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Entangling Schrödinger’s cat states by bridging discrete- and continuous-variable encoding

Daisuke Hoshi, Toshiaki Nagase, Sangil Kwon, Daisuke Iyama, Takahiko Kamiya, Shiori Fujii, Hiroto Mukai, Shahnawaz Ahmed, Anton Frisk Kockum, Shohei Watabe, Fumiki Yoshihara, Jaw-Shen Tsai

2025Nature Communications14 citationsDOIOpen Access PDF

Abstract

In quantum information processing, two primary research directions have emerged: one based on discrete variables (DV) and the other on the structure of quantum states in a continuous-variable (CV) space. Integrating these two approaches could unlock new potentials, overcoming their respective limitations. Here, we show that such a DV–CV hybrid approach, applied to superconducting Kerr parametric oscillators (KPOs), enables us to entangle a pair of Schrödinger’s cat states by two methods. The first involves the entanglement-preserving conversion between Bell states in the Fock-state basis (DV encoding) and those in the cat-state basis (CV encoding). The second method implements a $$\sqrt{{{{\rm{iSWAP}}}}}$$ gate between two cat states following the procedure for Fock-state encoding. This simple and fast gate operation completes a universal quantum gate set in a KPO system. Our work offers powerful applications of DV–CV hybridization and marks a first step toward developing a multi-qubit platform based on planar KPO systems. Quantum information processing normally uses either discrete- or continuous-variable encoding. Here, the authors bridge the two approaches, showing how to entangle Schrodinger’s cats states by conversion between Bell states in the Fock and cat bases and by a simple Fock-state-like gate operation.

Topics & Concepts

Bridging (networking)Continuous variableSchrödinger's catEncoding (memory)Discrete variablePhysicsComputer scienceQuantum mechanicsMathematicsApplied mathematicsMathematical optimizationArtificial intelligenceComputer networkQuantum Information and CryptographyQuantum Computing Algorithms and ArchitectureNeural Networks and Reservoir Computing