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Feynman
Jul7-04, 03:04 AM
:surprise:
Hello,
I've to calculate the derivate of :

\displaystyle \sigma_{N}(t):=\sum_{i=1}^{N}g_{i}(t)

and g_{i}(t) verify the differential equation:

\displaystyle \frac{d g_i}{d t}(t) =
\sum_{k=1}^{i-1} \frac{1}{k}K(k,i-k) g_{i-k}(t) g_k(t) - \sum_{l=1}^{\infty} \frac{1}{l}K(l,i) g_i(t)g_l(t) .

I've to justify:
\displaystyle \partial_{t}\sigma_{N}(t):= - \sum_{i,j\leqN;i+j>N}\frac{1}{j}K(j,i) g_i(t)g_l(t)
Thanks.

Wong
Jul7-04, 05:49 AM
It sounds like just some kind of troublesome computation...You may like to "visualise" the problem by putting things in an array (much the same way like you put entries to the matrix). Note the similarities in the two sums in your differential equation (both include summand of the form (1/m*K(m, n)g_n(t)g_m(t)). Then put the summands in an array. Say for example if you are taking m to be the row index and n to be the column index then the sum SUM(l from 1 to infinity) {1/l*K(l, i)g_i(t)g_l(t)} would occupy the entire ith column of your array. From this you may easily "visualise" that your proposition is true.