RandomMeas.jl is a modular Julia package implementing randomized measurement protocols and classical shadow estimators for quantum computing applications.
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Engineering method using dynamic circuits to generate randomized algorithm distributions on quantum hardware, achieving 14000x speedup for Pauli measurements and enabling 10M-circuit classical shadows on 28-40 qubit hydrogen models.
Geometric partitioning of lattice Hamiltonians into local patches enables energy measurements in patch eigenbases, producing lower-variance estimators than Pauli grouping for eigenstates with rigorous guarantees even under depolarizing noise.
Hybrid framework combines Pauli propagation with noise-canceling channels to compute observables more accurately on quantum hardware with lower classical and quantum resource costs.
citing papers explorer
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RandomMeas.jl: A Julia Package for Randomized Measurements in Quantum Devices
RandomMeas.jl is a modular Julia package implementing randomized measurement protocols and classical shadow estimators for quantum computing applications.
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Efficient implementation of randomized quantum algorithms with dynamic circuits
Engineering method using dynamic circuits to generate randomized algorithm distributions on quantum hardware, achieving 14000x speedup for Pauli measurements and enabling 10M-circuit classical shadows on 28-40 qubit hydrogen models.
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Shot-noise reduction for lattice Hamiltonians
Geometric partitioning of lattice Hamiltonians into local patches enables energy measurements in patch eigenbases, producing lower-variance estimators than Pauli grouping for eigenstates with rigorous guarantees even under depolarizing noise.
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Computing noise-canceling observables via Pauli propagation
Hybrid framework combines Pauli propagation with noise-canceling channels to compute observables more accurately on quantum hardware with lower classical and quantum resource costs.