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Found 3 papers, 2 papers with code
Foundations for learning from noisy quantum experiments
When one cannot explore the full state space but all operations are approximately known and noise in Clifford gates is gate-independent, we find an efficient algorithm for learning all operations up to a single unlearnable parameter characterizing the fidelity of the initial state.
Fast Estimation of Sparse Quantum Noise
As quantum computers approach the fault tolerance threshold, diagnosing and characterizing the noise on large scale quantum devices is increasingly important.
Quantum Physics
Efficient learning of quantum noise
We show how to construct a quantum noise correlation matrix allowing the easy visualization of correlations between all pairs of qubits, enabling the discovery of long-range two-qubit correlations in the 14 qubit device that had not previously been detected.
Quantum Physics
