Large Grants
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Previous Programs

2020 Consciousness in the Physical World

2019 Intelligence in the Physical World

2019 Information as Fuel

2018 Agency in the Physical World
Awardees; RFP download

2016 Physics of the Observer
Awardees; RFP download

2015 The Physics of What Happens
Awardees; RFP download

2013 Physics of Information
Awardees; RFP download

2010 The Nature of Time
Awardees; RFP download

2008 Foundational Questions in Physics and Cosmology
Awardees; RFP download

2006 Foundational Questions in Physics and Cosmology
Awardees; RFP download

Giulio Chiribella
University of Hong Kong

Adán Cabello
University of Seville

Matthias Kleinmann
University of the Basque Country

Project Title

The Observer Observed: a Bayesian Route to the Reconstruction of Quantum Theory

Project Summary

Quantum theory portrays a world where the outcomes of individual measurements cannot be predicted with certainty. But despite this apparent weakness, the quantum predictions are strikingly successful in many applications. Such a success demands for an explanation: Is quantum theory successful because it captures a bundle of primitive facts about the world? Or is it successful because it is a general-purpose tool for guessing the outcomes of our experiments? A new quantum interpretation, called Quantum Bayesianism (QBism), vigorously argues for the second alternative, regarding quantum theory as a "manual for betting agents". Still, it is not clear why an agent should opt for quantum theory, instead of classical probability theory or more exotic alternatives. Also, it is not clear how the agent-centric approach of QBism can be reconciled with the requirement that the laws of physics should transcend the viewpoint of individual observers. We believe that the solution to both puzzles is hidden in the curious way in which quantum theory combines the perspectives of different observers. Following this clue, we are seeking a derivation of quantum theory from basic principles regulating how different agents can formulate their pictures of reality in a consistent and maximally predictive fashion.

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