How can you be two places at once when you're not anywhere at all?

Yang Yang, Xianghan Zheng, Victor I. C. Chang +1 more

Summary With the advent of cloud computing, more and more consumers prefer to use the cloud services with the pay‐as‐you‐consume mode. The cloud storage brings about great convenience to users, who store data in cloud and access to it using the smart devices anytime and anywhere. Consumers' information should be encrypted to guarantee the data privacy. Flexible searching on ciphertext is a critical challenge to be solved for effective data utilization. In this paper, we propose a novel semantic keyword searchable proxy re‐encryption scheme for secure cloud storage. A highlight of this work is that the scheme is quantum attack resistant, while most of the available searchable encryption schemes are not. It supports not only exact keyword search but also synonym keyword search. Moreover, the data owner is capable to delegate his search right to another user using the proxy re‐encryption mechanism. In the generation process of re‐encryption key, the delegator and delegatee do not need to be interactive with each other. The scheme is also collusion resistant. Under the learning with errors hardness problem, this scheme is proved secure in standard model.

Adrian Danks

Gesine Grosche

Single-mode optical fiber is a highly efficient connecting medium used not only for optical telecommunications but also for the dissemination of ultrastable frequencies or timing signals. Ma et al. [Opt. Lett.19, 1777 (1994)] described a measurement and control system to deliver the same optical frequency at two places, namely the two ends of a fiber, by eliminating the "fiber-induced phase-noise modulation, which corrupts high-precision frequency-based applications." I present a simple detection and control scheme to deliver the same optical frequency at many places anywhere along a transmission path, or in its vicinity, with a relative instability of 1 part in 10(19). The same idea applies to radio frequency and timing signals. This considerably simplifies future efforts to make precise timing or frequency signals available to many users, as required in some large-scale science experiments.

Chih-Chieh Chen, Masaru Sogabe, Kodai Shiba +2 more

Abstract Quantifying the model complexity of quantum circuits provides a guide to avoid overfitting in quantum machine learning. Previously we established a Vapnik–Chervonenkis (VC) dimension upper bound for ‘encoding-first’ quantum circuits, where the input layer is the first layer of the circuit. In this work, we prove a general VC dimension upper bound for quantum circuit learning including ‘data re-uploading’ circuits, where the input gates can be single qubit rotations anywhere in the circuit. A linear lower bound is also constructed. The properties of the bounds and approximation-estimation trade-off considerations are discussed.

Hannah Whitehurst