Bibliographic record
Abstract
Quantum electrodynamicsThe single most important field theory is electromagnetism.It is responsible for atomic structure and for the great diversity of materials around us: solids, liquids, and gases.The development of nonrelativistic manybody theory was stimulated primarily by solid state and condensed matter physics, where the potentials used all derive from electromagnetism.This compels us to study quantum electrodynamics at high temperatures and densities where the motion of the electrons becomes relativistic.In metals, the density of plasma electrons rarely exceeds a few electrons per cubic angstrom.This means that the Fermi momentum, k F = (3π 2 n e ) 1/3 , is of order 10 keV at most.Unfortunately, it is difficult to test relativistic many-body theory in the basement of the physics building in table-top experiments!Our attention must then be directed toward astrophysical and cosmological applications.Dense astrophysical objects, such as white dwarf stars, will be considered in Chapter 16.There is another reason for developing the theory of QED at high temperature and density, and that is the extension to a nonabelian gauge theory, quantum chromodynamics (QCD).We may be able to study QCD at high energy density in terrestrial experiments by colliding energetic heavy nuclei (see Chapter 14). Quantizing the electromagnetic fieldFirst, let us consider the electromagnetic field in the absence of charged particles.From classical physics we can write down a field strength tensor as
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.078 | 0.031 |
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".