Experimental investigations of the dipolar interactions between single Rydberg atoms

This review summarizes experimental works performed over the last decade by several groups on the manipulation of a few individual interacting Rydberg atoms. These studies establish arrays of single Rydberg atoms as a promising platform for quantum state engineering, with potential applications to quantum metrology, quantum simulation and quantum information

Measurement of the Angular Dependence of the Dipole-Dipole Interaction Between Two Individual Rydberg Atoms at a F\"orster Resonance

We measure the angular dependence of the resonant dipole-dipole interaction between two individual Rydberg atoms with controlled relative positions. By applying a combination of static electric and magnetic fields on the atoms, we demonstrate the possibility to isolate a single interaction channel at a F\"orster resonance, that shows a well-defined angular dependence. We first identify spectroscopically the F\"orster resonance of choice and we then perform a direct measurement of the interaction strength between the two atoms as a function of the angle between the internuclear axis and the quantization axis. Our results show good agreement with the expected angular dependence $\propto(1-3\cos^2\theta)$, and represent an important step towards quantum state engineering in two-dimensional arrays of individual Rydberg atoms.Comment: 5 pages, 4 figure

Local optical control of the resonant dipole-dipole interaction between Rydberg atoms

We report on the local control of the transition frequency of a spin-$1/2$ encoded in two Rydberg levels of an individual atom by applying a state-selective light shift using an addressing beam. With this tool, we first study the spectrum of an elementary system of two spins, tuning it from a non-resonant to a resonant regime, where "bright" (superradiant) and "dark" (subradiant) states emerge. We observe the collective enhancement of the microwave coupling to the bright state. We then show that after preparing an initial single spin excitation and letting it hop due to the spin-exchange interaction, we can freeze the dynamics at will with the addressing laser, while preserving the coherence of the system. In the context of quantum simulation, this scheme opens exciting prospects for engineering inhomogeneous XY spin Hamiltonians or preparing spin-imbalanced initial states.Comment: 5 pages, 3 figure

Electrical read out for coherent phenomena involving Rydberg atoms in thermal vapor cells

We present a very sensitive and scalable method to measure the population of highly excited Rydberg states in a thermal vapor cell of rubidium atoms. We detect the Rydberg ionization current in a 5 mm electrically contacted cell. The measured current is found to be in excellent agreement with a theory for the Rydberg population based on a master equation for the three level problem including an ionization channel and the full Doppler distributions at the corresponding temperatures. The signal-to-noise ratio of the current detection is substantially better than purely optical techniques.Comment: 4 pages, 4 figure

An atom-by-atom assembler of defect-free arbitrary 2d atomic arrays

Large arrays of individually controlled atoms trapped in optical tweezers are a very promising platform for quantum engineering applications. However, to date, only disordered arrays have been demonstrated, due to the non-deterministic loading of the traps. Here, we demonstrate the preparation of fully loaded, two-dimensional arrays of up to 50 microtraps each containing a single atom, and arranged in arbitrary geometries. Starting from initially larger, half-filled matrices of randomly loaded traps, we obtain user-defined target arrays at unit filling. This is achieved with a real-time control system and a moving optical tweezers that performs a sequence of rapid atom moves depending on the initial distribution of the atoms in the arrays. These results open exciting prospects for quantum engineering with neutral atoms in tunable geometries

Study of the Mechanical Strength Improvement of Wafers for EWT Solar Cells by Chemical Etching after the Drilling Process

Mechanical stability of EWT solar cells deteriorates when holes are created in the wafer. Nevertheless, the chemical etching after the hole generation process improves the mechanical strength by removing part of the damage produced in the drilling process. Several sets of wafers with alkaline baths of different duration have been prepared. The mechanical strength has been measured by the ring on ring bending test and the failure stresses have been obtained through a FE simulation of the test. This paper shows the comparison of these groups of wafers in order to obtain an optimum value of the decreased thickness produced by the chemical etchin

