46 research outputs found
Cosmic cookery : making a stereoscopic 3D animated movie.
This paper describes our experience making a short stereoscopic movie visualizing the development of structure in
the universe during the 13.7 billion years from the Big Bang to the present day. Aimed at a general audience for
the Royal Society's 2005 Summer Science Exhibition, the movie illustrates how the latest cosmological theories
based on dark matter and dark energy are capable of producing structures as complex as spiral galaxies and
allows the viewer to directly compare observations from the real universe with theoretical results. 3D is an
inherent feature of the cosmology data sets and stereoscopic visualization provides a natural way to present the
images to the viewer, in addition to allowing researchers to visualize these vast, complex data sets.
The presentation of the movie used passive, linearly polarized projection onto a 2m wide screen but it was
also required to playback on a Sharp RD3D display and in anaglyph projection at venues without dedicated
stereoscopic display equipment. Additionally lenticular prints were made from key images in the movie. We
discuss the following technical challenges during the stereoscopic production process; 1) Controlling the depth
presentation, 2) Editing the stereoscopic sequences, 3) Generating compressed movies in display speci¯c formats.
We conclude that the generation of high quality stereoscopic movie content using desktop tools and equipment
is feasible. This does require careful quality control and manual intervention but we believe these overheads
are worthwhile when presenting inherently 3D data as the result is signi¯cantly increased impact and better
understanding of complex 3D scenes
A unified multiwavelength model of galaxy formation
We present a new version of the GALFORM semi-analytical model of galaxy formation. This brings together several previous developments of GALFORM into a single unified model, including a different initial mass function (IMF) in quiescent star formation and in starbursts, feedback from active galactic nuclei supressing gas cooling in massive halos, and a new empirical star formation law in galaxy disks based on their molecular gas content. In addition, we have updated the cosmology, introduced a more accurate treatment of dynamical friction acting on satellite galaxies, and updated the stellar population model. The new model is able to simultaneously explain both the observed evolution of the K-band luminosity function and stellar mass function, and the number counts and redshift distribution of sub-mm galaxies selected at 850μm. This was not previously achieved by a single physical model within the ΛCDM framework, but requires having an IMF in starbursts that is somewhat top-heavy. The new model is tested against a wide variety of observational data covering wavelengths from the far-UV to sub-mm, and redshifts from z = 0 to z = 6, and is found to be generally successful. These observations include the optical and near-IR luminosity functions, HI mass function, fraction of early type galaxies, Tully-Fisher, metallicity-luminosity and size-luminosity relations at z = 0, as well as far-IR number counts, and far-UV luminosity functions at z ∼ 3 − 6. Discrepancies are however found in galaxy sizes and metallicities at low luminosities, and in the abundance of low mass galaxies at high-z, suggesting the need for a more sophisticated model of supernova feedback
Non-linear CMB lensing with neutrinos and baryons: FLAMINGO simulations versus fast approximations
Weak lensing of the cosmic microwave background is rapidly emerging as a powerful probe of neutrinos, dark energy, and newphysics. We present a fast computation of the non-linear CMB lensing power spectrum that combines non-linear perturbationtheory at early times with powerspectrum emulation using cosmologicalsimulations at late times.Comparing our calculation withlight-cones from the FLAMINGO 5.6 Gpc cube dark-matter-only simulation, we confirm its accuracy to 1 per cent (2 per cent)up to multipoles L = 3000 (L = 5000) for a νCDM cosmology consistent with current data. Clustering suppression due tosmall-scale baryonic phenomena such as feedback from active galactic nuclei can reduce the lensing power by ∼ 10 per cent.To our perturbation theory and emulator-based calculation, we add SP(k), a new fitting function for this suppression, andconfirm its accuracy compared to the FLAMINGO hydrodynamic simulations to 4 per cent at L = 5000, with similar accuracy formassive neutrino models. We further demonstrate that scale-dependent suppression due to neutrinos and baryons approximatelyfactorize, implying that a careful treatment of baryonic feedback can limit biasing neutrino mass constraints
The FLAMINGO project: revisiting the tension and the role of baryonic physics
A number of recent studies have found evidence for a tension between
observations of large-scale structure (LSS) and the predictions of the standard
model of cosmology with the cosmological parameters fit to the cosmic microwave
background (CMB). The origin of this ' tension' remains unclear, but
possibilities include new physics beyond the standard model, unaccounted for
systematic errors in the observational measurements and/or uncertainties in the
role that baryons play. Here we carefully examine the latter possibility using
the new FLAMINGO suite of large-volume cosmological hydrodynamical simulations.
