arXiv subjects

Nickolay Y. Gnedin

Publications and source records attributed to Nickolay Y. Gnedin.

At least 37 records · Page 2Linked to original sources

arXiv2023

Compressing the cosmological information in one-dimensional correlations of the Lyman-$α$ forest

Observations of the Lyman-$α$ (Ly$α$) forest from spectroscopic surveys such as BOSS/eBOSS, or the ongoing DESI, offer a unique window to study the growth of structure on megaparsec scales. Interpretation of these measurements is a complicated task, requiring hydrodynamical simulations to model and marginalise over the thermal and ionisation state of the intergalactic medium. This complexity has limited the use of Ly$α$ clustering measurements in joint cosmological analyses. In this work we show that the cosmological information content of the 1D power spectrum ($P_\mathrm{1D}$) of the Ly$α$ forest can be compressed into a simple two-parameter likelihood without any significant loss of constraining power. We simulate $P_\mathrm{1D}$ measurements from DESI using hydrodynamical simulations and show that the compressed likelihood is model independent and lossless, recovering unbiased results even in the presence of massive neutrinos or running of the primordial power spectrum.

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arXiv2022

Modeling Cosmic Reionization

The transformation of cold neutral intergalactic hydrogen into a highly ionized warm plasma marks the end of the cosmic dark ages and the beginning of the age of galaxies. The details of this process reflect the nature of the early sources of radiation and heat, the statistical characteristics of the large-scale structure of the Universe, the thermodynamics and chemistry of cosmic baryons, and the histories of star formation and black hole accretion. A number of massive data sets from new ground- and space-based instruments and facilities over the next decade are poised to revolutionize our understanding of primeval galaxies, the reionization photon budget, the physics of the intergalactic medium (IGM), and the fine-grained properties of hydrogen gas in the "cosmic web". In this review we survey the physics and key aspects of reionization-era modeling and describe the diverse range of computational techniques and tools currently available in this field.

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arXiv2022

Cosmic Reionization On Computers: Baryonic Effects on Halo Concentrations During the Epoch of Reionization

Baryons both increase halo concentration through adiabatic contraction and expel mass through feedback processes. However, it is not well understood how the radiation fields prevalent during the epoch of reionization affect the evolution of concentration in dark matter halos. We investigate how baryonic physics during the epoch of reionization modify the structure of dark matter halos in the Cosmic Reionization On Computers (CROC) simulations. We use two different measures of halo concentration to quantify the effects. We compare concentrations of halos matched between full physics simulations and dark-matter-only simulations with identical initial conditions between $5 \leq z \leq 9$. Baryons in full physics simulations do pull matter towards the center, increasing the maximum circular velocity compared to dark-matter-only simulations. However, their overall effects are much less than if all the baryons were simply centrally concentrated indicating that heating processes efficiently counteract cooling effects. Finally, we show that the baryonic effects on halo concentrations at $z\approx5$ are relatively insensitive to environmental variations of reionization history. These results are pertinent to models of galaxy-halo connection during the epoch of reionization.

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arXiv2022

Reconstructing Large-scale Temperature Profiles around $z\sim 6$ Quasars

High-redshift quasars ionize HeII into HeIII around them, heating the IGM in the process and creating large regions with elevated temperature. In this work, we demonstrate a method based on a convolutional neural network (CNN) to recover the spatial profile for $T_0$, the temperature at the mean cosmic density, in quasar proximity zones. We train the neural network with synthetic spectra drawn from a Cosmic Reionization on Computers simulation. We discover that the simple CNN is able to recover the temperature profile with an accuracy of $\approx 1400$ K in an idealized case of negligible observational uncertainties. We test the robustness of the CNN and discover that it is robust against the uncertainties in quasar host halo mass, quasar continuum and ionizing flux. We also find that the CNN has good generality with regard to the hardness of quasar spectra. Saturated pixels pose a bigger problem for accuracy and may downgrade the accuracy to $1700$ K in the outer parts of the proximity zones. Using our method, one could distinguish whether gas is inside or outside the HeIII region created by the quasar. Because the size of the HeIII region is closely related to the total quasar lifetime, this method has great potential in constraining the quasar lifetime on $\sim $Myr timescales.

