Bulletin of the American Physical Society
APS March Meeting 2022
Volume 67, Number 3
Monday–Friday, March 14–18, 2022; Chicago
Session S40: Noise Reduction and Error Mitigation in Quantum Computing IFocus Recordings Available
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Sponsoring Units: DQI Chair: Elizabeth Bennewitz, University of Maryland Room: McCormick Place W-196B |
Thursday, March 17, 2022 8:00AM - 8:12AM |
S40.00001: Qubit-efficient exponential suppression of errors Andrew T Arrasmith, Piotr J Czarnik, Lukasz Cincio, Patrick J Coles Achieving a practical advantage with near-term quantum computers hinges on having effective methods to suppress errors. Recent breakthroughs have introduced methods capable of exponentially suppressing errors by preparing multiple noisy copies of a state and virtually distilling a more purified version. Here we present an alternative method, the Resource-Efficient Quantum Error Suppression Technique (REQUEST), that adapts this breakthrough to much fewer qubits by making use of active qubit resets, a feature now available on commercial platforms. Our approach exploits a space/time trade-off to achieve a similar error reduction using only 2N+1 qubits as opposed to MN+1 qubits, for M copies of an N qubit state. Additionally, we propose a method using near-Clifford circuits to find the optimal number of these copies in the presence of realistic noise, which limits this error suppression. We perform a numerical comparison between the original method and our qubit-efficient version with a realistic trapped-ion noise model. We find that REQUEST can reproduce the exponential suppression of errors of the virtual distillation approach, while out-performing virtual distillation when fewer than 3N+1 qubits are available. Finally, we examine the scaling of the number of shots N_S required for REQUEST to achieve useful corrections. We find that N_S remains reasonable well into the quantum advantage regime where N is hundreds of qubits. |
Thursday, March 17, 2022 8:12AM - 8:24AM |
S40.00002: Error Mitigation with a Few Ancillas Alvin Gonzales Achieving high-fidelity quantum computation in the era of noisy intermediate scale quantum technologies requires the use of error mitigation. We introduce a new error mitigation technique that uses a small number of ancillas to mitigate errors by exploiting the symmetries preserved by the computation. Fidelity improvements are achieved by performing a pair of controlled unitary checks at two locations in the circuit. The method is a generalization of symmetry verification since the two controlled operations can be different, which relaxes the condition of commutation required in symmetry verification. Our approach is applicable to general circuits. We evaluate the performance with extensive numerical simulations using different error models, circuits, and unitary check placement. We also explore efficient techniques for finding suitable unitary checks. In this work we restrict these checks to the Pauli group. |
Thursday, March 17, 2022 8:24AM - 8:36AM |
S40.00003: Error Mitigation Via Emulated Measurement of Stabilizers Amy Greene, Morten Kjaergaard, Gabriel O Samach, Mollie E Schwartz, Andreas Bengtsson, Michael F O'Keeffe, Milad Marvian Mashhad, David K Kim, Alexander Melville, Bethany M Niedzielski, Antti Vepsalainen, Roni Winik, Jonilyn L Yoder, Danna Rosenberg, Seth Lloyd, Terry P Orlando, Simon Gustavsson, William D Oliver Error mitigation techniques are critical for quantum information processing in the era of Noisy Intermediate-Scale Quantum technology. Strategies for mitigating coherent errors are of particular interest, since infidelity grows linearly with incoherent errors but can grow quadratically with coherent errors. Randomized compiling has been gaining traction as a technique that mitigates coherent errors by rendering them incoherent. In this work, we discuss an alternative error mitigation technique called Quantum Measurement Emulation (QME) which addresses coherent errors in logical qubits by emulating the measurement of stabilizer operators via stochastic gate application. We show how QME leads to a first-order insensitivity to coherent errors and describe how it compares to randomized compiling. |
Thursday, March 17, 2022 8:36AM - 8:48AM |
S40.00004: Experimental error mitigation using linear rescaling for variational quantum eigensolving with up to 20 qubits Eliott N Rosenberg, Paul Ginsparg, Peter L McMahon Quantum computers have the potential to help solve a range of physics and chemistry problems, but noise in quantum hardware currently limits our ability to obtain accurate results from the execution of quantum-simulation algorithms. Various methods have been proposed to mitigate the impact of noise on variational algorithms, including several that model the noise as damping expectation values of observables. In this work, we benchmark various methods, including a new method proposed here. We compare their performance in estimating the ground-state energies of several instances of the 1D mixed-field Ising model using the variational-quantum-eigensolver algorithm with up to 20 qubits on two of IBM's quantum computers. We find that several error-mitigation techniques allow us to recover energies to within 10% of the true values for circuits containing up to about 25 ansatz layers, where each layer consists of CNOT gates between all neighboring qubits and Y-rotations on all qubits. |
