Efficient classical simulation and benchmarking of quantum processes in
the Weyl basis
- URL: http://arxiv.org/abs/2008.12250v2
- Date: Mon, 15 Mar 2021 23:05:13 GMT
- Title: Efficient classical simulation and benchmarking of quantum processes in
the Weyl basis
- Authors: Daniel Stilck Fran\c{c}a, Sergii Strelchuk, Micha{\l} Studzi\'nski
- Abstract summary: We develop a randomized benchmarking algorithm which uses Weyl unitaries to efficiently identify and learn a mixture of error models.
We apply our methods to ansatz circuits that appear in the Variational Quantum Eigensolver.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: One of the crucial steps in building a scalable quantum computer is to
identify the noise sources which lead to errors in the process of quantum
evolution. Different implementations come with multiple hardware-dependent
sources of noise and decoherence making the problem of their detection
manyfoldly more complex. We develop a randomized benchmarking algorithm which
uses Weyl unitaries to efficiently identify and learn a mixture of error models
which occur during the computation. We provide an efficiently computable
estimate of the overhead required to compute expectation values on outputs of
the noisy circuit relying only on locality of the interactions and no further
assumptions on the circuit structure. The overhead decreases with the noise
rate and this enables us to compute analytic noise bounds that imply efficient
classical simulability. We apply our methods to ansatz circuits that appear in
the Variational Quantum Eigensolver and establish an upper bound on classical
simulation complexity as a function of noise, identifying regimes when they
become classically efficiently simulatable.
Related papers
- Efficient Learning for Linear Properties of Bounded-Gate Quantum Circuits [63.733312560668274]
Given a quantum circuit containing d tunable RZ gates and G-d Clifford gates, can a learner perform purely classical inference to efficiently predict its linear properties?
We prove that the sample complexity scaling linearly in d is necessary and sufficient to achieve a small prediction error, while the corresponding computational complexity may scale exponentially in d.
We devise a kernel-based learning model capable of trading off prediction error and computational complexity, transitioning from exponential to scaling in many practical settings.
arXiv Detail & Related papers (2024-08-22T08:21:28Z) - A polynomial-time classical algorithm for noisy quantum circuits [1.2708457954150887]
We provide a-time classical algorithm for noisy quantum circuits.
Our approach is based upon the intuition that noise exponentially damps non-local correlations.
For constant noise rates, any quantum circuit for which error mitigation is efficient on most input states, is also classically simulable on most input states.
arXiv Detail & Related papers (2024-07-17T17:48:39Z) - Optimized noise-assisted simulation of the Lindblad equation with
time-dependent coefficients on a noisy quantum processor [0.6990493129893112]
Noise can be an asset in digital quantum simulations of open systems on Noisy Intermediate-Scale Quantum (NISQ) devices.
We introduce an optimized decoherence rate control scheme that can significantly reduce computational requirements by multiple orders of magnitude.
arXiv Detail & Related papers (2024-02-12T12:48:03Z) - 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) - Superposed Quantum Error Mitigation [1.732837834702512]
Overcoming the influence of noise and imperfections is a major challenge in quantum computing.
We present an approach based on applying a desired unitary computation in superposition between the system of interest and some auxiliary states.
We demonstrate, numerically and on the IBM Quantum Platform, that parallel applications of the same operation lead to significant noise mitigation.
arXiv Detail & Related papers (2023-04-17T18:01:01Z) - 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) - Characterizing and mitigating coherent errors in a trapped ion quantum
processor using hidden inverses [0.20315704654772418]
Quantum computing testbeds exhibit high-fidelity quantum control over small collections of qubits.
These noisy intermediate-scale devices can support a sufficient number of sequential operations prior to decoherence.
While the results of these algorithms are imperfect, these imperfections can help bootstrap quantum computer testbed development.
arXiv Detail & Related papers (2022-05-27T20:35:24Z) - 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) - Quantum Causal Unravelling [44.356294905844834]
We develop the first efficient method for unravelling the causal structure of the interactions in a multipartite quantum process.
Our algorithms can be used to identify processes that can be characterized efficiently with the technique of quantum process tomography.
arXiv Detail & Related papers (2021-09-27T16:28:06Z) - 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) - 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.