arXiv subjects

J. D. Emberson

Publications and source records attributed to J. D. Emberson.

At least 19 recordsLinked to original sources

arXiv2026

Emulator-Based Inference of Cosmological Subgrid Models

The formation of structure in the Universe at large scales is dominated by gravity, with baryonic physics becoming significant at $\sim{\rm Mpc}$ scales. To capture the impact of baryonic physics, cosmological simulations must model gas dynamics and a host of relevant astrophysical processes. A recent extension of the Hardware/Hybrid Accelerated Cosmology Code (HACC) couples its gravity solver with a modern smoothed particle hydrodynamics method. This extension incorporates sub-resolution models for chemical enrichment, black hole and star formation, AGN kinetic and thermal feedback, supernova-driven feedback, galactic winds, and metal-line cooling. We present an inference framework based on high-fidelity emulators to aid in model calibration against observational targets, e.g., the galaxy stellar mass function, radial gas density profiles, and the cluster gas fraction. The emulators are trained on simulation suites comprising 64 boxes with side-length $128\,h^{-1}$Mpc and 16 boxes with side-length $256\,h^{-1}$Mpc with $2\times 512^3$ and $2\times 1024^3$ particles, respectively. Our analysis reveals two distinct AGN kinetic feedback modes -- a low-feedback mode yielding strong agreement with the observed radial gas density profiles of massive X-ray clusters, and a high-feedback mode providing a better fit to cluster gas fraction data, but systematically underestimating gas densities in inner regions.

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arXiv2025

Modeling Galaxy Formation in Cosmological Simulations with CRK-HACC

Self-consistently modeling baryonic effects in survey-scale cosmological simulations has become increasingly important as the diversity, precision, and statistical reach of modern observations continue to improve. The advent of exascale computing now enables a new generation of simulations that couple these physical processes across full-sky volumes with excellent statistical sampling of large-scale structure tracers such as galaxies, groups, and clusters. To support these efforts, we extend the CRK-HACC framework, a GPU-accelerated cosmological hydrodynamics code, with a suite of astrophysical subgrid models that simulate radiative cooling, star formation, stellar evolution, and AGN feedback within a numerically robust formulation optimized for scalability on modern exascale architectures. The models were selected and calibrated to reproduce observed galaxy stellar mass functions over the redshift range $0 < z < 2$ and cluster populations probed by cosmological surveys, capturing the large-scale baryonic evolution relevant for multi-wavelength, cross-correlated analyses. We describe the implementation and calibration of these models and demonstrate their consistency with observed galaxy population statistics and modern hydrodynamic simulations, establishing the baseline for exascale efforts that extend this framework to survey-scale volumes.

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arXiv2025

Cosmological Hydrodynamics at Exascale: A Trillion-Particle Leap in Capability

Resolving the most fundamental questions in cosmology requires simulations that match the scale, fidelity, and physical complexity demanded by next-generation sky surveys. To achieve the realism needed for this critical scientific partnership, detailed gas dynamics, along with a host of astrophysical effects, must be treated self-consistently with gravity for end-to-end modeling of structure formation. As an important step on this roadmap, exascale computing enables simulations that span survey-scale volumes while incorporating key subgrid processes that shape complex cosmic structures. We present results from CRK-HACC, a cosmological hydrodynamics code built for the extreme scalability requirements set by modern cosmological surveys. Using separation-of-scale techniques, GPU-resident tree solvers, in situ analysis pipelines, and multi-tiered I/O, CRK-HACC executed Frontier-E: a four trillion particle full-sky simulation, over an order of magnitude larger than previous efforts. The run achieved 513.1 PFLOPs peak performance, processing 46.6 billion particles per second and writing more than 100 PB of data in just over one week of runtime.

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arXiv2024

Advances in ArborX to support exascale applications

ArborX is a performance portable geometric search library developed as part of the Exascale Computing Project (ECP). In this paper, we explore a collaboration between ArborX and a cosmological simulation code HACC. Large cosmological simulations on exascale platforms encounter a bottleneck due to the in-situ analysis requirements of halo finding, a problem of identifying dense clusters of dark matter (halos). This problem is solved by using a density-based DBSCAN clustering algorithm. With each MPI rank handling hundreds of millions of particles, it is imperative for the DBSCAN implementation to be efficient. In addition, the requirement to support exascale supercomputers from different vendors necessitates performance portability of the algorithm. We describe how this challenge problem guided ArborX development, and enhanced the performance and the scope of the library. We explore the improvements in the basic algorithms for the underlying search index to improve the performance, and describe several implementations of DBSCAN in ArborX. Further, we report the history of the changes in ArborX and their effect on the time to solve a representative benchmark problem, as well as demonstrate the real world impact on production end-to-end cosmology simulations.

