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IBM’s Quantum-Enhanced Markov Chain Monte Carlo Algorithm Facilitates Complicated Probability Distribution Sampling
March 28, 2022, 3:33 p.m. | Synced
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Researchers from IBM Quantum propose a quantum algorithm for sampling from distributions that can be both complicated and useful, applying the algorithm to perform Markov Chain Monte Carlo (MCMC) iterative sampling on the Boltzmann distribution of classical Ising models.
The post IBM’s Quantum-Enhanced Markov Chain Monte Carlo Algorithm Facilitates Complicated Probability Distribution Sampling first appeared on Synced.
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