Electric field control of magnetization dynamics in ZnMnSe/ZnBeSe diluted-magnetic-semiconductor heterostructures

We show that the magnetization dynamics in diluted magnetic semiconductors can be controlled separately from the static magnetization by means of an electric field. The spin-lattice relaxation (SLR) time of magnetic Mn2+ ions was tuned by two orders of magnitude by a gate voltage applied to n-type modulation-doped (Zn,Mn)Se/(Zn,Be)Se quantum wells. The effect is based on providing an additional channel for SLR by a two-dimensional electron gas (2DEG). The static magnetization responsible for the giant Zeeman spin splitting of excitons was not influenced by the 2DEG density

Self-guided wakefield experiments driven by petawatt class ultra-short laser pulses

We investigate the extension of self-injecting laser wakefield experiments to the regime that will be accessible with the next generation of petawatt class ultra-short pulse laser systems. Using linear scalings, current experimental trends and numerical simulations we determine the optimal laser and target parameters, i.e. focusing geometry, plasma density and target length, that are required to increase the electron beam energy (to > 1 GeV) without the use of external guiding structures.Comment: 15 pages, 8 figure

Accurate and linear time pose estimation from points and lines

The final publication is available at link.springer.comThe Perspective-n-Point (PnP) problem seeks to estimate the pose of a calibrated camera from n 3Dto-2D point correspondences. There are situations, though, where PnP solutions are prone to fail because feature point correspondences cannot be reliably estimated (e.g. scenes with repetitive patterns or with low texture). In such scenarios, one can still exploit alternative geometric entities, such as lines, yielding the so-called Perspective-n-Line (PnL) algorithms. Unfortunately, existing PnL solutions are not as accurate and efficient as their point-based counterparts. In this paper we propose a novel approach to introduce 3D-to-2D line correspondences into a PnP formulation, allowing to simultaneously process points and lines. For this purpose we introduce an algebraic line error that can be formulated as linear constraints on the line endpoints, even when these are not directly observable. These constraints can then be naturally integrated within the linear formulations of two state-of-the-art point-based algorithms, the OPnP and the EPnP, allowing them to indistinctly handle points, lines, or a combination of them. Exhaustive experiments show that the proposed formulation brings remarkable boost in performance compared to only point or only line based solutions, with a negligible computational overhead compared to the original OPnP and EPnP.Peer ReviewedPostprint (author's final draft

Influence of realistic parameters on state-of-the-art LWFA experiments

We examine the influence of non-ideal plasma-density and non-Gaussian transverse laser-intensity profiles in the laser wakefield accelerator analytically and numerically. We find that the characteristic amplitude and scale length of longitudinal density fluctuations impacts on the final energies achieved by electron bunches. Conditions that minimize the role of the longitudinal plasma density fluctuations are found. The influence of higher order Laguerre-Gaussian laser pulses is also investigated. We find that higher order laser modes typically lead to lower energy gains. Certain combinations of higher order modes may, however, lead to higher electron energy gains.Comment: 16 pages, 6 figures; Accepted for publication in Plasma Physics and Controlled Fusio

Dynamic Control of Laser Produced Proton Beams

The emission characteristics of intense laser driven protons are controlled using ultra-strong (of the order of 10^9 V/m) electrostatic fields varying on a few ps timescale. The field structures are achieved by exploiting the high potential of the target (reaching multi-MV during the laser interaction). Suitably shaped targets result in a reduction in the proton beam divergence, and hence an increase in proton flux while preserving the high beam quality. The peak focusing power and its temporal variation are shown to depend on the target characteristics, allowing for the collimation of the inherently highly divergent beam and the design of achromatic electrostatic lenses.Comment: 9 Pages, 5 figure

Unsupervised Learning of Category-Specific Symmetric 3D Keypoints from Point Sets

Automatic discovery of category-specific 3D keypoints from a collection of objects of a category is a challenging problem. The difficulty is added when objects are represented by 3D point clouds, with variations in shape and semantic parts and unknown coordinate frames. We define keypoints to be category-specific, if they meaningfully represent objects’ shape and their correspondences can be simply established order-wise across all objects. This paper aims at learning such 3D keypoints, in an unsupervised manner, using a collection of misaligned 3D point clouds of objects from an unknown category. In order to do so, we model shapes defined by the keypoints, within a category, using the symmetric linear basis shapes without assuming the plane of symmetry to be known. The usage of symmetry prior leads us to learn stable keypoints suitable for higher misalignments. To the best of our knowledge, this is the first work on learning such keypoints directly from 3D point clouds for a general category. Using objects from four benchmark datasets, we demonstrate the quality of our learned keypoints by quantitative and qualitative evaluations. Our experiments also show that the keypoints discovered by our method are geometrically and semantically consistent