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arXiv2022

Modeling Dust Production, Growth, and Destruction in Reionization-Era Galaxies with the CROC Simulations: Methods and Parameter Exploration

We introduce a model for the explicit evolution of interstellar dust in a cosmological galaxy formation simulation. We post-process a simulation from the Cosmic Reionization on Computers project (CROC, Gnedin 2014), integrating an ordinary differential equation for the evolution of the dust-to-gas ratio along pathlines in the simulation sampled with a tracer particle technique. This model incorporates the effects of dust grain production in asymptotic giant branch (AGB) star winds and supernovae (SN), grain growth due to the accretion of heavy elements from the gas phase of the interstellar medium (ISM), and grain destruction due to thermal sputtering in the high temperature gas of supernova remnants (SNRs). A main conclusion of our analysis is the importance of a carefully chosen dust destruction model, for which different reasonable parameterizations can predict very different values at the $\sim 100$ pc resolution of the ISM in our simulations. We run this dust model on the single most massive galaxy in a 10$h^{-1}$ co-moving Mpc box, which attains a stellar mass of $\sim 2\times10^9 M_{\odot}$ by $z=5$. We find that the model is capable of reproducing dust masses and dust-sensitive observable quantities broadly consistent with existing data from high-redshift galaxies. The total dust mass in the simulated galaxy is somewhat sensitive to parameter choices for the dust model, especially the timescale for grain growth due to accretion in the ISM. Consequently, observable quantities that can constrain galaxy dust masses at these epochs are potentially useful for placing constraints on dust physics.

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arXiv2022

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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arXiv2022

Revealing the Galaxy-Halo Connection Through Machine Learning

Understanding the connections between galaxy stellar mass, star formation rate, and dark matter halo mass represents a key goal of the theory of galaxy formation. Cosmological simulations that include hydrodynamics, physical treatments of star formation, feedback from supernovae, and the radiative transfer of ionizing photons can capture the processes relevant for establishing these connections. The complexity of these physics can prove difficult to disentangle and obfuscate how mass-dependent trends in the galaxy population originate. Here, we train a machine learning method called Explainable Boosting Machines (EBMs) to infer how the stellar mass and star formation rate of nearly 6 million galaxies simulated by the Cosmic Reionization on Computers (CROC) project depend on the physical properties of halo mass, the peak circular velocity of the galaxy during its formation history $v_\mathrm{peak}$, cosmic environment, and redshift. The resulting EBM models reveal the relative importance of these properties in setting galaxy stellar mass and star formation rate, with $v_\mathrm{peak}$ providing the most dominant contribution. Environmental properties provide substantial improvements for modeling the stellar mass and star formation rate in only $\lesssim10\%$ of the simulated galaxies. We also provide alternative formulations of EBM models that enable low-resolution simulations, which cannot track the interior structure of dark matter halos, to predict the stellar mass and star formation rate of galaxies computed by high-resolution simulations with detailed baryonic physics.

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arXiv2022

Cosmic Reionization on Computers: Physical Origin of Long Dark Gaps in Quasar Absorption Spectra

I explore the properties of "dark gaps" - regions in quasar absorption spectra without significant transmission - with several simulations from the Cosmic Reionization On Computers (CROC) project. CROC simulations in largest available boxes (120 cMpc) come close to matching both the distribution of mean opacities and the frequency of dark gaps, but alas not in the same model: the run that matches the mean opacities fails to contain enough dark gaps and vice versa.:( Never-the-less, the run that matches the dark gap distributions serves as a counter-example to claims in the literature that the dark gap statistics requires a late end to reionization - in that run reionization ends at z=6.7 (likely too early). While multiple factors contribute to the frequency of large dark gaps in the simulations, the primary factor that controls the overall shape of the dark gap distribution is the ionization level in voids - the lowest density regions produce the highest transmission spikes that terminate long gaps. As the result, the dark gap distribution correlates strongly with the fraction of the spectrum above the gap detection threshold, the observed distribution is matched by the simulation in which this fraction is 2%. Hence, the gap distribution by itself does not constrain the timing of reionization.