We project the simulations onto observable harmonic space and compare with
observational measurements of the power and cross-power spectra of cosmic
shear, CMB lensing, and the thermal Sunyaev-Zel'dovich (tSZ) effect. We explore
the dependence of the predictions on box size and resolution, cosmological
parameters including the neutrino mass, and the efficiency and nature of
baryonic 'feedback'. Despite the wide range of astrophysical behaviours
simulated, we find that baryonic effects are not sufficiently large to remove
the tension. Consistent with recent studies, we find the CMB lensing
power spectrum is in excellent agreement with the standard model, whilst the
cosmic shear power spectrum, tSZ effect power spectrum, and the cross-spectra
between shear, CMB lensing, and the tSZ effect are all in varying degrees of
tension with the CMB-specified standard model. These results suggest that some
mechanism is required to slow the growth of fluctuations at late times and/or
on non-linear scales, but that it is unlikely that baryon physics is driving
this modification.Comment: 26 pages, 12 figures, MNRAS, accepted with minor revision
The FLAMINGO project: cosmological hydrodynamical simulations for large-scale structure and galaxy cluster surveys
We introduce the Virgo Consortium's FLAMINGO suite of hydrodynamical
simulations for cosmology and galaxy cluster physics. To ensure the simulations
are sufficiently realistic for studies of large-scale structure, the subgrid
prescriptions for stellar and AGN feedback are calibrated to the observed
low-redshift galaxy stellar mass function and cluster gas fractions. The
calibration is performed using machine learning, separately for three
resolutions. This approach enables specification of the model by the
observables to which they are calibrated. The calibration accounts for a number
of potential observational biases and for random errors in the observed stellar
masses. The two most demanding simulations have box sizes of 1.0 and 2.8 Gpc
and baryonic particle masses of and ,
respectively. For the latter resolution the suite includes 12 model variations
in a 1 Gpc box. There are 8 variations at fixed cosmology, including shifts in
the stellar mass function and/or the cluster gas fractions to which we
calibrate, and two alternative implementations of AGN feedback (thermal or
jets). The remaining 4 variations use the unmodified calibration data but
different cosmologies, including different neutrino masses. The 2.8 Gpc
simulation follows particles, making it the largest ever
hydrodynamical simulation run to . Lightcone output is produced on-the-fly
for up to 8 different observers. We investigate numerical convergence, show
that the simulations reproduce the calibration data, and compare with a number
of galaxy, cluster, and large-scale structure observations, finding very good
agreement with the data for converged predictions. Finally, by comparing
hydrodynamical and `dark-matter-only' simulations, we confirm that baryonic
effects can suppress the halo mass function and the matter power spectrum by up
to per cent.Comment: 44 pages, 23 figures. Accepted for publication in MNRAS. V3 includes
changes made in published version: jet simulations were redone to fix a bug,
but the differences are nearly invisible. For visualizations, see the
FLAMINGO website at https://flamingo.strw.leidenuniv.nl
FLAMINGO: Calibrating large cosmological hydrodynamical simulations with machine learning
To fully take advantage of the data provided by large-scale structure
surveys, we need to quantify the potential impact of baryonic effects, such as
feedback from active galactic nuclei (AGN) and star formation, on cosmological
observables. In simulations, feedback processes originate on scales that remain
unresolved. Therefore, they need to be sourced via subgrid models that contain
free parameters. We use machine learning to calibrate the AGN and stellar
feedback models for the FLAMINGO cosmological hydrodynamical simulations. Using
Gaussian process emulators trained on Latin hypercubes of 32 smaller-volume
simulations, we model how the galaxy stellar mass function and cluster gas
fractions change as a function of the subgrid parameters. The emulators are
then fit to observational data, allowing for the inclusion of potential
observational biases. We apply our method to the three different FLAMINGO
resolutions, spanning a factor of 64 in particle mass, recovering the observed
relations within the respective resolved mass ranges. We also use the
emulators, which link changes in subgrid parameters to changes in observables,
to find models that skirt or exceed the observationally allowed range for
cluster gas fractions and the stellar mass function. Our method enables us to
define model variations in terms of the data that they are calibrated to rather
than the values of specific subgrid parameters. This approach is useful,
because subgrid parameters are typically not directly linked to particular
observables, and predictions for a specific observable are influenced by
multiple subgrid parameters.Comment: 24 pages, 10 figures (Including the appendix). Submitted to MNRAS.
For visualisations, see the FLAMINGO website at
https://flamingo.strw.leidenuniv.nl
FLAMINGO: calibrating large cosmological hydrodynamical simulations with machine learning.
To fully take advantage of the data provided by large-scale structure surveys, we need to quantify the potential impact of baryonic effects, such as feedback from active galactic nuclei (AGN) and star formation, on cosmological observables. In simulations, feedback processes originate on scales that remain unresolved. Therefore, they need to be sourced via subgrid models that contain free parameters. We use machine learning to calibrate the AGN and stellar feedback models for the FLAMINGO (Fullhydro Large-scale structure simulations with All-sky Mapping for the Interpretation of Next Generation Observations) cosmological hydrodynamical simulations. Using Gaussian process emulators trained on Latin hypercubes of 32 smaller volume simulations, we model how the galaxy stellar mass function (SMF) and cluster gas fractions change as a function of the subgrid parameters. The emulators are then fit to observational data, allowing for the inclusion of potential observational biases. We apply our method to the three different FLAMINGO resolutions, spanning a factor of 64 in particle mass, recovering the observed relations within the respective resolved mass ranges. We also use the emulators, which link changes in subgrid parameters to changes in observables, to find models that skirt or exceed the observationally allowed range for cluster gas fractions and the SMF. Our method enables us to define model variations in terms of the data that they are calibrated to rather than the values of specific subgrid parameters. This approach is useful, because subgrid parameters are typically not directly linked to particular observables, and predictions for a specific observable are influenced by multiple subgrid parameters. [Abstract copyright: © 2023 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society.