Quantum Imaging with Incoherently Scattered Light from a Free-Electron Laser

The advent of accelerator-driven free-electron lasers (FEL) has opened new avenues for high-resolution structure determination via diffraction methods that go far beyond conventional x-ray crystallography methods. These techniques rely on coherent scattering processes that require the maintenance of first-order coherence of the radiation field throughout the imaging procedure. Here we show that higher-order degrees of coherence, displayed in the intensity correlations of incoherently scattered x-rays from an FEL, can be used to image two-dimensional objects with a spatial resolution close to or even below the Abbe limit. This constitutes a new approach towards structure determination based on incoherent processes, including Compton scattering, fluorescence emission or wavefront distortions, generally considered detrimental for imaging applications. Our method is an extension of the landmark intensity correlation measurements of Hanbury Brown and Twiss to higher than second-order paving the way towards determination of structure and dynamics of matter in regimes where coherent imaging methods have intrinsic limitations

Strong Casimir force reduction through metallic surface nanostructuring

The Casimir force between bodies in vacuum can be understood as arising from their interaction with an infinite number of fluctuating electromagnetic quantum vacuum modes, resulting in a complex dependence on the shape and material of the interacting objects. Becoming dominant at small separations, the force plays a significant role in nanomechanics and object manipulation at the nanoscale, leading to a considerable interest in identifying structures where the Casimir interaction behaves significantly different from the well-known attractive force between parallel plates. Here we experimentally demonstrate that by nanostructuring one of the interacting metal surfaces at scales below the plasma wavelength, an unexpected regime in the Casimir force can be observed. Replacing a flat surface with a deep metallic lamellar grating with sub-100 nm features strongly suppresses the Casimir force and for large inter-surfaces separations reduces it beyond what would be expected by any existing theoretical prediction.Comment: 11 pages, 8 figure

DNA methylation subgroups and the CpG island methylator phenotype in gastric cancer: A comprehensive profiling approach

10.1186/1471-230X-14-55BMC Gastroenterology141-BGMA

Shedding Light on the Galaxy Luminosity Function

From as early as the 1930s, astronomers have tried to quantify the statistical nature of the evolution and large-scale structure of galaxies by studying their luminosity distribution as a function of redshift - known as the galaxy luminosity function (LF). Accurately constructing the LF remains a popular and yet tricky pursuit in modern observational cosmology where the presence of observational selection effects due to e.g. detection thresholds in apparent magnitude, colour, surface brightness or some combination thereof can render any given galaxy survey incomplete and thus introduce bias into the LF. Over the last seventy years there have been numerous sophisticated statistical approaches devised to tackle these issues; all have advantages -- but not one is perfect. This review takes a broad historical look at the key statistical tools that have been developed over this period, discussing their relative merits and highlighting any significant extensions and modifications. In addition, the more generalised methods that have emerged within the last few years are examined. These methods propose a more rigorous statistical framework within which to determine the LF compared to some of the more traditional methods. I also look at how photometric redshift estimations are being incorporated into the LF methodology as well as considering the construction of bivariate LFs. Finally, I review the ongoing development of completeness estimators which test some of the fundamental assumptions going into LF estimators and can be powerful probes of any residual systematic effects inherent magnitude-redshift data.Comment: 95 pages, 23 figures, 3 tables. Now published in The Astronomy & Astrophysics Review. This version: bring in line with A&AR format requirements, also minor typo corrections made, additional citations and higher rez images adde

Templates and anchors for antenna-based wall following in cockroaches and robots

The interplay between robotics and neuromechanics facilitates discoveries in both fields: nature provides roboticists with design ideas, while robotics research elucidates critical features that confer performance advantages to biological systems. Here, we explore a system particularly well suited to exploit the synergies between biology and robotics: high-speed antenna-based wall following of the American cockroach (Periplaneta americana). Our approach integrates mathematical and hardware modeling with behavioral and neurophysiological experiments. Specifically, we corroborate a prediction from a previously reported wall-following template - the simplest model that captures a behavior - that a cockroach antenna-based controller requires the rate of approach to a wall in addition to distance, e.g., in the form of a proportional-derivative (PD) controller. Neurophysiological experiments reveal that important features of the wall-following controller emerge at the earliest stages of sensory processing, namely in the antennal nerve. Furthermore, we embed the template in a robotic platform outfitted with a bio-inspired antenna. Using this system, we successfully test specific PD gains (up to a scale) fitted to the cockroach behavioral data in a "real-world" setting, lending further credence to the surprisingly simple notion that a cockroach might implement a PD controller for wall following. Finally, we embed the template in a simulated lateral-leg-spring (LLS) model using the center of pressure as the control input. Importantly, the same PD gains fitted to cockroach behavior also stabilize wall following for the LLS model. © 2008 IEEE