IBM’s Quantum-Enhanced Markov Chain Monte Carlo Algorithm Facilitates Complicated Probability Distribution Sampling | Synced
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) i...
Source: Synced | AI Technology & Industry Review
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.