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Record W2013720178 · doi:10.1139/p05-064

Laws of superposition of successive collinear Lorentz boosts

2005· article· en· W2013720178 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Journal of Physics · 2005
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCrystallography and Radiation Phenomena
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsPhysicsSuperposition principleLorentz transformationLorentz factorInfinitesimalClassical mechanicsMathematical physicsVelocity-addition formulaQuantum mechanicsMathematical analysisFour-momentum

Abstract

fetched live from OpenAlex

We derive the laws of superposition of multiple successive collinear Lorentz boosts by four different methods. The first method exploits the relation between the Pochhammers of 2 x 2 nonautonomous matrices and the symmetric functions. The second method proceeds by diagonalizing the Lorentz boost. The third method is based on the characteristics of the Pauli matrices. The fourth method makes use of the relativistic law of addition of multiple collinear velocities, as well as the polygonometric identities. We give expressions, for the laws of superposition, parametrized using velocity and rapidity, as well as expressions in compact, symmetric, and unified forms. We also give the expressions of the laws of superposition in the special case of identical boosts, both for finite boosts, and for infinitesimal boosts. These latter results provide insight into the relation between Galilean (classical) and Lorentzian (relativistic) velocities.PACS Nos.: 03.30.+p, 02.10.Yn, 02.10.Ox

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.500
Threshold uncertainty score0.298

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.006
GPT teacher head0.210
Teacher spread0.204 · 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