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arXiv2024

The picasso gas model: Painting intracluster gas on gravity-only simulations

We introduce picasso, a model designed to predict thermodynamic properties of the intracluster medium based on the properties of halos in gravity-only simulations. The predictions result from the combination of an analytical gas model, mapping gas properties to the gravitational potential, and of a machine learning model to predict the model parameters for individual halos based on their scalar properties, such as mass and concentration. Once trained, the model can be applied to make predictions for arbitrary potential distributions, allowing its use with flexible inputs such as N-body particle distributions or radial profiles. We present the model, and train it using pairs of gravity-only and hydrodynamic simulations. We show that when trained to learn the mapping from gravity-only to non-radiative hydrodynamic simulations, picasso can make remarkably accurate and precise predictions of intracluster gas thermodynamics, with percent-level bias and $\sim 20 \%$ scatter for $r / R_{500c} \in [0.1,1]$. Training the model on hydrodynamic simulations including sub-resolution physics modeling yields robust predictions as well, albeit with the introduction of a radius-dependent bias and an increase in scatter. We further show that the model can be trained to make accurate predictions from very minimal halo information, down to mass and concentration, at the cost of modestly reduced precision. picasso is made publicly available as a Python package at https://github.com/fkeruzore/picasso, which includes trained models that can be used to make predictions easily and efficiently, in a fully auto-differentiable and hardware-accelerated framework

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arXiv2023

Optimization and Quality Assessment of Baryon Pasting for Intracluster Gas using the Borg Cube Simulation

Synthetic datasets generated from large-volume gravity-only simulations are an important tool in the calibration of cosmological analyses. Their creation often requires accurate inference of baryonic observables from the dark matter field. We explore the effectiveness of a baryon pasting algorithm in providing precise estimations of three-dimensional gas thermodynamic properties based on gravity-only simulations. We use the Borg Cube, a pair of simulations originating from identical initial conditions, with one run evolved as a gravity-only simulation, and the other incorporating non-radiative hydrodynamics. Matching halos in both simulations enables comparisons of gas properties on an individual halo basis. This comparative analysis allows us to fit for the model parameters that yield the closest agreement between the gas properties in both runs. To capture the redshift evolution of these parameters, we perform the analysis at five distinct redshift steps, spanning from $z=0$ to $2$. We find that the investigated algorithm, utilizing information solely from the gravity-only simulation, achieves few-percent accuracy in reproducing the median intracluster gas pressure and density, albeit with a scatter of approximately 20%, for cluster-scale objects up to $z=2$. We measure the scaling relation between integrated Compton parameter and cluster mass ($Y_{500c} | M_{500c}$), and find that the imprecision of baryon pasting adds less than 5% to the intrinsic scatter measured in the hydrodynamic simulation. We provide best-fitting values and their redshift evolution, and discuss future investigations that will be undertaken to extend this work.

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arXiv2023

Numerical Discreteness Errors in Multi-Species Cosmological N-body Simulations

We present a detailed analysis of numerical discreteness errors in two-species, gravity-only, cosmological simulations using the density power spectrum as a diagnostic probe. In a simple setup where both species are initialized with the same total matter transfer function, biased growth of power forms on small scales when the solver force resolution is finer than the mean interparticle separation. The artificial bias is more severe when individual density and velocity transfer functions are applied. In particular, significant large-scale offsets in power are measured between simulations with conventional offset grid initial conditions when compared against converged high-resolution results where the force resolution scale is matched to the interparticle separation. These offsets persist even when the cosmology is chosen so that the two particle species have the same mass, indicating that the error is sourced from discreteness in the total matter field as opposed to unequal particle mass. We further investigate two mitigation strategies to address discreteness errors: the frozen potential method and softened interspecies short-range forces. The former evolves particles under the approximately "frozen" total matter potential in linear theory at early times, while the latter filters cross-species gravitational interactions on small scales in low density regions. By modeling closer to the continuum limit, both mitigation strategies demonstrate considerable reductions in large-scale power spectrum offsets.

