i.e., blended) images of galaxies and performing self-consistent comparisons of detection and deblending algorithms based on a suite of metrics. The package, named Blending Toolkit (BTK), serves as a modular, flexible, easy-to-install, and simple-to-use interface for exploring and analyzing systematic effects related to blended galaxies in cosmological surveys such as the Vera Rubin Observatory Legacy Survey of Space and Time (LSST). BTK has three main components: (1) a set of modules that perform fast image simulations of blended galaxies, using the open source image simulation package GalSim; (2) a module that standardizes the inputs and outputs of existing deblending algorithms; (3) a library of deblending metrics commonly defined in the galaxy deblending literature. In combination, these modules allow researchers to explore the impacts of galaxy blending in cosmological surveys. Additionally, BTK provides researchers who are developing a new deblending algorithm a framework to evaluate algorithm performance and make principled comparisons with existing deblenders. BTK includes a suite of tutorials and comprehensive documentation. The source code is publicly available on GitHub at https://github.com/LSSTDESC/BlendingToolKit.

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The effects of different cooling and heating function models on a simulated analog of NGC300

Gas cooling and heating rates are vital components of hydrodynamic simulations. However, they are computationally expensive to evaluate exactly with chemical networks or photoionization codes. We compare two different approximation schemes for gas cooling and heating in an idealized simulation of an isolated galaxy. One approximation is based on a polynomial interpolation of a table of Cloudy calculations, as is commonly done in galaxy formation simulations. The other approximation scheme uses machine learning for the interpolation instead on an analytic function, with improved accuracy. We compare the temperature-density phase diagrams of gas from each simulation run to assess how much the two simulation runs differ. Gas in the simulation using the machine learning approximation is systematically hotter for low-density gas with $-3 \lesssim \log{(n_b/\mathrm{cm}^{-3})} \lesssim -1$. We find a critical curve in the phase diagram where the two simulations have equal amounts of gas. The phase diagrams differ most strongly at temperatures just above and below this critical curve. We compare CII emission rates for collisions with various particles (integrated over the gas distribution function), and find slight differences between the two simulations. Future comparisons with simulations including radiative transfer will be necessary to compare observable quantities like the total CII luminosity.

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Constraining Cosmology with Simulation-based inference and Optical Galaxy Cluster Abundance

We test the robustness of simulation-based inference (SBI) in the context of cosmological parameter estimation from galaxy cluster counts and masses in simulated optical datasets. We construct ``simulations'' using analytical models for the galaxy cluster halo mass function (HMF) and for the observed richness (number of observed member galaxies) to train and test the SBI method. We compare the SBI parameter posterior samples to those from an MCMC analysis that uses the same analytical models to construct predictions of the observed data vector. The two methods exhibit comparable performance, with reliable constraints derived for the primary cosmological parameters, ($Ω_m$ and $σ_8$), and richness-mass relation parameters. We also perform out-of-domain tests with observables constructed from galaxy cluster-sized halos in the Quijote simulations. Again, the SBI and MCMC results have comparable posteriors, with similar uncertainties and biases. Unsurprisingly, upon evaluating the SBI method on thousands of simulated data vectors that span the parameter space, SBI exhibits worsened posterior calibration metrics in the out-of-domain application. We note that such calibration tests with MCMC is less computationally feasible and highlight the potential use of SBI to stress-test limitations of analytical models, such as in the use for constructing models for inference with MCMC.

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The Beyond-Halo Mass Effects of the Cosmic Web Environment on Galaxies

Galaxy properties primarily depend on their host halo mass. Halo mass, in turn, depends on the cosmic web environment. We explore if the effect of the cosmic web on galaxy properties is entirely transitive via host halo mass, or if the cosmic web has an effect independent of mass. The secondary galaxy bias, sometimes referred to as ``galaxy assembly bias'', is the beyond-mass component of the galaxy-halo connection. We investigate the link between the cosmic web environment and the secondary galaxy bias in simulations. We measure the secondary galaxy bias through the following summary statistics: projected two-point correlation function, $\wprp$, and counts-in-cylinders statistics, $\Pncic$. First, we examine the extent to which the secondary galaxy bias can be accounted for with a measure of the environment as a secondary halo property. We find that the total secondary galaxy bias preferentially places galaxies in more strongly clustered haloes. In particular, haloes at fixed mass tend to host more galaxies when they are more strongly associated with nodes or filaments. This tendency accounts for a significant portion, but not the entirety, of the total secondary galaxy bias effect. Second, we quantify how the secondary galaxy bias behaves differently depending on the host halo proximity to nodes and filaments. We find that the total secondary galaxy bias is relatively stronger in haloes more associated with nodes or filaments. We emphasise the importance of removing halo mass effects when considering the cosmic web environment as a factor in the galaxy-halo connection.

