Dynamarq is a new scalable benchmarking framework that defines structural features for dynamic quantum circuits and uses statistical models to predict hardware fidelity with transferable parameters.
Approximate quantum fourier transform in logarithmic depth on a line
3 Pith papers cite this work. Polarity classification is still indexing.
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Presents an optimal gate-packing partitioning scheme for the QFT that aims to minimize e-bit count in distributed quantum systems and validates it on hardware.
Combining dynamical decoupling and zero-noise extrapolation on real quantum hardware improves energy gap estimates by at least 60% and reduces time-evolution errors by up to 99% for the Ising model in dynamic circuit Hamiltonian simulations.
citing papers explorer
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Characterizing and Benchmarking Dynamic Quantum Circuits
Dynamarq is a new scalable benchmarking framework that defines structural features for dynamic quantum circuits and uses statistical models to predict hardware fidelity with transferable parameters.
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Towards an Optimally Distributed Quantum Fourier Transform Circuit
Presents an optimal gate-packing partitioning scheme for the QFT that aims to minimize e-bit count in distributed quantum systems and validates it on hardware.
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Error Mitigation in Dynamic Circuits for Hamiltonian Simulation
Combining dynamical decoupling and zero-noise extrapolation on real quantum hardware improves energy gap estimates by at least 60% and reduces time-evolution errors by up to 99% for the Ising model in dynamic circuit Hamiltonian simulations.