Subtraction-Free Complexity, Cluster Transformations, and Spanning Trees

Subtraction-free computational complexity is the version of arithmetic circuit complexity that allows only three operations: addition, multiplication, and division. We use cluster transformations to design efficient subtraction-free algorithms for computing Schur functions and their skew, double, an...

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Published inFoundations of computational mathematics Vol. 16; no. 1; pp. 1 - 31
Main Authors Fomin, Sergey, Grigoriev, Dima, Koshevoy, Gleb
Format Journal Article
LanguageEnglish
Published New York Springer US 01.02.2016
Springer
Springer Nature B.V
Springer Verlag
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ISSN1615-3375
1615-3383
1615-3383
DOI10.1007/s10208-014-9231-y

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Abstract Subtraction-free computational complexity is the version of arithmetic circuit complexity that allows only three operations: addition, multiplication, and division. We use cluster transformations to design efficient subtraction-free algorithms for computing Schur functions and their skew, double, and supersymmetric analogues, thereby generalizing earlier results by P. Koev. We develop such algorithms for computing generating functions of spanning trees, both directed and undirected. A comparison to the lower bound due to M. Jerrum and M. Snir shows that in subtraction-free computations, “division can be exponentially powerful.” Finally, we give a simple example where the gap between ordinary and subtraction-free complexity is exponential.
AbstractList Subtraction-free computational complexity is the version of arithmetic circuit complexity that allows only three operations: addition, multiplication, and division. We use cluster transformations to design efficient subtraction-free algorithms for computing Schur functions and their skew, double, and supersymmetric analogues, thereby generalizing earlier results by P. Koev. We develop such algorithms for computing generating functions of spanning trees, both directed and undirected. A comparison to the lower bound due to M. Jerrum and M. Snir shows that in subtraction-free computations, “division can be exponentially powerful.” Finally, we give a simple example where the gap between ordinary and subtraction-free complexity is exponential.
Subtraction-free computational complexity is the version of arithmetic circuit complexity that allows only three operations: addition, multiplication, and division. We use cluster transformations to design efficient subtraction-free algorithms for computing Schur functions and their skew, double, and supersymmetric analogues, thereby generalizing earlier results by P. Koev. We develop such algorithms for computing generating functions of spanning trees, both directed and undirected. A comparison to the lower bound due to M. Jerrum and M. Snir shows that in subtraction-free computations, “division can be exponentially powerful.” Finally, we give a simple example where the gap between ordinary and subtraction-free complexity is exponential.
Audience Academic
Author Grigoriev, Dima
Koshevoy, Gleb
Fomin, Sergey
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  surname: Fomin
  fullname: Fomin, Sergey
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  surname: Grigoriev
  fullname: Grigoriev, Dima
  organization: CNRS, Mathématiques, Université de Lille
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  givenname: Gleb
  surname: Koshevoy
  fullname: Koshevoy, Gleb
  organization: Central Institute of Economics and Mathematics
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Issue 1
Keywords Primary 68Q25
Secondary 05E05
Cluster transformation
Arithmetic circuit
Star–mesh transformation
13F60
Schur function
Subtraction-free
Spanning tree
spanning tree
star-mesh transformation. 2010 Mathematics Subject Classification Primary 68Q25
cluster transformation
arithmetic circuit
Language English
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S Fomin (9231_CR11) 2002; 15
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I Goulden (9231_CR12) 1994; 170
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References_xml – reference: StrassenVVermeidung von DivisionenJ. Reine Angew. Math.19732641842025211680294.65021
– reference: W. T. Tutte, Graph theory as I have known it, Oxford University Press, 1998.
