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Record W4399349024 · doi:10.1007/978-3-031-51443-2_4

Introduction to Quantum Mechanics in Computational Chemistry

2024· book-chapter· en· W4399349024 on OpenAlexaff
Errol G. Lewars

Bibliographic record

VenueComputational Chemistry · 2024
Typebook-chapter
Languageen
FieldChemistry
TopicMolecular spectroscopy and chirality
Canadian institutionsTrent University
Fundersnot available
KeywordsTheoretical physicsChemistryPhysics

Abstract

fetched live from OpenAlex

A historical view demystifies the subject. The focus is strongly on chemical applications of quantum mechanics (QM). The use of QM in computational chemistry is shown by explaining the Schrödinger equation and showing how this led to the simple Hückel method, from which the extended Hückel method followed. This sets the stage well for ab initio theory, in Chap. 5 . QM grew out of studies of blackbody radiation and of the photoelectric effect. Besides QM, radioactivity and relativity contributed to the transition from classical to modern physics. The classical Rutherford nuclear atom, the Bohr atom, and the Schrödinger wave mechanical atom are discussed. Hybridization, wavefunctions, matrices and determinants, and other basic concepts are explained. For obtaining eigenvectors and eigenvalues from the secular equations, the elegant and simple matrix diagonalization method is explained and used. All the necessary mathematics for this is explained.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.520
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.001

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 head0.009
GPT teacher head0.245
Teacher spread0.236 · 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.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations2
Published2024
Admission routes1
Has abstractyes

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