Extreme Events in Resonant Radiation from Three-dimensional Light Bullets

We report measurements that show extreme events in the statistics of resonant radiation emitted from spatiotemporal light bullets. We trace the origin of these extreme events back to instabilities leading to steep gradients in the temporal profile of the intense light bullet that occur during the initial collapse dynamics. Numerical simulations reproduce the extreme valued statistics of the resonant radiation which are found to be intrinsically linked to the simultaneous occurrence of both temporal and spatial self-focusing dynamics. Small fluctuations in both the input energy and in the spatial phase curvature explain the observed extreme behaviour.Comment: 5 pages, 5 figures, submitte

Mid-infrared sub-wavelength grating mirror design: tolerance and influence of technological constraints

High polarization selective Si/SiO2 mid-infrared sub-wavelength grating mirrors with large bandwidth adapted to VCSEL integration are compared. These mirrors have been automatically designed for operation at \lambda = 2.3 $\mu$m by an optimization algorithm which maximizes a specially defined quality factor. Several technological constraints in relation with the grating manufacturing process have been imposed within the optimization algorithm and their impact on the optical properties of the mirror have been evaluated. Furthermore, through the tolerance computation of the different dimensions of the structure, the robustness with respect to fabrication errors has been tested. Finally, it appears that the increase of the optical performances of the mirror imposes a less tolerant design with severer technological constraints resulting in a more stringent control of the manufacturing process.Comment: The final publication is available at http://iopscience.iop.org/2040-8986/13/12/125502

Evolution in prostheses for sprinters with lower-limb amputation

Depuis une quinzaine d'années, les progrès techniques en appareillage ont été le facteur déterminant de la progression des performances des sportifs amputés de membre inférieur. Pour l'amputé tibial, la prothèse de course comprend un manchon gel et une emboîture solidarisés par un accrochage distal ou un vide virtuel. Par ses qualités dynamiques, le pied en fibre de carbone, garni de pointes, assure des performances remarquables. Pour l'amputé fémoral, équipé des mêmes pieds prothétiques, le genou est à biellettes et à contrôle des phases d'appui et pendulaire. Par rapport au coureur valide, le temps d'appui sur le membre appareillé est raccourci tandis que celui sur le membre sain est allongé. L'asymétrie du sprint de l'amputé tibial est discrète. C'est le travail des extenseurs de hanche qui est la principale compensation au déficit de propulsion dû à l'amputation. Chez l'amputé fémoral, l'absence de genou aggrave l'asymétrie. L'extension totale du genou prothétique, précoce en fin de phase oscillante et persistant pendant toute la phase d'appui, impose une compensation par une augmentation d'extension de la hanche controlatérale. Les transferts de charge de travail entre côté amputé et sain, par l'intermédiaire d'une hyperlordose lombaire, mettent en jeu le bassin, le tronc et les épaules. Les amputés sportifs font progresser la recherche en appareillage. Leurs orthoprothésistes acquièrent avec eux un savoir-faire dont bénéficient leurs patients non-sportifs.For about 15 years, technical advances in prosthetic treatment have been the main factor in the increased performance of athletes with lower-limb amputation. For trans-tibial amputation, the prosthesis for sprinting is composed of a gel liner and a socket joined by a locking or virtual vacuum liner. Because of these dynamic properties, the carbon prosthetic foot equipped with tacks ensures outstanding performance. For trans-femoral amputation, a hydraulic swing and a stance control unit are added to the same prosthesis. In comparison with the able-bodied runner, athletes with amputation have smaller loading times in the prosthetic limb and larger ones in the sound limb. The length of the energy-storing prosthetic foot is determined by the “up-on-the-toes” running gait. The sprinting gait with trans-tibial amputation is almost symmetrical. The hip extensor effort is the main compensation of propulsion reduction with lower-limb amputation. With trans-femoral amputation, the lack of knee increases the asymmetry. The total prosthetic knee extension (early in late-swing phase and lasting during total stance phase) compensates with extension of both hips, especially the opposite one. The amputation and sound limb load transfer with lumbar hyperlordosis concern the pelvis, trunk and shoulders. Because of athletes with amputation, research in prosthetic treatment has progressed. The development of orthotics and prostheses for such athletes has benefited non-athletes with amputation

Modulation control and spectral shaping of optical fiber supercontinuum generation in the picosecond regime

Numerical simulations are used to study how fiber supercontinuum generation seeded by picosecond pulses can be actively controlled through the use of input pulse modulation. By carrying out multiple simulations in the presence of noise, we show how tailored supercontinuum Spectra with increased bandwidth and improved stability can be generated using an input envelope modulation of appropriate frequency and depth. The results are discussed in terms of the non-linear propagation dynamics and pump depletion.Comment: Aspects of this work were presented in Paper ThJ2 at OECC/ACOFT 2008, Sydney Australia 7-10 July (2008). Journal paper submitted for publication 30 July 200

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector.

