The Universe is not a machine depleting energy
but a self-regulating frequency resonance system

**From Bits to Civilization: A Unified Theory of Cross-Scale Information Evolution**

Theory Originator: (Damon)  
Theoretical Foundation: scott.cgi's "Everything is Bits" + Information Gene Philosophy v1.0/v2.0  
Version: 3.0 (2025)  
Core Breakthrough: Establishing the "Bit-Frequency-Gene" Trinity Framework

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# Theoretical Manifesto

The universe is not a collection of matter, but a symphony of bits;  
Information is not abstract symbols, but the essence of existence;  
Evolution is not accidental emergence, but the inevitable iteration of frequencies.

**Core Proposition**: Information genes are stable combinations of bits, physically manifested as resonance patterns of specific frequencies, functionally characterized as replicable, mutable, and heritable units of order. From quantum to civilization, all evolution is a self-organizing process of information genes in the frequency domain.

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Chapter 1: Theoretical Foundation—The Unity of Bits, Frequency, and Information Genes

1.1 Ontological Anchor: Everything is Bits

1.1.1 Bits as the Indivisible Foundation

Core Proposition (quoted from scott.cgi, 2016):

"What is the most fundamental, indivisible matter?... That is the bit, the basic unit of information, representing the smallest information structure. Because matter is (recursively) composed of smaller matter, the smallest matter has the smallest structure, and the smallest material structure corresponds to the smallest information structure, namely 0 and 1."

Physical Verification:

Quantum Mechanics: After wave function collapse, measurement results are discrete eigenstates (0 or 1)

Planck Constant: $h = 6.626×10⁻³⁴ J·s$, representing "structural information at the observable limit"

Quantum Bits: 0/1 in superposition state, with probability distribution corresponding to

$$0,1$$

real numbers

Mathematical Proof (scott.cgi):

$$\text{Number of bits} \leftrightarrow [0,1]\text{ real numbers} \leftrightarrow \text{all real numbers}$$

Cardinality of real numbers = $2^{\aleph_0}$ (continuum)

Much greater than cardinality of natural numbers $\aleph_0$ (countable infinity)

Significance: The complexity of information space is exponential

1.1.2 Frequency as the Temporal Unfolding of Bits

Definition: Frequency is the periodic rate of change of bits in the time dimension

$$f = \frac{1}{T}, \quad E = hf, \quad p = \frac{h}{\lambda}$$

Cross-Scale Frequency Spectrum:

| Scale | Frequency Range | Physical Manifestation | Bit Expression |
|-------|----------------|------------------------|----------------|
| Quantum | 10²⁰ Hz | γ-ray photons | Ultra-high frequency flipping |
| Atomic | 10¹⁵ Hz | Electronic energy level transitions | Stable frequency locking |
| Molecular | 10¹² Hz | Chemical bond vibrations | Medium frequency resonance |
| Cellular | 10⁶ Hz | Membrane potential oscillations | Biological rhythms |
| Neural | 10² Hz | Brain waves (α/β/γ) | Information processing frequency |
| Social | 10⁻⁷ Hz | Institutional cycles (years) | Cultural frequency |

Key Insights:

Different frequencies are not "analogies" but real oscillations of bits at different time scales

Low frequency is not "slow" but "long-period stable patterns"

Frequency coupling (such as harmonics, subharmonics) is the physical mechanism of cross-scale information transfer

1.1.3 Precise Definition of Information Genes

Ultimate Definition: Information Gene (Informational Gene, IG) = A bit combination pattern with stable frequency characteristics, satisfying three elements:

Replicability: The pattern can propagate in spacetime without distortion (fidelity > threshold)

Mutability: External perturbations or internal fluctuations can change the pattern (mutation rate > 0)

Selectability: Environment exerts differential survival pressure on different patterns

Mathematical Expression:

$$IG = \{B(t), f_0, \sigma_f, \mathcal{R}, \mathcal{M}, \mathcal{S}\}$$

$B(t)$: Temporal evolution of bit sequence

$f_0$: Dominant frequency (center frequency)

$\sigma_f$: Frequency bandwidth (stability indicator)

$\mathcal{R}$: Replication operator (such as DNA polymerase, social imitation)

$\mathcal{M}$: Mutation operator (such as quantum fluctuations, genetic mutations)

$\mathcal{S}$: Selection operator (such as minimum energy principle, natural selection)

Differences from Traditional "Genes":

| Dimension | Biological Gene (DNA) | Information Gene (IG) |
|-----------|----------------------|----------------------|
| Carrier | Base sequence | Bit pattern |
| Replication | Base pairing | Frequency resonance |
| Mutation | Base substitution | Frequency perturbation |
| Selection | Fitness | Order degree |
| Scale | Biological layer | All scales |

1.2 Methodological Tools: Spectral Analysis and Order Degree

1.2.1 Spectral Entropy: A Measurable Order Indicator

Definition (based on Shannon entropy):

$$S_{freq} = -\sum_{i=1}^{N} p_i \log_2 p_i$$

$p_i = \frac{P_i}{\sum_j P_j}$: Normalized power of the i-th frequency component

$N$: Number of frequency resolution units (depends on sampling rate)

