Washington · Zenodo (CERN European Organization for Nuclear Research) · 2025
The Structural Complexity Lab is a deterministic, interpretation-only observational framework developed as an extension of Structural Eligibility Screening (SES). This work establishes prior art for a system that distinguishes traditional contract complexity signals—such as page count, clause count, cross-references, schedules, amendments, and party count—from structural complexity, defined as a behavioral property arising from deterministic structural primitives, rewrite operator behavior, and SES eligibility classifications. The Structural Complexity Lab operates exclusively on deterministically enumerated scenarios and authoritative SES outputs. It does not perform prediction, optimization, scoring, valuation, risk assessment, legal analysis, or financial modeling. All outputs are descriptive and observational only. The lab processes 60,000 deterministically enumerated structural scenarios and compares metadata-based complexity descriptors with structural complexity metrics derived from SES classifications. Observational results demonstrate that traditional complexity signals function as surface-level metadata and are not determinative of structural behavior within the observed dataset. Structural complexity is shown to be independent of contract length, clause count, or other surface features. This publication is presented as defensive prior art. No patent rights are claimed. The system is non-predictive, non-optimizing, and non-advisory. All findings are deterministic, reproducible, and interpretation-only.
Cited by 0Open access
Washington · Zenodo (CERN European Organization for Nuclear Research) · 2025
The Structural Complexity Lab is a deterministic, interpretation-only observational framework developed as an extension of Structural Eligibility Screening (SES). This work establishes prior art for a system that distinguishes traditional contract complexity signals—such as page count, clause count, cross-references, schedules, amendments, and party count—from structural complexity, defined as a behavioral property arising from deterministic structural primitives, rewrite operator behavior, and SES eligibility classifications. The Structural Complexity Lab operates exclusively on deterministically enumerated scenarios and authoritative SES outputs. It does not perform prediction, optimization, scoring, valuation, risk assessment, legal analysis, or financial modeling. All outputs are descriptive and observational only. The lab processes 60,000 deterministically enumerated structural scenarios and compares metadata-based complexity descriptors with structural complexity metrics derived from SES classifications. Observational results demonstrate that traditional complexity signals function as surface-level metadata and are not determinative of structural behavior within the observed dataset. Structural complexity is shown to be independent of contract length, clause count, or other surface features. This publication is presented as defensive prior art. No patent rights are claimed. The system is non-predictive, non-optimizing, and non-advisory. All findings are deterministic, reproducible, and interpretation-only.
Cited by 0Open access
IakovlevIA · Zenodo (CERN European Organization for Nuclear Research) · 2020
Using this script one can calculate structural complexity for ferromagnetic/paramagnetic phase transition in Ising model on square lattice 1024x1024. Configurations to be used are located in data.7z
Cited by 0Open access
IakovlevIA · Zenodo (CERN European Organization for Nuclear Research) · 2020
No description provided.
Cited by 0Open access
The Dictionary of Genomics, Transcriptomics and Proteomics · 2015
Cited by 0
Brauer, Wilfried, Rozenberg, Grzegorz, Salomaa, Arto · CERN Document Server (European Organization for Nuclear Research) · 1990
Cited by 0
Brauer, Wilfried, Rozenberg, Grzegorz, Salomaa, Arto · CERN Document Server (European Organization for Nuclear Research) · 1988
Cited by 0
Renzo L. Ricca, Theodore E. Simos, George Psihoyios et al. · AIP conference proceedings · 2011
In this paper we shall review some of the most recent developments and results on work on energy-complexity relations and, if time will allow it, we shall provide an analytical proof of eq. (
Cited by 0Open access
Rainer Schuler, Tomoyuki Yamakami · Lecture notes in computer science · 1992
Cited by 10Open access
Jan Jantzen, F.J. Evans · Elsevier eBooks · 1992
Cited by 1
Žarko Bošković · ARKIVOC · 2025
Cited by 0Open access
By Juris Hartmanis, Juris Hartmanis, Richard Chang · 1994
This column addresses the following questions about the complexity of approximating the CLIQUE problem. 1. Is finding the vertices of the largest clique more difficult than merely finding the vertices of a 2-approximate clique (that is, a clique with at least half the size of the largest clique)? 2. What computational resources can be used to find the vertices of a 2-approximate clique? 3. Could fewer resources be used? The results of recent studies (by Chang, Gasarch and Lund; Khanna, Motwani, Sudan and Vazirani; and Crescenzi, Kann and Trevisan) on the complexity of NPapproximation problems yield the following answers: (1) Yes, unless the Polynomial Hierarchy collapses; (2) Nondeterministic polynomial time with log log n+O(1) queries to SAT; and (3) Not unless the Polynomial Hierarchy collapses. Surprisingly, the proof of these results depends on the fact that a collapse of the Boolean Hierarchy implies a collapse of the Polynomial Hierarchy. y Supported in part by Na...
Cited by 0
Dennis K. Hubbard · AccessScience · 2018
AccessScience is an authoritative and dynamic online resource that contains incisively written, high-quality educational material covering all major scientific disciplines. An acclaimed gateway to scientific knowledge, AccessScience is continually expanding the ways it can demonstrate and explain core, trustworthy scientific information that inspires and guides users to deeper knowledge.
