I am a computational research scientist and software engineer at the Flatiron Institute, Center for Computational Astrophysics interested in developing software for scalable high-performance multi-physics simulations integrated with modern AI techniques. Prior to joining the foundation, I was a computational physicist at the Lawrence Livermore National Laboratory where I developed high-performance multi-physics simulation code on heterogenous architectures, in particular high-order Arbitrary Lagrangian-Eulerian (ALE) finite element methods for magnetohydrodynamics (MHD) simulations, as part of the Multiphysics on Advanced Platforms Project (MAPP). I also have in interest in simulating cosmological dark matter models, such as fuzzy dark matter.
I completed my PhD in Astrophysics 2017 at Harvard University under the advisorship of Lars Hernquist. During my PhD, I designed a finite volume moving mesh MHD code, and applied it to study structure formation and magnetic field growth in the interstellar medium and in cosmological settings. My physics modules were implemented into the Arepo code. I received an AB in Mathematics and Astrophysics in 2012 from Harvard.
My research interests include multi-physics simulations, cosmology, galaxy evolution, black hole physics, turbulence, numerical methods, computer visualization, and machine learning/AI.
I grew up in Hawaii and I enjoy spending time in the outdoors.
📝 I maintain a blog on introductory tutorials to scientific computing with Python, accessible at the undergraduate level. You can follow me on Medium and Twitter.
Download my curriculum vitae (CV) [.pdf]
Cosmological Structure Formation and Soliton Phase Transition in Fuzzy Dark Matter with Axion Self-Interactions
Mocz, P.; Fialkov, A.; Vogelsberger, M.; Boylan-Kolchin, M; Chavanis, P.H.; Amin, M.A.; Bose, S.; Dome, T.; Hernquist, L.; Lancaster, L.; Notis, M.; Painter, C.; Robles, V.H.; Zavala, J.; 2023 MNRAS, 521, 2608
Toward Cosmological Simulations of Dark Matter on Quantum Computers
Mocz, P.; Szasz, A.; 2021 ApJ, 910, 29
Galaxy Formation with BECDM - II. Cosmic Filaments and First Galaxies
Mocz, P.; Fialkov, A.; Vogelsberger, M.; Becerra, F.; Shen, X.; Robles, V.H.; Amin, M.A.; Zavala, J.; Boylan-Kolchin, M.; Bose, S.; Marinacci, F.; Chavanis, P.H.; Lancaster, K.; Hernquist, L.; 2021 MNRAS, 494, 2021
First star-forming structures in fuzzy cosmic filaments
Mocz, P.; Fialkov A.; Vogelsberger, M.; Becerra, F.; Amin, M.A.; Bose, S.; Boylan-Kolchin, M.; Chavanis, P.H.; Hernquist, L.; Lancaster, L.; Marinacci, M.; Robles, V.H.; Zavala, J; 2019 Phys. Rev. Lett. (Editors' Selection) 123, 14
A Markov model for non-lognormal density distributions in compressive isothermal turbulence
Mocz, P.; Burkhart, B.; 2019 ApJL, 884, 2
Formation, Gravitational Clustering and Interactions of Non-relativistic Solitons in an Expanding Universe
Amin, M.; Mocz, P.; 2019 Phys. Rev. D, 100, 6
Star formation from dense shocked regions in supersonic isothermal magnetoturbulence
Mocz, P.; Burkhart, B.; 2018 MNRAS, 480, 3916
On the Schrodinger-Poisson--Vlasov-Poisson correspondence
Mocz, P.; Lancaster, L.; Fialkov A.; Becerra, F.; Chavanis, P.H.; 2018 PhRvD, 97, 3519
Galaxy Formation with BECDM - I. Turbulence and relaxation of idealised haloes
Mocz, P.; Vogelsberger, M.; Robles, V.; Zavala J.; Boylan-Kolchin, M.; Fialkov A.; Hernquist, L.; 2017 MNRAS, 471, 4559
Moving mesh simulations of star forming cores in magneto-gravo-turbulence
Mocz, P.; Burkhart, B.; Hernquist, L.; McKee, C.; Springel, V.; 2017 ApJ, 838, 1
Interested in scientific computing? Check out my ~100 line Python tutorials on computational astro/physics at https://philip-mocz.medium.com/
See the collection at http://april1arxiv.github.io
PAVOREAL (PArellel VOlume REndering ALgorithm) on GPUs
Explore the shock structure in the Euler and MHD Riemann problems
Paper on my simulations of a cosmic-ray pressure gradient instability in a turbulent MHD environment at a shock interface, as part of my project for Astronomy 253 (plasma physics). Read the report (.pdf) and download the Matlab code
Bayesian nested sampling fitting of exoplanet radial velocity curve with 2 planets
A simple introduction (.pdf) to smoothed-particle hydrodynamics (SPH), and writing your own code
Computational Physicist
orcid.org/0000-0001-6631-2566
Philip Mocz pronounced: