Rupert Croft
Professor | Carnegie Mellon University
Pittsburgh, PA, UNITED STATES
Rupert Croft's research includes the structure of the universe, galaxy formation, and the measurement of cosmological parameters.
Biography
Rupert Croft is a professor in the Physics Department at Carnegie Mellon University. His research interests include the large-scale structure of the universe, galaxy formation, and the measurement of cosmological parameters. Croft has a DPhil from Oxford University.
Areas of Expertise (5)
Physical Chemistry (incl. Structural)
Organic Chemistry
Astronomical and Space Sciences
Atomic, Molecular, Nuclear, Particle and Plasma Physics
Quantum Physics
Media Appearances (1)
Milky Way-like galaxies may have existed in the early universe
Phys.org online
2015-08-05
Di Matteo and fellow CMU Physics Professor Rupert Croft have long been at the forefront of simulation cosmology, completing some of the largest simulations ever created. Their current simulation, called BlueTides, is 100 times larger than previous simulations. It was so large that it monopolized all of the National Science Foundation (NSF) supercomputer BlueWater's memory and almost 1 million CPUs in order to complete the simulation.
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Education (2)
Oxford University: Ph.D., Astrophysics 1995
Imperial College: B.Sc., Physics 1991
Links (3)
Articles (5)
Modeling quasar proximity zones in a realistic cosmological environment with a self-consistent light curve
Monthly Notices of the Royal Astronomical Society2024 We study quasar proximity zones in a simulation that includes a self-consistent quasar formation model and realistic intergalactic medium (IGM) environments. The quasar host halo is 1013 M⊙ at z = 6, more massive than typical halos studied in previous work. Between 6 < z < 7.5, the quasar luminosity varies rapidly, with a mean magnitude of MUV, mean = −24.8 and the fluctuation reaching up to two orders of magnitude. Using this light curve to post-process the dense environment around the quasar, we find that the proximity zone size (Rp) ranges between 0.5 and 5 pMpc. We show that the light curve variability causes a similar degree of scatter in Rp as does the density fluctuation, both of which result in a standard deviation of ∼0.3 pMpc.
AI-assisted super-resolution cosmological simulations III: time evolution
Monthly Notices of the Royal Astronomical Society2024 In this work, we extend our recently developed super-resolution (SR) model for cosmological simulations to produce fully time-consistent evolving representations of the particle phase-space distribution. We employ a style-based constrained generative adversarial network (StyleGAN), where the changing cosmic time is an input style parameter to the network. The matter power spectrum and halo mass function agree well with results from high-resolution N-body simulations over the full trained redshift range (10 ≤ z ≤ 0). Furthermore, we assess the temporal consistency of our SR model by constructing halo merger trees.
High-redshift supermassive black hole mergers in simulations with dynamical friction modelling
Monthly Notices of the Royal Astronomical Society2024 In the near future, projects like Laser Interferometer Space Antenna (LISA) and pulsar timing arrays are expected to detect gravitational waves from mergers between supermassive black holes, and it is crucial to precisely model the underlying merger populations now to maximize what we can learn from this new data. Here, we characterize expected high-redshift (z > 2) black hole mergers using the very large volume Astrid cosmological simulation, which uses a range of seed masses to probe down to low-mass black holes (BHs), and directly incorporates dynamical friction so as to accurately model the dynamical processes that bring black holes to the galaxy centre where binary formation and coalescence will occur.
The CAMELS project: Expanding the galaxy formation model space with new ASTRID and 28-parameter TNG and SIMBA suites
The Astrophysical Journal2023 We present CAMELS-ASTRID, the third suite of hydrodynamical simulations in the Cosmology and Astrophysics with MachinE Learning (CAMELS) project, along with new simulation sets that extend the model parameter space based on the previous frameworks of CAMELS-TNG and CAMELS-SIMBA, to provide broader training sets and testing grounds for machine-learning algorithms designed for cosmological studies. CAMELS-ASTRID employs the galaxy formation model following the ASTRID simulation and contains 2124 hydrodynamic simulation runs that vary three cosmological parameters (Ω m, σ 8, Ω b) and four parameters controlling stellar and active galactic nucleus (AGN) feedback.
PRIYA: a new suite of Lyman-α forest simulations for cosmology
Journal of Cosmology and Astroparticle Physics2023 We present the PRIYA suite of cosmological simulations, based on the code and hydrodynamic model of the ASTRID simulation, and designed for cosmological analyses of the Lyman-α forest. Our simulation suite spans a 9-dimensional parameter space, including 4 cosmological parameters and 5 astrophysical/thermal parameters. We have run 48 low fidelity simulations with 1536 3 particles in a 120 Mpc/h box and 3 high fidelity simulations with 3072 3 particles in a 120 Mpc/h box. All our simulations include a full physics model for galaxy formation, including supernova and AGN feedback, and thus also contain a realistic population of DLAs. We advance on earlier simulations suites by larger particle loads, by incorporating new physical models for patchy hydrogen and helium reionization, and by self-consistently incorporating a model for AGN feedback.
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