Class introduction

• Class content
  • Goal: how to understand and optimally collect astronomical data and extract information, in principle and in practice. Position you to take advantage of NMSU facilities if you are interested.

  • What do we mean by observational techniques?
    • Recover intrinsic information coming from sky via measurement as best as possible: requires understanding of instrumental signatures and how to remove them, calibration of data
    • All measurements have uncertainties and, often, understanding uncertainty on a measurement is as important as the measurement itself.
    • In some cases, uncertainties can be minimized by how data are collected, and how data are analyzed/calibrated.

  • class content:
    • knowledge
      • need to understand nature of light and errors and error analysis involved with its collection

      • need to understand how instruments work to understand information, accuracy, and to get most from the data, not to mention being in a position to understand/design instruments of the future. In many cases, instrument development drives scientific knowledge! Consequently, we will discuss telescopes, instruments, and detectors. Principally we will discuss imaging instruments and spectrographs. We may briefly discuss some other types of instruments (imaging spectroscopy, interferometry). We will cover instrumentation/methodology for UV/optical/IR observations; radio may be covered in a separate class, because many of the techniques are different. Also, high energy techniques often differ.

      • Organization: from astronomical object to measurement: properties of light/photons, effect of earth's atmosphere, telescope, instruments, detectors, data reduction, data analysis

    • practical tools
      • using telescopes and data reduction packages may be necessary skills, but perhaps are not best taught in a class environment. Observing/data reduction may best be learned by taking on a research project, e.g. with your advisor, and being forced to learn by doing. Be aware that different people use different tools! But critical to understand what is being done, as opposed to the operational set of commands to do it! We'll try to include some of this in class sessions, with possible periodic ``work-only" sessions.

      • NOTE: to get most from data (and often, to stand apart from the ``crowd''), you need to develop refined or new techniques of data analysis. Beware of canned procedures, or at least, remember that you need to fully understand what they are doing. Also, all instruments generally present slightly new problems which demand different techniques.

      • NOTE: hardly anything (telescopes, instruments, software) works flawlessly all of the time. Understanding how things work is your responsibility, not someone elses, even if it's someone elses responsibility to make them work.

      • potentially at a transition time in software for data reduction. Note issues involving IRAF, astropy, and the ARC DAWG. Some opportunities here!

    • inquiry
      • it is not possible to teach you everything you need to know, or to know how to do.
      • you need to learn how to ask questions (increasing in depth) and answer them, and especially develop the skill to question yourself

  • Beware that, while observational techniques are a critical part of doing science, they are tools to use towards an end: collecting and reducing data may be necessary, but is not sufficient, to do science!

  • Note changing face of astronomy, e.g. from traditionally-scheduled telescopes to automated telescopes, HST, SDSS. Traditional mode observing, remote observing, service observing/ queue scheduling, dedicated projects, virtual observatory. Big instruments with dedicated software. Many science users no longer reduce their own data. On the flip side, many jobs have to do with development of data pipelines, and expertise along these lines seems to be getting more scarce.

• Logistics
  • We will attempt for some topics to flip the classroom, with reading assignments that significant time/effort should be dedicated to. Come to class with questions. Some simple quizzes will be occasionally be imposed to ensure that reading is taken seriously. Importance of reading.
    • For this work, must spend sufficient time reading for full comprehension. Remember, the idea is that the material will not be repeated in class; we will try to probe the understanding and ability to apply it.
    • Strategies for reading: small bits, multiple times per day and multiple days
    • Question your understanding
    • Look at and work problems
    • Formulate questions: when possible, send them to me via email

  • We will attempt to spend some class time working problems and/or developing techniques. Some of this will be in shorter blocks to break up discussion/presentation, but we will have occasional full periods of practical sessions to develop some familiarity with working with data. While we will attempt to couple these sessions with material that we have been discussing, occasionally the practical sessions may follow a separate thread. If we do not complete practical work during a class period, the work be finished outside of class.

  • Will attempt to assign frequent short exercises, and less frequent somewhat more involved problems. Note there will be different expectations for the graduate and undergraduates in the class. Some problems may have been given, along with answers, in previous years: you are implicitly expected NOT to query older graduate students about these.

  • One midterm (early October?), one final.