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arXiv2022

Testing multiflavored ULDM models with SPARC

We perform maximum likelihood estimates (MLEs) for single and double flavor ultralight dark matter (ULDM) models using the Spitzer Photometry and Accurate Rotation Curves (SPARC) database. These estimates are compared to MLEs for several commonly used cold dark matter (CDM) models. By comparing various CDM models we find, in agreement with previous studies, that the Burkert and Einasto models tend to perform better than other commonly used CDM models. We focus on comparisons between the Einasto and ULDM models and analyze cases for which the ULDM particle masses are: free to vary; and fixed. For each of these analyses, we perform fits assuming the soliton and halo profiles are: summed together; and matched at a given radius. When we let the particle masses vary, we find a negligible preference for any particular range of particle masses, within $10^{-25}\,\text{eV}\leq m\leq10^{-19}\,\text{eV}$, when assuming the summed models. For the matched models, however, we find that almost all galaxies prefer particles masses in the range $10^{-23}\,\text{eV}\lesssim m\lesssim10^{-20}\,\text{eV}$. For both double flavor models we find that most galaxies prefer approximately equal particle masses. We find that the summed models give much larger variances with respect to the soliton-halo (SH) relation than the matched models. When the particle masses are fixed, the matched models give median and mean soliton and halo values that fall within the SH relation bounds, for most masses scanned. When the particle masses are fixed in the fitting procedure, we find the best fit results for the particle mass $m=10^{-20.5}\,\text{eV}$ (for the single flavor models) and $m_1=10^{-20.5}\,\text{eV}$, $m_2=10^{-20.2}\,\text{eV}$ for the double flavor, matched model. We discuss how our study will be furthered using a reinforcement learning algorithm.

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arXiv2021

Measuring the Density Fields around Bright Quasars at $z\sim 6$ with XQR-30 Spectra

Measuring the density of the intergalactic medium using quasar sightlines in the epoch of reionization is challenging due to the saturation of Lyman-$α$ absorption. Near a luminous quasar, however, the enhanced radiation creates a proximity zone observable in the quasar spectra where the Lyman-$α$ absorption is not saturated. In this study, we use $10$ high-resolution ($R\gtrsim 10,000$) $z\sim 6$ quasar spectra from the extended XQR-30 sample to measure the density field in the quasar proximity zones. We find a variety of environments within $3$ pMpc distance from the quasars. We compare the observed density cumulative distribution function (CDF) with models from the $\textit{Cosmic Reionization on Computers}$ simulation, and find a good agreement between $1.5$ to $3$pMpc from the quasar. This region is far away from the quasar hosts and hence approaching the mean density of the universe, which allows us to use the CDF to set constraints on the cosmological parameter $σ_8=0.6\pm0.3$. The uncertainty is mainly due to the limited number of high-quality quasar sightlines currently available. Utilizing the more than $>200$ known quasars at $z\gtrsim 6$, this method will allow us in the future to tighten the constraint on $σ_8$ to the percent level. In the region closer to the quasar within $1.5$ pMpc, we find the density is higher than predicted in the simulation by $1.23 \pm 0.17$, suggesting the typical host dark matter halo mass of a bright quasar ($M_{\rm 1450}<-26.5$) at $z\sim 6$ is $\log_{\rm 10} (M/M_\odot)=12.5^{+0.4}_{-0.7}$.

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arXiv2021

Recovering Density Fields inside Quasar Proximity Zones at $z\sim 6$

The matter density field at $z\sim 6$ is very challenging to probe. One of the traditional probes of the low density IGM that works successfully at lower redshifts is the Lyman-alpha forest in quasar spectra. However, at the end of reionization, the residual neutral hydrogen usually creates saturated absorption, thus much of the information about the gas density is lost. Luckily, in a quasar proximity zone, the ionizing radiation is exceptionally intense, thus creating a large region with non-zero transmitted flux. In this study we use the synthetic spectra from simulations to investigate how to recover the density fluctuations inside the quasar proximity zones. We show that, under ideal conditions, the density can be recovered accurately with a small scatter. We also discuss how systematics such as the quasar continuum fitting and reionization models affect the results. This study shows that by analyzing the absorption features inside quasar proximity zones we can potentially constrain quasar properties and the environments they reside in.

