Digital-analog quantum computing of fermion-boson models in superconducting circuits
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arXiv
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| Autores principales: | , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2023
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| _version_ | 1866915206768099328 |
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| author | Kumar, Shubham Hegade, Narendra N. Visuri, Anne-Maria Bhargava, B. A. Hernandez, Juan F. R. Solano, Enrique Albarrán-Arriagada, Francisco Barrios, Gabriel Alvarado |
| author_facet | Kumar, Shubham Hegade, Narendra N. Visuri, Anne-Maria Bhargava, B. A. Hernandez, Juan F. R. Solano, Enrique Albarrán-Arriagada, Francisco Barrios, Gabriel Alvarado |
| contents | High-fidelity quantum simulations demand hardware-software co-design architectures, which are crucial for adapting to complex problems such as strongly correlated dynamics in condensed matter. By leveraging co-design strategies, we can enhance the performance of state-of-the-art quantum devices in the noisy intermediate quantum (NISQ) and early error-correction regimes. In this direction, we propose a digital-analog quantum algorithm for simulating the Hubbard-Holstein model, describing strongly-correlated fermion-boson interactions, in a suitable architecture with superconducting circuits. It comprises a linear chain of qubits connected by resonators, emulating electron-electron (e-e) and electron-phonon (e-p) interactions, as well as fermion tunneling. Our approach is adequate for digital-analog quantum computing (DAQC) of fermion-boson models, including those described by the Hubbard-Holstein model. We show the reduction in the circuit depth of the DAQC algorithm, a sequence of digital steps and analog blocks, outperforming the purely digital approach. We exemplify the quantum simulation of a half-filled two-site Hubbard-Holstein model. In this example, we obtain time-dependent state fidelities larger than 0.98, showing that our proposal is suitable for studying the dynamical behavior of solid-state systems. Our proposal opens the door to computing complex systems for chemistry, materials, and high-energy physics. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2308_12040 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Digital-analog quantum computing of fermion-boson models in superconducting circuits Kumar, Shubham Hegade, Narendra N. Visuri, Anne-Maria Bhargava, B. A. Hernandez, Juan F. R. Solano, Enrique Albarrán-Arriagada, Francisco Barrios, Gabriel Alvarado Quantum Physics Superconductivity High-fidelity quantum simulations demand hardware-software co-design architectures, which are crucial for adapting to complex problems such as strongly correlated dynamics in condensed matter. By leveraging co-design strategies, we can enhance the performance of state-of-the-art quantum devices in the noisy intermediate quantum (NISQ) and early error-correction regimes. In this direction, we propose a digital-analog quantum algorithm for simulating the Hubbard-Holstein model, describing strongly-correlated fermion-boson interactions, in a suitable architecture with superconducting circuits. It comprises a linear chain of qubits connected by resonators, emulating electron-electron (e-e) and electron-phonon (e-p) interactions, as well as fermion tunneling. Our approach is adequate for digital-analog quantum computing (DAQC) of fermion-boson models, including those described by the Hubbard-Holstein model. We show the reduction in the circuit depth of the DAQC algorithm, a sequence of digital steps and analog blocks, outperforming the purely digital approach. We exemplify the quantum simulation of a half-filled two-site Hubbard-Holstein model. In this example, we obtain time-dependent state fidelities larger than 0.98, showing that our proposal is suitable for studying the dynamical behavior of solid-state systems. Our proposal opens the door to computing complex systems for chemistry, materials, and high-energy physics. |
| title | Digital-analog quantum computing of fermion-boson models in superconducting circuits |
| topic | Quantum Physics Superconductivity |
| url | https://arxiv.org/abs/2308.12040 |