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Choropleth maps have been studied and extended in many ways to counteract the many biases that can occur when using them. Two recent techniques, Surprise metrics and Value Suppressing Uncertainty Palettes (VSUPs), offer promising solutions but have yet to be tested empirically with users of visualizations. In this paper, we explore how well people can make use of these techniques in map exploration tasks. We report a crowdsourced experiment where n = 300 participants are assigned to one of Choropleth, Surprise (only), and VSUP conditions (depicting rates and Surprise in a suppressed palette). Results show clear differences in map analysis outcomes, e.g. with Surprise maps leading people to significantly higher areas of population, or VSUPs performing similar or better than Choropleths for rate selection. Qualitative analysis suggests that many participants may only consider a subset of the metrics presented to them during exploration and decision-making. We discuss how these results generally support the use of Surprise and VSUP techniques in practice, and opportunities for further technique development. The material for the study (data, study results and code) is publicly available on https://osf.io/exb95/., Comment: 9 pages

Measuring the quantum efficiency (QE) map of a photocathode injector typically requires laser scanning, an invasive operation that involves modifying the injector laser focus and rastering the focused laser spot across the photocathode surface. Raster scanning interrupts normal operation and takes considerable time to setup. In this paper, we demonstrate a novel method of measuring the QE map using a ghost imaging framework that correlates the injector laser spatial variation over time with the total charge yield. Ghost imaging enables passive, real-time monitoring of the QE map without manually modifying the injector laser or interrupting injector operation. We first demonstrate the method at the UCLA Pegasus photoinjector with the help of a digital micromirror device (DMD) and a piezoelectric mirror to increase our control of the overall transverse variance of the illumination profile. The reconstruction algorithm parameters are fine-tuned using simulations and the results are validated against the ground truth map acquired using the traditional rastering method. Finally, we apply the technique to data acquired parasitically from the LCLS photoinjector, showing the feasibility of this method to retrieve a QE map without interrupting normal operation., Comment: 9 pages, 10 figures

A new reference design is introduced for holographic coherent diffraction imaging. This consists in two references - "block" and "pinhole" shaped regions - placed adjacent to the imaging specimen. An efficient recovery algorithm is provided for the resulting holographic phase retrieval problem, which is based on solving a structured, overdetermined linear system. Analysis of the expected recovery error on noisy data, which is contaminated by Poisson shot noise, shows that this simple modification synergizes the individual references and hence leads to uniformly superior performance over single-reference schemes. Numerical experiments on simulated data confirm the theoretical prediction, and the proposed dual-reference scheme achieves a smaller recovery error than leading single-reference schemes.

A general mathematical framework and recovery algorithm is presented for the holographic phase retrieval problem. In this problem, which arises in holographic coherent diffraction imaging, a "reference" portion of the signal to be recovered via phase retrieval is a priori known from experimental design. A generic formula is also derived for the expected recovery error when the measurement data is corrupted by Poisson shot noise. This facilitates an optimization perspective towards reference design and analysis. We employ this optimization perspective towards quantifying the performance of various reference choices., Comment: 27 pages, 10 figures

This work presents a magnetic reconnection experiment in which the kinetic, magnetic and thermal properties of the plasma each play an important role in the overall energy balance and structure of the generated reconnection layer. Magnetic reconnection occurs during the interaction of continuous and steady flows of super-Alfvenic, magnetized, aluminum plasma, which collide in a geometry with two-dimensional symmetry, producing a stable and long-lasting reconnection layer. Optical Thomson scattering measurements show that when the layer forms, ions inside the layer are more strongly heated than electrons, reaching temperatures of Ti~ZTe>300 eV - much greater than can be expected from strong shock and viscous heating alone. Later in time, as the plasma density in the layer increases, the electron and ion temperatures are found to equilibrate, and a constant plasma temperature is achieved through a balance of the heating mechanisms and radiative losses of the plasma. Measurements from Faraday rotation polarimetry also indicate the presence of significant magnetic field pile-up occurring at the boundary of the reconnection region, which is consistent with the super-Alfvenic velocity of the inflows., Comment: 15 pages, 8 figures, 1 table

