Experimental breakeven demonstration of a qLDPC code encoding 4 logical qubits in 18 physical qubits on trapped ions, with up to 9x lower logical error rate than prior superconducting implementations.
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Bench- marking quantum processor performance at scale
19 Pith papers cite this work, alongside 22 external citations. Polarity classification is still indexing.
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abstract
As quantum processors grow, new performance benchmarks are required to capture the full quality of the devices at scale. While quantum volume is an excellent benchmark, it focuses on the highest quality subset of the device and so is unable to indicate the average performance over a large number of connected qubits. Furthermore, it is a discrete pass/fail and so is not reflective of continuous improvements in hardware nor does it provide quantitative direction to large-scale algorithms. For example, there may be value in error mitigated Hamiltonian simulation at scale with devices unable to pass strict quantum volume tests. Here we discuss a scalable benchmark which measures the fidelity of a connecting set of two-qubit gates over $N$ qubits by measuring gate errors using simultaneous direct randomized benchmarking in disjoint layers. Our layer fidelity can be easily related to algorithmic run time, via $\gamma$ defined in Ref.\cite{berg2022probabilistic} that can be used to estimate the number of circuits required for error mitigation. The protocol is efficient and obtains all the pair rates in the layered structure. Compared to regular (isolated) RB this approach is sensitive to crosstalk. As an example we measure a $N=80~(100)$ qubit layer fidelity on a 127 qubit fixed-coupling "Eagle" processor (ibm\_sherbrooke) of 0.26(0.19) and on the 133 qubit tunable-coupling "Heron" processor (ibm\_montecarlo) of 0.61(0.26). This can easily be expressed as a layer size independent quantity, error per layered gate (EPLG), which is here $1.7\times10^{-2}(1.7\times10^{-2})$ for ibm\_sherbrooke and $6.2\times10^{-3}(1.2\times10^{-2})$ for ibm\_montecarlo.
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quant-ph 19representative citing papers
Linearized gate set tomography scales error characterization to many qubits via sparse models, linear fitting, and shallow circuits, with simulations showing accuracy on 10-qubit systems including crosstalk.
A protocol for approximate error correction in quantum simulations of SU(2) lattice gauge theories that extracts gauge-violation syndromes via group QFT and applies iterative recovery sweeps called gauge cooling.
Thermodynamic recycling of algorithmic failure branches enables information erasure with heat dissipation below the Landauer limit on a quantum processor.
Continuous TE-PAI provides an unbiased randomized protocol for Hamiltonian simulation free of Trotter error at finite circuit depth, combined with structure-aware variance reduction that achieves up to 96% sampling-cost savings in n=30 tensor-network simulations.
Demonstration of utility-scale quantum simulation of collective dissipation in 1D qubit chains up to 86 emitters using Trotterized dynamic circuits, biased CDR error mitigation, and classical MC-TEBD validation on IBM hardware.
SCALA is a signaling cellular automaton with local attraction that achieves ~7.5% threshold and p_L proportional to p^{d/4} scaling for toric codes while keeping computation strictly local and robust to measurement and decoder noise.
A 50-qubit quantum processor produces dynamical structure factors for KCuF3 that quantitatively match neutron-scattering measurements of its spinon spectrum.
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 extrapolation on utility-scale circuits.
Gaussian randomized rounding on two-qubit marginals of depth-D circuits with local depolarizing noise p yields samples whose expected Max-Cut cost matches the noisy quantum device up to an approximation ratio of 1-O[(1-p)^D].
VarQEC uses a distinguishability loss as a machine-learning objective to variationally discover resource-efficient encoding circuits optimized for given noise models.
Genetic algorithm-optimized dynamical decoupling sequences empirically outperform canonical DD sequences on IBM quantum processors for circuits up to 100 qubits, with gains increasing with size and complexity.
RP000, a room-temperature CMOS photonic three-qubit processor, delivers higher or comparable accuracy to parameter-matched classical nets on ML classification and better noise tolerance than a superconducting processor.
Hybrid framework combines Pauli propagation with noise-canceling channels to compute observables more accurately on quantum hardware with lower classical and quantum resource costs.
Exascale classical simulation validates noise-tolerant performance of a 98-qubit QPU up to 48 qubits for LR-QAOA, with statistical analysis showing coherent regime up to 93 qubits before outputs become indistinguishable from random.
In the large-N limit, spin squeezing torsion yields a nonlinear qubit governed by the two-state Gross-Pitaevskii equation that solves single-input state discrimination on the Bloch sphere.
Offset-charge-tunable transmon qubit achieves 99.37% fidelity in charge-parity mapping and over 93.4% in continuous monitoring at 4 μs intervals via randomized benchmarking.
