Spin-motion coupling in a circular Rydberg state quantum simulator: case of two atoms

Rydberg atoms are remarkable tools for the quantum simulation of spin arrays. Circular Rydberg atoms open the way to simulations over very long time scales, using a combination of laser trapping of the atoms and spontaneous-emission inhibition, as shown in the proposal of a XXZ spin-array simulator based on chains of trapped circular atoms [T.L. Nguyen $\textit{et al.}$, Phys. Rev. X 8, 011032 (2018)]. Such simulators could reach regimes (thermalization, glassy dynamics) that are out of the reach of those based on ordinary, low-angular-momentum short-lived Rydberg atoms. Over the promised long time scales, the unavoidable coupling of the spin dynamics with the atomic motion in the traps may play an important role. We study here the interplay between the spin exchange and motional dynamics in the simple case of two interacting circular Rydberg atoms confined in harmonic traps. The time evolution is solved exactly when the position dependence of the dipole-dipole interaction terms can be linearized over the extension of the atomic motion. We present numerical simulations in more complex cases, using the realistic parameters of the simulator proposal. We discuss three applications. First, we show that realistic experimental parameters lead to a regime in which atomic and spin dynamics become fully entangled, generating interesting non-classical motional states. We also show that, in other parameter regions, the spin dynamics notably depends on the initial temperature of the atoms in the trap, providing a sensitive motional thermometry method. Last, and most importantly, we discuss the range of parameters in which the motion has negligible influence over the spin dynamics.Comment: 18 pages, 12 figure

A spiraled segmented waveguide sensor: Principle and experiment

A novel type of chemo-optical sensor has been designed, fabricated and characterized. The sensor is simple to fabricate, puts low demands on light source quality and shows resolution of index changes of ~ $3.10^{-8}

Geographically weighted evidence combination approaches for combining discordant and inconsistent volunteered geographical information

There is much interest in being able to combine crowdsourced data. One of the critical issues in information sciences is how to combine data or information that are discordant or inconsistent in some way. Many previous approaches have taken a majority rules approach under the assumption that most people are correct most of the time. This paper analyses crowdsourced land cover data generated by the Geo-Wiki initiative in order to infer the land cover present at locations on a 50 km grid. It compares four evidence combination approaches (Dempster Shafer, Bayes, Fuzzy Sets and Possibility) applied under a geographically weighted kernel with the geographically weighted average approach applied in many current Geo-Wiki analyses. A geographically weighted approach uses a moving kernel under which local analyses are undertaken. The contribution (or salience) of each data point to the analysis is weighted by its distance to the kernel centre, reflecting Tobler’s 1st law of geography. A series of analyses were undertaken using different kernel sizes (or bandwidths). Each of the geographically weighted evidence combination methods generated spatially distributed measures of belief in hypotheses associated with the presence of individual land cover classes at each location on the grid. These were compared with GlobCover, a global land cover product. The results from the geographically weighted average approach in general had higher correspondence with the reference data and this increased with bandwidth. However, for some classes other evidence combination approaches had higher correspondences possibly because of greater ambiguity over class conceptualisations and / or lower densities of crowdsourced data. The outputs also allowed the beliefs in each class to be mapped. The differences in the soft and the crisp maps are clearly associated with the logics of each evidence combination approach and of course the different questions that they ask of the data. The results show that discordant data can be combined (rather than being removed from analysis) and that data integrated in this way can be parameterised by different measures of belief uncertainty. The discussion highlights a number of critical areas for future research

Array of Individual Circular Rydberg Atoms Trapped in Optical Tweezers

Circular Rydberg atoms (CRAs), i.e., Rydberg atoms with maximal orbital momentum, are highly promising for quantum computation, simulation and sensing. They combine long natural lifetimes with strong inter-atomic interactions and coupling to electromagnetic fields. Trapping individual CRAs is essential to harness these unique features. We report the first demonstration of CRAs laser-trapping in a programmable array of optical bottle beams. We observe the decay of a trapped Rubidium circular level over 5ms using a novel optical detection method. This first optical detection of alkali CRAs is both spatially- and level selective. We finally observe the mechanical oscillations of the CRAs in the traps. This work opens the route to the use of circular levels in quantum devices. It is also promising for quantum simulation and information processing using the full extent of Rydberg manifolds

Comparative study of nonlinear-optical polymers for guided-wave second-harmonic generation at telecommunication wavelengths

