SYNTHETIC APERTURE COLOR FINESSE PL CODE
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As the Monte Carlo method is generic, any complex structure can be handled by MCFOST and its use can be extended to other astrophysical objects.

SYNTHETIC APERTURE COLOR FINESSE PL CODE

The code can reproduce most of the observations of disks, including SEDs, scattered light images, IR and mm visibilities, and atomic and molecular line maps. MCFOST is primarily designed to study protoplanetary disks. The code has been strongly optimized for speed. The calculations are done exactly within the limitations of the Monte Carlo noise and machine precision, i.e., no approximation are used in the calculations. It is mainly designed to study the circumstellar environment of young stellar objects, but has been used for a wide range of astrophysical problems. MCFOST is a 3D continuum and line radiative transfer code based on an hybrid Monte Carlo and ray-tracing method. Moreover, FastSpecFit is designed with speed and parallelism in mind, enabling it to deliver robust model fits to tens of millions of targets. FastSpecFit extracts nearly 800 observed- and rest-frame quantities from each target, including light-weighted ages and stellar velocity dispersions based on the underlying stellar continuum line-widths, velocity shifts, integrated fluxes, and equivalent widths for nearly 40 rest-frame ultraviolet, optical, and near-infrared emission lines arising from both star formation and active galactic nuclear activity K-corrections and rest-frame absolute magnitudes and colors and more. The code is currently specialized to handle data from the Dark Energy Spectroscopic Instrument (DESI) Survey, which is amassing spectrophotometry for an unprecedented 40 million extragalactic targets, although the algorithms are general enough to accommodate other upcoming, massively multiplexed spectroscopic surveys. CRPropa3 features a very flexible simulation setup with python steering and shared-memory parallelization.įastSpecFit models the observed-frame optical spectroscopy and broadband photometry of extragalactic targets using physically grounded stellar continuum and emission-line templates. Additionally, the low-energy Galactic propagation can be simulated by solving the transport equation using stochastic differential equations. It enables the user to predict the spectra of UHECR (and of their secondaries), their composition and arrival direction distribution. CRPropa3 can model the deflection in (inter)galactic magnetic fields, the propagation of secondary electromagnetic cascades, and neutrinos for a multitude of scenarios for different source distributions and magnetic environments. It takes into account pion production, photodisintegration, and energy losses by pair production of all relevant isotopes in the ambient low-energy photon fields, as well as nuclear decay. We motivate how PINION performance can be drastically improved and potentially generalized to large-scale simulations.ĬRPropa3, an improved version of CRPropa2 ( ascl:1412.013), provides a simulation framework to study the propagation of ultra-high-energy nuclei up to iron on their voyage through an (extra)galactic environment. We show that while the network's predictions are in good agreement with simulation to redshift z > 7, the network's accuracy suffers for z < 7 primarily due to the oversimplified propagation mask. We evaluate the accuracy of our predictions by analysing the dimensionless power spectra and morphology statistics estimations against C2-Ray results.

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With only five redshift snapshots and a propagation mask as a simplistic approximation of the ionizing photon mean free path, PINION can accurately predict the entire reionization history between z = 6 and 12. We trained PINION on the C2-Ray simulation outputs and a physics constraint on the reionization chemistry equation is enforced. Here we introduce the Physics-Informed neural Network for reIONization (PINION), which can accurately and swiftly predict the complete 4-D hydrogen fraction evolution from the smoothed gas and mass density fields from pre-computed N-body simulation. However, these simulations are computationally expensive and can not readily produce the required scale and resolution simultaneously. Physically motivated results can be simulated with radiative transfer codes. With the advent of the Square Kilometre Array Observatory (SKAO), scientists will be able to directly observe the Epoch of Reionization by mapping the distribution of neutral hydrogen at different redshifts.

Synthetic aperture color finesse pl