  • class info/notes accessible through Canvas on web: http://astronomy.nmsu.edu/holtz/a535
    • web notes are not a textbook, and often just provide a framework
    • Steve Majewski (UVa) class notes

  • Texts/references:
    • Chromey, To Measure the Sky, covers much of the material from the class, at moderately low level
    • Rieke, Measuring the Universe. Relatively new book that covers much of the material we will discuss – although not always from the same perspective.
    • Schroeder, Astronomical Optics. Good reference on optics relevant for astronomy. Goes into significantly more detail than we will cover in class.
    • Astronomical CCD Observing and Reduction Techniques (ed., S. Howell). Out of print.
    • Sutton, Observational Astronomy
    • Birney et al, Observational Astronomy
    • Kitchin, Astrophysical Techniques, and Optical Astronomical Spectroscopy
    • Howell, Handbook of CCD Astronomy
    • Bevington, Data Reduction and Error Analysis for the Physical Sciences: error analysis and propagation, least squares fitting, etc.
    • Press et al., Numerical Recipes, lots of numerical techniques: fitting, interpolation, lots more

  • trip to APO - two weekends in October ??. Housing. Training.

• Pre-class assessment

• Introduction to NMSU telescopes(APO):
  • ARC 3.5m: consortium with U. Wash (25%), NMSU (15.625%), U. Colorado (12.5%), Johns Hopkins University (8%), U. Virginia (6.25%), Georgia State University (6.25%), University of Oklahoma (6.25%) University of Wyoming(6.25%) several leasing partners. Instruments:
    • ARCTIC: ``wider-field" optical imager (SPICAM - old imager)

    • AGILE - high speed imager

    • DIS - double imaging spectrograph: slit spectrograph

    • KOSMOS - coming soon! slit spectrograph

    • ARCES - echelle spectrograph

    • NICFPS: IR imager (+grism)

    • TRIPLESPEC: IR spectrograph

  • SDSS 2.5m: wide field telescope. Projects:
    • SDSSI (-2005): Sloan galaxy survey: image 1/4 of northern sky, identify galaxies, get spectra of all galaxies (about a million) brighter than some limit, derive redshifts/distances to produce a 3D map. Successful in this, but perhaps even more successful in helping to develop a firmer understanding of the distribution of quantitative galaxy properties, and also to provide a homogeneous data set of photometry and galaxy spectra across a large region of the sky.
    • SDSSII (2005-2008): finish Sloan galaxy survey, Sloan supernove survey, SEGUE: Sloan Extension for Galactic Understanding and Exploration. SN survey images a strip of the sky (stripe 82) repeatedly to look for time variable objects. SEGUE extends spectrscopy to target Milky Way stars, mostly at higher Galactic latitudes
    • SDSSIII (2008-2014): BOSS, MARVELS, SEGUE-2, APOGEE. BOSS gets reshifts of luminous red galaxies and quasars to study baryon acoustic osciallation signature in the spatial distribution of galaxies. MARVELS uses novel technology to detect planets. APOGEE targets MW stars, focussing on lower Galactic latitudes, using a new multi-object near-IR spectrograph
    • SDSSIV (2014-2020): eBOSS, MaNGA, APOGEE (inc. APOGEE-S). eBOSS extends BAO observations to higher redshift. APOGEE continues map the Milky Way; APOGEE starts southern hemisphere observations at las Campanas Observatory with a second spectrograph. MaNGA program to get integral field spectroscopy of 10,000 ``nearby" galaxies.
    • SDSSV (2020-): Milky Way Mapper (MWM), Black Hole Mapper (BHM), Local Volume Mapper (LVM).

  • NMSU 1m. Instruments:
    • 2048x2048 camera

    • feed to SDSS APOGEE (but no longer usable after eBOSS completion, since APOGEE spectrograph is used all the time with the 2.5m)

    • capability: high speed multichannel photometer

    • ARCSAT: 0.5m with two imaging cameras, FLARECAM and SURVEYCAM

  • NMSU Tortugas mountain observatory : 24" with imaging camera. Introduction sessions next week.

  • NMSU campus observatory. Training session Monday 8/26.

• Observing opportunities: APO, DST, NOAO, HST. Proposal procedure. Existing data opportunities: SDSS, HST archive, etc.

• Student experience/interests