Report from the Tri-Agency Cosmological Simulation Task Force

The Tri-Agency Cosmological Simulations (TACS) Task Force was formed when Program Managers from the Department of Energy (DOE), the National Aeronautics and Space Administration (NASA), and the National Science Foundation (NSF) expressed an interest in receiving input into the cosmological simulations landscape related to the upcoming DOE/NSF Vera Rubin Observatory (Rubin), NASA/ESA's Euclid, and NASA's Wide Field Infrared Survey Telescope (WFIRST). The Co-Chairs of TACS, Katrin Heitmann and Alina Kiessling, invited community scientists from the USA and Europe who are each subject matter experts and are also members of one or more of the surveys to contribute. The following report represents the input from TACS that was delivered to the Agencies in December 2018.Comment: 36 pages, 3 figures. Delivered to NASA, NSF, and DOE in Dec 201

Intrinsic alignments of galaxies in the Horizon-AGN cosmological hydrodynamical simulation

The intrinsic alignments of galaxies are recognised as a contaminant to weak gravitational lensing measurements. In this work, we study the alignment of galaxy shapes and spins at low redshift ($z\sim 0.5$) in Horizon-AGN, an adaptive-mesh-refinement hydrodynamical cosmological simulation box of 100 Mpc/h a side with AGN feedback implementation. We find that spheroidal galaxies in the simulation show a tendency to be aligned radially towards over-densities in the dark matter density field and other spheroidals. This trend is in agreement with observations, but the amplitude of the signal depends strongly on how shapes are measured and how galaxies are selected in the simulation. Disc galaxies show a tendency to be oriented tangentially around spheroidals in three-dimensions. While this signal seems suppressed in projection, this does not guarantee that disc alignments can be safely ignored in future weak lensing surveys. The shape alignments of luminous galaxies in Horizon-AGN are in agreement with observations and other simulation works, but we find less alignment for lower luminosity populations. We also characterize the systematics of galaxy shapes in the simulation and show that they can be safely neglected when measuring the correlation of the density field and galaxy ellipticities.Comment: 20 pages, 23 figure

Intrinsic galaxy shapes and alignments I: Measuring and modelling COSMOS intrinsic galaxy ellipticities

The statistical properties of the ellipticities of galaxy images depend on how galaxies form and evolve, and therefore constrain models of galaxy morphology, which are key to the removal of the intrinsic alignment contamination of cosmological weak lensing surveys, as well as to the calibration of weak lensing shape measurements. We construct such models based on the halo properties of the Millennium Simulation and confront them with a sample of 90,000 galaxies from the COSMOS Survey, covering three decades in luminosity and redshifts out to z=2. The ellipticity measurements are corrected for effects of point spread function smearing, spurious image distortions, and measurement noise. Dividing galaxies into early, late, and irregular types, we find that early-type galaxies have up to a factor of two lower intrinsic ellipticity dispersion than late-type galaxies. None of the samples shows evidence for redshift evolution, while the ellipticity dispersion for late-type galaxies scales strongly with absolute magnitude at the bright end. The simulation-based models reproduce the main characteristics of the intrinsic ellipticity distributions although which model fares best depends on the selection criteria of the galaxy sample. We observe fewer close-to-circular late-type galaxy images in COSMOS than expected for a sample of randomly oriented circular thick disks and discuss possible explanations for this deficit.Comment: 18 pages, 8 figures; updated simulations and galaxy sample definition, more galaxy samples analysed; matches version published in MNRA

Incorporating peak grouping information for alignment of multiple liquid chromatography-mass spectrometry datasets

Motivation: The combination of liquid chromatography and mass spectrometry (LC/MS) has been widely used for large-scale comparative studies in systems biology, including proteomics, glycomics and metabolomics. In almost all experimental design, it is necessary to compare chromatograms across biological or technical replicates and across sample groups. Central to this is the peak alignment step, which is one of the most important but challenging preprocessing steps. Existing alignment tools do not take into account the structural dependencies between related peaks that co-elute and are derived from the same metabolite or peptide. We propose a direct matching peak alignment method for LC/MS data that incorporates related peaks information (within each LC/MS run) and investigate its effect on alignment performance (across runs). The groupings of related peaks necessary for our method can be obtained from any peak clustering method and are built into a pairwise peak similarity score function. The similarity score matrix produced is used by an approximation algorithm for the weighted matching problem to produce the actual alignment result.<p></p> Results: We demonstrate that related peak information can improve alignment performance. The performance is evaluated on a set of benchmark datasets, where our method performs competitively compared to other popular alignment tools.<p></p> Availability: The proposed alignment method has been implemented as a stand-alone application in Python, available for download at http://github.com/joewandy/peak-grouping-alignment.<p></p&gt