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Subhalos in Galaxy Clusters: Coherent Accretion and Internal Orbits

Subhalo dynamics in galaxy cluster host halos govern the observed distribution and properties of cluster member galaxies. We use the IllustrisTNG simulation to investigate the accretion and orbits of subhalos found in cluster-size halos. We find that the median change in the major axis direction of cluster-size host halos is approximately $80$ degrees between $a\sim0.1$ and present-day. We identify coherent regions in the angular distribution of subhalo accretion, and $\sim68\%$ of accreted subhalos enter their host halo through $\sim38\%$ of the surface area at the virial radius. The majority of galaxy clusters in the sample have $\sim2$ such coherent regions. We further measure angular orbits of subhalos with respect to the host major axis and use a clustering algorithm to identify distinct orbit modes with varying oscillation timescales. The orbit modes correlate with subhalo accretion conditions. Subhalos in orbit modes with shorter oscillations tend to have lower peak masses and accretion directions somewhat more aligned with the major axis. One orbit mode, exhibiting the least oscillatory behavior, largely consists of subhalos that accrete near the plane perpendicular to the host halo major axis. Our findings are consistent with expectations from inflow from major filament structures and internal dynamical friction: most subhalos accrete through coherent regions, and more massive subhalos experience fewer orbits after accretion. Our work offers a unique quantification of subhalo dynamics that can be connected to how the intracluster medium strips and quenches cluster galaxies.

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Emergence of the Temperature-Density Relation in the Low-Density Intergalactic Medium

We examine the evolution of the phase diagram of the low-density intergalactic medium during the Epoch of Reionization in simulation boxes with varying reionization histories from the Cosmic Reionization on Computers project. The PDF of gas temperature at fixed density exhibits two clear modes: a warm and cold temperature mode, corresponding to the gas inside and outside of ionized bubbles. We find that the transition between the two modes is "universal" in the sense that its timing is accurately parameterized by the value of the volume-weighted neutral fraction for any reionization history. This "universality" is more complex than just a reflection of the fact that ionized gas is warm and neutral gas is cold: it holds for the transition at a fixed value of gas density, and gas at different densities transitions from the cold to the warm mode at different values of the neutral fraction, reflecting a non-trivial relationship between the ionization history and the evolving gas density PDF. Furthermore, the "emergence" of the tight temperature-density relation in the warm mode is also approximately "universally" controlled by the volume-weighted neutral fraction for any reionization history. In particular, the "emergence" of the temperature-density relation (as quantified by the rapid decrease in its width) occurs when the neutral fraction is $10^{-4}\lesssim X_\mathrm{HI} \lesssim10^{-3}$ for any reionization history. Our results indicate that the neutral fraction is a primary quantity controlling the various properties of the temperature-density relation, regardless of reionization history.

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Fast and Flexible Inference Framework for Continuum Reverberation Mapping using Simulation-based Inference with Deep Learning

Continuum reverberation mapping (CRM) of active galactic nuclei (AGN) monitors multiwavelength variability signatures to constrain accretion disk structure and supermassive black hole (SMBH) properties. The upcoming Vera Rubin Observatory's Legacy Survey of Space and Time (LSST) will survey tens of millions of AGN over the next decade, with thousands of AGN monitored with almost daily cadence in the deep drilling fields. However, existing CRM methodologies often require long computation time and are not designed to handle such large amount of data. In this paper, we present a fast and flexible inference framework for CRM using simulation-based inference (SBI) with deep learning to estimate SMBH properties from AGN light curves. We use a long-short-term-memory (LSTM) summary network to reduce the high-dimensionality of the light curve data, and then use a neural density estimator to estimate the posterior of SMBH parameters. Using simulated light curves, we find SBI can produce more accurate SMBH parameter estimation with $10^3-10^5$ times speed up in inference efficiency compared to traditional methods. The SBI framework is particularly suitable for wide-field RM surveys as the light curves will have identical observing patterns, which can be incorporated into the SBI simulation. We explore the performance of our SBI model on light curves with irregular-sampled, realistic observing cadence and alternative variability characteristics to demonstrate the flexibility and limitation of the SBI framework.

