18 KiB
Signal Theory Compendium: Physics-Disruptive Signal Processing
"We are going to piss off physics."
This document compiles all signal theory developed in the Research Stack that challenges conventional physics by blurring boundaries between information theory, quantum mechanics, classical signal processing, thermodynamics, and genomics.
Table of Contents
- Spectral Encoding Theory
- Electromagnetic Spectrum Theory
- Wavefront Emission Theory
- Signal Policy Theory
- Morphic DSP Theory
- DSP Erasure Coding Theory
- PBACS Signal Transport Theory
- Mutual Information Signal Theory
- Energy Gradient Signal Theory
- Spectral Field Theory
- S3C Resonance Theory
- CMYK Frequency Core Theory
- Hydrogen Spectral Basis Theory
- Spectral Genome Theory
- Modulation Codec Theory
- Predictive Harmony Social Synchrony
Spectral Encoding Theory
File: Semantics/Spectrum.lean
Core Concepts
- Erdős-Hooley Constant: δ ≈ 0.08607 (Q16.16: 5643/65536)
- Spectral Signature: Finite vector of Q16.16 amplitudes (8 bins default)
- Spectral Overlap: Inner product between signatures
- Piecewise Eigenvector Merge: Superposition with saturation
- Resonance Degeneracy: Count of overlapping non-zero bins
- Density Bound: Active bins must not exceed threshold
Key Operations
spectralOverlap sig1 sig2 = Σ(sig1[i] × sig2[i])
piecewiseMerge left right[i] = min(1.0, left[i] + right[i])
resonanceDegeneracy left right = count(left[i] ≠ 0 ∧ right[i] ≠ 0)
Genetic Event Encoding
Maps genetic events (A, T, G, C) to unique spectral peak positions, creating a "spectral barcode" for genetic event encoding.
Electromagnetic Spectrum Theory
File: Semantics/ElectromagneticSpectrum.lean
Spectrum Bands
- Radio, Microwave, Infrared, Optical, Ultraviolet, X-ray, Gamma
- Ionizing Bands: X-ray, Gamma (isIonizingBand predicate)
- Plasma Interactions: None, Plasma Coupling, Ionization
Band Profile Structure
BandProfile {
band: SpectrumBand
intensity: Q16_16
}
ElectromagneticSample {
bandProfile: BandProfile
interaction: PlasmaInteraction
}
Wavefront Emission Theory
File: Semantics/WavefrontEmitter.lean
Wavefront Structure
Wavefront {
emitterId: Nat
emissionTime: Nat
amplitude: Q16_16
frequency: Q16_16
phase: Q16_16
position: {row, col}
}
Wavefront Parameters
- Default amplitude: 1.0
- Default frequency: 0.1 (ω)
- Propagation speed: 1.0 (v)
- Decay rate: 0.01 (γ)
Wavefront Computation
Wavefront value at position and time:
if distance ≤ waveDistance:
decay = γ × distance
decayedAmplitude = amplitude - decay
phaseShift = ω × distance
oscillation = ±1 (based on phaseShift parity)
value = decayedAmplitude × oscillation
else:
value = 0
State Change Trigger
State changes emit wavefronts that propagate through the resonant field, enabling event-driven field dynamics.
Signal Policy Theory
File: ExtensionScaffold/Compression/SignalPolicy.lean
Signal Band Classification
- Quiet: value < 0.25
- Active: 0.25 ≤ value < 0.50
- Stressed: 0.50 ≤ value < 0.75
- Extreme: value ≥ 0.75
Signal Policy Structure
SignalPolicy {
exploreBias: Q16_16
tunnelBias: Q16_16
promoteBias: Q16_16
gossipBias: Q16_16
}
Adaptive Resource Allocation
Branch budget adapts to signal band:
- Quiet: base budget
- Active: +1 slot
- Stressed: +2 slots
- Extreme: +1 slot
Priority scoring incorporates signal weight for adaptive gossip propagation.
