The Q/U Imaging ExperimenT (QUIET) has observed the cosmic microwave background (CMB) at 43 and 95 GHz. The 43 GHz results have been published in a previous paper, and here we report the measurement of CMB polarization power spectra using the 95 GHz data. This data set comprises 5337 hr of observations recorded by an array of 84 polarized coherent receivers with a total array sensitivity of 87 μK √ s. Four low-foreground fields were observed, covering a total of ∼1000 deg 2 with an effective angular resolution of 12. 8, allowing for constraints on primordial gravitational waves and high signal-to-noise measurements of the E-modes across three acoustic peaks. The data reduction was performed using two independent analysis pipelines, one based on a pseudo-C (PCL) cross-correlation approach, and the other on a maximum-likelihood (ML) approach. All data selection criteria and filters were modified until a predefined set of null tests had been satisfied before inspecting any non-null power spectrum. The results derived by the two pipelines are in good agreement. We characterize the EE, EB, and BB power spectra between = 25 and 975 and find that the EE spectrum is consistent with ΛCDM, while the BB power spectrum is consistent with zero. Based on these measurements, we constrain the tensor-to-scalar ratio to r = 1.1 +0.9 −0.8 (r < 2.8 at 95% C.L.) as derived by the ML pipeline, and r = 1.2 +0.9 −0.8 (r < 2.7 at 95% C.L.) as derived by the PCL pipeline. In one of the fields, we find a correlation with the dust component of the Planck Sky Model, though the corresponding excess power is small compared to statistical errors. Finally, we derive limits on all known systematic errors, and demonstrate that these correspond to a tensor-to-scalar ratio smaller than r = 0.01, the lowest level yet reported in the literature.

The Q/U Imaging ExperimenT (QUIET) is designed to measure polarization in the cosmic microwave background, targeting the imprint of inflationary gravitational waves at large angular scales(∼1 • ). Between 2008 October and 2010 December, two independent receiver arrays were deployed sequentially on a 1.4 m side-fed Dragonian telescope. The polarimeters that form the focal planes use a compact design based on high electron mobility transistors (HEMTs) that provides simultaneous measurements of the Stokes parameters Q, U, and I in a single module. The 17-element Q-band polarimeter array, with a central frequency of 43.1 GHz, has the best sensitivity (69 μKs 1/2 ) and the lowest instrumental systematic errors ever achieved in this band, contributing to the tensor-to-scalar ratio at r < 0.1. The 84-element W-band polarimeter array has a sensitivity of 87 μKs 1/2 at a central frequency of 94.5 GHz. It has the lowest systematic errors to date, contributing at r < 0.01. The two arrays together cover multipoles in the range ∼ 25-975. These are the largest HEMT-based arrays deployed to date. This article describes the design, calibration, performance, and sources of systematic error of the instrument.

The Q/U Imaging ExperimenT (QUIET) employs coherent receivers at 43 GHz and 94 GHz, operating on the Chajnantor plateau in the Atacama Desert in Chile, to measure the anisotropy in the polarization of the cosmic microwave background (CMB). QUIET primarily targets the B modes from primordial gravitational waves. The combination of these frequencies gives sensitivity to foreground contributions from diffuse Galactic synchrotron radiation. Between 2008 October and 2010 December, over 10,000 hr of data were collected, first with the 19 element 43 GHz array (3458 hr) and then with the 90 element 94 GHz array. Each array observes the same four fields, selected for low foregrounds, together covering ≈1000 deg 2 . This paper reports initial results from the 43 GHz receiver, which has an array sensitivity to CMB fluctuations of 69 μK √ s. The data were extensively studied with a large suite of null tests before the power spectra, determined with two independent pipelines, were examined. Analysis choices, including data selection, were modified until the null tests passed. Cross-correlating maps with different telescope pointings is used to eliminate a bias. This paper reports the EE, BB, and EB power spectra in the multipole range = 25-475. With the exception of the lowest multipole bin for one of the fields, where a polarized foreground, consistent with Galactic synchrotron radiation, is detected with 3σ significance, the E-mode spectrum is consistent with the ΛCDM model, confirming the only previous detection of the first acoustic peak. The B-mode spectrum is consistent with zero, leading to a measurement of the tensor-to-scalar ratio of r = 0.35 +1.06 −0.87 . The combination of a new time-stream "double-demodulation" technique, side-fed Dragonian optics, natural sky rotation, and frequent boresight rotation leads to the lowest level of systematic contamination in the B-mode power so far reported, below the level of r = 0.1.

