Error Mitigation for Deep Quantum Optimization Circuits by Leveraging
Problem Symmetries
- URL: http://arxiv.org/abs/2106.04410v2
- Date: Wed, 9 Jun 2021 15:49:36 GMT
- Title: Error Mitigation for Deep Quantum Optimization Circuits by Leveraging
Problem Symmetries
- Authors: Ruslan Shaydulin and Alexey Galda
- Abstract summary: We introduce an application-specific approach for mitigating the errors in QAOA evolution by leveraging the symmetries present in the classical objective function to be optimized.
Specifically, the QAOA state is projected into the symmetry-restricted subspace, with projection being performed either at the end of the circuit or throughout the evolution.
Our approach improves the fidelity of the QAOA state, thereby increasing both the accuracy of the sample estimate of the QAOA objective and the probability of sampling the binary string corresponding to that objective value.
- Score: 2.517903855792476
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: High error rates and limited fidelity of quantum gates in near-term quantum
devices are the central obstacles to successful execution of the Quantum
Approximate Optimization Algorithm (QAOA). In this paper we introduce an
application-specific approach for mitigating the errors in QAOA evolution by
leveraging the symmetries present in the classical objective function to be
optimized. Specifically, the QAOA state is projected into the
symmetry-restricted subspace, with projection being performed either at the end
of the circuit or throughout the evolution. Our approach improves the fidelity
of the QAOA state, thereby increasing both the accuracy of the sample estimate
of the QAOA objective and the probability of sampling the binary string
corresponding to that objective value. We demonstrate the efficacy of the
proposed methods on QAOA applied to the MaxCut problem, although our methods
are general and apply to any objective function with symmetries, as well as to
the generalization of QAOA with alternative mixers. We experimentally verify
the proposed methods on an IBM Quantum processor, utilizing up to 5 qubits.
When leveraging a global bit-flip symmetry, our approach leads to a 23% average
improvement in quantum state fidelity.
Related papers
- 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) - Measurement-Based Quantum Approximate Optimization [0.24861619769660645]
We focus on measurement-based quantum computing protocols for approximate optimization.
We derive measurement patterns for applying QAOA to the broad and important class of QUBO problems.
We discuss the resource requirements and tradeoffs of our approach to that of more traditional quantum circuits.
arXiv Detail & Related papers (2024-03-18T06:59:23Z) - Bayesian Optimization for QAOA [0.0]
We present a Bayesian optimization procedure to optimise a quantum circuit.
We show that our approach allows for a significant reduction in the number of calls to the quantum circuit.
Our results suggest that the method proposed here is a promising framework to leverage the hybrid nature of QAOA on the noisy intermediate-scale quantum devices.
arXiv Detail & Related papers (2022-09-08T13:59:47Z) - Improving the performance of quantum approximate optimization for
preparing non-trivial quantum states without translational symmetry [10.967081346848687]
We study the performance of the quantum approximate optimization algorithm (QAOA) for preparing ground states of target Hamiltonians.
We propose a generalized QAOA assisted by the parameterized resource Hamiltonian to achieve a better performance.
Our work paves the way for performing QAOA on programmable quantum processors without translational symmetry.
arXiv Detail & Related papers (2022-06-06T14:17:58Z) - Characterizing Error Mitigation by Symmetry Verification in QAOA [2.9860417981482263]
Hardware errors are a major obstacle to demonstrating quantum advantage with the quantum approximate optimization algorithm (QAOA)
Symmetry verification uses parity checks that leverage the symmetries of the objective function to be optimized.
We numerically investigate the symmetry verification on the MaxCut problem and identify the error regimes in which this approach improves the QAOA objective.
arXiv Detail & Related papers (2022-04-12T14:51:14Z) - General Hamiltonian Representation of ML Detection Relying on the
Quantum Approximate Optimization Algorithm [74.6114458993128]
The quantum approximate optimization algorithm (QAOA) conceived for solving optimization problems can be run on the existing noisy intermediate-scale quantum (NISQ) devices.
We solve the maximum likelihood (ML) detection problem for general constellations by appropriately adapting the QAOA.
In particular, for an M-ary Gray-mapped quadrature amplitude modulation (MQAM) constellation, we show that the specific qubits encoding the in-phase components and those encoding the quadrature components are independent in the quantum system of interest.
arXiv Detail & Related papers (2022-04-11T14:11:24Z) - Adiabatic Quantum Computing for Multi Object Tracking [170.8716555363907]
Multi-Object Tracking (MOT) is most often approached in the tracking-by-detection paradigm, where object detections are associated through time.
As these optimization problems are often NP-hard, they can only be solved exactly for small instances on current hardware.
We show that our approach is competitive compared with state-of-the-art optimization-based approaches, even when using of-the-shelf integer programming solvers.
arXiv Detail & Related papers (2022-02-17T18:59:20Z) - Circuit Symmetry Verification Mitigates Quantum-Domain Impairments [69.33243249411113]
We propose circuit-oriented symmetry verification that are capable of verifying the commutativity of quantum circuits without the knowledge of the quantum state.
In particular, we propose the Fourier-temporal stabilizer (STS) technique, which generalizes the conventional quantum-domain formalism to circuit-oriented stabilizers.
arXiv Detail & Related papers (2021-12-27T21:15:35Z) - Quantum Approximate Optimization Algorithm applied to the binary
perceptron [0.46664938579243564]
We apply digitized Quantum Annealing (QA) and Quantum Approximate Optimization Algorithm (QAOA) to a paradigmatic task of supervised learning in artificial neural networks.
We provide evidence for the existence of optimal smooth solutions for the QAOA parameters, which are transferable among typical instances of the same problem.
We prove numerically an enhanced performance of QAOA over traditional QA.
arXiv Detail & Related papers (2021-12-19T18:33:22Z) - Analytical and experimental study of center line miscalibrations in M\o
lmer-S\o rensen gates [51.93099889384597]
We study a systematic perturbative expansion in miscalibrated parameters of the Molmer-Sorensen entangling gate.
We compute the gate evolution operator which allows us to obtain relevant key properties.
We verify the predictions from our model by benchmarking them against measurements in a trapped-ion quantum processor.
arXiv Detail & Related papers (2021-12-10T10:56:16Z) - Quantum Approximate Optimization Algorithm Based Maximum Likelihood
Detection [80.28858481461418]
Recent advances in quantum technologies pave the way for noisy intermediate-scale quantum (NISQ) devices.
Recent advances in quantum technologies pave the way for noisy intermediate-scale quantum (NISQ) devices.
arXiv Detail & Related papers (2021-07-11T10:56:24Z)
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.