Morphic DSP Theory
File: Semantics/MorphicDSP.lean
Reconfigurable DSP Modes
- Multiply, Accumulate, Convolution, FFT, Filter, Adaptive
- Morphic Scalar State Machine controls DSP configuration
- OEPI threshold determines DSP allocation priority
DSP Slice Bank
- 5 slices for morphic scalar FPGA optimization
- Allocation based on OEPI threshold:
- Critical (≥95%): 5 slices
- Medium (≥70%): 3 slices
- Low: 1 slice
AngrySphinx Gates
Boundary enforcement gates:
- ALLOW_DSP_COLLAPSE / REFUSE_DSP_COLLAPSE
- ALLOW_MERGE / HOLD_BOUNDARY_FLUIDITY
- ALLOW_SPLIT / REQUIRE_RENORMALIZATION
- ALLOW_TOPOLOGY_ADAPT / REFUSE_NO_RECEIPT
- ALLOW_PROBABILISTIC / REQUIRE_DETERMINISTIC_REPLAY
Acoustic Gradient Fields (n-Space Sound Wave Modeling)
AcousticGradientField {
dimensions: Nat
fieldPoints: Array AcousticPoint
}
AcousticPoint {
position: Array Q16_16 (n-dimensional coordinates)
pressure: Q16_16
}
Gradient computation via central difference, acoustic impedance as gradient magnitude |∇f|, geodesic flow following gradient descent on acoustic manifold.
Fitness-Entropy Compensation (BioRxiv Integration)
From bioRxiv "Fitness–Entropy Compensation effect" (DOI: 10.1101/2025.07.05.663304):
f = f_max - α × H
Gibbs free energy compensation:
ΔG = ΔH - TΔS
DSP Erasure Coding Theory
File: Semantics/DspErasureCoding.lean
3-Stream Redundancy Scheme
- Primary stream (identity permutation)
- Recovery stream 1 (affine permutation: π₁(i) = (offset₁ + step₁ × i) mod n)
- Recovery stream 2 (affine permutation: π₂(i) = (offset₂ + step₂ × i) mod n)
Genomic Compression Parameters
- ρ_seq²: sequence alignment accuracy
- v_epigenetic²: methylation dynamics
- τ_structure²: 3D folding tension
- σ_entropy²: nucleotide diversity
- q_conservation²: evolutionary constraint
- κ_hierarchy²: chromatin levels
- ε_mutation: mutation rate
Spectral Erasure Detection
Detects erasures using spectral anomaly detection with adaptive threshold based on genomic field strength:
genomicWeight = (ρ_seq + v_epigenetic + τ_structure + σ_entropy + q_conservation) / ((1 + κ_hierarchy²) × (1 + ε_mutation))
adaptiveThreshold = threshold × (1 + genomicWeight)
FPGA DSP Integration
Opcodes:
- RESONATE (0x14): TSM_RESONATE / PHONON_LOCK
- MERGE_MODES (0x42): TSM_MERGE_MODES
PBACS Signal Transport Theory
File: Semantics/PBACSSignal.lean
PBACS Unified State Vector
State {
phi: UInt32 (L2 φ-accumulator)
error: Int32 (L1 Error accumulator)
tension: UInt32 (L4 Tension accumulator)
phase: Phase (L4 PIST Phase sort)
lastSymbol: Symbol (L1 Output symbol)
bracket: BracketedDIAT (L5 BracketedDIAT)
}
Canonical Update Law
- Phi increment: φ_{t+1} = φ_t + 106070 (≈ 2^32 / φ²)
- Threshold LUT lookup: θ_t = 32768 if φ_t ≥ 0x80000000 else -32768
- Error accumulation: e_{t+1} = v_t + e_t - (b_t ? θ_t : 0)
- Symbol decision: b_t = (θ_t < v_t + e_t)
- Tension update: tension_{t+1} = (tension_t × 921 + |e_{t+1}| × 103) / 1024
- Phase transition: grounded → drift → seismic based on tension
- Bracket update: constraint-preserving interval
Mutual Information Signal Theory
File: Semantics/MISignal.lean
MI Signal Definition
MI(x) = baseline_bpb - actual_bpb
Mutual information extracted through compression improvement.
