Adiabatic quantum algorithm for artificial graphene
arXiv:2204.03013 · doi:10.1103/PhysRevA.106.052408
Abstract
We devise a quantum-circuit algorithm to solve the ground state and ground energy of artificial graphene. The algorithm implements a Trotterized adiabatic evolution from a purely tight-binding Hamiltonian to one including kinetic, spin-orbit and Coulomb terms. The initial state is obtained efficiently using Gaussian-state preparation, while the readout of the ground energy is organized into seventeen sets of measurements, irrespective of the size of the problem. The total depth of the corresponding quantum circuit scales polynomially with the size of the system. A full simulation of the algorithm is performed and ground energies are obtained for lattices with up to four hexagons. Our results are benchmarked with exact diagonalization for systems with one and two hexagons. For larger systems we use the exact statevector and approximate matrix product state simulation techniques. The latter allows to systematically trade off precision with memory and therefore to tackle larger systems. We analyze adiabatic and Trotterization errors, providing estimates for optimal periods and time discretizations given a finite accuracy. In the case of large systems we also study approximation errors.
arXiv comment13 pages, 7 figures: paper with code
References in corpus (38)
- Electric Field Effect in Atomically Thin Carbon Films
- Supplementary information for "Quantum supremacy using a programmable superconducting processor"
- Polynomial-Time Algorithms for Prime Factorization and Discrete Logarithms on a Quantum Computer
- A variational eigenvalue solver on a quantum processor
- The density-matrix renormalization group in the age of matrix product states
- Hardware-efficient Variational Quantum Eigensolver for Small Molecules and Quantum Magnets
- Quantum Simulation
- Supervised learning with quantum enhanced feature spaces
- Quantum computational advantage using photons
- A Quantum Adiabatic Evolution Algorithm Applied to Random Instances of an NP-Complete Problem
- Quantum support vector machine for big data classification
- Quantum computational chemistry
- Adiabatic Quantum Computing
- Simulated Quantum Computation of Molecular Energies
- Quantum Amplitude Amplification and Estimation
- Circuit-centric quantum classifiers
- Scalable Quantum Simulation of Molecular Energies
- Power of data in quantum machine learning
- Quantum optimization using variational algorithms on near-term quantum devices
- Data re-uploading for a universal quantum classifier
- Toward the first quantum simulation with quantum speedup
- A rigorous and robust quantum speed-up in supervised machine learning
- Quantum advantage in learning from experiments
- A Theory of Trotter Error
- Simulation of Electronic Structure Hamiltonians Using Quantum Computers
- Quantum chemistry calculations on a trapped-ion quantum simulator
- Superconductivity in rhombohedral trilayer graphene
- Quantum Simulation of Electronic Structure with Linear Depth and Connectivity
- Generalized Hartree-Fock Theory and the Hubbard Model
- Adiabatic Theorem without a Gap Condition
- Engineering artificial graphene in a two-dimensional electron gas
- Strategies for solving the Fermi-Hubbard model on near-term quantum computers
- Realizable Hamiltonians for Universal Adiabatic Quantum Computers
- Solving the Optimal Trading Trajectory Problem Using a Quantum Annealer
- Quantum algorithms to simulate many-body physics of correlated fermions
- Qibo: a framework for quantum simulation with hardware acceleration
- The performance of the quantum adiabatic algorithm on random instances of two optimization problems on regular hypergraphs
- Adiabatic Quantum Computing for Random Satisfiability Problems
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