Abstract
We deal with the Sobolev space theory for the stochastic partial differential equation (SPDE) driven by Wiener processes
as well as the SPDE driven by space-time white noise
Here, \(\alpha \in (0,1), \beta < \alpha +1/2\), \(\{w_t^k : k=1,2,\ldots \}\) is a family of independent one-dimensional Wiener processes and \({\dot{W}}\) is a space-time white noise defined on \([0,\infty )\times {\mathbb {R}}^d\). The time non-local operator \(\partial _{t}^{\alpha }\) denotes the Caputo fractional derivative of order \(\alpha \), the function \(\phi \) is a Bernstein function, and the spatial non-local operator \(\phi (\varDelta )\) is the integro-differential operator whose symbol is \(-\phi (|\xi |^2)\). In other words, \(\phi (\varDelta )\) is the infinitesimal generator of the d-dimensional subordinate Brownian motion. We prove the uniqueness and existence results in Sobolev spaces and obtain the maximal regularity results of solutions.
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The authors are very grateful to the referee for valuable comments and suggestions. We could considerably improve the early version of this article due to the referee.
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Auxiliary results
Auxiliary results
In this section, we obtain some sharp upper bounds of space-time fractional derivatives of the fundamental solution q(t, x) related to the equation
First we record some elementary facts on Bernstein functions.
Lemma A.1
Let \(\phi \) be a Bernstein function satisfying Assumption 3.1.
(i) There exists a constant \(c=c(\gamma ,\kappa _0,\delta _0)\) such that for any \(\lambda >0\),
(ii) For any \(\gamma \in (0,1)\), the function \(\phi ^\gamma :=\left( \phi (\cdot )\right) ^\gamma \) is also a Bernstein function with no drift, and it satisfies Assumption 3.1 with \(\gamma \delta _0\) and \(\kappa _0^{\gamma }\), in place of \(\delta _0\) and \(\kappa _0\), respectively.
(iii) Let \(\mu _\gamma \) be the Lévy measure of \(\phi ^\gamma \) (i.e., \(\phi ^{\gamma }(\lambda )=\int _{(0,\infty )} (1-e^{-\lambda t})\mu _{\gamma }(dt)\)), and set
Then
and for any \(f\in C_b^2({\mathbb {R}}^d)\) and \(r>0\), it holds that
Proof
(i) By (3.4) this and the change of variables,
(ii) \(\phi ^\gamma \) is a Bernstein function due to [42, Corollary 3.8 (iii)], and (3.3) easily yields
If we denote drift of \(\phi ^{\gamma }\) by \(b_{\gamma }\) (see (2.4)), it follows that
Hence, we have
(iii) (A.3) follows from [24, Lemma 3.3] (recall that \(\phi ^{\gamma }\) is a Bernstein function with no drift), and the second assertion is a consequence of (2.7). \(\square \)
Recall that p(t, x) is the transition density of the subordinate Brownian motion \(X_t\) with characteristic exponent \(\phi (|\xi |^2)\). Also, for any \(t>0\), and \(x\in {\mathbb {R}}^d\),
where \(\eta _t(ds)\) is the distribution of \(S_t\) (see [2, Sect. 5.3.1]). Thus \(X_t\) is rotationally invariant.
Lemma A.2
(i) There exists a constant \(C=C(d,\delta _0,\kappa _0)\) such that for \((t,x)\in (0,\infty )\times {\mathbb {R}}^d\),
(ii) For any \(m\in {\mathbb {N}}\), there exists a constant \(C=C(d,\delta _0,\kappa _0, m)\) so that for any \((t,x)\in (0,\infty )\times {\mathbb {R}}^d\),
Proof
See [27, Lemma 3.4, Lemma 3.6]. \(\square \)
The following lemma is an extension of [24, Lemma 4.2]. The main difference is that our estimate holds for all \(t>0\). Such result is needed for us to prove estimates of solutions to SPDEs (see, e.g., (3.2)).
