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astronomy

Karl Glazebrook

Karl Glazebrook is a astronomy topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Karl Glazebrook rather than just read about it. In short: Karl Glazebrook (born 1965) is a British astronomer, known for his work on galaxy formation, for playing a key role in developing the "nod and shuffle" technique for doing redshift surveys with large telescopes, and for originating the Perl Data Language (PDL). Glazebrook was born in 1965 in the United Kingdom, and educated at the University of Cambridge and the University of Edinburgh (PhD 1992).

Key takeaways

  • Karl Glazebrook belongs to astronomy; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Karl Glazebrook to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Karl Glazebrook from memory before moving on to harder problems.

Reference excerpt

Karl Glazebrook (born 1965) is a British astronomer, known for his work on galaxy formation, for playing a key role in developing the "nod and shuffle" technique for doing redshift surveys with large telescopes, and for originating the Perl Data Language (PDL). Glazebrook was born in 1965 in the United Kingdom, and educated at the University of Cambridge and the University of Edinburgh (PhD 1992). He held post-doctoral appointments at the University of Durham and University of Cambridge before moving to the Anglo-Australian Observatory, where he played a central role in supporting the 2dF galaxy survey as its instrument scientist. He moved to Johns Hopkins University in 2000 where he was Professor of Astronomy until 2006, at which time he became Professor of Astronomy at Swinburne University of Technology in Melbourne, Australia. His work has been cited over 40,000 times in the literature of astronomy. Glazebrook also developed the open-source Perl Data Language, a perl-based alternative to the commercial IDL. Glazebrook was one of the leaders of the Gemini Deep Deep Survey (GDDS) which measured the evolution of galaxies using Gemini Observatory and the Hubble and Spitzer Space Telescopes. The project, along with a number of other studies, determined in 2004 that massive galaxies formed surprisingly early in the distant Universe, explaining why a lot of them appear so remarkably old. As a whimsical side-project Glazebrook also determined that the bulk-averaged color of the Universe is cosmic latte. Both pieces of work received wide publicity in the international press. The bulk-averaged color earned some additional international publicity because a software bug had initially suggested a pale turquoise instead of the bland beige. He is also well known in the astronomical community for his pioneering work in developing the baryon oscillation technique to use the distribution of galaxies as a probe of dark energy. After his move to Australia he played a leading role in the WiggleZ Dark Energy Survey between 2006 and 2011.

Honours and awards 2018 Australian Laureate Fellowship 2008, awarded the Maria & Eric Muhlmann Award for the development of innovative research instruments and techniques from the Astronomical Society of the Pacific. Outer main-belt asteroid 10099 Glazebrook, discovered by Spacewatch at Kitt Peak in 1991, was named in his honor. Naming citation was published on 11 November 2000 (M.P.C. 41571).

References

Worked examples

Example 1 — a first encounter with Karl Glazebrook

Start with the simplest possible case. Write down what Karl Glazebrook claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In astronomy, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Karl Glazebrook before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Karl Glazebrook ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Karl Glazebrook

In research
Karl Glazebrook appears in astronomy research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Karl Glazebrook in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Karl Glazebrook is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1965 births, 21st-century Australian astronomers, Academic staff of Swinburne University of Technology, so understanding it makes those chapters shorter.
In everyday life
Look for Karl Glazebrook outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Karl Glazebrook in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Karl Glazebrook means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Karl Glazebrook out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Karl Glazebrook in simple terms?

Karl Glazebrook (born 1965) is a British astronomer, known for his work on galaxy formation, for playing a key role in developing the "nod and shuffle" technique for doing redshift surveys with large telescopes, and for originating the Perl Data Language (PDL). Glazebrook was born in 1965 in the Un…

Why does Karl Glazebrook matter?

Because it connects several astronomy ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Karl Glazebrook?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Karl Glazebrook.

Tags

  • 1965 births
  • 21st-century Australian astronomers
  • Academic staff of Swinburne University of Technology
  • Alumni of the University of Edinburgh
  • Living people
  • People educated at Chislehurst and Sidcup Grammar School
  • Physicists of Durham University

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