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All-optical generation of deterministic squeezed Schrödinger-cat states

Zhucheng Zhang, Lei Shao, Wangjun Lu, Xiaoguang Wang

2022Physical review. A/Physical review, A12 citationsDOIOpen Access PDF

Abstract

Quantum states are important resources and their preparations are essential prerequisites to all quantum technologies. However, they are extremely fragile due to the inevitable dissipations. Here the all-optical generation of a deterministic squeezed Schr\"odinger-cat state based on dissipation is proposed. Our system is based on the Fredkin-type interaction between three optical modes, one of which is subject to coherent two-photon driving and the others are coherent driving. We show that an effective degenerate three-wave-mixing process can be engineered in our system, which can cause the simultaneous loss of two photons, resulting in the generation of a deterministic squeezed Schr\"odinger-cat state. More importantly, by controlling the driving fields in our system, the two-photon loss can be adjustable, which can accelerate the generation of squeezed Schr\"odinger-cat states. In addition, we exploit the squeezed Schr\"odinger-cat states to estimate the phase in the optical interferometer and show that the quantum Fisher information about the phase can reach the Heisenberg limit in the limit of a large photon number. Meanwhile, it can have an order of magnitude factor improvement over the Heisenberg limit in the low-photon-number regime, which is very valuable for fragile systems that cannot withstand large photon fluxes. This work proposes an all-optical scheme to deterministically prepare the squeezed Schr\"odinger-cat state with high speed and can also be generalized to other physical platforms.

Topics & Concepts

PhysicsPhotonDegenerate energy levelsSqueezed coherent stateQuantum mechanicsQuantumSchrödinger's catHeisenberg limitCoherent statesQuantum opticsLimit (mathematics)DissipationQuantum entanglementQuantum networkMathematicsMathematical analysisQuantum Information and CryptographyMechanical and Optical ResonatorsNeural Networks and Reservoir Computing