Quantum Information Protocols with limited resources

• Applicant: Professor Dr. Juan Ignacio Cirac
• Subject Area: Optics, Quantum Optics and Physics of Atoms, Molecules and Plasmas
• Term: from 2019 to 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 414325145

After many years of intensive research, it is now possible to control and manipulate tens of qubits with high precision. This has been achieved with trapped ions, cold atoms, superconductors, and photons, and it is very likely that other technologies will soon catch up. Even though a full-fledged quantum computer is still out of reach in the near term, it is expected that in the next few years quantum processors composed of up to hundred qubits will be available, and that one will be able to reliably perform more than a thousand quantum gates without having to resort to error correction schemes. Under these conditions, can we take advantage of those small systems? And, what can we learn?The long-term goals and visions of this project are to: (i) develop applications and protocols which can be carried out with small quantum processors, and that outperform existing and planned classical devices; (ii) revisit classical algorithms and methods inspired by quantum information processing to apply them to quantum devices and many-body systems; (iii) bridge the gap between abstract results and specific experimental setups.For the goals outlined above, the first four years will be dedicated to• Developing quantum algorithms for 50-100 qubits and 1000-10000 quantum gates: The algorithms will have applications in optimization problems, the analysis of quantum many-body states as they appear in atomic and condensed matter physics, as well as in quantum-enhanced machine learning.• The application of classical machine learning for quantum systems: This will combine the tensor network approach with string bond states, and aim at the characterization of many-body systems relevant for experiments and the certification of quantum many-body properties assisted by machine learning.• The investigation of how to implement those and other ideas with different technologies: This will include trapped ions, cold neutral atoms, photons, superconducting qubits, as well as novel scenarios.In the long run, as experiments take over, we will investigate protocols that include more qubits, more sophisticated communication channels and also hybrid quantum/classical algorithms and protocols.

• DFG Programme: Research Grants
• International Connection: Austria
• Cooperation Partner: Professor Dr. Philip Walther