Efficient simulation of parametrized quantum circuits under non-unital noise through Pauli backpropagation

• URL: http://arxiv.org/abs/2501.13050v1
• Date: Wed, 22 Jan 2025 17:58:59 GMT
• Title: Efficient simulation of parametrized quantum circuits under non-unital noise through Pauli backpropagation
• Authors: Victor Martinez, Armando Angrisani, Ekaterina Pankovets, Omar Fawzi, Daniel Stilck França,
• Abstract summary: Pauli backpropagation algorithms have already demonstrated their ability to efficiently simulate certain classes of parameterized quantum circuits. Here, we close this gap by adapting Pauli backpropagation to non-unital noise.
• Score: 4.903915603499684
• License:
• Abstract: As quantum devices continue to grow in size but remain affected by noise, it is crucial to determine when and how they can outperform classical computers on practical tasks. A central piece in this effort is to develop the most efficient classical simulation algorithms possible. Among the most promising approaches are Pauli backpropagation algorithms, which have already demonstrated their ability to efficiently simulate certain classes of parameterized quantum circuits-a leading contender for near-term quantum advantage-under random circuit assumptions and depolarizing noise. However, their efficiency was not previously established for more realistic non-unital noise models, such as amplitude damping, that better capture noise on existing hardware. Here, we close this gap by adapting Pauli backpropagation to non-unital noise, proving that it remains efficient even under these more challenging conditions. Our proof leverages a refined combinatorial analysis to handle the complexities introduced by non-unital channels, thus strengthening Pauli backpropagation as a powerful tool for simulating near-term quantum devices.

Related papers

• Simulating quantum circuits with arbitrary local noise using Pauli Propagation [0.0]
  We present a classical algorithm for estimating expectation values of arbitrary observables on typical quantum circuits under any incoherent local noise. We show that this does not apply to average-case circuits, as these can be efficiently simulated using Pauli-path methods.
  arXiv  Detail & Related papers  (2025-01-22T18:57:16Z)
• Bayesian Quantum Amplitude Estimation [49.1574468325115]
  We introduce BAE, a noise-aware Bayesian algorithm for quantum amplitude estimation. We show that BAE achieves Heisenberg-limited estimation and benchmark it against other approaches.
  arXiv  Detail & Related papers  (2024-12-05T18:09:41Z)
• Optimal Quantum Purity Amplification [2.05170973574812]
  Quantum purity amplification (QPA) offers a novel approach to counteract the pervasive noise that degrades quantum states. We present the optimal QPA protocol for general quantum systems against global depolarizing noise. Our findings suggest that QPA could improve the performance of quantum information processing tasks.
  arXiv  Detail & Related papers  (2024-09-26T17:46:00Z)
• Bayesian Parameterized Quantum Circuit Optimization (BPQCO): A task and hardware-dependent approach [49.89480853499917]
  Variational quantum algorithms (VQA) have emerged as a promising quantum alternative for solving optimization and machine learning problems. In this paper, we experimentally demonstrate the influence of the circuit design on the performance obtained for two classification problems. We also study the degradation of the obtained circuits in the presence of noise when simulating real quantum computers.
  arXiv  Detail & Related papers  (2024-04-17T11:00:12Z)
• Noise-induced shallow circuits and absence of barren plateaus [2.5295633594332334]
  We show that any noise truncates' most quantum circuits to effectively logarithmic depth. We then prove that quantum circuits under any non-unital noise exhibit lack of barren plateaus for cost functions composed of local observables.
  arXiv  Detail & Related papers  (2024-03-20T19:00:49Z)
• 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)
• Limitations of variational quantum algorithms: a quantum optimal transport approach [11.202435939275675]
  We obtain extremely tight bounds for standard NISQ proposals in both the noisy and noiseless regimes. The bounds limit the performance of both circuit model algorithms, such as QAOA, and also continuous-time algorithms, such as quantum annealing.
  arXiv  Detail & Related papers  (2022-04-07T13:58:44Z)
• Quantum algorithms for quantum dynamics: A performance study on the spin-boson model [68.8204255655161]
  Quantum algorithms for quantum dynamics simulations are traditionally based on implementing a Trotter-approximation of the time-evolution operator. variational quantum algorithms have become an indispensable alternative, enabling small-scale simulations on present-day hardware. We show that, despite providing a clear reduction of quantum gate cost, the variational method in its current implementation is unlikely to lead to a quantum advantage.
  arXiv  Detail & Related papers  (2021-08-09T18:00:05Z)
• Pulse-level noisy quantum circuits with QuTiP [53.356579534933765]
  We introduce new tools in qutip-qip, QuTiP's quantum information processing package. These tools simulate quantum circuits at the pulse level, leveraging QuTiP's quantum dynamics solvers and control optimization features. We show how quantum circuits can be compiled on simulated processors, with control pulses acting on a target Hamiltonian.
  arXiv  Detail & Related papers  (2021-05-20T17:06:52Z)
• Comparative Study of Sampling-Based Simulation Costs of Noisy Quantum Circuits [0.8206877486958002]
  We characterize the simulation costs of two major quantum schemes, stabilizer-state sampling of magic states and Heisenberg propagation. It revealed that in the low noise regime, stabilizer-state sampling results in a smaller sampling cost, while Heisenberg propagation is better in the high noise regime.
  arXiv  Detail & Related papers  (2020-11-12T07:12:47Z)
• Quantum circuit architecture search for variational quantum algorithms [88.71725630554758]
  We propose a resource and runtime efficient scheme termed quantum architecture search (QAS) QAS automatically seeks a near-optimal ansatz to balance benefits and side-effects brought by adding more noisy quantum gates. We implement QAS on both the numerical simulator and real quantum hardware, via the IBM cloud, to accomplish data classification and quantum chemistry tasks.
  arXiv  Detail & Related papers  (2020-10-20T12:06:27Z)

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.