Abstract The introduction gives an overview of the philosophical problem of agency: How does agency fit into the natural world as described by the sciences? We introduce the general methodology of modelling and specify what that means in the case of agency, where an initial explication of the notion is required. We briefly introduce the agency model of Projective Simulation to be discussed later in the book. We mention that the notion of experiment takes on a special role in quantum mechanics, because the experimenter’s active role is ineliminable there. The introduction also includes a per-chapter overview of the five main chapters of the book.
Abstract The introduction gives an overview of the philosophical problem of agency: How does agency fit into the natural world as described by the sciences? We introduce the general methodology of modelling and specify what that means in the case of agency, where an initial explication of the notion is required. We briefly introduce the agency model of Projective Simulation to be discussed later in the book. We mention that the notion of experiment takes on a special role in quantum mechanics, because the experimenter’s active role is ineliminable there. The introduction also includes a per-chapter overview of the five main chapters of the book.
Abstract The approach to quantum mechanics that we present in this book aligns fairly well with the QBist position in quantum foundations, which takes quantum mechanics as describing the interaction of an agent with the world: A theory mainly offers a way for the agent to manage her expectations about the outcomes of her interactions, not a picture of what nature is really like. We introduce QBism briefly and situate the framework within a range of options for integrating agency and quantum mechanics. We agree with QBism on many fundamental issues, but we do not subscribe to QBism wholesale. We agree with QBism’s pragmatic outlook that takes scientific theories to be tools for agents to use, and with the QBist goal of developing a participatory realism. But we are critical of the particular idealisations that QBism in its present form subscribes to. Most importantly, we are critical of the structural choice not to resolve the agent nor the world in any detail. In our view, scientific agents learn by modelling. Models are tools that agents can use and develop in dealing with the world. Guided by concrete examples, we describe a scientific modelling framework that allows for loops of three different degrees of difficulty and complexity. These range from quantum state updating, which neatly fits the QBist approach of working within a fixed probability space, via a broader class of updates including so-called Hamiltonian learning, up to the most difficult cases in which true scientific creativity is at play. All three levels of difficulty need to be acknowledged for a full picture of real scientific agency. At the end of the chapter, we describe the project of modelling scientific agency itself, which leads to the topics of Chaps. 5 and 6 .
Quantum theory underpins much of modern physics and its implications draw the attention of industry, academia and public funding agencies. However there are many unsettled conceptual and philosophical problems in the interpretation of quantum mechanics which are a matter of extensive debate. These hotly debated topics include the meaning of the wave function, the nature of the quantum objects, the role of the observer, the non-locality of the quantum world, and the emergence of classicality from the quantum domain. Containing chapters written by eminent researchers from the fields of physics and philosophy, this book provides interdisciplinary, comprehensive and up-to-date perspectives of the problems related to the interpretation of quantum theory. It is ideal for academic researchers in physics and philosophy working on the ontology of quantum mechanics.
Abstract Quantum mechanics is our most successful and versatile account of the basic constituents of matter, of their interaction and of their compounds. We introduce the theory via a sketch of its history and lay out its mathematical structure in some detail. Before this background we address the important and controversial question of how to interpret that structure. We contextualise our own position, which is linked to our account of ontological emergence as detailed in Chap. 2 , and which is mathematically best expressed in the Heisenberg picture of quantum dynamics. Indeterminism and irreversible processes are fundamental for our approach. We discuss the dialectics of the deterministic challenge to our position and argue that indeterminism in the form of quantum randomness has turned from a philosophical riddle to a technological resource. This claim is supported by a discussion of quantum information science, including some of its basic protocols. Towards the end of the chapter we argue that agency and quantum mechanics come as a package deal. For one, quantum mechanics describes the world as offering open possibilities for the future at a fundamental physical level, which is needed for real higher-order organisation, including agency. Of course, this does not in any way show that the actual existence of agents in our world is guaranteed. But it does show that general agency scepticism has no basis in physics. Second, we show that quantum mechanics is best understood as a theory that describes our agential interactions with nature, and not as a theory that represents nature from the point of view of an inert, detached observer.
The Introduction provides the reader with a more detailed overview over the goal and the approach of this book, including the new features against previous publications. Special attention is paid to the importance of notions and to the relationship between classical and quantum mechanics. Another key topic is Schrödinger’s forgotten 1926 requirements to any path from classical to quantum mechanics. The approach of this book fulfills all four of them, and this will help to overcome several difficulties of interpretation. Mittelstaedt’s “reconstruction” of quantum mechanics is discussed in some detail, because there are several similarities to that approach. The Introduction concludes with the key lines along which this book is organized.
This introduction presents an overview of the key concepts discussed in the subsequent chapters of this book. The book explores the minimalist ontology of matter points and their dynamics in general philosophical as well as mathematical terms, independently of any particular physical theory. It shows how this ontology fits both classical mechanics of gravitation and quantum mechanics, as long as the latter includes a primitive ontology of matter distributed in ordinary space, as in Bohmian mechanics. The book points out the similarities between these two theories as well as their differences. It explains how in both cases one gets from an ontology and a dynamics defined for the universe as a whole to a description of subsystems of the universe and a dynamics for them. The book shows how an ontology of persisting particles that move according to a deterministic law can explain the characteristic phenomena of quantum field theory and ground its empirical predictions.
Abstract Attempts to understand various aspects of the empirical world often rely on modelling processes that involve a reconstruction of the system(s) under investigation. Typically the reconstruction uses mathematical frameworks like gauge theory and renormalisation group methods, but more recently simulations also have become an indispensable tool for investigation. In fact, many areas of physics as well as other disciplines rely on simulation knowledge when traditional experiments are impossible or prohibitively expensive. This book is a philosophical examination of the various techniques and assumptions related to modelling and simulation, with the goal of showing how these abstract descriptions can contribute to our understanding of the physical world. Particular issues include the role of fictional models in science, how mathematical formalisms can yield physical information, and how we should approach the use of inconsistent models for specific types of systems. It also addresses the role of simulation, specifically the conditions under which simulation can be seen as a technique for measurement, replacing more traditional experimental approaches. Inherent worries about the legitimacy of simulation "knowledge" are also addressed, including an analysis of verification and validation and the role of simulation data in the search for the Higgs boson. In light of the significant role played by simulation in the Large Hadron Collider (LHC) experiments, it is argued that the traditional distinction between simulation and experiment is no longer applicable in some contexts of modern science. Consequently, a reevaluation of the way and extent to which simulation delivers empirical knowledge is required.