All-optical reconstruction of atomic ground-state population

The population distribution within the ground-state of an atomic ensemble is of large significance in a variety of quantum optics processes. We present a method to reconstruct the detailed population distribution from a set of absorption measurements with various frequencies and polarizations, by utilizing the differences between the dipole matrix elements of the probed transitions. The technique is experimentally implemented on a thermal rubidium vapor, demonstrating a population-based analysis in two optical pumping examples. The results are used to verify and calibrate an elaborated numerical model, and the limitations of the reconstruction scheme which result from the symmetry properties of the dipole matrix elements are discussed.Comment: 6 pages, 4 figure

Storing images in warm atomic vapor

Reversible and coherent storage of light in atomic medium is a key-stone of future quantum information applications. In this work, arbitrary two-dimensional images are slowed and stored in warm atomic vapor for up to 30 $\mu$s, utilizing electromagnetically induced transparency. Both the intensity and the phase patterns of the optical field are maintained. The main limitation on the storage resolution and duration is found to be the diffusion of atoms. A techniqueanalogous to phase-shift lithography is employed to diminish the effect of diffusion on the visibility of the reconstructed image

Policy support of economic growth corridors: A Canadian approach to urban-rural development

The purpose of this paper is to provide a rationale for a federal policy to support the development of growth corridors within Canada. The intent is to provide insight into growth corridors by defining what is meant by them, by looking at several North American examples and by providing an in-depth look and rationale of the newly formed Halifax – Moncton Growth Corridor. The paper offers lessons learned from this process which include that all stakeholders should be engaged and regional benefits and opposing interest must be identified. The researcher argues that a policy that addresses growth corridor development would encourage regions to work more collaboratively and would assist the government address the urban – rural dilemma.Keywords: growth corridors, policy, Halifax-Moncton growth corrido

Box spline prewavelets of small support

The purpose of this paper is the construction of bi- and trivariate prewavelets from box-spline spaces, \ie\ piecewise polynomials of fixed degree on a uniform mesh. They have especially small support and form Riesz bases of the wavelet spaces, so they are stable. In particular, the supports achieved are smaller than those of the prewavelets due to Riemenschneider and Shen in a recent, similar constructio

Measurement of Dicke Narrowing in Electromagnetically Induced Transparency

Dicke narrowing is a phenomena that dramatically reduces the Doppler width of spectral lines, due to frequent velocity-changing collisions. A similar phenomena occurs for electromagnetically induced transparency (EIT) resonances, and facilitates ultra-narrow spectral features in room-temperature vapor. We directly measure the Dicke-like narrowing by studying EIT line-shapes as a function of the angle between the pump and the probe beams. The measurements are in good agreement with an analytic theory with no fit parameters. The results show that Dicke narrowing can increase substantially the tolerance of hot-vapor EIT to angular deviations. We demonstrate the importance of this effect for applications such as imaging and spatial solitons using a single-shot imaging experiment, and discuss the implications on the feasibility of storing images in atomic vapor.Comment: Introduction revise

Enhancing Ligand Pose Sampling for Molecular Docking

Deep learning promises to dramatically improve scoring functions for molecular docking, leading to substantial advances in binding pose prediction and virtual screening. To train scoring functions-and to perform molecular docking-one must generate a set of candidate ligand binding poses. Unfortunately, the sampling protocols currently used to generate candidate poses frequently fail to produce any poses close to the correct, experimentally determined pose, unless information about the correct pose is provided. This limits the accuracy of learned scoring functions and molecular docking. Here, we describe two improved protocols for pose sampling: GLOW (auGmented sampLing with sOftened vdW potential) and a novel technique named IVES (IteratiVe Ensemble Sampling). Our benchmarking results demonstrate the effectiveness of our methods in improving the likelihood of sampling accurate poses, especially for binding pockets whose shape changes substantially when different ligands bind. This improvement is observed across both experimentally determined and AlphaFold-generated protein structures. Additionally, we present datasets of candidate ligand poses generated using our methods for each of around 5,000 protein-ligand cross-docking pairs, for training and testing scoring functions. To benefit the research community, we provide these cross-docking datasets and an open-source Python implementation of GLOW and IVES at https://github.com/drorlab/GLOW_IVES .Comment: Published at the Machine Learning for Structural Biology Workshop, NeurIPS 202

Helly-Type Theorems in Property Testing

Helly's theorem is a fundamental result in discrete geometry, describing the ways in which convex sets intersect with each other. If $S$ is a set of $n$ points in $R^d$, we say that $S$ is $(k,G)$-clusterable if it can be partitioned into $k$ clusters (subsets) such that each cluster can be contained in a translated copy of a geometric object $G$. In this paper, as an application of Helly's theorem, by taking a constant size sample from $S$, we present a testing algorithm for $(k,G)$-clustering, i.e., to distinguish between two cases: when $S$ is $(k,G)$-clusterable, and when it is $\epsilon$-far from being $(k,G)$-clusterable. A set $S$ is $\epsilon$-far $(0<\epsilon\leq1)$ from being $(k,G)$-clusterable if at least $\epsilon n$ points need to be removed from $S$ to make it $(k,G)$-clusterable. We solve this problem for $k=1$ and when $G$ is a symmetric convex object. For $k>1$, we solve a weaker version of this problem. Finally, as an application of our testing result, in clustering with outliers, we show that one can find the approximate clusters by querying a constant size sample, with high probability

Topological stability of stored optical vortices

We report an experiment in which an optical vortex is stored in a vapor of Rb atoms. Due to its 2\pi phase twist, this mode, also known as the Laguerre-Gauss mode, is topologically stable and cannot unwind even under conditions of strong diffusion. To supplement our finding, we stored a flat phase Gaussian beam with a dark center. Contrary to the optical vortex, which stays stable for over 100 microseconds, the dark center in the retrieved flat-phased image was filled with light at storage times as small as 10 microseconds. This experiment proves that higher electromagnetic modes can be converted into atomic coherences, and that modes with phase singularities are robust to decoherence effects such as diffusion. This opens the possibility to more elaborate schemes for two dimensional information storage in atomic vapors.Comment: 4 pages, 4 figures v2: minor grammatical corrections v3: problem with references fixed v4: minor clarifications added to the tex

S2E15: Why do we toss 33% of food we produce when people are hungry?

Almost a billion people in the world are food insecure, and each year we throw away about one-third of the food we produce. Susanne Lee, executive-in-residence at the Maine Business School, and Peter O’Brien, a senior majoring in economics, examined the issue of food waste and have some possible solutions