Thursday, March 17, 2022 8:48AM - 9:00AM |
S40.00005: Scalable error mitigation for noisy quantum circuits produces competitive expectation values Youngseok Kim, Christopher J Wood, Theodore J Yoder, Seth T Merkel, Jay M Gambetta, Kristan Temme, Abhinav Kandala The measurement of relevant physical observables on near-term quantum processors that are classically intractable is a key milestone for demonstrating a useful quantum advantage. Existing quantum computers are noisy and require error mitigation techniques to achieve an accurate estimation of the observables. Zero-noise extrapolation (ZNE) is a popular error mitigation technique that has been adopted in several small-scale experiments, however, the practical scaling of this method to a larger system size remains unknown. Here, we establish the scalability of ZNE and use it to enhance the accuracy of the quench dynamics of a 2D Ising spin-lattice using up to 26 qubits of a fully programmable superconducting processor. We discuss several additional experiment strategies to extend the reach of ZNE. Finally, we show that the measured observables can surpass an established classical approximate method in the limit of increasing entanglement. |
Thursday, March 17, 2022 9:00AM - 9:12AM |
S40.00006: A Variational Approach to Quantum Error Mitigation Gokul Subramanian Ravi, Kaitlin N Smith, Pranav Gokhale, Andrea Mari, Nathan Earnest, Ali Javadi-Abhari, Frederic T Chong Variational Quantum Algorithms (VQAs) are relatively robust to noise, but errors are still a significant detriment to VQAs on near-term quantum machines. It is imperative to employ error mitigation techniques (EMs) to improve VQA fidelity. While existing EMs built from theory provide gains, the disconnect between theory and real machine execution limits their benefits. |
Thursday, March 17, 2022 9:12AM - 9:48AM |
S40.00007: Recent progress in error mitigation with fixed-frequency superconducting quantum processors Invited Speaker: Abhinav Kandala Error mitigation has emerged as a crucial ingredient in near-term, noisy quantum computation. Although quantum error correction is ultimately required to indefinitely extend the computation time, improvements in hardware will further enhance the reach and efficacy of error mitigation techniques. In this talk, I will highlight recent advances in fixed-frequency quantum processors and discuss related challenges for techniques such as zero-noise extrapolation. Ultimately, for these techniques to be valuable, they need to enable quantum computation that is competitive against relevant approximate classical techniques. In this context, I will discuss our recent experiments that suggest that these devices could be an attractive platform for the exploration of non-equilibrium many-body physics. This talk will discuss work from arXiv:2108.09197, arXiv:2106.00675 and arXiv:2105.15201. |
Thursday, March 17, 2022 9:48AM - 10:00AM |
S40.00008: Quantum simulation of mixed-field Ising model dynamics using pulse-level-controlled Trotter circuits and zero-noise extrapolation I Chi Chen, Benjamin Burdick, Thomas Iadecola, Peter P Orth, Yongxin Yao Quantum computers promise to enable the efficient simulation of quantum many-body systems with resources that do not increase exponentially with system size. However, uncorrected quantum noise in current noisy intermediate-scale quantum (NISQ) hardware results in the accumulation of substantial errors during a quantum computation, severely limiting their use. Here, we address this issue using a combination of error mitigation strategies on IBM QPUs and discuss the scaling of their performance with the number and quality of the qubits. We simulate the dynamics of the nonintegrable mixed-field Ising model in a regime where the system exhibits persistent oscillations for certain initial states. These coherent oscillations result from a phenomenon known as quantum many-body scars and provide a useful benchmark for the accuracy of the simulations. By exploiting pulse-level control and implementing several error mitigation techniques, including zero-noise extrapolation, dynamical decoupling, Pauli twirling, and symmetry-based postselection, we are able to follow the many-body coherent oscillations over a longer period of time. |
Thursday, March 17, 2022 10:00AM - 10:12AM |
S40.00009: Pulse Sequence Design for Crosstalk Mitigation Murphy Yuezhen Niu, Vadim Smelyanskiy, Hengyun Zhou, Dvir Kafri, Jonathan Gross, Juan Atalaya
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Thursday, March 17, 2022 10:12AM - 10:24AM |
