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OCME · Bilingual mathematics & derivations

Second Modern Structures: Complex Invariants, Spans, Group Homomorphisms, Convergence, Measure, Processes and Multivariable Functions

On this page
  1. Complex number
  2. Absolute value
  3. Natural-number powers and principal square roots
  4. Real vector space
  5. Linear systems in two variables and degenerate constraints
  6. Finite group
  7. Subset
  8. Function mapping
  9. Metric space
  10. Sequence
  11. Quantifiers and explicit domains
  12. Set
  13. Set operations
  14. Real number
  15. Finite discrete probability distribution
  16. Real random variables on finite sample spaces
  17. Plane vectors in a fixed basis
  18. Coordinate plane
  19. Complex modulus and conjugation
  20. Linear combinations and span
  21. Subgroups and group homomorphisms
  22. Convergence in a metric space
  23. Sigma-algebras and measure spaces
  24. Discrete-time stochastic process
  25. Multivariable real-valued function

Complete seven traceable knowledge objects in dependency order on the existing number-system and function foundations.

This is a suggested learning sequence, not a universal logical dependency or a formal proof.

  1. Stage 1 · required

    Complex number

    Existing canonical prerequisite for the new objects in this pulse.

  2. Stage 1 · required

    Absolute value

    Existing canonical prerequisite for the new objects in this pulse.

  3. Stage 1 · required

    Natural-number powers and principal square roots

    Existing canonical prerequisite for the new objects in this pulse.

  4. Stage 1 · required

    Real vector space

    Existing canonical prerequisite for the new objects in this pulse.

  5. Stage 1 · required

    Linear systems in two variables and degenerate constraints

    Existing canonical prerequisite for the new objects in this pulse.

  6. Stage 1 · required

    Finite group

    Existing canonical prerequisite for the new objects in this pulse.

  7. Stage 1 · required

    Subset

    Existing canonical prerequisite for the new objects in this pulse.

  8. Stage 1 · required

    Function mapping

    Existing canonical prerequisite for the new objects in this pulse.

  9. Stage 1 · required

    Metric space

    Existing canonical prerequisite for the new objects in this pulse.

  10. Stage 1 · required

    Sequence

    Existing canonical prerequisite for the new objects in this pulse.

  11. Stage 1 · required

    Quantifiers and explicit domains

    Existing canonical prerequisite for the new objects in this pulse.

  12. Stage 1 · required

    Set

    Existing canonical prerequisite for the new objects in this pulse.

  13. Stage 1 · required

    Set operations

    Existing canonical prerequisite for the new objects in this pulse.

  14. Stage 1 · required

    Real number

    Existing canonical prerequisite for the new objects in this pulse.

  15. Stage 1 · required

    Finite discrete probability distribution

    Existing canonical prerequisite for the new objects in this pulse.

  16. Stage 1 · required

    Real random variables on finite sample spaces

    Existing canonical prerequisite for the new objects in this pulse.

  17. Stage 1 · required

    Plane vectors in a fixed basis

    Existing canonical prerequisite for the new objects in this pulse.

  18. Stage 1 · required

    Coordinate plane

    Existing canonical prerequisite for the new objects in this pulse.

  19. Stage 2 · optional

    Complex modulus and conjugation

    Complex conjugation preserves the real part and reverses the imaginary coefficient; modulus squared is the sum of their squares.

  20. Stage 3 · optional

    Linear combinations and span

    A linear combination is a scalar-weighted sum of finitely many vectors; the span collects every finite linear combination.

  21. Stage 4 · optional

    Subgroups and group homomorphisms

    A subgroup is a group under the inherited operation; a group homomorphism preserves multiplication, and its kernel and image follow from the complete map table.

  22. Stage 5 · optional

    Convergence in a metric space

    A sequence in a metric space converges to x when, for every positive epsilon, eventually all n≥N lie in the epsilon-ball around x.

  23. Stage 6 · optional

    Sigma-algebras and measure spaces

    A sigma-algebra contains the empty set and is closed under complements and countable unions; a measure is nonnegative, zero on the empty set and countably additive.

  24. Stage 7 · optional

    Discrete-time stochastic process

    A discrete-time stochastic process is a time-indexed family of random variables on one probability space; marginal distributions do not determine its joint law.

  25. Stage 8 · optional

    Multivariable real-valued function

    A multivariable real-valued function maps inputs in an explicitly declared real-vector domain to real numbers; coordinate roles and domain are function data.

Path source & status

path-pulse-foundations-20261023 · candidate

Original paths JSON