Repeated quantum error detection in a surface code

Andersen, Christian Kraglund; Remm, Ants; Lazar, Stefania; Krinner, Sebastian; Lacroix, Nathan; Norris, Graham J.; Gabureac, Mihai; Eichler, Christopher; Wallraff, Andreas

doi:10.1038/s41567-020-0920-y

Cited by 274 publications

(221 citation statements)

References 47 publications

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“…Recent advances in qubit numbers [1][2][3][4] , as well as operational [5][6][7][8][9][10][11][12][13] , and measurement [14][15][16] fidelities have enabled leading quantum computing platforms, such as superconducting and trapped-ion processors, to target demonstrations of quantum error correction (QEC) [17][18][19][20][21][22][23] and quantum advantage 2,[24][25][26] . In particular, twodimensional stabilizer codes, such as the surface code, are a promising approach 23,27 towards achieving quantum fault tolerance and, ultimately, large-scale quantum computation 28 . One of the central assumptions of textbook QEC is that any error can be decomposed into a set of Pauli errors that act within the computational space of the qubit.…”

Section: Introductionmentioning

confidence: 99%

Leakage detection for a transmon-based surface code

et al. 2020

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Leakage outside of the qubit computational subspace, present in many leading experimental platforms, constitutes a threatening error for quantum error correction (QEC) for qubits. We develop a leakage-detection scheme via Hidden Markov models (HMMs) for transmon-based implementations of the surface code. By performing realistic density-matrix simulations of the distance-3 surface code (Surface-17), we observe that leakage is sharply projected and leads to an increase in the surface-code defect probability of neighboring stabilizers. Together with the analog readout of the ancilla qubits, this increase enables the accurate detection of the time and location of leakage. We restore the logical error rate below the memory break-even point by post-selecting out leakage, discarding less than half of the data for the given noise parameters. Leakage detection via HMMs opens the prospect for near-term QEC demonstrations, targeted leakage reduction and leakage-aware decoding and is applicable to other experimental platforms.

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Section: Introductionmentioning

confidence: 99%

Leakage detection for a transmon-based surface code

et al. 2020

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“…The experiments described in this paper are performed in a cryogenic setup [43,44], the wiring scheme of which is summarized in Fig. 6.…”

Section: Appendix A: Experimental Setup and Device Parametersmentioning

confidence: 99%

“…via two feedlines [44,45] with the readout pulses generated by an FPGA-based signal analyzer (FPGA SA). The measurement signals at the output ports of the sample are first amplified with a wide-bandwidth near-quantumlimited traveling-wave parametric amplifier (TWPA) [46], then with a HEMT amplifier and finally with low-noise, room-temperature amplifiers (RT AMP) [44]. Thereafter, the signals are down-converted and processed using the weighted integration units of the FPGA SAs.…”

Section: Appendix A: Experimental Setup and Device Parametersmentioning

confidence: 99%

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Improving the Performance of Deep Quantum Optimization Algorithms with Continuous Gate Sets

et al. 2020

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Variational quantum algorithms are believed to be promising for solving computationally hard problems on noisy intermediate-scale quantum (NISQ) systems. Gaining computational power from these algorithms critically relies on the mitigation of errors during their execution, which for coherence-limited operations is achievable by reducing the gate count. Here, we demonstrate an improvement of up to a factor of 3 in algorithmic performance for the quantum approximate optimization algorithm (QAOA) as measured by the success probability, by implementing a continuous hardware-efficient gate set using superconducting quantum circuits. This gate set allows us to perform the phase separation step in QAOA with a single physical gate for each pair of qubits instead of decomposing it into two CZ gates and single-qubit gates. With this reduced number of physical gates, which scales with the number of layers employed in the algorithm, we experimentally investigate the circuit-depth-dependent performance of QAOA applied to exact-cover problem instances mapped onto three and seven qubits, using up to a total of 399 operations and up to nine layers. Our results demonstrate that the use of continuous gate sets may be a key component in extending the impact of near-term quantum computers.

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“…As proposed in Ref. 20, we can prepare arbitrary logical states by first initializing the data-qubit register in the product state…”

Section: Logical State Initialization Using Stabilizer Measurementsmentioning

confidence: 99%

Logical-qubit operations in an error-detecting surface code

Marques¹,

Varbanov²,

Moreira³

et al. 2021

Preprint

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Future fault-tolerant quantum computers will require storing and processing quantum data in logical qubits. We realize a suite of logical operations on a distance-two logical qubit stabilized using repeated error detection cycles. Logical operations include initialization into arbitrary states, measurement in the cardinal bases of the Bloch sphere, and a universal set of single-qubit gates. For each type of operation, we observe higher performance for fault-tolerant variants over non-fault-tolerant variants, and quantify the difference through detailed characterization. In particular, we demonstrate process tomography of logical gates, using the notion of a logical Pauli transfer matrix. This integration of high-fidelity logical operations with a scalable scheme for repeated stabilization is a milestone on the road to quantum error correction with higher-distance superconducting surface codes.

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Repeated quantum error detection in a surface code

Cited by 274 publications

References 47 publications

Leakage detection for a transmon-based surface code

Leakage detection for a transmon-based surface code

Improving the Performance of Deep Quantum Optimization Algorithms with Continuous Gate Sets

Logical-qubit operations in an error-detecting surface code

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