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Paul-André Meyer

Paul-André Meyer 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 Paul-André Meyer rather than just read about it. In short: Paul-André Meyer (21 August 1934 – 30 January 2003) was a French mathematician, who played a major role in the development of the general theory of stochastic processes. He worked at the Institut de Recherche Mathématique (IRMA) in Strasbourg and is known as the founder of the 'Strasbourg school' in stochastic analysis.

Paul-André Meyer — main illustration
Paul-André Meyer — illustration

Key takeaways

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

Reference excerpt

Paul-André Meyer (21 August 1934 – 30 January 2003) was a French mathematician, who played a major role in the development of the general theory of stochastic processes. He worked at the Institut de Recherche Mathématique (IRMA) in Strasbourg and is known as the founder of the 'Strasbourg school' in stochastic analysis.

Biography Meyer was born in 1934 in Boulogne, a suburb of Paris. His family fled from France in 1940 and sailed to Argentina, settling in Buenos Aires, where Paul-André attended a French school. He returned to Paris in 1946 and entered the Lycée Janson de Sailly, where he first encountered advanced mathematics through his teacher, M Heilbronn. He entered the École Normale Supérieure in 1954 where he studied mathematics. There, he attended lectures on probability by Michel Loève, a former disciple of Paul Lévy who had come from Berkeley to spend a year in Paris. These lectures triggered Meyer's interest in the theory of stochastic processes, and he went on to write a thesis in potential theory, on multiplicative and additive functionals of Markov processes, under the supervision of Jacques Deny. After his doctoral thesis, Meyer traveled to the United States and worked for a couple of years with the American mathematician Joseph Doob, who was then developing new ideas in the theory of stochastic processes. It was there that he derived his famous theorem on the decomposition of a submartingale, now known as the Doob–Meyer decomposition. After his return to France he established a group in Strasbourg where he ran his famous 'Séminaire de probabilités de Strasbourg', which became an epicenter for the development of the theory of stochastic processes in France for two decades.

Scientific work Meyer is best known for his continuous-time analog of Doob's decomposition of a submartingale, known as the Doob–Meyer decomposition and his work on the 'general theory' of stochastic processes, published in his monumental book Probabilities and Potential, written with Claude Dellacherie. Some of his main areas of research in probability theory were the general theory of stochastic processes, Markov processes, stochastic integration, stochastic differential geometry and quantum probability. His most cited book is Probabilities and Potential B, written with Claude Dellacherie. The preceding book is the English translation of the second book in a series of five written by Meyer and Dellacherie from 1975 to 1992 and elaborated from Meyer's pioneering book Probabilités et Potentiel, published in 1966. In the period 1966-1980 Meyer organised the Seminaire de Probabilities in Strasbourg, and he and his co-workers developed what is called the general theory of processes. This theory was concerned with the mathematical foundations of the theory of continuous time stochastic processes, especially Markov processes. Notable achievements of the 'Strasbourg School' were the development of stochastic integrals for semimartingales, and the concept of a predictable (or previsible) process. IRMA created an annual prize in his memory; the first Paul André Meyer prize was awarded in 2004 [1]. Persi Diaconis of Stanford University wrote about Meyer that:

I only met Paul-Andre Meyer once (at Luminy in 1995). He kindly stayed around after my talk and we spoke for about an hour. I was studying rates of convergence of finite state space Markov chains. He made it clear that, for him, finite state space Markov chains is a trivial subject. Hurt but undaunted, I explained some of our results and methods. He thought about it and said, “I see, yes, those are very hard problems”. The analytic parts of Dirichlet space theory have played an enormous role in my recent work. I am sure that there is much to learn from the abstract theory as well. In the present paper I treat rates of convergence for a simple Markov chain. I am sorry not to have another hour with Paul-Andre Meyer. Perhaps he would say “This piece of our story might help you”. Perhaps one of his students or colleagues can help fill the void.

Some books and articles written by Paul-André Meyer C. Dellacherie, P.A. Meyer: Probabilities and Potential B, North-Holland, Amsterdam New York 1982. P.A. Meyer: " Martingales and Stochastic Integrals I," Springer Lecture Notes in Mathematics 284, 1972. Brelot's axiomatic theory of the Dirichlet problem and Hunt's theory, Annales de l'Institut Fourier, 13 no. 2 (1963), p. 357–372 Intégrales stochastiques I, Séminaire de probabilités de Strasbourg, 1 (1967), p. 72–94 Intégrales stochastiques II, Séminaire de probabilités de Strasbourg, 1 (1967), p. 95–117 Intégrales stochastiques III, Séminaire de probabilités de Strasbourg, 1 (1967), p. 118–141 Intégrales stochastiques IV, Séminaire de probabilités de Strasbourg, 1 (1967), p. 124–162 Generation of sigma-fields by step processes, Séminaire de probabilités de Strasbourg, 10 (1976), p. 118–124 P.A. Meyer: ' Inégalités de normes pour les integrales stochastiques," Séminaire de Probabilités XII, Springer Lecture Notes in Math. 649, 757–762, 1978.

References

External links In memory of P. A. Meyer Colloque international sur les processus stochastiques et l’héritage de P.A. Meyer Paul-André Meyer at the Mathematics Genealogy Project Literature by and about Paul-André Meyer in the German National Library catalogue

Illustrations

Paul-André Meyer illustration

Worked examples

Example 1 — a first encounter with Paul-André Meyer

Start with the simplest possible case. Write down what Paul-André Meyer 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 Paul-André Meyer 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 Paul-André Meyer 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 Paul-André Meyer

In research
Paul-André Meyer 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 Paul-André Meyer 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
Paul-André Meyer is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1934 births, 2003 deaths, 20th-century French mathematicians, so understanding it makes those chapters shorter.
In everyday life
Look for Paul-André Meyer 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 Paul-André Meyer in 20 minutes

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

Frequently asked questions

What is Paul-André Meyer in simple terms?

Paul-André Meyer (21 August 1934 – 30 January 2003) was a French mathematician, who played a major role in the development of the general theory of stochastic processes. He worked at the Institut de Recherche Mathématique (IRMA) in Strasbourg and is known as the founder of the 'Strasbourg school' i…

Why does Paul-André Meyer 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 Paul-André Meyer?

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 Paul-André Meyer.

Tags

  • 1934 births
  • 2003 deaths
  • 20th-century French mathematicians
  • French probability theorists
  • Members of the French Academy of Sciences
  • École normale supérieure (Paris) alumni

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