Scintillation light detection in the 6-m drift-length ProtoDUNE Dual Phase liquid argon TPC

DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6x6x6m3 liquid argon time-projection-chamber (LArTPC) that recorded cosmic-muon data at the CERN Neutrino Platform in 2019&ndash;2020 as a prototype of the DUNE Far Detector. Charged particles propagating through the LArTPC produce ionization and scintillation light. The scintillation light signal in these detectors can provide the trigger for non-beam events. In addition, it adds precise timing capabilities and improves the calorimetry measurements. In ProtoDUNE-DP, scintillation and electroluminescence light produced by cosmic muons in the LArTPC is collected by photomultiplier tubes placed up to 7 m away from the ionizing track. In this paper, the ProtoDUNE-DP photon detection system performance is evaluated with a particular focus on the different wavelength shifters, such as PEN and TPB, and the use of Xe-doped LAr, considering its future use in giant LArTPCs. The scintillation light production and propagation processes are analyzed and a comparison of simulation to data is performed, improving understanding of the liquid argon properties.</p

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on experimental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation. &nbsp;</p

Hunger in the Land of Plenty: Local Responses to Food Insecurity in Iowa

Story County (estimated population 92,406 in 2013) lies in the heart of central Iowa, a state renowned for its remarkable agricultural productivity. Iowa leads all states for production of corn, soybean, and hogs. Revenues from agricultural products in Iowa total more than $30 billion annually according the 2012 Agricultural Census (USDA-NASS 2014). This productivity stems from a favorable natural and political environment. The temperate climate, productive soils, and gentle topography are ideal for our production system of commodity agriculture facilitated by federal policies, which include subsidized crop insurance and commodity payments (Horrigan, Lawrence, and Walker 2002). Despite this productivity and political support for commodity production, a very small amount of acreage in Iowa produces food crops such as fruits and vegetables. Within Story County, the amount of cropland dedicated to fruit, vegetable, and nut production per one thousand residents is 2.4 acres, compared to 3.7 acres statewide, which is much lower than the US average of 32 acres per one thousand residents (ISUEO 2014). Paradoxically, in this land so perfectly suited for agriculture, there is an increasing demand for food assistance. Iowa State University Extension and Outreach (ISUEO) estimates 16,366 people live in poverty in Story County, a 20.1 percent poverty rate, compared to a statewide average of 12.2 percent (2014). ISUEO further estimates that 15.2 percent of Story County residents are food insecure, representing nearly 14,000 individuals. Comparatively, the statewide rate is 12.7 percent (ISUEO 2014). Compounding the problem, 45 percent of people who are food insecure in Story County do not qualify for direct government assistance because their income is above the economic threshold set for federal food assistance, and so they depend on charitable efforts to meet their needs. According to Feeding America’s statistics, Story County is the most food insecure county in Iowa (Gundersen, Engelhard, and Waxman 2015). The juxtaposition of a productive agricultural system with persistent hunger and need for food assistance is widely apparent in Story County and has inspired community-based efforts to address food needs. Through this chapter, we analyze the work of Food at First (FAF), a nonprofit that has emerged in response to the need for food assistance in Story County. Their work addresses the food needs of Story County residents by providing a daily free meal program and market as well as the recent development of a community garden. We illustrate the benefits of the FAF effort dedicated to building community-based solutions to hunger and food insecurity through a form of food democracy. We also explore key challenges associated with doing this work, including pragmatic issues of retaining and engaging volunteers. Further, we examine limitations of this model by exploring the underlying causes of food insecurity and how this organization contests as well as perpetuates a neoliberal model of food assistance. This neoliberal focus emphasizes individual responsibility and corporate charitable donations rather than collective, and/or government-level, responsibility for community food insecurity. We hope to raise important questions about how this community-driven work critically improves food security and a broader sense of community while still falling short of addressing poverty and inequality, the underlying reason for food insecurity in Ames and across the country

Simulating the WFIRST coronagraph Integral Field Spectrograph

A primary goal of direct imaging techniques is to spectrally characterize the atmospheres of planets around other stars at extremely high contrast levels. To achieve this goal, coronagraphic instruments have favored integral field spectrographs (IFS) as the science cameras to disperse the entire search area at once and obtain spectra at each location, since the planet position is not known a priori. These spectrographs are useful against confusion from speckles and background objects, and can also help in the speckle subtraction and wavefront control stages of the coronagraphic observation. We present a software package, the Coronagraph and Rapid Imaging Spectrograph in Python (crispy) to simulate the IFS of the WFIRST Coronagraph Instrument (CGI). The software propagates input science cubes using spatially and spectrally resolved coronagraphic focal plane cubes, transforms them into IFS detector maps and ultimately reconstructs the spatio-spectral input scene as a 3D datacube. Simulated IFS cubes can be used to test data extraction techniques, refine sensitivity analyses and carry out design trade studies of the flight CGI-IFS instrument. crispy is a publicly available Python package and can be adapted to other IFS designs.Comment: 15 page

