Noise correlations increase the fidelity of randomly compiled Clifford circuits under a broad class of Gaussian noise.
Non-Markovian Noise Suppression Simplified through Channel Representation
4 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
abstract
Non-Markovian noise, arising from memory effects in the environment, poses substantial challenges to conventional quantum noise suppression protocols, including quantum error correction and mitigation. We introduce a channel representation for arbitrary non-Markovian quantum dynamics, termed the Choi channel, which translates the complex dynamics of non-Markovian noise into the familiar picture of noise channels. It therefore provides a systematic way to design non-Markovian noise suppression protocols: one can apply existing channel-level error-suppression techniques in the Choi-channel picture and then translate them back to the circuit picture. The performance of the resulting non-Markovian protocols, including their noise-suppression effects and complexity, can often be inherited directly from the corresponding Choi-channel protocols without requiring a separate analysis. With this framework, we devise new protocols using Pauli twirling, probabilistic error cancellation, and virtual channel purification. Pauli twirling reduces non-Markovian noise to noise with only classical temporal correlations; probabilistic error cancellation can fully cancel non-Markovian noise; and virtual channel purification can suppress non-Markovian noise without detailed knowledge of its specific form. Through these examples, the Choi channel serves as a foundational bridge for systematically converting existing channel-level techniques into non-Markovian noise suppression protocols.
fields
quant-ph 4representative citing papers
SNT merges SV and PEC for subspace-tailored error mitigation in Trotterized FHM simulations, mapping out optimal combinations by hardware quality and shot budget while quantifying when noisy devices could surpass classical methods.
Modulating relative weights of interaction channels in a quantum Brownian motion model allows control over non-Markovianity, inducing transitions to Markovian regimes using Gaussian master equations.
Resource estimation for magic-state distillation on silicon spin qubits finds 42% overhead reduction via optimized pulses and ~3x physical footprint reduction with biased codes versus surface code.
citing papers explorer
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Noise Correlations as a Resource in Pauli-Twirled Circuits
Noise correlations increase the fidelity of randomly compiled Clifford circuits under a broad class of Gaussian noise.
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Near-Term Fermionic Simulation with Subspace Noise Tailored Quantum Error Mitigation
SNT merges SV and PEC for subspace-tailored error mitigation in Trotterized FHM simulations, mapping out optimal combinations by hardware quality and shot budget while quantifying when noisy devices could surpass classical methods.
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Controlling the non-Markovianity of quantum Brownian motion
Modulating relative weights of interaction channels in a quantum Brownian motion model allows control over non-Markovianity, inducing transitions to Markovian regimes using Gaussian master equations.
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Hardware-Tailored Resource Estimation for Magic-State Distillation on Silicon Spin Qubits
Resource estimation for magic-state distillation on silicon spin qubits finds 42% overhead reduction via optimized pulses and ~3x physical footprint reduction with biased codes versus surface code.