Cited by 0
Rainer Schuler, Tomoyuki Yamakami · Journal of Computer and System Sciences · 1996
Cited by 7
Wessels, Bernhard (Wissenschaftszentrum Berlin fuer Sozialforschung gGmbH, Berlin (Germany)), Wissenschaftszentrum Berlin fuer Sozialforschung gGmbH, Berlin (Germany) · OpenGrey (Institut de l'Information Scientifique et Technique) · 1990
UuStB Koeln(38)-911101779 / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische Informationsbibliothek
Cited by 0
John McDonough, Andrzej Herczyński · Advances in Complex Systems · 2025
Beginning in the early Renaissance, mathematical transformations of melodic lines became a common musical practice and many composers constructed their pieces according to deliberate structural principles. The prolation canon, whereby a number of simultaneous voices follow the same sequence of notes, each at a different tempo, became a tour de force in the early 15th century and remained popular through the Baroque era. In the following centuries, other forms of complexities, often based on rhythmic shifts or daring pitch variations have been introduced by composers. Various statistical and computational methods have been developed to assess such structural innovations and, in particular, to objectively define the information content and complexity of music. Here we focus on compositions based on discernible melodic subjects or themes, and propose a new, direct measure of structural complexity based on the tonal and rhythmic variations of the defining motifs. For multi-voice compositions with temporal scaling regularities, such as prolation canons, the tonal and rhythmic complexities are reflected in the corresponding fractal indexes. The proposed measures are tested on synthetic examples and also compared with the results of two empirical studies. They are then applied to a number of masterful compositions, single and multi-voice, and are shown to provide discerning insights into musical structures, sensitive to local structural articulations.
Cited by 0
Milan Studeny · 1998
Complexity of a model of conditional independence structure is introduced as the least cardinality of a generating set. Four basic types of complexity are distinguished which depend on the type of generating. A method of calculation of complexity of a given conditional independence model is proposed. The method is based on a more effective way of representation of the model by means of a list of dominant conditional independence statements. Prospects of the proposed approach are discussed in the end. AMS classification: 68T30, 62H05. Keywords: probabilistic model, semi-graphoid, complexity, dominant triplet. 1 INTRODUCTION The most of structured models used in probabilistic reasoning and in multivariate statistics, especially graphical models, are models of probabilistic conditional independence structure. Verification of validity of such a stuctural model is based on statistical conditional independence tests. This leads to natural questions. Which conditional independence tests sh...
Cited by 3
Prasenjit Betal, Pabitra Mitra, Chittaranjan R. Mandal et al. · Communications in computer and information science · 2026
Cited by 0
VERHOEVEN, Yves, SANTHA, Miklos · OpenGrey (Institut de l'Information Scientifique et Technique) · 2005
Dans cette thèse, nous abordons des problèmes de complexité structurelle, traitant de la classification des problèmes en fonction de leurs difficultés relatives, et nous nous intéressons aussi à l'existence d'une solution à un problème plus concret d'algorithmique en-ligne. Suivant cette dichotomie, dans la première partie de cette thèse nous étudions des problèmes de la classe des problèmes totaux TFNP, à savoir les problèmes de Sperner et la recherche de minimum local. Nous montrons les complétudes de problèmes de Sperner localement 2-dimensionnels dans les classes d'arguments de parité PPA, PPAD et PPADS. Nous améliorons ainsi des résultats de Papadimitriou et Grigni. Nous étudions ensuite le nombre de requêtes, au sens classique et au sens quantique, nécessaires pour résoudre un problème de Sperner en dimension arbitraire sur une pseudo-variété ; nous prouvons une borne inférieure ainsi qu'une borne supérieure correspondant à la complexité d'un algorithme, cette dernière étant optimale pour un cas précédemment étudié par Crescenzi et Silvestri. Enfin, nous donnons deux algorithmes, un classique et un quantique, pour déterminer la position d'un minimum local d'une fonction définie sur les sommets d'un graphe. Les analyses de nos deux algorithmes sont fondées sur l'existence de séparateurs de petite taille dans les graphes, et nous montrons un tel résultat qui améliore un résultat antérieur de Gilbert, Hutchinson et Tarjan. Dans la seconde partie de la thèse, nous nous intéressons à l'existence d'un algorithme en-ligne sans mémoire pour le problème CNN. Notre résultat généralise et améliore un résultat antérieur de Koutsoupias et Taylor.
Cited by 0Open access
L. D. Barnett, Christopher L. Buckley, Seth Bullock · Physical Review E · 2009
Tononi [Proc. Natl. Acad. Sci. U.S.A. 91, 5033 (1994)] proposed a measure of neural complexity based on mutual information between complementary subsystems of a given neural network, which has attracted much interest in the neuroscience community and beyond. We develop an approximation of the measure for a popular Gaussian model which, applied to a continuous-time process, elucidates the relationship between the complexity of a neural system and its structural connectivity. Moreover, the approximation is accurate for weakly coupled systems and computationally cheap, scaling polynomially with system size in contrast to the full complexity measure, which scales exponentially. We also discuss connectivity normalization and resolve some issues stemming from an ambiguity in the original Gaussian model.
Cited by 72Open access