Deterministic and stochastic sampling of two coupled Kerr parametric oscillators


Date

2023

Publication Type

Journal Article

ETH Bibliography

yes

Citations

Altmetric

Data

Abstract

The vision of building computational hardware for problem optimization has spurred large efforts in the physics community. In particular, networks of Kerr parametric oscillators (KPOs) are envisioned as simulators for finding the ground states of Ising Hamiltonians. It was shown, however, that KPO networks can feature large numbers of unexpected solutions that are difficult to sample with the existing deterministic (i.e., adiabatic) protocols. In this work, we experimentally realize a system of two classical coupled KPOs, and we find good agreement with the predicted mapping to Ising states. We then introduce a protocol based on stochastic sampling of the system, and we show how the resulting probability distribution can be used to identify the ground state of the corresponding Ising Hamiltonian. This method is akin to a Monte Carlo sampling of multiple out-of-equilibrium stationary states and is less prone to become trapped in local minima than deterministic protocols.

Publication status

published

Editor

Book title

Volume

5 (1)

Pages / Article No.

Publisher

American Physical Society

Event

Edition / version

Methods

Software

Geographic location

Date collected

Date created

Subject

Organisational unit

03906 - Degen, Christian / Degen, Christian check_circle
03571 - Sigrist, Manfred (emeritus) / Sigrist, Manfred (emeritus) check_circle

Notes

Funding

177198 - Zeptonewton force sensing on a membrane resonator platform (SNF)
190078 - Electronic and photonic quantum engineered systems (SNF)
20‐2 FEL‐66 - Sound with a twist: Topological Acoustic Phases with quantum Emitters (ETHZ)
206008 - Integrated Phase Logic Networks (SNF)

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