REVIEW 8 cited by
Scalability of quantum error mitigation techniques: from utility to advantage
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
Scalability of quantum error mitigation techniques: from utility to advantage
read the original abstract
Error mitigation has elevated quantum computing to the scale of hundreds of qubits and tens of layers; however, yet larger scales (deeper circuits) are needed to fully exploit the potential of quantum computing to solve practical problems otherwise intractable. Here we demonstrate three key results that pave the way for the leap from quantum utility to quantum advantage: (1) we present a thorough derivation of random and systematic errors associated to the most advanced error mitigation strategies, including probabilistic error cancellation (PEC), zero noise extrapolation (ZNE) with probabilistic error amplification, and tensor-network error mitigation (TEM); (2) we prove that TEM (i) has the lowest sampling overhead among all three techniques under realistic noise, (ii) is optimal, in the sense that it saturates the universal lower cost bound for error mitigation, and (iii) is therefore the most promising approach to quantum advantage; (3) we propose a concrete notion of practical quantum advantage in terms of the universality of algorithms, stemming from the commercial need for a problem-independent quantum simulation device. We also establish a connection between error mitigation, relying on additional measurements, and error correction, relying on additional qubits, by demonstrating that TEM with a sufficient bond dimension works similarly to an error correcting code of distance 3. We foresee that the interplay and trade-off between the two resources will be the key to a smooth transition between error mitigation and error correction, and hence between near-term and fault-tolerant quantum computers. Meanwhile, we argue that quantum computing with optimal error mitigation, relying on modest classical computer power for tensor network contraction, has the potential to reach larger scales in accurate simulation than classical methods alone.
Forward citations
Cited by 8 Pith papers
-
Characterization of Unlearnable Noise with Mid-Circuit-Measurement-Based Cycle Benchmarking
Mid-circuit measurements enable reversal of Pauli cycles in Clifford gates, making previously unidentifiable noise components learnable under a new generalized cycle benchmarking protocol.
-
Characterization of Unlearnable Noise with Mid-Circuit-Measurement-Based Cycle Benchmarking
Mid-circuit-measurement-based generalized cycle benchmarking resolves unlearnable Pauli fidelities in Clifford gates by reversing Pauli cycles and revealing a learnability condition.
-
Bowtie VarQTE: A Resource-Efficient Quantum State Preparation Primitive
Bowtie VarQTE is a hybrid classical-quantum variational time evolution method that exploits causal light-cones to reduce quantum resource use for state preparation while achieving fidelities comparable to approximate ...
-
Syndrome aware mitigation of logical errors
Conditioning logical error mitigation on the measured error-correcting syndromes cuts sampling overhead exponentially and can make error correction useful above its standard pseudo-threshold.
-
Reliable high-accuracy error mitigation for utility-scale quantum circuits
QESEM is a characterization-based error mitigation technique that achieves unbiased estimates with substantially reduced runtime cost compared to probabilistic error cancellation while outperforming zero-noise extrapo...
-
Superdiffusion resilience in Heisenberg Chains with 2D interactions on a quantum processor
Quantum simulation finds SU(2)-symmetric 2D interactions most resilient to superdiffusion breakdown in generalized Heisenberg models.
-
Systematic Experiment Tracking in Quantum Software: A Case Study of Reservoir Computing with Error Mitigation
MLflow-style experiment tracking, extended with quantum provenance, supports reproducible multi-stage quantum software pipelines, shown on error-mitigated quantum reservoir computing for chaotic time-series prediction.
-
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.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.