Chris Hirata (Ohio State University)

Aug. 25, 2022, 2:00pm (ET)

Calibrating infrared detectors for precision cosmology

Modern weak gravitational lensing surveys have used the shape correlations of distant galaxies to infer the growth rate of cosmic structure with unprecedented precision. As we look forward to next-generation surveys, this precision must be matched by an improved treatment of systematic uncertainties from both astrophysical and observational effects. One category of observational systematics is how detector effects — that our detectors are not ideal devices that count photons in each square pixel — impact galaxy shape measurement. I will describe recent and ongoing efforts to characterize the infrared detectors for the Nancy Grace Roman Space Telescope. The infrared detectors have several effects that are familiar from visible CCD surveys, such as the “brighter-fatter” effect and pixel-to-pixel area variations, but also some new features such as capacitive cross-talk. On the other hand, the infrared detectors can be non-destructively read, which provides new opportunities to use correlations in test data to distinguish different  detector effects. I will conclude with a view forward to how the Roman detector measurements can be incorporated into weak lensing analyses.

Justin Pierel (STScI)

June 02, 2022, 2:00 PM (ET)

Cosmological Tensions in the Era of Next Generation Telescopes

Type Ia Supernovae (SNe Ia) have been the source of many astronomical discoveries over the past several decades, perhaps most prominently the accelerated expansion of the universe by so-called “dark energy” in 1998. Today, our most precise cosmological measurements from SNe Ia in the local universe have diverged significantly from the predictions of our most successful cosmological model (ΛCDM). Upcoming surveys from the Vera C. Rubin Observatory and Nancy G. Roman Space Telescope will attempt to unravel the mysteries of dark energy, increasing our SN Ia sample by orders of magnitude. In order to fully leverage this new wealth of information, we must find new innovations for understanding and mitigating systematic uncertainties in cosmological measurements. I will discuss a series of efforts designed to reduce various systematics associated with SNIa standardization, as well as the promise of near-infrared observations provided by Roman. In addition to these traditional luminosity distance measurements, I will highlight a relatively new means of leveraging SNe for cosmology: gravitational lensing. The new era of next generation telescopes will truly enable these fully independent probes for cosmology, which provide a critical check on SNe Ia and unique constraints on dark energy, as we attempt to resolve the age of cosmological tensions. Weak lensing measurements by the Dark Energy Survey (DES) and the new generation of wide field galaxy surveys offer an exciting window on the properties and laws of the Universe. I will describe our approach to constrain non-standard cosmological models with the latest DES weak lensing data, especially focusing on tests of gravity on cosmological scales. I will then give my perspective on the lessons learnt and challenges for future tests, especially with the Rubin Observatory. I will end by presenting a new approach I propose to overcome one of these challenges and maximise the potential for discovery of new physics in the coming decade.

Agnès Ferté (Jet Propulsion Laboratory)

April 14, 2022, 2:00 PM (EST)

Tests of gravity with weak lensing surveys

Weak lensing measurements by the Dark Energy Survey (DES) and the new generation of wide field galaxy surveys offer an exciting window on the properties and laws of the Universe. I will describe our approach to constrain non-standard cosmological models with the latest DES weak lensing data, especially focusing on tests of gravity on cosmological scales. I will then give my perspective on the lessons learnt and challenges for future tests, especially with the Rubin Observatory. I will end by presenting a new approach I propose to overcome one of these challenges and maximise the potential for discovery of new physics in the coming decade.

Peter Taylor (Jet Propulsion Laboratory)

October 28, 2021, 2:00 PM (EST)

The RSD Sorting Hat

Redshift-space distortions (RSD) and weak lensing (WL) studies yield some of the tightest cosmological constraints. Large overlapping data sets from Euclid, the Rubin Observatory, the Roman Space Science Telescope and the Dark Energy Spectroscopic Instruments will enable a joint RSD/WL analysis. Such an analysis could significantly outperform WL and RSD analyses performed in isolation. In this talk I show how to optimally extract information from the RSD signal using angular statistics. This is a first step towards combing WL and RSD.

