Destiny: A Candidate Architecture for the Joint Dark Energy Mission

Destiny is a simple, direct, low cost mission to determine the properties of dark energy by obtaining a cosmologically deep supernova (SN) type Ia Hubble diagram. Operated at L2, its science instrument is a 1.65m space telescope, featuring a grism-fed near-infrared (NIR) (0.85-1.7micron) survey camera/spectrometer with a 0.12 square degree field of view. During its two-year primary mission, Destiny will detect, observe, and characterize ~3000 SN Ia events over the redshift interval 0.4<z<1.7 within a 3 square degree survey area. In conjunction with ongoing ground-based SN Ia surveys for z<0.8, Destiny mission data will be used to construct a high-precision Hubble diagram and thereby constrain the dark energy equation of state from a time when it was strongly matter-dominated to the present when dark energy dominates. The grism-images simultaneously provide broad-band photometry, redshifts, and SN classification, as well as time-resolved diagnostic data for investigating additional SN luminosity diagnostics. Destiny will be used in its third year as a high resolution, wide-field imager to conduct a multicolor NIR weak lensing (WL) survey covering 1000 square degrees. The large-scale mass power spectrum derived from weak lensing distortions of field galaxies as a function of redshift will provide independent and complementary constraints on the dark energy equation of state. The combination of SN and WL is much more powerful than either technique on its own. Used together, these surveys will have more than an order of magnitude greater sensitivity than will be provided by ongoing ground-based projects. The dark energy parameters, w_0 and w_a, will be measured to a precision of 0.05 and 0.2 respectively.Comment: Contains full color figure

Wide-Field InfraRed Survey Telescope (WFIRST) Final Report

In December 2010, NASA created a Science Definition Team (SDT) for WFIRST, the Wide Field Infra-Red Survey Telescope, recommended by the Astro 2010 Decadal Survey as the highest priority for a large space mission. The SDT was chartered to work with the WFIRST Project Office at GSFC and the Program Office at JPL to produce a Design Reference Mission (DRM) for WFIRST. Part of the original charge was to produce an interim design reference mission by mid-2011. That document was delivered to NASA and widely circulated within the astronomical community. In late 2011 the Astrophysics Division augmented its original charge, asking for two design reference missions. The first of these, DRM1, was to be a finalized version of the interim DRM, reducing overall mission costs where possible. The second of these, DRM2, was to identify and eliminate capabilities that overlapped with those of NASA's James Webb Space Telescope (henceforth JWST), ESA's Euclid mission, and the NSF's ground-based Large Synoptic Survey Telescope (henceforth LSST), and again to reduce overall mission cost, while staying faithful to NWNH. This report presents both DRM1 and DRM2.Comment: 102 pages, 57 figures, 17 table

Blip-Up Blip-Down Circular EPI (BUDA-cEPI) for Distortion-Free dMRI with Rapid Unrolled Deep Learning Reconstruction

Purpose: We implemented the blip-up, blip-down circular echo planar imaging (BUDA-cEPI) sequence with readout and phase partial Fourier to reduced off-resonance effect and T2* blurring. BUDA-cEPI reconstruction with S-based low-rank modeling of local k-space neighborhoods (S-LORAKS) is shown to be effective at reconstructing the highly under-sampled BUDA-cEPI data, but it is computationally intensive. Thus, we developed an ML-based reconstruction technique termed "BUDA-cEPI RUN-UP" to enable fast reconstruction. Methods: BUDA-cEPI RUN-UP - a model-based framework that incorporates off-resonance and eddy current effects was unrolled through an artificial neural network with only six gradient updates. The unrolled network alternates between data consistency (i.e., forward BUDA-cEPI and its adjoint) and regularization steps where U-Net plays a role as the regularizer. To handle the partial Fourier effect, the virtual coil concept was also incorporated into the reconstruction to effectively take advantage of the smooth phase prior, and trained to predict the ground-truth images obtained by BUDA-cEPI with S-LORAKS. Results: BUDA-cEPI with S-LORAKS reconstruction enabled the management of off-resonance, partial Fourier, and residual aliasing artifacts. However, the reconstruction time is approximately 225 seconds per slice, which may not be practical in a clinical setting. In contrast, the proposed BUDA-cEPI RUN-UP yielded similar results to BUDA-cEPI with S-LORAKS, with less than a 5% normalized root mean square error detected, while the reconstruction time is approximately 3 seconds. Conclusion: BUDA-cEPI RUN-UP was shown to reduce the reconstruction time by ~88x when compared to the state-of-the-art technique, while preserving imaging details as demonstrated through DTI application.Comment: Number: Figures: 8 Tables: 3 References: 7

The Whole is Greater than the Sum of the Parts: Optimizing the Joint Science Return from LSST, Euclid and WFIRST

