Skip to Main Content
Remote Access Theory of Probability and Mathematical Statistics

Theory of Probability and Mathematical Statistics

ISSN 1547-7363(online) ISSN 0094-9000(print)

   
 
 

 

Boundedness of the nodal domains of additive Gaussian fields


Author: S. Muirhead
Journal: Theor. Probability and Math. Statist. 106 (2022), 143-155
MSC (2020): Primary 60G60; Secondary 60F99
DOI: https://doi.org/10.1090/tpms/1169
Published electronically: May 16, 2022
MathSciNet review: 4438448
Full-text PDF

Abstract | References | Similar Articles | Additional Information

Abstract: We study the connectivity of the excursion sets of additive Gaussian fields, i.e. stationary centred Gaussian fields whose covariance function decomposes into a sum of terms that depend separately on the coordinates. Our main result is that, under mild smoothness and correlation decay assumptions, the excursion sets $\{f \le \ell \}$ of additive planar Gaussian fields are bounded almost surely at the critical level $\ell _c = 0$. Since we do not assume positive correlations, this provides the first examples of continuous non-positively-correlated stationary planar Gaussian fields for which the boundedness of the nodal domains has been confirmed. By contrast, in dimension $d \ge 3$ the excursion sets have unbounded components at all levels.


References [Enhancements On Off] (What's this?)

References

Similar Articles

Retrieve articles in Theory of Probability and Mathematical Statistics with MSC (2020): 60G60, 60F99

Retrieve articles in all journals with MSC (2020): 60G60, 60F99


Additional Information

S. Muirhead
Affiliation: School of Mathematics and Statistics, University of Melbourne
Email: smui@unimelb.edu.au

Keywords: Gaussian fields, level sets, nodal domains, percolation
Received by editor(s): June 24, 2021
Accepted for publication: October 21, 2021
Published electronically: May 16, 2022
Additional Notes: Supported by the Australian Research Council (ARC) Discovery Early Career Researcher Award DE200101467.
Article copyright: © Copyright 2022 Taras Shevchenko National University of Kyiv