Charlotte Wood (University of Notre Dame)

October 21, 2021, 2:00 PM (EST)

Testing the Top Rung of the Distance Ladder: Comparing H_0 Using Cepheid Distances vs. SBF Distances

While type Ia supernovae are powerful tools for measuring the Hubble constant, they are not perfectly standard candles and require corrections to make them standard. We aim to constrain the systematic uncertainties on estimations of the Hubble constant due to type Ia supernova variations by comparing type Ia supernovae with distances calibrated through infrared surface brightness fluctuations (which target supernovae in older, elliptical galaxies) and supernovae with distances calibrated through Cepheid variables (which target supernovae in younger, spiral galaxies). The two populations of supernovae are quite different observationally, so we re-estimate the Hubble constant using different subsamples of the supernovae (e.g, only those in Cepheid-calibrated galaxies or only those in SBF-calibrated galaxies) and look at how different the values can be.

Carlos Correa (IATE, Universidad Nacional de Córdoba)

August 19, 2021, 2:00 PM (EST)

Cosmic voids as cosmological laboratories

In this seminar, I will talk about the main results of my PhD research about cosmic voids and their application to Cosmology. Voids are promising cosmological probes for testing the dark energy problem and alternative gravity theories. Since they are the largest observable structures, they encode key information about the geometry and expansion history of the Universe. Furthermore, the potential of voids has been increased recently with the development of modern spectroscopic surveys, such as BOSS, eBOSS, DESI, HETDEX and Euclid, which will cover a volume and a redshift range without precedents. Two of the most important cosmological statistics in void studies are: (i) the void size function, which describes the abundance of voids in the Universe, and (ii) the void-galaxy cross-correlation function, which characterises the density and peculiar velocity fields around them. In the first part of the talk, I will give an introduction on this topic.

In the second part, I will explain a new cosmological test based on the void-galaxy cross-correlation function that we have developed. The methodology introduces three novel aspects: (i) the test is based on two perpendicular projections of the correlation function with respect to the line of sight, (ii) it is fiducial-cosmology free, and (iii) our model reproduces the observed distortion patterns due to the coupled Kaiser (dynamical) and Alcock-Paczynski (geometrical) effects, as well as the scale-mixing effect due to the binning scheme used in the measurements process.

Finally, in the third part, I will address an important issue that has prevented the correct application of tests based on voids to observational data: our picture of redshift-space distortions around voids is incomplete. Traditionally, we have only focused on how they affect the spatial distribution of tracers. The truth is that they also affect intrinsic void properties, such as their number, size and spatial distribution. This is a source of additional distortion patterns that lead to biased cosmological constraints if they are not treated properly.

Kyle Boone (eScience Institue, University of Washington)

August 3, 2021, 2:00 PM (EST)

Modeling supernova light curves with physics-enabled deep learning

Upcoming cosmological surveys such as the LSST at the Rubin Observatory will discover millions of supernovae and other transients. To take advantage of these large datasets, we have developed a deep generative model of transient light curves. Our model combines deep learning to model the unknown physics of the sources with an explicit physics model of how light propagates through the universe and is observed on a detector. I’ll discuss several applications of such a model, including classification of transients, identifying new kinds of transients, and how to perform supernova cosmology without classification.

Anna Porredon (The Ohio State University)

July 15, 2021, 2:00 PM (EST)

Lens sample optimization for multi-probe cosmological analyses

The cosmological information extracted from photometric surveys is most robust when multiple probes of the large-scale structure of the universe are used. Two of the most sensitive probes are galaxy clustering and the tangential shear of background galaxy shapes produced by foreground (or lens) galaxies, so-called galaxy-galaxy lensing. The optimal choice of lens galaxies is governed by the joint but conflicting requirements to obtain accurate redshift information and large statistics. I will show how we optimized the selection of one of the lens samples in the Dark Energy Survey Year 3 analysis and the resulting cosmological constraints from the combination of galaxy clustering and galaxy-galaxy lensing. I will also discuss the application of such optimization to the Euclid survey.

David Kirkby (University of California, Irvine)

June 17, 2021, 2:00 PM (EST)

Towards Dark Energy: The Dark Energy Spectroscopic Instrument (DESI) in five questions

The Dark Energy Spectroscopic Instrument (DESI) is the first of a new generation of cosmology surveys designed to provide a more precise understanding of cosmic acceleration.  DESI achieved first light in October 2019, followed by a lengthy COVID shutdown, and just began its five-year survey on May 14.  During this colloquium, we will discuss some of the challenges DESI faces to deliver a uniform dataset on schedule, and strategies we have developed to address these challenges.

