001041472 001__ 1041472
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001041472 037__ $$aFZJ-2025-02265
001041472 041__ $$aEnglish
001041472 1001_ $$0P:(DE-Juel1)176305$$aLinssen, Charl$$b0$$eCorresponding author$$ufzj
001041472 245__ $$aODE-toolbox 2.5.8
001041472 250__ $$a2.5.8
001041472 260__ $$c2025
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001041472 520__ $$aChoosing the optimal solver for systems of ordinary differential equations (ODEs) is a critical step in dynamical systems simulation. ODE-toolbox is a Python package that assists in solver benchmarking, and recommends solvers on the basis of a set of user-configurable heuristics. For all dynamical equations that admit an analytic solution, ODE-toolbox generates propagator matrices that allow the solution to be calculated at machine precision. For all others, first-order update expressions are returned based on the Jacobian matrix.In addition to continuous dynamics, discrete events can be used to model instantaneous changes in system state, such as a neuronal action potential. These can be generated by the system under test as well as applied as external stimuli, making ODE-toolbox particularly well-suited for applications in computational neuroscience.
001041472 536__ $$0G:(DE-HGF)POF4-5111$$a5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511)$$cPOF4-511$$fPOF IV$$x0
001041472 536__ $$0G:(DE-HGF)POF4-5234$$a5234 - Emerging NC Architectures (POF4-523)$$cPOF4-523$$fPOF IV$$x1
001041472 536__ $$0G:(DE-HGF)POF4-5235$$a5235 - Digitization of Neuroscience and User-Community Building (POF4-523)$$cPOF4-523$$fPOF IV$$x2
001041472 536__ $$0G:(EU-Grant)945539$$aHBP SGA3 - Human Brain Project Specific Grant Agreement 3 (945539)$$c945539$$fH2020-SGA-FETFLAG-HBP-2019$$x3
001041472 536__ $$0G:(DE-Juel1)Helmholtz-SLNS$$aSLNS - SimLab Neuroscience (Helmholtz-SLNS)$$cHelmholtz-SLNS$$x4
001041472 536__ $$0G:(DE-Juel1)PHD-NO-GRANT-20170405$$aPhD no Grant - Doktorand ohne besondere Förderung (PHD-NO-GRANT-20170405)$$cPHD-NO-GRANT-20170405$$x5
001041472 536__ $$0G:(EU-Grant)101147319$$aEBRAINS 2.0 - EBRAINS 2.0: A Research Infrastructure to Advance Neuroscience and Brain Health (101147319)$$c101147319$$fHORIZON-INFRA-2022-SERV-B-01$$x6
001041472 7001_ $$0P:(DE-HGF)0$$aJain, Shraddha$$b1
001041472 7001_ $$0P:(DE-Juel1)186954$$aBabu, Pooja$$b2$$ufzj
001041472 7001_ $$0P:(DE-Juel1)151166$$aMorrison, Abigail$$b3$$ufzj
001041472 7001_ $$0P:(DE-Juel1)142538$$aEppler, Jochen Martin$$b4
001041472 8564_ $$uhttps://github.com/nest/ode-toolbox/releases/tag/v2.5.8
001041472 909CO $$ooai:juser.fz-juelich.de:1041472$$popenaire$$pVDB$$pec_fundedresources
001041472 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)176305$$aForschungszentrum Jülich$$b0$$kFZJ
001041472 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)186954$$aForschungszentrum Jülich$$b2$$kFZJ
001041472 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)151166$$aForschungszentrum Jülich$$b3$$kFZJ
001041472 9131_ $$0G:(DE-HGF)POF4-511$$1G:(DE-HGF)POF4-510$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5111$$aDE-HGF$$bKey Technologies$$lEngineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action$$vEnabling Computational- & Data-Intensive Science and Engineering$$x0
001041472 9131_ $$0G:(DE-HGF)POF4-523$$1G:(DE-HGF)POF4-520$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5234$$aDE-HGF$$bKey Technologies$$lNatural, Artificial and Cognitive Information Processing$$vNeuromorphic Computing and Network Dynamics$$x1
001041472 9131_ $$0G:(DE-HGF)POF4-523$$1G:(DE-HGF)POF4-520$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5235$$aDE-HGF$$bKey Technologies$$lNatural, Artificial and Cognitive Information Processing$$vNeuromorphic Computing and Network Dynamics$$x2
001041472 9141_ $$y2025
001041472 9201_ $$0I:(DE-Juel1)JSC-20090406$$kJSC$$lJülich Supercomputing Center$$x0
001041472 9201_ $$0I:(DE-Juel1)IAS-6-20130828$$kIAS-6$$lComputational and Systems Neuroscience$$x1
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