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arXiv2023

Improving initialization and evolution accuracy of cosmological neutrino simulations

Neutrino mass constraints are a primary focus of current and future large-scale structure (LSS) surveys. Non-linear LSS models rely heavily on cosmological simulations -- the impact of massive neutrinos should therefore be included in these simulations in a realistic, computationally tractable, and controlled manner. A recent proposal to reduce the related computational cost employs a symmetric neutrino momentum sampling strategy in the initial conditions. We implement a modified version of this strategy into the Hardware/Hybrid Accelerated Cosmology Code (HACC) and perform convergence tests on its internal parameters. We illustrate that this method can impart $\mathcal{O}(1\%)$ numerical artifacts on the total matter field on small scales, similar to previous findings, and present a method to remove these artifacts using Fourier-space filtering of the neutrino density field. Moreover, we show that the converged neutrino power spectrum does not follow linear theory predictions on relatively large scales at early times at the $15\%$ level, prompting a more careful study of systematics in particle-based neutrino simulations. We also present an improved method for backscaling linear transfer functions for initial conditions in massive neutrino cosmologies that is based on achieving the same relative neutrino growth as computed with Boltzmann solvers. Our self-consistent backscaling method yields sub-percent accuracy in the total matter growth function. Comparisons for the non-linear power spectrum with the Mira-Titan emulator at a neutrino mass of $m_{\nu}=0.15~\mathrm{eV}$ are in very good agreement with the expected level of errors in the emulator and in the direct N-body simulation.

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arXiv2022

Simulating Hydrodynamics in Cosmology with CRK-HACC

We introduce CRK-HACC, an extension of the Hardware/Hybrid Accelerated Cosmology Code (HACC), to resolve gas hydrodynamics in large-scale structure formation simulations of the universe. The new framework couples the HACC gravitational N-body solver with a modern smoothed particle hydrodynamics (SPH) approach called CRKSPH. $\underline{\text{C}}$onservative $\underline{\text{R}}$eproducing $\underline{\text{K}}$ernel $\underline{\text{SPH}}$ utilizes smoothing functions that exactly interpolate linear fields while manifestly preserving conservation laws (momentum, mass, and energy). The CRKSPH method has been incorporated to accurately model baryonic effects in cosmology simulations - an important addition targeting the generation of precise synthetic sky predictions for upcoming observational surveys. CRK-HACC inherits the codesign strategies of the HACC solver and is built to run on modern GPU-accelerated supercomputers. In this work, we summarize the primary solver components and present a number of standard validation tests to demonstrate code accuracy, including idealized hydrodynamic and cosmological setups, as well as self-similarity measurements.

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arXiv2022

Modeling the Lyman-$α$ forest with Eulerian and SPH hydrodynamical methods

We compare two state-of-the-art numerical codes to study the overall accuracy in modeling the intergalactic medium and reproducing Lyman-$α$ forest observables for DESI and high-resolution data sets. The codes employ different approaches to solving both gravity and modeling the gas hydrodynamics. The first code, Nyx, solves the Poisson equation using the Particle-Mesh (PM) method and the Euler equations using a finite volume method. The second code, \CRKHACC, uses a Tree-PM method to solve for gravity, and an improved Lagrangian smoothed particle hydrodynamics (SPH) technique, where fluid elements are modeled with particles, to treat the intergalactic gas. We compare the convergence behavior of the codes in flux statistics as well as the degree to which the codes agree in the converged limit. We find good agreement overall with differences being less than observational uncertainties, and a particularly notable $\lesssim$1\% agreement in the 1D flux power spectrum. This agreement was achieved by applying a tessellation methodology for reconstructing the density in \CRKHACC instead of using an SPH kernel as is standard practice. We show that use of the SPH kernel can lead to significant and unnecessary biases in flux statistics; this is especially prominent at high redshifts, $z \sim 5$, as the Lyman-$α$ forest mostly comes from lower-density regions which are intrinsically poorly sampled by SPH particles.