kNN Weighted MI Prediction
MI_pred = Σ(w_i × MI_i × S_i) / Σ(w_i × S_i)
Where w_i = 1/(d_i + ε), distances and similarities are parallel arrays.
Surprise Metric
surprise = log(1 + |MI_actual - MI_predicted|)
Approximated as direct delta in Q16.16 for integer arithmetic.
Structure Yield
ρ(x) = MI(x) / (cost(x) + ε)
Information per unit compute cost.
Weighted Feature Distance
d(z₁, z₂) = √( Σ w_i × ((z₁_i - z₂_i) / s_i)² )
9-dimensional weighted feature distance.
Energy Gradient Signal Theory
File: Semantics/EnergyGradientSignal.lean
Energy Gradient Components
EnergyGradient {
temporalGradient: UInt32 (∂E/∂t)
spatialGradient: UInt32 (|∇_x E|)
gradientMagnitude: UInt32 (|∇E|)
gradientDirection: UInt32 (direction angle)
}
Energy Waveform
EnergyWaveform {
amplitude: UInt32 (|∇E(t)|)
frequency: UInt32 (ω_∇E)
phase: UInt32 (φ_∇E)
}
Thermodynamic Channels
- energyGradientChannel
- energyIncreaseChannel
- energyDecreaseChannel
- entropyProductionChannel
Shape-Energy Coupling
C_SE = α × ∇h × ∇E
Coupling between shape gradient and energy gradient.
Spectral Field Theory
File: Semantics/SpectralField.lean
Local Field Structure
LocalField {
massField: Q16_16
polarityField: Q16_16
spectrum: SpectralSignature
}
Field Accumulation
Piecewise summation of mass, polarity, and spectral contributions from neighborhood.
Interaction Score
score = (mass × massField) + (polarity × polarityField) + spectralOverlap(spectrum, field.spectrum)
Field Magnitude
L2 norm approximation of field components.
S3C Resonance Theory
File: Semantics/S3CResonance.lean
Ductile Manifold State
DuctileState {
N: Nat (manifold density)
linkNum: Nat (topological link multiplicity)
kResonant: Q16_16 (resonant frequency index)
jScore: Q16_16 (computed J-score)
phase: Q16_16 (MAC phase coherence [0,1])
isDuctile: Bool
}
Parabolic J-Score
J(k) = 32 - 0.5 × (k - 22)²
Peak at k = 21.5 → J = 31.875
God-Tier threshold: J > 30.0
MAC Phase Coherence
Threshold: 0.99 (64881 in Q16.16)
Phase integrity check: phase ≥ 0.99
CMYK Frequency Core Theory
File: ExtensionScaffold/Temporal/CMYKFrequencyCore.lean
Channel Banks
- C: base frequency 600 Hz, delta 20 Hz
- M: base frequency 1200 Hz, delta 20 Hz
- Y: base frequency 1800 Hz, delta 20 Hz
- K: base frequency 2400 Hz, delta 20 Hz
Hex Nibble Encoding
4 hex nibbles map to 4 channel-local frequency bins:
freq(ch, h) = baseFreq(ch) + deltaFreq × h.toNat
Packet Encoding/Decoding
Bidirectional mapping between hex nibbles and channel frequencies with exact inverse.