S40.00010: Quantum Crosstalk Suppression Criteria Through Filter Function Design Zeyuan Zhou, Yasuo Oda, Gregory Quiroz Managing noise in quantum systems is a necessity for achieving scalable quantum information processing. While primary error sources include unwanted interactions between a quantum system and its environment, crosstalk can also prove to be a significant source of noise for some technologies. For example, superconducting qubit architectures are known to be susceptible to crosstalk occurring via control-line interference or parasitic ZZ-type interactions between qubits. In this work, we investigate the latter and develop criteria for crosstalk suppression from within the frequency-domain perspective of the filter function formalism. We demonstrate how this criteria can be leveraged to improve simultaneous noise characterization and control of multi-qubit systems. The efficacy of the criteria is examined via numerical simulations and experimental studies on the IBM Quantum Experience. |
Thursday, March 17, 2022 10:24AM - 10:36AM |
S40.00011: Mitigating Crosstalk on Quantum Computers via Digital Precompilation Adam Winick, Jan Balewski, Gang Huang, Yilun Xu, Joel Wallman, Joseph V Emerson Crosstalk errors have been a bane for experimentalists designing quantum computers for more than a decade. Fast two-qubit gates require spatially or spectrally nearby qubits, but such qubits are intrinsically more difficult to address individually. During this talk, we describe a scalable framework for modeling crosstalk effects on quantum information processors. We show how to apply optimal control techniques to tune up arbitrary high-fidelity parallel operations with substantial local and nonlocal crosstalk. We report on experimental data that validates the practicability of our work. These results show that instead of engineering away undesirable interactions during fabrication, chip designers should focus on removing other sources of errors and mitigate such effects with software through careful characterization and control optimization. |
Thursday, March 17, 2022 10:36AM - 10:48AM |
S40.00012: Unifying and benchmarking state-of-the-art quantum error mitigation techniques Max H Gordon Error mitigation is an essential component of achieving practical quantum advantage in the near term, and a number of different approaches have been proposed. In this work [1], we recognize that many state-of-the-art error mitigation methods share a common feature: they are data-driven, employing classical data obtained from runs of different quantum circuits. For example, Zero-noise extrapolation (ZNE) uses variable noise data and Clifford-data regression (CDR) uses data from near-Clifford circuits. We show that Virtual Distillation (VD) can be viewed in a similar manner by considering classical data produced from different numbers of state preparations. This allows us to unify these three methods under a general data-driven error mitigation framework that we call UNIfied Technique for Error mitigation with Data (UNITED). We find that our UNITED method can outperform the individual methods (i.e., the whole is better than the individual parts). Specifically, we employ a realistic noise model obtained from a trapped ion quantum computer to benchmark UNITED, as well as state-of-the-art methods, for problems with various numbers of qubits, circuit depths and total numbers of shots. We find that different techniques are optimal for different shot budgets. For our largest considered shot budget (1010), UNITED gives the most accurate correction. Our work represents a benchmarking of current error mitigation methods, and provides a guide for the regimes when certain methods are most useful. |
Thursday, March 17, 2022 10:48AM - 11:00AM |
S40.00013: Getting more out of quantum coherence, pushing Robust Amplitude Estimation further Archismita Dalal, Amara Katabarwa, Peter Johnson A universal fault-tolerant quantum computer holds the promise to speed up computational problems that are otherwise intractable on classical computers; however, for the near term we only have access to noisy intermediate-scale quantum (NISQ) computers. A major issue for quantum algorithms, especially in the NISQ era, is that they require too many independent measurements; this motivated Robust Amplitude Estimation (RAE), which is a quantum-enhanced algorithm for estimating expectation values of Pauli operators with fewer measurements. The impact of device noise on RAE is incorporated into one of its subroutines as a circuit-depolarizing noise model, which is unrealistic and hence hinders algorithmic performance. Rather than explicitly incorporating realistic noise effects in RAE, which is infeasible, we tailor device noise to generate an effective noise model, whose impact on RAE closely resembles that of the circuit-depolarizing model. Using IBM's quantum devices, we show that our noise-tailored RAE algorithm is able to regain improvements in both bias and precision that are expected for RAE in far noisier situations. Thus our work extends the feasibility of RAE on NISQ computers, consequently bringing us one step closer towards achieving quantum advantage using these devices. |
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