Self-Consistent Determination of Single-Impurity Anderson Model Using Hybrid Quantum-Classical Approach on a Spin Quantum Simulator
- URL: http://arxiv.org/abs/2410.07808v1
- Date: Thu, 10 Oct 2024 10:49:40 GMT
- Title: Self-Consistent Determination of Single-Impurity Anderson Model Using Hybrid Quantum-Classical Approach on a Spin Quantum Simulator
- Authors: Xinfang Nie, Xuanran Zhu, Yu-ang Fan, Xinyue Long, Hongfeng Liu, Keyi Huang, Cheng Xi, Liangyu Che, Yuxuan Zheng, Yufang Feng, Xiaodong Yang, Dawei Lu,
- Abstract summary: In this paper, we experimentally demonstrate a hybrid quantum-classical approach to correlated materials.
We address the most computationally demanding aspect of the calculation, namely the computation of the Green's function.
As the number of qubits with high control fidelity continues to grow, our experimental findings pave the way for solving even more complex models.
- Score: 3.5919681412083038
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: The accurate determination of the electronic structure of strongly correlated materials using first principle methods is of paramount importance in condensed matter physics, computational chemistry, and material science. However, due to the exponential scaling of computational resources, incorporating such materials into classical computation frameworks becomes prohibitively expensive. In 2016, Bauer et al. proposed a hybrid quantum-classical approach to correlated materials Phys. Rev. X 6, 031045 (2016)}] that can efficiently tackle the electronic structure of complex correlated materials. Here, we experimentally demonstrate that approach to tackle the computational challenges associated with strongly correlated materials. By seamlessly integrating quantum computation into classical computers, we address the most computationally demanding aspect of the calculation, namely the computation of the Green's function, using a spin quantum processor. Furthermore, we realize a self-consistent determination of the single impurity Anderson model through a feedback loop between quantum and classical computations. A quantum phase transition in the Hubbard model from the metallic phase to the Mott insulator is observed as the strength of electron correlation increases. As the number of qubits with high control fidelity continues to grow, our experimental findings pave the way for solving even more complex models, such as strongly correlated crystalline materials or intricate molecules.
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) - Modeling Non-Covalent Interatomic Interactions on a Photonic Quantum
Computer [50.24983453990065]
We show that the cQDO model lends itself naturally to simulation on a photonic quantum computer.
We calculate the binding energy curve of diatomic systems by leveraging Xanadu's Strawberry Fields photonics library.
Remarkably, we find that two coupled bosonic QDOs exhibit a stable bond.
arXiv Detail & Related papers (2023-06-14T14:44:12Z) - Photonic Quantum Computing For Polymer Classification [62.997667081978825]
Two polymer classes visual (VIS) and near-infrared (NIR) are defined based on the size of the polymer gaps.
We present a hybrid classical-quantum approach to the binary classification of polymer structures.
arXiv Detail & Related papers (2022-11-22T11:59:52Z) - Say NO to Optimization: A Non-Orthogonal Quantum Eigensolver [0.0]
A balanced description of both static and dynamic correlations in electronic systems with nearly degenerate low-lying states presents a challenge for multi-configurational methods on classical computers.
We present here a quantum algorithm utilizing the action of correlating cluster operators to provide high-quality wavefunction ans"atze.
arXiv Detail & Related papers (2022-05-18T16:20:36Z) - Simulating challenging correlated molecules and materials on the
Sycamore quantum processor [0.0]
Simulating complex molecules and materials is an anticipated application of quantum devices.
We simulate static and dynamical electronic structure on a superconducting quantum processor.
Our work serves to convert artificial measures of quantum advantage into a physically relevant setting.
arXiv Detail & Related papers (2022-03-29T07:11:40Z) - Estimating Phosphorescent Emission Energies in Ir(III) Complexes using
Large-Scale Quantum Computing Simulations [0.0]
We apply the iterative qubit coupled cluster (iQCC) method on classical hardware to the calculation of the transition energies in nine phosphorescent iridium complexes.
Our simulations would require a gate-based quantum computer with a minimum of 72 fully-connected and error-corrected logical qubits.
The iQCC quantum method is found to match the accuracy of the fine-tuned DFT functionals, has a better Pearson correlation coefficient, and still has considerable potential for systematic improvement.
arXiv Detail & Related papers (2021-11-07T20:02:10Z) - Quantum-Classical Hybrid Algorithm for the Simulation of All-Electron
Correlation [58.720142291102135]
We present a novel hybrid-classical algorithm that computes a molecule's all-electron energy and properties on the classical computer.
We demonstrate the ability of the quantum-classical hybrid algorithms to achieve chemically relevant results and accuracy on currently available quantum computers.
arXiv Detail & Related papers (2021-06-22T18:00:00Z) - Assessing the Precision of Quantum Simulation of Many-Body Effects in
Atomic Systems using the Variational Quantum Eigensolver Algorithm [0.0]
This study investigates the physical effects beyond the mean-field approximation, known as electron correlation, in the ground state energies of atomic systems.
We use the classical-quantum hybrid variational quantum eigensolver (VQE) algorithm.
When more qubits become available, our study will serve as among the first steps taken towards computing other properties of interest to various applications.
arXiv Detail & Related papers (2021-01-14T11:26:32Z) - Benchmarking adaptive variational quantum eigensolvers [63.277656713454284]
We benchmark the accuracy of VQE and ADAPT-VQE to calculate the electronic ground states and potential energy curves.
We find both methods provide good estimates of the energy and ground state.
gradient-based optimization is more economical and delivers superior performance than analogous simulations carried out with gradient-frees.
arXiv Detail & Related papers (2020-11-02T19:52:04Z) - Graph Neural Network for Hamiltonian-Based Material Property Prediction [56.94118357003096]
We present and compare several different graph convolution networks that are able to predict the band gap for inorganic materials.
The models are developed to incorporate two different features: the information of each orbital itself and the interaction between each other.
The results show that our model can get a promising prediction accuracy with cross-validation.
arXiv Detail & Related papers (2020-05-27T13:32:10Z)
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.