Hydrogen Spectral Basis Theory
File: Semantics/Toybox/HydrogenSpectralBasis.lean
Physical Constants (Wolfram Alpha Verified)
- Rydberg constant: R_H = 109677.58 cm⁻¹
- Speed of light: c = 2.99792458 × 10¹⁰ cm/s
- Planck constant: h = 4.135667696 × 10⁻¹⁵ eV·s
Rydberg Formula
ν̃ = R_H × (1/n₁² - 1/n₂²)
Spectral Series
- Lyman series: n=1 → n=2,3,4,5,6,7 (UV, ionization at 91.2nm)
- Balmer series: n=2 → n=3,4,5,6,7 (visible)
Wavelengths:
- Lyman-α: 121.6 nm
- Balmer H-α: 656.3 nm (red)
7-Dimensional Spectral Basis
Hydrogen spectral lines as canonical basis for information encoding:
- 6 Lyman lines + 1 Balmer H-α = foundational basis
- Physical, not metaphysical: exact frequencies from quantum mechanics
Information Encoding via Spectral Resonance
HydrogenEncoded {
spectralIndex: Fin 7
amplitude: Q16_16
phase: Q16_16
}
Resonance strength via Lorentzian:
strength = 1 / (1 + (Δλ)²)
Spectral Genome Theory
File: Semantics/Toybox/SpectralGenome.lean
K-mer Counting (3-mers = 64 codons)
Base encoding: A=0, C=1, G=2, T=3 3-mer index: b₁ × 16 + b₂ × 4 + b₃
Discrete Cosine Transform (DCT-II)
Basis function:
cos(π/n × (j + 0.5) × k)
Transform k-mer counts to spectral coefficients.
Compression: Pandigital Continued Fraction Encoding
Spectral coefficients encoded as CF convergents for rational approximation.
Falsifiable Prediction
For 1000 human promoters:
- DCT-II of 3-mer spectrum + CF encoding achieves 2.5:1 compression
- Baseline gzip: 1.8:1 compression
- Required: p < 10⁻⁶ (6.5σ)
Modulation Codec Theory
File: Semantics/Semantics/BraidSerial.lean
Modulation Modes
- None: Direct phase encoding (full byte)
- QPSK: 4-state phase modulation (2 bits/symbol)
- QAM-16: 16-state phase/amplitude modulation (4 bits/symbol)
- DMT: Multi-carrier modulation using strands as subcarriers
QPSK Constellation
4 phase states: 0°, 90°, 180°, 270° Phase values: 0x7FFF, 0x4000, 0x8000, 0xC000 in Q0.16
QAM-16 Constellation
16 phase/amplitude states: 4 amplitudes × 4 phases 4×4 grid with varying amplitude levels.
DMT Subcarrier Parameters
8 strands as subcarriers with 45° phase offset increments:
offset_i = i × 0x2000
Modulation:
phase_out = base_phase + subcarrier_offset
Demodulation:
demod_phase = phase_in - subcarrier_offset
byte = phaseToByte(demod_phase)
Biological Acoustic Sensing Theory
File: Semantics/Semantics/Extensions/CognitiveAcousticDynamics.lean
Core Concepts
- Acoustic Pressure Amplification: Water density (~1000× air) magnifies pressure wave propagation
- Statolith Displacement: Gravity-sensing organelles respond to pressure gradients as mechanical sensors
- Pressure Wave Transduction: Biological systems encode acoustic information without dedicated auditory equipment
- Medium-Dependent Signal Encoding: Same acoustic event produces different information density based on propagation medium
Pressure Wave Magnification
Raindrop Impact Acoustic Pressures:
- Shallow puddle (submerged): hundreds of Pascals
- Human conversation (1m in air): 0.005-0.05 Pascals
- Amplification factor: ~10,000× in water vs air
Jet Engine Equivalence:
- Seed within few centimeters of raindrop impact experiences pressure equivalent to being within few meters of jet engine in air
- Demonstrates extreme signal amplification in dense media
Biological Signal Transduction Mechanism
- Raindrop Impact: Creates acoustic pressure wave in water/soil
- Pressure Propagation: Water density amplifies wave amplitude
- Statolith Response: Gravity-sensing organelles mechanically respond to pressure gradients
- Signal Encoding: Statolith displacement triggers germination signaling cascade
- Biological Response: Seeds germinate ~37% faster in response to acoustic stimulation
