Chaos

We review the recently proposed universal concept of dynamic complexity and its new mathematics based on the unreduced interaction problem solution. We then consider its progress-bringing applications at various levels of complex world dynamics, including complex-dynamical nanometal physics and living condensed matter, unreduced nanobiosystem dynamics and the integral medicine concept, causally complete management of complex economical and social dynamics, and the ensuing concept of truly sustainable world governance.

The functioning of complex natural structures, such as living systems, still lacks a generally accepted theoretical basis with respective empirical experimental verification for decades. We propose a class of experiments to test whether such systems could be subject to an unknown ordering principle that cannot be captured by known physical laws. We hypothesise that the quantum mechanical uncertainty principle enables ordering phenomena in nearly chaotic systems in the sense of a strong emergence principle, which would not be expected when they (...) are modelled conventionally, as several authors have already formulated in various forms. To account for the harsh conditions prevailing in living systems that may preclude fragile macroscopic quantum coherence, our hypothesis does not require such coherence at all, contrary to earlier related proposals. To test this hypothesis, two virtually identical and sufficiently complex experimental setups should be compared. One setup will operate with deterministic pseudo-random number generators at key sensitive points, while the other one will use quantum-based physical random-number generators, the two setups being otherwise identical. Existing artificial neural networks are proposed as possible test objects, and their performance under identical training conditions can be used as a quantitative benchmark. As this working hypothesis extends far beyond artificial networks, a successful outcome of such an experiment could have significant implications for many other branches of science. (shrink)

This work proposes that deterministic systems can still generate structured novelty given that Trace, treated as hx/Actuality/Prospective state-order (trace order), yields Variable Complementary Determinism (VCD) through which reactive fields and reactants propagate into functions and reactions, informational dynamics, behavior (choice and creation), and, without mind as a first-source assumption, coordinative awareness/intelligence as scalar, legible threshold expressions. -/- "Full UID Master Index available on GitHub; search for repository: armandosotouidt".

Recent work has shown equivalence between the formal apparatus of quantum mechanics and a general class of non-Markovian systems called indivisible stochastic systems. This short paper demonstrates how these indivisible dynamical systems can be used to describe the effective dynamics of coarse-grained observers. The observation suggests that quantum mechanics may arise as the expected phenomenology of coarse-grained systems in a classical, deterministic substrate.

The digital implementation of the Lorenz equations using logical gates, as described in this paper, provides a framework for modeling chaotic behavior in discrete systems. This approach can be extended to biological systems, where chaotic dynamics may underlie critical cellular processes such as energy production and epigenetic regulation. Here, we propose that the genetic codes of mitochondrial DNA (mtDNA) and nuclear DNA exhibit self-similar and chaotic properties, analogous to the strange attractors generated by our digital system. Furthermore, we explore the (...) role of ATP and histones as state variables within this chaotic framework, regulated by feedback mechanisms and a bijective mapping between mtDNA and nuclear DNA. (shrink)

Inhere we expand the concept of Holobiont to incorporate niche construction theory in order to increase our understanding of the current planetary crisis. By this, we propose a new ontology, the Ecobiont, as the basic evolutionary unit of analysis. We make the case of Homo Sapiens organized around modern cities (technobionts) as a different Ecobiont from classical Homo Sapiens (i.e. Hunter- gatherers Homo Sapiens). We consider that Ecobiont ontology helps to make visible the coupling of Homo Sapiens with other biological (...) entities under processes of natural and cultural evolution. Not to see this coupling hidden systemic risks and enhance the probability of catastrophic events. So Ecobiont ontology is necessary to understand and respond to the current planetary crisis. -/- . (shrink)

Recent work by Frigg et. al. and Mayo-Wilson have called attention to a particular sort of error associated with attempts to model certain complex systems: structural modeling error. The assessment of the degree of SME in a model presupposes agreement between modelers about the best way to individuate natural systems, an agreement which can be more problematic than it appears. This problem, which we dub “the system individuation problem” arises in many of the same contexts as SME, and the two (...) often compound one another. This paper explores the common roots of the two problems in concerns about the precision of predictions generated by scientific models, and discusses how both concerns bear on the study of complex natural systems, particularly the global climate. (shrink)

