| dc.contributor.author | Clozeau, Nicolas | |
| dc.contributor.author | Singh, Harprit | |
| dc.date.accessioned | 2025-09-08T09:52:23Z | |
| dc.date.available | 2025-09-08T09:52:23Z | |
| dc.date.issued | 2025-09 | |
| dc.identifier.uri | http://publications.mfo.de/handle/mfo/4316 | |
| dc.description | Both authors would like to thank the Oberwolfach Research Fellows (OWRF) program for supporting a research stay during which a part of this work was carried out, as well as Rhys Steele and Lucas Broux for valuable discussions during that stay. HS gratefully acknowledges financial support from the Swiss National Science Foundation (SNSF), grant number 225606. | en_US |
| dc.description.abstract | We show local well-posedness of the g-PAM and the $\phi^{K+1}_2$-equation for $K\geq 1$ on the two-dimensional torus when the coefficient field is random and correlated to the driving noise. In the setting considered here, even when the model in the sense of [Hai14] is stationary, naive use of renormalisation constants in general leads to variance blow-up. Instead, we prove convergence of renormalised models choosing random renormalisation functions analogous to the deterministic variable coefficient setting. The main technical contribution are stochastic estimates on the model in this correlated setting which are obtained by a combination of heat kernel asymptotics, Gaussian integration by parts formulae and Hairer-Quastel type bounds [HQ18]. | en_US |
| dc.language.iso | en_US | en_US |
| dc.publisher | Mathematisches Forschungsinstitut Oberwolfach | en_US |
| dc.relation.ispartofseries | Oberwolfach Preprints;2025-09 | |
| dc.title | Renormalisation of Singular SPDEs with Correlated Coefficients | en_US |
| dc.type | Preprint | en_US |
| dc.rights.license | This document may be downloaded, read, stored and printed for your own use within the limits of § 53 UrhG but it may not be distributed via the internet or passed on to external parties. | en |
| dc.rights.license | Dieses Dokument darf im Rahmen von § 53 UrhG zum eigenen Gebrauch kostenfrei heruntergeladen, gelesen, gespeichert und ausgedruckt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden. | de |
| dc.identifier.doi | 10.14760/OWP-2025-09 | |
| local.scientificprogram | OWRF 2025 | |
| local.series.id | OWP-2025-09 | en_US |
| local.subject.msc | 60 | en_US |
| dc.identifier.ppn | 1936360284 | |