LSST Dark Energy School

Many Dark Energy Schools have been held as part of LSST DESC meetings. Below you will find (most of) the materials used for the lessons presented at these schools – slides, activities, resources – as well as videos of the lectures on YouTube or Zoom cloud. 

DE Schools III through IX were supported by the former LSSTC Enabling Science effort, including matching funds from the Simonyi-Gates Challenge. All DE Schools have also received support through the host institutions. The DE Schools promote learning through peer interactions; see A Quick Guide to Active Learning in Lectures for more details.

DE School XIV, Zürich, July 8, 2024

Confluence page contains material accessible to DESC members only.

Gotta Catch ’Em All - The hunt for gravitationally lensed supernovae in LSST (Nikki Arendse)

Everything you should know about AuxTel, but didn’t know to ask (Jérémy Neveu)

Greater than the sum of its parts: cross-correlations with external data (David Alonso)

Terrible plots: How can we use QA diagnostics during commissioning and beyond? (Arun Kannawadi & Mike Jarvis)

DE School XIII, SLAC, July 24, 2023

Confluence page contains material accessible to DESC members only.

Galaxy clusters: special fields, special challenges (Camille Avestruz)

PZ and the legend of the six bands: photo-z’s for LSST (Sam Schmidt)

LSST observing strategy - a dive into a community-driven survey optimization (Humna Awan)

The LSST Camera: design drivers and expected performance (Aaron Roodman)

DE School XII, Chicago, August 1, 2022

Confluence page contains material accessible to DESC members only.

All together now: covariances for 3x2pt analysis (Danielle Leonard)

Watch the class on Zoom cloud here

Lesson Materials and Resources:

Artifact or science? Instrument signature removal (Merlin Fisher-Levine)

Watch the class on Zoom cloud here

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Robust reproducible results in python — reducing reliance on notebooks! (Eric Charles)

Watch the class on Zoom cloud here

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Making values-based decisions for your career (Lucianne Walkowicz)

Material and recordings are available to DESC members here

DE School XI, Tucson, January 20, 2020

Confluence page contains material accessible to DESC members only.

What we talk about when we talk about neutrinos (Chris Walter)

Watch the class on Zoom cloud here

Lesson Materials and Resources:

Can machine learning solve my problem? (Emille Ishida)

Watch the class on Zoom cloud here

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Are we there yet? How to read the statistical signposts. (Alex Malz)

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Extremely large optics fabrication & testing at the Richard F. Caris Mirror Lab (Dae Wook Kim)

Watch the class on Zoom cloud here

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DE School X, Paris, July 15, 2019

Confluence page contains material accessible to DESC members only.

Combining ground and space-based imaging for cosmic shear (Catherine Heymans)

Watch the class on Youtube here

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Interpolating data using Gaussian Processes: « With great power comes great responsibility. » (Pierre-Francois Leget)

Watch the class on Youtube here

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Multi-band and multi-resolution deblending: Why it is important to leverage all available information (Fred Moolekamp)

Watch the class on Youtube here

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Designing libraries and APIs (Mike Jarvis and Joe Zuntz)

Watch the class on Youtube here

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DE School IX, Berkeley, February 25, 2019

Confluence page contains material accessible to DESC members only.

Complementarity of dark energy and dark matter probes for LSST (Keith Bechtol)

Zoom recording: slides, audio

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Supernova cosmology with LSST and survey strategy (Renee Hlozek)

Zoom recording: slides, audio

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Why might the DESC photometric calibration requirements keep you up at night? (Eli Rykoff)

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Collaborative software development in Python (Stéfan van der Walt)

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DE School VIII, Carnegie Mellon University, July 23, 2018

Confluence page contains material accessible to DESC members only.

What are “3 x 2-point” observables for cosmology? An introduction with the Core Cosmology Library (Elisa Chisari)

Watch the class on YouTube here!

Lesson Materials and Resources:

Let there be light: What’s under the carpet in mock galaxy catalogs? (Yao-Yuan Mao)

Watch the class on YouTube here!

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Validation: Your Data, Your Analysis, and You (Michael Wood-Vasey)

Watch the class on YouTube here!

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Why, when and how to write parallelized code (in DESC). (Debbie Bard & Francois Lanusse)

Watch the class on YouTube here!

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DE School VII, SLAC National Accelerator Laboratory, February 5, 2018

Confluence page contains material accessible to DESC members only.

Expect the Unexpected: Lessons Learned Commissioning Astronomical Instruments (Kevin Reil)

Watch the class on YouTube here!

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Is my code good enough? Improving software through code review (Mike Jarvis)

Watch the class on YouTube here!

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DE School VI, Stony Brook University, July 10, 2017

Confluence page contains material accessible to DESC members only.

