JD Emberson

JD Emberson

JD is a computational cosmologist in the Argonne Computational Science (CPS) Division. He has a broad interest in the development and application of numerical techniques for large-scale cosmological structure formation simulations. This includes both N-body as well as hydrodynamic methods in order to gain insight into various astrophysical phenomena including dark energy, neutrinos, and primordial non-Gaussianity (see word cloud below). JD is one of the main developers of HACC with an emphasis on integrating robust hydrodynamical modeling for use on next-generation Exascale platforms. A large part of this effort includes understanding the systematic errors associated with the discrete nature of simulations and the various modeling choices made in multi-species and sub-resolution frameworks. JD has a keen interest in scientific data visualization; a collection of animations from his recent simulation endeavors can be found below.

Word cloud showcasing my research interests. This image was generated using a python script that queries the arXiv API to download all of my research paper abstracts and then computes tf-idf scores on their text. Font sizes are ranked by the tf-idf score and plotted using the python WordCloud library.

Codes

  • SONICC is a python code that computes density and velocity transfer functions for use in the initial conditions of cosmological neutrino simulations. The transfer functions are backscaled from CAMB at a specified target redshift using a scale-dependent growth function that yields self-consistent evolution for all three matter species (cold dark matter, baryons, massive neutrinos) in the Newtonian forward model of the simulation.

Animations

An animation of the Frontier-E simulation run with CRK-HACC on 9000 nodes (96% of the machine) of the Frontier supercomputer. This movie shows the formation of the largest object in the simulation, which reaches 4.7e15 Msun/h at redshift z = 0. The left panel shows a 64x64x76 Mpc/h subvolume of the simulation (only 1/100,000^th the full simulation volume) around the large object, with the right panel providing a zoom-in. In each panel, we show the gas density colored by its temperature. In the right panel, the white circles show star particles while the open black circles show AGN particles. 

An animation of the Borg Cube simulation run with CRK-HACC on 196,608 cores (70% of the machine) of the Theta supercomputer. The Borg Cube is an adiabatic hydrodynamic simulation containing 2×2304^3 cold dark matter plus baryon particles in a box of side length 800 Mpc/h. We show the evolution from redshift z = 10 (13 billion years ago) to z = 0 for a subvolume of size 50x50x67 Mpc/h. Colour traces the gas temperature field while white highlights peaks in the baryon density field. We zoom up on the formation of a massive cluster (4×10^4 Msun) where the surrounding gas has been shock heated to temperatures approaching 10^8 K.

This animation displays the output of the TianNu simulation containing 2.64 trillion neutrino plus 330 billion cold dark matter particles in a box of side length 1200 Mpc/h. TianNu was run on 331,776 cores (86% of the machine) of the Tianhe-2 supercomputer with the code CubeP3M. We begin with the depiction of slices of the cold dark matter density field (on the left, in blue) and the neutrino density field (on the right, in red) where the side length is 1000 Mpc/h and the slice depth is 8 Mpc/h. The movie starts at z = 5 (12.5 billion years ago) and proceeds until the present day, at z = 0. The left panel shows the development of the cold dark matter cosmic web while the right panel demonstrates the gravitational clustering of neutrinos around the largest cold dark matter structures. The second part of the animation dives into the simulation, travelling at roughly 10^15 times the speed of light, until stopping at a cluster of mass 10^15 Msun.

This movie shows the propagation of an ionization front through the intergalactic medium. The colour traces the density of ionized gas within the box, which has side length 1 Mpc/h and is shown at redshift z = 6 (12.8 billion years ago). An ionization front produced by starlight from a nearby galaxy passes from left to right across the box. The movie starts by spinning around the box when a relatively dim flux is applied. This highlights the ability of small-scale absorption systems at the leading edge of the box to self-shield against ionizing radiation. The strength of the illuminating flux is then slowly increased and we see the ionization front sweep across the entire width. As the incident starlight brightens, the self-shielding of absorption systems increasingly diminishes. A final spin around the box at high illuminating flux reveals the structure contained within the volume as the ionization front has fully penetrated this patch of the intergalactic medium.

