Open Calls for Papers
- Published on 08 November 2023
Guest Editors: Thiago B. Murari, Marcelo A. Moret, Hernane B. de B. Pereira, Tarcísio M. Rocha Filho, José F. F. Mendes and Tiziana Di Matteo
Submissions are invited for a Topical Issue of EPJ B on Recent Advances in Complex Systems.
In general, a complex system is a system composed of many components that may interact with each other in nonlinear ways. Examples of complex systems include fractals, chaos, nonlinear dynamics, self-organized criticality, and complex networks. This issue aims to promote research in complex systems, both in pure and applied contexts.
- Published on 07 November 2023
Guest Editors: Philipp Hövel and Igor Sokolov
Submissions are invited for a Topical Issue of EPJ B on Mathematical Modeling in Epidemiology: Limits and Pitfalls.
The last/on-going SARS-CoV2 pandemic has triggered an unprecedented boost of studies on mathematical modeling of epidemics. Large-scale data have become available on high spatial, temporal, and social resolution. Many groups have entered the field, devoting time and attention to the topic. Now, it is time to re-evaluate methods and approaches of modeling and to learn from the past for the future:
- Published on 06 June 2023
Guest Editors: Ivan V. Borzenets, Chung-Ting Ke, Ethan Arnault, Tobias Stauber
Submissions are invited for a Topical Issue of EPJ B on Superconducting Graphene.
The goal of this topical issue is to focus on all aspects of research related to superconductivity in graphene. We aim to have an even spread of papers discussing proximity induced graphene as well as "magic angle" and strain/gate induced superconductivity in graphene. At the same time, we hope to cover both intrinsic physical properties, as well as device applications (mainly quantum information quantum sensing).
- Published on 15 May 2023
Guest Editors: Philipp Hövel, Rainer Adelung, Jan Bielecki, Wilhelm Braun, Claus Hilgetag, Hermann Kohlstedt, Claudia Lenk, Alex Schaum, Jan Trieschmann, Peer Wulff
Submissions are invited for a Topical Issue of EPJ B on Neuromorphic Bio-inspired Computing.
As a result of a billion years of ongoing evolution, nervous systems exhibit remarkable capabilities for the interactions with their surroundings. In contrast to man-made, clockdriven Boolean Turing machines, information processing in biological nervous systems is characterized by highly parallel, energy efficient, and adaptive architecture. When it comes, for instance, to pattern recognition, failure tolerance, and cognitive tasks in real time, even simple creatures outperform supercomputers, in particular under the aspect of power dissipation. From an engineering point of view, nervous systems process information in such a way that even state-of-the-art silicon technology and modern digital computing strategies seem to be outstripped. They excel by using information pathways that are characterized by a highly irregular and flexible tissue consisting of neurons, synapses and axons operating at low conduction velocities that lead to pronounced signal delays. From a holistic point of view, nervous systems can be considered as time-varying networks in which spike dynamics and cellular morphology are intricately linked and reciprocally interwoven.
EPJ B Topical Issue: New frontiers in exploring the dynamics of community structure in online social networks
- Published on 09 May 2023
Guest Editors: Shuo Yu, Asif Ali Laghari, Mengmeng Yang, Renaud Lambiotte
Submissions are invited for a Topical Issue of EPJ B on New frontiers in exploring the dynamics of community structure in online social networks.
Social networks have become an important part of our everyday life. These networks have revolutionized the way we live and interact with each other. Numerous applications of social networks go beyond just personal communication, including finding new friends and business contacts as well as organizing public events, or finding people who share similar interests. Understanding the dynamics of community structure in online social networks is important for many reasons. First, such knowledge can help improve marketing strategies since it sheds light on the relationships between users and the products or services sold. Second, this information can be used in the design and development of social networking systems that support these relationships. Third, understanding how communities emerge and evolve will help us better predict future behavior in response to various events. Online social networks have become popular venues for connecting with others and sharing content. However, they also harbor the potential to enable malicious activities by users who intend to harm members of these communities. To help mitigate this threat, it is critical to understand how community structures evolve and what factors affect them. The dynamics of community structure in online social networks have attracted growing interest from many disciplines. Network science, sociology, and social psychology have all contributed to the research community's understanding of how contextual factors influence what individuals perceive as "communities" and how they behave within those communities. However, even though most studies treat individual participation as relatively stable across periods (e.g., by comparing one time period to another or averaging across multiple periods), there is no scientific consensus on how users' behaviors change over time, whether because of changes in their characteristics such as demographics, mood, and personality; or because of trends in technology adoption; or both.
EPJ B Topical Issue: Quantum phase transitions and open quantum systems: A tribute to Prof. Amit Dutta
- Published on 14 April 2023
Guest Editors: Uma Divakaran, Victor Mukherjee, Krishnendu Sengupta, Ferenc Iglói
Submissions are invited for a Topical Issue of EPJ B on Quantum phase transitions and open quantum systems: A tribute to Prof. Amit Dutta.
Understanding zero temperature quantum phase transitions is essential to explain the unconventional behavior observed in some systems at small but finite temperatures. This non-trivial behavior is attributed to a delicate interplay of zero temperature quantum fluctuations and thermal fluctuations. Quantum critical systems taken out of equilibrium and evolving in presence of dissipation present a novel path to understand this undergoing critical phenomena. Recent experimental progress using different platforms, including ultracold atoms, superconducting qubits and nitrogen vacancy centers in diamonds, have made these questions even more relevant.
- Published on 29 May 2020
Submissions are invited for a Topical Issue of EPJ B on Extreme Value Statistics and Search in Biology: Theory and Simulations.
The reliability of the functioning of biological systems is still puzzling taking into account that many processes governing this functioning are prone to strong fluctuations on very different scales. In many cases these processes rely on a single or a few events, for example, those starting a signalling cascade, and may be dominated by the first or the first successful encounter of the corresponding units. Such encounters are often modelled as different variants of random search processes. The analysis of such processes pertinent to specific biological situations shows that in many cases a search process by a single agent is extremely ineffective, with typical encounter times considerably larger than what is necessary from the biological point of view. Therefore, the successful encounters are rare events.