Filter-enhanced adiabatic quantum computing on a digital quantum processor
- URL: http://arxiv.org/abs/2503.20674v1
- Date: Wed, 26 Mar 2025 16:08:12 GMT
- Title: Filter-enhanced adiabatic quantum computing on a digital quantum processor
- Authors: Erenay Karacan, Conor Mc Keever, Michael Foss-Feig, David Hayes, Michael Lubasch,
- Abstract summary: We describe a strategy to implement a ground-state filter on quantum hardware in the presence of noise.<n>The adiabatically prepared input state increases the success probability of the filter and also reduces its circuit depth requirements.<n>We demonstrate a significant improvement in ground-state accuracies for paradigmatic quantum spin models.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Eigenstate filters underpin near-optimal quantum algorithms for ground state preparation. Their realization on current quantum computers, however, poses a challenge as the filters are typically represented by deep quantum circuits. Additionally, since the filters are created probabilistically, their circuits need to be rerun many times when the associated success probability is small. Here we describe a strategy to implement a ground-state filter on quantum hardware in the presence of noise by prepending the filter with digitized adiabatic quantum computing. The adiabatically prepared input state increases the success probability of the filter and also reduces its circuit depth requirements. At the same time, the filter enhances the accuracy of the adiabatically prepared ground state. We compare the approach to the purely adiabatic protocol through numerical simulations and experiments on the Quantinuum H1-1 quantum computer. We demonstrate a significant improvement in ground-state accuracies for paradigmatic quantum spin models.
Related papers
- Quantum quench dynamics as a shortcut to adiabaticity [31.114245664719455]
We develop and test a quantum algorithm in which the incorporation of a quench step serves as a remedy to the diverging adiabatic timescale.
Our experiments show that this approach significantly outperforms the adiabatic algorithm.
arXiv Detail & Related papers (2024-05-31T17:07:43Z) - Quantum subspace expansion in the presence of hardware noise [0.0]
Finding ground state energies on current quantum processing units (QPUs) continues to pose challenges.
Hardware noise severely affects both the expressivity and trainability of parametrized quantum circuits.
We show how to integrate VQE with a quantum subspace expansion, allowing for an optimal balance between quantum and classical computing capabilities and costs.
arXiv Detail & Related papers (2024-04-14T02:48:42Z) - 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) - Scalable noisy quantum circuits for biased-noise qubits [37.69303106863453]
We consider biased-noise qubits affected only by bit-flip errors, which is motivated by existing systems of stabilized cat qubits.
For realistic noise models, phase-flip will not be negligible, but in the Pauli-Twirling approximation, we show that our benchmark could check the correctness of circuits containing up to $106$ gates.
arXiv Detail & Related papers (2023-05-03T11:27:50Z) - Quantum process tomography of continuous-variable gates using coherent
states [49.299443295581064]
We demonstrate the use of coherent-state quantum process tomography (csQPT) for a bosonic-mode superconducting circuit.
We show results for this method by characterizing a logical quantum gate constructed using displacement and SNAP operations on an encoded qubit.
arXiv Detail & Related papers (2023-03-02T18:08:08Z) - GASP -- A Genetic Algorithm for State Preparation [0.0]
We present a genetic algorithm for state preparation (GASP) which generates relatively low-depth quantum circuits for initialising a quantum computer in a specified quantum state.
GASP can produce more efficient circuits of a given accuracy with lower depth and gate counts than other methods.
arXiv Detail & Related papers (2023-02-22T04:41:01Z) - Escaping from the Barren Plateau via Gaussian Initializations in Deep Variational Quantum Circuits [63.83649593474856]
Variational quantum circuits have been widely employed in quantum simulation and quantum machine learning in recent years.<n>However, quantum circuits with random structures have poor trainability due to the exponentially vanishing gradient with respect to the circuit depth and the qubit number.<n>This result leads to a general standpoint that deep quantum circuits would not be feasible for practical tasks.
arXiv Detail & Related papers (2022-03-17T15:06:40Z) - Quantum Gaussian filter for exploring ground-state properties [0.0]
Filter methods realize a projection from a superposed quantum state onto a target state, which can be efficient if two states have sufficient overlap.
We propose a quantum Gaussian filter (QGF) with the filter operator being a Gaussian function of the system Hamiltonian.
A hybrid quantum-classical algorithm feasible on near-term quantum computers is developed.
arXiv Detail & Related papers (2021-12-11T16:55:13Z) - QuantumNAS: Noise-Adaptive Search for Robust Quantum Circuits [26.130594925642143]
Quantum noise is the key challenge in Noisy Intermediate-Scale Quantum (NISQ) computers.
We propose and experimentally implement QuantumNAS, the first comprehensive framework for noise-adaptive co-search of variational circuit and qubit mapping.
For QML tasks, QuantumNAS is the first to demonstrate over 95% 2-class, 85% 4-class, and 32% 10-class classification accuracy on real quantum computers.
arXiv Detail & Related papers (2021-07-22T17:58:13Z) - Quantum Error Mitigation Relying on Permutation Filtering [84.66087478797475]
We propose a general framework termed as permutation filters, which includes the existing permutation-based methods as special cases.
We show that the proposed filter design algorithm always converges to the global optimum, and that the optimal filters can provide substantial improvements over the existing permutation-based methods.
arXiv Detail & Related papers (2021-07-03T16:07:30Z) - Automatically Differentiable Quantum Circuit for Many-qubit State
Preparation [1.5662820454886202]
We propose the automatically differentiable quantum circuit (ADQC) approach to efficiently prepare arbitrary quantum many-qubit states.
The circuit is optimized by updating the latent gates using back propagation to minimize the distance between the evolved and target states.
Our work sheds light on the "intelligent construction" of quantum circuits for many-qubit systems by combining with the machine learning methods.
arXiv Detail & Related papers (2021-04-30T12:22:26Z) - Direct approach to realising quantum filters for high-precision
measurements [7.454723938034161]
We find a novel approach to realising quantum filters directly from their frequency-domain transfer functions.
It opens a path towards the systematic design of optimal quantum measurement devices.
arXiv Detail & Related papers (2020-02-18T15:32:27Z)
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.