Steering a quantum system over a Schroedinger bridge

A new approach to the steering problem for quantum systems relying on Nelson's stochastic mechanics and on the theory of Schroedinger bridges is presented. The method is illustrated by working out a simple Gaussian example.Comment: Proc. Intern. Conf. on the Mathematical Theory of Networks and Systems, Perpignan, France, June 2000, CD-ROM, paper nr. 268, M. Fliess and A. El Jai Ed

A new markovian model for tennis matches

In this paper we present a generalisation of previously considered Markovian models for Tennis that overcome the assumption that the points played are i.i.d. Indeed, we postulate that in any game there are two different situations: the first 6 points and the, possible, additional points after the first deuce, with different winning probabilities. We are able to compute the winning probabilities and the expected number of points played to complete a game and a set in this more general setting. We apply our results considering scores of matches between Novak Djokovic, Roger Federer and Rafael Nadal

Hellinger vs. Kullback-Leibler multivariable spectrum approximation

In this paper, we study a matricial version of the Byrnes-Georgiou-Lindquist generalized moment problem with complexity constraint. We introduce a new metric on multivariable spectral densities induced by the family of their spectral factors which, in the scalar case, reduces to the Hellinger distance. We solve the corresponding constrained optimization problem via duality theory. A highly nontrivial existence theorem for the dual problem is established in the Byrnes-Lindquist spirit. A matricial Newton-type algorithm is finally provided for the numerical solution of the dual problem. Simulation indicates that the algorithm performs effectively and reliably.Comment: 32 pages, 1 figur

Lyapunov Control on Quantum Open System in Decoherence-free Subspaces

A scheme to drive and manipulate a finite-dimensional quantum system in the decoherence-free subspaces(DFS) by Lyapunov control is proposed. Control fields are established by Lyapunov function. This proposal can drive the open quantum system into the DFS and manipulate it to any desired eigenstate of the free Hamiltonian. An example which consists of a four-level system with three long-lived states driven by two lasers is presented to exemplify the scheme. We have performed numerical simulations for the dynamics of the four-level system, which show that the scheme works good.Comment: 5 pages, 6 figure

The Inclusion of Green Light in a Red and Blue Light Background Impact the Growth and Functional Quality of Vegetable and Flower Microgreen Species

Microgreens are edible seedlings of vegetables and flowers species which are currently considered among the five most profitable crops globally. Light-emitting diodes (LEDs) have shown great potential for plant growth, development, and synthesis of health-promoting phytochemicals with a more flexible and feasible spectral manipulation for microgreen production in indoor farms. However, research on LED lighting spectral manipulation specific to microgreen production, has shown high variability in how these edible seedlings behave regarding their light environmental conditions. Hence, developing species-specific LED light recipes for enhancement of growth and valuable functional compounds is fundamental to improve their production system. In this study, various irradiance levels and wavelengths of light spectrum produced by LEDs were investigated for their effect on growth, yield, and nutritional quality in four vegetables (chicory, green mizuna, china rose radish, and alfalfa) and two flowers (french marigold and celosia) of microgreens species. Microgreens were grown in a controlled environment using sole-source light with different photosynthetic photon flux density (110, 220, 340 mu mol m(-2) s(-1)) and two different spectra (RB: 65% red, 35% blue; RGB: 47% red, 19% green, 34% blue). At harvest, the lowest level of photosynthetically active photon flux (110 mu mol m(-2) s(-1)) reduced growth and decreased the phenolic contents in almost all species. The inclusion of green wavelengths under the highest intensity showed positive effects on phenolic accumulation. Total carotenoid content and antioxidant capacity were in general enhanced by the middle intensity, regardless of spectral combination. Thus, this study indicates that the inclusion of green light at an irradiance level of 340 mu mol m(-2) s(-1) in the RB light environment promotes the growth (dry weight biomass) and the accumulation of bioactive phytochemicals in the majority of the microgreen species tested

An estimate of attributable cases of alzheimer disease and vascular dementia due to modifiable risk factors. the impact of primary prevention in europe and in italy

Background: Up to 53.7% of all cases of dementia are assumed to be due to Alzheimer disease (AD), while 15.8% are considered to be due to vascular dementia (VaD). In Europe, about 3 million cases of AD could be due to 7 potentially modifiable risk factors: diabetes, midlife hypertension and/or obesity, physical inactivity, depression, smoking, and low educational level. Aims: To estimate the number of VaD cases in Europe and the number of AD and VaD cases in Italy attributable to these 7 potentially modifiable risk factors. Methods: Assuming the nonindependence of the 7 risk factors, the adjusted combined population attributable risk (PAR) was estimated for AD and VaD. Results: In Europe, adjusted combined PAR was 31.4% for AD and 37.8% for VaD. The total number of attributable cases was 3,033,000 for AD and 873,000 for VaD. In Italy, assuming a 20% reduction of the prevalence of each risk factor, adjusted combined PAR decreased from 45.2 to 38.9% for AD and from 53.1 to 46.6% for VaD, implying a 6.4 and 6.5% reduction in the prevalence of AD and VaD, respectively. Conclusion: A relevant reduction of AD and VaD cases in Europe and Italy could be obtained through primary prevention

Mediterranean diet adherence and synergy with acute myocardial infarction and its determinants. a multicenter case-control study in Italy.

Cardiovascular diseases are the leading causes of mortality and morbidity in Western countries. The possible synergistic effect of poor adherence to a Mediterranean diet (MD) and other risk factors for acute myocardial infarction (AMI) such as hypertension, cholesterol, ever smoker, BMI> 25, diabetes, has not been deeply studied. Design Case-control study. Methods Patients with first AMI and controls from four tertiary referral Italian centers were screened for enrolment. Dietary information was collected through a questionnaire and a MD adherence score was calculated. Physical activity and smoking habits were also registered. The Synergy Index was calculated according to Rothman. Results 127 cases and 173 controls were enrolled. The analysis was conducted using a dichotomous variable for the MD score with values 7 representing good adherence. Multivariate analysis showed the following variables associated to AMI: ever smoker (OR = 2.08), diabetes (OR = 1.42), hypertension (OR = 2.08), hypercholesterolemia (OR = 2.47), BMI> 25 (OR = 1.99), while a protective effect emerged both in subjects scoring > 7 on the MD score(OR = 0.55) and in subjects resident of Southern Italy (OR = 0.38). A synergistic effect does exist between poor adherence to the MD and the following risk factors: hypertension, hypercholesterolemia, BMI >25, diabetes and being a resident in central and northern Italy. Conclusion Synergy between heart disease risk factors and MD underlines the need to enlarge the list of known modifiable cardiovascular risk factors to include and promote adherence to Mediterranean dietary habits

VAESim: A probabilistic approach for self-supervised prototype discovery

In medical image datasets, discrete labels are often used to describe a continuous spectrum of conditions, making unsupervised image stratification a challenging task. In this work, we propose VAESim, an architecture for image stratification based on a conditional variational autoencoder. VAESim learns a set of prototypical vectors during training, each associated with a cluster in a continuous latent space. We perform a soft assignment of each data sample to the clusters and reconstruct the sample based on a similarity measure between the sample embedding and the prototypical vectors. to update the prototypical embeddings, we use an exponential moving average of the most similar representations between actual prototypes and samples in the batch size. We test our approach on the MNIST handwritten digit dataset and the pneumoniaMNIST medical benchmark dataset, where we show that our method outperforms baselines in terms of kNN accuracy (up to +15% improvement in performance) and performs at par with classification models trained in a fully supervised way. our model also outperforms current end-to-end models for unsupervised stratification