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Noise Transfer Approach to GKP Quantum Circuits.

Timothy C Ralph¹, Matthew S Winnel¹, S Nibedita Swain^1,2,3

¹Centre for Quantum Computation and Communication Technology, School of Mathematics and Physics, University of Queensland, Brisbane, QLD 4072, Australia.

Entropy (Basel, Switzerland)

|October 25, 2024

Summary

This summary is machine-generated.

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We present a Heisenberg picture method for analyzing quantum circuits, factoring evolution into signal and noise. This approach may be particularly useful for quantum computing systems using Gottesman-Kitaev-Preskill (GKP) qubits.

Area of Science:

Quantum Mechanics
Quantum Information Science
Computational Quantum Physics

Background:

Quantum mechanics offers equivalent Schrödinger and Heisenberg pictures for problem-solving.
The choice of picture can significantly influence computational resource requirements.

Purpose of the Study:

To introduce a novel method for analyzing Bosonic quantum circuits using the Heisenberg picture.
To explore the potential for factoring quantum evolution into signal and noise components.

Main Methods:

Development of a Heisenberg picture-based analysis for Bosonic quantum circuits.
Application of the method to identify signal and noise contributions in quantum evolution.
Investigation of the method's utility for specific quantum computing architectures.

Keywords:

cat states Bosonic codes quantum computing

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Main Results:

The Heisenberg picture approach allows for a useful factoring of quantum evolution into signal and noise.
This factoring is analogous to techniques used in classical communication systems.
The method shows promise for analyzing quantum computing systems, especially those employing Gottesman-Kitaev-Preskill (GKP) qubits.

Conclusions:

The Heisenberg picture offers a computationally advantageous perspective for analyzing certain quantum systems.
The developed method provides a new tool for understanding and mitigating noise in quantum computations.
This approach may be particularly beneficial for error correction and fault tolerance in quantum computing.