Constraining mass ratio and extinction in the FU Orionis binary system with infrared integral field spectroscopy

We report low resolution near infrared spectroscopic observations of the eruptive star FU Orionis using the Integral Field Spectrograph Project 1640 installed at the Palomar Hale telescope. This work focuses on elucidating the nature of the faint source, located 0.5" south of FU Ori, and identified in 2003 as FU Ori S. We first use our observations in conjunction with published data to demonstrate that the two stars are indeed physically associated and form a true binary pair. We then proceed to extract J and H band spectro-photometry using the damped LOCI algorithm, a reduction method tailored for high contrast science with IFS. This is the first communication reporting the high accuracy of this technique, pioneered by the Project 1640 team, on a faint astronomical source. We use our low resolution near infrared spectrum in conjunction with 10.2 micron interferometric data to constrain the infrared excess of FU Ori S. We then focus on estimating the bulk physical properties of FU Ori S. Our models lead to estimates of an object heavily reddened, A_V =8-12, with an effective temperature of ~ 4000-6500 K . Finally we put these results in the context of the FU Ori N-S system and argue that our analysis provides evidence that FU Ori S might be the more massive component of this binary syste

The IFS for WFIRST CGI: Science Requirements to Design

Direct Imaging of exoplanets using a coronagraph has become a major field of research both on the ground and in space. Key to the science of direct imaging is the spectroscopic capabilities of the instrument, our ability to extract spectra, and measure the abundance of molecular species such as Methane. To take these spectra, the WFIRST coronagraph instrument (CGI) uses an integral field spectrograph (IFS), which encodes the spectrum into a two-dimensional image on the detector. This results in more efficient detection and characterization of targets, and the spectral information is critical to achieving detection limits below the speckle floor of the imager. The CGI IFS operates in two18% bands spanning 600nm to 840nm at a nominal spectral resolution of R50. We present the current science and engineering requirements for the IFS design, the instrument design, anticipated performance, and how the calibration is integrated into the focal plane wavefront control algorithms. We also highlight the role of the Prototype Imaging Spectrograph for Coronagraphic Exoplanet Studies (PISCES) at the JPL High Contrast Imaging Testbed to demonstrate performance and validate calibration methodologies for the flight instrument

Multicolor Monitoring of Dysregulated Protein Kinases in Chronic Myelogenous Leukemia

The Bcr-Abl and Lyn protein tyrosine kinases have been separately linked to the emergence of imatinib resistance in patients with chronic myelogenous leukemia. We have developed fluorescent sensors for these kinases that are enzymatically and photophysically distinct, allowing us to simultaneously, yet separately, visualize the tyrosine kinase activities of both Abl and Lyn. Multicolor monitoring revealed that an imatinib resistant cell line (MYL-R) displays a remarkable 13-fold enhancement in Lyn kinase activity relative to its imatinib sensitive counterpart (MYL). By contrast, both cell lines display nearly identical Abl activities. The upregulation of Lyn kinase phosphotransferase activity in MYL-R cells is linked to an overexpression of the Lyn B isoform. Furthermore, MYL-R cells possess a 4-fold higher level of activated Lyn and 5-fold lower level of autoinhibited Lyn than MYL cells. Furthermore, studies with an activating SH2 ligand revealed that Lyn from imatinib-resistant MYL-R cells is primed and active, whereas Lyn from imatinib-sensitive cells is dependent upon phosphorylated SH2 ligands for activity

Further Development of Verification Check-Cases for Six- Degree-of-Freedom Flight Vehicle Simulations

This follow-on paper describes the principal methods of implementing, and documents the results of exercising, a set of six-degree-of-freedom rigid-body equations of motion and planetary geodetic, gravitation and atmospheric models for simple vehicles in a variety of endo- and exo-atmospheric conditions with various NASA, and one popular open-source, engineering simulation tools. This effort is intended to provide an additional means of verification of flight simulations. The models used in this comparison, as well as the resulting time-history trajectory data, are available electronically for persons and organizations wishing to compare their flight simulation implementations of the same models