The Computational Power of Quantum Matter: Algorithms and Characterization

Abstract

Measurement-based quantum computation offers a route to quantum information processing that uses a predefined quantum resource state in conjunction with measurements to effectively implement quantum algorithms. The computational power of measurement-based quantum computation critically depends on the entanglement among physical qubits in the resource state. Our overall goal is to design and test high impact measurement-based quantum computation algorithms for noisy intermediate-scale quantum machines. Specifically, we propose to: i) Construct phase estimation algorithms for cluster states in the context of measurement-based quantum computation; ii) Broaden the class of known computational phases of matter for measurement-based quantum computation using ideas of symmetry-protected topological order to establish new measurement-based quantum computation algorithms; and iii) Construct and implement methods to make resource estimates for the above algorithms. Our resource estimates will allow us to determine likelihood for success on noisy intermediate-scale quantum machines. Our methods include derivations and numerical tests on both classical computers and available quantum machines. If successful, our work will set the stage for using measurements on noisy quantum states to process information.

Document Details

Document Type
DoD Grant Award
Publication Date
Jan 06, 2020
Source ID
W911NF2010013

Entities

People

  • V W Scarola

Organizations

  • Army Contracting Command
  • National Security Agency
  • Virginia Tech

Tags

Fields of Study

  • Physics

Readers

  • Neural Network Machine Learning.
  • Parallel and Distributed Computing.
  • Quantum Dot Semiconductor Device Photonics and Graphene Optoelectronic Materials and THz Physics.

Technology Areas

  • Quantum Computing