A Hitchhiker’s Guide to Machine Learning – applications to supernova classification (Michelle Lochner)

Lesson Materials and Resources:

Cosmology with Galaxy Clusters; and “Now you see me, now you don’t - Effects of selection biases” (Anja von der Linden)

Watch the class on YouTube here!

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Testing Code, as You Code – unit tests and more (Mike Jarvis)

Watch the class on YouTube here!

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DE School V, SLAC, February 13, 2017

Confluence page contains material accessible to DESC members only.

Machine Learning in the LSST Era (David Kirkby)

Watch the class on YouTube here!

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Weak Lensing Shear Estimation Methods and Systematics (Rachel Mandelbaum)

Watch the class on YouTube here!

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Null Tests: Looking for Signal in All the Wrong Places (Mike Jarvis)

Watch the class on YouTube here!

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Cosmology with Strong Gravitational Lenses (Phil Marshall)

Watch the class on YouTube here!

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DE School IV, University of Oxford, July 18, 2016

Confluence page contains material accessible to DESC members only.

Cross-Correlations of Dark Energy Probes (Jo Dunkley)

Watch the class on YouTube here!

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The Era of Large Surveys: What Will LSST Deliver? (Mario Juric)

Watch the class on YouTube here!

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How Bright is that Object? (Robert Lupton)

Watch the class on YouTube here!

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Photometric Redshifts for LSST (Jeff Newman)

Watch the class on YouTube here!

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DE School III, SLAC National Accelerator Laboratory, March 7, 2016

Confluence page contains material accessible to DESC members only.

Robust Model Fitting with Applications to Astronomy (Andrew Connolly)

Watch the class on YouTube here!

Lesson Materials and Resources:

OR

Which Dark Energy Models Will We Test in the LSST-WFIRST-Euclid Era? (Bhuvnesh Jain)

Watch the class on YouTube here!

Lesson Resources:

More than Just a Phase: the LSST Atmospheric PSF (Josh Meyers)

Watch the class on YouTube here!

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Primer on Wavefronts and Aberrations: the LSST Optical PSF (Aaron Roodman)

Watch the class on YouTube here!

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DE School II, Argonne National Laboratory, October 26, 2015

Confluence page contains material accessible to DESC members only.

Dark Energy and Lensing: From GR to Data Analysis (Scott Dodelson)

Watch the class on YouTube here!

Overview of modified gravity models for acceleration and how they might be detected using weak lensing in LSST.

Learning Objectives:

Lesson Materials and Resources:

Survey Strategy and Dark Energy Systematics (Eric Gawiser)

Watch the class on YouTube here!

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Future Computing Architectures and Data Analysis (Salman Habib and Adrian Pope)

Watch the class on YouTube here!

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How to simulate our Universe (Katrin Heitmann)

Watch the class on YouTube here! 

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DE School I, SLAC National Laboratory, February 2, 2015

Confluence page contains material accessible to DESC members only.

Image processing algorithms: Building science-ready catalogs (Jim Bosch)

Watch the class on YouTube here!

A very high-level view of the LSST Data Management (DM) pipelines, and a closer look at the details of algorithms for object detection. 

Learning Objectives:

After completing this class, students will be able to:

Lesson Materials and Resources:

LSST’s Cosmological Probes (Shirley Ho)

Watch the class on YouTube here!

This lesson is designed to introduce several of the dark energy probes in LSST. It assumes basic knowledge of cosmology and statistics. 

Learning objectives:

After this class, students will be able to:

Lesson Materials and Resources:

Key LSST Design Choices, and How They Were Driven by Science (Steve Kahn)

Watch the class on YouTube here!

Learning Objectives:

After completing this class, students will be able to:

Lesson Materials and Resources:

How to use statistics to describe the large scale structure of the Universe (David Kirkby)

Watch the class on YouTube here!

An introduction to large scale structure in the Universe and techniques used to measure its statistics, including the topics of co-variance, random fields and the power spectrum. 

Learning Objectives:

After completing this class, students will be able to:

Lesson Materials:

Cosmic Co-variance (Michael Schneider)

Watch the class on YouTube here!

In this lesson we will cover how we infer cosmological parameter constraints in the presence of correlated errors, including how we infer cosmological parameters from large-scale structure probes and how we combine parameter constraints from different surveys. 

Learning Objectives:

After completing this class, students will be able to:

Lesson Materials:

How the Physics of Sensors Impacts Dark Energy Science (Chris Stubbs)

Watch the class on YouTube here!

This lesson deals with the non-idealities encountered in real-world CCDs. We illustrate how to assess the impact of one particular gremlin on weak lensing measurements, lateral electric fields arising from radially symmetrical impurities in the Silicon wafer. 

Learning Objectives:

After completing this class, students will be able to:

Lesson Materials and Resources: