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The Everett Interpretation

Emily Adlam

Published Jun 12, 2025• 0 citations
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Abstract

Abstract This chapter discusses what would need to be done to address the epistemic difficulties associated with the Everett interpretation, then considers a number of putative solutions to the Everettian probability problem and assesses whether these approaches succeed in solving the epistemic aspects of that problem. The discussion covers naïve branch counting and Saunders’ sophisticated branch counting; Vaidman’s ‘measure of existence’ approach; the Deutsch-Wallce decision-theoretic approach; and the Sebens-Carroll and Vaidman-McQueen self-locating uncertainty approaches.

DOI
10.1093/9780197808887.003.0006

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Abstract This chapter discusses what would need to be done to address the epistemic difficulties associated with the Everett interpretation, then considers a number of putative solutions to the Everettian probability problem and assesses whether these approaches succeed in solving the epistemic aspects of that problem. The discussion covers naïve branch counting and Saunders’ sophisticated branch counting; Vaidman’s ‘measure of existence’ approach; the Deutsch-Wallce decision-theoretic approach; and the Sebens-Carroll and Vaidman-McQueen self-locating uncertainty approaches.
The current landscape of views on chance in the Everett interpretation is rocky. Everettians (Wallace 2012, Sebens and Carroll 2018, McQueen and Vaidman 2019) agree that chance should be derived using principles governing uncertain or partial belief, but they cannot agree on how. Critics (Baker 2007, Dawid and Thébault 2015, Mandolesi 2019) maintain that any such approach is circular. We smooth the landscape by shifting focus from what Everettians take to be uncertain to what they should think is certain: namely, the conditions under which branches are isolated. Our approach to isolation resolves the main tensions among the different Everettian chance derivations while clarifying how they avoid circularity.
I consider exactly what is involved in a solution to the probability problem of the Everett interpretation, in the light of recent work on applying considerations from decision theory to that problem. I suggest an overall framework for understanding probability in a physical theory, and conclude that this framework, when applied to the Everett interpretation, yields the result that that interpretation satisfactorily solves the measurement problem. 1. Introduction 2. What is probability? 2.1Objective probability and the Principal Principle 2.2Three ways of satisfying the functional definition 2.3Cautious functionalism 2.4Is the functional definition complete? 3. The Everett interpretation and subjective uncertainty 3.1Interpreting quantum mechanics 3.2The need for subjective uncertainty 3.3Saunders' argument for subjective uncertainty 3.4Objections to Saunders' argument 3.5Subjective uncertainty again: arguments from interpretative charity 3.6Quantum weights and the functional definition of probability 4. Rejecting subjective uncertainty 4.1The fission program 4.2Against the fission program 5. Justifying the axioms of decision theory 5.1The primitive status of the decision-theoretic axioms 5.2Holistic scepticism 5.3The role of an explanation of decision theory 6. Conclusion
This chapter extends chapter 5's formal proof into a general discussion of how we should assess evidence — and, in particular, how we should test scientific theories — given the possibility that Everettian quantum mechanics is correct. The chapter proves — initially with informal arguments, but in due course with full mathematical rigor — that rational scientists should treat the branch weights assigned by quantum theory to quantum-mechanical branches exactly as if they were probabilities; as such, the chapter argues, probability is actually on firmer conceptual footing in quantum theory than in classical physics. After a brief digression to consider probability in approaches to quantum theory other than the Everett interpretation, the chapter concludes by placing the work in the broader context of recent work on Everett probability.
A longstanding issue in attempts to understand the Everett (many-worlds) approach to quantum mechanics is the origin of the Born rule: why is the probability given by the square of the amplitude? Following Vaidman, we note that observers are in a position of self-locating uncertainty during the period between the branches of the wave function splitting via decoherence and the observer registering the outcome of the measurement. In this period, it is tempting to regard each branch as equiprobable, but we argue that the temptation should be resisted. Applying lessons from this analysis, we demonstrate (using methods similar to those of Zurek’s envariance-based derivation) that the Born rule is the uniquely rational way of apportioning credence in Everettian quantum mechanics. In doing so, we rely on a single key principle: changes to the environment alone do not affect the probabilities one ought to assign to measurement outcomes in a local subsystem. We arrive at a method for assigning probabilities in cases that involve both classical and quantum self-locating uncertainty. This method provides unique answers to quantum Sleeping Beauty problems, as well as a well-defined procedure for calculating probabilities in quantum cosmological multiverses with multiple similar observers. 1. Introduction2. Preliminaries: Many-Worlds, Self-locating Uncertainty, and Branch-counting 2.1. The many-worlds interpretation2.2. Self-locating uncertainty and the Everettian multiverse2.3. Indifference and the quantitative probability problem2.4. Against branch-counting3. The Epistemic Irrelevance of the Environment 3.1. The epistemic separability principle3.2. Deriving the Born rule4. Varieties of Uncertainty 4.1. Epistemic separability principle and indifference4.2. Mixed uncertainties4.3. Large universe cosmology and the quantum multiverse5. Probability in Practice 5.1. Betting and branching5.2. Theory confirmation6. Comparison to Other Approaches 6.1. Zurek’s envariance-based derivation of the Born rule6.2. The decision-theoretic programme7. ConclusionAppendix