Non-Gaussianity of invariant measures to SPDEs in Da Prato–Debussche regime

Abstract We propose an elementary method to show non-Gaussianity of invariant measures of parabolic stochastic partial differential equations with polynomial non-linearities in the Da Prato–Debussche regime. The approach is essentially algebraic and involves using the generator equation of the SPDE at stationarity. Our results in particular cover the $$\Phi ^4_\delta $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msubsup> <mml:mi>Φ</mml:mi> <mml:mi>δ</mml:mi> <mml:mn>4</mml:mn> </mml:msubsup> </mml:math> measures in dimensions $$\delta &lt;\frac{14}{5}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>δ</mml:mi> <mml:mo>&lt;</mml:mo> <mml:mfrac> <mml:mn>14</mml:mn> <mml:mn>5</mml:mn> </mml:mfrac> </mml:mrow> </mml:math> , which includes cases where the invariant measure is singular with respect to the invariant measure of the linear solution.

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Publication Details

Journal
Stochastic Partial Differential Equations Analysis and Computations
Published
2025-06-19
DOI
https://doi.org/10.1007/s40072-025-00370-3
Primary Topic
Stochastic processes and financial applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Non-Gaussianity of invariant measures to SPDEs in Da Prato–Debussche regime

Ajay Chandra, Ilya Chevyrev
Stochastic Partial Differential Equations Analysis and Computations
Stochastic processes and financial applications
article

Non-Gaussianity of invariant measures to SPDEs in Da Prato–Debussche regime

Ajay Chandra, Ilya Chevyrev
article en

Abstract

Abstract We propose an elementary method to show non-Gaussianity of invariant measures of parabolic stochastic partial differential equations with polynomial non-linearities in the Da Prato–Debussche regime. The approach is essentially algebraic and involves using the generator equation of the SPDE at stationarity. Our results in particular cover the $$\Phi ^4_\delta $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msubsup> <mml:mi>Φ</mml:mi> <mml:mi>δ</mml:mi> <mml:mn>4</mml:mn> </mml:msubsup> </mml:math> measures in dimensions $$\delta &lt;\frac{14}{5}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>δ</mml:mi> <mml:mo>&lt;</mml:mo> <mml:mfrac> <mml:mn>14</mml:mn> <mml:mn>5</mml:mn> </mml:mfrac> </mml:mrow> </mml:math> , which includes cases where the invariant measure is singular with respect to the invariant measure of the linear solution.

Stochastic Partial Differential Equations Analysis and Computations
Scuola Internazionale Superiore di Studi Avanzati (IT), Imperial College London (GB)
Deutsche Forschungsgemeinschaft, Technische Universität Berlin, Engineering and Physical Sciences Research Council
Openalex Percentile: Top 82%
Stochastic processes and financial applications
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