Two generalizations of Mehler's formula in white noise analysis

IF 1.1 2区 经济学 Q3 BUSINESS, FINANCE Finance and Stochastics Pub Date : 2022-06-21 DOI:10.1080/17442508.2022.2089039
W. Bock, Maximilian Bock
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Abstract

ABSTRACT Mehler's formula is an important tool in Gaussian analysis. In this article, we study two generalizations of Mehler's formula for the Ornstein–Uhlenbeck semigroup, i.e. the semigroup generated by the number operator. The first generalization leads to transformation groups which have as infinitesimal generator a perturbation of the number operator with suitable integral kernel operators, which are well studied in white noise analysis. For the second one, we characterize the complex Hida measures for which a version of Mehler's formula for the Ornstein–Uhlenbeck semigroup can be extended to. We apply this result to the Feynman integrand for a quadratic potential. Here the time independent eigenstates of the considered transformation groups and the time evolution of eigenvalues are provided.
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白噪声分析中梅勒公式的两个推广
梅勒公式是高斯分析中的一个重要工具。本文研究了Ornstein-Uhlenbeck半群(即由数算子生成的半群)的两种对Mehler公式的推广。第一个推广导致变换群具有一个具有合适的积分核算子的数字算子的微扰作为无限小发生器,这在白噪声分析中得到了很好的研究。对于第二个问题,我们描述了复杂的Hida测度,对于这些测度,可以将Ornstein-Uhlenbeck半群的Mehler公式的一个版本推广到。我们把这个结果应用到二次势的费曼积分上。这里给出了所考虑的变换群的时间无关特征态和特征值的时间演化。
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来源期刊
Finance and Stochastics
Finance and Stochastics 管理科学-数学跨学科应用
CiteScore
2.90
自引率
5.90%
发文量
20
审稿时长
>12 weeks
期刊介绍: The purpose of Finance and Stochastics is to provide a high standard publication forum for research - in all areas of finance based on stochastic methods - on specific topics in mathematics (in particular probability theory, statistics and stochastic analysis) motivated by the analysis of problems in finance. Finance and Stochastics encompasses - but is not limited to - the following fields: - theory and analysis of financial markets - continuous time finance - derivatives research - insurance in relation to finance - portfolio selection - credit and market risks - term structure models - statistical and empirical financial studies based on advanced stochastic methods - numerical and stochastic solution techniques for problems in finance - intertemporal economics, uncertainty and information in relation to finance.
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