Bulletin of the American Physical Society
APS March Meeting 2023
Volume 68, Number 3
Las Vegas, Nevada (March 5-10)
Virtual (March 20-22); Time Zone: Pacific Time
Session T69: Quantum Error Mitigation Techniques for Quantum ComputationInvited
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Sponsoring Units: DQI Chair: Riddhi Swaroop Gupta, IBM Quantum Room: Room 421 |
Thursday, March 9, 2023 11:30AM - 12:06PM |
T69.00001: Probabilistic error cancellation with sparse Pauli-Lindblad models on noisy quantum processors Invited Speaker: Ewout van den Berg The practical capabilities of contemporary quantum processors are largely limited by noise. Eventually, this problem will be resolved using quantum error correction, but in the meantime we can improve performance using error-mitigation techniques. Probabilistic error cancellation (PEC) is one such technique and works by forming a model of the noise associated with one or more gates in a quantum circuit. By generating circuit instances with samples from the inverse noise distribution, we can effectively cancel the noise on such gates and improve the accuracy of measured observables. |
Thursday, March 9, 2023 12:06PM - 12:42PM |
T69.00002: From error suppression to error mitigation in quantum algorithms Invited Speaker: Dorit Aharonov Arguably, the most pressing challenge faced by developers of quantum computers, is to reduce the effects of noise and inaccuracies on the performance of quantum circuits. This is important not only for the ability to run useful quantum algorithms in the "NISQ era", namely with the relatively small and noisy quantum computers available today, but also for lowering the barriers and reducing the immense resources required for achieving the holy grail of quantum fault tolerance. Quite a few tools have been developed for this task, under the names of error suppression and error mitigation. In this talk I will introduce the error suppression and mitigation software developed at QEDMA Quantum Computing, and present experimental demonstrations of significant improvements in performance achieved when applying this software to several quantum algorithms and devices. |
Thursday, March 9, 2023 12:42PM - 1:18PM |
T69.00003: Characterizing the ultimate potential and limitations of quantum error mitigation Invited Speaker: Ryuji Takagi The inevitable accumulation of errors in near-future quantum devices represents a key obstacle in delivering practical quantum advantages, motivating the development of various quantum error-mitigation methods. Although numerous quantum error-mitigation protocols have been proposed, their general potential and limitations have still been elusive, hindering us from pinpointing the theoretical goal that new error-mitigation proposals should aim at. In this talk, I will review recent advances in the general theory of quantum error mitigation toward characterizing its ultimate capability. I will introduce universal performance bounds applicable to general error-mitigation protocols, which provide an effective platform to discuss the optimality of specific mitigation methods among a general class. I will apply these bounds to show that the number of samples required for general mitigation protocols must grow exponentially with the circuit depth for various noise models, revealing the fundamental obstacles in showing useful applications of noisy near-term quantum devices. This talk includes results reported in R. Takagi, S. Endo, S. Minagawa, M. Gu, "Fundamental limits of quantum error mitigation", npj Quantum Inf. 8, 114 (2022), and R. Takagi, H. Tajima, M. Gu, "Universal sample lower bounds for quantum error mitigation", arXiv:2208.09178. |
Thursday, March 9, 2023 1:18PM - 1:54PM |
T69.00004: The learnability of Pauli noise Invited Speaker: Senrui Chen Understanding quantum noise is a major challenge for scaling up quantum computing systems. Despite recent developments in quantum noise characterization methods, the fundamental question of what information about gate noise is self-consistently learnable has been unclear even for a single CNOT gate. In this work, we give a precise characterization about the learnability of Pauli noise associated with Clifford gates using graph theoretical tools, showing that the learnable information corresponds exactly to the cycle space of the pattern transfer graph of a given gate set. We show that a modified version of cycle benchmarking can extract all learnable information of Pauli noise. We experimentally demonstrate Pauli noise characterization of IBM’s CNOT gate, where we learn all 14 learnable degrees of freedom and bound the 2 unlearnable degrees of freedom using physical constraints. The implications of these results for quantum error mitigation will be discussed. We will also talk about the possibility to resolve the unlearnability by going beyond qubits and leveraging additional energy levels. |
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