This paper challenges the prevailing consensus that chaotic systems are deterministic “in principle” despite practical unpredictability due to sensitivity to initial conditions—the butterfly effect. Drawing on the framework of Mutual Exclusivity and Phenomenological Absolutism as its core principle, we argue that the epistemic impossibility of specifying a complete set of initial conditions is not a mere human limitation but reflects the ontic structure of reality itself. Under austere physical realism—where epistemic and ontic structures collapse into localized, absolute, mutually exclusive “is-nesses”—there (...) exists no persisting global substrate, phase space, or precise microstate capable of entailing future trajectories. Chaos therefore manifests genuine ontic indeterminism: each successive phenomenal configuration arises according to law-like phenomenological regularities (via attentive configurations and energetic entities) without being strictly determined by any prior complete state. Furthermore, we position Mutual Exclusivity as a self-reflexive meta-framework, securing its foundational immunity by identifying any epistemic critique or conceptual distinction as a localized ontic actualization in its own right. By demonstrating that trans-is-ness comparisons are not merely epistemically impossible but ontically inapplicable, we neutralize standard analytical objections. This framework preserves the full empirical and predictive success of physics and probability while dissolving longstanding paradoxes in the philosophy of science. It offers a leaner ontology than Everettian or block-universe alternatives and carries significant implications for agency, ethics, and the interpretation of quantum and relativistic phenomena. Ultimately, chaos is not “practically” indeterministic; when epistemic limits are taken as ontically constitutive, indeterminism is the character of physical reality under austere phenomenological absolutism. (shrink)

It is now a reflex to speak of “chaos” as though it were a property of the world itself; an unruly surplus in reality or ontological residue that appears whenever order weakens or control fails. We reach for the term in moments of political volatility, psychological overload, ecological instability, and technological acceleration, with the same tacit assumption; something “out there” has become “chaotic.” The world, we believe, is doing something to us. It has become disorderly, ungovernable, or incomprehensible. Because we (...) use the word as if it names a real and independent force, we treat its appearance as evidence of a threatening shift in reality rather than as a diagnostic signal of a failure in our relationship to reality. This is our initial error. Chaos is not what the world does to us. Chaos is what symbolic systems experience when they lose correspondence but refuse revision. (shrink)

Chaos theory is an interdisciplinary area of scientific study and branch of mathematics focused on underlying patterns and deterministic laws of dynamical systems that are highly sensitive to initial conditions. While the rules describing chaotic dynamical systems are well-specified and simple, the behaviour of many such systems is remarkably complex and produces output that appears random and for which long-term prediction is limited. The book begins by laying out preliminary material needed to understand the literature on chaos, providing the background (...) that any reader would need to be able to navigate the literature. It goes on to discuss the history of the field, the different definitions of chaos, differences between classical and quantum chaos and the implications of chaos for modelling phenomena and forecasting system behaviour before rounding out with broader implications. (shrink)

The Lorenz system is a classic chaotic system exhibiting the butterfly effect and strange attractor behavior. In this paper, we propose a digital implementation of the Lorenz equations using logical gates. We map derivative, difference, multiplication, and addition operations to digital equivalents—previous step feedback, XOR, AND, and OR gates respectively. This allows the construction of a fully digital, discrete-time chaotic system capable of exploring complex state spaces and demonstrating algorithmic strange attractor behavior.

Specific Decisional System offers a groundbreaking exploration into how artificial intelligence can make, adjust, and implement decisions with mathematical precision. Focused on the core logic of Artificial Research by Deduction, this book introduces readers to a structured, three-stage process that governs how intelligent systems validate decisions, transform them into actionable instructions, and evolve through self-correction. With real-world examples ranging from automated transport to banking systems, it reveals how AI can operate autonomously while adapting in real time to new priorities and (...) changing environments. -/- Whether you're a researcher, engineer, policy designer, or visionary entrepreneur, this book provides a forward-looking framework for designing intelligent systems that are not only efficient and responsive, but capable of learning and improving themselves. It also introduces the original concept of “Probability and Deduction” as a method to directly link logic, modelling, and execution—creating a seamless path from mathematical reasoning to robotic action. -/- Specific Decisional System is a must-read for anyone interested in the future of automation, intelligent governance, and the next generation of self-replicating, self-improving Artificial Intelligence. (shrink)