International audiencex

The dispersion time of random walks on finite graphs

We study two random processes on an $n$-vertex graph inspired by the internal diffusion limited aggregation (IDLA) model. In both processes $n$ particles start from an arbitrary but fixed origin. Each particle performs a simple random walk until first encountering an unoccupied vertex, and at which point the vertex becomes occupied and the random walk terminates. In one of the processes, called $\textit{Sequential-IDLA}$, only one particle moves until settling and only then does the next particle start whereas in the second process, called $\textit{Parallel-IDLA}$, all unsettled particles move simultaneously. Our main goal is to analyze the so-called dispersion time of these processes, which is the maximum number of steps performed by any of the $n$ particles. In order to compare the two processes, we develop a coupling that shows the dispersion time of the Parallel-IDLA stochastically dominates that of the Sequential-IDLA; however, the total number of steps performed by all particles has the same distribution in both processes. This coupling also gives us that dispersion time of Parallel-IDLA is bounded in expectation by dispersion time of the Sequential-IDLA up to a multiplicative $\log n$ factor. Moreover, we derive asymptotic upper and lower bound on the dispersion time for several graph classes, such as cliques, cycles, binary trees, $d$-dimensional grids, hypercubes and expanders. Most of our bounds are tight up to a multiplicative constant.ERC Grant Dynamic Marc

Class III antiarrhythmic drugs amiodarone and dronedarone impair KIR2.1 backward trafficking

Drug-induced ion channel trafficking disturbance can cause cardiac arrhythmias. The subcellular level at which drugs interfere in trafficking pathways is largely unknown. KIR2.1 inward rectifier channels, largely responsible for the cardiac inward rectifier current (IK1), are degraded in lysosomes. Amiodarone and dronedarone are class III antiarrhythmics. Chronic use of amiodarone, and to a lesser extent dronedarone, causes serious adverse effects to several organs and tissue types, including the heart. Both drugs have been described to interfere in the late-endosome/lysosome system. Here we defined the potential interference in KIR2.1 backward trafficking by amiodarone and dronedarone. Both drugs inhibited IK1 in isolated rabbit ventricular cardiomyocytes at supraclinical doses only. In HK-KWGF cells, both drugs dose- and time-dependently increased KIR2.1 expression (2.0 ± 0.2-fold with amiodarone: 10 μM, 24 hrs; 2.3 ± 0.3-fold with dronedarone: 5 μM, 24 hrs) and late-endosomal/lysosomal KIR2.1 accumulation. Increased KIR2.1 expression level was also observed in the presence of Nav1.5 co-expression. Augmented KIR2.1 protein levels and intracellular accumulation were also observed in COS-7, END-2, MES-1 and EPI-7 cells. Both drugs had no effect on Kv11.1 ion channel protein expression levels. Finally, amiodarone (73.3 ± 10.3% P < 0.05 at −120 mV, 5 μM) enhanced IKIR2.1 upon 24-hrs treatment, whereas dronedarone tended to increase IKIR2.1 and it did not reach significance (43.8 ± 5.5%, P = 0.26 at −120 mV; 2 μM). We conclude that chronic amiodarone, and potentially also dronedarone, treatment can result in enhanced IK1 by inhibiting KIR2.1 degradation

Class III antiarrhythmic drugs amiodarone and dronedarone impair KIR2.1 backward trafficking

Drug-induced ion channel trafficking disturbance can cause cardiac arrhythmias. The subcellular level at which drugs interfere in trafficking pathways is largely unknown. KIR2.1 inward rectifier channels, largely responsible for the cardiac inward rectifier current (IK 1), are degraded in lysosomes. Amiodarone and dronedarone are class III antiarrhythmics. Chronic use of amiodarone, and to a lesser extent dronedarone, causes serious adverse effects to several organs and tissue types, including the heart. Both drugs have been described to interfere in the late-endosome/lysosome system. Here we defined the potential interference in KIR2.1 backward trafficking by amiodarone and dronedarone. Both drugs inhibited IK 1 in isolated rabbit ventricular cardiomyocytes at supraclinical doses only. In HK-KWGF cells, both drugs dose- and time-dependently increased KIR2.1 expression (2.0 ± 0.2-fold with amiodarone: 10 μM, 24 hrs; 2.3 ± 0.3-fold with dronedarone: 5 μM, 24 hrs) and late-endosomal/lysosomal KIR2.1 accumulation. Increased KIR2.1 expression level was also observed in the presence of Nav1.5 co-expression. Augmented KIR2.1 protein levels and intracellular accumulation were also observed in COS-7, END-2, MES-1 and EPI-7 cells. Both drugs had no effect on Kv11.1 ion channel protein expression levels. Finally, amiodarone (73.3 ± 10.3% P < 0.05 at −120 mV, 5 μM) enhanced IKIR 2.1 upon 24-hrs treatment, whereas dronedarone tended to increase IKIR 2.1 and it did not reach significance (43.8 ± 5.5%, P = 0.26 at −120 mV; 2 μM). We conclude that chronic amiodarone, and potentially also dronedarone, treatment can result in enhanced IK 1 by inhibiting KIR2.1 degradation