24.02.2013 Views

On the Stochastic Cahn-Hilliard/Allen-Cahn equation - Isaac Newton ...

On the Stochastic Cahn-Hilliard/Allen-Cahn equation - Isaac Newton ...

On the Stochastic Cahn-Hilliard/Allen-Cahn equation - Isaac Newton ...

SHOW MORE
SHOW LESS

You also want an ePaper? Increase the reach of your titles

YUMPU automatically turns print PDFs into web optimized ePapers that Google loves.

Regularity of <strong>the</strong> distribution (continued)<br />

For σ = 1, <strong>the</strong> ”main” term is ɛ1−d/4 since 2 − d/2 > 1 − d/4.<br />

Thus <strong>the</strong> truncated sequence ũn is such that for t > 0,<br />

� t �<br />

|Dz,r ũn(x, t)| 2 dzdr > 0 a.s.<br />

(iv) For σ which does not vanish, write<br />

0<br />

O<br />

Dz,r ũn(x, t) = σ(ũn(x, t))vn(z, r)<br />

where vn(z, r) behaves as <strong>the</strong> previous Malliavin derivative (when σ = 1)<br />

for t > 0,<br />

� t<br />

0<br />

�<br />

O<br />

|Dz,r ũn(x, t)| 2 dzdr > 0 a.s.<br />

ũn(x, t) has a density (Bouleau-Hirsch criterion)<br />

u = ũn on Ωn and P(Ωn) → 1 implies that u(x, t) has a density.<br />

A. Millet (SAMM, Paris 1 and PMA) <strong>Cahn</strong>-<strong>Hilliard</strong>/<strong>Allen</strong>-<strong>Cahn</strong> <strong>equation</strong> Workshop <strong>Stochastic</strong> PDEs 18 / 18

Hooray! Your file is uploaded and ready to be published.

Saved successfully!

Ooh no, something went wrong!