Sample-Optimal Quantum Process Tomography with Non-Adaptive Incoherent Measurements

Watch a 27-minute conference talk from TQC 2023 (Theory of Quantum Computation, Communication and Cryptography Conference) exploring the optimal sample complexity for quantum process tomography using non-adaptive incoherent measurements. Learn about groundbreaking research that establishes both upper and lower bounds for the number of copies needed to construct approximate classical descriptions of quantum channels. Discover how the presentation extends previous work to demonstrate that $\tilde{\mathcal{O}}(\din^3\dout^3/\varepsilon^2)$ copies suffice for learning quantum channels within $\varepsilon$ diamond norm accuracy, while also proving $\Omega(\din^3\dout^3/\varepsilon^2)$ copies are necessary when using incoherent non-adaptive measurements - even with ancilla assistance. Follow along as the speaker progresses through key concepts including quantum channels, problem formulation, strategy development, proofs, algorithmic implementation, and discusses open questions in quantum process tomography.