A quantum parallel Markov chain Monte Carlo.
J Comput Graph Stat
; 32(4): 1402-1415, 2023.
Article
en En
| MEDLINE
| ID: mdl-38127472
ABSTRACT
We propose a novel hybrid quantum computing strategy for parallel MCMC algorithms that generate multiple proposals at each step. This strategy makes the rate-limiting step within parallel MCMC amenable to quantum parallelization by using the Gumbel-max trick to turn the generalized accept-reject step into a discrete optimization problem. When combined with new insights from the parallel MCMC literature, such an approach allows us to embed target density evaluations within a well-known extension of Grover's quantum search algorithm. Letting PdenotethenumberofproposalsinasingleMCMCiteration,thecombinedstrategyreducesthenumberoftargetevaluationsrequiredfromðª(P)toðªP1/2. In the following, we review the rudiments of quantum computing, quantum search and the Gumbel-max trick in order to elucidate their combination for as wide a readership as possible.
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Colección:
01-internacional
Base de datos:
MEDLINE
Idioma:
En
Revista:
J Comput Graph Stat
Año:
2023
Tipo del documento:
Article
Pais de publicación:
Estados Unidos