Skip to content

Multiply perfect number

A positive integer whose sum of positive divisors is an integer multiple k of the number itself.

Version
v1 · 2026-09-08 · History
Domain-specific #
5703
Origin domain
number theory
Subdomain
number theory

Core Idea

A k-perfect or multiply perfect number n satisfies σ(n)=kn, generalizing perfect numbers at k=2 and linking prime factorization to multiplicative divisor-sum constraints.[1] The divisor-sum function factors multiplicatively across coprime prime powers; their geometric sums must combine to exactly k times the original factorization. The abstraction is therefore identified by a declared carrier, a transformation or constraint over that carrier, and an invariant that tells an analyst whether the named structure is genuinely present.

The load-bearing residual is not the broad topic of number theory. It is the domain-specific identity determined by positive integer n, divisor convention, divisor-sum function, and integer multiplier k satisfy the exact equation σ(n)=kn. That residual remains recognizable when examples, notation, scale, or implementation change, but it disappears if the carrier is mistyped, the condition that positive integer n, divisor convention, divisor-sum function, and integer multiplier k satisfy the exact equation σ(n)=kn fails, a neighboring object is substituted, or notation and topical resemblance replace the constitutive test. This gives the entry an operational identity rather than merely a historical label.

A useful analysis keeps three layers separate. The constitutive layer says what must be true: positive integer n, divisor convention, divisor-sum function, and integer multiplier k satisfy the exact equation σ(n)=kn. The evidential layer asks what observation or proof warrants the claim: type the carrier, state every parameter and convention in the definition, test that positive integer n, divisor convention, divisor-sum function, and integer multiplier k satisfy the exact equation σ(n)=kn, compare the nearest accepted identity, and report counterexamples, uncertainty, and limiting cases. The use layer asks what reasoning becomes available once the identity is established: recognizing and comparing instances of Multiply perfect number, deriving its domain-specific consequences, selecting valid models or methods, and preventing transfer beyond its assumptions. Conflating the layers is the most common source of scope inflation.

Structural Signature

  • Carrier: the typed number theory carrier, defining objects and relations, parameters, conventions, evidence, boundary cases, and comparison targets
  • Inputs or antecedent state: the exact number theory carrier, defining parameters and conventions, boundary conditions, source evidence, comparison cases, and any measurement or proof assumptions needed to evaluate Multiply perfect number
  • Constitutive operation: The divisor-sum function factors multiplicatively across coprime prime powers; their geometric sums must combine to exactly k times the original factorization.
  • Invariant: positive integer n, divisor convention, divisor-sum function, and integer multiplier k satisfy the exact equation σ(n)=kn
  • Recognition test: type the carrier, state every parameter and convention in the definition, test that positive integer n, divisor convention, divisor-sum function, and integer multiplier k satisfy the exact equation σ(n)=kn, compare the nearest accepted identity, and report counterexamples, uncertainty, and limiting cases
  • Output or consequence: recognizing and comparing instances of Multiply perfect number, deriving its domain-specific consequences, selecting valid models or methods, and preventing transfer beyond its assumptions
  • Failure boundary: the carrier is mistyped, the condition that positive integer n, divisor convention, divisor-sum function, and integer multiplier k satisfy the exact equation σ(n)=kn fails, a neighboring object is substituted, or notation and topical resemblance replace the constitutive test

What It Is Not

  • It is not the whole field of number theory. The field contains many questions and methods that do not instantiate Multiply perfect number.
  • It is not its most familiar example. A canonical instance directly demonstrates that positive integer n, divisor convention, divisor-sum function, and integer multiplier k satisfy the exact equation σ(n)=kn. exhibits the structure, but the example is evidence for the abstraction rather than its definition.
  • It is not the neighboring catalog concept Perfect number. A perfect number is specifically 2-perfect; multiply perfect numbers allow any integer multiplier k greater than one.
  • It is not a claim that every boundary case has one uncontested classification. a generalized or degenerate case may change existence, uniqueness, measurement, or naming conventions, so the exact definition of Multiply perfect number must control the decision
  • It is not an unrestricted metaphor for any process that seems similar. Outside number theory, the vocabulary and validity conditions do not transfer literally.

