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Trapped Ion Quantum Computing
Experimental Realization of the Markov Chain Monte Carlo Algorithm on a Quantum Computer
arXiv
Authors: Baptiste Claudon, Sergi Ramos-Calderer, Jean-Philip Piquemal
Year
2026
Paper ID
28603
Status
Preprint
Abstract Read
~2 min
Abstract Words
114
Citations
N/A
Abstract
Quantum algorithms present a quadratically improved complexity over classical ones for certain sampling tasks. For instance, the Quantum Amplitude Estimation (QAE) algorithm promises to speedup the estimation of the mean of certain functions, given access to the quantum state corresponding to the probability distribution to be sampled from. Classically, samples are often obtained by running steps a Markov Chain. In this work, we experimentally use encodings of Markov chains to prepare quantum states and run a quantum Markov Chain Monte Carlo algorithm (qMCMC) on Quantinuum's H2 and Helios quantum computers. We demonstrate that it is possible to obtain accurate results on current Noisy Intermediate Scale Quantum (NISQ) hardware, operating directly on the physical qubits.
Why This Paper Matters
- This paper contributes to the Trapped-Ion Quantum Computing research area in the Quantum Articles archive.
- It adds a 2026 reference point for readers tracking recent quantum research.
- Quantum algorithms present a quadratically improved complexity over classical ones for certain sampling tasks.
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