We often hear that evolutionary theory tells us that the history of life has been directed by the whims of randomness, or even that ‘we are here by chance’. At the same time, evolutionary theorists often construct models of evolution that are taken to be predictive, and geneticists and molecular biologists occasionally offer us extremely accurate predictions of molecular-level evolutionary change. How should we understand this interaction between prediction and randomness? I will explore here one particular kind of prediction – (...) predictions on the basis of quantitative estimates of fitness – in light of both the data that we need to draw those predictions and some recent mathematical work on the impact of chaos on evolutionary models, with the aim of examining what we might still be able to say about the predictability of the future of life in an evolving world. (shrink)

Is the brain really a computer? In particular, is our intelligence a computational achievement: is it because our brains are computers that we get on in the world as well as we do? In this paper I will evaluate an ambitious new argument to the contrary, developed in Landgrebe and Smith (2021a, 2022). Landgrebe and Smith begin with the fact that many dynamical systems in the world are difficult or impossible to model accurately (inter alia, because it is intractable to (...) find exact solutions to the differential equations that describe them—meaning we have to approximate—but at the same time they are such that small differences in starting conditions lead to big differences in final conditions, thwarting accurate approximation). Yet we manage to survive and thrive in a world full of such systems. Landgrebe and Smith argue from these premises that it is not because our brains are computers that we get on as well as we do: instead it is because of the various ways that we dynamically couple with such systems, these couplings themselves impossible to model well enough to emulate in silico. Landgrebe and Smith thus defend a dynamical systems model in the lineage of Gibson (1979), Van Gelder (1995), and Thompson (2007), though their focus is on decisively refuting the computationalist alternatives rather than developing the positive account. Here I will defend the claim that human intelligence is genuinely computational (and that whole brain emulation and others forms of AGI may be possible) against this argument. (shrink)

Космовидение - термин, под которым следует понимать совокупность оснований, из которых возникает системное понимание Вселенной, таких ее составляющих, как жизнь, мир, в котором мы живем, природа, феномен человека, и их взаимосвязей. таким образом, это область аналитической философии, питаемая науками, целью которой является совокупное и эпистемологически устойчивое знание обо всем, чем мы являемся и что в нас содержится, что нас окружает и что так или иначе с нами связано. это старое, как человеческая мысль, понятие, которое не только использует элементы научной космологии, (...) но и охватывает все, что относится к вселенной и жизни в философии и науке. Космовидение — это не набор идей, гипотез и предположений, а система, основанная на наблюдениях, анализе, доказательствах и демонстрациях. Космовидение не ставит своей целью определить, установить или предложить, а лишь понять, проанализировать и интерпретировать. Каждый из нас строит и переносит свое космовидение в течение жизни, не устанавливая форм, как фон для нашего мышления и поведения. С лингвистической точки зрения термин "космовидение" происходит от немецкого, эквивалентного понятию "Weltanschauung", используемому рядом философов. Однако эта лингвистическая связь неприменима, поскольку противоречит тому, что мы предлагаем в качестве космовидения. Это немецкое слово обозначает дологическое или протоэкспериментальное видение реальности, имеющее интуитивный контекст и далекое от критического знания, еще не существовавшего на момент его формулировки. Несомненно, космовидения в том смысле, как мы их понимаем, содержат и используют эти протоэкспериментальные или дологические элементы, включающие историю, коллективное бессознательное и все архетипы, которые мы носим в себе. Однако в той концепции, которую мы здесь применяем, космовидение выходит далеко за пределы этого содержания, во-первых, постоянно подчиняя его современному критическому мышлению и, наконец, делая аналитический опыт (а не саму мысль или интуицию) своей актуальной вселенной. Антониу Лопес раскрывает широту этого содержания: "Космовидения не являются продуктом мысли. Они не возникают из простого желания знать. Постижение реальности - важный момент в ее конфигурации, но, тем не менее, только один. Оно исходит из жизненного поведения, из жизненного опыта, из структуры нашей психической совокупности. Возвышение жизни до сознания в познании реальности, в оценке жизни и в волевой реальности — это медленная и тяжелая работа, которую проделало человечество в развитии представлений о жизни". (В. Дильтей, 1992 [1911]: 120)".. В данной работе мы стремимся изложить космовидение, основанное на тех реалиях, которые сегодня предлагает наука. Мы ни в коем случае не собираемся заниматься наукой или теоретизировать философию, но всегда будем стремиться опираться на них или, по крайней мере, защищаться ими от тех когнитивных искажений, которые мы обычно несем. (shrink)

