James Ladyman

University of Bristol, Philosophy, Faculty Member

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I am interested in most areas of philosophy, but my work has primarily been in philosophy of science. I have worked extensively on scientific realism, constructive empiricism and structural realism (I made the distinction in my 1998 paper between epistemic and ontic forms of structural realism and I have defended the latter). I have also worked on scientific representation and more recently on physicalism, the relationship between the special sciences and physics, naturalised metaphysics, the philosophy of information and computation, and the philosophy of mathematics. I have always been interested in the philosophy of physics, especially quantum mechanics, and work specifically on identity and individuality in quantum mechanics and time-symmetric quantum mechanics. I am currently trying to understand Quantum Field Theory.

I am currently writing a textbook, Philosophy of Physics, and co-editing a collection of papers in philosophy of science with Alexander Bird, Arguing about Science. I am also co-editing a book with Don Ross, Scientific Metaphysics, which will feature papers by Anjan Chakravartty, Daniel Dennett, Michael Friedman, Jenann Ismael, Andrew Melnyk and Mark Wilson, and an introduction by Harold Kincaid. I am also currently writing a paper with Don Ross, to appear in the volume.
Address: The University of Bristol,
Department of Philosophy,
9 Woodland Road,
Bristol
BS8 1TB

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Books by James Ladyman

Scientific Metaphysics

by Don Ross and James Ladyman

The book gathers original essays by leading philosophers on the question of whether, and how, met... more The book gathers original essays by leading philosophers on the question of whether, and how, metaphysics should be naturalized. Though naturalization has been used to mean a variety of different things, in this book it is generally taken to refer to the project of making metaphysics a part of natural science, motivated by the same aims and subject to the same demands as science. Of course, there is rich room for debate about just what these aims and demands are, and over whether any specific kind of metaphysics could achieve and satisfy them. The book includes a rich range of perspectives on these debates. (It does not aim to include voices defending traditional, non-naturalized metaphysics.) In the course of this, numerous related sub-topics are treated in detail. These include the general nature of reality according to physics, the relationships between physics and special sciences, the relationship between scientific and everyday ideas of mind, subjectivity and the kinds of things there are, and attitudes toward metaphysics among historical precursors of contemporary views, such as Kant, Quine, and Peirce. Contributors are Anjan Chakravartty, Daniel Dennett, Michael Friedman, Paul Humphreys, Jenann Ismael, Harold Kincaid, James Ladyman, Andrew Melnyk, Don Ross and Mark Wilson.

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Everything Must Go: Metaphysics Naturalised

Understanding Philosophy of Science

Papers by James Ladyman

Philosophy of Science

Bloomsbury Academic eBooks, 2015

Philosophy of Science

The Bloomsbury Companion to Analytic Philosophy, 2014

What Is a Complex System?

Yale University Press eBooks, Aug 5, 2020

What is a complex system? Although “complexity science” is used to understand phenomena as divers... more What is a complex system? Although “complexity science” is used to understand phenomena as diverse as the behavior of honeybees, the economic markets, the human brain, and the climate, there is no agreement about its foundations. In this introduction for students, academics, and general readers, the authors develop an account of complexity that brings the different concepts and mathematical measures applied to complex systems into a single framework. The book begins with an overview and a brief history of complexity science. Complexity science is relatively new but already indispensable. Many of the most important problems in engineering, medicine, and public policy are now addressed with the ideas and methods of complexity science. The conceptual foundations of complexity science are disputed, and there are many and diverging views among scientists about what complexity and complex systems are. Its origins lie in cybernetics and systems theory and it is related to dynamical systems theory and the study of cellular automata. The book introduces the different features of complex systems and discusses different conceptions of complexity with the authors documenting their own account. In do so, they explain why complexity science is so important in today's world.

The Extended Mind

Features of Complex Systems

Yale University Press eBooks, Aug 5, 2020

This chapter uses the representative examples of complex systems discussed in the previous chapte... more This chapter uses the representative examples of complex systems discussed in the previous chapter to arrive at a list of the distinctive features of complex systems. These features include numerosity; disorder and diversity; feedback; and non-equilibrium. The interesting thing about complex systems is that these conditions can give rise to the following products: spontaneous order and self-organisation; nonlinearity; robustness; nested structure and modularity; history and memory; and adaptive behaviour. Not all these features are present in all complex systems. Whenever any of the products are found in a system, they are the collective result of the conditions, but not all the products are found in all complex systems. Often products help produce other products — for example, memory is impossible without a degree of robustness, and adaptive behaviour can build nested structure and modularity. The chapter considers each of them in turn in more detail and assesses whether each is necessary and/or sufficient for complexity on any or some conceptions of what complex systems are.

