Real-time hybrid quantum-classical computations for trapped ions with Python control-flow
- authored by
- Tobias Schmale, Bence Temesi, Niko Trittschanke, Nicolas Pulido-Mateo, Ilya Elenskiy, Ludwig Krinner, Timko Dubielzig, Christian Ospelkaus, Hendrik Weimer, Daniel Borcherding
- Abstract
In recent years, the number of hybrid algorithms that combine quantum and classical computations has been continuously increasing. These two approaches to computing can mutually enhance each others' performances thus bringing the promise of more advanced algorithms that can outmatch their pure counterparts. In order to accommodate this new class of codes, a proper environment has to be created, which enables the interplay between the quantum and classical hardware.For many of these hybrid processes the coherence time of the quantum computer arises as a natural time constraint, making it crucial to minimize the classical overhead. For ion-trap quantum computers however, this is a much less limiting factor than with superconducting technologies, since the relevant timescale is on the order of seconds instead of microseconds. In fact, we show that the operating time-scales of trapped-ion quantum computers are compatible with the execution speed of the Python programming language, enabling us to develop an interpreted scheme for real-time control of quantum computations. In particular, compilation of all instructions in advance is not necessary, unlike with superconducting qubits. This keeps the implementation of hybrid algorithms simple and also lets users benefit from the rich environment of existing Python libraries.In order to show that this approach of interpreted quantum-classical computations (IQCC) is feasible, we bring real-world examples and evaluate them in realistic benchmarks.
- Organisation(s)
-
Institute of Theoretical Physics
Institute of Quantum Optics
QuantumFrontiers
- External Organisation(s)
-
Physikalisch-Technische Bundesanstalt PTB
Technische Universität Braunschweig
- Type
- Conference contribution
- Pages
- 193-199
- No. of pages
- 7
- Publication date
- 2023
- Publication status
- Published
- Peer reviewed
- Yes
- ASJC Scopus subject areas
- Hardware and Architecture, Software, Statistical and Nonlinear Physics
- Electronic version(s)
-
https://doi.org/10.48550/arXiv.2303.01282 (Access:
Open)
https://doi.org/10.1109/QSW59989.2023.00031 (Access: Closed)