Error mitigation by training with fermionic linear optics
- URL: http://arxiv.org/abs/2102.02120v1
- Date: Wed, 3 Feb 2021 15:56:23 GMT
- Title: Error mitigation by training with fermionic linear optics
- Authors: Ashley Montanaro and Stasja Stanisic
- Abstract summary: We describe a method of reducing errors which is tailored to quantum algorithms for simulating fermionic systems.
The method is based on executing quantum circuits in the model of fermionic linear optics, which are known to be efficiently simulable classically.
In classical numerical simulations of 12-qubit examples with physically realistic levels of depolarising noise, errors were reduced by a factor of around 34 compared with the uncorrected case.
- Score: 0.05076419064097732
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Noisy intermediate-scale quantum (NISQ) computers could solve
quantum-mechanical simulation problems that are beyond the capabilities of
classical computers. However, NISQ devices experience significant errors which,
if not corrected, can render physical quantities measured in these simulations
inaccurate or meaningless. Here we describe a method of reducing these errors
which is tailored to quantum algorithms for simulating fermionic systems. The
method is based on executing quantum circuits in the model of fermionic linear
optics, which are known to be efficiently simulable classically, to infer the
relationship between exact and noisy measurement outcomes, and hence undo the
effect of noise. We validated our method by applying it to the VQE algorithm
for estimating ground state energies of instances of the Fermi-Hubbard model.
In classical numerical simulations of 12-qubit examples with physically
realistic levels of depolarising noise, errors were reduced by a factor of
around 34 compared with the uncorrected case. Smaller experiments on quantum
hardware demonstrate an average reduction in errors by a factor of 10 or more.
Related papers
- 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) - Quantum Trajectory Approach to Error Mitigation [0.0]
Quantum Error Mitigation (EM) is a collection of strategies to reduce errors on noisy quantum devices.
We show that the inverse of noise maps can be realised by performing classical post-processing.
We demonstrate our result on a model relevant for current NISQ devices.
arXiv Detail & Related papers (2023-05-31T14:10:35Z) - Towards Neural Variational Monte Carlo That Scales Linearly with System
Size [67.09349921751341]
Quantum many-body problems are central to demystifying some exotic quantum phenomena, e.g., high-temperature superconductors.
The combination of neural networks (NN) for representing quantum states, and the Variational Monte Carlo (VMC) algorithm, has been shown to be a promising method for solving such problems.
We propose a NN architecture called Vector-Quantized Neural Quantum States (VQ-NQS) that utilizes vector-quantization techniques to leverage redundancies in the local-energy calculations of the VMC algorithm.
arXiv Detail & Related papers (2022-12-21T19:00:04Z) - Probing finite-temperature observables in quantum simulators of spin
systems with short-time dynamics [62.997667081978825]
We show how finite-temperature observables can be obtained with an algorithm motivated from the Jarzynski equality.
We show that a finite temperature phase transition in the long-range transverse field Ising model can be characterized in trapped ion quantum simulators.
arXiv Detail & Related papers (2022-06-03T18:00:02Z) - Simulation and performance analysis of quantum error correction with a
rotated surface code under a realistic noise model [0.6946929968559495]
Demonstration of quantum error correction (QEC) is one of the most important milestones in the realization of fully-fledged quantum computers.
In this work, we performed a full simulation of QEC for the rotated surface codes with a code distance 5, which employs 49 qubits.
We evaluate the logical error probability in a realistic noise model that incorporates not only Pauli errors but also coherent errors due to a systematic control error or unintended interactions.
arXiv Detail & Related papers (2022-04-25T02:45:06Z) - Fermionic approach to variational quantum simulation of Kitaev spin
models [50.92854230325576]
Kitaev spin models are well known for being exactly solvable in a certain parameter regime via a mapping to free fermions.
We use classical simulations to explore a novel variational ansatz that takes advantage of this fermionic representation.
We also comment on the implications of our results for simulating non-Abelian anyons on quantum computers.
arXiv Detail & Related papers (2022-04-11T18:00:01Z) - Measuring NISQ Gate-Based Qubit Stability Using a 1+1 Field Theory and
Cycle Benchmarking [50.8020641352841]
We study coherent errors on a quantum hardware platform using a transverse field Ising model Hamiltonian as a sample user application.
We identify inter-day and intra-day qubit calibration drift and the impacts of quantum circuit placement on groups of qubits in different physical locations on the processor.
This paper also discusses how these measurements can provide a better understanding of these types of errors and how they may improve efforts to validate the accuracy of quantum computations.
arXiv Detail & Related papers (2022-01-08T23:12:55Z) - Numerical Simulations of Noisy Quantum Circuits for Computational
Chemistry [51.827942608832025]
Near-term quantum computers can calculate the ground-state properties of small molecules.
We show how the structure of the computational ansatz as well as the errors induced by device noise affect the calculation.
arXiv Detail & Related papers (2021-12-31T16:33:10Z) - Model-Independent Error Mitigation in Parametric Quantum Circuits and
Depolarizing Projection of Quantum Noise [1.5162649964542718]
Finding ground states and low-lying excitations of a given Hamiltonian is one of the most important problems in many fields of physics.
quantum computing on Noisy Intermediate-Scale Quantum (NISQ) devices offers the prospect to efficiently perform such computations.
Current quantum devices still suffer from inherent quantum noise.
arXiv Detail & Related papers (2021-11-30T16:08:01Z) - Neural Error Mitigation of Near-Term Quantum Simulations [0.0]
We introduce $textitneural error mitigation$, a novel method that uses neural networks to improve estimates of ground states and ground-state observables.
Our results show that neural error mitigation improves the numerical and experimental VQE computation to yield low-energy errors.
Our method is a promising strategy for extending the reach of near-term quantum computers to solve complex quantum simulation problems.
arXiv Detail & Related papers (2021-05-17T18:00:57Z) - Error mitigation and quantum-assisted simulation in the error corrected
regime [77.34726150561087]
A standard approach to quantum computing is based on the idea of promoting a classically simulable and fault-tolerant set of operations.
We show how the addition of noisy magic resources allows one to boost classical quasiprobability simulations of a quantum circuit.
arXiv Detail & Related papers (2021-03-12T20:58:41Z)
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.