Connolly, Michael P. and Higham, Nicholas J. (2022) Probabilistic Rounding Error Analysis of Householder QR Factorization. [MIMS Preprint] (Submitted)
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Abstract
When an $m\times n$ matrix is premultiplied by a product of $n$ Householder matrices the worst-case normwise rounding error bound is proportional to $mnu$, where $u$ is the unit roundoff. We prove that this bound can be replaced by one proportional to $\sqrt{mn}u$ that holds with high probability if the rounding errors are mean independent and of mean zero, under the assumption that a certain bound holds with probability $1$. The proof makes use of a matrix concentration inequality. In particular, this result applies to Householder QR factorization. The same square rooting of the error constant applies to two-sided transformations by Householder matrices and hence to standard QR-type algorithms for computing eigenvalues and singular values. It also applies to Givens QR factorization. These results complement recent probabilistic rounding error analysis results for inner-product based algorithms and show that the square rooting effect is widespread in numerical linear algebra. Our numerical experiments, which make use of a new backward error formula for QR factorization, show that the probabilistic bounds give a much better indicator of the actual backward errors and their rate of growth than the worst-case bounds.
Item Type: | MIMS Preprint |
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Uncontrolled Keywords: | floating-point arithmetic, backward error analysis, backward error, probabilistic rounding error analysis, Givens QR factorization, Householder QR factorization, matrix concentration inequality |
Subjects: | MSC 2010, the AMS's Mathematics Subject Classification > 15 Linear and multilinear algebra; matrix theory MSC 2010, the AMS's Mathematics Subject Classification > 65 Numerical analysis |
Depositing User: | Nick Higham |
Date Deposited: | 08 Aug 2022 18:59 |
Last Modified: | 08 Aug 2022 18:59 |
URI: | https://eprints.maths.manchester.ac.uk/id/eprint/2865 |
Available Versions of this Item
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Probabilistic Rounding Error Analysis of Householder QR Factorization. (deposited 15 Feb 2022 14:20)
- Probabilistic Rounding Error Analysis of Householder QR Factorization. (deposited 08 Aug 2022 18:59) [Currently Displayed]
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