Pith. Sign in

RECORD

Statistical Dark Matter: Synergy is everywhere but is hard to capture

PaperPDF from arXiv

data files

Paper breakdownThe authors' claims, conditions and measurements, as JSON Signed receiptProof this review has not been altered
X Bluesky LinkedIn Reddit Hacker News
Alberto Liardi, Fernando E. Rosas, Daniele Marinazzo, Thomas F. Varley, Michael Gastpar, Pedro A.M. Mediano

Information Theory · Submitted 27 Sep 2026

abstract compiled · 2026-10-06 · no language-model review

The authors' main claim These findings imply that synergy constitutes a prevalent, yet often invisible, informational component of complex systems.

how it is stated · asserted 0.89 read the record →

Comment (0) Read on arXiv ↗
Cite ▾
arXiv ID2610.03764 (version 2)
Pith IDMMCYEL4K, Pith's permanent record of this paper and its review
CitationAlberto Liardi, Daniele Marinazzo, Fernando E. Rosas, Michael Gastpar, Pedro A.M. Mediano, Thomas F. Varley. "Statistical Dark Matter: Synergy is everywhere but is hard to capture." arXiv:2610.03764 (2026). https://pith.science/paper/MMCYEL4K
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, 2026-10-06: 1 request, 4,863 input tokens.

What the abstract itself states, as probabilities: claims first 0.05 · states limitation 0.26 · human participants 0.04 · controlled comparison 0.05 · randomized assignment 0.01 · states quantitative result 0.08 · compares with prior results 0.87 · mentions code or data availability 0.02.

The abstract, sentence by sentence

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

The information-theoretic construct of synergy refers to the statistical structure that is contained in three or more variables, but not in any subset of them. Here we leverage recent advances in multivariate information theory to show that synergy is far more prevalent in complex systems than previously thought. In particular, we show that many-body systems tend to become strongly dominated by synergy as the number of subcomponents grows. At the same time, our results also reveal that commonly used tools for statistical modelling severely underestimate synergistic structures. These findings imply that synergy constitutes a prevalent, yet often invisible, informational component of complex systems. With a certain poetic licence, we interpret these results as suggesting that synergy is the dark matter of statistics - interdependencies that we know exist, but standard instruments fail to detect.

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 The information-theoretic construct of synergy refers to the statistical structure that is contained in three or more variables, but not in any subset of them. background 1.00 0.04 0.03 asserted 0.99
s1 Here we leverage recent advances in multivariate information theory to show that synergy is far more prevalent in complex systems than previously thought. contribution 0.68 0.84 0.39 asserted 1.00
s2 In particular, we show that many-body systems tend to become strongly dominated by synergy as the number of subcomponents grows. result 1.00 0.93 0.30 asserted 1.00
s3 At the same time, our results also reveal that commonly used tools for statistical modelling severely underestimate synergistic structures. result 1.00 0.88 0.15 asserted 1.00
s4 These findings imply that synergy constitutes a prevalent, yet often invisible, informational component of complex systems. interpretation 0.97 0.76 0.66 asserted 0.89
s5 With a certain poetic licence, we interpret these results as suggesting that synergy is the dark matter of statistics - interdependencies that we know exist, but standard instruments fail to detect. interpretation 1.00 0.29 0.24 hedged possibility 0.97

What kind of paper the classifier reports this is: theoretical result 0.80 · evidence from proof or derivation 0.47.

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

The information-theoretic construct of synergy refers to the statistical structure that is contained in three or more variables, but not in any subset of them. Here we leverage recent advances in multivariate information theory to show that synergy is far more prevalent in complex systems than previously thought. In particular, we show that many-body systems tend to become strongly dominated by synergy as the number of subcomponents grows. At the same time, our results also reveal that commonly used tools for statistical modelling severely underestimate synergistic structures. These findings imply that synergy constitutes a prevalent, yet often invisible, informational component of complex systems. With a certain poetic licence, we interpret these results as suggesting that synergy is the dark matter of statistics - interdependencies that we know exist, but standard instruments fail to detect.

Human review

How Pith checks papers → · Full audit of this paper →

Discussion

Know something about this paper? Leave a comment, or highlight any passage above to comment on it.