Practical characterization of quantum devices without tomography.

By M. D. da Silva, Olivier Landon-Cardinal, David Poulin. Physical Review Letters, 2011

313 citations recorded by the source corpus.

Quantum tomography is the main method used to assess the quality of quantum information processing devices. However, the amount of resources needed for quantum tomography is exponential in the device size. Part of the problem is that tomography generates much more information than is usually sought. Taking a more targeted approach, we develop schemes that enable (i) estimating the fidelity of an experiment to a theoretical ideal description, (ii) learning which description within a reduced subset best matches the experimental data. Both these approaches yield a significant reduction in resources compared to tomography. In particular, we demonstrate that fidelity can be estimated from a number of simple experiments that is independent of the system size, removing an important roadblock for the experimental study of larger quantum information processing units.

Subfields: Artificial Intelligence, Atomic and Molecular Physics, and Optics

View Paper: https://www.semanticscholar.org/paper/c2394ffeb0d2e3f32a99ab897af71867ff3a806f

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In Atomic and Molecular Physics, and Optics

Citations in the corpus

The randomized measurement toolbox (2022, methodology): “75,76 for details) and was first used to efficiently estimate the process fidelity of a Toffoli gate in a superconducting transmon architecture 77 .”
Entanglement in a Quantum Annealing Processor (2014, background): “However, this approach is limited to a small number of qubits [41].”
Efficient tomography of a quantum many-body system (2016, methodology): “In such a setting, Lieb-Robinson bounds imply exponentially decreasing correlations with distance, ensuring the existence of an efficient MPS representation of the state (corollary 3 of [19], see also [20]).”
Efficient Long-Range Entanglement Using Dynamic Circuits (2023, methodology): “Similarly to the state fidelity, we use the Monte Carlo process certification following [31] to determine the average gate fidelity of our noisy CNOT gate.”
Predicting many properties of a quantum system from very few measurements (2020, methodology): “The best-known technique is based on few Pauli measurements that are selected randomly using importance sampling [19, 27].”
Quantum tomography via compressed sensing: error bounds, sample complexity and efficient estimators (2012, methodology): “The result uses the DFE protocol of [33, 34], modified as mentioned above, where the states |φ j〉 are the eigenstates of ρ̂.”
Characterizing Quantum Gates via Randomized Benchmarking (2011, methodology): “[23] M.”