Publications

  1. A Gigaparsec-Scale Hydrodynamic Volume Reconstructed with Deep Learning
    C. Jacobus, S. Chabanier, P. Harrington, J. Emberson, Z. Lukić, and S. Habib
    Submitted to ApJ. arXiv:2411.16920.
  2. The picasso gas model: Painting intracluster gas on gravity-only simulations
    F. Kéruzoré, L.E. Bleem, N. Frontiere, N. Krishnan, M. Buehlmann, J.D. Emberson, S. Habib, and P. Larsen
    Accepted for publication in OJAp. arXiv:2408.17445.
  3. Advances in ArborX to Support Exascale Applications
    A. Prokopenko, D. Arndt, D. Lebrun-Grandie, B. Turcksin, N. Frontiere, J.D. Emberson, and M. Buehlmann
    IJHPCA. DOI:10.1177/10943420241298296. arXiv:2409.10743.
  4. Optimization and Quality Assessment of Baryon Pasting for Intracluster Gas using the Borg Cube Simulation
    F. Kéruzoré, L.E. Bleem, M. Buehlmann, J.D. Emberson, N. Frontiere, S. Habib, K. Heitmann, and P. Larsen
    OJAp, 6, 43 (2023). DOI:10.21105/astro.2306.13807. arXiv:2306.13807.
  5. Numerical Discreteness Errors in Multi-Species Cosmological N-body Simulations
    X. Liu, J.D. Emberson, M. Buehlmann, N. Frontiere, and S. Habib
    MNRAS, 522, 3 (2023). DOI:10.1093/mnras/stad1176. arXiv:2303.00639.
  6. Improving initialization and evolution accuracy of cosmological neutrino simulations
    J.M. Sullivan, J.D. Emberson, S. Habib, and N. Frontiere
    JCAP, 2023, 6, 3 (2023). DOI:10.1088/1475-7516/2023/06/003. arXiv:2302.09134.
  7. Simulating Hydrodynamics in Cosmology with CRK-HACC
    N. Frontiere, J.D. Emberson, M. Buehlmann, J. Adamo, S. Habib, K. Heitmann, and C.-A. Faucher-Giguere
    ApJS, 264, 2 (2023). DOI:10.3847/1538-4365/aca58d. arXiv:2202.02840.
  8. Modeling the Lyman-alpha forest with Eulerian and SPH hydrodynamical methods
    S. Chabanier, J.D. Emberson, Z. Lukic, J. Pulido, S. Habib, E. Rangel, J. Sexton, N. Frontiere, and M. Buehlmann
    MNRAS, 518, 3 (2023). DOI:10.1093/mnras/stac3294. arXiv:2207.05023.
  9. Measuring the evolution of intergalactic gas from z=0 to 5 using the kinematic Sunyaev-Zel’dovich effect
    J. Chaves-Montero, C. Hernandez-Monteagudo, R. Angulo, and J.D. Emberson
    MNRAS, 503, 2 (2021). DOI:10.1093/mnras/staa3782. arXiv:1911.10690.
  10. On the road to percent accuracy III: non-linear reaction of the matter power spectrum to massive neutrinos
    M. Cataneo, J.D. Emberson, D. Inman, J. Harnois-Deraps, and C. Heymans
    MNRAS, 491, 3 (2020). DOI:10.1093/mnras/stz3189. arXiv:1909.02561.
  11. The Borg Cube Simulation: Cosmological Hydrodynamics with CRK-SPH
    J.D. Emberson, N. Frontiere, S. Habib, K. Heitmann, P. Larsen, A. Pope, and H. Finkel
    ApJ, 877, 85 (2019). DOI:10.3847/1538-4357/ab1b31. arXiv:1811.03593.
  12. Cosmological neutrino simulations at extreme scale
    J.D. Emberson, H.-R. Yu, D. Inman, T.-J. Zhang, U.-L. Pen, et al.
    RAA, 17, 085 (2017). DOI:10.1088/1674-4527/17/8/85. arXiv:1611.01545.
  13. Measurement of the Cold Dark Matter-Neutrino Dipole in the TianNu Simulation
    D. Inman, H.-R. Yu, H.-M. Zhu, J.D. Emberson, et al.
    Physical Review D, 95, 083518 (2017). DOI:10.1103/PhysRevD.95.083518. arXiv:1610.09354.
  14. Differential Neutrino Condensation onto Cosmic Structure
    H.-R. Yu, J.D. Emberson, D. Inman, T.-J. Zhang, U.-L. Pen, et al.
    Nature Astronomy, 1, 0143 (2017). DOI:10.1038/s41550-017-0143. arXiv:1609.08968.
  15. Evolution of Low Mass Galactic Subhalos and Dependence on Concentration
    J.D. Emberson, T. Kobayashi, and M.A. Alvarez
    ApJ, 812, 9 (2015). DOI:10.1088/0004-637X/812/1/9. arXiv:1504.00667.
  16. Precision reconstruction of the dark matter-neutrino relative velocity from N-body simulations
    D. Inman, J.D. Emberson, U.-L. Pen, A. Farchi, H.-R. Yu, and J. Harnois-Deraps
    Physical Review D, 92, 023502 (2015). DOI:10.1103/PhysRevD.92.023502. arXiv:1503.07480.
  17. High Performance P3M N-body code: CUBEP3M
    J. Harnois-Deraps, U.-L. Pen, I.T. Iliev, H. Merz, J.D. Emberson, and V. Desjacques
    MNRAS, 436, 540 (2013). DOI:10.1093/mnras/stt1591. arXiv:1208.5098.
  18. The Opacity of the Intergalactic Medium During Reionization: Resolving Small-Scale Structure
    J.D. Emberson, R.M. Thomas, and M.A. Alvarez
    ApJ, 763, 146 (2013). DOI:10.1088/0004-637X/763/2/146. arXiv:1208.3679.
  19. Interpolation in waveform space: enhancing the accuracy of gravitational waveform families using numerical relativity
    K. Cannon, J.D. Emberson, C. Hanna, D. Keppel, and H. Pfeiffer
    Physical Review D, 87, 044008 (2013). DOI:10.1103/PhysRevD.87.044008. arXiv:1211.7095.