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arXiv2020

Measuring the evolution of intergalactic gas from z=0 to 5 using the kinematic Sunyaev-Zel'dovich effect

A complete census of baryons in the late universe is a long-standing challenge due to the intermediate temperate and rarefied character of the majority of cosmic gas. To gain insight into this problem, we extract measurements of the kinematic Sunyaev-Zel'dovich (kSZ) effect from the cross-correlation of angular redshift fluctuations maps, which contain precise information about the cosmic density and velocity fields, and CMB maps high-pass filtered using aperture photometry; we refer to this technique as ARF-kSZ tomography. Remarkably, we detect significant cross-correlation for a wide range of redshifts and filter apertures using 6dF galaxies, BOSS galaxies, and SDSS quasars as tracers, yielding a 11 sigma detection of the kSZ effect. We then leverage these measurements to set constraints on the location, density, and abundance of gas inducing the kSZ effect, finding that this gas resides outside dark matter haloes, presents densities ranging from 10 to 250 times the cosmic average, and comprises half of cosmic baryons. Taken together, these findings indicate that ARF-kSZ tomography provides a nearly complete census of intergalactic gas from z=0 to 5.

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arXiv2019

On the road to percent accuracy III: non-linear reaction of the matter power spectrum to massive neutrinos

We analytically model the non-linear effects induced by massive neutrinos on the total matter power spectrum using the halo model reaction framework of Cataneo et al. 2019. In this approach the halo model is used to determine the relative change to the matter power spectrum caused by new physics beyond the concordance cosmology. Using standard fitting functions for the halo abundance and the halo mass-concentration relation, the total matter power spectrum in the presence of massive neutrinos is predicted to percent-level accuracy, out to $k=10 \, h \, {\rm Mpc}^{-1}$. We find that refining the prescriptions for the halo properties using $N$-body simulations improves the recovered accuracy to better than 1%. This paper serves as another demonstration for how the halo model reaction framework, in combination with a single suite of standard $Λ$CDM simulations, can recover percent-level accurate predictions for beyond-$Λ$CDM matter power spectra, well into the non-linear regime.

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arXiv2019

The Borg Cube Simulation: Cosmological Hydrodynamics with CRK-SPH

A challenging requirement posed by next-generation observations is a firm theoretical grasp of the impact of baryons on structure formation. Cosmological hydrodynamic simulations modeling gas physics are vital in this regard. A high degree of modeling flexibility exists in this space making it important to explore a range of methods in order to gauge the accuracy of simulation predictions. We present results from the first cosmological simulation using Conservative Reproducing Kernel Smoothed Particle Hydrodynamics (CRK-SPH). We employ two simulations: one evolved purely under gravity and the other with non-radiative hydrodynamics. Each contains 2x2304^3 cold dark matter plus baryon particles in an 800 Mpc/h box. We compare statistics to previous non-radiative simulations including power spectra, mass functions, baryon fractions, and concentration. We find self-similar radial profiles of gas temperature, entropy, and pressure and show that a simple analytic model recovers these results to better than 40% over two orders of magnitude in mass. We quantify the level of non-thermal pressure support in halos and demonstrate that hydrostatic mass estimates are biased low by 24% (10%) for halos of mass 10^15 (10^13) Msun/h. We compute angular power spectra for the thermal and kinematic Sunyaev-Zel'dovich effects and find good agreement with the low-l Planck measurements. Finally, artificial scattering between particles of unequal mass is shown to have a large impact on the gravity-only run and we highlight the importance of better understanding this issue in hydrodynamic applications. This is the first in a simulation campaign using CRK-SPH with future work including subresolution gas treatments.

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arXiv2017

Cosmological neutrino simulations at extreme scale

Constraining neutrino mass remains an elusive challenge in modern physics. Precision measurements are expected from several upcoming cosmological probes of large-scale structure. Achieving this goal relies on an equal level of precision from theoretical predictions of neutrino clustering. Numerical simulations of the non-linear evolution of cold dark matter and neutrinos play a pivotal role in this process. We incorporate neutrinos into the cosmological N-body code CUBEP3M and discuss the challenges associated with pushing to the extreme scales demanded by the neutrino problem. We highlight code optimizations made to exploit modern high performance computing architectures and present a novel method of data compression that reduces the phase-space particle footprint from 24 bytes in single precision to roughly 9 bytes. We scale the neutrino problem to the Tianhe-2 supercomputer and provide details of our production run, named TianNu, which uses 86% of the machine (13,824 compute nodes). With a total of 2.97 trillion particles, TianNu is currently the world's largest cosmological N-body simulation and improves upon previous neutrino simulations by two orders of magnitude in scale. We finish with a discussion of the unanticipated computational challenges that were encountered during the TianNu runtime.

