European COST Action to develop “A quantum theory of complex and networked systems”
Open webnair 4:00 p.m. GMT – Thursday, June 2
We're about to start putting together a 4 year project proposal that will enable a series of large and well funded workshops (and travel support). It's all about results intersecting quantum information and complex systems science – a.k.a. complex network theory. And I wanted to make this as open as possible, as an extra effort to ensure that the interested leading research groups hear about this so they won't feel left out. We're planning an open webinar next week:
* 4:00 p.m. GMT – Thursday, June 2 (https://plus.google.com/u/0/events/cdl4067cj5ccc5b6q1d5n6t2vnk?authkey=C...)
You and or your group representatives are welcome to join us in this overview discussion – everyone is welcome. Simply join the G+ hangout page! (https://plus.google.com/u/0/events/cdl4067cj5ccc5b6q1d5n6t2vnk?authkey=C...). If you have questions, you can post them in the comments or even write me directly: jacob.biamonte at qubit dot org
The topics we're considering are contemporary – there's been work done already [a] but the future is largely open so there's plenty to contribute. And we've been getting increasing interest these days as other groups pick up these topics and enter the QuamPlexity fray. So it's worth it to consolidate this growing effort, and to build a network. I'm hopeful we can build this up to a dozen groups with well over 100 participants with your help. (The current network on quantum thermo has over 250 participants).
I've taken a few hours to paste together what I currently see as a starting place to organize this network. We will improve this as we create the proposal.
- The big idea.
See the description here. www.QuamPlexity.org
As well as the introduction video here. https://youtu.be/qHg4xhIohq4
- How will a 'quantum theory' of complex and networked systems be beneficial?
Fundamental science.
Complex network science has made its name explaining phenomena in a diverse range of disciplines (everything from the Internet to biological networks have been shown to follow predicable patterns, from what used to appear random). The tools of complex network and systems science essentially fail when facing quantum effects, despite increasing contemporary interest in porting these tools to apply to quantum phenomena. So one benefit is therefore to push forward the applicability of complex network and system science theory, such that it applies to the quantum domain. And to better understand why the existing tools fail.
Technological applications.
Recent efforts have pushed the experimental demonstration of quantum effects into new ground. This includes the D-Wave processor, with around 1000 spins as well as long range quantum communication channels. These devices are pushing the existing tool set to predict quantum effects into new domains, where even the classical description of the interacting constituents could exhibit emerge complexity. The tools to address emergent complexity in the quantum model are lacking and only now being developed: for example, the topology of the underlying graph of interacting spins is of central importance to the ultimate usefulness of a quantum annealer, and the robustness and degree correlation of wide-scale communication networks governed by quantum effects, gives rise to new effects simply not present in the successful classical theory of complexity and degree correlation in communication networks.
An emergent common language.
By correctly studying information as an entity fundamentally governed by the laws of physics, development of an emerging common language is already binding certain ideas and mapping some techniques between the fields of quantum physics and complexity science. What’s more, the ubiquitous use of various network and graph theories inside of both disciplines, creates a stage for an abstracted comparison of networked systems, recovering both fields as special cases of more general mathematical entities. Work along these lines is really only just getting started. And even with these similarities, and other bridges still being built, there seems to be an even vaster host of differences. Pinpointing these similarities and reconciling these differences in increasingly precise terms broadly defines this research track. An ultimate goal is to form a new theory, uniting these disciplines.
- What are some big questions?
1. Can we discover and overcome the fundamental reasons why contemporary complex network theory fails to predict certain quantum effects?
2. How can information theory (as studied) in quantum physics, be further employed as a tool in network science, as an indicator augmenting contemporary degree and correlation measures with those based on entropy and information?
3. The Ising model arises in complex network science for its predictive capabilities, to study phase transitions and to model even social phenomena. At the same time, quantum annealers evolve to the ground state configurations of the Ising model as a means to solve computational problems. The use of network and graph theory has been successfully employed in the study of the D-Wave annealer, yet big questions about the most effective topology remain and are situated in the collection of problems which have been addressed in traditional network theory, this time with a quantum twist.
4. Reaction networks (systems governed by mass-action kinetic, such as biological and chemical reactions) are a formidable challenge to contemporary network science. Degree measures fail to offer predicable insights. These networks have been mapped to a non-unitary field theory. Information theoretic measures and other 'quantum techniques' appear ripe to reconcile network theory which the class of stochastic reaction networks.
- Why work together? (complex systems scientists and quantum information scientists)
One could argue that the fields of quantum information science and complex network theory (a.k.a. complexity science) both address complexity, yet from opposite perspectives. Indeed, the former makes use of a complex system as a computational resource whereas the later generally studies (and often using computer simulations) the scaling, collective behavior and emergent properties of complex system(s).
Accordingly, how the term complexity arises in these two fields is not always interchangeable. So called, computational complexity in quantum information science considers quantifying computational resources whereas complexity science investigates how relationships between parts give rise to collective behaviors of the whole.
The reason to combine efforts is well-motivated and happening already. Two fields solved related problems from totally different directions. Positioned centrally in the future of network science is the desire to reconcile the methods so they now work when facing quantum effects, and the recent scaling up of quantum experiments create a stage for a new type of complexity.
[a] Rules for participation. http://www.cost.eu/download/Rules_for_Participation_in_implementation_of...
[b] The framework follows an 'open call' to submit proposals.
http://www.cost.eu/service/glossary/Open-Call
Lists all EU member states, as well as a few others that can take part.
[c] Overview of the 'quantum theory' of complex and networked systems. http://quamplexity.org/quantum-complex-network-science/
