Spatially Dense, Continuous-Variable Quantum Computing with Solid State Spin Nonlinearities

• URL: http://arxiv.org/abs/2608.12504v1
• Date: Wed, 12 Aug 2026 18:33:34 GMT
• Title: Spatially Dense, Continuous-Variable Quantum Computing with Solid State Spin Nonlinearities
• Abstract summary: We propose and describe an approach for bosonic quantum information processing using strain-sensitive solid-state spins as nonlinear elements.<n>We show that this architecture can allow for a high spatial density of logical qubits by leveraging both the efficiency of bosonic error correction schemes and the small sizes of the constituent nanomechanical resonators and spin qubits.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Nanomechanical structures have been investigated as a method of achieving long-lived quantum excitations at radio frequencies. Their high quality factors are especially intriguing as a medium for bosonic encoding of quantum information. However, to leading order, mechanical modes typically lack the nonlinearities necessary to achieve interaction between bosonic channels and thus are limited in their ability to scale to the many-qubit regime necessary for practical quantum computing. In this work, we propose and describe an approach for bosonic quantum information processing that uses strain-sensitive solid-state spins as nonlinear elements to produce the relevant nonclassical mechanical states. We outline the architecture required to achieve nearest-neighbor connectivity between mechanical cat-state qubits on-chip, as well as the control and readout architecture required for universal quantum computation. In addition, we show that this architecture can allow for a high spatial density of logical qubits by leveraging both the efficiency of bosonic error correction schemes and the small sizes of the constituent nanomechanical resonators and spin qubits. Finally, we identify the necessary performance metrics that will enable error-correction thresholds at high qubit densities, illuminating a path towards scalable quantum information processing.

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