Brian Sutton
Brian Sutton is Associate Professor of Mathematics at RandolphMacon College in
Ashland, VA. His primary research areas are numerical linear algebra and random matrix
theory. He is the
First Place recipient of the Fourteenth
Leslie Fox Prize in numerical analysis for his work on computing the CS (CosineSine)
matrix decomposition, and his current work on the CS decomposition is funded by NSF
grant DMS0914559. With Alan Edelman, he founded the stochastic operator approach
to random matrix theory, which reinterprets finite random matrices as
discretizations of a select few continuous operators, moving the field into the
domain of functional analysis. At RandolphMacon, Brian has taught courses on
numerical analysis, differential equations, probability, and statistics, as well
as an interdisciplinary course on epidemiology.
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Curriculum vitae
CV (PDF)
Contact
bsutton@rmc.edu
http://faculty.rmc.edu/bsutton/
Copley 235
Department of Mathematics, RandolphMacon College,
PO Box 5005,
Ashland, VA 23005
Current courses
Please visit Moodle.
Software
Computing the complete CS decomposition (Fortran and MATLAB code)
Click on the links for manuscripts, presentation slides, and computer code.

The fundamental CS decomposition

Divide and conquer the CS decomposition

Submitted for publication.

Stable computation of the CS decomposition: simultaneous bidiagonalization

SIAM J. Matrix Anal. Appl. 33 (2012), no. 1, 1–21.

On the minimum semidefinite rank of a simple graph

With Matthew Booth, Philip Hackney, Benjamin Harris, Charles R. Johnson, Margaret Lay,
Terry D. Lenker, Lon H. Mitchell, Sivaram K. Narayan, and Amanda Pascoe.
Linear Multilinear Algebra 59 (2011), no. 5, 483–506.

Computing the complete CS decomposition

Computing the complete CS decomposition. Numer. Algorithms. 50 (2009),
no. 1, 33–65.

Implicit construction of multiple eigenvalues for trees

With Charles R. Johnson and Andrew J. Witt. Implicit construction of multiple
eigenvalues for trees. Linear Multilinear Algebra 57 (2009),
no. 4, 409–420.

The betaJacobi matrix model, the CS decomposition, and generalized singular
value problems

With Alan Edelman. The betaJacobi matrix model, the CS decomposition, and generalized singular
value problems. Found. Comput. Math. 8 (2008), no. 2, 259–285.

On the minimum rank of a positive semidefinite matrix with a given
graph

With Matthew Booth, Philip Hackney, Benjamin Harris, Charles R. Johnson,
Margaret Lay, Lon H. Mitchell, Sivaram K. Narayan, Amanda Pascoe, Kelly Steinmetz,
and Wendy Wang. On the minimum rank of a positive semidefinite matrix
with a given graph. SIAM J. Matrix Anal. Appl. 30 (2008), no. 2, 731–740.

From random matrices to stochastic operators

With Alan Edelman. From random matrices to stochastic operators. J. Stat. Phys.
127 (2007), no. 6, 1121–1165.

The Stochastic Operator Approach to Random Matrix Theory

The Stochastic Operator Approach to Random Matrix Theory. Ph.D. thesis,
Massachusetts Institute of Technology, 2005.

Tails of condition number distributions

With Alan Edelman. Tails of condition number distributions. SIAM J. Matrix
Anal. Appl. 27 (2005), no. 2, 547–560.

Hermitian matrices, eigenvalue multiplicities, and
eigenvector components

With Charles R. Johnson. Hermitian matrices, eigenvalue multiplicities, and
eigenvector components. SIAM J. Matrix Anal. Appl. 26 (2004/05), no. 2, 390–399.

On the relative position of multiple eigenvalues in the spectrum of an
Hermitian matrix with a given graph

With Charles R. Johnson, António Leal Duarte, Carlos M. Saiago, and Andrew J. Witt.
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.

Identification problem for the wave equation with Neumann data input
and Dirichlet data observations

With Xiaobing Feng, Suzanne Lenhart, Vladimir Protopopescu, and Lizabeth Rachele.
Identification problem for the wave equation with Neumann data input and Dirichlet data
observations. Nonlinear Anal. 52 (2003), no. 7, 1777–1795.
Some mostly older presentations.
Copyright 2010, Brian Sutton.