A big part of physics is the art of approximation. It's almost never possible to have a perfectly 'exact' description of a situation.
For instance, in introductory physics we have students work a number of problems involving objects falling under the influence of gravity. Air resistance is rarely considered, and if were to be considered, approximations of some sort would be required, since there's no complete theory of turbulence.
Everything that involves a complex computer simulation, say molecular dynamics or fluid flow, involves approximations.
Even when you look at the simplest calculations involving elementary particles, all of these are intellectually justified by the renormalization concept that assumes that, at some very small length scale, the laws of physics that we know will break down -- but we know that QED, QCD and such are very good approximations.
The first virtue of an approximation is that it captures the qualitative character of a problem, after that, it's a matter of adding an increasing number of decimal places of quantitative accuracy.
More sophisticated models of radiation transport exist (these are critical to the development of H-bombs, etc.) and an obvious follow-up to this paper would be to use a better radiation transport code to validate the result.
> The first virtue of an approximation is that it captures the qualitative character of a problem, after that, it's a matter of adding an increasing number of decimal places of quantitative accuracy.
Unless the approximate model diverges from the actual process in extreme cases, such as very high, very low values.
One thing comes to my mind, if only slightly related: `Reciprocity failure' [1], an effect in photography, where the usual model of relationship between shutter speed (exposure time), photo material sensitivity and lightness of the scene photographed diverges from reality for extreme values.
In such cases, increasing precision of the model isn't just a numerical task (variable precision, iteration count, etc.).
For instance, in introductory physics we have students work a number of problems involving objects falling under the influence of gravity. Air resistance is rarely considered, and if were to be considered, approximations of some sort would be required, since there's no complete theory of turbulence.
Everything that involves a complex computer simulation, say molecular dynamics or fluid flow, involves approximations.
Even when you look at the simplest calculations involving elementary particles, all of these are intellectually justified by the renormalization concept that assumes that, at some very small length scale, the laws of physics that we know will break down -- but we know that QED, QCD and such are very good approximations.
The first virtue of an approximation is that it captures the qualitative character of a problem, after that, it's a matter of adding an increasing number of decimal places of quantitative accuracy.
More sophisticated models of radiation transport exist (these are critical to the development of H-bombs, etc.) and an obvious follow-up to this paper would be to use a better radiation transport code to validate the result.