Syllabi

Introduction to Astronomy

References

Astronomical Observation and Data Analysis

  • Atmospheric Windows: In which wavelengths best to observe what target?
    • Blackbody Radiation
    • Earth’s Atmosphere
  • Science Goals: What and Why to observe
  • Planning: How to observe the target
    • Ground-based and Space-based Observations
    • Observing Constraints
      • Where is it? Coordinates
      • Is it observable tonight? Rising and Setting Times
      • North and South Hemisphere
      • Weather: Cloud, Humidity, Turbulence
      • Moon
      • Satellites Trails
    • Signal-to-Noise
      • Exposure Time
      • Filters
  • Engineering: Science vs Cost
    • Telescope Design and Operation
      • Tracking and Auto-guiding
    • Instrumentation
      • From Analog to Digital: Photographic Plates and CCD
      • Pixel Sensitivity
      • Pixel Scale
      • Field-of-View
      • Total Telescope-Instrument Throughput
  • Data Reduction with Astropy
    • Dark Current: Dark Frame Subtraction
    • Flat Field: Flat Frame Division
    • Background Subtraction
    • Bad/Hot Pixels
    • Image alignment/registration
    • Open datasets
  • Plate-solving with Astrometry.net
  • World Coordinate System (WCS)
  • Photometry with Photutils
    • Aperture Photometry
      • Optimizing Aperture Size and Shape
    • PSF Photometry
    • Treatment of Outliers
      • Weather: Cloud, Humidity, Turbulence
      • Everything Else Unaccounted for (Systematics)
      • Saturation
      • Cosmic Rays
  • Barycentric Time Correction (MJD to BJD Conversion)
    • Light Travel Time Delay
  • Transit Modeling
    • Basic Model
      • Pytransit
      • Starry
    • Parameterization
      • Transforms
      • Quadratic Limb Darkening: u1, u2 -> q1, q2 (Kipping+2016)
      • Impact Parameter and Rp/Rs (Espinosa+2018)
      • Stellar Density
  • Period Search, Periodogram
    • BLS
    • TLS
    • (Generalized) Lomb-Scargle
  • Spectroscopy using specutils
    • Cross-correlation
  • RV Modeling
    • Basic Model
    • Parameterization
  • Joint RV+Transit Modeling

References

Algorithms: Fast, Numerically Stable, Closed-form Solutions

  • Python Basics
  • Version Control with Git and GitHub
  • Reproducible research with showyourwork
  • Probability Distributions
  • Sympy: Analytic
  • Bayesian vs Frequentist Statistics
  • Fitting Models to Data
    • Linear Algebra
    • Maximum Likelihood
  • Optimization
    • Gradient-free, scipy.optimize.solve
    • Autodiff using jax
  • Monte Carlo Methods
    • Propagation of Uncertainties
  • Sampling
    • MCMC
    • Nested Sampling
    • Convergence Tests
  • Reporting Results
    • Posteriors vs Point Estimates
    • Percentiles
  • Visualization
    • Corner Plot
    • Posteriors
  • Mixture Models
  • Gaussian Process Regression
  • Hierarchical Modeling
  • Machine Learning

References

Miscellaneous readings

General references

Tools