Uploaded August 2022 | Updated September 2026, 2 weeks ago
University of Oxford mathematician Dr Tom Crawford explains how to calculate the eigenvalues and eigenvectors of a matrix, with 2 fully worked examples.
Check out ProPrep with a 30-day free trial to see how it can help you to improve your performance in STEM-based subjects: proprep.uk/info/TOM-Crawford
Test your understanding with some practice exercises courtesy of ProPrep. You can download the workbooks and solutions for free here: proprep.uk/Academic/DownloadBook?file=Proprep%20-%20Linear%20Algebra%20-%20Eigenvectors%20Eigenvalues%20and%20Diagonalization%20-%20workbook%20uk.pdf
You can also find several video lectures from ProPrep explaining the topic further here: proprep.uk/general-modules/all/linear-algebra/eigenvectors-eigenvalues-and-diagonalization/eigenvectors-and--eigenvalues-of-a-matrix/vid25751
And fully worked video solutions from ProPrep instructors are here: proprep.uk/general-modules/all/linear-algebra/eigenvectors-eigenvalues-and-diagonalization/eigenvectors-and--eigenvalues-of-a-matrix/vid25736
Watch other videos from the Oxford Linear Algebra series at the links below.
Solving Systems of Linear Equations using Elementary Row Operations (ERO’s): youtu.be/9pF__coVyEE
Calculating the inverse of 2x2, 3x3 and 4x4 matrices: youtu.be/VKOaG3Ogf9Q
What is the Determinant Function: youtube.com/watch?v=bLsBWVYSg0A
The Easiest Method to Calculate Determinants: youtu.be/qniUv4EZB0w
The video begins by introducing the eigenvalue equation which we are trying to solve, with a discussion of possible methods of solution. We see that the only way a non-zero eigenvector can be found is if the determinant of the characteristic matrix is zero, which gives us the characteristic equation, or characteristic polynomial. Solving this equal to zero gives the eigenvalues, which are then substituted back into the eigenvalue equation to give the corresponding eigenvectors.
The method is demonstrated first with a 2x2 matrix example, and then for a 3x3 matrix. In both cases we consider a general eigenvector before choosing one parameter to make the final vector as simple as possible.
Produced by Dr Tom Crawford at the University of Oxford. Tom is an Early-Career Teaching and Outreach Fellow at St Edmund Hall: seh.ox.ac.uk/people/tom-crawford
For more maths content check out Tom's website tomrocksmaths.com
You can also follow Tom on Facebook, Twitter and Instagram @tomrocksmaths.
facebook.com/tomrocksmaths
twitter.com/tomrocksmaths
instagram.com/tomrocksmaths
Get your Tom Rocks Maths merchandise here: beautifulequations.net/collections/tom-rocks-maths
University of Oxford mathematician Dr Tom Crawford explains how to calculate the eigenvalues and eigenvectors of a matrix, with 2 fully worked examples.
Check out ProPrep with a 30-day free trial to see how it can help you to improve your performance in STEM-based subjects: proprep.uk/info/TOM-Crawford
Test your understanding with some practice exercises courtesy of ProPrep. You can download the workbooks and solutions for free here: proprep.uk/Academic/DownloadBook?file=Proprep%20-%20Linear%20Algebra%20-%20Eigenvectors%20Eigenvalues%20and%20Diagonalization%20-%20workbook%20uk.pdf
You can also find several video lectures from ProPrep explaining the topic further here: proprep.uk/general-modules/all/linear-algebra/eigenvectors-eigenvalues-and-diagonalization/eigenvectors-and--eigenvalues-of-a-matrix/vid25751
And fully worked video solutions from ProPrep instructors are here: proprep.uk/general-modules/all/linear-algebra/eigenvectors-eigenvalues-and-diagonalization/eigenvectors-and--eigenvalues-of-a-matrix/vid25736
Watch other videos from the Oxford Linear Algebra series at the links below.
