000885756 001__ 885756
000885756 005__ 20240313094848.0
000885756 0247_ $$2doi$$a10.1088/1751-8121/abb169
000885756 0247_ $$2ISSN$$a0022-3689
000885756 0247_ $$2ISSN$$a0301-0015
000885756 0247_ $$2ISSN$$a0305-4470
000885756 0247_ $$2ISSN$$a1361-6447
000885756 0247_ $$2ISSN$$a1751-8113
000885756 0247_ $$2ISSN$$a1751-8121
000885756 0247_ $$2ISSN$$a2051-2155
000885756 0247_ $$2ISSN$$a2051-2163
000885756 0247_ $$2Handle$$a2128/25921
000885756 0247_ $$2WOS$$aWOS:000576613600001
000885756 037__ $$aFZJ-2020-04068
000885756 082__ $$a530
000885756 1001_ $$0P:(DE-Juel1)144806$$aHelias, Moritz$$b0$$eCorresponding author
000885756 245__ $$aMomentum-dependence in the infinitesimal Wilsonian renormalization group
000885756 260__ $$aBristol$$bIOP Publ.$$c2020
000885756 3367_ $$2DRIVER$$aarticle
000885756 3367_ $$2DataCite$$aOutput Types/Journal article
000885756 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1603097055_22881
000885756 3367_ $$2BibTeX$$aARTICLE
000885756 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000885756 3367_ $$00$$2EndNote$$aJournal Article
000885756 520__ $$aWilson's original formulation of the renormalization group is perturbative in nature. We here present an alternative derivation of the infinitesimal momentum shell renormalization group, akin to the Wegner and Houghton scheme, that is a priori exact. We show that the momentum-dependence of vertices is key to obtain a diagrammatic framework that has the same one-loop structure as the vertex expansion of the Wetterich equation. Momentum dependence leads to a delayed functional differential equation in the cutoff parameter. Approximations are then made at two points: truncation of the vertex expansion and approximating the functional form of the momentum dependence by a momentum-scale expansion. We exemplify the method on the scalar phiv4-theory, computing analytically the Wilson–Fisher fixed point, its anomalous dimension η(d) and the critical exponent ν(d) non-perturbatively in d ∈ [3, 4] dimensions. The results are in reasonable agreement with the known values, despite the simplicity of the method.
000885756 536__ $$0G:(DE-HGF)POF3-574$$a574 - Theory, modelling and simulation (POF3-574)$$cPOF3-574$$fPOF III$$x0
000885756 536__ $$0G:(EU-Grant)785907$$aHBP SGA2 - Human Brain Project Specific Grant Agreement 2 (785907)$$c785907$$fH2020-SGA-FETFLAG-HBP-2017$$x1
000885756 536__ $$0G:(DE-82)EXS-SF-neuroIC002$$aneuroIC002 - Recurrence and stochasticity for neuro-inspired computation (EXS-SF-neuroIC002)$$cEXS-SF-neuroIC002$$x2
000885756 536__ $$0G:(DE-Juel-1)BMBF-01IS19077A$$aRenormalizedFlows - Transparent Deep Learning with Renormalized Flows (BMBF-01IS19077A)$$cBMBF-01IS19077A$$x3
000885756 588__ $$aDataset connected to CrossRef
000885756 773__ $$0PERI:(DE-600)1363010-6$$a10.1088/1751-8121/abb169$$gVol. 53, no. 44, p. 445004 -$$n44$$p445004 -$$tJournal of physics / A$$v53$$x1751-8121$$y2020
000885756 8564_ $$uhttps://juser.fz-juelich.de/record/885756/files/Helias_2020_J._Phys._A%20_Math._Theor._53_445004.pdf$$yOpenAccess
000885756 8564_ $$uhttps://juser.fz-juelich.de/record/885756/files/Helias_2020_J._Phys._A%20_Math._Theor._53_445004.pdf?subformat=pdfa$$xpdfa$$yOpenAccess
000885756 8767_ $$88163081$$92020-11-26$$d2020-12-02$$eHybrid-OA$$jZahlung erfolgt$$zBelegnr. 1200160393
000885756 909CO $$ooai:juser.fz-juelich.de:885756$$pdnbdelivery$$popenCost$$pec_fundedresources$$pVDB$$pdriver$$pOpenAPC$$popen_access$$popenaire
000885756 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)144806$$aForschungszentrum Jülich$$b0$$kFZJ
000885756 9131_ $$0G:(DE-HGF)POF3-574$$1G:(DE-HGF)POF3-570$$2G:(DE-HGF)POF3-500$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bKey Technologies$$lDecoding the Human Brain$$vTheory, modelling and simulation$$x0
000885756 9141_ $$y2020
000885756 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2020-02-27
000885756 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2020-02-27
000885756 915__ $$0LIC:(DE-HGF)CCBY4$$2HGFVOC$$aCreative Commons Attribution CC BY 4.0
000885756 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search$$d2020-02-27
000885756 915__ $$0StatID:(DE-HGF)1150$$2StatID$$aDBCoverage$$bCurrent Contents - Physical, Chemical and Earth Sciences$$d2020-02-27
000885756 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2020-02-27
000885756 915__ $$0StatID:(DE-HGF)0110$$2StatID$$aWoS$$bScience Citation Index$$d2020-02-27
000885756 915__ $$0StatID:(DE-HGF)0111$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2020-02-27
000885756 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5$$d2020-02-27
000885756 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
000885756 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC$$d2020-02-27
000885756 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bJ PHYS A-MATH THEOR : 2018$$d2020-02-27
000885756 915__ $$0StatID:(DE-HGF)0430$$2StatID$$aNational-Konsortium$$d2020-02-27$$wger
000885756 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2020-02-27
000885756 915__ $$0StatID:(DE-HGF)0420$$2StatID$$aNationallizenz$$d2020-02-27$$wger
000885756 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2020-02-27
000885756 920__ $$lyes
000885756 9201_ $$0I:(DE-Juel1)INM-6-20090406$$kINM-6$$lComputational and Systems Neuroscience$$x0
000885756 9801_ $$aFullTexts
000885756 980__ $$ajournal
000885756 980__ $$aVDB
000885756 980__ $$aUNRESTRICTED
000885756 980__ $$aI:(DE-Juel1)INM-6-20090406
000885756 980__ $$aAPC
000885756 981__ $$aI:(DE-Juel1)IAS-6-20130828