A more accurate algorithm for computing the Christoffel transformation
A monic Jacobi matrix is a tridiagonal matrix which contains the parameters of the three-term recurrence relation satisfied by the sequence of monic polynomials orthogonal with respect to a measure. The basic Christoffel transformation with shift α transforms the monic Jacobi matrix associated with...
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Veröffentlicht in: | Journal of computational and applied mathematics 2007-08, Vol.205 (1), p.567-582 |
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description | A monic Jacobi matrix is a tridiagonal matrix which contains the parameters of the three-term recurrence relation satisfied by the sequence of monic polynomials orthogonal with respect to a measure. The basic Christoffel transformation with shift
α
transforms the monic Jacobi matrix associated with a measure
d
μ
into the monic Jacobi matrix associated with
(
x
-
α
)
d
μ
. This transformation is known for its numerous applications to quantum mechanics, integrable systems, and other areas of mathematics and mathematical physics. From a numerical point of view, the Christoffel transformation is essentially computed by performing one step of the LR algorithm with shift, but this algorithm is not stable. We propose a more accurate algorithm, estimate its forward errors, and prove that it is forward stable, i.e., that the obtained forward errors are of similar magnitude to those produced by a backward stable algorithm. This means that the magnitude of the errors is the best one can expect, because it reflects the sensitivity of the problem to perturbations in the input data. |
doi_str_mv | 10.1016/j.cam.2006.05.027 |
format | Article |
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α
transforms the monic Jacobi matrix associated with a measure
d
μ
into the monic Jacobi matrix associated with
(
x
-
α
)
d
μ
. This transformation is known for its numerous applications to quantum mechanics, integrable systems, and other areas of mathematics and mathematical physics. From a numerical point of view, the Christoffel transformation is essentially computed by performing one step of the LR algorithm with shift, but this algorithm is not stable. We propose a more accurate algorithm, estimate its forward errors, and prove that it is forward stable, i.e., that the obtained forward errors are of similar magnitude to those produced by a backward stable algorithm. This means that the magnitude of the errors is the best one can expect, because it reflects the sensitivity of the problem to perturbations in the input data.</description><identifier>ISSN: 0377-0427</identifier><identifier>EISSN: 1879-1778</identifier><identifier>DOI: 10.1016/j.cam.2006.05.027</identifier><identifier>CODEN: JCAMDI</identifier><language>eng</language><publisher>Amsterdam: Elsevier B.V</publisher><subject>Christoffel transformation ; Difference and functional equations, recurrence relations ; Exact sciences and technology ; Forward stability ; Fourier analysis ; LR algorithm ; Mathematical analysis ; Mathematics ; Numerical analysis ; Numerical analysis. Scientific computation ; Operator theory ; Roundoff error analysis ; Sciences and techniques of general use ; Special functions</subject><ispartof>Journal of computational and applied mathematics, 2007-08, Vol.205 (1), p.567-582</ispartof><rights>2006 Elsevier B.V.</rights><rights>2007 INIST-CNRS</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c467t-d59d2db67defe2291485758c8d05db6695938c349788e5601d12ce98da84124e3</citedby><cites>FETCH-LOGICAL-c467t-d59d2db67defe2291485758c8d05db6695938c349788e5601d12ce98da84124e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.cam.2006.05.027$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=18748038$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Bueno, María I.</creatorcontrib><creatorcontrib>Dopico, Froilán M.</creatorcontrib><title>A more accurate algorithm for computing the Christoffel transformation</title><title>Journal of computational and applied mathematics</title><description>A monic Jacobi matrix is a tridiagonal matrix which contains the parameters of the three-term recurrence relation satisfied by the sequence of monic polynomials orthogonal with respect to a measure. The basic Christoffel transformation with shift
α
transforms the monic Jacobi matrix associated with a measure
d
μ
into the monic Jacobi matrix associated with
(
x
-
α
)
d
μ
