Analog simulation of noisy quantum circuits

• URL: http://arxiv.org/abs/2410.08639v1
• Date: Fri, 11 Oct 2024 09:04:02 GMT
• Title: Analog simulation of noisy quantum circuits
• Authors: Etienne Granet, Kévin Hémery, Henrik Dreyer,
• Abstract summary: We propose a simulation technique based on a representation of hardware noise in terms of trajectories generated by operators that remain close to identity at low noise. This representation significantly reduces the variance over the quantum trajectories, speeding up noisy simulations by factors around $10$ to $100$.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: It is well-known that simulating quantum circuits with low but non-zero hardware noise is more difficult than without noise. It requires either to perform density matrix simulations (coming with a space overhead) or to sample over "quantum trajectories" where Kraus operators are inserted randomly (coming with a runtime overhead). We propose a simulation technique based on a representation of hardware noise in terms of trajectories generated by operators that remain close to identity at low noise. This representation significantly reduces the variance over the quantum trajectories, speeding up noisy simulations by factors around $10$ to $100$. As a by-product, we provide a formula to factorize multiple-Pauli channels into a concatenation of single Pauli channels.

Related papers

• 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)
• Simulating photonic devices with noisy optical elements [0.615738282053772]
  In the near-term, the performance of any quantum algorithm should be tested and simulated in the presence of noise. We apply the recently proposed noisy gates approach to efficiently simulate noisy optical circuits. We also evaluate the performance of a photonic variational quantum algorithm to solve the MAX-2-CUT problem.
  arXiv  Detail & Related papers  (2023-11-17T16:06:20Z)
• Classical simulations of noisy variational quantum circuits [0.0]
  Noisely affects quantum computations so that they not only become less accurate but also easier to simulate classically as systems scale up. We construct a classical simulation algorithm, LOWESA, for estimating expectation values of noisy parameterised quantum circuits.
  arXiv  Detail & Related papers  (2023-06-08T17:52:30Z)
• Importance sampling for stochastic quantum simulations [68.8204255655161]
  We introduce the qDrift protocol, which builds random product formulas by sampling from the Hamiltonian according to the coefficients. We show that the simulation cost can be reduced while achieving the same accuracy, by considering the individual simulation cost during the sampling stage. Results are confirmed by numerical simulations performed on a lattice nuclear effective field theory.
  arXiv  Detail & Related papers  (2022-12-12T15:06:32Z)
• Approximation Algorithm for Noisy Quantum Circuit Simulation [3.55689240295244]
  This paper introduces a novel approximation algorithm for simulating noisy quantum circuits. Our method offers a speedup over the commonly-used approximation (sampling) algorithm -- quantum trajectories method.
  arXiv  Detail & Related papers  (2022-11-30T14:20:22Z)
• Quantum emulation of the transient dynamics in the multistate Landau-Zener model [50.591267188664666]
  We study the transient dynamics in the multistate Landau-Zener model as a function of the Landau-Zener velocity. Our experiments pave the way for more complex simulations with qubits coupled to an engineered bosonic mode spectrum.
  arXiv  Detail & Related papers  (2022-11-26T15:04:11Z)
• Stochastic Approach For Simulating Quantum Noise Using Tensor Networks [0.8258451067861933]
  We show that our simulation error is relatively low, even for large numbers of qubits. By using the slicing technique, we can simulate up to 100 qubitOA circuits with high depth using supercomputers.
  arXiv  Detail & Related papers  (2022-10-28T03:44:59Z)
• 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)
• A deep learning model for noise prediction on near-term quantum devices [137.6408511310322]
  We train a convolutional neural network on experimental data from a quantum device to learn a hardware-specific noise model. A compiler then uses the trained network as a noise predictor and inserts sequences of gates in circuits so as to minimize expected noise.
  arXiv  Detail & Related papers  (2020-05-21T17:47:29Z)
• Efficient classical simulation of random shallow 2D quantum circuits [104.50546079040298]
  Random quantum circuits are commonly viewed as hard to simulate classically. We show that approximate simulation of typical instances is almost as hard as exact simulation. We also conjecture that sufficiently shallow random circuits are efficiently simulable more generally.
  arXiv  Detail & Related papers  (2019-12-31T19:00:00Z)

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.