Lemma A.3
Let \(\gamma \in (0,1)\) and \(m\in {\mathbb {N}}_0\). Then for any \((t,x)\in (0,\infty )\times {\mathbb {R}}^d\),
Proof
Note first that for any given \(a>0\),
Also note that by (3.3), if \(a^2 \ge \phi ^{-1}(t^{-1})\), then
Therefore, by (A.5),
Hence, to finish the proof, we may assume \(t^{-\gamma }(\phi ^{-1}(t^{-1}))^{\frac{d+m}{2}} \ge \frac{\phi (|x|^{-2})^\gamma }{|x|^{d+m}}\) (equivalently, \(t \phi (|x|^{-2})\le 1\)) and prove
By (A.4) with \(r=|x|/2\),
By (A.3), (A.1) with \(\phi ^{\gamma }\), and (3.4), we have
This together with Lemma A.2 (ii) yields (recall we assume \(t\phi (|x|^{-2})\le 1\))
For III, by the fundamental theorem of calculus and Lemma A.2 (ii),
For the last inequality above, we used \(|x+usy|\ge |x|/2\). By (A.3), and (3.4) with \(r=|x|^{-2}\) and \(R=\rho ^{-2}\),
Therefore, it follows that for \(t \phi (|x|^{-2})\le 1\),
Now we estimate II. By using the integration by parts m-times, we have
Differentiating \(j_{\gamma ,d}(\rho )\), and then using (A.2) and (A.3), for \(k\in {\mathbb {N}}_{0}\) we get
This and Lemma A.2 (ii) yield that
for \(t\phi (|x|^{-2})\le 1\). Hence, the lemma is proved. \(\square \)
Below we provide the proof of Lemma 3.2. The proof is mainly based on [27, Lemma 3.7, Lemma 3.8].
Proof of Lemma 3.2
(i) See [27, Lemma 3.7 (iii)].
(ii) See [27, Lemma 3.8] for (3.6) with arbitrary \(\beta \) and for (3.7) when \(\beta \notin {\mathbb {N}}\). Hence, we only prove (3.7) when \(\beta \in {\mathbb {N}}\). Let \(\beta \in {\mathbb {N}}\), then by [27, Lemma 3.8], we have
For the last inequality, we used \(rt^{-\alpha }\le 2\) whenever \(r\le 2t^{\alpha }\).
(iii) We follow the proof of [27, Lemma 3.8]. By [27, Lemma 3.7], there exist constants \(c,C>0\) depending only on \(\alpha ,\beta \) such that
for \(rt^{-\alpha }\ge 1\), and
for \(rt^{-\alpha }\le 1\). Therefore, we have
Let \(x\in {\mathbb {R}}^d\setminus \{0\}\). Then for any \(r>0\) and \(y\ne 0\) sufficiently close to x, we have
due to Lemma A.3. Using (A.8) and the dominated convergence theorem, we get
Hence, by (A.6) and (A.7) (also recall \(rt^{-\alpha }\le 2\) whenever \(r\le 2t^{\alpha }\)),
By Lemma A.3,
Also, by the change of variables \(rt^{-\alpha }\rightarrow r\),
Hence, (3.8) is proved.
Next we prove (3.9). Assume \(t^\alpha \phi (|x|^{-2})\ge 1\). Again we consider I and II defined in (A.9). For I we have
By Lemma A.3 (recall that \(t^{\alpha }\phi (|x|^{-2})\ge 1\)),
Note that if \(r \le 2(\phi (|x|^{-2}))^{-1}\), then by (3.4)
Thus, using \(r\le 2(\phi (|x|^{-2}))^{-1}\), we get
We also get, by Lemma A.3,
Thus, I is handled. Next we estimate II. By (3.4), we find that
Therefore, by Lemma A.3 and the change of variables \(rt^{-\alpha }\rightarrow r\),
As (A.10), if \(r \le 2t^{\alpha }\), then by (3.4)
Therefore,
This and (A.11) take care of II, and consequently (3.9) is proved.
(iv) See [27, Corollary 3.9] for (3.10). We prove (3.11). By (3.8), (3.9), Fubini’s theorem, and (A.1),
(v) By (3.24) in [27] (or see (34) of [18]),
Hence, by Fubini’s theorem and (A.5) for \(\gamma \in (0,1)\),
Similarly, we get
Thus (v) is also proved. \(\square \)
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Kim, KH., Park, D. & Ryu, J. A Sobolev space theory for the stochastic partial differential equations with space-time non-local operators. J. Evol. Equ. 22, 57 (2022). https://doi.org/10.1007/s00028-022-00813-7
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DOI: https://doi.org/10.1007/s00028-022-00813-7
Keywords
- Stochastic partial differential equations
- Sobolev space theory
- Space-time non-local operators
- Maximal \(L_p\)-regularity
- Space-time white noise