Cuffaro, M. E. and Hartmann, S. (eds.). Open Systems: Physics,
Metaphysics, and Methodology. Oxford University Press (in
preparation).
With chapters by: Emily Adlam, Luis C. Barbado and Caslav Brukner, Elena
Castellani and Emilia Margoni, Eddy K. Chen, Elise Crull, Michael E. Cuffaro
and Stephan Hartmann, Richard Dawid, Gemma De las Cuevas, George Ellis,
Doreen Fraser and Adam Koberinski, Sean Gryb and David Sloan, William
L. Harper, Molly Kao, James Ladyman and Karim Thébault, Olimpia
Lombardi, Wayne C. Myrvold, Daniele Oriti, Josh Quirke and Alistair Wilson,
Katie Robertson, Karim Thébault, Lev Vaidman, David Wallace.
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This book offers a thorough technical elaboration and philosophical defense of an objectivist informational interpretation of quantum mechanics according to which its novel content is located in its kinematical framework, that is, in how the theory describes systems independently of the specifics of their dynamics.
It will be of interest to researchers and students in the philosophy of physics and in theoretical physics with an interest in the foundations of quantum mechanics. Additionally, parts of the book may be used as the basis for courses introducing non-physics majors to quantum mechanics, or for self-study by those outside of the university with an interest in quantum mechanics.
'Understanding Quantum Raffles' is a wonderful book for both the specialists and those with curious minds. The elegance and the simplicity with which the 'three Mikes' explain some of the deepest aspects of quantum mechanics on the basis of probabilities and correlations are dazzling and delightful. The same elegance and simplicity also make the book ideal for any engaged reader who ever wondered what is so special about quantum mechanics. In our age of new quantum technologies, this is something anyone should read. (Guido Bacciagaluppi, author of Quantum Theory at the Crossroads)
This book makes a sustained argument for an informational interpretation of quantum theory, blending an elegant mathematical characterisation of quantum correlations with incisive historical and philosophical analysis. A must-read for those interested in quantum foundations, and also a fertile source of teaching inspiration for quantum theory. (Leah Henderson, Department of Theoretical Philosophy, University of Groningen)
This is one of the most fascinating and accessible presentations of the informational approach to quantum mechanics. What has so far been mostly restricted to the theoretical physics community is here masterfully explained for a broader audience even without a physics background. Scholars, students, and laypeople alike will appreciate the clear, vivid, and yet deep discussion of what raffle tickets and correlation elliptopes can tell us about the physics and philosophy of the quantum world. (Markus Müller, Institute for Quantum Optics and Quantum Information, Vienna)
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Chapters:
- Ontic Pancomputationalism, by
Neal
G. Anderson and
Gualtiero Piccinini,
- Relativistic Computation, by
Hajnal Andréka,
Judit X. Madarász,
István Németi,
Péter Németi, and
Gergely Székely,
- Zuse's Thesis, Gandy's Thesis, and Penrose's Thesis, by
Jack
Copeland,
Oron Shagrir, and
Mark Sprevak,
- How to Make Orthogonal Positions Parallel: Revisiting the Quantum
Parallelism Thesis, by
Armond
Duwell,
- Abstraction/Representation Theory and the Natural Science of
Computation, by
Dominic Horsman,
Viv Kendon, and
Susan Stepney,
- Quantum Theory as a Principle Theory: Insights from an
Information-Theoretic Reconstruction, by
Adam Koberinski and
Markus P. Müller,
- Intension in the Physics of Computation: Lessons from the Debate
About Landauer's Principle, by
James
Ladyman,
- Church's Thesis, Turing's Limits, and Deutsch's Principle, by
Rossella Lupacchini,
- How is There a Physics of Information? On Characterising Physical
Evolution as Information Processing, by
Owen
Maroney and
Chris
Timpson,
- Feasible Computation: Methodological Contributions from Computational
Science, by
Robert H. C. Moir,
- Maxwell's Demon Does Not Compute, by
John D. Norton,
- Physics-Like Models of Computation, by
Klaus Sutner.
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