Observability of complex systems
Name
Liu-2013-The observability of complex systems.pdf
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500.06 KB
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Author(s)
Liu, Yang-Yu
Slotine, Jean-Jacques E.
Barabasi, Albert-Laszlo
Date Issued
January 2013
Journal
Proceedings of the National Academy of Sciences
Publisher
National Academy of Sciences (U.S.)
Citation
Liu, Y.-Y., J.-J. Slotine, and A.-L. Barabasi. “From the Cover: Observability of complex systems.” Proceedings of the National Academy of Sciences 110, no. 7 (February 12, 2013): 2460-2465.
Version
Final published version
Abstract
A quantitative description of a complex system is inherently limited by our ability to estimate the system’s internal state from experimentally accessible outputs. Although the simultaneous measurement of all internal variables, like all metabolite concentrations in a cell, offers a complete description of a system’s state, in practice experimental access is limited to only a subset of variables, or sensors. A system is called observable if we can reconstruct the system’s complete internal state from its outputs. Here, we adopt a graphical approach derived from the dynamical laws that govern a system to determine the sensors that are necessary to reconstruct the full internal state of a complex system. We apply this approach to biochemical reaction systems, finding that the identified sensors are not only necessary but also sufficient for observability. The developed approach can also identify the optimal sensors for target or partial observability, helping us reconstruct selected state variables from appropriately chosen outputs, a prerequisite for optimal biomarker design. Given the fundamental role observability plays in complex systems, these results offer avenues to systematically explore the dynamics of a wide range of natural, technological and socioeconomic systems.
MIT Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Massachusetts Institute of Technology. Department of Mechanical Engineering
Massachusetts Institute of Technology. Nonlinear Systems Laboratory
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1073/pnas.1215508110
