Measurement-based quantum computing on a fibre-optical platform
Jonas Neergaard-Nielsen
DTU Physics Faculty+ meeting 2021-05-27
We generated a "substrate" for optical quantum computing
...and implemented quantum gates and a small circuit.
But we don't have a quantum computer... yet.
Quantum computing
- is a different model of computing than classical computers (Turing machines)
- relies on quantum superposition (\(\alpha|0\rangle+\beta|1\rangle\)) and interference
- may solve problems that are impossible on classical supercomputers
- is a rapidly growing industry — major players like Google, IBM, Amazon, Microsoft, Alibaba, ..., plus tons of startups
- is technologically very diverse:
superconductors, semiconductors, trapped ions, photonics, and more
Google Sycamore with 54 qubits
- demonstrated quantum supremacy in 2019
- but scaling up is hard!
Our approach to scalability:
Expand temporally — reuse few physical resources over and over
Standard GATE MODEL of quantum computation
Measurement-based quantum computing (MBQC)
Gate based model
Coherent, high-fidelity qubit interactions
MBQC
Creation of massively entangled state
- the computational substrate
Photonics is ideally suited for this!
Continuous variable quantum information
Standard optical qubits:
a single photon in one of two modes
Continuous-variable states occupy the full Hilbert space, not just the two lowest states
Continuous variable cluster state
Generating qubit clusters:
Generating CV clusters:
Easier approach:
- requires just squeezed states and linear optics
Our tools
squeezers
optical fibres
homodyne detectors
Cluster state generation procedure
Cluster state verification
M. V. Larsen, X. Guo, C. Breum, J. S. Neergaard-Nielsen, U. L. Andersen
Science 366, 369 (2019)
Summer 2019:
disassemble, B309 → B307, reassemble
Implementing gates on the cluster
Implementing gates on the cluster
M. V. Larsen, X. Guo, C. Breum, J. S. Neergaard-Nielsen, U. L. Andersen
accepted in Nature Physics
Main credits: Mikkel Vilsbøll Larsen - now on his way to Canada
