Experimental Bayesian Quantum Phase Estimation on a Silicon Photonic Chip

Abstract

Quantum phase estimation is a fundamental subroutine in many quantum algorithms, including Shor's factorization algorithm and quantum simulation. However, so far results have cast doubt on its practicability for near-term, nonfault tolerant, quantum devices. Here we report experimental results demonstrating that this intuition need not be true. We implement a recently proposed adaptive Bayesian approach to quantum phase estimation and use it to simulate molecular energies on a silicon quantum photonic device. The approach is verified to be well suited for prethreshold quantum processors by investigating its superior robustness to noise and decoherence compared to the iterative phase estimation algorithm. This shows a promising route to unlock the power of quantum phase estimation much sooner than previously believed.

Contextuality Test of the Nonclassicality of Variational Quantum Eigensolvers

“…In the last decade much attention has been focused on algorithms for quantum simulation of chemical systems [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21]. One such algorithm, the variational quantum eigensolver (VQE, first proposed in [11]), has emerged as an important potential application of NISQ computers.…”

“…One such algorithm, the variational quantum eigensolver (VQE, first proposed in [11]), has emerged as an important potential application of NISQ computers. Experimental realizations of VQE have been performed on a number of platforms [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23].…”

Structured filtering

“…Current efficient methods for parameter estimation in quantum systems are implicitly biased via structural assumptions about the posterior distribution [6,9,14,39]. Here we show that even the subtle biases introduced through filtering with Liu-West resampling can catastrophically fail to estimate parameters for problems where the experiments chosen are incapable of distinguishing between two equivalent hypotheses.…”

Quantum Phase Estimation with Time‐Frequency Qudits in a Single Photon

“…Our successful implementation of the controlled gate in this paper demonstrates all the capability needed for implementing the arbitrary (diagonal) ‐rotation. We note the two operations needed to achieve a standard iterative PEA can also be used to implement a Bayesian phase estimation approach known as rejection filtering phase estimation (RFPE) . RFPE is robust to noise and promises a speed up over standard iterative PEAs by gaining information about multiple bits (for us, dits) of the phase at a time.…”