Scope of Application

Multiply perfect number belongs to number theory and is useful where the analyst can specify the typed number theory carrier, defining objects and relations, parameters, conventions, evidence, boundary cases, and comparison targets, then evaluate positive integer n, divisor convention, divisor-sum function, and integer multiplier k satisfy the exact equation σ(n)=kn. The scope is broad within that domain but bounded by the need for positive integer n, divisor convention, divisor-sum function, and integer multiplier k satisfy the exact equation σ(n)=kn. The entry records a descriptive analytical identity; practical use requires the governing domain's evidence, standards, and safety obligations.[n1]

  • Definition and recognition. Determine whether a proposed instance satisfies the constitutive conditions rather than merely sharing terminology.
  • Construction or evolution. Track how the exact number theory carrier, defining parameters and conventions, boundary conditions, source evidence, comparison cases, and any measurement or proof assumptions needed to evaluate Multiply perfect number are converted, constrained, or organized by The divisor-sum function factors multiplicatively across coprime prime powers; their geometric sums must combine to exactly k times the original factorization..
  • Comparison. Compare instances using carrier, parameters, convention, domain, scale, boundary conditions, evidence, exact versus approximate form, and limiting behavior, without treating convenience measures as the definition.
  • Boundary analysis. Diagnose cases where a generalized or degenerate case may change existence, uniqueness, measurement, or naming conventions, so the exact definition of Multiply perfect number must control the decision and state which convention or theorem controls the decision.
  • Downstream reasoning. Use the established identity to support recognizing and comparing instances of Multiply perfect number, deriving its domain-specific consequences, selecting valid models or methods, and preventing transfer beyond its assumptions while preserving the assumptions under which the inference is valid.

Clarity

The abstraction clarifies a crowded vocabulary by making positive integer n, divisor convention, divisor-sum function, and integer multiplier k satisfy the exact equation σ(n)=kn the center of the account. A claim should name the carrier, the governing operation or relation, the applicable assumptions, and the recognition test. A bare label is insufficient because the name Multiply perfect number can be used for a formal identity, an implementation, or a neighboring result unless carrier and convention are stated. The disciplined statement is: given the exact number theory carrier, defining parameters and conventions, boundary conditions, source evidence, comparison cases, and any measurement or proof assumptions needed to evaluate Multiply perfect number, the structure counts as Multiply perfect number exactly when positive integer n, divisor convention, divisor-sum function, and integer multiplier k satisfy the exact equation σ(n)=kn.

This format also separates identity from measurement. Empirical, computational, or documentary proxies support recognition only under declared validity and uncertainty assumptions; formal cases require proof rather than measurement. Measurements can be noisy, implementations can approximate, and proofs can use equivalent characterizations; none of those facts licenses changing the object being measured. When reports disagree, first check scope and convention, then data or proof, and only then interpret the disagreement as substantive.

Manages Complexity

Without the abstraction, an analyst must reason directly over many local details: the carrier roles, admissibility assumptions, competing conventions, derived invariants, boundary cases, and proof or validation obligations specific to Multiply perfect number. Multiply perfect number compresses them into the roles in the structural signature. That compression permits comparison across instances without erasing the variables that determine validity. It also exposes which details may be varied safely and which are constitutive.

The compression has a price. A single label can hide canonical, generalized, restricted, approximate, computational, empirical, and historically variant formulations of Multiply perfect number. Good use therefore carries a small declaration of assumptions alongside the name. The abstraction manages complexity when it reduces the state space of the question while keeping the failure boundary visible; it mismanages complexity when the label substitutes for that boundary analysis.

Abstract Reasoning

  1. Identify the carrier. State what the elements, states, objects, or observations are: the typed number theory carrier, defining objects and relations, parameters, conventions, evidence, boundary cases, and comparison targets. Reject examples whose alleged carrier belongs to a different problem.
  2. Lock the constitutive rule. Express positive integer n, divisor convention, divisor-sum function, and integer multiplier k satisfy the exact equation σ(n)=kn independently of one notation or implementation. This step prevents the canonical example from becoming the definition.
  3. Derive consequences. From positive integer n, divisor convention, divisor-sum function, and integer multiplier k satisfy the exact equation σ(n)=kn, infer recognizing and comparing instances of Multiply perfect number, deriving its domain-specific consequences, selecting valid models or methods, and preventing transfer beyond its assumptions. Record each assumption used so that a later change of setting does not silently preserve an invalid conclusion.
  4. Test adversarial cases. Examine a generalized or degenerate case may change existence, uniqueness, measurement, or naming conventions, so the exact definition of Multiply perfect number must control the decision and an object that resembles Multiply perfect number in purpose or vocabulary but does not satisfy its invariant is outside the class. A robust identity explains why the first is convention-sensitive and why the second is outside the class.
  5. Compare and refine. Use carrier, parameters, convention, domain, scale, boundary conditions, evidence, exact versus approximate form, and limiting behavior to compare legitimate instances, and refine the model when discrepancies reflect hidden variation rather than failure of the abstraction itself.