The development and operation of liquid-argon time-projection chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies

Calibration of the charge and energy loss per unit length of the MicroBooNE liquid argon time projection chamber using muons and protons

We describe a method used to calibrate the position- and time-dependent response of the MicroBooNE liquid argon time projection chamber anode wires to ionization particle energy loss. The method makes use of crossing cosmic-ray muons to partially correct anode wire signals for multiple effects as a function of time and position, including cross-connected TPC wires, space charge effects, electron attachment to impurities, diffusion, and recombination. The overall energy scale is then determined using fully-contained beam-induced muons originating and stopping in the active region of the detector. Using this method, we obtain an absolute energy scale uncertainty of 2% in data. We use stopping protons to further refine the relation between the measured charge and the energy loss for highly-ionizing particles. This data-driven detector calibration improves both the measurement of total deposited energy and particle identification based on energy loss per unit length as a function of residual range. As an example, the proton selection efficiency is increased by 2% after detector calibration

Reconstruction and measurement of (100) MeV energy electromagnetic activity from π0 arrow γγ decays in the MicroBooNE LArTPC

We present results on the reconstruction of electromagnetic (EM) activity from photons produced in charged current νμ interactions with final state π0s. We employ a fully-automated reconstruction chain capable of identifying EM showers of (100) MeV energy, relying on a combination of traditional reconstruction techniques together with novel machine-learning approaches. These studies demonstrate good energy resolution, and good agreement between data and simulation, relying on the reconstructed invariant π0 mass and other photon distributions for validation. The reconstruction techniques developed are applied to a selection of νμ + Ar → μ + π0 + X candidate events to demonstrate the potential for calorimetric separation of photons from electrons and reconstruction of π0 kinematics

Sustainable bioenergy for climate mitigation: Developing drought-tolerant trees and grasses

\u2022 Background and Aims Bioenergy crops are central to climate mitigation strategies that utilize biogenic carbon, such as BECCS (bioenergy with carbon capture and storage), alongside the use of biomass for heat, power, liquid fuels and, in the future, biorefining to chemicals. Several promising lignocellulosic crops are emerging that have no food role \u2013 fast-growing trees and grasses \u2013 but are well suited as bioenergy feedstocks, including Populus, Salix, Arundo, Miscanthus, Panicum and Sorghum. \u2022 Scope These promising crops remain largely undomesticated and, until recently, have had limited germplasm resources. In order to avoid competition with food crops for land and nature conservation, it is likely that future bioenergy crops will be grown on marginal land that is not needed for food production and is of poor quality and subject to drought stress. Thus, here we define an ideotype for drought tolerance that will enable biomass production to be maintained in the face of moderate drought stress. This includes traits that can readily be measured in wide populations of several hundred unique genotypes for genome-wide association studies, alongside traits that are informative but can only easily be assessed in limited numbers or training populations that may be more suitable for genomic selection. Phenotyping, not genotyping, is now the major bottleneck for progress, since in all lignocellulosic crops studied extensive use has been made of next-generation sequencing such that several thousand markers are now available and populations are emerging that will enable rapid progress for drought-tolerance breeding. The emergence of novel technologies for targeted genotyping by sequencing are particularly welcome. Genome editing has already been demonstrated for Populus and offers significant potential for rapid deployment of drought-tolerant crops through manipulation of ABA receptors, as demonstrated in Arabidopsis, with other gene targets yet to be tested. \u2022 Conclusions Bioenergy is predicted to be the fastest-developing renewable energy over the coming decade and significant investment over the past decade has been made in developing genomic resources and in collecting wild germplasm from within the natural ranges of several tree and grass crops. Harnessing these resources for climate-resilient crops for the future remains a challenge but one that is likely to be successful

Convolutional Neural Networks Applied to Neutrino Events in a Liquid Argon Time Projection Chamber

We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identification or event detection on simulated neutrino interactions. We also address technical issues that arise when applying this technique to data from a large LArTPC at or near ground level