Logic
The systematic study of valid reasoning and the rules that determine when a conclusion follows from its premises.
A discipline is a lens, not an owner — the same idea can be viewed through many.
Concepts viewed through this lens
These numbers describe the current Thinking OS knowledge slice, not the whole field.
Disciplines it bridges to
Each bridge is built by ideas the two fields share, the thinking patterns that recur across both, and a representative relationship that shows how they connect.
Logicconnects toComputer Science
Shared concepts
Shared thinking patterns
Why this bridge exists
Algorithm models Turing machine — Algorithm models Turing Machine.
Explore this connection →Logicconnects toMathematics
Shared thinking patterns
Why this bridge exists
Prediction is derived from Hypothesis — A prediction is derived from a hypothesis.
Explore this connection →Logicconnects toComputational Complexity
Shared thinking patterns
Why this bridge exists
Algorithm models Turing machine — Algorithm models Turing Machine.
Explore this connection →Logicconnects toTheory of Computation
Shared concepts
Shared thinking patterns
Why this bridge exists
Algorithm models Turing machine — Algorithm models Turing Machine.
Explore this connection →Logicconnects toAlgorithms
Shared concepts
Shared thinking patterns
Why this bridge exists
Computational complexity theory is a Computability theory — computational complexity theory is a kind of computability theory.
Explore this connection →Logicconnects toStatistics
Shared concepts
Shared thinking patterns
Why this bridge exists
Prediction is derived from Hypothesis — A prediction is derived from a hypothesis.
Explore this connection →Logicconnects toPhilosophy of Science
Shared concepts
Shared thinking patterns
Why this bridge exists
Prediction is derived from Hypothesis — A prediction is derived from a hypothesis.
Explore this connection →Logicconnects toDiscrete Mathematics
Shared concepts
Shared thinking patterns
Why this bridge exists
Algorithm is a Sequence — An algorithm is an ordered sequence of steps.
Explore this connection →
Field shape — representation health
56/100 overall · 15 concepts
The eight dimensions measure Thinking OS coverage of this field, not the quality or importance of the discipline.
What kind of structure is this field?
Interpreted from the current atlas — how this field is represented, not a judgement of the field.
Representation health 56/100 — dense but shallow. Strongest: cross-disciplinary, taxonomy. Thinnest: factual depth.
structural · Measures the current Thinking OS representation, not the quality or importance of the field.
79% of its relations reach into 34 other disciplines — an outward-facing field in the atlas.
structural · Measures the current Thinking OS representation, not the quality or importance of the field.
Its 56 representation-health is above the 55 median of 211 similarly-sized disciplines (comparable by concept count).
structural · Measures the current Thinking OS representation, not the quality or importance of the field.
20% of its concepts have a single connection (mean internal degree 1.3) — a fairly cohesive internal structure.
structural · Measures the current Thinking OS representation, not the quality or importance of the field.
53% of its concepts carry a source, 27% a Tier A/B source; 40% of relations carry claim-level evidence.
atlas representation · Measures the current Thinking OS representation, not the quality or importance of the field.
How this lens connects
The kinds of relationship that characterise this discipline lens in the current slice.
Coverage matrix
How these concepts distribute across domains and concept families — real counts, not a score.
Knowledge timeline
Real, sourced key dates of these concepts.
- c. 300 BCEAlgorithm · First use · Computer Science
- c. 300 BCEAxiom · Formalization · Mathematics
- c. 300 BCEMathematical proof · Formalization · Mathematics
- c. 820 CEAlgorithm · Formalization · Computer Science
Ideas that connect this discipline outward
Concepts viewed through this lens that reach disciplines it does not itself carry — concept-level bridges (distinct from the discipline-to-discipline bridges below).
- AlgorithmreachesArtificial IntelligenceBiochemistryBioinformaticsBiologyCell BiologyComputational BiologyComputational ComplexityData StructuresEvolutionary BiologyGeneticsHistoryInformation TheoryMachine LearningMolecular BiologyNumerical AnalysisOptimizationStatistics
- HypothesisreachesBiologyHistoryHistory of ScienceLawMathematicsPhysics
- Computability theoryreachesAlgorithmsComputational ComplexityTheory of Computation
- Set theoryreachesDiscrete MathematicsSet TheoryTopology
- Type theoryreachesComputer ScienceMathematicsProgramming Languages
- Lambda calculusreachesComputational ComplexityTheory of Computation
Mental models that recur here
Cause and effect ×2
One thing genuinely bringing about another — as opposed to two things merely moving together. Establishing it needs a mechanism and controls, not just a pattern.
Information ×1
Anything that reduces uncertainty. It can be encoded into a signal, sent across a channel, and decoded — and noise can corrupt it on the way.
Probability ×1
A way to reason about uncertainty by assigning each possible outcome a share of the whole, between impossible (0) and certain (1).
People represented in this atlas
People tagged with this lens who have a recorded contribution. Not exhaustive, and not a ranking.
- Ernst Zermelo
1871–1953
- Alonzo Church
1903–1995
- Kurt Gödel
1906–1978
- Alexander Leitsch
1952–present
- Euclid
- 15 concepts are viewed through this lens.
- 8 of them bridge into other disciplines.
- Its signature thinking pattern is “Cause and effect” (recurs in 2 concepts).
- The most common kind of connection here is “Kind & structure”.
- It is most tightly linked to Computer Science.
Derived from the current graph structure — observations, not a judgement of the field.