001050048 001__ 1050048
001050048 005__ 20251219155103.0
001050048 0247_ $$2arXiv$$aarXiv:2505.10248
001050048 037__ $$aFZJ-2025-05762
001050048 088__ $$2arXiv$$aarXiv:2505.10248
001050048 1001_ $$0P:(DE-Juel1)188965$$aSalwa, Yasmeen Neyaz$$b0$$eCorresponding author$$ufzj
001050048 245__ $$aScalable 28nm IC implementation of coupled oscillator network featuring tunable topology and complexity
001050048 260__ $$c2025
001050048 3367_ $$0PUB:(DE-HGF)25$$2PUB:(DE-HGF)$$aPreprint$$bpreprint$$mpreprint$$s1766155727_16742
001050048 3367_ $$2ORCID$$aWORKING_PAPER
001050048 3367_ $$028$$2EndNote$$aElectronic Article
001050048 3367_ $$2DRIVER$$apreprint
001050048 3367_ $$2BibTeX$$aARTICLE
001050048 3367_ $$2DataCite$$aOutput Types/Working Paper
001050048 520__ $$aIntegrated circuit implementations of coupled oscillator networks have recently gained increased attention. The focus is usually on using these networks for analogue computing, for example for solving computational optimization tasks. For use within analog computing, these networks are run close to critical dynamics. On the other hand, such networks are also used as an analogy of transport networks such as electrical power grids to answer the question of how exactly such critical dynamic states can be avoided. However, simulating large network of coupled oscillators is computationally intensive, with specifc regards to electronic ones. We have developed an integrated circuit using integrated Phase-Locked Loop (PLL) with modifications, that allows to flexibly vary the topology as well as a complexity parameter of the network during operation. The proposed architecture, inspired by the brain, employs a clustered architecture, with each cluster containing 7 PLLs featuring programmable coupling mechanisms. Additionally, the inclusion of a RISC-V processor enables future algorithmic implementations. Thus, we provide a practical alternative for large-scale network simulations both in the field of analog computing and transport network stability research.
001050048 536__ $$0G:(DE-HGF)POF4-5234$$a5234 - Emerging NC Architectures (POF4-523)$$cPOF4-523$$fPOF IV$$x0
001050048 588__ $$aDataset connected to DataCite
001050048 7001_ $$0P:(DE-Juel1)176328$$aAshok, A.$$b1$$ufzj
001050048 7001_ $$0P:(DE-Juel1)133935$$aSchiek, Michael$$b2$$ufzj
001050048 7001_ $$0P:(DE-Juel1)159350$$aGrewing, C.$$b3$$ufzj
001050048 7001_ $$0P:(DE-Juel1)145837$$aZambanini, A.$$b4$$ufzj
001050048 7001_ $$0P:(DE-Juel1)142562$$avan Waasen, S.$$b5$$ufzj
001050048 8564_ $$uhttps://arxiv.org/abs/2505.10248
001050048 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)188965$$aForschungszentrum Jülich$$b0$$kFZJ
001050048 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)176328$$aForschungszentrum Jülich$$b1$$kFZJ
001050048 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)133935$$aForschungszentrum Jülich$$b2$$kFZJ
001050048 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)159350$$aForschungszentrum Jülich$$b3$$kFZJ
001050048 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)145837$$aForschungszentrum Jülich$$b4$$kFZJ
001050048 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)142562$$aForschungszentrum Jülich$$b5$$kFZJ
001050048 9131_ $$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$$vNeuromorphic Computing and Network Dynamics$$x0
001050048 920__ $$lyes
001050048 9201_ $$0I:(DE-Juel1)PGI-4-20110106$$kPGI-4$$lIntegrated Computing Architectures$$x0
001050048 980__ $$apreprint
001050048 980__ $$aEDITORS
001050048 980__ $$aVDBINPRINT
001050048 980__ $$aI:(DE-Juel1)PGI-4-20110106
001050048 980__ $$aUNRESTRICTED