Evidence map›Paper›PMID 37091949›Full record

ArticleMethodsX2023

Quantum field lens coding and classification algorithm to predict measurement outcomes.

Philip B Alipour, T Aaron Gulliver

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in MethodsX, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Philip B AlipourDepartment of Electrical and Computer Engineering, University of Victoria, Victoria BC, V8W 2Y2, Canada.
T Aaron GulliverDepartment of Electrical and Computer Engineering, University of Victoria, Victoria BC, V8W 2Y2, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study develops a method to implement a quantum field lens coding and classification algorithm for two quantum double-field (QDF) system models: 1- a QDF model, and 2- a QDF lens coding model by a DF computation (DFC). This method determines entanglement entropy (EE) by implementing QDF operators in a quantum circuit. The physical link between the two system models is a quantum field lens coding algorithm (QF-LCA), which is a QF lens distance-based, implemented on real

Indexed as

DF ComputationEntanglement entropyQDF Lens codingQDF TransformationQuantum artificial intelligenceQuantum double-fieldQuantum field lens coding and classification (QF-LCC)Quantum fourier transformQuantum lens distance-based classification

Identifiers

PMID37091949
PMCPMC10114244

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.