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Compressed baryon acoustic oscillation analysis is robust to modified-gravity models

We study the robustness of the baryon acoustic oscillation (BAO) analysis to the underlying cosmological model. We focus on testing the standard BAO analysis that relies on the use of a template. These templates are constructed assuming a fixed fiducial cosmological model and used to extract the location of the acoustic peaks. Such "compressed analysis" had been shown to be unbiased when applied to the $Λ$CDM model and some of its extensions. However, it has not been known whether this type of analysis introduces biases in a wider range of cosmological models where the template may not fully capture relevant features in the BAO signal. In this study, we apply the compressed analysis to noiseless mock power spectra that are based on Horndeski models, a broad class of modified-gravity theories specified with eight additional free parameters. We study the precision and accuracy of the BAO peak-location extraction assuming DESI, DESI II, and MegaMapper survey specifications. We find that the bias in the extracted peak locations is negligible; for example, it is less than 10% of the statistical error for even the proposed future MegaMapper survey. Our findings indicate that the compressed BAO analysis is remarkably robust to the underlying cosmological model.

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Cosmic Reionization on Computers: The Evolution of Ionizing Background and Mean Free Path

Observations of the end stages of reionization indicate that at $z\approx 5-6$, the ionizing background is not uniform and the mean free path (MFP) changes drastically. As MFP is closely related to the distribution of Lyman Limit Systems and Damped Lyman-alpha Systems (LLSs and DLAs, or ionizing photon "sinks"), it is important to understand them. In this study, we utilize the CROC simulations, which have both sufficient spatial resolution to resolve galaxy formation and LLSs alongside a fully coupled radiative transfer to simulate the reionization processes. In our analysis, we connect the evolution of the ionizing background and the MFP. We analyze two CROC boxes with distinct reionization histories and find that the distribution of ionizing background in both simulations display significant skewness that deviate from log-normal. Further, the ionizing background in late reionization box still displays significant fluctuations ($\sim 40\%$) at $z\approx5$. We also measure the MFP along sightlines that start 0.15 pMpc away from the center of potential quasar hosting halos. The evolution of the MFP measured from these sightlines exhibits a break that coincides with when all the neutral islands disappear in the reionization history of each box (the `ankle' of the reionization history of the box). In the absence of LLSs, the MFP will be biased high by $\approx 20\%$ at $z\approx 5$. We also compare the MFP measured in random sightlines. We find that at $z\approx 5$ the MFP measured in sightlines that start from massive halos are systematically smaller by $\approx 10\%$ compared with the MFP measured in random sightlines. We attribute this difference to the concentration of dense structures within 1 pMpc from massive halos. Our findings highlight the importance of high fidelity models in the interpretation of observational measurements.

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OLIMPO: a Balloon-Borne SZE Imager to Probe ICM Dynamics and the WHIM

OLIMPO is a proposed Antarctic balloon-borne Sunyaev-Zel'dovich effect (SZE) imager to study gas dynamics associated with structure formation along with the properties of the warm-hot intergalactic medium (WHIM) residing in the connective filaments. During a 25 day flight OLIMPO will image a total of 10 z~0.05 galaxy clusters and 8 bridges at 145, 250, 365, and 460 GHz at an angular resolution of 1.0'-3.3'. The maps will be significantly deeper than those planned from CMB-S4 and CCAT-P, and will have excellent fidelity to the large angular scales of our low-z targets, which are difficult to probe from the ground. In combination with X-ray data from eROSITA and XRISM we will transform our current static view of galaxy clusters into a full dynamic picture by measuring the internal intra-cluster medium (ICM) velocity structure with the kinematic SZE, X-ray spectroscopy, and the power spectrum of ICM fluctuations. Radio observations from ASKAP and MeerKAT will be used to better understand the connection between ICM turbulence and shocks with the relativistic plasma. Beyond the cluster boundary, we will combine thermal SZE maps from OLIMPO with X-ray imaging from eROSITA to measure the thermodynamics of the WHIM residing in filaments, providing a better understanding of its properties and its contribution to the total baryon budget.

