Mechanism of organization increase in complex systems

This paper proposes a variational approach to describe the evolution of organization of complex systems from first principles, as increased efficiency of physical action. Most simply stated, physical action is the product of the energy and time necessary for motion. When complex systems are modeled as flow networks, this efficiency is defined as a decrease of action for one element to cross between two nodes, or endpoints of motion - a principle of least unit action. We find a connection with another principle that of most total action, or a tendency for increase of the total action of a system. This increase provides more energy and time for minimization of the constraints to motion in order to decrease unit action, and therefore to increase organization. Also, with the decrease of unit action in a system, its capacity for total amount of action increases. We present a model of positive feedback between action efficiency and the total amount of action in a complex system, based on a system of ordinary differential equations, which leads to an exponential growth with time of each and a power law relation between the two. We present an agreement of our model with data for core processing units of computers. This approach can help to describe, measure, manage, design and predict future behavior of complex systems to achieve the highest rates of self-organization and robustness.Comment: 22 pages, 4 figures, 1 tabl

Exponential Self-Organization and Moore\u27s Law: Measures and Mechanisms

The question of how complex systems become more organized and efficient with time is open. Examples are the formation of elementary particles from pure energy, the formation of atoms from particles, the formation of stars and galaxies, and the formation of molecules from atoms, of organisms, and of the society. In this sequence, order appears inside complex systems and randomness (entropy) is expelled to their surroundings. Key features of self-organizing systems are that they are open and they are far away from equilibrium, with increasing energy flows through them. This work searches for global measures of such self-organizing systems, which are predictable and do not depend on the substrate of the system studied. Our results will help to understand the existence of complex systems and mechanisms of self-organization. In part we also provide insights, in this work, about the underlying physical essence of Moore’s law and the multiple logistic growth observed in technological progress

Self-Organization of Cosmic Elements During Stellar Evolution

An open question in science is how complex systems self-organize to produce emergent structures and properties. One aspect is to find the dependence of structure and organization on the size of a system. It has long been known that there is a quality-quantity relationship in natural systems, which is to say that the properties of system depend on its size. More recently, this has been termed the Size-Complexity Rule. In this Thesis paper, we study the average rates of nucleosynthesis and action efficiency of stars with varying initial metallicities and explosion energies from simulations (Nomoto, Tominaga, Umeda, Kobayashi, & Maeda, 2006) based on the Stellar Abundances for Galactic Archaeology database (Suda et al., 2008). Our goal is to study the size-complexity relation in stars of varying metallicities and explosion energies and to compare them with other complex systems. Here, as a measure of complexity of a star, we are using the grouping and approximate number of reactions of nucleons into heavier elements, because they increase the variety of elements and changes the structure of the star. Then we calculate the average rate of grouping of nucleons by multiplying each of them by their level of grouping, defined as how many of them are joined into a nucleus, and then divide by the lifetime of the star over which these isotopes were synthesized. As seen in our previous work, complexity, as measured by action efficiency grows exponentially in time and as a power law of all other characteristics of a system, including its size. Here we find that, as for the other systems studied, the complexity of a star in terms of grouping of its elements and the rate of increase of complexity is a power law of its size despite differing explosion energies and initial metalicities. As shown by these stars, the bigger a system is, the higher the levels of complexity it can reach even if the initial metallicity and explosion energy are different. This is seen in how each star’s progress, average rate, flow, and action efficiency of nucleosynthesis dramatically increase as a function of their initial number of nucleons. Our goal is to find how universal the size-complexity relation is, and whether there are any exceptions. We are planning to study other systems to find whether they obey the same rule and, as stellar evolution simulations improve, to study in detail not just the average rate, but the instantaneous rate of nucleosynthesis

The entropy of suffering : an inquiry into the consequences of the 4-Hour Rule for the patient-doctor relationship in Australian public hospitals

