A. Hoekstra, B. Chopard, and P. Coveney, Multiscale modelling and simulation: a position paper, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, vol.15, issue.2, pp.372-2014, 2021.
DOI : 10.1007/s00466-013-0948-2

D. Vicino, O. Dalle, and G. Wainer, A data type for discretized time representation in DEVS, Proceedings of the Seventh International Conference on Simulation Tools and Techniques, 2014.
DOI : 10.4108/icst.simutools.2014.254803
URL : https://hal.archives-ouvertes.fr/hal-01055555

B. Zeigler, H. Praehofer, and T. Kim, Theory of Modeling and Simulation: Integrating Discrete Event and Continuous Complex Dynamic Systems, 2000.

R. Gattass and E. Mazur, Femtosecond laser micromachining in transparent materials, Nature Photonics, vol.12, issue.4, pp.219-225, 2008.
DOI : 10.1364/OPEX.12.002120

G. Ben-nissan and S. M. , Capturing protein structural kinetics by mass spectrometry, Chemical Society Reviews, vol.9, issue.7, pp.3627-3664, 2011.
DOI : 10.1074/mcp.M900620-MCP200

K. , Scientific background on the Nobel Prize in Chemistry 2013, The Royal Swedish Academy of Sciences, p.2013

F. Castiglione, F. Pappalardo, C. Bianca, G. Russo, and S. Motta, Modeling Biology Spanning Different Scales: An Open Challenge, BioMed Research International, vol.11, issue.3, 2014.
DOI : 10.2196/ijmr.2092
URL : https://hal.archives-ouvertes.fr/hal-01308210

C. Bettini, C. Dyreson, W. Evans, R. Snodgrass, and X. Wang, Temporal Databases: Research and Practice, chapter A glossary of time granularity concepts, pp.406-413, 1998.

C. Bettini, X. Wang, and S. Jajodia, A general framework for time granularity and its application to temporal reasoning, Annals of Mathematics and Artificial Intelligence, vol.22, issue.1/2, pp.29-58, 1998.
DOI : 10.1023/A:1018938007511

S. Guo, X. Hu, and W. X. , On time granularity and event granularity in simulation service composition (WIP), Proceedings of the Symposium on Theory of Modeling & Simulation, p.2012

R. Goldstein, S. Breslav, and A. Khan, A quantum of continuous simulated time, Proceedings of the Symposium on Theory of Modeling & Simulation, p.2016

P. Reynolds and A. Natrajan, Consistency maintenance in multiresolution simulation, ACM Transactions on Modeling and Computer Simulation, vol.7, issue.3, pp.368-392, 1997.
DOI : 10.1145/259207.259235

P. Davis and J. Bigelow, Experiments in Multiresolution Modeling (MRM) Monograph Reports, 1998.

M. Heiner and D. Gilbert, BioModel engineering for multiscale Systems Biology, Progress in Biophysics and Molecular Biology, vol.111, issue.2-3, pp.119-128, 2013.
DOI : 10.1016/j.pbiomolbio.2012.10.001

J. Dada and P. Mendes, Multi-scale modelling and simulation in systems biology, Integrative Biology, vol.26, issue.9, pp.86-96, 2011.
DOI : 10.1093/bioinformatics/btq069

Z. Qu, A. Garfinkel, J. Weiss, and M. Nivala, Multi-scale modeling in biology: How to bridge the gaps between scales?, Progress in Biophysics and Molecular Biology, vol.107, issue.1, pp.21-31, 2011.
DOI : 10.1016/j.pbiomolbio.2011.06.004

J. Elliott, Novel approaches to multiscale modelling in materials science, International Materials Reviews, vol.398, issue.6727, pp.207-225, 2011.
DOI : 10.1063/1.1743957

A. Brandt, Multiscale Scientific Computation: Review 2001, Multiscale and multiresolution methods, pp.3-95, 2000.
DOI : 10.1007/978-3-642-56205-1_1

E. Weinan, Principles of Multiscale Modeling, 2011.

M. Saunders and G. Voth, Coarse-Graining Methods for Computational Biology, Annual Review of Biophysics, vol.42, issue.1, pp.73-93, 2013.
DOI : 10.1146/annurev-biophys-083012-130348

S. Shirazi, A. , V. Mammen, S. , and J. C. , Abstraction of agent interaction processes: Towards large-scale multi-agent models. Simulation: Transactions of the Society for Modeling and Simulation International, pp.524-538, 2013.