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arXiv2021

Spatial Decorrelation of Young Stars and Dense Gas as a Probe of the Star Formation-Feedback Cycle in Galaxies

The spatial decorrelation of dense molecular gas and young stars observed on $\lesssim 1$ kiloparsec scales in nearby galaxies indicates rapid dispersal of star-forming regions by stellar feedback. We explore the sensitivity of this decorrelation to different processes controlling the structure of the interstellar medium, the abundance of molecular gas, star formation, and feedback in a suite of simulations of an isolated dwarf galaxy with structural properties similar to NGC300 that self-consistently model radiative transfer and molecular chemistry. Our fiducial simulation reproduces the magnitude of decorrelation and its scale dependence measured in NGC300, and we show that this agreement is due to different aspects of feedback, including H$_2$ dissociation, gas heating by the locally variable UV field, early mechanical feedback, and supernovae. In particular, early radiative and mechanical feedback affects the correlation on $\lesssim 100$ pc scales, while supernovae play a significant role on $\gtrsim 100$ pc scales. The correlation is also sensitive to the choice of the local star formation efficiency per freefall time, $ε_{\rm ff}$, which provides a strong observational constraint on $ε_{\rm ff}$ when the global star formation rate is independent of its value. Finally, we explicitly show that the degree of correlation between the peaks of molecular gas and star formation density is directly related to the distribution of the lifetimes of star-forming regions.

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arXiv2021

Approximating Density Probability Distribution Functions Across Cosmologies

Using a suite of self-similar cosmological simulations, we measure the probability distribution functions (PDFs) of real-space density, redshift-space density, and their geometric mean. We find that the real-space density PDF is well-described by a function of two parameters: $n_s$, the spectral slope, and $σ_L$, the linear rms density fluctuation. For redshift-space density and the geometric mean of real- and redshift-space densities, we introduce a third parameter, $s_L={\sqrt{\langle(dv^L_{\rm pec}/dr)^2\rangle}}/{H}$. We find that density PDFs for the LCDM cosmology is also well-parameterized by these three parameters. As a result, we are able to use a suite of self-similar cosmological simulations to approximate density PDFs for a range of cosmologies. We make the density PDFs publicly available and provide an analytical fitting formula for them.

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arXiv2021

Reconstruction of the Density Power Spectrum from Quasar Spectra using Machine Learning

We describe a novel end-to-end approach using Machine Learning to reconstruct the power spectrum of cosmological density perturbations at high redshift from observed quasar spectra. State-of-the-art cosmological simulations of structure formation are used to generate a large synthetic dataset of line-of-sight absorption spectra paired with 1-dimensional fluid quantities along the same line-of-sight, such as the total density of matter and the density of neutral atomic hydrogen. With this dataset, we build a series of data-driven models to predict the power spectrum of total matter density. We are able to produce models which yield reconstruction to accuracy of about 1% for wavelengths $k \leq 2 h Mpc^{-1}$, while the error increases at larger $k$. We show the size of data sample required to reach a particular error rate, giving a sense of how much data is necessary to reach a desired accuracy. This work provides a foundation for developing methods to analyse very large upcoming datasets with the next-generation observational facilities.

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arXiv2021

A Hydro-Particle-Mesh Code for Efficient and Rapid Simulations of the Intracluster Medium

We introduce the cosmological HYPER code based on an innovative hydro-particle-mesh (HPM) algorithm for efficient and rapid simulations of gas and dark matter. For the HPM algorithm, we update the approach of Gnedin & Hui (1998) to expand the scope of its application from the lower-density intergalactic medium (IGM) to the higher-density intracluster medium (ICM). While the original algorithm tracks only one effective particle species, the updated version separately tracks the gas and dark matter particles as they do not exactly trace each other on small scales. For the approximate hydrodynamics solver, the pressure term in the gas equations of motion is calculated using robust physical models. In particular, we use a dark matter halo model, ICM pressure profile, and IGM temperature-density relation, all of which can be systematically varied for parameter-space studies. We show that the HYPER simulation results are in good agreement with the halo model expectations for the density, temperature, and pressure radial profiles. Simulated galaxy cluster scaling relations for Sunyaev-Zel'dovich (SZ) and X-ray observables are also in good agreement with mean predictions, with scatter comparable to that found in hydrodynamic simulations. HYPER also produces lightcone catalogs of dark matter halos and full-sky tomographic maps of the lensing convergence, SZ effect, and X-ray emission. These simulation products are useful for testing data analysis pipelines, generating training data for machine learning, understanding selection and systematic effects, and for interpreting astrophysical and cosmological constraints.