Understanding the Constant Variable: In reality, there is no such thing as a constant. And, also, there is no such thing as a variable. There is the conservation of a circle, and, that is ‘all.’.

Understanding (physics, philosophy, and psychology as) a constant variable.

We live in a universe that can be seen and experienced from many different perspectives. We therefore need to look at the universe from many different angles. Everything and everyone is a form of the universe being expressed in a particular way. In other words, each one of us can say with absolute certainly “We are the Universe!” Since we are the universe, each one of us provides a valuable perspective that complements the contributions of everyone and everything else around (...) us. Each of us is the universe being expressed in a particular location in a specific way. We’re all part of the same moving and evolving cosmos, but the view of it is unique from each of our respective locations. This suggests that the universe is not only omnicentric, but that it is also multiperspectival – there are many different, and equally valid, viewpoints on this. Each one of us is a cosmic laboratory within which we can discover the secrets of the universe. We speak in various ways, we are each the universe having become aware of itself in our own unique way. The insights that the universe has many different perspectives and is both cosmic and personal has great transformative potential, and is worth reflecting on deeply. (shrink)

The unreduced solution to the arbitrary interaction problem, absent in the standard theory framework, reveals many equally real and mutually incompatible system configurations, or "realizations". This is the essence of universal dynamic undecidability, or multivaluedness, and the ensuing causal randomness (unpredictability), non-computability, irreversible time flow (evolution, emergence), and dynamic complexity of every real system, object, or process. This creative undecidability of real-world dynamics provides causal explanations for "quantum mysteries", relativity postulates, cosmological problems, and the huge efficiency of high-complexity phenomena, such (...) as life, intelligence, and consciousness, giving rise to extended applications, far beyond the critical limits of usual science paradigm. (shrink)

The thesis of this paper is that panpsychism theory is very close to jungian theory, especially thinking of the quantum psychoid aspects of C.G.Jung and W.Pauli theory: a psyche that touches matter and matter with a “latent psyche”. The two theories seem to describe the same reality, an animation of matter in a spiritual sense, as the jungian Self seems to do at a higher level.The complexity theory appears instead to be a description of reality still nomothetic.

Unified and causal complex-dynamic origin of standard (special and general) relativistic and quantum effects revealed previously at the lowest levels of world interaction dynamics is explicitly generalised to all higher levels of unreduced interaction processes, thus additionally confirming the causally complete character of complex-dynamical, naturally quantised relativity, which does not contain any artificially added, abstract postulates. We demonstrate some elementary applications of this generalised quantum relativity at higher levels of complex brain and social interaction dynamics.

Instead of postulated fixed structures and abstract principles of usual positivistic science, the unreduced diversity of living world reality is consistently derived as dynamically emerging results of unreduced interaction process development, starting from its simplest configuration of two coupled homogeneous protofields. The dynamically multivalued, or complex and intrinsically chaotic, nature of these real interaction results extends dramatically the artificially reduced, dynamically single-valued projection of standard theory and solves its stagnating old and accumulating new problems, “mysteries” and “paradoxes” within the unified (...) and causally complete picture of intrinsically evolving, dynamically complex reality. The permanently unfolding complexity progress thus revealed is fundamentally unlimited and does not need to stop at the directly observed diversity of usual matter complexity. The exciting, but rigorously substantiated and objectively inevitable prospects of further civilisation complexity development towards its superior levels of genuine sustainability and global Noosphere are outlined, with practically important conclusions for today’s critical problem solution. (shrink)

This book provides an analysis of the construction, diagnosis (as chaotic) and evaluation of models in chaos theory. It contains a detailed look at the interaction of the different models used in chaos theory and analyses how these models influence the way chaos is defined. Furthermore, the book discusses the conditions for the occurrence of chaos and the detection of chaos in nature.