Knowledge Transfer

Knowledge transfers strongly among subfields of number theory because they reuse the typed number theory carrier, defining objects and relations, parameters, conventions, evidence, boundary cases, and comparison targets, The divisor-sum function factors multiplicatively across coprime prime powers; their geometric sums must combine to exactly k times the original factorization., and type the carrier, state every parameter and convention in the definition, test that positive integer n, divisor convention, divisor-sum function, and integer multiplier k satisfy the exact equation σ(n)=kn, compare the nearest accepted identity, and report counterexamples, uncertainty, and limiting cases. A theorem, diagnostic, or modeling warning can travel when those roles remain literal. For example, the distinction between constitutive identity and a convenient observable transfers from A canonical instance directly demonstrates that positive integer n, divisor convention, divisor-sum function, and integer multiplier k satisfy the exact equation σ(n)=kn. to An applied instance preserves the same invariant under a changed scale, notation, jurisdiction, dataset, or implementation..[2]

Transfer outside the home domain is weaker. The skeletal pattern—type the carrier, apply the defining mechanism of Multiply perfect number, preserve its invariant, and derive only consequences licensed by the stated boundary—may suggest an analogy, but the domain-specific mechanisms, admissible evidence, and consequences do not come along automatically. The safe transfer procedure maps each role explicitly, checks the invariant again, and refuses the name when only a superficial resemblance remains.

Examples

Canonical

A canonical instance directly demonstrates that positive integer n, divisor convention, divisor-sum function, and integer multiplier k satisfy the exact equation σ(n)=kn. The example exposes the carrier and directly tests that positive integer n, divisor convention, divisor-sum function, and integer multiplier k satisfy the exact equation σ(n)=kn; changing incidental notation preserves the identity, while removing that condition destroys it. This example is canonical because every role can be inspected: the carrier is the typed number theory carrier, defining objects and relations, parameters, conventions, evidence, boundary cases, and comparison targets; the operative rule is The divisor-sum function factors multiplicatively across coprime prime powers; their geometric sums must combine to exactly k times the original factorization.; the invariant is positive integer n, divisor convention, divisor-sum function, and integer multiplier k satisfy the exact equation σ(n)=kn; and the result supports recognizing and comparing instances of Multiply perfect number, deriving its domain-specific consequences, selecting valid models or methods, and preventing transfer beyond its assumptions.[1] Changing incidental notation or scale leaves the structure intact, while removing positive integer n, divisor convention, divisor-sum function, and integer multiplier k satisfy the exact equation σ(n)=kn destroys the classification.

Mapped back: the typed number theory carrier, defining objects and relations, parameters, conventions, evidence, boundary cases, and comparison targets → The divisor-sum function factors multiplicatively across coprime prime powers; their geometric sums must combine to exactly k times the original factorization. → positive integer n, divisor convention, divisor-sum function, and integer multiplier k satisfy the exact equation σ(n)=kn → recognizing and comparing instances of Multiply perfect number, deriving its domain-specific consequences, selecting valid models or methods, and preventing transfer beyond its assumptions

Applied / In Practice

An applied instance preserves the same invariant under a changed scale, notation, jurisdiction, dataset, or implementation. The applied case qualifies only because the same invariant and boundary test remain literal under changed parameters or implementation. The applied case is not licensed merely by vocabulary. It qualifies because the same recognition test—type the carrier, state every parameter and convention in the definition, test that positive integer n, divisor convention, divisor-sum function, and integer multiplier k satisfy the exact equation σ(n)=kn, compare the nearest accepted identity, and report counterexamples, uncertainty, and limiting cases—can be run and because the same failure boundary—the carrier is mistyped, the condition that positive integer n, divisor convention, divisor-sum function, and integer multiplier k satisfy the exact equation σ(n)=kn fails, a neighboring object is substituted, or notation and topical resemblance replace the constitutive test—remains meaningful.[n1] The case also shows why practical outputs should report assumptions, resolution, and uncertainty instead of a naked label.

Mapped back: declared instance → recognition test → boundary check → qualified use

Structural Tensions

  • T1: Axiomatic identity vs. operational recognition. The defining conditions may be exact while empirical or computational recognition is approximate. Neither pole can be removed without changing the analytical task. Diagnostic: Can the reviewer state both the exact condition and the evidence used to infer it?
  • T2: Local roles vs. global consequence. The mechanism is enacted through local relations, but the abstraction is usually valued for a global classification or prediction. Neither pole can be removed without changing the analytical task. Diagnostic: Does the claimed global result actually follow from the declared local conditions?
  • T3: Ideal form vs. finite representation. Theory states a clean invariant while data structures, measurements, or proofs expose only finite representations. Neither pole can be removed without changing the analytical task. Diagnostic: Would increasing resolution converge toward the same classification?
  • T4: Canonical convention vs. legitimate variants. A standard formulation supports communication, while variants may preserve the same core under changed assumptions. Neither pole can be removed without changing the analytical task. Diagnostic: Which role is invariant across variants, and which convention-specific conclusion changes?
  • T5: Compression vs. hidden assumptions. The name compresses a complex argument but can conceal prerequisites. Neither pole can be removed without changing the analytical task. Diagnostic: Can each downstream inference be traced to an explicit assumption?
  • T6: Autonomous residual vs. reduction to catalog neighbors. The candidate uses broader structures but adds an identity-bearing residual. Neither pole can be removed without changing the analytical task. Diagnostic: After subtracting the proposed parent and named neighbors, does the constitutive residual still support independent diagnostics?

