Protocol learns k-local Lindbladians to ε accuracy with Õ(n^{2k}/ε²) samples and projects to valid generators; improves to log n under sparsity assumptions.
Relaxations and Exact Solutions to Quantum Max Cut via the Algebraic Structure of Swap Operators
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The authors provide a poly-time algorithm that learns local quantum Hamiltonians to precision ε from poly copies of the Gibbs state at any constant β>0 by reducing the problem to a low-degree sum-of-squares relaxation via new polynomial approximations.
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Robust Structure Learning of $k$-local Lindbladians
Protocol learns k-local Lindbladians to ε accuracy with Õ(n^{2k}/ε²) samples and projects to valid generators; improves to log n under sparsity assumptions.
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Learning quantum Hamiltonians at any temperature in polynomial time
The authors provide a poly-time algorithm that learns local quantum Hamiltonians to precision ε from poly copies of the Gibbs state at any constant β>0 by reducing the problem to a low-degree sum-of-squares relaxation via new polynomial approximations.