A general framework and query-efficient algorithms for learning structured quantum unitaries based on Pauli spectrum support on small subgroups or sparsity, unifying prior results for multiple circuit classes.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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quant-ph 2years
2025 2verdicts
UNVERDICTED 2representative citing papers
Efficient witnesses and testing algorithms based on stabilizer Rényi entropy certify and quantify magic in mixed states, with experimental demonstration on IonQ hardware showing robustness under strong noise.
citing papers explorer
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Efficient Learning of Structured Quantum Circuits via Pauli Dimensionality and Sparsity
A general framework and query-efficient algorithms for learning structured quantum unitaries based on Pauli spectrum support on small subgroups or sparsity, unifying prior results for multiple circuit classes.
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Efficient witnessing and testing of magic in mixed quantum states
Efficient witnesses and testing algorithms based on stabilizer Rényi entropy certify and quantify magic in mixed states, with experimental demonstration on IonQ hardware showing robustness under strong noise.