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Simulación Numérica en Astrofísica:
La conexión "teoría-observación"
As in other fields of science, numerical simulations has emerged as the third scientific methodology alongside observation and analytic theory
A key goal of simulations is the rationalization of the various morphological classes of an astrophysical object (jets, e.g.) in terms of a few underlying parameters.
Numerical simulations opens a unique "spectral window" on our theoretical understanding of astrophysical phenomena. Most numerical simulations are designed to elucidate complex dynamical behavior contained within a theoretical model rather than to reproduce an observation, although the latter is certainly an end goal.
Alan Bridle remarked that the Oxford English dictionary defines simulation as "...an attempt to deceive". While it is true that a poorly executed or interpreted numerical simulation may have that effect, this is also true of a poorly executed observation or analytical derivation. Bridle goes on to suggest that we use the word model instead of simulation to avoid this connotation. Within the computational science community, no such semantic difficulties exist, and furthermore, to simulate and to model have very different meanings.
In astronomy, a model is a mathematical description of some object of interest. Models are generally either kinematic or dynamic when describing macroscopic systems (e.g., jets).
The following steps show how numerical models of jets have matured over time; although these are representative of other areas in computational astrophysics:
First
One starts by simulating a simple dynamical model. One uses simple physics (ideal gas)
and the minimum number of spatial dimensions required to capture the essential physics. At this
stage, one generally discovers gross flow structures and the sensitivity of these structures to
initial parameters.
Second
To generalize the dynamical model by adding more physics and/or more spatial dimensions.
At this stage, with sufficient numerical resolution two qualitative barriers are breached, one
observational (the 3D models of jets begin to exhibit complex asymmetric morphologies reminiscent
of actual sources) and one theoretical (the models can exhibit the full range of dynamical
behavior: flow structures, modes of instability...).
Third
Construction of a predictive astrophysical model adding, e.g., an emission model (or
turbulence) so
that numerical models can be compared with observations. One needs to worry about physical
processes occurring on unresolved scales in the simulation and incorporate mathematical models
into the system of equations to deal with them. Once a predictive model is constructed, one
can begin testing the model against observations -in an iterative process - and attempt to
reproduce generic features of an entire class of objects (morphology, spectra, polarization,...).
Fourth
In the final stage the predictive model is applied to a specific source. The outputs at this
stage are synthetic maps, spectra and other observables convolved with telescope response functions
so that meaningful comparisons with observations can be made. This is the stage at which science
in the pure sense can be done. A hypothesis can be falsified or further refined. Predictions can
be made which can be tested by subsequent observations.
The above classification is an obvious oversimplification, because it ignores the fact that observations steadily improve. What was once a predictive model when only crude observations existed becomes downgraded as observations improve.
Referencias:
- M. Norman, in "Astrophysical Jets", ed. by D. Burgarella, M. Livio and C.P. O'Dea, page 211, Cambridge University Press (1993) . - M. Norman, in "Energy Transport in Radio Galaxies and Quasars, ed. by P.E. Hardee, A. H. Bridle, and J.A. Zensus, Astron. Soc. Pac. Conf. Ser., vol. 100. page 405 (1996).