Increasing the Measured Effective Quantum Volume with Zero Noise Extrapolation

• URL: http://arxiv.org/abs/2306.15863v2
• Date: Tue, 2 Jul 2024 21:57:54 GMT
• Title: Increasing the Measured Effective Quantum Volume with Zero Noise Extrapolation
• Authors: Elijah Pelofske, Vincent Russo, Ryan LaRose, Andrea Mari, Dan Strano, Andreas Bärtschi, Stephan Eidenbenz, William J. Zeng,
• Abstract summary: We show that ZNE can increase the effective quantum volume over the vendor-measured quantum volume. Specifically, we measure the effective quantum volume of four IBM Quantum superconducting processor units.
• Score: 1.0037949839020766
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Quantum Volume is a full-stack benchmark for near-term quantum computers. It quantifies the largest size of a square circuit which can be executed on the target device with reasonable fidelity. Error mitigation is a set of techniques intended to remove the effects of noise present in the computation of noisy quantum computers when computing an expectation value of interest. Effective quantum volume is a proposed metric that applies error mitigation to the quantum volume protocol in order to evaluate the effectiveness not only of the target device but also of the error mitigation algorithm. Digital Zero-Noise Extrapolation (ZNE) is an error mitigation technique that estimates the noiseless expectation value using circuit folding to amplify errors by known scale factors and extrapolating to the zero-noise limit. Here we demonstrate that ZNE, with global and local unitary folding with fractional scale factors, in conjunction with dynamical decoupling, can increase the effective quantum volume over the vendor-measured quantum volume. Specifically, we measure the effective quantum volume of four IBM Quantum superconducting processor units, obtaining values that are larger than the vendor-measured quantum volume on each device. This is the first such increase reported.

Related papers

• The curse of random quantum data [62.24825255497622]
  We quantify the performances of quantum machine learning in the landscape of quantum data. We find that the training efficiency and generalization capabilities in quantum machine learning will be exponentially suppressed with the increase in qubits. Our findings apply to both the quantum kernel method and the large-width limit of quantum neural networks.
  arXiv  Detail & Related papers  (2024-08-19T12:18:07Z)
• Power Characterization of Noisy Quantum Kernels [52.47151453259434]
  We show that noise may make quantum kernel methods to only have poor prediction capability, even when the generalization error is small. We provide a crucial warning to employ noisy quantum kernel methods for quantum computation.
  arXiv  Detail & Related papers  (2024-01-31T01:02:16Z)
• QuantumSEA: In-Time Sparse Exploration for Noise Adaptive Quantum Circuits [82.50620782471485]
  QuantumSEA is an in-time sparse exploration for noise-adaptive quantum circuits. It aims to achieve two key objectives: (1) implicit circuits capacity during training and (2) noise robustness. Our method establishes state-of-the-art results with only half the number of quantum gates and 2x time saving of circuit executions.
  arXiv  Detail & Related papers  (2024-01-10T22:33:00Z)
• Near-Term Distributed Quantum Computation using Mean-Field Corrections and Auxiliary Qubits [77.04894470683776]
  We propose near-term distributed quantum computing that involve limited information transfer and conservative entanglement production. We build upon these concepts to produce an approximate circuit-cutting technique for the fragmented pre-training of variational quantum algorithms.
  arXiv  Detail & Related papers  (2023-09-11T18:00:00Z)
• Leveraging hardware-control imperfections for error mitigation via generalized quantum subspace [0.8399688944263843]
  In the era of quantum computing without full fault-tolerance, it is essential to suppress noise effects via the quantum error mitigation techniques to enhance the computational power of the quantum devices. One of the most effective noise-agnostic error mitigation schemes is the generalized quantum subspace expansion (GSE) method. We propose the fault-subspace method, which constructs an error-mitigated quantum state with copies of quantum states with different noise levels.
  arXiv  Detail & Related papers  (2023-03-14T07:01:30Z)
• Iterative Qubits Management for Quantum Index Searching in a Hybrid System [56.39703478198019]
  IQuCS aims at index searching and counting in a quantum-classical hybrid system. We implement IQuCS with Qiskit and conduct intensive experiments. Results demonstrate that it reduces qubits consumption by up to 66.2%.
  arXiv  Detail & Related papers  (2022-09-22T21:54:28Z)
• Universal cost bound of quantum error mitigation based on quantum estimation theory [0.0]
  We present a unified approach to analyzing the cost of various quantum error mitigation methods on the basis of quantum estimation theory. We derive for a generic layered quantum circuit under a wide class of Markovian noise that, unbiased estimation of an observable encounters an exponential growth with the circuit depth in the lower bound on the measurement cost. Our results contribute to the understanding of the physical limitations of quantum error mitigation and offer a new criterion for evaluating the performance of quantum error mitigation techniques.
  arXiv  Detail & Related papers  (2022-08-19T15:04:36Z)
• Error mitigation increases the effective quantum volume of quantum computers [1.0499611180329804]
  We show that error mitigation increases the effective quantum volume of several quantum computers. We encourage the adoption of quantum volume as a benchmark for assessing the performance of error mitigation techniques.
  arXiv  Detail & Related papers  (2022-03-10T17:14:34Z)
• Achieving fault tolerance against amplitude-damping noise [1.7289359743609742]
  We develop a protocol for fault-tolerant encoded quantum computing components in the presence of amplitude-damping noise. We describe a universal set of fault-tolerant encoded gadgets and compute the pseudothreshold for the noise. Our work demonstrates the possibility of applying the ideas of quantum fault tolerance to targeted noise models.
  arXiv  Detail & Related papers  (2021-07-12T14:59:54Z)
• Minimizing estimation runtime on noisy quantum computers [0.0]
  "engineered likelihood function" (ELF) is used for carrying out Bayesian inference. We show how the ELF formalism enhances the rate of information gain in sampling as the physical hardware transitions from the regime of noisy quantum computers. This technique speeds up a central component of many quantum algorithms, with applications including chemistry, materials, finance, and beyond.
  arXiv  Detail & Related papers  (2020-06-16T17:46:18Z)
• An Application of Quantum Annealing Computing to Seismic Inversion [55.41644538483948]
  We apply a quantum algorithm to a D-Wave quantum annealer to solve a small scale seismic inversions problem. The accuracy achieved by the quantum computer is at least as good as that of the classical computer.
  arXiv  Detail & Related papers  (2020-05-06T14:18:44Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.