Theoretical Physics Seminar (WS23/24)

Networks: Theory and Application to Biological and Social Systems

Ort: Gebäude E2 6 - Seminarraum E11 (0.11)
Zeit: Dienstag, 10 Uhr (c.t.)
Beginn: 24.10.2023
Veranstaltungsnummer: 146214
Poster: poster_ws23_networks.pdf

Zielgruppe: Das Seminar gibt Einblicke in unsere aktuelle Forschung im Bereich Network Science. Es ist für Studierende, die Interesse an einer Master- oder Bachelorarbeit bei uns haben, besonders zu empfehlen. Studierende, die einen Seminarschein erlangen wollen (z.B. im Master-Studiengang Physik), sind uns herzlichwillkommen.

Kurzzusammenfassung: Die komplexe Netzwerke stellt ein sehr aktuelles, interdisziplinäres Forschungsgebiet dar und findet Anwendung in den unterschiedlichsten Gebieten der Physik, Chemie, Biologie, Technologie sowie zur Beschreibung sozio-ökonomischer Systeme, zum Beispiel in gekoppelten Lasern, neuronalen Netzwerken, genetischen Regulationsnetzwerken, elektronischen Schaltkreisen, chemischen oder elektrochemischen Oszillatoren, den Strom-, Straßen- und Schienennetzen oder dem Internet. Im Seminar liegt der Fokus auf Netzwerkmodellen, Charakterisierung von Netzwerkeigenschaften und Anwendungen. Letztere reichen von biologischen Systeme über ankheitsausbreitung bis hin zu technologischen Beispielen.

Ansprechpartner:
Dr. habil. Philipp Hövel: philipp.hoevel(at)uni-saarland.de, Raum 4.03, Gebäude E2 6

Literatur

• [ALB02a] R. Albert and A. L. Barabási: Statistical mechanics of complex networks, Rev. Mod. Phys. 74, 47–97 (2002).
• [BAC12] L. Backstrom, P. Boldi, M. Rosa, J. Ugander, and S. Vigna: Four degrees of separation, in Proceedings of the 4th Annual ACM Web Science Conference, edited by 2012), pp. 33–42.
• [BAD22a] A. Badie-Modiri, A.K. Rizi, M. Karsai, M. Kivelä: Directed Percolation in Temporal Networks, Phys. Rev. Research 4, L022047 (2022).
• [BAD22] A. Badie-Modiri, A. K. Rizi, M. Karsai, M. Kivelä: Directed Percolation in Random Temporal Network Models with Heterogeneities, Phys. Rev. E 105, 054313 (2022).
• [BAR03a] A. L. Barabási and E. Bonabeau: Scale-free networks, Sci. Am. 288, 50–59 (2003).
• [BAR16] A. L. Barabási: Network Science (Cambridge University Press, Cambridge, 2016). 
• [BAS06a] D. S. Bassett and E. T. Bullmore: Small-world brain networks, Neuroscientist 12, 512–523 (2006). 
• [BAS17] D. S. Bassett and O. Sporns: Network neuroscience, Nat. Neurosci. 20, 353 (2017), Review Article.
• [COO19] S. J. Cook, T. A. Jarrell, C. A. Brittin, Y. Wang, A. E. Bloniarz, M. A. Yakovlev, K. C. Nguyen, L. T.-H. Tang, E. A. Bayer, J. S. Duerr, et al.: Whole-animal connectomes of both Caenorhabditis elegans sexes, Nature 571, 63–71  (2019).
• [ERD59] P. Erdős and A. Rényi: On random graphs, Publ. Math. Debrecen 6, 290–297 (1959).
• [EUL41] L. Euler: Solutio problematis ad geometriam situs pertinentis, Commentarii academiae scientiarum Petropolitanae 8, 128–140 (1741).
• [KEA12] A. Keane, T. Dahms, J. Lehnert, S. A. Suryanarayana, P. Hövel, and E. Schöll: Synchronisation in networks of delay-coupled type-I excitable systems, Eur. Phys. J. B 85, 407 (2012).
• [KUR02a] Y. Kuramoto and D. Battogtokh: Coexistence of Coherence and Incoherence in Nonlocally Coupled Phase Oscillators., Nonlin. Phen. in Complex Sys. 5, 380–385 (2002).
• [LEH11] J. Lehnert, T. Dahms, P. Hövel, and E. Schöll: Loss of synchronization in complex neural networks with delay, Europhys. Lett. 96, 60013 (2011).
• [LOO23] S. A.M. Loos, S. H.L. Klapp, and T. Martynec: Long-range Order and Directional Defect Propagation in the Nonreciprocal XY Model with Vision Cone Interactions, Physical Review Letters 130, 198301 (2023).
• [LOR18] P. Lorenz, F. Wolf, J. Braun, N. Djurdjevac Conrad, and P. Hövel: Capturing the Dynamics of Hashtag-Communities, in Complex Networks & Their Applications VI., edited by C. Cherifi, H. Cherifi, M. Karsai, and M. Musolesi (Springer, Cham, 2018), vol. 689 of Studies in Computational Intelligence, pp. 401–413.
• [LOR18a] P. Lorenz-Spreen, F. Wolf, J. Braun, G. Ghoshal, N. Djurdjevac Conrad, and P. Hövel: Tracking online topics over time: understanding dynamic hashtag communities, Comput. Soc. Netw. 5, 9 (2018).
• [LOR19] P. Lorenz-Spreen, B. Moch Mønsted, P. Hövel, and S. Lehmann: Accelerating dynamics of collective attention, Nat. Commun. 10, 1759 (2019).
• [MAE21] T. Maertens, E. Schöll, J. Ruiz, and P. Hövel: Multilayer network analysis of C. elegans: Looking into the locomotory circuitry, Neurocomputing 427, 238–261 (2021).
• [MIL67] S. Milgram: The Small-World Problem, Psychology Today 106, 61–67 (1967).
• [NEW03] M. E. J. Newman: The structure and function of complex networks, SIAM Review 45, 167–256 (2003).
• [NEW10] M.E.J. Newman: Networks - An Introduction, Oxford University Press (2010). 2nd edition (2018).
• [NEW18] M. Newman: Networks (Oxford university press, 2018).
• [OME11] I. Omelchenko, Y. Maistrenko, P. Hövel, and E. Schöll: Loss of coherence in dynamical networks: spatial chaos and chimera states, Phys. Rev. Lett. 106, 234102 (2011).
• [RUB10] M. Rubinov and O. Sporns: Complex network measures of brain connectivity: uses and interpretations., Neuroimage 52, 1059–1069 (2010).
• [VIO19] A. Viol, F. Palhano-Fontes, H. Onias, D. B. de Araujo, P. Hövel, and G. M. Viswanathan: Characterizing complex networks using entropy-degree diagrams: Unveiling changes in functional brain connectivity induced by Ayahuasca, Entropy 21 (2019).
• [VIO21] A. Viol, V. Vuksanović, and P. Hövel: Information parity in complex networks, Phys. A 561, 125233 (2021). 
• [VIO23] A. Viol, G. M. Viswanathan, O. Soldatkina, F. Palhano-Fontes, H. Onias, D. de Araujo, and P. Hoevel: Information parity on cortical functional brain networks increases under psychedelic influences, J. Phys. Complex 4, 01LT02 (2023).
• [WAT98] D. J. Watts and S. H. Strogatz: Collective dynamics of ’small-world’ networks, Nature 393, 440–442 (1998).
• [YAN17c] G. Yan, P. E. Vértes, E. K. Towlson, Y. L. Chew, J. D. Walker, W. R. Schafer, and A. L. Barabási: Network control principles predict neuron function in the Cenorhabditis elegans connectome, Nature 550, 519 (2017).

