Timeline for General systems of linear differential equations with variable coefficients
Current License: CC BY-SA 3.0
4 events
| when toggle format | what | by | license | comment | |
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| Feb 24, 2014 at 9:40 | comment | added | PLG | Rather well: since an analytical closed form expression for the fundamental matrix is available, I can for example easily see the solution dependency on, say, certain parameters. If the problem comes up in a particular application, it is most likely that the values that $A(t)$ take have a meaning (the parameters). Then, the consequences of changing these parameters are more easily obtained: a good example is 1D quantum random walks. Having a Bessel function solution enables one to demonstrate balistic spread. This is much harder to justify from a numerical fit... | |
| Feb 22, 2014 at 17:23 | comment | added | username | @Pierre-LouisGiscard on the example I suggest, how does that work for you? | |
| Feb 22, 2014 at 15:05 | comment | added | PLG | Good point. I think I like closed form expressions for what they are, not for what you can do with them. I don't quite agree with your second point however, because I always found it easier to understand how the solution behaves from a closed form expression than from a numerical evaluation. | |
| Feb 21, 2014 at 15:08 | history | answered | username | CC BY-SA 3.0 |