Starting for the good results reached in physics researchers in economics and finance have been interested in testing nonlinear dependence and chaos in economic models and data. A wide variety of reasons for this interest have been suggested, including an attempt to improve the forecasting accuracy of linear time series models and to better explain the dynamics of the underlying variables of interest using a richer class of models than that permitted by limiting the set to the linear case. But (...) chaos theory has not had the same impact in the economics as it has in the hard sciences like physics. The literature did not provide a solid support for chaos as a consequence of the high noise level that exists in most economic time series, the relatively small sample sizes of data, and the weak robustness of chaos tests for these data. (shrink)

The stories we tell in our attempt to make sense of the world, our myths and religion, literature and philosophy, science and art, are the comforting vehicles we use to transmit ideas of order. But beneath the quest for order lies the uneasy dread of fundamental disorder. True chaos is hard to imagine and even harder to represent, especially without some recourse to the familiar coherency of order. In this book, Martin Meisel considers the long effort to conjure, depict, and (...) rationalize extreme disorder, with all the passions, excitements, and compromises the act has provoked. In seven chapters--"Shaping Chaos," "Nothing and Something," "Number," "Carnival," "War," "Energy," and "Entropy"--Meisel builds a rough history from major social, psychological, and cosmological turning points in the imagining of chaos. He uses examples from literature, philosophy, painting, graphic art, science, linguistics, music, and film, particularly exploring the remarkable shift in the eighteenth and nineteenth centuries from conceiving of chaos as disruptive to celebrating its liberating and energizing potential. Discussions of Sophocles, Plato, Lucretius, Calderon, Milton, Haydn, Blake, Faraday, Chekhov, Faulkner, Wells, and Beckett, among others, are matched with incisive readings of art by Brueghel, Rubens, Goya, Turner, Dix, Dada and the futurists. Meisel addresses the revolution in mapping energy and entropy and the manifold impact of thermodynamics. Known for his pathbreaking studies of literature, drama, and the visual arts, Meisel uses this chaotic frame to elaborate on larger concerns of purpose, mortality, meaning, and mind. (shrink)

This study presents the fundamental concepts and technical details of a U-model-based control system design framework, including U-model realisation from classic model sets, control system design procedures, and simulated showcase examples. Consequently, the framework provides readers with clear understandings and practical skills for further research expansion and applications. In contrast to the classic model-based design and model-free design methodologies, this model-independent design takes two parallel formations: it designs an invariant virtual controller with a specified closed-loop transfer function in a feedback (...) control loop and it determines the real controller output by resolving the inverse of the plant U-model. It should be noted that this U-control provides a universal control system design platform for many existing linear/nonlinear and polynomial/state-space models and it complements many existing design approaches. Simulation studies are used as examples to demonstrate the analytically developed formulations and guideline for potential applications. (shrink)

This article focuses on three recent discussions on determinism in the philosophy of science. First, determinism and predictability will be discussed. Then, second, the paper turns to the topic of determinism, indeterminism, observational equivalence and randomness. Finally, third, there will be a discussion about deterministic probabilities. The paper will end with a conclusion.

In this paper, we investigate the ultimate bound set and positively invariant set of a 3D Lorenz-like chaotic system, which is different from the well-known Lorenz system, Rössler system, Chen system, Lü system, and even Lorenz system family. Furthermore, we investigate the global exponential attractive set of this system via the Lyapunov function method. The rate of the trajectories going from the exterior of the globally exponential attractive set to the interior of the globally exponential attractive set is also obtained (...) for all the positive parameters values a,b,c. The innovation of this paper is that our approach to construct the ultimate bounded and globally exponential attractivity sets assumes that the corresponding sets depend on some artificial parameters ; that is, for the fixed parameters of the system, we have a series of sets depending on λ and m. The results contain the known result as a special case for the fixed λ and m. The efficiency of the scheme is shown numerically. The theoretical results may find wide applications in chaos control and chaos synchronization. (shrink)

In this article, the dynamical behaviors of two classes of chaotic systems are considered based on generalized Lyapunov function theorem with integral inequalities. Explicit estimations of the ultimate bounds are derived. The results presented in this article contain the existing results as special cases. Computer simulation results show that the proposed method is effective. © 2014 Wiley Periodicals, Inc. Complexity 21: 363–369, 2015.