Mathematical Model
Pressure Wave Amplitude in Medium:
P_water ≈ ρ_water/ρ_air × P_air ≈ 1000 × P_air
Statolith Displacement Threshold:
displacement = f(P_acoustic, distance_from_impact, medium_density)
germination_rate ∝ displacement
Germination Acceleration:
rate_with_acoustic = rate_baseline × 1.37
Integration Points
- CognitiveAcousticDynamics.lean: Formal modeling of biological acoustic sensing
- ShockwaveAlignmentRelaxation.lean: Shockwave propagation in biological media
- WavefrontEmitter.lean: Pressure wave generation and propagation
- Spectral Encoding Theory: Acoustic signal spectral signatures
Research Stack Connections
This biological acoustic sensing mechanism demonstrates:
- Information-Physics equivalence in biological systems
- Mechanical signal transduction without dedicated sensors
- Medium-dependent signal amplification
- Environmental signal encoding in biological state machines
Predictive Harmony Social Synchrony
Status: External neuroacoustic route prior, not a therapy claim.
Source: Watts et al., "Listening to a Consonant Chord Progression during
Live Face-to-Face Gaze Enhances Neural Activity in Social Systems", Journal of
Neuroscience, DOI 10.1523/JNEUROSCI.1116-25.2026.
Core Concept
Structured, predictable chord progressions paired with live face-to-face gaze can be treated as a synchronization prior:
shared predictable harmonic structure
+ live mutual-attention channel
-> cross-agent temporal alignment witness
The useful stack primitive is not "music causes bonding." It is:
predictable temporal structure can reduce coordination uncertainty when the
participants also share a live social alignment channel.
Minimal Gate
S_harmony = P_chord * G_live * A_cross
Where:
P_chord= structured/consonant chord-progression scoreG_live= live gaze or mutual-attention gateA_cross= cross-agent temporal alignment witness
The negative control is the same note/instrument set with scrambled or unstructured temporal order.
Integration Points
- Phonon Music Logogram Layer: harmonic function and voice leading remain route hints, not payload authority.
- Cognitive Acoustic Dynamics: predictable acoustic structure becomes a low-load synchrony sidecar.
- BMVR/BVMR/CMR: route admission can use the synchrony gate, but replay still requires receipts.
- Static decompression: harmonic skeletons can guide timing sidecars, but byte-exact closure remains separate.
Hold Boundaries
HOLD_NO_SYNCHRONY_RECEIPT
HOLD_NO_NEGATIVE_CONTROL
HOLD_THERAPY_CLAIM
QUARANTINE_SOCIAL_CONTROL
Physics-Disruptive Synthesis
This signal theory compendium challenges conventional physics through:
- Information-Physics Equivalence: Genetic events map to spectral signatures, hydrogen spectral lines encode information, energy gradients carry thermodynamic information
- Quantum-Classical Hybrid: DSP operations controlled by morphic scalar state machines, wavefront emission in resonant fields, S3C resonance with parabolic J-scores
- Thermodynamic Information Channels: Energy gradients as information carriers, entropy production channels, Gibbs free energy compensation
- Genomic-Spectral Isomorphism: 3-mer DCT spectra compress genetic information, hydrogen spectral basis provides physical foundation, spectral genome hypothesis falsifiable at 6.5σ
- Multi-Carrier Biological Modulation: DMT using strands as subcarriers, PBACS signal transport with phi-torsion, fitness-entropy compensation from bioRxiv
"We are going to piss off physics." — Mission Accomplished.
Generated from Research Stack Signal Theory Modules All values in Q16.16 fixed-point unless otherwise noted