388 research outputs found
Parity-dependent State Engineering and Tomography in the ultrastrong coupling regime
Reaching the strong coupling regime of light-matter interaction has led to an
impressive development in fundamental quantum physics and applications to
quantum information processing. Latests advances in different quantum
technologies, like superconducting circuits or semiconductor quantum wells,
show that the ultrastrong coupling regime (USC) can also be achieved, where
novel physical phenomena and potential computational benefits have been
predicted. Nevertheless, the lack of effective decoupling mechanism in this
regime has so far hindered control and measurement processes. Here, we propose
a method based on parity symmetry conservation that allows for the generation
and reconstruction of arbitrary states in the ultrastrong coupling regime of
light-matter interactions. Our protocol requires minimal external resources by
making use of the coupling between the USC system and an ancillary two-level
quantum system.Comment: Improved version. 9 pages, 5 figure
Dynamical Casimir effect entangles artificial atoms
We show that the physics underlying the dynamical Casimir effect may generate
multipartite quantum correlations. To achieve it, we propose a circuit quantum
electrodynamics (cQED) scenario involving superconducting quantum interference
devices (SQUIDs), cavities, and superconducting qubits, also called artificial
atoms. Our results predict the generation of highly entangled states for two
and three superconducting qubits in different geometric configurations with
realistic parameters. This proposal paves the way for a scalable method of
multipartite entanglement generation in cavity networks through dynamical
Casimir physics.Comment: Improved version and references added. Accepted for publication in
Physical Review Letter
Organizational and Technological Aspects of a Platform for Collective Food Awareness
Can Internet-of-food technologies foster collective food awareness within a food consumer community? The paper contributes to answer this question in a fourfold aspect. Firstly, we model a cooperative process for generating and sharing reliable food information that is derived from food instrumental measurements performed by consumers via smart food things. Secondly, we outline the functional architecture of a platform capable to support such a process and to let a consumer community share reliable food information. Thirdly, we identify main entities and their attributes necessary to model the contextualized interaction between a consumer and the platform. Lastly, we review articles reviewing technologies capable of acquiring and quantifying food characteristics for food performances assessment. The purpose is to give an insight into current research directions on technologies employable in a platform for collective food awareness
DEEP CONVOLUTIONAL NEURAL NETWORKS FOR SENTIMENT ANALYSIS OF CULTURAL HERITAGE
Abstract. The promotion of Cultural Heritage (CH) goods has become a major challenges over the last years. CH goods promote economic development, notably through cultural and creative industries and tourism. Thus, an effective planning of archaeological, cultural, artistic and architectural sites within the territory make CH goods easily accessible. A way of adding value to these services is making them capable of providing, using new technologies, a more immersive and stimulating fruition of information. In this light, an effective contribution can be provided by sentiment analysis. The sentiment related to a monument can be used for its evaluation considering that if it is positive, it influences its public image by increasing its value. This work introduces an approach to estimate the sentiment of Social Media pictures CH related. The sentiment of a picture is identified by an especially trained Deep Convolutional Neural Network (DCNN); aftewards, we compared the performance of three DCNNs: VGG16, ResNet and InceptionResNet. It is interesting to observe how these three different architectures are able to correctly evaluate the sentiment of an image referred to a ancient monument, historical buildings, archaeological sites, museum objects, and more. Our approach has been applied to a newly collected dataset of pictures from Instagram, which shows CH goods included in the UNESCO list of World Heritage properties.</p
Endocrine health conditions in adult survivors of childhood cancer: the need for specialized adult-focused follow-up clinics
Prevalence of cardiovascular risk factors in long-term survivors of childhood cancer: 16 years follow up from a prospective registry.
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