What is the inverse of the covariance operator in Brownian motion?

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SUMMARY

The inverse of the covariance operator in Brownian motion is defined by the equation \( (\tau_1| A^{-1} | \tau_2) = 2D \min(\tau_1, \tau_2) \), as stated in Philippe Martin's book. The relationship \( -\frac{1}{2D} \frac{d^2}{d\tau_1^2} (\tau_1| A^{-1} | \tau_2) = \delta( \tau_1 - \tau_2) \) illustrates the equality of operators \( -\frac{1}{2D} \frac{d^2}{d\tau^2} = A \). The discussion raises questions about the derivative's action on the members of the covariance matrix \( 1/A \) and its implications for Dirac distributions.

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Heidi
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in fact the answer is given in the book (written by philippe Martin).
we have
$$ (\tau_1| A^{-1} | \tau_2) = 2D \ min(\tau_1 ,\tau_2) = 2D(\tau_1 \theta (\tau_2 -\tau_1)+\tau_2 \theta (\tau_1 -\tau_2))$$
So
$$-1/2D \frac{d^2}{d\tau_1^2} (\tau_1| A^{-1} | \tau_2) = \delta( \tau_1 - \tau_2) $$

the author writes then that we see that we have the operators equality
$$-1/2D \frac{d^2}{d\tau^2} = A$$

is it obvious for you?
thanks

Edit:
does the derivative act in the same way on every members of the
covariant matrix 1/A? in this case we could consider that we have the product ot A and 1/A giving a dirac.
 
Last edited:
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I found an interesting answer to a similar question here
have you more explanations?
 
Last edited:

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