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Mathav Murugan and Laurent Saloff-Coste
Transition probability estimates for long range random walks view print
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Published: |
August 12, 2015 |
Keywords: |
long range random walks; heat kernel estimates; heavy-tailed |
Subject: |
60J10, 60J75, 60J15 |
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Abstract
Let (M,d,μ) be a uniformly discrete metric measure space satisfying space homogeneous volume doubling condition. We consider discrete time Markov chains on M symmetric with respect to μ and whose one-step transition density is
comparable to
(Vh(d(x,y)) ϕ(d(x,y))-1,
where ϕ is a positive continuous regularly varying function with index β ∈ (0,2) and Vh is the homogeneous volume growth function.
Extending several existing work by other authors, we prove global upper and lower bounds for n-step transition probability density that are sharp up to constants.
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Acknowledgements
Both authors were partially supported by NSF grants DMS 1004771 and DMS 1404435
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Author information
Mathav Murugan:
Department of Mathematics, University of British Columbia and Pacific Institute for the Mathematical Sciences, Vancouver, BC V6T 1Z2, Canada.
mathav@math.ubc.ca
Laurent Saloff-Coste:
Department of Mathematics, Cornell University, Ithaca, NY 14853, USA.
lsc@math.cornell.edu
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