Judit Prat (U of Chicago, KICP)

April 8, 2021, 2:00 PM (EST)

Galaxy-galaxy lensing and Lensing Ratios for Cosmological Analyses

Galaxy cosmic surveys are a powerful tool to extract cosmological information. In particular, the combination of weak lensing and galaxy clustering measurements, usually known as 3x2pt, provides a potent and robust way to constrain the parameters controlling the structure formation in the late Universe. Galaxy-galaxy lensing, which is the cross-correlation of the shapes of source background galaxies with lens foreground galaxy positions, is one of the three probes that is part of this combination. In this talk, I will describe how we can accurately measure and model galaxy-galaxy lensing correlations using the well-understood large scales with the purpose of extracting cosmological information. Besides this, I will also describe how we can construct suitable ratios of these measurements to exploit the otherwise usually disregarded small-scale information and naturally integrate it as a part of the 3x2pt analysis. 

François Lanusse (CNRS) 

March 25, 2021, 2:00 PM (EST)

Merging deep learning with physical models for the analysis of modern cosmological surveys

The upcoming generation of cosmological surveys such as LSST will aim to map the Universe in great detail and on an unprecedented scale. This of course implies new and outstanding challenges at all levels of the scientific analysis, from pixel level data reduction to cosmological inference. In this talk, I will illustrate how recent advances in deep learning and associated automatic differentiation frameworks, can help us tackle these challenges and rethink our approach to data analysis for cosmological surveys. We will see how at the pixel level, combining physical models of the instrument (which account for noise/PSF) with deep generative models (which account for complex galaxy morphologies) can allow us to solve a number of astronomical inverse problems ranging from deconvolution to deblending galaxy images. At the intermediate level of estimating gravitational lensing maps, I will present our recent work on combining analytic theoretical priors with simulation-driven deep learning priors, in order to solve the challenging dark matter mass-mapping inversion problem, and sample from its full posterior. Finally, at the cosmological analysis level, I will present our efforts to implement N-body simulations directly in TensorFlow, opening the door to a range of novel and efficient inference techniques, and allowing for fast hybrid physical/ml simulations.

Erfan Nourbakhsh (UC Davis)

March 4, 2021,  2:00 PM (EST)

Galaxy blending effects in deep imaging probes of cosmology

I examine the systematic error in cosmological probes introduced by galaxy-galaxy blends in deep imaging surveys such as LSST. I simulate blending using a mock catalog of galaxies which includes weak gravitational lensing effects by modifying it to emulate ground based seeing along with the systematics that arises from imperfect detection of overlapping galaxies. With galaxy positions and shears, I compute shear-shear correlation functions after slicing the sample into tomographic redshift bins, using them as three dimensional probes to study the science impact of two dimensional blending. I then investigate the sensitivity of the cosmological parameter estimation to blending and the systematics evolution.

Ross Cawthon (University of Wisconsin-Madison)

February 25, 2021,  2:00 PM (EST)

Calibrating Photometric Redshifts for Cosmic Surveys

Cosmic surveys like the Dark Energy Survey (DES) and the upcoming Rubin Observatory Legacy Survey of Space and Time (LSST) observe hundreds of millions to billions of galaxies. These large surveys help us study the composition and history of the Universe as well as the properties of dark matter, dark energy, gravity, and potentially new physics. A major limitation to these surveys is redshift accuracy. These large imaging surveys attempt to get redshift information from just a few color bands, rather than full spectra. I will discuss three major classes of techniques to get redshift information in these surveys: photometric redshifts, which use color information, clustering redshifts, which use spatial information, and 'self-calibration' techniques, which infer redshifts from typical cosmological measurements like galaxy clustering and galaxy-galaxy lensing. I will highlight recent work in DES.

Kimmy Wu (SLAC)

December 10, 2020,  2:00 PM (EST)

Improved constraint on primordial gravitational waves with delensing

Abstract: Inflation generically predicts a background of primordial gravitational waves, which generate a primordial B-mode component in the polarization of the cosmic microwave background (CMB). The measurement of such a B-mode signature would lend significant support to the paradigm of inflation. Observed B modes also contain a component from the gravitational lensing of primordial E modes, which can obscure the measurement of the primordial B modes. We reduce the sample variance in the BB spectrum contributed from this lensing component by a process called 'delensing.' In this talk, I will show results from the first demonstration in an improved constraint on primordial gravitational waves with delensing using data from BICEP/Keck, the South Pole Telescope (SPT), and Planck. In addition, I will provide an outlook of joint-analysis efforts of the BICEP/Keck and the SPT collaborations (the South Pole Observatory) to constrain primordial gravitational waves.