. This transformation is known for its numerous applications to quantum mechanics, integrable systems, and other areas of mathematics and mathematical physics. From a numerical point of view, the Christoffel transformation is essentially computed by performing one step of the LR algorithm with shift, but this algorithm is not stable. We propose a more accurate algorithm, estimate its forward errors, and prove that it is forward stable, i.e., that the obtained forward errors are of similar magnitude to those produced by a backward stable algorithm. This means that the magnitude of the errors is the best one can expect, because it reflects the sensitivity of the problem to perturbations in the input data.</description><subject>Christoffel transformation</subject><subject>Difference and functional equations, recurrence relations</subject><subject>Exact sciences and technology</subject><subject>Forward stability</subject><subject>Fourier analysis</subject><subject>LR algorithm</subject><subject>Mathematical analysis</subject><subject>Mathematics</subject><subject>Numerical analysis</subject><subject>Numerical analysis. Scientific computation</subject><subject>Operator theory</subject><subject>Roundoff error analysis</subject><subject>Sciences and techniques of general use</subject><subject>Special functions</subject><issn>0377-0427</issn><issn>1879-1778</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2007</creationdate><recordtype>article</recordtype><recordid>eNp9kEFLAzEQhYMoWKs_wNte9LZrks1uEjyVYlUoeNFziMlsm7K7qUlW8N-b0oI3TzMM35uZ9xC6JbgimLQPu8rooaIYtxVuKkz5GZoRwWVJOBfnaIZrzkvMKL9EVzHucAYlYTO0WhSDD1BoY6agU276jQ8ubYei86EwfthPyY2bIm2hWG6Di8l3HfRFCnqMGRl0cn68Rhed7iPcnOocfaye3pcv5frt-XW5WJeGtTyVtpGW2s-WW-iA0vyBaHgjjLC4yeNWNrIWpmaSCwFNi4kl1IAUVgtGKIN6ju6Pe_fBf00QkxpcNND3egQ_RUVlLWnLaAbJETTBxxigU_vgBh1-FMHqkJjaqZyYOiSmcKNyYllzd1quo9F9lx0aF_-EgjOBa5G5xyMH2em3g6CicTAasC6AScp698-VX75vgGc</recordid><startdate>20070801</startdate><enddate>20070801</enddate><creator>Bueno, María I.</creator><creator>Dopico, Froilán M.</creator><general>Elsevier B.V</general><general>Elsevier</general><scope>6I.</scope><scope>AAFTH</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20070801</creationdate><title>A more accurate algorithm for computing the Christoffel transformation</title><author>Bueno, María I. ; Dopico, Froilán M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c467t-d59d2db67defe2291485758c8d05db6695938c349788e5601d12ce98da84124e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2007</creationdate><topic>Christoffel transformation</topic><topic>Difference and functional equations, recurrence relations</topic><topic>Exact sciences and technology</topic><topic>Forward stability</topic><topic>Fourier analysis</topic><topic>LR algorithm</topic><topic>Mathematical analysis</topic><topic>Mathematics</topic><topic>Numerical analysis</topic><topic>Numerical analysis. Scientific computation</topic><topic>Operator theory</topic><topic>Roundoff error analysis</topic><topic>Sciences and techniques of general use</topic><topic>Special functions</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bueno, María I.</creatorcontrib><creatorcontrib>Dopico, Froilán M.</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Journal of computational and applied mathematics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bueno, María I.</au><au>Dopico, Froilán M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A more accurate algorithm for computing the Christoffel transformation</atitle><jtitle>Journal of computational and applied mathematics</jtitle><date>2007-08-01</date><risdate>2007</risdate><volume>205</volume><issue>1</issue><spage>567</spage><epage>582</epage><pages>567-582</pages><issn>0377-0427</issn><eissn>1879-1778</eissn><coden>JCAMDI</coden><abstract>A monic Jacobi matrix is a tridiagonal matrix which contains the parameters of the three-term recurrence relation satisfied by the sequence of monic polynomials orthogonal with respect to a measure. The basic Christoffel transformation with shift
α
transforms the monic Jacobi matrix associated with a measure
d
μ
into the monic Jacobi matrix associated with
(
x
-
α
)
d
μ
. This transformation is known for its numerous applications to quantum mechanics, integrable systems, and other areas of mathematics and mathematical physics. From a numerical point of view, the Christoffel transformation is essentially computed by performing one step of the LR algorithm with shift, but this algorithm is not stable. We propose a more accurate algorithm, estimate its forward errors, and prove that it is forward stable, i.e., that the obtained forward errors are of similar magnitude to those produced by a backward stable algorithm. This means that the magnitude of the errors is the best one can expect, because it reflects the sensitivity of the problem to perturbations in the input data.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/j.cam.2006.05.027</doi><tpages>16</tpages><oa>free_for_read</oa></addata></record> |
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source | ScienceDirect Journals (5 years ago - present); EZB-FREE-00999 freely available EZB journals |
subjects | Christoffel transformation Difference and functional equations, recurrence relations Exact sciences and technology Forward stability Fourier analysis LR algorithm Mathematical analysis Mathematics Numerical analysis Numerical analysis. Scientific computation Operator theory Roundoff error analysis Sciences and techniques of general use Special functions |
title | A more accurate algorithm for computing the Christoffel transformation |
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