Super-resolution emulator of cosmological simulations using deep physical models
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Super-resolution emulator of cosmological simulations using deep physical models. / Ramanah, Doogesh Kodi; Charnock, Tom; Villaescusa-Navarro, Francisco; Wandelt, Benjamin D.
In: Monthly Notices of the Royal Astronomical Society, Vol. 495, No. 4, 23.05.2020, p. 4227-4236.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Super-resolution emulator of cosmological simulations using deep physical models
AU - Ramanah, Doogesh Kodi
AU - Charnock, Tom
AU - Villaescusa-Navarro, Francisco
AU - Wandelt, Benjamin D.
PY - 2020/5/23
Y1 - 2020/5/23
N2 - We present an extension of our recently developed Wasserstein optimized model to emulate accurate high-resolution (HR) features from computationally cheaper low-resolution (LR) cosmological simulations. Our deep physical modelling technique relies on restricted neural networks to perform a mapping of the distribution of the LR cosmic density field to the space of the HR small-scale structures. We constrain our network using a single triplet of HR initial conditions and the corresponding LR and HR evolved dark matter simulations from the QUIJOTE suite of simulations. We exploit the information content of the HR initial conditions as a well-constructed prior distribution from which the network emulates the small-scale structures. Once fitted, our physical model yields emulated HR simulations at low computational cost, while also providing some insights about how the large-scale modes affect the small-scale structure in real space.
AB - We present an extension of our recently developed Wasserstein optimized model to emulate accurate high-resolution (HR) features from computationally cheaper low-resolution (LR) cosmological simulations. Our deep physical modelling technique relies on restricted neural networks to perform a mapping of the distribution of the LR cosmic density field to the space of the HR small-scale structures. We constrain our network using a single triplet of HR initial conditions and the corresponding LR and HR evolved dark matter simulations from the QUIJOTE suite of simulations. We exploit the information content of the HR initial conditions as a well-constructed prior distribution from which the network emulates the small-scale structures. Once fitted, our physical model yields emulated HR simulations at low computational cost, while also providing some insights about how the large-scale modes affect the small-scale structure in real space.
KW - methods: numerical
KW - methods: statistical
KW - dark matter
KW - large-scale structure of Universe
U2 - 10.1093/mnras/staa1428
DO - 10.1093/mnras/staa1428
M3 - Journal article
VL - 495
SP - 4227
EP - 4236
JO - Royal Astronomical Society. Monthly Notices
JF - Royal Astronomical Society. Monthly Notices
SN - 0035-8711
IS - 4
ER -
ID: 246729157