Professor
Department of Mathematics
RandolphMacon College
Office: Copley 232
Email: bsutton@rmc.edu
Ph.D., Mathematics, Massachusetts Institute of Technology (2005)
Computational and applied mathematics, linear algebra, numerical analysis, random matrix theory
Courses
Visit canvas.rmc.edu.
CV
Book
Numerical Analysis: Theory and Experiments

 A textbook for an undergraduate course on numerical analysis prominently featuring Chebyshev methods.
 Published by SIAM. Also available from Amazon.
 A note from the author.
 Reviewed in MAA Reviews.
 Reviewed at zbMATH.
 On the Basic Library List (MAA’s Recommendations for Undergraduate Libraries).
 Sample chapters:
 An accompanying library of MATLAB codes is posted on GitHub.
Articles
 Sutton, Brian D. Simultaneous diagonalization of nearly commuting Hermitian matrices: doonethendotheother. Submitted.
 Sutton, Brian D. Numerical construction of structured matrices with given eigenvalues. Spec. Matrices. 7 (2019), no. 1, 263–271.
 Gawlik, Evan S.; Nakatsukasa, Yuji; Sutton, Brian D. A backward stable algorithm for computing the CS decomposition via the polar decomposition. SIAM J. Matrix Anal. Appl. 39 (2018), no. 3, 1448–1469.
 Edelman, Alan; Persson, PerOlof; Sutton, Brian D. Lowtemperature random matrix theory at the soft edge. J. Math. Phys. 55 (2014), no. 6, 063302, 12 pp.
 Kang, Kingston; Lothian, William; Sears, Jessica; Sutton, Brian D. Simultaneous multidiagonalization for the CS decomposition. Numer. Algorithms 66 (2014), no. 3, 479–493.
 Sutton, Brian D. Divide and conquer the CS decomposition. SIAM J. Matrix Anal. Appl. 34 (2013), no. 2, 417–444.
 Sutton, Brian D. Stable computation of the CS decomposition: simultaneous bidiagonalization. SIAM J. Matrix Anal. Appl. 33 (2012), no. 1, 1–21.
 Booth, Matthew; Hackney, Philip; Harris, Benjamin; Johnson, Charles R.; Lay, Margaret; Lenker, Terry D.; Mitchell, Lon H.; Narayan, Sivaram K.; Pascoe, Amanda; Sutton, Brian D. On the minimum semidefinite rank of a simple graph. Linear Multilinear Algebra 59 (2011), no. 5, 483–506.
 Johnson, Charles R.; Sutton, Brian D.; Witt, Andrew J. Implicit construction of multiple eigenvalues for trees. Linear Multilinear Algebra 57 (2009), no. 4, 409–420.
 Sutton, Brian D. Computing the complete CS decomposition. Numer. Algorithms 50 (2009), no. 1, 33–65.
 Booth, Matthew; Hackney, Philip; Harris, Benjamin; Johnson, Charles R.; Lay, Margaret; Mitchell, Lon H.; Narayan, Sivaram K.; Pascoe, Amanda; Steinmetz, Kelly; Sutton, Brian D.; Wang, Wendy. On the minimum rank among positive semidefinite matrices with a given graph. SIAM J. Matrix Anal. Appl. 30 (2008), no. 2, 731–740.
 Edelman, Alan; Sutton, Brian D. The betaJacobi matrix model, the CS decomposition, and generalized singular value problems. Found. Comput. Math. 8 (2008), no. 2, 259–285.
 Edelman, Alan; Sutton, Brian D. From random matrices to stochastic operators. J. Stat. Phys. 127 (2007), no. 6, 1121–1165.
 Edelman, Alan; Sutton, Brian D. Tails of condition number distributions. SIAM J. Matrix Anal. Appl. 27 (2005), no. 2, 547–560.
 Johnson, Charles R.; Sutton, Brian D. Hermitian matrices, eigenvalue multiplicities, and eigenvector components. SIAM J. Matrix Anal. Appl. 26 (2004/05), no. 2, 390–399.
 Johnson, Charles R.; Duarte, António Leal; Saiago, Carlos M.; Sutton, Brian D.; Witt, Andrew J. On the relative position of multiple eigenvalues in the spectrum of an Hermitian matrix with a given graph. Special issue on nonnegative matrices, Mmatrices and their generalizations (Oberwolfach, 2000). Linear Algebra Appl. 363 (2003), 147–159.
 Feng, Xiaobing; Lenhart, Suzanne; Protopopescu, Vladimir; Rachele, Lizabeth; Sutton, Brian. Identification problem for the wave equation with Neumann data input and Dirichlet data observations. Nonlinear Anal. 52 (2003), no. 7, 1777–1795.
Additional publications
 Edelman, Alan; Sutton, Brian D.; Wang, Yuyang . Random matrix theory, numerical computation and applications. Modern aspects of random matrix theory, 53–82, Proc. Sympos. Appl. Math., 72, Amer. Math. Soc., Providence, RI, 2014.
 Sutton, Brian D. The stochastic operator approach to random matrix theory. Thesis (Ph.D.)–Massachusetts Institute of Technology. 2005.
Posts
 What’s that shape? Instability in interpolation (22 Jun 2019)
 Graphical Big O (29 Aug 2019)
 The condition number for differential equations (25 Jan 2020)