Dontopedia

Funk-Hecke Theorem

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-06.)

Funk-Hecke Theorem has 19 facts recorded in Dontopedia across 4 references, with 3 live disagreements.

19 facts·14 predicates·4 sources·3 in dispute

Mostly:justifies approach(3), applies to(2), uses basis(1)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (1)

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describedByDescribed by(1)

Other facts (17)

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17 facts
PredicateValueRef
Justifies ApproachUsing Chebyshev/Gegenbauer as attention kernels[3]
Justifies ApproachComputing Lohe sync in spectral space[3]
Justifies ApproachUsing spectral coefficients as memory traces[3]
Applies toConvolution on S^{d 1}[1]
Applies toConvolution on Sphere[3]
Uses BasisGegenbauer Polynomials C N^α[1]
Justifies ComputingLohe Sync in Spectral Space[1]
StatesConvolution on S^{d-1} with kernel k(⟨x,y⟩) = multiplication in spectral domain[1]
Justifies UsingSpectral Coefficients As Memory Traces[1]
From Spectral Graph Theorytrue[1]
Justifies Use ofChebyshev Gegenbauer Attention Kernels[1]
Is Key Mathematical Ideatrue[1]
Applied Recursivelynull[2]
Applies Recursively Herenull[2]
Rdf:typeMathematical Theorem[3]
Implies Equivalencemultiplication in spectral domain[3]
Application Moderecursively[4]

Timeline

Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.

usesBasisblah/watt-activation/part-102
ex:gegenbauer-polynomials-c_n^α
justifiesComputingblah/watt-activation/part-102
ex:lohe-sync-in-spectral-space
statesblah/watt-activation/part-102
Convolution on S^{d-1} with kernel k(⟨x,y⟩) = multiplication in spectral domain
appliesToblah/watt-activation/part-102
ex:convolution-on-s^{d-1}
justifiesUsingblah/watt-activation/part-102
ex:spectral-coefficients-as-memory-traces
fromSpectralGraphTheoryblah/watt-activation/part-102
true
justifiesUseOfblah/watt-activation/part-102
ex:chebyshev-gegenbauer-attention-kernels
isKeyMathematicalIdeablah/watt-activation/part-102
true
appliedRecursivelyblah/watt-activation/part-229
null
appliesRecursivelyHereblah/watt-activation/part-229
null
typeblah/watt-activation/102
ex:MathematicalTheorem
labelblah/watt-activation/102
Funk-Hecke Theorem
appliesToblah/watt-activation/102
ex:convolution-on-sphere
impliesEquivalenceblah/watt-activation/102
multiplication in spectral domain
justifiesApproachblah/watt-activation/102
Using Chebyshev/Gegenbauer as attention kernels
justifiesApproachblah/watt-activation/102
Computing Lohe sync in spectral space
justifiesApproachblah/watt-activation/102
Using spectral coefficients as memory traces
labelblah/watt-activation/228
Funk-Hecke theorem
applicationModeblah/watt-activation/228
recursively

References (4)

4 references
  1. [1]Part 1028 facts
    ctx:discord/blah/watt-activation/part-102
  2. [2]Part 2292 facts
    ctx:discord/blah/watt-activation/part-229
  3. [3]1027 facts
    ctx:discord/blah/watt-activation/102
    • full textwatt-activation-102
      text/plain3 KBdoc:agent/watt-activation-102/197f49fd-089d-42f2-ae23-c3d99df52ba0
      Show excerpt
      [2026-03-08 18:20] xenonfun: easier to read and consolidated doc: https://github.com/MonumentalSystems/CustomModelMLXConversion/blob/62d270249a911f6ab482a2d89000a4b47c51363d/HARMONIC_PORT.md [2026-03-08 18:21] xenonfun: ``` cumsum-based
  4. [4]2282 facts
    ctx:discord/blah/watt-activation/228
    • full textwatt-activation-228
      text/plain3 KBdoc:agent/watt-activation-228/218c4ece-61aa-47aa-a16e-b77f7f994d5f
      Show excerpt
      [2026-03-11 05:23] xenonfun: ⏺ It is, and the math backs it up cleanly. What the network discovered spontaneously is essentially a depth-wise DFT — the same decomposition that LoheFFNv3 uses within each block (ring → DFT modes), but now o

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