Bibliographic record
Abstract
The entangled quantum states play a key role in quantum information. The association of the quantum state vector with each individual physical system in an attributive way is a source of many false paradoxes and inconsistencies. The paradoxes are avoided if the purely statistical interpretation (SI) of the quantum state vector is adopted. According the SI the quantum theory (QT) does not provide any deterministic prediction for any individual experimental result obtained for a free physical system, for a trapped ion or for a quantum dot. In this article it is shown that if the SI is used then, contrary to the general belief, the QT does not predict for the ideal spin singlet state perfect anti-correlation of the coincidence coumts for the distant detectors. Subsequently the various proofs of the Bell's theorem are reanalyzed and in particular the importance and the implications of the use of the unique probability space in these proofs are elucidated. The use of the unique probability space is shown to be equivalent to the use of the joint probability distributions for the non commuting observables. The experimental violation of the Bell's inequalities proves that the naive realistic particle like spatio- temporal description of the various quantum mechanical experiments is impossible. Of course it does not give any argument for the action at the distance and it does not provide the proof of the completeness of the QM. The fact that the quantum state vector is not an attribute of a single quantum system and that the quantum observables are contextual has to be taken properly into account in any implementation of the quantum computing device.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".