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arXiv2021

The Effect of Warm Dark Matter on Early Star Formation Histories of Massive Galaxies: Predictions from the CROC Simulations

Several massive ($M_{*} > 10^8 M_{\odot}$), high-redshift ($z = 8-10$) galaxies have recently been discovered to contain stars with ages of several hundred million years, pushing the onset of star formation in these galaxies back to $z\sim15$. The very existence of stars formed so early may serve as a test for cosmological models with suppressed small-scale power (and, hence, late formation of cosmic structure). We explore the ages of the oldest stars in numerical simulations from the Cosmic Reionization On Computers (CROC) project with cold dark matter (CDM) and two warm dark matter (WDM) cosmologies with 3 and 6 keV particles. There are statistically significant differences of $\sim 5\;{\rm Myr}$ between average stellar ages of massive galaxies in CDM and 3 keV WDM, while CDM and 6 keV WDM are statistically indistinguishable. Even this 5 Myr difference, however, is much less than current observational uncertainties on the stellar population properties of high-redshift galaxies. The age distributions of all galaxies in all cosmologies fail to produce a substantial Balmer break, although uncertainties in dust attenuation are a potentially significant factor. Finally, we assess the convergence of our simulation predictions and find that the systematic uncertainties on individual galaxy properties are comparable to the differences between cosmologies, suggesting these differences may not be numerically robust.

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arXiv2021

Gravitational Self-force Errors of Poisson Solvers on Adaptively Refined Meshes

An error in the gravitational force that the source of gravity induces on itself (a self-force error) violates both the conservation of linear momentum and the conservation of energy. If such errors are present in a self-gravitating system and are not sufficiently random to average out, the obtained numerical solution will become progressively more unphysical with time: the system will acquire or lose momentum and energy due to numerical effects. In this paper, we demonstrate how self-force errors can arise in the case where self-gravity is solved on an adaptively refined mesh when the refinement is nonuniform. We provide the analytical expression for the self-force error and numerical examples that demonstrate such self-force errors in idealized settings. We also show how these errors can be corrected to an arbitrary order by straightforward addition of correction terms at the refinement boundaries.

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arXiv2021

Cosmic Reionization On Computers: The Galaxy-Halo Connection between $5 \leq z \leq10$

We explore the connection between the stellar component of galaxies and their host halos during the epoch of reionization ($5 \leq z\leq10$) using the CROC (Cosmic Reionization on Computers) simulations. We compare simulated galaxies with observations and find that CROC underpredicts the abundance of luminous galaxies when compared to observed UV luminosity functions, and analogously the most massive galaxies when compared to observed stellar mass functions. We can trace the deficit of star formation to high redshifts, where the slope of the star formation rate to stellar mass relation is consistent with observations, but the normalization is systematically low. This results in a star formation rate density and stellar mass density that is systematically offset from observations. However, the less luminous or lower stellar mass objects have luminosities and stellar masses that agree fairly well with observational data. We explore the stellar-to-halo mass ratio, a key quantity that is difficult to measure at high redshifts and that models do not consistently predict. In CROC, the stellar-to-halo mass ratio {\it decreases} with redshift, a trend opposite to some abundance matching studies. These discrepancies uncover where future effort should be focused in order to improve the fidelity of modeling cosmic reionization. We also compare the CROC galaxy bias with observational measurements using Lyman-Break Galaxy (LBG) samples. The good agreement of simulation and data shows that the clustering of dark matter halos is properly captured in CROC.

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