Dynamical Casimir Effect in Quantum Information Processing

We demonstrate, in the regime of ultrastrong matter-field coupling, the strong connection between the dynamical Casimir effect (DCE) and the performance of quantum information protocols. Our results are illustrated by means of a realistic quantum communication channel and show that the DCE is a fundamental limit for quantum computation and communication and that novel schemes are required to implement ultrafast and reliable quantum gates. Strategies to partially counteract the DCE are also discussed.Comment: 7 pages, 5 figure

DESIGN OF A LAMBDA CONFIGURATION IN ARTIFICIAL COHERENT NANOSTRUCTURES

The implementation of a three-level Lambda System in artificial atoms would allow to perform advanced control tasks typical of quantum optics in the solid state realm, with photons in the mu m/mm range. However hardware constraints put an obstacle since protection from decoherence is often conflicting with efficient coupling to external fields. We address the problem of performing conventional STImulated Raman Adiabatic Passage (STIRAP) in the presence of low-frequency noise. We propose two strategies to defeat decoherence, based on "optimal symmetry breaking" and dynamical decoupling. We suggest how to apply to the different implementations of superconducting artificial atoms, stressing the key role of non-Markovianity

A METABOLIC-LIKE CYCLE FOR SYNTHETIC APPLICATIONS

Systems Biocatalysis is a new approach consisting of organizing enzymes in vitro to generate an artificial metabolism for synthetic purposes. The interconversion of functional groups is the main objective of biocatalysis, and systems organizing a series of enzymes to achieve a multi-step reaction have been reported. The assembly of essentially the same enzymes utilized in Nature to drive the transformation of carbohydrates towards useful synthetic intermediates [1] has been referred to as an artificial metabolism. SysBiocat aims at a similar goal addressing the generalization and organization of group of enzymes (a tool-box) able to perform a series of reactions of general synthetic utility where the feasibility is connected with the obtainment of enzymes of wide substrate specificity or in a rich array of variable common catalytic functions. [2] As a demonstration of this concept, we have recently assembled a biochemical like cycle (Asp-cycle) connecting among them an unsaturated carboxylate (fumaric acid), an alpha-amino acid (L-aspartic acid), a keto acid (oxalacetic acid) and the corresponding alpha-hydroxyacid (D- or L-malic acid). [3] In this view, the obtained cycle may be exploited by coupling it with synthetically relevant reactions which are driven to completion thanks to one or more irreversible steps in the reaction sequence. ____ [1] W.D. Fessner, C. Walter, “Artificial metabolism”, Angew Chem Int Ed, 1992, 31, p. 614 [2] U. T. Bornscheuer, G. W. Huisman, R. J. Kazlauskas, S. Lutz, J. C. Moore, K. Robins, “Engineering The Third Wave Of Biocatalysis”, Nature, 2012, 485, p. 185 [3] D. Tessaro, L. Pollegioni, L. Piubelli, P. D’Arrigo, S. Servi, “Systems Biocatalysis: An Artificial Metabolism for Interconversion of Functional Groups”, ACS Catalysis, 2015, 5, p. 160

Multimodal Motion Conditioned Diffusion Model for Skeleton-based Video Anomaly Detection

Anomalies are rare and anomaly detection is often therefore framed as One-Class Classification (OCC), i.e. trained solely on normalcy. Leading OCC techniques constrain the latent representations of normal motions to limited volumes and detect as abnormal anything outside, which accounts satisfactorily for the openset'ness of anomalies. But normalcy shares the same openset'ness property, since humans can perform the same action in several ways, which the leading techniques neglect. We propose a novel generative model for video anomaly detection (VAD), which assumes that both normality and abnormality are multimodal. We consider skeletal representations and leverage state-of-the-art diffusion probabilistic models to generate multimodal future human poses. We contribute a novel conditioning on the past motion of people, and exploit the improved mode coverage capabilities of diffusion processes to generate different-but-plausible future motions. Upon the statistical aggregation of future modes, anomaly is detected when the generated set of motions is not pertinent to the actual future. We validate our model on 4 established benchmarks: UBnormal, HR-UBnormal, HR-STC, and HR-Avenue, with extensive experiments surpassing state-of-the-art results.Comment: Accepted at ICCV202

Clinical, Cognitive and Behavioural Assessment in Children with Cerebellar Disorder

Cerebellar disorders are characterised clinically by specific signs and symptoms, often associated with neurodevelopmental disorder. While the clinical signs of cerebellar disorders are clearly recognisable in adults and have a precise anatomo-functional correlation, in children the semiotics are less clear and vary with age because of the particular nature of the cerebellum's maturation. Unlike other structures of the central nervous system, this begins at a later stage of foetal development and extends over a longer period of time, even after birth. As a result, the typical signs of cerebellar dysfunction will only become evident when the cerebellar functions have become integrated into the complex circuits of the central nervous system. This means that poor motor coordination in the very early years of life may not necessarily correlate with cerebellar dysfunction, and this may also be encountered in healthy children. The cerebellum's role in cognitive and emotional functions relies on its structure and the complexity of its connections. Cognitive and behavioral impairment in cerebellar disorders can be the results of acquired lesions or the action of genetic and environmental risk factors, to which the cerebellum is particularly vulnerable considering its pattern of development. In the pathological setting, early evidence of cerebellar damage may be very vague, due, partly, to spontaneous compensation phenomena and the vicarious role of the connecting structures (an expression of the brain's plasticity). Careful clinical assessment will nonetheless enable appropriate instrumental procedures to be arranged. It is common knowledge that the contribution of neuroimaging is crucial for diagnosis of cerebellar conditions, and neurophysiological investigations can also have a significant role. The ultimate goal of clinicians is to combine clinical data and instrumental findings to formulate a precise diagnostic hypothesis, and thus request a specific genetic test in order to confirm their findings, wherever possible

Contracting Skeletal Kinematic Embeddings for Anomaly Detection

Detecting the anomaly of human behavior is paramount to timely recognizing endangering situations, such as street fights or elderly falls. However, anomaly detection is complex, since anomalous events are rare and because it is an open set recognition task, i.e., what is anomalous at inference has not been observed at training. We propose COSKAD, a novel model which encodes skeletal human motion by an efficient graph convolutional network and learns to COntract SKeletal kinematic embeddings onto a latent hypersphere of minimum volume for Anomaly Detection. We propose and analyze three latent space designs for COSKAD: the commonly-adopted Euclidean, and the new spherical-radial and hyperbolic volumes. All three variants outperform the state-of-the-art, including video-based techniques, on the ShangaiTechCampus, the Avenue, and on the most recent UBnormal dataset, for which we contribute novel skeleton annotations and the selection of human-related videos. The source code and dataset will be released upon acceptance.Comment: Submitted to Patter Recognition Journa

A Case of Intra and Extra-vascular Lipoma of the Subclavian Vein

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Repetition Versus Noiseless Quantum Codes For Correlated Errors

We study the performance of simple quantum error correcting codes with respect to correlated noise errors characterized by a finite correlation strength. Specifically, we consider bit flip (phase flip) noisy quantum memory channels and use repetition and noiseless quantum codes. We characterize the performance of the codes by means of the entanglement fidelity as function of the error probability and degree of memory. Finally, comparing the entanglement fidelities of repetition and noiseless quantum codes, we find a threshold for the correlation strength that allows to select the code with better performance.Comment: few changes, 14 page