– reference: A. Aho, J. Hopcroft, and J. Ullman, The design and analysis of computer algorithms, Addison-Wesley, 1975.
– reference: A. I. Molev, Comultiplication rules for the double Schur functions and Cauchy identities, Electron. J. Combin.16 (2009), no. 1, Research Paper 13, 44 pp.
– reference: GrigorievDVorobjovNComplexity of Null- and Positivstellensatz proofsAnn. Pure Appl. Logic200211315316010.1016/S0168-0072(01)00055-018757400992.03073
– reference: KirchhoffGÜber die Auflösung der Gleichungen, auf welche man bei der Untersuchungen der linearen Vertheilung galvanischer Ströme geführt wirdAnn. Phys. Chem.18477249750810.1002/andp.18471481202
– reference: DemmelJKoevPAccurate and efficient evaluation of Schur and Jack functionsMath. Comp.20067525322323910.1090/S0025-5718-05-01780-121763971076.05083
– reference: GouldenIGreeneCA new tableau representation for supersymmetric Schur functionsJ. Algebra199417068770310.1006/jabr.1994.136113028640840.20008
– reference: LitvinovGLIdempotent and tropical mathematics; complexity of algorithms and interval analysisComput. Math. Appl.2013651483149610.1016/j.camwa.2012.09.0083061718
– reference: W. T. Tutte, Graph theory, Addison-Wesley, 1984.
– reference: P. W. Kasteleyn, Graph theory and crystal physics, in: Graph theory and theoretical physics, 43–110, Academic Press, 1967.
– reference: BerensteinAFominSZelevinskyAParametrizations of canonical bases and totally positive matricesAdv. Math.19961224914910.1006/aima.1996.005714054490966.17011
– reference: SchnorrCPA lower bound on the number of additions in monotone computationsTheor. Comput. Sci.1976230531510.1016/0304-3975(76)90083-94185170342.68024
– reference: J. Riordan, Review MR0022160 (9,166f), Math. Reviews, AMS, 1948.
– reference: D. G. Wagner, Matroid inequalities from electrical network theory, Electron. J. Combin.11 (2004/06), no. 2, Article 1, 17 pp.
– reference: KoevPAccurate computations with totally nonnegative matricesSIAM J. Matrix Anal. Appl.20072973175110.1137/04061903X23384601198.65057
– reference: B. Bollobás, Modern graph theory, Springer, 1998.
– reference: DemmelJGuMEisenstatSSlapničarIVeselićKDrmačZComputing the singular value decomposition with high relative accuracyLinear Algebra Appl.19992991–3218010.1016/S0024-3795(99)00134-217237090952.65032
– reference: FominSZelevinskyACluster algebras I: FoundationsJ. Amer. Math. Soc.20021549752910.1090/S0894-0347-01-00385-X18876421021.16017
– reference: I. G. Macdonald, Symmetric functions and Hall polynomials, Oxford Mathematical Monographs, 1999.
– reference: NarayananHOn the complexity of computing Kostka numbers and Littlewood-Richardson coefficientsJ. Algebraic Combin.20062434735410.1007/s10801-006-0008-522600221101.05066
– reference: V. I. Danilov, A. V. Karzanov, and G. A. Koshevoy, Systems of separated sets and their geometric models, Uspehi Mat. Nauk, 65 (2010), 67-152 (in Russian); English translation in Russian Math. Surveys65 (2010), no. 4, 659–740.
– reference: JerrumMSnirMSome exact complexity results for straight-line computations over semiringsJ. Assoc. Comput. Mach.19822987489710.1145/322326.3223416667830485.68038
– reference: C. Chan, V. Drensky, A. Edelman, R. Kan, and P. Koev, On computing Schur functions and series thereof, preprint, 2008.
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Snippet Subtraction-free computational complexity is the version of arithmetic circuit complexity that allows only three operations: addition, multiplication,...
Subtraction-free computational complexity is the version of arithmetic circuit complexity that allows only three operations: addition, multiplication, and...
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SubjectTerms Algorithms
Analysis
Applications of Mathematics
Clusters
Complexity
Computation
Computational complexity
Computer Science
Dividing (mathematics)
Division
Economics
Graph theory
Linear and Multilinear Algebras
Lower bounds
Math Applications in Computer Science
Mathematical analysis
Mathematical models
Mathematics
Mathematics and Statistics
Matrix Theory
Numerical Analysis
Subtraction
Supersymmetry
Transformations
Transformations (mathematics)
Trees
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Title Subtraction-Free Complexity, Cluster Transformations, and Spanning Trees
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