The focus of this report is on the opportunities enabled by the combination of LSST, Euclid and WFIRST, the optical surveys that will be an essential part of the next decade's astronomy. The sum of these surveys has the potential to be significantly greater than the contributions of the individual parts. As is detailed in this report, the combination of these surveys should give us multi-wavelength high-resolution images of galaxies and broadband data covering much of the stellar energy spectrum. These stellar and galactic data have the potential of yielding new insights into topics ranging from the formation history of the Milky Way to the mass of the neutrino. However, enabling the astronomy community to fully exploit this multi-instrument data set is a challenging technical task: for much of the science, we will need to combine the photometry across multiple wavelengths with varying spectral and spatial resolution. We identify some of the key science enabled by the combined surveys and the key technical challenges in achieving the synergies.Comment: Whitepaper developed at June 2014 U. Penn Workshop; 28 pages, 3 figure

Report by the ESA-ESO Working Group on Fundamental Cosmology

ESO and ESA agreed to establish a number of Working Groups to explore possible synergies between these two major European astronomical institutions. This Working Group's mandate was to concentrate on fundamental questions in cosmology, and the scope for tackling these in Europe over the next ~15 years. One major resulting recommendation concerns the provision of new generations of imaging survey, where the image quality and near-IR sensitivity that can be attained only in space are naturally matched by ground-based imaging and spectroscopy to yield massive datasets with well-understood photometric redshifts (photo-z's). Such information is essential for a range of new cosmological tests using gravitational lensing, large-scale structure, clusters of galaxies, and supernovae. Great scope in future cosmology also exists for ELT studies of the intergalactic medium and space-based studies of the CMB and gravitational waves; here the synergy is less direct, but these areas will remain of the highest mutual interest to the agencies. All these recommended facilities will produce vast datasets of general applicability, which will have a tremendous impact on broad areas of astronomy.Comment: ESA-ESO Working Groups Report No. 3, 125 pages, 28 figures. A PDF version including the cover is available from http://www.stecf.org/coordination/esa_eso/cosmology/report_cover.pdf and a printed version (A5 booklet) is available in limited numbers from the Space Telescope-European Coordinating Facility (ST-ECF): [email protected]

Adaption in Dynamic Contrast-Enhanced MRI

In breast DCE MRI, dynamic data are acquired to assess signal changes caused by contrast agent injection in order to classify lesions. Two approaches are used for data analysis. One is to fit a pharmacokinetic model, such as the Tofts model, to the data, providing physiological information. For accurate model fitting, fast sampling is needed. Another approach is to evaluate architectural features of the contrast agent distribution, for which high spatial resolution is indispensable. However, high temporal and spatial resolution are opposing aims and a compromise has to be found. A new area of research are adaptive schemes, which sample data at combined resolutions to yield both, accurate model fitting and high spatial resolution morphological information. In this work, adaptive sampling schemes were investigated with the objective to optimize fitting accuracy, whilst providing high spatial resolution images. First, optimal sampling design was applied to the Tofts model. By that it could be determined, based on an assumed parameter distribution, that time points during the onset and the initial fast kinetics, lasting for approximately two minutes, are most relevant for fitting. During this interval, fast sampling is required. Later time points during wash-out can be exploited for high spatial resolution images. To achieve fast sampling during the initial kinetics, data acquisition has to be accelerated. A common way to increase imaging speed is to use view-sharing methods, which omit certain k-space data and interpolate the missing data from neighboring time frames. In this work, based on phantom simulations, the influence of different view-sharing techniques during the initial kinetics on fitting accuracy was investigated. It was found that all view-sharing methods imposed characteristic systematic errors on the fitting results of Ktrans. The best fitting performance was achieved by the scheme ``modTRICKS'', which is a combination of the often used schemes keyhole and TRICKS. It is not known prior to imaging, when the contrast agent will arrive in the lesion or when the wash-out begins. Currently used adaptive sequences change resolutions a fixed time points. However, missing time points on the upslope may cause fitting errors and missing the signal peak may lead to a loss in morphological information. This problem was addressed with a new automatic resolution adaption (AURA) sequence. Acquired dynamic data were analyzed in real-time to find the onset and the beginning of the wash-out and consequently the temporal resolution was automatically adapted. Using a perfusion phantom it could be shown that AURA provides both, high fitting accuracy and reliably high spatial resolution images close to the signal peak. As alternative approach to AURA, a sequence which allows for retrospective resolution adaption, was assesses. Advantages are that adaption does not have to be a global process, and can be tailored regionally to local sampling requirements. This can be useful for heterogeneous lesions. For that, a 3D golden angle radial sequence was used, which acquires contrast information with each line and the golden angles allow arbitrary resolutions at arbitrary time points. Using a perfusion phantom, it could be shown that retrospective resolution adaption yields high fitting accuracy and relatively high spatial resolution maps