The big news about chaos is supposed to be that the smallest of changes in a system can result in very large differences in that system's behavior. The so-called butterfly effect has become one of the most popular images of chaos. The idea is that the flapping of a butterfly's wings in Argentina could cause a tornado in Texas three weeks later. By contrast, in an identical copy of the world sans the Argentinian butterfly, no such storm would have arisen (...) in Texas. The mathematical version of this property is known as sensitive dependence. However, it turns out that sensitive dependence is somewhat old news, so some of the implications flowing from it are perhaps not such “big news” after all. Still, chaos studies have highlighted these implications in fresh ways and led to thinking about other implications as well. In addition to exhibiting sensitive dependence, chaotic systems possess two other properties: they are deterministic and nonlinear (Smith 2007). This entry discusses systems exhibiting these three properties and what their philosophical implications might be for theories and theoretical understanding, confirmation, explanation, realism, determinism, free will and consciousness, and human and divine action. (shrink)

Nicht Stabilität, sondern Instabilität sei der Grundcharakter der Natur, so hören wir von Jan Schmidt als Auftakt zu seinem Buch „Das Andere der Natur“ (Hirzel-Verlag, 2015). „Das Eine der Natur“, welches reduktionistisch zu erfassen ist, soll durch ein „Anderes“ ergänzt werden. Von dieser anderen Seite her zeigt sich „Natur ... auch (als) instabil, komplex, chaotisch, zufällig, emergent...“, und aus dieser Sicht des Naturgeschehens heraus will der Autor eine Philosophie der Instabilität entwerfen. Der gelernte Physiker und Philosoph lehrt an der Hochschule (...) Darmstadt (hda) Wissenschafts- und Technikphilosophie. Sein Buch beleuchtet das Thema „Instabilitäten“ aus vielen Blickwinkeln. Was sind Instabilitäten, was Selbstorganisation, was ist Zeit, was Zufall, was Kausalität? Diese Erkenntnisse bezieht der Autor dann auf den Kosmos, auf die Evolution bis hin zum menschlichen Gehirn und seinen Leistungen. Mit dieser Rezension gehe ich ausführlich auf dieses lesenswerte Buch ein. (shrink)

A dynamical system is called chaotic if small changes to its initial conditions can create large changes in its behavior. By analogy, we call a dynamical system structurally chaotic if small changes to the equations describing the evolution of the system produce large changes in its behavior. Although there are many definitions of “chaos,” there are few mathematically precise candidate definitions of “structural chaos.” I propose a definition, and I explain two new theorems that show that a set of models (...) is structurally chaotic if it contains a chaotic function. I conclude by discussing the relationship between structural chaos and structural stability. (shrink)