W. Dzwinel, R. Wciss-lo, D. Yuen, and M. S. Pam, particle automata in modeling of multiscale biological systems, ACM Transactions on Modeling and Computer SimulationTOMACS), vol.26, issue.3, p.2016

F. Abraham, J. Broughton, N. Bernstein, and E. Kaxiras, Spanning the length scales in dynamic simulation, Computers in Physics, vol.12, issue.6, pp.538-546, 1998.
DOI : 10.1063/1.168756

T. Brereton, D. Kroese, O. Stenzel, V. Schmidt, and B. Baumeier, Efficient simulation of charge transport in deep-trap media, Proceedings Title: Proceedings of the 2012 Winter Simulation Conference (WSC), 2012.
DOI : 10.1109/WSC.2012.6465003

V. Nguyen, M. Stroeven, and L. Sluys, Multiscale continuous and discontinous modeling of heterogeneous materials: A review on recent developments, Journal of Multiscale Modelling, issue.04, pp.3229-270, 2011.

I. Kevrekidis, C. Gear, and G. Hummer, Equation-free: The computer-aided analysis of complex multiscale systems, AIChE Journal, vol.124, issue.423, pp.1346-1355, 2004.
DOI : 10.1021/ja025789n

E. Weinan, B. Engquist, X. Li, W. Ren, and E. Vanden-eijnden, Heterogeneous multiscale methods: A review, Communications in Computational Physics, vol.2, issue.3, pp.367-450, 2007.

E. Weinan, W. Ren, and E. Vanden-eijnden, A general strategy for designing seamless multiscale methods, Journal of Computational Physics, vol.228, issue.15, pp.5437-5453, 2009.

D. Lockerby, A. Patronis, M. Borg, and R. Jm, Asynchronous coupling of hybrid models for efficient simulation of multiscale systems, Journal of Computational Physics, vol.284, pp.261-272, 2015.
DOI : 10.1016/j.jcp.2014.12.035

P. Fritzson and V. Engelson, Modelica ??? A unified object-oriented language for system modeling and simulation, Proceedings of the European Conference on Object-Oriented Programming, 1998.
DOI : 10.1007/BFb0054087
URL : http://www.ifs.uni-linz.ac.at/~ecoop/cd/papers/1445/14450067.pdf

H. Vangheluwe, J. De-lara, and P. Mosterman, An introduction to multiparadigm modelling and simulation, Proceedings of the Conference on AI, Simulation and Planning in High Automony Systems (AIS), 2000.

D. Groen, S. Zasada, and P. Coveney, Survey of Multiscale and Multiphysics Applications and Communities, Computing in Science & Engineering, vol.16, issue.2, pp.34-43, 2014.
DOI : 10.1109/MCSE.2013.47
URL : http://arxiv.org/pdf/1208.6444

A. Van-elteren, I. Pelupessy, and S. Zwart, Multiscale and multi-domain computational astrophysics, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, pp.372-2014, 2021.

