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Subjective and Objective Probabilities in Quantum Mechanics

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Paper breakdownThe authors' claims, conditions and measurements, as JSON Signed receiptProof this review has not been altered
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Mark Srednicki

Quantum Physics · Submitted 3 Jan 2005

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim We discuss how the apparently objective probabilities predicted by quantum mechanics can be treated in the framework of Bayesian probability theory, in which all probabilities are subjective.

how it is stated · asserted 0.55 read the record →

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arXiv IDquant-ph/0501009 (version 2)
Pith IDLZKBUUW7, Pith's permanent record of this paper and its review
CitationMark Srednicki. "Subjective and Objective Probabilities in Quantum Mechanics." arXiv:quant-ph/0501009 (2005). https://pith.science/paper/LZKBUUW7
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The compiled record

The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

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Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-09-23: 1 request, 2,876 input tokens.

What the abstract itself states, as probabilities: claims first 0.03 · states limitation 0.13 · human participants 0.02 · controlled comparison 0.02 · randomized assignment 0.01 · states quantitative result 0.03 · compares with prior results 0.92 · mentions code or data availability 0.01.

The abstract, sentence by sentence

arXiv listing abstract v2. Results and the main claim are underlined; .

We discuss how the apparently objective probabilities predicted by quantum mechanics can be treated in the framework of Bayesian probability theory, in which all probabilities are subjective. Our results are in accord with earlier work by Caves, Fuchs, and Schack, but our approach and emphasis are different. We also discuss the problem of choosing a noninformative prior for a density matrix.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 We discuss how the apparently objective probabilities predicted by quantum mechanics can be treated in the framework of Bayesian probability theory, in which all probabilities are subjective. contribution 0.93 0.66 0.59 asserted 0.55
s1 Our results are in accord with earlier work by Caves, Fuchs, and Schack, but our approach and emphasis are different. background 0.64 0.40 0.07 asserted 0.78
s2 We also discuss the problem of choosing a noninformative prior for a density matrix. contribution 0.89 0.45 0.05 unclear 0.54

What kind of paper the classifier reports this is: position or commentary 0.96 · evidence from argument 0.98.

What was examined, and what was not

sources read
  • arXiv listing abstract v2
not examined
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  • figures and tables
  • references and citing sentences
  • relations to other papers
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  • P abstract
not run
  • S sections
  • T body sentences
  • C citations
  • R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

We discuss how the apparently objective probabilities predicted by quantum mechanics can be treated in the framework of Bayesian probability theory, in which all probabilities are subjective. Our results are in accord with earlier work by Caves, Fuchs, and Schack, but our approach and emphasis are different. We also discuss the problem of choosing a noninformative prior for a density matrix.

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References
How the literature uses it

3 arXiv papers cite this in 3 sentences

Each citing sentence is taken from the citing paper's LaTeX source and typed by Pith's classifier. A label appears at probability 0.8 or more (0.95 for support), a contest at 0.7 or more; the quoted words are the citing authors'. How each label was checked · JSON

Papers citing it · 1 sentence without a confident label

Cites it as background 2 papers
  • The general context is Bayesian probability theory[For a compact introduction, see [ref] ; for complete details, see [ref] ; for arguments for the necessity of the Bayesian point of view, see [ref] .].

    Quantum Mechanics with Extended Probabilities · Probability · 1.00

  • (For a compact introduction, see [ref] ; for complete details, see [ref] ; for an elegant presentation of the necessity of the Bayesian point of view, see [ref] .) Suppose we have a set of theories that we wish to discriminate between.

    Are We Typical? · Testing theories using Bayesian Probabilities · 0.99

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