We present a method for mitigating measurement errors on quantum computing platforms
that does not form the full assignment matrix, or its inverse, and works in a subspace defined …

Matrix computations are both fundamental and ubiquitous in computational science and its
vast application areas. Along with the development of more advanced computer systems …

Since the release of version 2.0 of the LAPACK software and the second edition of the
Users' Guide in 1994, LAPACK has been expanded further and has become an even wider …

In the nearly seven years since I finished writing the first edition of this book research on the
accuracy and stability of numerical algorithms has continued to flourish and mature. Our …

Which of the following statements is true?• Users want “black box” software that they can use
with complete confidence for general problem classes without having to understand the fine …

This textbook covers both direct and iterative methods for the solution of linear systems, least
squares problems, eigenproblems, and the singular value decomposition. Earlier versions …

Excerpt More than 25 years have passed since the first edition of this book was published in
1996. Least squares and least-norm problems have become more significant with every …

Functions of matrices have been studied for as long as matrix algebra itself. Indeed, in his
seminal A Memoir on the Theory of Matrices (1858), Cayley investigated the square root of a …

This book presents the fundamentals of sparse matrix algorithms, from theory to algorithms
and data structures to working code. The focus is on direct methods for solving systems of …

Following the initial release of LAPACK and the emerging importance of distributed memory
computing, work began on adapting LAPACK to distributed-memory architectures. Since …