Weitere mögliche Themen:

• [BAJ12] P. Bajardi, A. Barrat, L. Savini, and V. Colizza: Optimizing surveillance for livestock disease spreading through animal movements, J. Royal Soc. Interface 9, 2814–2825 (2012).
• [BRO06a] D. Brockmann, L. Hufnagel, and T. Geisel: The scaling laws of human travel, Nature 439, 462–465 (2006).
• [BRO13] D. Brockmann and D. Helbing: The hidden geometry of complex, network-driven contagion phenomena, Science 342, 1337–1342 (2013).
• [HUF04] L. Hufnagel, D. Brockmann, and T. Geisel: Forecast and control of epidemics in a globalized world, Proc. Natl. Acad. Sci. 101, 15124 (2004).
• [HUM21] R. Humphries, M. Spillane, K. Mulchrone, S. Wieczorek, M. O'Riordain, and P. Hövel: A metapopulation network model for the spreading of SARS-CoV-2: Case study for Ireland, Infect. Dis. Model. 6, 420–437 (2021).
• [LEN11] H. H. K. Lentz, M. Konschake, K. Teske, M. Kasper, B. Rother, R. Carmanns, B. Petersen, F. J. Conraths, and T. Selhorst: Trade communities and their spatial patterns in the german pork production network, Preventive Veterinary Medicine 98, 176–181 (2011).
• [POL14a] C. Poletto, M. F. Gomes, A. Pastore y Piontti, L. Rossi, L. Bioglio, D. L. Chao, I. M. Longini Jr, M. E. Halloran, V. Colizza, and A. Vespignani: Assessing the impact of travel restrictions on international spread of the 2014 West African Ebola epidemic, Eurosurveillance 19, 20936 (2014).
• [TIZ12]  M. Tizzoni, P. Bajardi, C. Poletto, J. J. Ramasco, D. Balcan, B. Gonçalves, N. Perra, V. Colizza, and A. Vespignani: Real-time numerical forecast of global epidemic spreading: case study of 2009 a/h1n1pdm, BMC Medicine  10, 165 (2012).