Reconstruction of the noise correlation spectral density from the cavity emission in a two-qubit system

• URL: http://arxiv.org/abs/2607.15909v1
• Date: Fri, 17 Jul 2026 12:34:08 GMT
• Title: Reconstruction of the noise correlation spectral density from the cavity emission in a two-qubit system
• Abstract summary: We describe the dynamics of two cavity-coupled qubits that are subject to correlated noise.<n>We find that the cavity emission enables the characterization of the noise correlations.<n>We present a method for extracting the noise correlation spectral density from the cavity emission in the case where the underlying noise type remains unidentified.
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• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: A significant challenge in the field of large-scale fault-tolerant quantum computation is the influence of noise. In addition to the influence of noise on individual qubits, the smaller additional effect of noise correlations is also of high significance because correlated errors pose a challenge for quantum error correction. We describe the dynamics of two cavity-coupled qubits that are subject to correlated noise, assuming that the qubits are affected by longitudinal noise and not coupled directly. We find that the cavity emission enables the characterization of the noise correlations and describe the cases of white noise, quasi-static noise, and Ornstein-Uhlenbeck noise. For a known frequency spectrum, the reconstruction of the noise correlation spectral density from the cavity emission is possible by averaging over many different noise realizations. We demonstrate that, in the case of white noise, the noise correlation effects scale with the fifth order of the cavity-qubit coupling constant and are thus strongly suppressed compared with the case of quasi-static noise, where they scale with the third order. Furthermore, we present a method for extracting the noise correlation spectral density from the cavity emission in the case where the underlying noise type remains unidentified. This can be achieved by applying the convolution theorem.

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