Adaptive Variational Quantum Dynamics Simulations

By Yongxin Yao, N. Gomes, Feng Zhang, Caizhuang Wang, K. Ho, Thomas Iadecola, P. Orth. PRX Quantum, 2020

133 citations recorded by the source corpus.

We propose a general-purpose, self-adaptive approach to construct variational wavefunction ans\"atze for highly accurate quantum dynamics simulations. The McLachlan variational principle for real-time dynamics governs the equations of motion of variational parameters, where the variational ansatz is automatically generated and dynamically expanded along the time-evolution path, such that the "McLachlan distance", which is a measure of the simulation accuracy, remains below a fixed threshold. The adaptive variational quantum dynamics simulation (AVQDS) approach is applied to the Lieb-Schultz-Mattis spin chain model, where it captures the finite-rate quantum quench dynamics to high accuracy. The AVQDS circuits that prepare the quantum states along the dynamical path are shallower than those obtained from naive Trotterization by over an order of magnitude. We envision that a wide range of dynamical simulations of quantum many-body systems on near-term quantum devices will be made possible through the AVQDS framework.

Subfields: Artificial Intelligence, Atomic and Molecular Physics, and Optics, Physical and Theoretical Chemistry

View Paper: https://www.semanticscholar.org/paper/5fee716dd68a9073aa02dddea4d316de841548e7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Patrick J. Coles
2. M. Cerezo
3. Lukasz Cincio
4. Suguru Endo
5. Piotr Czarnik
6. Andrew Arrasmith
7. Jarrod R. McClean
8. Simon C. Benjamin

In Atomic and Molecular Physics, and Optics

1. Patrick J. Coles
2. M. Cerezo
3. Suguru Endo
4. Lukasz Cincio
5. Simon C. Benjamin
6. Jarrod R. McClean
7. Xiao Yuan
8. Ryan Babbush

In Physical and Theoretical Chemistry

1. Xiao Yuan
2. Simon C. Benjamin
3. Jarrod R. McClean
4. Ryan Babbush
5. Suguru Endo

Citations in the corpus

• Diagnosing Barren Plateaus with Tools from Quantum Optimal Control (2021, methodology): “[15] Yong-Xin Yao, Niladri Gomes, Feng Zhang, Cai-Zhuang Wang, Kai-Ming Ho, Thomas Iadecola, and Peter P Orth.”
• Variational quantum algorithms (2020, methodology): “Recent works also extend the algorithms to use adaptive ansatz to reduce the circuit depth [99, 100]”