Solving Systems of Linear Equations using Elementary Row Operations (ERO’s): youtu.be/9pF__coVyEE
Calculating the inverse of 2x2, 3x3 and 4x4 matrices: youtu.be/VKOaG3Ogf9Q
What is the Determinant Function: youtube.com/watch?v=bLsBWVYSg0A
The Easiest Method to Calculate Determinants: youtu.be/qniUv4EZB0w
The video begins by introducing the eigenvalue equation which we are trying to solve, with a discussion of possible methods of solution. We see that the only way a non-zero eigenvector can be found is if the determinant of the characteristic matrix is zero, which gives us the characteristic equation, or characteristic polynomial. Solving this equal to zero gives the eigenvalues, which are then substituted back into the eigenvalue equation to give the corresponding eigenvectors.
The method is demonstrated first with a 2x2 matrix example, and then for a 3x3 matrix. In both cases we consider a general eigenvector before choosing one parameter to make the final vector as simple as possible.
Produced by Dr Tom Crawford at the University of Oxford. Tom is an Early-Career Teaching and Outreach Fellow at St Edmund Hall: seh.ox.ac.uk/people/tom-crawford
For more maths content check out Tom's website tomrocksmaths.com
You can also follow Tom on Facebook, Twitter and Instagram @tomrocksmaths.
facebook.com/tomrocksmaths
twitter.com/tomrocksmaths
instagram.com/tomrocksmaths
Get your Tom Rocks Maths merchandise here: beautifulequations.net/collections/tom-rocks-maths








![Yang Mills Mass Gap Hypothesis with Martin Hairer (2014 Fields Medal)
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Professor Martin Hairer (Imperial College London, 2014 Fields Medal) explains his recent work on the million-dollar Yang Mills Equation to Oxford Mathematician Dr Tom Crawford.
Recorded at the 2024 Heidelberg Laureate Forum. Thanks to the Heidelberg Laureate Forum Foundation.
Martin’s recent publications on the topic can be found at the links below.
Chandra, A., Chevyrev, I., Hairer, M. et al. Stochastic quantisation of Yang–Mills–Higgs in 3D. Invent. math. 237, 541–696 (2024). https://doi.org/10.1007/s00222-024-01264-2
Chandra, A., Chevyrev, I., Hairer, M. et al. Langevin dynamic for the 2D Yang–Mills measure. Publ.math.IHES 136, 1–147 (2022). https://doi.org/10.1007/s10240-022-00132-0
[8] arXiv:2411.03482
Ergodicity of 2D singular stochastic Navier-Stokes equations, Martin Hairer, Wenhao Zhao
Thanks to DeleteMe for sponsoring this video.
Other videos recorded at the 11th HLF.
Gerd Faltings (1986 Fields Medal): https://youtu.be/FVULa2yjUe0
Klein Bottles: https://youtu.be/gjbJB-YM7Rg
Po-Shen Loh: https://youtu.be/WTs5jpwqW4A
Previous videos recorded with Martin Hairer.
Random Tea: https://youtu.be/vDTqswT0ajk
Infinite Tetris: https://youtu.be/Z6XP3n-Sjiw
Brownian Castles: https://youtu.be/4jR8Sg4PYAA
Produced by Dr Tom Crawford at the University of Oxford. Tom is Public Engagement Lead at the Oxford University Department for Continuing Education: https://www.conted.ox.ac.uk/profiles/tom-crawford
For more maths content check out Toms website https://tomrocksmaths.com/
You can also follow Tom on Facebook, Twitter and Instagram @tomrocksmaths.
https://www.facebook.com/tomrocksmaths/
https://twitter.com/tomrocksmaths
https://www.instagram.com/tomrocksmaths/
With thanks to
Huel
Oxford University
St Edmund Hall
Oxford University Department of Continuing Education
Sidney Sussex College
Netflix
Dmitry Tonkonog
Culinan Studio
Faulkes Flying Foundation Yang Mills Mass Gap Hypothesis with Martin Hairer (2014 Fields Medal)](https://i.ytimg.com/vi/Ae9lTCUzJjE/mqdefault.jpg)