We show that delaminations in bilayer graphene (BLG) with electrostatically induced interlayer asymmetry can provide one with ballistic channels for electrons with energies inside the electrostatically induced BLG gap. These channels are formed by a combination of valley-polarised evanescent states propagating along the delamination edges (which persist in the presence of a strong magnetic field) and standing waves bouncing between them inside the delaminated region (in a strong magnetic field, these transform into Landau levels in the monolayers). For inverted stacking between BLGs on the left and right of the delamination (AB-2ML-BA or BA-2ML-AB), the lowest energy ballistic channels are gapless, have linear dispersion and appear to be weakly topologically protected. When BLG stacking order on both sides of the delamination is the same (AB-2ML-AB or BA-2ML-BA), the lowest energy ballistic channels are gapped, with gap $\varepsilon_g$ scaling as $\varepsilon_g\propto W^{-1}$ with delamination width and as $\varepsilon_g\propto\delta^{-1}$ with the on-layer energy difference within the delamination. Depending on their width, delaminations may also support several `higher energy' waveguide modes. Our results are based on both an analytical study of the wavematching of Dirac states and tight binding model calculations, and we analyse in detail the dependence of the delamination spectrum on electrostatic conditions in the structure, such as the vertical displacement field., Comment: 12 pages, 9 figures

Instruments to visualize transient structural changes of inhomogeneous materials on the nanometer scale with atomic spatial and temporal resolution are demanded to advance materials science, bioscience, and fusion sciences. One such technique is femtosecond electron microdiffraction, in which a short pulse of electrons with femtosecond-scale duration is focused into a micron-scale spot and used to obtain diffraction images to resolve ultrafast structural dynamics over localized crystalline domain. In this letter, we report the experimental demonstration of time-resolved mega-electron-volt electron microdiffraction which achieves a 5 {\mu}m root-mean-square (rms) beam size on the sample and a 100 fs rms temporal resolution. Using pulses of 10k electrons at 4.2 MeV energy with a normalized emittance 3 nm-rad, we obtained high quality diffraction from a single 10 {\mu}m paraffin (C_44 H_90) crystal. The phonon softening mode in optical-pumped polycrystalline Bi was also time-resolved, demonstrating the temporal resolution limits of our instrument design. This new characterization capability will open many research opportunities in material and biological sciences.

A central challenge in neuroscience is to understand neural computations and circuit mechanisms that underlie the encoding of ethologically relevant, natural stimuli. In multilayered neural circuits, nonlinear processes such as synaptic transmission and spiking dynamics present a significant obstacle to the creation of accurate computational models of responses to natural stimuli. Here we demonstrate that deep convolutional neural networks (CNNs) capture retinal responses to natural scenes nearly to within the variability of a cell's response, and are markedly more accurate than linear-nonlinear (LN) models and Generalized Linear Models (GLMs). Moreover, we find two additional surprising properties of CNNs: they are less susceptible to overfitting than their LN counterparts when trained on small amounts of data, and generalize better when tested on stimuli drawn from a different distribution (e.g. between natural scenes and white noise). Examination of trained CNNs reveals several properties. First, a richer set of feature maps is necessary for predicting the responses to natural scenes compared to white noise. Second, temporally precise responses to slowly varying inputs originate from feedforward inhibition, similar to known retinal mechanisms. Third, the injection of latent noise sources in intermediate layers enables our model to capture the sub-Poisson spiking variability observed in retinal ganglion cells. Fourth, augmenting our CNNs with recurrent lateral connections enables them to capture contrast adaptation as an emergent property of accurately describing retinal responses to natural scenes. These methods can be readily generalized to other sensory modalities and stimulus ensembles. Overall, this work demonstrates that CNNs not only accurately capture sensory circuit responses to natural scenes, but also yield information about the circuit's internal structure and function., Comment: L.T.M. and N.M. contributed equally to this work. Presented at NIPS 2016

Chirality is a fundamental property of electrons with the relativistic spectrum found in graphene and topological insulators. It plays a crucial role in relativistic phenomena, such as Klein tunneling, but it is difficult to visualize directly. Here we report the direct observation and manipulation of chirality and pseudospin polarization in the tunneling of electrons between two almost perfectly aligned graphene crystals. We use a strong in-plane magnetic field as a tool to resolve the contributions of the chiral electronic states that have a phase difference between the two components of their vector wavefunction. Our experiments not only shed light on chirality, but also demonstrate a technique for preparing graphene's Dirac electrons in a particular quantum chiral state in a selected valley., Comment: 26 pages, 13 figures