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020 _a9783031695865
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024 7 _a10.1007/978-3-031-69586-5
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050 4 _aQA274-274.9
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072 7 _aMAT029000
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100 1 _aGoodair, Daniel.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_983215
245 1 0 _aStochastic Calculus in Infinite Dimensions and SPDEs
_h[electronic resource] /
_cby Daniel Goodair, Dan Crisan.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2024.
300 _aX, 136 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringerBriefs in Mathematics,
_x2191-8201
505 0 _a1 Introduction -- 2 Stochastic Calculus in Infinite Dimensions -- 3 Stochastic Differential Equations in Infinite Dimensions -- 4 A Toolbox for Nonlinear SPDEs -- 5 Existence Theory for Nonlinear SPDEs and the Stochastic Navier-Stokes Equations -- A Appendix -- References -- Index .
520 _aIntroducing a groundbreaking framework for stochastic partial differential equations (SPDEs), this work presents three significant advancements over the traditional variational approach. Firstly, Stratonovich SPDEs are explicitly addressed. Widely used in physics, Stratonovich SPDEs have typically been converted to Ito form for mathematical treatment. While this conversion is understood heuristically, a comprehensive treatment in infinite dimensions has been lacking, primarily due to insufficient rigorous results on martingale properties. Secondly, the framework incorporates differential noise, assuming the noise operator is only bounded from a smaller Hilbert space into a larger one, rather than within the same space. This necessitates additional regularity in the Ito form to solve the original Stratonovich SPDE. This aspect has been largely overlooked, despite the increasing popularity of gradient-dependent Stratonovich noise in fluid dynamics and regularisation by noise studies. Lastly, the framework departs from the explicit duality structure (Gelfand Triple), which is typically expected in the study of analytically strong solutions. This extension builds on the classical variational framework established by Röckner and Pardoux, advancing it in all three key aspects. Explore this innovative approach that not only addresses existing challenges but also opens new avenues for research and application in SPDEs. .
650 0 _aStochastic processes.
_976770
650 0 _aCalculus.
_983216
650 1 4 _aStochastic Calculus.
_983217
700 1 _aCrisan, Dan.
_eauthor.
_0(orcid)0000-0003-1486-1517
_1https://orcid.org/0000-0003-1486-1517
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_983218
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031695858
776 0 8 _iPrinted edition:
_z9783031695872
776 0 8 _iPrinted edition:
_z9783031695889
830 0 _aSpringerBriefs in Mathematics,
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856 4 0 _uhttps://doi.org/10.1007/978-3-031-69586-5
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