Mariana Bergonzi

@article{castro_discrete-event_2024,

title = {Discrete-event simulation of continuous-time systems: evolution and state of the art of quantized state system methods},

author = {Rodrigo Castro and Mariana Bergonzi and Ezequiel Pecker-Marcosig and Joaquín Fernández and Ernesto Kofman},

url = {https://journals.sagepub.com/doi/10.1177/00375497241230985},

doi = {10.1177/00375497241230985},

issn = {0037-5497, 1741-3133},

year  = {2024},

date = {2024-01-01},

urldate = {2025-07-01},

journal = {SIMULATION},

volume = {100},

number = {6},

pages = {613–638},

abstract = {In this work, we attempt to bring together the origins, main results, and recent advances on discrete-event simulation of continuous-time systems. Starting from the early approaches that aimed to represent continuous-time dynamics within the discrete-event system specification (DEVS) formalism framework, the work shows how these ideas gave place to the formalization of the quantized state system (QSS) family of numerical integration algorithms. Then, we describe the QSS algorithms, their properties, their extensions, and the main practical software tools implementing them. We also present a selection of simulation examples illustrating the main features and advantages through comparisons with state-of-the-art continuous-time simulation solvers.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{bergonzi_quantization-based_2024,

title = {Quantization-based simulation of spiking neurons: theoretical properties and performance analysis},

author = {Mariana Bergonzi and Joaquín Fernández and Rodrigo Castro and Alexandre Muzy and Ernesto Kofman},

url = {https://doi.org/10.1080/17477778.2023.2284143},

doi = {10.1080/17477778.2023.2284143},

issn = {1747-7778},

year  = {2024},

date = {2024-01-01},

urldate = {2025-07-01},

journal = {Journal of Simulation},

volume = {18},

number = {5},

pages = {789–812},

abstract = {In this work we present an exhaustive analysis of the use of Quantized State Systems (QSS) algorithms for the discrete event simulation of Leaky Integrate and Fire models of spiking neurons. Making use of some properties of these algorithms, we first derive theoretical error bounds for the sub-threshold dynamics as well as estimates of the computational costs as a function of the accuracy settings. Then, we corroborate those results on different simulation experiments, where we also study how these algorithms scale with the size of the network and its connectivity. The results obtained show that the QSS algorithms, without any type of optimisation or specialisation, obtain accurate results with low computational costs even in large networks with a high level of connectivity.},

note = {Publisher: Taylor & Francis 

_eprint: https://doi.org/10.1080/17477778.2023.2284143},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{bergonzi_discrete-time_2021,

title = {Discrete-Time Modeling of COVID-19 Propagation in Argentina with Explicit Delays},

author = {Mariana Bergonzi and Ezequiel Pecker-Marcosig and Ernesto Kofman and Rodrigo Castro},

doi = {10.1109/MCSE.2020.3040700},

issn = {1521-9615},

year  = {2021},

date = {2021-01-01},

journal = {Computing in Science & Engineering},

volume = {23},

number = {01},

pages = {35–45},

abstract = {We present a new deterministic discrete-Time compartmental model of COVID-19 that explicitly takes into account relevant delays related to the stages of the disease, its diagnosis and report system, allowing to represent the presence of imported cases. In addition to developing the model equations, we describe an automatic parameter fitting mechanism using official data on the spread of the virus in Argentina. The result consistently reflects the behavior of the disease with respect to characteristic times: latency, infectious period, report of cases (confirmed and dead), and allows for detecting automatically changes in the reproductive number and in the mortality factor. We also analyse the model's prediction capability and present simulation results assuming different future scenarios. We discuss usage of the model in a closed-loop control scheme, where the explicit presence of delays plays a key role in projecting more realistic dynamics than that of classic continuous-Time models.},

note = {Publisher: IEEE Computer Society},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{bergonzi_modelado_2020,

title = {Modelado con Retardos Explıcitos de la Propagacion de COVID-19 en Argentina},

author = {Mariana Bergonzi and Rodrigo Castro and Ernesto Kofman},

url = {https://fceia.unr.edu.ar/~kofman/files/covid19_AADECA.pdf},

year  = {2020},

date = {2020-01-01},

urldate = {2025-07-01},

keywords = {},

pubstate = {published},

tppubtype = {article}

}