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Nick Pippenger

Nick Pippenger is a computer science 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 Nick Pippenger rather than just read about it. In short: Nicholas John Pippenger is a researcher in computer science. He has produced a number of fundamental results many of which are being widely used in the field of theoretical computer science, database processing and compiler optimization.

Key takeaways

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

Reference excerpt

Nicholas John Pippenger is a researcher in computer science. He has produced a number of fundamental results many of which are being widely used in the field of theoretical computer science, database processing and compiler optimization. He has also achieved the rank of IBM Fellow at Almaden IBM Research Center in San Jose, California. He has taught at the University of British Columbia in Vancouver, British Columbia, Canada and at Princeton University in the US. In the Fall of 2006 Pippenger joined the faculty of Harvey Mudd College. Pippenger holds a B.S. in Natural Sciences from Shimer College and a PhD from the Massachusetts Institute of Technology. He is married to Maria Klawe, former President of Harvey Mudd College. In 1997 he was inducted as a Fellow of the Association for Computing Machinery. In 2013 he became a fellow of the American Mathematical Society. The complexity class, Nick's Class (NC), of problems quickly solvable on a parallel computer, was named by Stephen Cook after Nick Pippenger for his research on circuits with polylogarithmic depth and polynomial size. Pippenger became one of the most recent mathematicians to write a technical article in Latin, when he published a brief derivation of a new formula for e, whereby the Wallis product for π is modified by taking roots of its terms:

e 2 = ( 2 1 ) 1 / 2 ( 2 3 4 3 ) 1 / 4 ( 4 5 6 5 6 7 8 7 ) 1 / 8 ⋯ . {\displaystyle {\frac {e}{2}}=\left({\frac {2}{1}}\right)^{1/2}\left({\frac {2}{3}}{\frac {4}{3}}\right)^{1/4}\left({\frac {4}{5}}{\frac {6}{5}}{\frac {6}{7}}{\frac {8}{7}}\right)^{1/8}\cdots .}

References

External links Pippenger's web page at HMC

Worked examples

Example 1 — a first encounter with Nick Pippenger

Start with the simplest possible case. Write down what Nick Pippenger claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, 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 Nick Pippenger 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 Nick Pippenger 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 Nick Pippenger

In research
Nick Pippenger appears in computer science 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 Nick Pippenger 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
Nick Pippenger is common in secondary-school and first-year university syllabi. It links to neighbouring topics American computer scientist stubs, American computer scientists, Fellows of the American Mathematical Society, so understanding it makes those chapters shorter.
In everyday life
Look for Nick Pippenger 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 Nick Pippenger in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Nick Pippenger 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 Nick Pippenger out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Nick Pippenger in simple terms?

Nicholas John Pippenger is a researcher in computer science. He has produced a number of fundamental results many of which are being widely used in the field of theoretical computer science, database processing and compiler optimization.

Why does Nick Pippenger matter?

Because it connects several computer science 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 Nick Pippenger?

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 Nick Pippenger.

Tags

  • American computer scientist stubs
  • American computer scientists
  • Fellows of the American Mathematical Society
  • Fellows of the Association for Computing Machinery
  • Harvey Mudd College faculty
  • IBM Fellows
  • Living people
  • Massachusetts Institute of Technology alumni
  • Shimer College alumni
  • Theoretical computer scientists

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