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Supersymmetry with Cadabra

High Energy Physics - Theory · Submitted 11 Dec 2021

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

The authors' main claim This article provides a quick guide to the implementation of supersymmetry with Cadabra, a symbolic computer algebra system.

how it is stated · asserted 0.99 read the record →

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arXiv ID2112.09158 (version 1)
Pith IDVX5LSSVR, Pith's permanent record of this paper and its review
CitationBehzad Mansouri. "Supersymmetry with Cadabra." arXiv:2112.09158 (2021). https://pith.science/paper/VX5LSSVR
Claim paper

The compiled record

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.

Open the compiled record

Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-09-23: 1 request, 2,936 input tokens.

What the abstract itself states, as probabilities: claims first 0.03 · states limitation 0.07 · human participants 0.02 · controlled comparison 0.01 · randomized assignment 0.01 · states quantitative result 0.02 · compares with prior results 0.04 · mentions code or data availability 0.06.

The abstract, sentence by sentence

arXiv listing abstract v1. Results and the main claim are underlined; .

This article provides a quick guide to the implementation of supersymmetry with Cadabra, a symbolic computer algebra system. Details are provided on the implementation of Grassmann variables, fermionic fields, supercharges, and superderivatives and the treatment of superfield expressions and supersymmetric Lagrangians. Finally, the automation of supersymmetric Lagrangian generation in the Cadabra programming framework is discussed.

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 This article provides a quick guide to the implementation of supersymmetry with Cadabra, a symbolic computer algebra system. contribution 0.97 0.69 0.12 asserted 0.99
s1 Details are provided on the implementation of Grassmann variables, fermionic fields, supercharges, and superderivatives and the treatment of superfield expressions and supersymmetric Lagrangians. method 0.53 0.73 0.08 asserted 1.00
s2 Finally, the automation of supersymmetric Lagrangian generation in the Cadabra programming framework is discussed. contribution 0.87 0.75 0.16 asserted 0.96

What kind of paper the classifier reports this is: method or tool 1.00 · evidence from simulation or computation 0.70.

What was examined, and what was not

sources read
  • arXiv listing abstract v1
not examined
  • full text
  • figures and tables
  • references and citing sentences
  • relations to other papers
levels run
  • P abstract
not run
  • 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

This article provides a quick guide to the implementation of supersymmetry with Cadabra, a symbolic computer algebra system. Details are provided on the implementation of Grassmann variables, fermionic fields, supercharges, and superderivatives and the treatment of superfield expressions and supersymmetric Lagrangians. Finally, the automation of supersymmetric Lagrangian generation in the Cadabra programming framework is discussed.

Human review
How the literature uses it

What this paper does with the arXiv papers it cites

Each citing sentence is taken from the citing paper's LaTeX source and typed by Pith's classifier. A label appears at probability 0.8 or more (0.95 for support), a contest at 0.7 or more; the quoted words are the citing authors'. How each label was checked · JSON

What it cites · 5 sentences without a confident label

Cites as background 5 papers

Discussion

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