Experimental implementation of fully controlled dephasing dynamics and synthetic spectral densities

Engineering, controlling, and simulating quantum dynamics is a strenuous task. However, these techniques are crucial to develop quantum technologies, preserve quantum properties, and engineer decoherence. Earlier results have demonstrated reservoir engineering, construction of a quantum simulator for Markovian open systems, and controlled transition from Markovian to non-Markovian regime. Dephasing is an ubiquitous mechanism to degrade the performance of quantum computers. However, a fully controllable all-purpose quantum simulator for generic dephasing is still missing. Here we demonstrate full experimental control of dephasing allowing us to implement arbitrary decoherence dynamics of a qubit. As examples, we use a photon to simulate the dynamics of a qubit coupled to an Ising chain in a transverse field and also demonstrate a simulation of non-positive dynamical map. Our platform opens the possibility to simulate dephasing of any physical system and study fundamental questions on open quantum systems.Comment: V2: Added some text and new figur

Learning to Select Bi-Aspect Information for Document-Scale Text Content Manipulation

In this paper, we focus on a new practical task, document-scale text content manipulation, which is the opposite of text style transfer and aims to preserve text styles while altering the content. In detail, the input is a set of structured records and a reference text for describing another recordset. The output is a summary that accurately describes the partial content in the source recordset with the same writing style of the reference. The task is unsupervised due to lack of parallel data, and is challenging to select suitable records and style words from bi-aspect inputs respectively and generate a high-fidelity long document. To tackle those problems, we first build a dataset based on a basketball game report corpus as our testbed, and present an unsupervised neural model with interactive attention mechanism, which is used for learning the semantic relationship between records and reference texts to achieve better content transfer and better style preservation. In addition, we also explore the effectiveness of the back-translation in our task for constructing some pseudo-training pairs. Empirical results show superiority of our approaches over competitive methods, and the models also yield a new state-of-the-art result on a sentence-level dataset.Comment: accepted by AAAI202

High visibility on-chip quantum interference of single surface plasmons

Quantum photonic integrated circuits (QPICs) based on dielectric waveguides have been widely used in linear optical quantum computation. Recently, surface plasmons have been introduced to this application because they can confine and manipulate light beyond the diffraction limit. In this study, the on-chip quantum interference of two single surface plasmons was achieved using dielectric-loaded surface-plasmon-polariton waveguides. The high visibility (greater than 90%) proves the bosonic nature of single plasmons and emphasizes the feasibility of achieving basic quantum logic gates for linear optical quantum computation. The effect of intrinsic losses in plasmonic waveguides with regard to quantum information processing is also discussed. Although the influence of this effect was negligible in the current experiment, our studies reveal that such losses can dramatically reduce quantum interference visibility in certain cases; thus, quantum coherence must be carefully considered when designing QPIC devices.Comment: 6 pages, 4 figure