Quantum technologies (QT) are being awaited with excitement. They are supported by many governments, the corporate sector, international bodies and technology forecasters. There is discursive investment as well in terms of creating expectations and laying down a vision for the ‘Second Quantum Revolution’. Science and technology studies are also playing their part to think of the quantum future along with philosophical discussions around it. These visions and expectations perform an implicit and latent function of steering policy proposals and governance. At the current stage of development of quantum technologies, a comprehensive and cogent legal framework is hard to envisage. As it is difficult to foresee the final shape of these technologies, a way to proceed can be to focus on the legal enquiry related to economic, political and policy factors which contribute to its material emergence. This can broaden the focus from thinking about its impact to contextualizing its production and development. Further, it allows a way of determining the extent to which social science and ethical frames can apply to the governance of QT, given the legal and practical realities of technology production and use. This article maps the myriad governance frameworks being envisaged to think about the future of QT. It zooms onto the discussion related to the access divide being framed for QT to understand the points of legal intervention. It uses the case of quantum computing to understand the way legal and practical policy solutions have been ideated. It highlights the way these solutions entrench power of digital infrastructure providers further. This seeks to motivate further work to expand the scope of a legal framework for QT.

By harnessing optical memories based on electromagnetically induced transparency in warm vapors of gaseous alkali metals and cold atomic clouds, this article presents new methods for motion sensing. The proposed scheme for velocimetry can substantially increase the sensitivity of some recent works based on the light-dragging effect in a moving medium, and on the other hand, our proposal, when realized using cold atoms, opens new research questions with regard to limits of light storage in cold atomic clouds. Ultimately, a detailed experimental setup is presented for the realization of the velocimetry scheme using stopped light, which includes considerations for the choice of the medium, laser configuration and control. By investigating the limits of optical memories in motion sensing applications, this research opens up new avenues for employing optical memories beyond applications in quantum information science.

Quantum learning models hold the potential to bring computational advantages over the classical realm. As powerful quantum servers become available on the cloud, ensuring the protection of clients’ private data becomes crucial. By incorporating quantum homomorphic encryption schemes, we present a general framework that enables quantum delegated and federated learning with a computation-theoretical data privacy guarantee. We show that learning and inference under this framework feature substantially lower communication complexity compared with schemes based on blind quantum computing. In addition, in the proposed quantum federated learning scenario, there is less computational burden on local quantum devices from the client side, since the server can operate on encrypted quantum data without extracting any information. We further prove that certain quantum speedups in supervised learning carry over to private delegated learning scenarios employing quantum kernel methods. Our results provide a valuable guide toward privacy-guaranteed quantum learning on the cloud, which may benefit future studies and security-related applications.