Measuring Features of Complex Systems

Yale University Press eBooks, Aug 5, 2020

This chapter offers a guide to quantifying complexity based on the fruits of the analysis of the ... more This chapter offers a guide to quantifying complexity based on the fruits of the analysis of the previous chapters. Many measures of complexity have been proposed since scientists first began to study complex systems, and the list is still growing. If complexity is a collection of features rather than a single phenomenon, then all quantitative measures of complexity can quantify only aspects of complexity rather than complexity as such. The chapter demonstrates the truism of complexity science that it is computational and probabilistic. It also further explains some of the new kinds of invariance and forms of universal behaviour that emerge when complex systems are modelled as networks and information-processing systems. The chapter then looks at a few, by now classic, measures of complexity from the 1980s and 1990s, including effective complexity, effective measure complexity, statistical complexity, and logical depth.

Materialism

Routledge eBooks, Apr 29, 2019

Do weak values show the past of a quantum particle?

arXiv (Cornell University), Sep 28, 2021

We investigate four key issues with using a nonzero weak value of the spatial projection operator... more We investigate four key issues with using a nonzero weak value of the spatial projection operator to infer the past path of an individual quantum particle. First, we note that weak measurements disturb a system, so any approach relying on such a perturbation to determine the location of a quantum particle describes the state of a disturbed system, not that of a hypothetical undisturbed system. Secondly, even assuming no disturbance, there is no reason to associate the non-zero weak value of an operator containing the spatial projection operator with the classical idea of 'particle presence'. Thirdly, weak values are only measurable over ensembles, and so to infer properties of individual particles from values of them is problematic. Finally, weak value approaches to the path of a particle do not provide information beyond standard quantum mechanics (and the classical modes supporting the experiment). We know of no experiment with testable consequences that demonstrates a connection between particle presence and weak values.

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Is the dynamical quantum Cheshire cat detectable?

arXiv (Cornell University), Apr 7, 2022

We explore how one might detect the dynamical quantum Cheshire cat proposed by Aharonov et al. We... more We explore how one might detect the dynamical quantum Cheshire cat proposed by Aharonov et al. We show that, in practice, we need to bias the initial state by adding/subtracting a small probability amplitude ('field') of the orthogonal state, which travels with the disembodied property, to make the effect detectable (i.e. if our initial state is |↑z⟩, we need to bias this with some small amount δ of state |↓z⟩). This biasing, which can be done either directly or via weakly entangling the state with a pointer, effectively provides a phase reference with which we can measure the evolution of the state. The outcome can then be measured as a small probability difference in detections in a mutually unbiased basis, proportional to this biasing δ. We show this is different from counterfactual communication, which provably does not require any probe field to travel between sender Bob and receiver Alice for communication. We further suggest an optical polarisation experiment where these phenomena might be demonstrated in a laboratory.

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Review: Philosophy in the Next Century

Prediction and confi rmation

The challenges to materialism from post-Newtonian physics

Materialism in the nineteenth century

Structural Realism

Oxford Bibliographies Online Datasets, Aug 26, 2013

Reduction, Abstraction, Analysis: Proceedings of the 31st International Ludwig Wittgenstein-Symposium in Kirchberg, 2008

What is a complex system?

European journal for philosophy of science, Jun 19, 2012

Complex systems research is becoming ever more important in both the natural and social sciences.... more Complex systems research is becoming ever more important in both the natural and social sciences. It is commonly implied that there is such a thing as a complex system across the disciplines. However, there is no concise definition of a complex system, let alone a definition that all disciplines agree on. We review various attempts to characterize a complex system, and consider a core set of features that are widely associated with complex systems by scientists in the field. We argue that some of these features are neither necessary nor sufficient for complexity, and that some of them are too vague or confused to be of any analytical use. In order to bring mathematical rigour to the issue we then review some standard measures of complexity from the scientific literature, and offer a taxonomy for them, before arguing that the one that best captures the qualitative notion of complexity is that of the statistical complexity. Finally, we offer our own list of necessary conditions as a characterization of complexity. These conditions are qualitative and may not be jointly sufficient for complexity. We close with some suggestions for future work.

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Philosophy of science as epistemology and metaphysics

Scientific Metaphysics

by Don Ross and James Ladyman

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Everything Must Go: Metaphysics Naturalised

Understanding Philosophy of Science

Philosophy of Science

Bloomsbury Academic eBooks, 2015

Philosophy of Science

The Bloomsbury Companion to Analytic Philosophy, 2014

What Is a Complex System?