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arXiv2016

Measurement of the Cold Dark Matter-Neutrino Dipole in the TianNu Simulation

Measurements of neutrino mass in cosmological observations rely on two point statistics that are hindered by significant degeneracies with the optical depth and galaxy bias. The relative velocity effect between cold dark matter and neutrinos induces a large scale dipole into the matter density field and may be able to provide orthogonal constraints to standard techniques. We numerically investigate this dipole in the TianNu Simulation, which contains cold dark matter and 50 meV neutrinos. We first compute the dipole using a new linear response technique where we treat the displacement caused by the relative velocity as a phase in Fourier space and then integrate the matter power spectrum over redshift. Then, we compute the dipole numerically in real space using the simulation density and velocity fields. We find excellent agreement between the linear response and N-body methods. Utilizing the dipole as an observational tool will require two tracers of the matter distribution that are differently biased with respect to the neutrino density.

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arXiv2016

Differential Neutrino Condensation onto Cosmic Structure

Astrophysical techniques have pioneered the discovery of neutrino mass properties. Current cosmological observations give an upper bound on neutrino masses by attempting to disentangle the small neutrino contribution from the sum of all matter using precise theoretical models. We discover the differential neutrino condensation effect in our TianNu N-body simulation. Neutrino masses can be inferred using this effect by comparing galaxy properties in regions of the universe with different neutrino relative abundance (i.e. the local neutrino to cold dark matter density ratio). In "neutrino-rich"' regions, more neutrinos can be captured by massive halos compared to "neutrino-poor" regions. This effect differentially skews the halo mass function and opens up the path to independent neutrino mass measurements in current or future galaxy surveys.

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arXiv2015

Evolution of Low Mass Galactic Subhalos and Dependence on Concentration

We carry out a detailed study of the orbital dynamics and structural evolution of over 6000 subhalos in the Via Lactea II simulation, from infall to present. By analyzing subhalos with masses down to m = 4e5 Msun, we find that lower mass subhalos, which are not strongly affected by dynamical friction, exhibit behaviors qualitatively different from those found previously for more massive ones. Furthermore, there is a clear trend of subhalos that fell into the host earlier being less concentrated. We show that the concentration at infall characterizes various aspects of subhalo evolution. In particular, tidal effects truncate the growth of less concentrated subhalos at larger distances from the host; subhalos with smaller concentrations have larger infall radii. The concentration at infall is further shown to be a determining factor for the subsequent mass loss of subhalos within the host, and also for the evolution of their internal structure in the v_max-r_max plane. Our findings raise the prospects of using the concentration to predict the tidal evolution of subhalos, which will be useful for obtaining analytic models of galaxy formation, as well as for near field cosmology.

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arXiv2015

Precision reconstruction of the dark matter-neutrino relative velocity from N-body simulations

Discovering the mass of neutrinos is a principle goal in high energy physics and cosmology. In addition to cosmological measurements based on two-point statistics, the neutrino mass can also be estimated by observations of neutrino wakes resulting from the relative motion between dark matter and neutrinos. Such a detection relies on an accurate reconstruction of the dark matter-neutrino relative velocity which is affected by non-linear structure growth and galaxy bias. We investigate our ability to reconstruct this relative velocity using large N-body simulations where we evolve neutrinos as distinct particles alongside the dark matter. We find that the dark matter velocity power spectrum is overpredicted by linear theory whereas the neutrino velocity power spectrum is underpredicted. The magnitude of the relative velocity observed in the simulations is found to be lower than what is predicted in linear theory. Since neither the dark matter nor the neutrino velocity fields are directly observable from galaxy or 21 cm surveys, we test the accuracy of a reconstruction algorithm based on halo density fields and linear theory. Assuming prior knowledge of the halo bias, we find that the reconstructed relative velocities are highly correlated with the simulated ones with correlation coefficients of 0.94, 0.93, 0.91 and 0.88 for neutrinos of mass 0.05, 0.1, 0.2 and 0.4 eV. We confirm that the relative velocity field reconstructed from large scale structure observations such as galaxy or 21 cm surveys can be accurate in direction and, with appropriate scaling, magnitude.

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