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Lilian Matthiesen

Lilian Matthiesen 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 Lilian Matthiesen rather than just read about it. In short: Lilian Matthiesen (born 1984) is a mathematician whose research involves analytic number theory including the application of Fourier analysis to Diophantine geometry. Educated in England, she has worked in France, Germany, and Sweden, and is University Professor in the Mathematics Institute of the University of Göttingen in Germany.

Key takeaways

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

Reference excerpt

Lilian Matthiesen (born 1984) is a mathematician whose research involves analytic number theory including the application of Fourier analysis to Diophantine geometry. Educated in England, she has worked in France, Germany, and Sweden, and is University Professor in the Mathematics Institute of the University of Göttingen in Germany.

Education and career Matthiesen earned a Ph.D. at the University of Cambridge in England in 2012, with the dissertation Applications of the nilpotent Hardy–Littlewood method supervised by Ben Green. After postdoctoral research at the University of Bristol, and in France at Paris-Sud University and the Institut de mathématiques de Jussieu – Paris Rive Gauche, she became an assistant professor at Leibniz University Hannover in Germany in 2015. She moved to the KTH Royal Institute of Technology in Stockholm in 2016, and became an associate professor there, before taking a position as University Professor in the Mathematics Institute of the University of Göttingen in Germany.

Recognition Matthiesen was the 2020 recipient of the Göran Gustafsson Prize, a 2023 recipient of the Wallenberg Prize of the Swedish Mathematical Society, and the 2024 recipient of the Tage Erlander Prize of the Royal Swedish Academy of Sciences.

References

External links Home page

Worked examples

Example 1 — a first encounter with Lilian Matthiesen

Start with the simplest possible case. Write down what Lilian Matthiesen 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 Lilian Matthiesen 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 Lilian Matthiesen 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 Lilian Matthiesen

In research
Lilian Matthiesen 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 Lilian Matthiesen 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
Lilian Matthiesen is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1984 births, 21st-century mathematicians, 21st-century women mathematicians, so understanding it makes those chapters shorter.
In everyday life
Look for Lilian Matthiesen 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 Lilian Matthiesen in 20 minutes

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

Frequently asked questions

What is Lilian Matthiesen in simple terms?

Lilian Matthiesen (born 1984) is a mathematician whose research involves analytic number theory including the application of Fourier analysis to Diophantine geometry. Educated in England, she has worked in France, Germany, and Sweden, and is University Professor in the Mathematics Institute of the…

Why does Lilian Matthiesen 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 Lilian Matthiesen?

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 Lilian Matthiesen.

Tags

  • 1984 births
  • 21st-century mathematicians
  • 21st-century women mathematicians
  • Academic staff of Leibniz University Hannover
  • Academic staff of the KTH Royal Institute of Technology
  • Academic staff of the University of Göttingen
  • Alumni of the University of Cambridge
  • Living people
  • Number theorists

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