Representing future urban and regional scenarios for flood hazard mitigation

In this paper we analyse urban and regional growth trends by using dynamic spatial models. The objective of this approach is twofold: on the one hand to monitor sustainable development trends and on the other hand to assess flood risk in urban areas. We propose the use of future urban scenarios in order to forecast the effects of urban and regional planning policies. In the last 20 years the extent of built-up areas in Europe has increased by 20%, exceeding clearly the 6% rate of population growth over the same period. This trend contributes to unsustainable development patterns, and moreover, the exposure to natural hazards is increasing in large regions of Europe. The paper is organised in two parts. In the first part we analyse a study case in Friuli-Venezia Giulia (FVG) Region in northern Italy. We analyse several spatial indicators in the form of maps describing population growth and patterns, and the historical growth of built-up areas. Then we show the results of a dynamic spatial model for simulating land use scenarios. The model is based on a spatial dynamics bottom-up approach, and can be defined as a cellular automata (CA)-based model. Future urban scenarios are produced by taking into account several factors –e.g. land use development, population growth or spatial planning policies–. Urban simulations offer a useful approach to understanding the consequences of current spatial planning policies. Inappropriate regional and urban planning can exacerbate the negative effects of extreme hydrological processes. Good land management and planning practices, including appropriate land use and development control in flood-prone areas, represent suitable non-structural solutions to minimise flood damages. The overall effects of these measures in terms of both sustainable development and flood defence can be quantified with the proposed modelling approach. In the second part of the paper we show some preliminary results of a pilot study case. Two future simulations produced by the model were used for a flood risk assessment in Pordenone (one of the four provinces of FVG). In the last 100 years Pordenone has suffered several floods. The two major events were the heavy floods of 1966 (100-year flood event; >500 mm of rain in 36 hours) and 2002 (up to 580 mm of rain in 36 hours). The disastrous consequences of those heavy floods have shown how vulnerable this area is. The flood risk analysis is based on a hydrological hazard map for the Livenza River catchment area, provided by the regional Water Authority. That map covers most of flood hazard areas of Pordenone province. Early results of this study show that the main driving force of natural disasters damage is not only increasing flood hazard, but increasing vulnerability, mainly due to urbanisation in flood prone areas.

Study of the Mechanical Strength Improvement of Wafers for EWT Solar Cells by Chemical Etching after the Drilling Process

Mechanical stability of EWT solar cells deteriorates when holes are created in the wafer. Nevertheless, the chemical etching after the hole generation process improves the mechanical strength by removing part of the damage produced in the drilling process. Several sets of wafers with alkaline baths of different duration have been prepared. The mechanical strength has been measured by the ring on ring bending test and the failure stresses have been obtained through a FE simulation of the test. This paper shows the comparison of these groups of wafers in order to obtain an optimum value of the decreased thickness produced by the chemical etchin

Single-Atom Addressing in Microtraps for Quantum-State Engineering using Rydberg Atoms

We report on the selective addressing of an individual atom in a pair of single-atom microtraps separated by $3\;\mu$m. Using a tunable light-shift, we render the selected atom off-resonant with a global Rydberg excitation laser which is resonant with the other atom, making it possible to selectively block this atom from being excited to the Rydberg state. Furthermore we demonstrate the controlled manipulation of a two-atom entangled state by using the addressing beam to induce a phase shift onto one component of the wave function of the system, transferring it to a dark state for the Rydberg excitation light. Our results are an important step towards implementing quantum information processing and quantum simulation with large arrays of Rydberg atoms.Comment: 4 pages, 3 figure

Crop conditional Convolutional Neural Networks for massive multi-crop plant disease classification over cell phone acquired images taken on real field conditions

Convolutional Neural Networks (CNN) have demonstrated their capabilities on the agronomical field, especially for plant visual symptoms assessment. As these models grow both in the number of training images and in the number of supported crops and diseases, there exist the dichotomy of (1) generating smaller models for specific crop or, (2) to generate a unique multi-crop model in a much more complex task (especially at early disease stages) but with the benefit of the entire multiple crop image dataset variability to enrich image feature description learning. In this work we first introduce a challenging dataset of more than one hundred-thousand images taken by cell phone in real field wild conditions. This dataset contains almost equally distributed disease stages of seventeen diseases and five crops (wheat, barley, corn, rice and rape-seed) where several diseases can be present on the same picture. When applying existing state of the art deep neural network methods to validate the two hypothesised approaches, we obtained a balanced accuracy (BAC=0.92) when generating the smaller crop specific models and a balanced accuracy (BAC=0.93) when generating a single multi-crop model. In this work, we propose three different CNN architectures that incorporate contextual non-image meta-data such as crop information onto an image based Convolutional Neural Network. This combines the advantages of simultaneously learning from the entire multi-crop dataset while reducing the complexity of the disease classification tasks. The crop-conditional plant disease classification network that incorporates the contextual information by concatenation at the embedding vector level obtains a balanced accuracy of 0.98 improving all previous methods and removing 71% of the miss-classifications of the former methods