QPDE applied to 2- and 3-spin Heisenberg models on IBM processors yields 85-93% accuracy versus classical values after noise mitigation.
Review synthesizing crosstalk mechanisms, mitigation strategies, and security vulnerabilities across major quantum computing platforms from existing literature.
citing papers explorer
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Breakeven demonstration of quantum low-density parity-check codes
Experimental breakeven demonstration of a qLDPC code encoding 4 logical qubits in 18 physical qubits on trapped ions, with up to 9x lower logical error rate than prior superconducting implementations.
-
Scalable linearized gate set tomography
Linearized gate set tomography scales error characterization to many qubits via sparse models, linear fitting, and shallow circuits, with simulations showing accuracy on 10-qubit systems including crosstalk.
-
Approximate Error Correction for Quantum Simulations of SU(2) Lattice Gauge Theories
A protocol for approximate error correction in quantum simulations of SU(2) lattice gauge theories that extracts gauge-violation syndromes via group QFT and applies iterative recovery sweeps called gauge cooling.
-
Thermodynamic Recycling of Algorithmic Failure Branches: Quantum-Computer Demonstration with Quantum Error Correction
Thermodynamic recycling of algorithmic failure branches enables information erasure with heat dissipation below the Landauer limit on a quantum processor.
-
Structure-Aware Variance Reduction for Unbiased Randomized Hamiltonian Simulation
Continuous TE-PAI provides an unbiased randomized protocol for Hamiltonian simulation free of Trotter error at finite circuit depth, combined with structure-aware variance reduction that achieves up to 96% sampling-cost savings in n=30 tensor-network simulations.
-
Utility-scale quantum experiments using dynamic circuits to address collective dissipation in interacting qubits
Demonstration of utility-scale quantum simulation of collective dissipation in 1D qubit chains up to 86 emitters using Trotterized dynamic circuits, biased CDR error mitigation, and classical MC-TEBD validation on IBM hardware.
-
High-performance cellular automaton decoders for quantum repetition and toric code
SCALA is a signaling cellular automaton with local attraction that achieves ~7.5% threshold and p_L proportional to p^{d/4} scaling for toric codes while keeping computation strictly local and robust to measurement and decoder noise.
-
Benchmarking quantum simulation with neutron-scattering experiments
A 50-qubit quantum processor produces dynamical structure factors for KCuF3 that quantitatively match neutron-scattering measurements of its spinon spectrum.
-
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 extrapolation on utility-scale circuits.
-
Sampling (noisy) quantum circuits through randomized rounding
Gaussian randomized rounding on two-qubit marginals of depth-D circuits with local depolarizing noise p yields samples whose expected Max-Cut cost matches the noisy quantum device up to an approximation ratio of 1-O[(1-p)^D].
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Learning Encodings by Maximizing State Distinguishability: Variational Quantum Error Correction
VarQEC uses a distinguishability loss as a machine-learning objective to variationally discover resource-efficient encoding circuits optimized for given noise models.
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Empirical learning of dynamical decoupling on quantum processors
Genetic algorithm-optimized dynamical decoupling sequences empirically outperform canonical DD sequences on IBM quantum processors for circuits up to 100 qubits, with gains increasing with size and complexity.
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Design and Benchmarking of a Quantum Photonic Chip
RP000, a room-temperature CMOS photonic three-qubit processor, delivers higher or comparable accuracy to parameter-matched classical nets on ML classification and better noise tolerance than a superconducting processor.
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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.
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Large-Scale Quantum Circuit Simulation on an Exascale System for QPU Benchmarking
Exascale classical simulation validates noise-tolerant performance of a 98-qubit QPU up to 48 qubits for LR-QAOA, with statistical analysis showing coherent regime up to 93 qubits before outputs become indistinguishable from random.
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From spin squeezing to fast state discrimination
In the large-N limit, spin squeezing torsion yields a nonlinear qubit governed by the two-state Gross-Pitaevskii equation that solves single-input state discrimination on the Bloch sphere.
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Characterizing charge-parity detection based on an offset-charge-tunable transmon qubit via randomized benchmarking
Offset-charge-tunable transmon qubit achieves 99.37% fidelity in charge-parity mapping and over 93.4% in continuous monitoring at 4 μs intervals via randomized benchmarking.
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Applications of the Quantum Phase Difference Estimation Algorithm to the Excitation Energies in Spin Systems on a NISQ Device
QPDE applied to 2- and 3-spin Heisenberg models on IBM processors yields 85-93% accuracy versus classical values after noise mitigation.
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Crosstalk In Contemporary Quantum Devices
Review synthesizing crosstalk mechanisms, mitigation strategies, and security vulnerabilities across major quantum computing platforms from existing literature.