Stimulating and facilitating the development of quantum information science and technology.
Quantum 2.0 refers to the development and use of many-particle quantum superposition and entanglement in large engineered systems to advance science and technology. Examples of such large quantum systems are quantum computers and simulators, quantum communication networks, and arrays of quantum sensors. New resulting technologies will go far beyond the (quantum 1.0) capabilities offered by single systems.
This conference—the second in the series— will bring together academics, engineers, national laboratory and industry scientists and others working to advance quantum science and technology. Our goal is to promote the development of mature quantum technologies that will allow us to build Quantum 2.0 systems capable of quantum advantage. Participants will have the opportunity to interact and discover common ground, and potentially build collaborations leading to new concepts or development opportunities. It also aims to look forward to new scientific frontiers beyond the scope of current technologies.
The Quantum 2.0 2022 conference is open to scientists and engineers interested in developing and using quantum systems, to scientists exploring new fundamental concepts in quantum information science, and to computer/information scientists interested in processing and controlling information on quantum devices. The meeting is expected to be of particular interest to those who employ optical concepts and techniques, broadly interpreted, to implement and use the technology. These technologies include, but are not limited to:
Scalable quantum computers, simulators, or entanglement-based communications networks; quantum-enhanced sensors including accelerometers, gravimeters, magnetometers, interferometers, microscopes, telescopes, rangers, spectrometers, clocks, quantum lights sources and detectors; sensor networks; distributed or remote quantum processors; quantum-enabled information processors and quantum algorithmic design. Both fundamental and applied studies, including theoretical or algorithmic, of the above are appropriate.