{
  "abstract": "We construct a class of novel tamed schemes for superlinear stochastic partial differential equations (SPDEs), including the stochastic Allen–Cahn equation driven by either multiplicative or additive noise. The schemes preserve the same Lyapunov structure as the original system, and we rigorously establish their longtime unconditional stability. Furthermore, we prove that the corresponding Galerkin-based fully discrete tamed schemes inherit the unique ergodicity of the underlying SPDEs and achieve optimal strong convergence rates in both the multiplicative- and additive-noise cases.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Mathematics & National Center for Applied Mathematics Shenzhen (NCAMS) & Shenzhen International Center for Mathematics, Southern University of Science and Technology, Shenzhen, 518055, People’s Republic of China",
    "School of Mathematical Science, Eastern Institute of Technology, Ningbo, 315200, People’s Republic of China"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Zhihui Liu",
      "orcid": "0000-0003-0890-623X"
    },
    {
      "affs": [
        1
      ],
      "name": "Jie Shen",
      "orcid": "0000-0002-4885-5732"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/cadnpfqk02qzz.bib",
  "cited_by": 13,
  "doi": "10.1007/s10915-026-03484-5",
  "fulltext_url": null,
  "id": "cadnpfqk02qzz",
  "issns": [
    "0885-7474",
    "1573-7691"
  ],
  "landing_url": "https://doi.org/10.1007/s10915-026-03484-5",
  "language": "en",
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2612|Numerical Solvers for Ordinary Differential Equations"
    ]
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  "openalex": "W4416043753",
  "pdf_url": "https://link.springer.com/content/pdf/10.1007/s10915-026-03484-5.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-23",
  "publisher": "Springer Science+Business Media",
  "ris": "https://research.draconitic.com/paper/cadnpfqk02qzz.ris",
  "sources": [
    {
      "first_seen": "2026-11-07T13:20:42Z",
      "native_id": "W4416043753",
      "source": "openalex",
      "url": "https://doi.org/10.1007/s10915-026-03484-5"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "openalex:2612|Numerical Solvers for Ordinary Differential Equations",
      "subfield": "numerical-analysis"
    }
  ],
  "title": "Numerical Ergodicity and Optimal Strong Error Estimates for a Class of Novel Tamed Schemes to Superlinear SPDEs",
  "title_text": "Numerical Ergodicity and Optimal Strong Error Estimates for a Class of Novel Tamed Schemes to Superlinear SPDEs",
  "type": "peer-reviewed",
  "updated_at": "2026-11-09T13:21:00Z",
  "url": "https://research.draconitic.com/paper/cadnpfqk02qzz",
  "venue": "Journal of Scientific Computing",
  "versions": []
}