780 research outputs found
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
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