I am a NASA Einstein Fellow at Department of Astrophysical Sciences at Princeton University. I develop theory and high-performance simulations to study structure formation on scales from cosmology to star formation. I am at the forefront of research in fuzzy dark matter, which has seen considerably growing interest in the physics and astronomy communities over the last few years. The near-century-old dark matter problem is one of the most intriguing mysteries in modern physics: we do not know the nature of 84 percent of matter in the Universe, yet it is thought to govern cosmic structure and hold galaxies together. Ultralight (fuzzy) dark matter is a promising candidate, and I have created the first cosmological simulations of this type of dark matter fully coupled to baryonic physics. With my work, I can learn about the behavior of the theory and predict how future missions such as the James Webb Space Telescope could reveal the nature of the elusive dark matter particle. A second active research area of mine is the study of turbulent, self-gravitating systems. The theory of compressive turbulence lags behind the study of the incompressible Navier-Stokes equations. I work on developing it to gain physical insight into long-standing open problems, such as the inefficiency of star formation and the fundamental nature of turbulence.
I also develop a variety of new robust, high-performance methods for computational physics. My PhD thesis was completed at Harvard University with my advisor Lars Hernquist on moving mesh magnetohydrodynamics and applications to cosmology and star formation. As part of that work, I invented a new accurate method for solving the magnetohydrodynamic equations on a moving-mesh in the Arepo code. The method preserves mass, momentum, energy, the divergence-free property of the magnetic fields, and Galilean-invariance (exact advection).
I have broad interests in cosmology, galaxy evolution and feedback, black hole physics, structure formation, turbulence in the ISM, alternative theories of dark matter (fuzzy dark matter), numerical methods, computer visualization, and applications of machine learning and computer vision to astronomy.
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.; 2019 MNRAS, submitted
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
Fuzzy Dark Matter Soliton Cores around Supermassive Black Holes
Davies, E.Y.; Mocz, P.; 2019 MNRAS, 492, 5721
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
Heating of Milky Way disc stars by dark matter fluctuations in cold dark matter and fuzzy dark matter paradigms
Church, B.; Mocz, P.; Ostriker, J.P.; 2019 MNRAS, 485, 2861
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
Check out 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
Bayesian nested sampling fitting of exoplanet radial velocity curve with 2 planets
A simple introduction (.pdf) to smoothed-particle hydrodynamics (SPH), if you ever wanted to code your own!