As a medical practitioner, predominantly working in Australian public hospitals, I have always been interested in the factors that shape and influence my and my colleagues’ performance in the practice of medicine. In 2011, the Australian Government instituted a range of reforms to the public health-care system, including some directed at improving access for patients to Emergency Departments, which had, over many years, become increasingly overwhelmed by the number and complexity of presentations. This included a target of four hours within which patients in Emergency Departments were to be discharged, admitted or transferred to alternative institutions. These reforms generated widespread strong emotional responses from medical and other health staff with whom I worked, and I was prompted to consider the origins of these powerful human reactions to the administrative intervention. Emergency Departments are often described, derisively, as chaotic working environments. However, this epithet may instead be describing something quite profound about the ontological nature of hospitals and Emergency Departments — that they are, indeed, non-linear dynamical physical systems in which phenomena of complexity exist. Other human-centred interactional and transactional systems have been successfully examined from a complexity perspective, including economics and human physiology. Framing inquiry into Emergency Departments, and the humans who encounter each other within them, from a complexity perspective might also then prove useful in defining and characterising the complex and manifold relationships and interactions between people, technology and systemic organising principles. This health services research evaluates the lived experience of four medical practitioners through the paradigm of phenomenological inquiry, as actors on a performance landscape of clinical encounters and as key sources of information about the structure and functions of that performance manifold. Inquiry into and analysis of these rich descriptive data yield strong inferences that non-linear dynamics are operating across scales — from the cellular to the organisational. The complexity perspective provides a unifying explanatory power for making sense of how energetic transactions and transformations between patients, health-care practitioners, technology and the hospital system unfold to result in the recovery from injury and trauma. Specifically, literature on interoception suggests that human biological systems are exquisitely sensitive to changes in dynamic steady-states that might indicate increased entropy. This inquiry suggests that suffering is a phenomenological experience of sudden increases in entropy. An explanatory model in complexity, using the Second Law of Thermodynamics in open systems, suggests that entropy — that is, suffering — can be understood as being transferred and expelled from patient to doctor. Framing in this explanatory model would suggest that the patient-doctor relationship is a powerful systemic attractor in a dynamic system. Elaborating this construct of energetic dynamics further suggests that insertion of system controllers, such as time-based targets, can have profound non-linear effects on the function of these dynamics and, hence, the outcomes of these patient-doctor encounters. The implications of this inquiry include a new and powerful reframing of the ontological characterisation of the practice of medicine in Emergency Departments in terms of nonlinear open thermodynamic functions operating at distance from equilibrium. It recommends a more thoughtful consideration of human experiences such as suffering and its relief. Giving priority and visibility to suffering within health-care, a recrudescence of times past when technology in medicine was limited, may elucidate ways of practising that improve patient experiences and health outcomes. Furthermore, the findings suggest that medical practitioners, health workers and administrators are called on to deeply consider embracing complex dynamics as problem framing references, and to engage with methodologies that build better theories about the nature of phenomena under investigation. Rather than seeking to diminish or extinguish the complexities of Emergency Departments, researchers and practitioners might acknowledge and engage with the next wave of complexity-informed health-care research to better understand how and why health-care relieves suffering and restores human function

An Initial Framework Assessing the Safety of Complex Systems

Trabajo presentado en la Conference on Complex Systems, celebrada online del 7 al 11 de diciembre de 2020.Atmospheric blocking events, that is large-scale nearly stationary atmospheric pressure patterns, are often associated with extreme weather in the mid-latitudes, such as heat waves and cold spells which have significant consequences on ecosystems, human health and economy. The high impact of blocking events has motivated numerous studies. However, there is not yet a comprehensive theory explaining their onset, maintenance and decay and their numerical prediction remains a challenge. In recent years, a number of studies have successfully employed complex network descriptions of fluid transport to characterize dynamical patterns in geophysical flows. The aim of the current work is to investigate the potential of so called Lagrangian flow networks for the detection and perhaps forecasting of atmospheric blocking events. The network is constructed by associating nodes to regions of the atmosphere and establishing links based on the flux of material between these nodes during a given time interval. One can then use effective tools and metrics developed in the context of graph theory to explore the atmospheric flow properties. In particular, Ser-Giacomi et al. [1] showed how optimal paths in a Lagrangian flow network highlight distinctive circulation patterns associated with atmospheric blocking events. We extend these results by studying the behavior of selected network measures (such as degree, entropy and harmonic closeness centrality)at the onset of and during blocking situations, demonstrating their ability to trace the spatio-temporal characteristics of these events.This research was conducted as part of the CAFE (Climate Advanced Forecasting of sub-seasonal Extremes) Innovative Training Network which has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 813844