Read e-book online Analytical methods for Markov equations PDF

By Lorenzi, Luca

ISBN-10: 1315355620

ISBN-13: 9781315355627

ISBN-10: 1482243326

ISBN-13: 9781482243321

ISBN-10: 1482243342

ISBN-13: 9781482243345

The moment variation of this publication has a brand new identify that extra adequately displays the desk of contents. during the last few years, many new effects were confirmed within the box of partial differential equations. This version takes these new effects into consideration, particularly the learn of nonautonomous operators with unbounded coefficients, which has bought nice awareness. also, this variation is the 1st to take advantage of a unified method of include the recent ends up in a novel place.

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Proper choices of the function ω allow to prove precise estimates of the Green function g. , A = div(Q∇) + b, ∇ + c and the case when A = (1 + |x|α )∆ + c, assuming that at least α > 0 or c is negative and unbounded. ❊ Study of both the invariant measures associated with {T (t)} and of its regularity properties in Lp -spaces related to this measure. By definition, an invariant measure is a probability measure µ such that f dµ, T (t)f dµ = RN RN t > 0, f ∈ Bb (RN ). The spaces Lp (RN , µ) are the “right” Lp -spaces for {T (t)}.

In the first one we define the function g and prove some of its properties. Finally, in Step 2, we complete the proof. Step 1. 1. We extend the function gk to (0, +∞) × RN × RN with value zero for x, y ∈ / Bk and still denote by gk the so obtained function. A straightforward computation shows that, for any fixed t ∈ (0, +∞) and x, y ∈ RN , the sequence {gk (t, x, y)} is increasing. 2. Recalling that, for any t > 0 and x ∈ Bk , the function gk+1 (t, x, ·) − gk (t, x, ·) is continuous in Bk , we conclude that gk+1 ≥ gk in (0, +∞) × Bk × Bk , implying that the sequence {gk } is pointwise increasing in (0, +∞) × RN × RN .

In the case when c ≡ 0, the semigroup {T (t)} is associated with a transition function. This leads to the existence of a Markov process associated with {T (t)}. 5. Of course, there is a huge literature on the subject. Here, we just recall the definitions and the main properties of the Markov processes associated with the semigroup. Among them, we introduce the Dynkin formula and the link with the theory of differential stochastic equations. Most of the results of this chapter are taken from [197].

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Analytical methods for Markov equations by Lorenzi, Luca


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