mathematics

Grégory Miermont

Grégory Miermont is a mathematics 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 Grégory Miermont rather than just read about it. In short: Grégory Miermont (born 16 July 1979) is a French mathematician working on probability, random trees and random maps. Biography After high school, Miermont trained for two years at Classe préparatoire aux grandes écoles at the end of which he was admitted at the École normale supérieure in Paris.

Key takeaways

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

Reference excerpt

Grégory Miermont (born 16 July 1979) is a French mathematician working on probability, random trees and random maps.

Biography After high school, Miermont trained for two years at Classe préparatoire aux grandes écoles at the end of which he was admitted at the École normale supérieure in Paris. He studied there from 1998 to 2002, spending the 2001–2002 year as a visiting student in Berkeley. He received his doctorate at Pierre and Marie Curie University in 2003, under the supervision of Jean Bertoin. Then, he became a CNRS researcher in 2004 at University of Paris-Sud and École normale supérieure, and was promoted to the rank of professor in 2009. Since 2012 he is a professor at the École normale supérieure de Lyon.

Work Miermont worked on the theory of probability, more precisely on the geometry and scaling limits of random planar maps, and on fragmentation related to random trees.

Awards and honors

Diplomas, titles and awards 2003: PhD Thesis (advisor J. Bertoin) 2008: Habilitation dissertation 2007: Prize of the Fondation des Sciences Mathématiques de Paris 2009: Rollo Davidson Prize 2012: Prize of the European Mathematical Society 2014: Doeblin Prize[1] Archived 26 October 2020 at the Wayback Machine 2015: Medallion lecturer: Compact Brownian Surfaces

Selected writings G. Miermont, Self-similar fragmentations derived from the stable tree. I. Splitting at heights, Probab. Theory Related Fields, 127 (2003), pp. 423–454 doi:10.1007/s00440-003-0295-x. B. Haas and G. Miermont, The genealogy of self-similar fragmentations with negative index as a continuum random tree, Electron. J. Probab., 9 (2004), pp. no. 4, 57–97 doi:10.1214/EJP.v9-187. G. Miermont, Tessellations of random maps of arbitrary genus, Ann. Scient. Ec. Norm. Supér. 42, fascicule 5, 725–781 (2009). URL G. Miermont, "The Brownian map is the scaling limit of uniform random plane quadrangulations". Acta Math. 210, 319–401 (2013) doi:10.1007/s11511-013-0096-8.

References

External links Grégory Miermont's website Grégory Miermont at the Mathematics Genealogy Project

Illustrations

Worked examples

Example 1 — a first encounter with Grégory Miermont

Start with the simplest possible case. Write down what Grégory Miermont claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In mathematics, 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 Grégory Miermont 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 Grégory Miermont 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 Grégory Miermont

In research: Grégory Miermont appears in mathematics 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 Grégory Miermont 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: Grégory Miermont is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1979 births, 21st-century French mathematicians, Academic staff of the École normale supérieure (Paris), so understanding it makes those chapters shorter.
In everyday life: Look for Grégory Miermont 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 Grégory Miermont in 20 minutes

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

Frequently asked questions

What is Grégory Miermont in simple terms?

Grégory Miermont (born 16 July 1979) is a French mathematician working on probability, random trees and random maps. Biography After high school, Miermont trained for two years at Classe préparatoire aux grandes écoles at the end of which he was admitted at the École normale supérieure in Paris.

Why does Grégory Miermont matter?

Because it connects several mathematics 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 Grégory Miermont?

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 Grégory Miermont.