Sihao Cheng (Johns Hopkins University)

October 8, 2020,  2:00 PM (EST)

CNN without training: a new vocabulary for patterns and its cosmological applications

Abstract: Textures and patterns are ubiquitous in astronomical data but challenging for quantitative analysis. I will present a new tool, called the “scattering transform”. It borrows ideas from convolutional neural nets (CNNs) while sharing advantages of traditional statistical estimators. As an example, I will show its application to weak lensing data for constraining cosmological parameters and show that it outperforms classic statistics. It is a powerful new approach in astrophysics and beyond.

Leanne Guy (Vera Rubin LSST DM)

September 24, 2020, 2:00PM - 3:00PM (EST)

The ESA Gaia Mission and Gaia Data Release 2

Abstract: Gaia is a space astrometry mission of the European Space Agency (ESA) and the successor to the ESA Hipparcos mission (1989-1993). The main goal of the Gaia mission is to perform a stellar census of 1 billion of the brightest objects in our galaxy. Since launch in 2013, Gaia has delivered two public catalogs, Gaia Data Release 1 (Gaia DR1) and 2 (Gaia DR2), both of which represent intermediate steps towards the anticipated final publication of the most accurate three-dimensional map of the positions, motions, and chemical composition of stars in our Galaxy. In this talk, I will give an overview of the Gaia mission and take a detailed look at the contents of Gaia Data Release 2 and how to access them via the Gaia Archive.

Eli Rykoff (SLAC)

September 10, 2020, 2:00PM - 3:00PM (EST)

The Magic of Red Galaxies

Abstract:

Red elliptical galaxies are not exciting.  All the action is long past, their star formation ended billions of years ago, they have retired from their busy mergers, and now they are made up of old stars, fading away. These properties make them uniquely valuable tools for tracing the history of structure formation in the Universe.  Both on their own and gathered into galaxy clusters, the largest peaks in the cosmic density field, they track the growth of structure over a large mass range.  
In this talk I will review what red galaxies are, how we measure their redshifts, and how we can make use of them in large photometric surveys such as the Dark Energy Survey (DES) and the Rubin Observatory Legacy Survey of Space and Time (LSST).  And yes, I will also answer the question “but what about dust?”

Richard Kessler (Kavli Institute for Cosmological Physics)

June 18 2020, 2:00PM - 3:00PM (EST) (reprogrammed)

Tutorial on Supernova Analysis Software (SNANA)

Abstract:
I will give a tutorial on the SNANA software that has been used for more than a decade to measure dark energy properties with Type Ia Supernovae. The tutorial includes underlying codes such as simulations and light curve fitting, and computing-environment issues needed for large groups to collaborate effectively on a complex analysis.

Jonathan Blazek (Ecole Polytechnique Federale de Lausanne)

March 26 2020, 2:00PM - 3:00PM

Galaxies Far, Far Away...
A general description of intrinsic alignments and biasing

Abstract: Observational cosmology with galaxy surveys provides a powerful probe of the cosmological model. Current and next-generation projects such as DES, LSST, and DESI will allow us to measure geometry and growth of structure in the Universe and to compare with both theoretical predictions and complementary observations. However, these measurements rely on our ability to understand where and how galaxies form in order to use them as robust tracers of the underlying cosmic structure. I will discuss the questions of galaxy biasing and intrinsic alignments, which impact the observed galaxy positions and shapes, from a cosmologist’s perspective. Rather than starting with particular astrophysical processes relevant to galaxy formation, I will show how we can describe galaxy observables in a general and flexible expansion using nonlinear perturbation theory. I will discuss the standard effects of gravitational collapse as well as the impact of baryonic physics from the early Universe. Finally, I will discuss how these perturbative expansions can provide opportunities to explore physics beyond the usual models.

Supranta Boruah ( University of Waterloo )

February 27 2020, 2:00PM - 3:00PM

Cosmic flows in the local Universe: comparing reconstructions to observations

Abstract: Peculiar velocities are sourced by the gravitational instabilities in the Universe and are therefore sensitive of the dark matter structures. Studying peculiar velocities is currently the only way to constrain the growth of structures in the Universe. In this talk, I will describe a method for analyzing peculiar velocities by comparing observations to reconstruction. I will then present a recent application of this method to analyzing the peculiar velocities using local observations of Tully-Fisher galaxies and Type Ia supernovae. In the second part of the talk, I will talk about a novel reconstruction method based on Bayesian forward modelling of the large scale structure. I will talk about several application of this promising reconstruction approach including in analyzing peculiar velocities.