Structural–Framed Character

The entry is structurally mixed but domain-framed. Its portable skeleton is type the carrier, apply the defining mechanism of Multiply perfect number, preserve its invariant, and derive only consequences licensed by the stated boundary. Its identity-bearing terms—Multiply perfect number, carrier, parameter, invariant, boundary, evidence, model, transformation, and application—derive their meaning from number theory and cannot be replaced by generic systems language without losing the tests that distinguish valid from invalid instances.

This mixed character explains why the abstraction is reusable inside the domain yet does not meet the Prime bar. The structure organizes reasoning, but its claims still depend on domain-specific objects, evidence, and intervention semantics.

Structural Core vs. Domain Accent

The structural core consists of a carrier, The divisor-sum function factors multiplicatively across coprime prime powers; their geometric sums must combine to exactly k times the original factorization., a recognition invariant, and a consequence. That skeleton may resemble patterns elsewhere, especially type the carrier, apply the defining mechanism of Multiply perfect number, preserve its invariant, and derive only consequences licensed by the stated boundary. The domain accent is not decorative: Multiply perfect number, carrier, parameter, invariant, boundary, evidence, model, transformation, and application determine what counts as an admissible carrier, a valid transition, and successful evidence.

The abstraction therefore remains domain-specific. A cross-domain reuse that preserves only words such as 'balance,' 'cut,' 'sequence,' 'loss,' or 'simulation' is metaphor. Literal transfer requires the original role structure and diagnostics, which in this case remain anchored in number theory.

The proposed strict upward parent is prime:ratio. prime:ratio is the nearest broader Prime; the source domain and invariant supply the autonomous residual. This is a proposal-only workspace relationship: the accepted Prime supplies a genuinely instantiated structural prerequisite or superclass, while Multiply perfect number adds domain-specific constraints.

The entry does not collapse into that parent because the domain-specific identity determined by positive integer n, divisor convention, divisor-sum function, and integer multiplier k satisfy the exact equation σ(n)=kn It also declines a nearby thematic catalog node: the neighbor does not literally subsume the constitutive identity of Multiply perfect number. This explicit assert-and-decline pattern keeps the proposed DAG narrow and prevents a merely thematic edge.

The prospective workspace queue contains one strict upward edge to prime:ratio. No live DAG mutation is authorized.

Relationships to Other Abstractions

Local relationship map for Multiply perfect numberParents appear above the current abstraction, mutual partners to the right, and children below. Node labels state whether each abstraction is prime or domain-specific; colors identify relation types.Multiplyperfect numberDOMAINPrime abstraction: Ratio — is a kind ofRatioPRIME

Current abstraction Multiply perfect number Domain-specific

Parents (1) — more general patterns this builds on

  • Multiply perfect number is a kind of Ratio Prime

    The proposed strict upward parent is prime:ratio.

Hierarchy path (1) — routes to 1 parentless root

Neighborhood in Abstraction Space

Multiply perfect number sits in a crowded region of the domain-specific corpus (1st percentile for distinctiveness): several abstractions share nearly its structure, so a description that fits it tends to fit its neighbors too.

Family — Number-Theoretic Sequences & Classes (37 abstractions)

Nearest neighbors

Computed from structural-signature embeddings · 2026-09-08

Not to Be Confused With

  • Perfect number. A perfect number is specifically 2-perfect; multiply perfect numbers allow any integer multiplier k greater than one.
  • One canonical example. An instance demonstrates the structure but does not define the whole abstraction.
  • Measurement or implementation of Multiply perfect number. A proxy or realization is evidence for the abstraction, not the abstraction itself.
  • Generalized Multiply perfect number. An extension qualifies only when its changed axioms and retained invariant are stated.

Notes

[n1] Ronald Sorli, 'Algorithms in the Study of Multiperfect and Odd Perfect Numbers', University of Technology, Sydney. ↩a ↩b

References

[1] Achim Flammenkamp, 'The Multiply Perfect Numbers Page'. registry ↩a ↩b

[2] Keneth Adrian P Dagal, 'A Lower Bound for τ(n) for k-Multiperfect Number', 2013. registry