Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 554

The DOI matches its Crossref record.

Discrete-scale invariance and complex dimensions

Open access
Sornette, Didier·1998·Physics Reports

Abstract

Abstract We discuss the concept of discrete-scale invariance and how it leads to complex critical exponents (or dimensions), i.e. to the log-periodic corrections to scaling. After their initial suggestion as formal solutions of renormalization group equations in the 1970s, complex exponents have been studied in the 1980s in relation to various problems of physics embedded in hierarchical systems. Only recently has it been realized that discrete-scale invariance and its associated complex exponents may appear “spontaneously” in Euclidean systems, i.e. without the need for a pre-existing hierarchy. Examples are diffusion-limited-aggregation clusters, rupture in heterogeneous systems, earthquakes, animals (a generalization of percolation) among many other systems. We review the known mechanisms for the spontaneous generation of discrete-scale invariance and provide an extensive list of situations where complex exponents have been found. This is done in order to provide a basis for a better fundamental understanding of discrete-scale invariance. The main motivation to study discrete-scale invariance and its signatures is that it provides new insights in the underlying mechanisms of scale invariance. It may also be very interesting for prediction purposes.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/s0370-1573(97)00076-8

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 554

Metadata

Authors
Sornette, D.
Venue
Physics Reports
Publisher
Elsevier BV
Published
1998-04-01
Volume
297
Issue
5
Pages
239-270
ISSN
0370-1573 (ISSN-L)
OpenAlex
W2039966934
Cited by
554
References
0
FWCI
14.59
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Discrete-scale invariance and complex dimensions. https://app.cochat.ai/papers/10.1016/s0370-1573(97)00076-8
The paper
Sornette, D. (1998). Discrete-scale invariance and complex dimensions. Physics Reports. https://doi.org/10.1016/s0370-1573(97)00076-8

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.