Climatology is a paradigmatic complex systems science. Understanding the global climate involves tackling problems in physics, chemistry, economics, and many other disciplines. I argue that complex systems like the global climate are characterized by certain dynamical features that explain how those systems change over time. A complex system's dynamics are shaped by the interaction of many different components operating at many different temporal and spatial scales. Examining the multidisciplinary and holistic methods of climatology can help us better understand the nature (...) of complex systems in general. -/- Questions surrounding climate science can be divided into three rough categories: foundational, methodological, and evaluative questions. "How do we know that we can trust science?" is a paradigmatic foundational question (and a surprisingly difficult one to answer). Because the global climate is so complex, questions like "what makes a system complex?" also fall into this category. There are a number of existing definitions of `complexity,' and while all of them capture some aspects of what makes intuitively complex systems distinctive, none is entirely satisfactory. Most existing accounts of complexity have been developed to work with information-theoretic objects (signals, for instance) rather than the physical and social systems studied by scientists. -/- Dynamical complexity, a concept articulated in detail in the first third of the dissertation, is designed to bridge the gap between the mathematics of contemporary complexity theory (in particular the formalism of "effective complexity" developed by Gell-Mann and Lloyd [2003]) and a more general account of the structure of science generally. Dynamical complexity provides a physical interpretation of the formal tools of mathematical complexity theory, and thus can be used as a framework for thinking about general problems in the philosophy of science, including theories, explanation, and lawhood. -/- Methodological questions include questions about how climate science constructs its models, on what basis we trust those models, and how we might improve those models. In order to answer questions about climate modeling, it's important to understand what climate models look like and how they are constructed. Climate model families are significantly more diverse than are the model families of most other sciences (even sciences that study other complex systems). Existing climate models range from basic models that can be solved on paper to staggeringly complicated models that can only be analyzed using the most advanced supercomputers in the world. I introduce some of the central concepts in climatology by demonstrating how one of the most basic climate models might be constructed. I begin with the assumption that the Earth is a simple featureless blackbody which receives energy from the sun and releases it into space, and show how to model that assumption formally. I then gradually add other factors (e.g. albedo and the greenhouse effect) to the model, and show how each addition brings the model's prediction closer to agreement with observation. After constructing this basic model, I describe the so-called "complexity hierarchy" of the rest of climate models, and argue that the sense of "complexity" used in the climate modeling community is related to dynamical complexity. -/- With a clear understanding of the basics of climate modeling in hand, I then argue that foundational issues discussed early in the dissertation suggest that computation plays an irrevocably central role in climate modeling. "Science by simulation" is essential given the complexity of the global climate, but features of the climate system--the presence of non-linearities, feedback loops, and chaotic dynamics--put principled limits on the effectiveness of computational models. This tension is at the root of the staggering pluralism of the climate model hierarchy, and suggests that such pluralism is here to stay, rather than an artifact of our ignorance. Rather than attempting to converge on a single "best fit" climate model, we ought to embrace the diversity of climate models, and view each as a specialized tool designed to predict and explain a rather narrow range of phenomena. Understanding the climate system as a whole requires examining a number of different models, and correlating their outputs. This is the most significant methodological challenge of climatology. -/- Climatology's role contemporary political discourse raises an unusually high number of evaluative questions for a physical science. The two leading approaches to crafting policy surrounding climate change center on mitigation (i.e. stopping the changes from occurring) and adaptation (making post hoc changes to ameliorate the harm caused by those changes). Crafting an effective socio-political response to the threat of anthropogenic climate change, however, requires us to integrate multiple perspectives and values: the proper response will be just as diverse and pluralistic as the climate models themselves, and will incorporate aspects of both approaches. I conclude by offering some concrete recommendations about how to integrate this value pluralism into our socio-political decision making framework. (shrink)

Book Review of "Trinity in Relation: Creation, Incarnation, and Grace in an Evolving Cosmos" by Gloria L. Schaab.

Chaos theory not only stretched the concept of chaos well beyond its traditional semantic boundaries, but it also challenged fundamental tenets of physics and science in general. Hence, its present and potential impact on the Western worldview cannot be underestimated. I will illustrate the relevance of chaos theory in regard to modern Western thought by tracing the concept of order, which modern thinkers emphasised as chaos’ dichotomic counterpart. In particular, I will underline how the concern of seventeenth-century natural philosophers with (...) order and conservation oriented the production of their concept of nature. Moreover, I will match this resulting world of natural facts with both the classical construction of the cosmos, and the nineteenth-century physico-chemical structure of conservation laws. Furthermore, I will recall the challenges to the deterministic and determinable modern scientific framework. These challenges arose from within the hard sciences, and they were often understood as a temporary lack of knowledge. I will argue that scientists long failed to acknowledge results that were at odds with their expectations, which were deeply engrained in modern Western thought, and which even harked back to the classical theoretical framework. Finally, I will suggest a link between the cultural earthquake that shook Western societies during the ‘long sixties,’ and the questioning of scientific expectations, which chaos theory defied. (shrink)