Quantum State Preparation on a Superconducting Qubit Lattice
ORAL
Abstract
Efficient quantum state preparation is integral to both encoding quantum information and simulating quantum systems. As quantum systems scale up, preparation of a desired quantum state within the coherence-time limit of the comprising qubits becomes increasingly difficult to achieve. We have developed a 21-qubit superconducting quantum processor consisting of a 3x3 array of 9 lattice qubits (qubits containing readable quantum information) and 12 coupler qubits (qubits that mediate interactions between lattice sites). Our platform uses asymmetric tunable transmon qubits, which natively emulate a Bose-Hubbard Hamiltonian, as well as precision temporal control to allow customization of the lattice Hamiltonian. Additionally, this platform allows for precise control of single and two-qubit gates, expanding our capabilities to include implementation near term quantum algorithms on the lattice. Although the primary application of near-term algorithms such as VQE, ASP, QAOA has been towards optimization problems, these same techniques can be used to prepare the ground state of a designed or induced Hamiltonian [1]. In this talk, we will discuss applications of near-term quantum algorithms to preparing interesting condensed matter states on a superconducting quantum processor.
References:
[1] Vladimir Kremenetski et al. “Quantum Alternating Operator Ansatz (QAOA) Phase Diagrams and Applications for Quantum Chemistry”. In: (2021)
References:
[1] Vladimir Kremenetski et al. “Quantum Alternating Operator Ansatz (QAOA) Phase Diagrams and Applications for Quantum Chemistry”. In: (2021)
*S.M. is supported by a NASA Space Technology Research Fellowship. This material is based upon work supported in part by the U.S. Department of Energy, Office of Science, National Quantum Information Science Research Centers, Quantum Systems Accelerator; in part by the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA); and by the U.S. Department of Energy under Air Force Contract No. FA8702-15-D-0001. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the ODNI, IARPA, USAF, or DOE.
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Presenters
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Sarah E Muschinske
- Massachusetts Institute of Technology MIT