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Record W4381586516 · doi:10.48550/arxiv.2306.11549

Experience in quantum physics: toward a theory of everything

2023· preprint· en· W4381586516 on OpenAlexfundno aff
Ding Jia

Bibliographic record

VenuearXiv (Cornell University) · 2023
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicQuantum Mechanics and Applications
Canadian institutionsnot available
FundersInstitut Périmètre de physique théoriqueGovernment of CanadaMinistero dello Sviluppo EconomicoInnovation, Science and Economic Development Canada
KeywordsQuantum gravityTheoretical physicsExperiential learningQuantumRelation (database)EpistemologyPhysicsMathematical economicsMathematicsComputer scienceQuantum mechanicsPhilosophyMathematics education

Abstract

fetched live from OpenAlex

A theory of everything should not only tell us the laws for matter, gravity, and possibly boundary condition for the universe. In addition, it should specify the relation between theory and experience. Here I argue for a minimal prescription in extracting empirical predictions from path integrals by showing that alternative prescriptions are unjustifiable. In this minimal prescription, the relative probability for one experience is obtained by summing over all configurations compatible with that experience, without any further restriction associated with other experiences of the same or other experiential beings. An application to Wigner's friend settings shows that quantum theory admits objective predictions for subjective experiences. Still, quantum theory differs from classical theory in offering individualized as opposed to collective accounts of experiences. This consideration of experience in fundamental theories issues several challenges to popular quantum interpretations, and points to the outstanding need for a theory of experience in understanding physical theories of everything.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.018
Scholarly communication0.0050.014
Open science0.0020.003
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.144
GPT teacher head0.233
Teacher spread0.089 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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