Observational diagnostics of gas in protoplanetary disks

Protoplanetary disks are composed primarily of gas (99% of the mass). Nevertheless, relatively few observational constraints exist for the gas in disks. In this review, I discuss several observational diagnostics in the UV, optical, near-IR, mid-IR, and (sub)-mm wavelengths that have been employed to study the gas in the disks of young stellar objects. I concentrate in diagnostics that probe the inner 20 AU of the disk, the region where planets are expected to form. I discuss the potential and limitations of each gas tracer and present prospects for future research.Comment: Review written for the proceedings of the conference "Origin and Evolution of Planets 2008", Ascona, Switzerland, June 29 - July 4, 2008. Date manuscript: October 2008. 17 Pages, 6 graphics, 134 reference

Star and Planet Formation with ALMA: an Overview

Submillimeter observations with ALMA will be the essential next step in our understanding of how stars and planets form. Key projects range from detailed imaging of the collapse of pre-stellar cores and measuring the accretion rate of matter onto deeply embedded protostars, to unravelling the chemistry and dynamics of high-mass star-forming clusters and high-spatial resolution studies of protoplanetary disks down to the 1 AU scale.Comment: Invited review, 8 pages, 5 figures; to appear in the proceedings of "Science with ALMA: a New Era for Astrophysics". Astrophysics & Space Science, in pres

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 10^3 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype

Probing the circumstellar structure of pre-main sequence stars

Peer reviewe

Thermal Neutron Computed Tomography of Soil Water and Plant Roots

Neutron radiography is a noninvasive imaging technique that measures the attenuation of thermal neutrons, as is done with x-ray and γ-ray radiography, to characterize the internal composition of materials. Neutron and x-ray imaging are complementary techniques, with neutron imaging especially well suited for materials containing H atoms and other low-atomic-weight attenuating materials. Although neutron computed tomography (NCT) techniques are routinely used in engineering, relatively little is known about their application to soils. We developed new techniques that use thermal neutron attenuation to measure the spatial and temporal distribution of water in soils and near roots at near 0.5-mm spatial resolution or higher. The neutron source was a Mark II Triga Reactor at McClellan Nuclear Radiation Center in Sacramento, CA. After calibration using both deuterated and regular water, the effects of beam hardening and neutron scattering could be corrected for, provided that the total path length for a soil–water mixture does not exceed 1.0 cm, limiting soil sample thickness to about 2.5 cm. Using regular water, for a wide range of soil water content values, experiments demonstrated that NCT is sensitive to small changes in soil volumetric water content, allowing estimation of the spatial distribution of soil water, roots, and root water uptake. Although the spatial resolution of the applied NCT system was 80 μm, an error analysis showed that the averaging measurement volume should be not less than about 0.5 mm for the uncertainty in volumetric water content to be minimized to near 0.01 m3 m−3. A single root water uptake experiment with a corn (Zea mays L.) seedling demonstrated the successful application of NCT, with images showing spatially variable soil water content gradients in the rhizosphere and bulk soil