The design and precise implementation of joint-probe analyses are important research directions for large-scale structure surveys, such as DES and LSST. The combination of galaxy clustering and weak lensing in DES has led to accurate measurement of dark energy and structure growth in the low-z universe. In this talk, I will focus on several systematic effects both on large scales and small scales, the covariances of joint-probes, as well as the computational challenges. I will explain how the FFTLog algorithm and its extensions overcome the challenges and enable accurate modeling for the multi-probe analyses. Accurate and efficient modeling methods like these will be in high demand in the future, when more probes and surveys are jointly analyzed to improve their scientific gains.

Understanding how galaxies populate dark matter halos allows linking different levels of hierarchical clustering. In particular, the halo occupation distribution (DOH)  emerged recently as a useful statistic to relate galaxies to the halo mass they inhabit. Analyzing this relation in simulations and observational data allows us to find a lot of information both about galaxy formation and evolution in different environments, as clustering of matter.

The statistical analysis of lensed galaxies is a powerful tool to study the dark matter distribution of the Universe. For instance, the distortion of galaxy shapes induced by the large scale structure of the Universe can be used to reconstruct the projected matter density along the line-of-sight (mass maps). Mass maps are useful as they provide a wealth of information that goes beyond and complements the more traditional two-point statistics used in Cosmology. The data from the first three years of observations of the Dark Energy Survey (DES Y3) will allow to construct the largest curved-sky galaxy weak lensing mass map to date, covering about 5000 sq. deg of the southern sky. During this talk, we will show preliminary DES Y3 mass maps and explore the possibility of constraining cosmological parameters using the second and third moments of the mass maps.

The post-recombination background cosmic evolution is determined by two parameters in the standard ΛCDM model, the Hubble constant (𝐻0) and today's matter energy fraction (Ω𝑚). Instead of just 𝐻0, it is much more beneficial to compare all constraints individually in the 𝐻0-Ω𝑚 plane. I will show those advantages with a systematic constraint comparison and discuss how different observations probe the cosmic evolution. In the 𝐻0-Ω𝑚space and based on the standard ΛCDM model, most different types of constraints consistently overlap in some region along different degeneracy directions. The Cepheid-based local measurement is the most outlying constraint. It is difficult for nonstandard models with modifications at high-, mid- or low-redshifts to reconcile all constraints if none of them have unaccounted-for systematic effects. Incidentally, I will discuss a hidden dark matter scenario where the dark matter has an independent thermal history and show that this scenario is difficult to resolve the Hubble constant tension. A more Likely solution to the tension is an alteration to the local result, either due to some previously unseen feature in our local cosmic environment, or some other unknown systematic effect. I will also talk about how to use the Index of Inconsistency (IOI) to generalize such a multi-constraint comparison in multi-parameter space.

The discovery of the accelerating expansion of the Universe, through the observation of distant type Ia supernovae (SNIa), showed that the Universe consists of 70% “dark energy” whose nature remains unknown. Next-generation wide-field surveys such as the LSST will constrain dark energy properties using measurements of multiple cosmological probes. Among these, SNIa will directly constrain the equation of state of dark energy. Other probes, such as the cosmic shear, will test General Relativity through the growth of structure. LSST will increase the number of observed galaxies and transient objects by orders of magnitude. Consequently, constraints on dark energy properties will be limited by systematic uncertainty, and not by statistics. In the first part of the seminar, I will talk about reducing instrumental systematics and specifically on improving the Point Spread Function (PSF) modeling based on a physical model called OptAtmo.  I will show some preliminary results of the OptAtmo model on Dark Energy Survey (DES) data and compare it to the current PSF model used in the cosmic shear analysis of DES. In the second part of the seminar, I will describe how to reduce astrophysical systematics for measuring distances using SNIa. I will first present the current cosmological context, focusing on the state of the art SNIa cosmology. I will then discuss the limitations of the current method, which is based on light-curve properties (stretch, color). Then, I will introduce the new SNIa model called the SUpernova Generator and Reconstructor (SUGAR), which I developed within The Nearby Supernova Factory collaboration. SUGAR improves the spectrophotometric description of SNIa, and hence the distance inference. Finally, I will talk about the implication of SUGAR in the context of LSST and how it will help us understand the properties of dark energy.