Measurement-based state preparation of Kerr parametric oscillators

TL;DR

This paper demonstrates a method for stochastic state preparation of Kerr parametric oscillators using homodyne detection, avoiding control field modulation, and analyzes its success probability through a developed theoretical model.

Contribution

It introduces a homodyne detection-based stochastic state preparation method for KPOs that does not require pump or auxiliary drive modulation, enhancing robustness against control imperfections.

Findings

Detection data correlates strongly with KPO state after averaging.

Success probability depends on measurement noise and bit flips.

Optimal averaging time range is identified for high success probability.

Abstract

Kerr parametric oscillators (KPOs) have attracted increasing attention in terms of their application to quantum information processing and quantum simulations. The state preparation and measurement of KPOs are typical requirements when they are used as qubits. The methods previously proposed for state preparations of KPOs utilize modulation of a pump field or an auxiliary drive field. We study the stochastic state preparation of a KPO based on homodyne detection, which does not require modulation of a pump field nor an auxiliary drive field, and thus can exclude unwanted effects of possible imperfection in control of these fields. We quantitatively show that the detection data, if averaged over a proper time to decrease the effect of measurement noise, has a strong correlation with the state of the KPO, and therefore can be used to estimate the state of the KPO (stochastic state preparation). We examine the success probability of the state estimation taking into account the effect of the measurement noise and bit flips. Moreover, the proper range of the averaging time to realize a high success probability is obtained by developing a binomial-coherent-state model, which describes the stochastic dynamics of the KPO under homodyne detection.