W. Goddard, B. Merinov, A. Van-duin, and J. T. , Multi-paradigm multi-scale simulations for fuel cell catalysts and membranes, Molecular Simulation, vol.357, issue.3-4, pp.3-4251, 2006.
DOI : 10.1016/0022-0728(93)80380-Z
URL : http://csdrm.caltech.edu/publications/cit-asci-tr/cit-asci-tr347.pdf

K. Regenauer-lieb, M. Veveakis, T. Poulet, F. Wellmann, A. Karrech et al., Multiscale coupling and multiphysics approaches in earth sciences: Theory, Journal of Coupled Systems and Multiscale Dynamics, vol.1, issue.1, pp.49-73, 2013.
DOI : 10.1166/jcsmd.2013.1012

B. Chopard, J. Borgdorff, A. Hoekstra, R. Ewald, M. John et al., A framework for multi-scale modelling Combining micro and macromodeling in DEVS for computational biology, 2014. 37. Uhrmacher AM, Proceedings of the Winter Simulation Conference (WSC), 2007.

J. Santucci, L. Capocchi, and B. Zeigler, System entity structure extension to integrate abstraction hierarchies and time granularity into DEVS modeling and simulation, SIMULATION, vol.6, issue.4, pp.92747-769, 2016.
DOI : 10.1177/875647939000600106

, 39. golang.org. The Go Programming Language: Packages (Software Version 1, p.2016

, 41. nsnam.org. ns-3 Discrete-Event Network Simulator Tutorial (Software Version ns-3, 2016.

D. Goldberg, What every computer scientist should know about floating-point arithmetic, ACM Computing Surveys, vol.23, issue.1, pp.5-48, 1991.
DOI : 10.1145/103162.103163

D. Rapaport, The Art of Molecular Dynamics, 2004.

D. Shaw, J. Grossman, J. Bank, B. Batson, J. Butts et al., Anton 2: Raising the Bar for Performance and Programmability in a Special-Purpose Molecular Dynamics Supercomputer, SC14: International Conference for High Performance Computing, Networking, Storage and Analysis, 2014.
DOI : 10.1109/SC.2014.9

P. Hartmann, Z. Donkó, P. Lévai, and G. Kalman, Molecular dynamics simulation of strongly coupled QCD plasmas, Nuclear Physics A, vol.774, pp.881-884, 2006.
DOI : 10.1016/j.nuclphysa.2006.06.157

L. Smolin, Atoms of space and time, Scientific American, vol.23, issue.4, pp.94-103, 2014.

M. Vogelsberger, S. Genel, V. Springel, P. Torrey, D. Sijacki et al., Properties of galaxies reproduced by a hydrodynamic simulation, Nature, vol.116, issue.7499, pp.509177-182, 2014.
DOI : 10.1086/382245

F. Adams and G. Laughlin, A dying universe: the long-term fate and evolutionof astrophysical objects, Reviews of Modern Physics, vol.210, issue.2, pp.337-372, 1997.
DOI : 10.1093/mnras/210.1.43
URL : http://arxiv.org/pdf/astro-ph/9701131

F. Wieland, The threshold of event simultaneity Simulation: Transactions of the Society for Modeling and Simulation International, pp.23-31, 1999.

B. Zeigler, Y. Moon, and K. D. , High performance modelling and simulation: Progress and challenges, 1996.

J. Lee, How do earthquake early warning systems work? Published online by National Geographic, 2013.

N. Josuttis, The C++ Standard Library: A Tutorial and Reference, 2012.

J. Nutaro, Building Software for Simulation: Theory and Algorithms with Applications in C++, 2011.
DOI : 10.1002/9780470877999

L. Lamport, Time, clocks, and the ordering of events in a distributed system, Communications of the ACM, vol.21, issue.7, pp.558-565, 1978.
DOI : 10.1145/359545.359563

D. Jefferson, Virtual time, ACM Transactions on Programming Languages and Systems, vol.7, issue.3, pp.404-425, 1985.
DOI : 10.1145/3916.3988

M. Raynal and M. Singhal, Logical time: capturing causality in distributed systems, Computer, vol.29, issue.2, pp.49-56, 1996.
DOI : 10.1109/2.485846
URL : http://www.cs.northwestern.edu/~fabianb/classes/eecs-345-w08/lectures/Raynal-LogicalTime.pdf