B-modes in the cosmic microwave background (CMB) polarization is a smoking gun signature of the inflationary universe. To achieve better sensitivity to this faint signal, CMB polarization experiments aim to maximize the number of detector elements, resulting in a large focal plane receiver. Detector calibration of the polarization response becomes essential. It is extremely useful to be able to calibrate "simultaneously" all detectors on the large focal plane. We developed a novel calibration system that rotates a large "sparse" grid of metal wires, in front of and fully covering the field of view of the focal plane receiver. Polarized radiation is created via the reflection of ambient temperature from the wire surface. Since the detector has a finite beam size, the observed signal is smeared according to the beam property. The resulting smeared polarized radiation has a reasonable intensity (a few Kelvin or less) compared to the sky temperature (∼10 K observing condition). The system played a successful role for receiver calibration of QUIET, a CMB polarization experiment located in the Atacama desert in Chile. The successful performance revealed that this system is applicable to other experiments based on different technologies, e.g. TES bolometers.

Summary Progress in sustainability science is hindered by challenges in creating and managing complex data acquisition, processing, simulation, post‐processing, and intercomparison pipelines. To address these challenges, we developed the Framework to Advance Climate, Economic, and Impact Investigations with Information Technology (FACE‐IT) for crop and climate impact assessments. This integrated data processing and simulation framework enables data ingest from geospatial archives; data regridding, aggregation, and other processing prior to simulation; large‐scale climate impact simulations with agricultural and other models, leveraging high‐performance and cloud computing; and post‐processing to produce aggregated yields and ensemble variables needed for statistics, for model intercomparison, and to connect biophysical models to global and regional economic models. FACE‐IT leverages the capabilities of the Globus Galaxies platform to enable the capture of workflows and outputs in well‐defined, reusable, and comparable forms. We describe FACE‐IT and applications within the Agricultural Model Intercomparison and Improvement Project and the Center for Robust Decision‐making on Climate and Energy Policy. Copyright © 2015 John Wiley & Sons, Ltd.

Accurate prediction of trends in marine pollution is strategic, given the negative effects of low water quality on human marine activities. We describe here the computational and functional performance evaluation of a decision making tool that we developed in the context of an operational workflow for food quality forecast and assessment. Our Water Community Model (WaComM) uses a particle-based Lagrangian approach relying on tridimensional marine dynamics field produced by coupled Eulerian atmosphere and ocean models. WaComM has been developed matching the hierarchical parallelization design requirements and tested in Intel X86-64 and IBM P8 multi core environments and integrated in FACE-IT Galaxy workflow. The predicted pollutant concentration and the amount of pollutants accumulated in the sampled mussels are compared in search of coherent trends to prove the correct model behaviour. In the case study shown in this paper, the predicted Lagrangian tracers, acting as pollutant concentration surrogates, tend to spread rapidly and undergo rapid dilution as expected depending on dominant water column integrated currents

Sensors incorporated into mobile devices provide unique opportunities to capture detailed environmental information that cannot be readily collected in other ways. We show here how data from networked navigational sensors on leisure vessels can be used to construct unique new datasets, using the example of underwater topography (bathymetry) to demonstrate the approach. Specifically, we describe an end-to-end workflow that involves the collection of large numbers of timestamped (position, depth) measurements from "internet of floating things" devices on leisure vessels; the communication of data to cloud resources, via a specialized protocol capable of dealing with delayed, intermittent, or even disconnected networks; the integration of measurement data into cloud storage; the efficient correction and interpolation of measurements on a cloud computing platform; and the creation of a continuously updated bathymetric database. Our prototype implementation of this workflow leverages the FACE-IT Galaxy workflow engine to integrate network communication and database components with a CUDA-enabled algorithm running in a virtualized cloud environment

Nowadays fishes and mussels farming is very important, from an economical point of view, for the local social background of the Bay of Naples. Hence, the accurate forecast of marine pollution becomes crucial to have reliable evaluation of its adverse effects on coastal inhabitants' health. The use of connected smart devices for monitoring the sea water pollution is getting harder because of the saline environment, the network availability and the maintain and calibration costs2. To this purpose, we designed and implemented WaComM (Water Community Model), a community open source model for sea pollutants transport and dispersion. WaComM is a model component of a scientific workflow which allows to perform, on a dedicated computational infrastructure, numerical simulations providing spatial and temporal high-resolution predictions of weather and marine conditions of the Bay of Naples leveraging on the cloud based31FACE-IT workflow engine27. In this paper we present some remarks about the development of WaComM, using hierarchical parallelism which implies distributed memory, shared memory and GPGPUs. Some numerical details are also discussed. Peer-review under responsibility of the Conference Program Chairs