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Record W2007605701 · doi:10.1139/cjp-2014-0261

Relativistic corrections to the central force problem in a generalized potential approach

2014· article· en· W2007605701 on OpenAlexvenueno aff
Ashmeet Singh, Binoy Krishna Patra

Bibliographic record

VenueCanadian Journal of Physics · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicExperimental and Theoretical Physics Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsHamiltonian (control theory)Central forcePotential energyClassical mechanicsSemiclassical physicsKinetic energyFifth forceRelativistic quantum chemistryWork (physics)Gravitational potentialGravitationQuantum electrodynamicsQuantum mechanicsDark energyCosmology

Abstract

fetched live from OpenAlex

We present a novel technique to obtain relativistic corrections to the central force problem in the Lagrangian formulation, using a generalized potential energy function. We derive a general expression for a generalized potential energy function for all powers of the velocity, which when made a part of the regular classical Lagrangian can reproduce the correct (relativistic) force equation. We then go on to derive the Hamiltonian and estimate the corrections to the total energy of the system up to the fourth power in |v|/c. We find a more comprehensive understanding of relativistic corrections to the central force results and provide corrections to both the kinetic and potential energy of the system. We employ our methodology to calculate relativistic corrections to the circular orbit under the gravitational force and also first-order corrections to the ground state energy of the hydrogen atom using a semiclassical approach. Our predictions in both problems give reasonable agreement with the known results. Thus we feel that this work has pedagogical value and can be used by undergraduate students to better understand the central force and the relativistic corrections to it.

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 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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.859
Threshold uncertainty score0.343

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 head0.007
GPT teacher head0.204
Teacher spread0.197 · 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 teacher head, 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

Citations1
Published2014
Admission routes1
Has abstractyes

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