Centre for Engineered Quantum Systems, School of Physics, The University of Sydney, Sydney NSW 2006, Australia.
Institute for Quantum Computing and Department of Applied Mathematics, University of Waterloo, Waterloo, Ontario, Canada, N2L 3G1.
Phys Rev Lett. 2015 Aug 14;115(7):070501. doi: 10.1103/PhysRevLett.115.070501. Epub 2015 Aug 10.
We present a method for estimating the probabilities of outcomes of a quantum circuit using Monte Carlo sampling techniques applied to a quasiprobability representation. Our estimate converges to the true quantum probability at a rate determined by the total negativity in the circuit, using a measure of negativity based on the 1-norm of the quasiprobability. If the negativity grows at most polynomially in the size of the circuit, our estimator converges efficiently. These results highlight the role of negativity as a measure of nonclassical resources in quantum computation.
我们提出了一种使用蒙特卡罗抽样技术，应用于拟概率表示来估计量子电路结果概率的方法。我们的估计值以电路总负度决定的速率收敛到真实的量子概率，使用基于拟概率的 1 范数的负度测量。如果负度在电路大小上最多呈多项式增长，那么我们的估计器将有效地收敛。这些结果强调了负度作为量子计算中非经典资源的度量的作用。
