Thinking·OS

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Algorithm models Turing machine. Activate to inspect this relation.Algorithm is a Sequence. Activate to inspect this relation.Analysis of algorithms is a Computational complexity theory. Activate to inspect this relation.Big O notation is part of Analysis of algorithms. Activate to inspect this relation.BQP (quantum complexity) is part of Computational complexity theory. Activate to inspect this relation.Church-Turing Thesis depends on Turing machine. Activate to inspect this relation.Church-Turing Thesis explains Computability. Activate to inspect this relation.Class P depends on Time Complexity. Activate to inspect this relation.Class P is part of Complexity Class NP. Activate to inspect this relation.Class P is part of Computational complexity theory. Activate to inspect this relation.Computability depends on Turing machine. Activate to inspect this relation.Computability theory depends on Turing machine. Activate to inspect this relation.Computational complexity theory is a Computability theory. Activate to inspect this relation.Computational complexity theory is part of Algorithm. Activate to inspect this relation.Decidability is part of Computability. Activate to inspect this relation.Decidability is part of Computability theory. Activate to inspect this relation.Finite automaton is analogous to Turing machine. Activate to inspect this relation.Finite-state machine is analogous to Turing machine. Activate to inspect this relation.Halting problem applies to Decidability. Activate to inspect this relation.Halting problem applies to Turing machine. Activate to inspect this relation.Halting problem depends on Turing machine. Activate to inspect this relation.Halting problem is part of Computability. Activate to inspect this relation.Lambda calculus is analogous to Turing machine. Activate to inspect this relation.NP-complete is part of Computational complexity theory. Activate to inspect this relation.NP-completeness is part of Complexity Class NP. Activate to inspect this relation.NP-completeness is part of Computational complexity theory. Activate to inspect this relation.P versus NP applies to Complexity Class NP. Activate to inspect this relation.P versus NP applies to Class P. Activate to inspect this relation.P versus NP applies to Algorithm. Activate to inspect this relation.Space Complexity measures Turing machine. Activate to inspect this relation.Space Complexity requires Big O notation. Activate to inspect this relation.Time Complexity measures Turing machine. Activate to inspect this relation.Time Complexity requires Big O notation. Activate to inspect this relation.Turing machine is a Finite automaton. Activate to inspect this relation.Turing machine models Computability. Activate to inspect this relation.Turing machine models Algorithm. Activate to inspect this relation.Big O notationAnalysis of algorithmsSpace ComplexityTime ComplexityComputational complexity theoryTuring machineClass PComputability theoryAlgorithmBQP (quantum complexity)NP-completeNP-completenessFinite automatonComputabilityChurch-Turing ThesisHalting problemLambda calculusFinite-state machineComplexity Class NPP versus NPDecidabilitySequence
Relationship types

143 concepts viewed through this lens. Bridge concepts connect this view to Anthropology, Audio Engineering, Biochemistry, Bioinformatics….

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  • Focused concept
  • Connected concept
  • Bridge concept (just outside the lens)
  • Arrow points from cause / source to effect / target
  • A line with no arrow is a two-way relationship
  • Node colour marks the concept’s primary discipline
22 concepts36 relationships13 disciplines5 relation families

Big O notation

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At a glance

Big O notation is a mathematical notation that describes the approximate size of a function on a domain.

Disciplines
Computer Science · Algorithms · Computational Complexity
Role in the graph
Connector
Relationships
3 · 2 relation families
Mental models
1

What am I looking at?

In this lens (143)

Bridge concepts (162)

Just outside the lens — they connect it to other context.

  • Complexity Class NP3
    Computational Complexity · connects to Class P, NP-completeness, P versus NP
  • DNA3
    Biochemistry, Bioinformatics, Cell Biology, Evolutionary Biology, Genetics, Molecular Biology · connects to Algorithm, Encoding, Sequence
  • Network3
    Anthropology, Discrete Mathematics, Linear Algebra, Mathematics, Network Science, Sociology, Urban Planning · connects to Client-server model, Communication protocol, Latency
  • Optimization3
    Business, Economics, Engineering, Mathematical Modelling, Optimization, Systems Engineering · connects to Gradient descent, Machine learning, NP-complete
  • Pattern3
    Biology, Cognitive Science, Design, Education, Educational Science, Machine Learning, Mathematics · connects to Hierarchy, Machine learning, Sequence

Insights from this view

Structural observations about the concepts shown here — descriptions of this graph, not claims about the world.

  • This view connects 13 disciplines: Algorithms, Bioinformatics, Computational Complexity, Computer Science, Data Structures, Discrete Mathematics, History, Logic, Mathematics, Molecular Biology, Programming Languages, Software Engineering, Theory of Computation.
  • Big O notation is a bridge concept — viewed here through Algorithms, Computational Complexity, Computer Science.
  • The connections here span 5 relation families.
  • Information explains 3 concepts in this view (Algorithms, Bioinformatics, Computational Complexity, Computer Science, Data Structures, Discrete Mathematics, History, Logic, Mathematics, Molecular Biology, Software Engineering, Theory of Computation).

Relationships as a list

The focused concept’s relationships. Pick another concept in the graph above to update this list.

Explore through a different lens

A lens is a deterministic projection of the graph. Pick a discipline, thinking pattern or journey to reframe the whole view.

By discipline

ChemistryBiologyPhysicsMathematicsComputer ScienceGeologyMineralogyEconomics

By thinking pattern

Bayesian updatingCause and effectCompoundingConservationConstraintsDefense in depthDiffusion & spreadEmergenceEnergy transformationEntropy & irreversibilityEquilibriumFeedback loopIncentivesInformationLevels & hierarchyModularityNetworksOptimizationOscillationProbabilityRecursion & self-similarityScaleSignal vs noiseSource–pathway–receptorStocks and flowsSymmetry & invarianceThresholds & tipping pointsTrade-offsTriangulationVariation & selectionWaves

By journey

From a Leaf to the ClimateWhy Music Moves UsHow Machines LearnReasoning about a Leaf and the Climate

Concept collections

Concept collections are curated lenses onto the fabric — themed sets of ideas that recur across disciplines. They are not journeys; they are a way to read the graph.

About this view

What this is

Start from one concept and expand outward. The view never shows everything at once — click a node to refocus, filter by relationship type, or switch to an accessible list.

One fabric

3750 concepts and 5051 typed relations form one connected component — no isolated silo.

How to read it

Focus a concept, or apply a lens (discipline, mental model, journey) to see only the threads that matter.