1.1k citations
- University of Maryland, College ParkUS40 papers
- Duke UniversityUS34 papers
- Joint Quantum InstituteUS33 papers
- Joint Center for Quantum Information and Computer ScienceUS28 papers
- National Institute of Standards and TechnologyUS9 papers
- Harvard UniversityUS8 papers
- California Institute of TechnologyUS6 papers
- University of California, BerkeleyUS6 papers
- U.S. National Science FoundationUS6 papers
- Massachusetts Institute of TechnologyUS5 papers
- The Ohio State UniversityUS5 papers
- Colorado School of MinesUS4 papers
9 papers · 2 filters
Training of Quantum Circuits on a Hybrid Quantum Computer
D. Zhu, N. M. Linke, M. Benedetti +10
Generative modeling is a flavor of machine learning with applications ranging from computer vision to chemical design. It is expected to be one of the techniques most suited to tak…
Parallel Entangling Operations on a Universal Ion Trap Quantum Computer
C. Figgatt, A. Ostrander, N. M. Linke +4
The circuit model of a quantum computer consists of sequences of gate operations between quantum bits (qubits), drawn from a universal family of discrete operations. The ability to…
Verified Quantum Information Scrambling
Kevin A. Landsman, Caroline Figgatt, Thomas Schuster +4
Quantum scrambling is the dispersal of local information into many-body quantum entanglements and correlations distributed throughout the entire system. This concept underlies the…
Low cost quantum circuits for classically intractable instances of the Hamiltonian dynamics simulation problem
Yunseong Nam, Dmitri Maslov
We develop circuit implementations for digital-level quantum Hamiltonian dynamics simulation algorithms suitable for implementation on a reconfigurable quantum computer, such as tr…
Machine learning assisted readout of trapped-ion qubits
Alireza Seif, Kevin A. Landsman, Norbert M. Linke +3
We reduce measurement errors in a quantum computer using machine learning techniques. We exploit a simple yet versatile neural network to classify multi-qubit quantum states, which…
Approximate Quantum Fourier Transform with T gates
Yunseong Nam, Yuan Su, Dmitri Maslov
The ability to implement the Quantum Fourier Transform (QFT) efficiently on a quantum computer facilitates the advantages offered by a variety of fundamental quantum algorithms, su…