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Regularization, Renormalization, and Dimensional Analysis: Dimensional Regularization meets Freshman E&M

High Energy Physics - Phenomenology · Submitted 18 Dec 2008

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim We contrast this approach with the cutoff regularization approach, and demonstrate that dimensional regularization preserves the translational symmetry.

how it is stated · asserted 1.00 read the record →

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arXiv ID0812.3578 (version 2)
Pith IDTV54PQEE, Pith's permanent record of this paper and its review
CitationFredrick Olness, Randall Scalise. "Regularization, Renormalization, and Dimensional Analysis: Dimensional Regularization meets Freshman E&M." arXiv:0812.3578 (2008). https://pith.science/paper/TV54PQEE
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The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

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Compiled by classifier-1.13-20260917 via OpenRouter, question bank abstract-p1-20260923, 2026-09-23: 1 request, 3,549 input tokens, $0.0001 reported.

What the abstract itself states, as probabilities: claims first 0.02 · states limitation 0.07 · human participants 0.02 · controlled comparison 0.24 · randomized assignment 0.01 · states quantitative result 0.03 · compares with prior results 0.90 · mentions code or data availability 0.02.

The abstract, sentence by sentence

arXiv listing abstract v2. Results and the main claim are underlined; .

We illustrate the dimensional regularization technique using a simple problem from elementary electrostatics. We contrast this approach with the cutoff regularization approach, and demonstrate that dimensional regularization preserves the translational symmetry. We then introduce a Minimal Subtraction (MS) and a Modified Minimal Subtraction (MS-Bar) scheme to renormalize the result. Finally, we consider dimensional transmutation as encountered in the case of compact extra-dimensions.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 We illustrate the dimensional regularization technique using a simple problem from elementary electrostatics. contribution 0.79 0.89 0.07 asserted 1.00
s1 We contrast this approach with the cutoff regularization approach, and demonstrate that dimensional regularization preserves the translational symmetry. result 0.54 0.91 0.25 asserted 1.00
s2 We then introduce a Minimal Subtraction (MS) and a Modified Minimal Subtraction (MS-Bar) scheme to renormalize the result. method 0.87 0.88 0.08 asserted 0.96
s3 Finally, we consider dimensional transmutation as encountered in the case of compact extra-dimensions. contribution 0.93 0.69 0.11 asserted 0.81

What kind of paper the classifier reports this is: theoretical result 0.73 · evidence from proof or derivation 1.00.

What was examined, and what was not

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  • arXiv listing abstract v2
not examined
  • full text
  • figures and tables
  • references and citing sentences
  • relations to other papers
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  • P abstract
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  • S sections
  • T body sentences
  • C citations
  • R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

We illustrate the dimensional regularization technique using a simple problem from elementary electrostatics. We contrast this approach with the cutoff regularization approach, and demonstrate that dimensional regularization preserves the translational symmetry. We then introduce a Minimal Subtraction (MS) and a Modified Minimal Subtraction (MS-Bar) scheme to renormalize the result. Finally, we consider dimensional transmutation as encountered in the case of compact extra-dimensions.

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