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Towards Quantifying the Impact of Triaxiality on Optical Signatures of Galaxy Clusters: Weak Lensing and Galaxy Distributions

We present observational evidence of the impact of triaxiality on radial profiles that extend to 40 Mpc from galaxy cluster centres in optical measurements. We perform a stacked profile analysis from a sample of thousands of nearly relaxed galaxy clusters from public data releases of the Dark Energy Survey (DES) and the Dark Energy Camera Legacy Survey (DECaLS). Using the central galaxy elliptical orientation angle as a proxy for galaxy cluster orientation, we measure cluster weak lensing and excess galaxy density axis-aligned profiles, extracted along the central galaxy's major or minor axes on the plane-of-the-sky. Our measurements show a $\gtrsim2-3σ$ difference per radial bin between the normalized axis-aligned profiles. The profile difference between each axis-aligned profile and the azimuthally averaged profile ($\sim\pm10-20\%$ along major/minor axis) appears inside the clusters ($\sim0.4$ Mpc) and extends to the large-scale structure regime ($\sim10-20$ Mpc). The magnitude of the difference appears to be relatively insensitive to cluster richness and redshift, and extends further out in the weak lensing surface mass density than in the galaxy overdensity. Looking forward, this measurement can easily be applied to other observational or simulation datasets and can inform the systematics in cluster mass modeling related to triaxiality. We expect imminent upcoming wide-area deep surveys, such as the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST), to improve our quantification of optical signatures of cluster triaxiality.

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Cosmic Reionization On Computers: Statistics, Physical Properties and Environment of Lyman Limit Systems at $z\sim6$

Lyman limit systems (LLSs) are dense hydrogen clouds with high enough HI column densities to absorb Lyman continuum photons emitted from distant quasars. Their high column densities imply an origin in dense environments; however, the statistics and distribution of LLSs at high redshifts still remain uncertain. In this paper, we use self-consistent radiative transfer cosmological simulations from the "Cosmic Reionization On Computers" (CROC) project to study the physical properties of LLSs at the tail end of cosmic reionization at $z\sim6$. We generate 3000 synthetic quasar sightlines to obtain a large number of LLS samples in the simulations. In addition, with the high physical fidelity and resolution of CROC, we are able to quantify the association between these LLS samples and nearby galaxies. Our results show that the fraction LLSs spatially associated with nearby galaxies is increasing with the HI column density. Moreover, we find that LLSs that are not near any galaxy typically reside in filamentary structures connecting neighboring galaxies in the intergalactic medium (IGM). This quantification of the distribution and associations of LLSs to large scale structures informs our understanding of the IGM-galaxy connection during the Epoch of Reionization, and provides a theoretical basis for interpreting future observations.

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Exploring the Dependence of Gas Cooling and Heating Functions on the Incident Radiation Field with Machine Learning

Gas cooling and heating functions play a crucial role in galaxy formation. But, it is computationally expensive to exactly compute these functions in the presence of an incident radiation field. These computations can be greatly sped up by using interpolation tables of pre-computed values, at the expense of making significant and sometimes even unjustified approximations. Here, we explore the capacity of machine learning to approximate cooling and heating functions with a generalized radiation field. Specifically, we use the machine learning algorithm XGBoost to predict cooling and heating functions calculated with the photoionization code Cloudy at fixed metallicity, using different combinations of photoionization rates as features. We perform a constrained quadratic fit in metallicity to enable a fair comparison with traditional interpolation methods at arbitrary metallicity. We consider the relative importance of various photoionization rates through both a principal component analysis (PCA) and calculation of SHapley Additive exPlanation (SHAP) values for our XGBoost models. We use feature importance information to select different subsets of rates to use in model training. Our XGBoost models outperform a traditional interpolation approach at each fixed metallicity, regardless of feature selection. At arbitrary metallicity, we are able to reduce the frequency of the largest cooling and heating function errors compared to an interpolation table. We find that the primary bottleneck to increasing accuracy lies in accurately capturing the metallicity dependence. This study demonstrates the potential of machine learning methods such as XGBoost to capture the non-linear behavior of cooling and heating functions.

