Quantum speedup of Monte Carlo methods

@article{Montanaro2015QuantumSO,
  title={Quantum speedup of Monte Carlo methods},
  author={A. Montanaro},
  journal={Proceedings. Mathematical, Physical, and Engineering Sciences / The Royal Society},
  year={2015},
  volume={471}
}
  • A. Montanaro
  • Published 2015
  • Mathematics, Medicine, Physics
  • Proceedings. Mathematical, Physical, and Engineering Sciences / The Royal Society
Monte Carlo methods use random sampling to estimate numerical quantities which are hard to compute deterministically. One important example is the use in statistical physics of rapidly mixing Markov chains to approximately compute partition functions. In this work, we describe a quantum algorithm which can accelerate Monte Carlo methods in a very general setting. The algorithm estimates the expected output value of an arbitrary randomized or quantum subroutine with bounded variance, achieving a… Expand
Adaptive Quantum Simulated Annealing for Bayesian Inference and Estimating Partition Functions
Quantum risk analysis
Quantum algorithm for credit valuation adjustments
Quantum Monte-Carlo Integration: The Full Advantage in Minimal Circuit Depth
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 75 REFERENCES
Speedup via quantum sampling
A quantum–quantum Metropolis algorithm
Quantum simulations of classical annealing processes.
Quantum speed-up of Markov chain based algorithms
  • M. Szegedy
  • Mathematics, Computer Science
  • 45th Annual IEEE Symposium on Foundations of Computer Science
  • 2004
Efficient circuits for quantum walks
A quantum algorithm for additive approximation of Ising partition functions
Hamiltonian Simulation with Nearly Optimal Dependence on all Parameters
...
1
2
3
4
5
...