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Merger Response of Halo Anisotropy Properties

Anisotropy properties -- halo spin, shape, position offset, velocity offset, and orientation -- are an important family of dark matter halo properties that indicate the level of directional variation of the internal structures of haloes. These properties reflect the dynamical state of haloes, which in turn depends on the mass assembly history. In this work, we study the evolution of anisotropy properties in response to merger activity using the IllustrisTNG simulations. We find that the response trajectories of the anisotropy properties significantly deviate from secular evolution. These trajectories have the same qualitative features and timescales across a wide range of merger and host properties. We propose explanations for the behaviour of these properties and connect their evolution to the relevant stages of merger dynamics. We measure the relevant dynamical timescales. We also explore the dependence of the strength of the response on time of merger, merger ratio, and mass of the main halo. These results provide insight into the physics of halo mergers and their effects on the statistical behaviour of halo properties. This study paves the way towards a physical understanding of scaling relations, particularly to how systematics in their scatter are connected to the mass assembly histories of haloes.

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MultiCAM: A multivariable framework for connecting the mass accretion history of haloes with their properties

Models that connect galaxy and halo properties often summarize a halo's mass accretion history (MAH) with a single value, and use this value as the basis for predictions. However, a single-value summary fails to capture the complexity of MAHs and information can be lost in the process. We present MultiCAM, a generalization of traditional abundance matching frameworks, which can simultaneously connect the full MAH of a halo with multiple halo and/or galaxy properties. As a first case study, we apply MultiCAM to the problem of connecting dark matter halo properties to their MAHs in the context of a dark matter-only simulation. While some halo properties, such as concentration, are more strongly correlated to the early-time mass growth of a halo, others, like the virial ratio, have stronger correlations with late-time mass growth. This highlights the necessity of considering the impact of the entire MAH on halo properties. For most of the halo properties we consider, we find that MultiCAM models that use the full MAH achieve higher accuracy than conditional abundance matching models which use a single epoch. We also demonstrate an extension of MultiCAM that captures the covariance between predicted halo properties. This extension provides a baseline model for applications where the covariance between predicted properties is important.

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Statistical Inference for Coadded Astronomical Images

Coadded astronomical images are created by stacking multiple single-exposure images. Because coadded images are smaller in terms of data size than the single-exposure images they summarize, loading and processing them is less computationally expensive. However, image coaddition introduces additional dependence among pixels, which complicates principled statistical analysis of them. We present a principled Bayesian approach for performing light source parameter inference with coadded astronomical images. Our method implicitly marginalizes over the single-exposure pixel intensities that contribute to the coadded images, giving it the computational efficiency necessary to scale to next-generation astronomical surveys. As a proof of concept, we show that our method for estimating the locations and fluxes of stars using simulated coadds outperforms a method trained on single-exposure images.

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Can Cooling and Heating Functions be Modeled with Homogeneous Radiation Fields?

Cooling and heating functions describe how radiative processes impact the thermal state of a gas as a function of its temperature and other physical properties. In a most general case the functions depend on the detailed distributions of ionic species and on the radiation spectrum. Hence, these functions may vary on a very wide range of spatial and temporal scales. In this paper, we explore cooling and heating functions between $5\leq z \leq10$ in simulated galaxies from the Cosmic Reionization On Computers (CROC) project. We compare three functions. First, the actual cooling and heating rates of hydrodynamic cells as a function of cell temperature. Second, the median cooling and heating functions computed using median interstellar medium (ISM) properties (median ISM). Last, the median of the cooling and heating functions of all gas cells (instantaneous). We find that the median ISM and instantaneous approaches to finding a median cooling and heating function give identical results within the spread due to cell-to-cell variation. However, the actual cooling (heating) rates experienced by the gas at different temperatures in the simulations do not correspond to either summarized cooling (heating) functions. In other words, the thermodynamics of the gas in the simulations cannot be described by a single set of a cooling plus a heating function with a spatially constant radiation field that could be computed with common tools, such as Cloudy.

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