Physical Meaning:

$S_{freq} \to 0$: Energy concentrated in a single frequency (like laser, high order)

$S_{freq} \to \log_2 N$: Energy uniformly distributed (like white noise, disorder)

Relationship with Thermodynamic Entropy (Landauer's Principle):

$$\Delta S_{thermo} \geq k_B \ln 2 \cdot \Delta S_{info}$$

Changing 1 bit of information → changing $k_B \ln 2$ of thermodynamic entropy

Verification: Quantum computing experiments confirm that erasing 1 bit requires dissipating at least $k_B T \ln 2$ energy

1.2.2 Frequency Order Degree: Bridging Philosophy and Physics

Definition:

$$O_{freq} = 1 - \frac{S_{freq}}{S_{max}} = 1 - \frac{S_{freq}}{\log_2 N}$$

Value Range: $O_{freq} \in [0, 1]$

$O_{freq} = 1$: Perfect single frequency (like phonons in ideal crystals)

$O_{freq} = 0$: Completely random (like cosmic microwave background)

Measurement Methods:

Spectral Measurement (Physical Layer)

Terahertz time-domain spectrometer: 0.1-10 THz

Resolution: 0.01 THz

Applications: Meridian acupoints, molecular vibrations

Electrical Signal Measurement (Biological Layer)

Multi-channel electroencephalogram (EEG): 0.5-100 Hz

Sampling rate: 1000 Hz

Applications: Brain wave analysis, heart rate variability

Time Series Analysis (Social Layer)

Fourier transform to extract periodic components

Wavelet transform for non-stationary signals

Applications: Economic cycles, social network dynamics

Example Calculation: Assume the terahertz spectrum of an acupoint is:

| Frequency (THz) | Power (a.u.) |
|----------------|--------------|
| 2.0 | 0.1 |
| 2.5 | 0.6 |
| 3.0 | 0.2 |
| 3.5 | 0.05 |
| 4.0 | 0.05 |

Calculation:

$$p = [0.1, 0.6, 0.2, 0.05, 0.05]$$

$$S_{freq} = -(0.1\log_2 0.1 + 0.6\log_2 0.6 + 0.2\log_2 0.2 + 2 \times 0.05\log_2 0.05) \approx 1.58$$

$$O_{freq} = 1 - \frac{1.58}{\log_2 5} = 1 - \frac{1.58}{2.32} \approx 0.32$$

Interpretation: The frequency order degree of this acupoint is 0.32, indicating that although there is a main peak (2.5 THz), the dispersion is relatively high.

1.2.3 Cross-Scale Scale Invariance

Fractal Principle (scott.cgi):

"All structures are formed by the arrangement and combination of more basic structures... Everything in the universe is constructed through fractal recursion."

Mathematical Expression:

$$O_{level+1} = \mathcal{F}(O_{level}, \text{coupling})$$

$\mathcal{F}$: Hierarchical transition function

coupling: Inter-layer coupling strength

Empirical Cases:

Physics: Crystal (atomic O≈0.9) → Solid (macroscopic O≈0.85)

Biology: DNA (molecular O≈0.8) → Chromosome (cellular O≈0.75)

Society: Individual behavior (O≈0.6) → Institution (collective O≈0.7)

1.3 Evolutionary Mechanisms: Frequency Version of Replication-Mutation-Selection

1.3.1 Information Inertia: Frequency Locking

Definition: The tendency of a system to maintain its current frequency pattern

Physical Origins:

Quantum Layer: Energy level spacing → transitions require precise energy ($\Delta E = hf$)

Chemical Layer: Potential well depth → activation energy prevents frequency changes

Biological Layer: Epigenetics → DNA methylation stabilizes gene frequency

Social Layer: Path dependence → QWERTY keyboard frequency locking

Mathematical Model (Damped Oscillator):

$$m\ddot{x} + \gamma\dot{x} + kx = F_0 \cos(\omega t)$$

Natural frequency: $\omega_0 = \sqrt{k/m}$

Damping coefficient $\gamma$: Information inertia strength

Maximum resonance amplitude when $\omega \approx \omega_0$

1.3.2 Information Resonance: Frequency Coupling

Three Modes:

Linear Resonance (Frequency Matching)

Condition: $f_1 = f_2$

Example: Phase locking of photons in laser cavity

Effect: Efficient energy transfer

Nonlinear Resonance (Frequency Conversion)

Condition: $f_3 = n_1 f_1 + n_2 f_2$ (harmonic/sum frequency)

Example: Second harmonic generation ($2\omega$ laser)

Effect: Frequency up/down conversion

Stochastic Resonance (Noise Synergy)

Condition: Weak signal + appropriate noise

Example: Subthreshold stimulus detection in neurons

Effect: Enhanced signal-to-noise ratio

Cross-Hierarchical Resonance Cases:

Bio-Cultural Resonance:

Human brain γ waves (40 Hz) ↔ Language phoneme frequency (4-8 Hz)

Mechanism: Cross-frequency coupling of neural oscillations (PAC, Phase-Amplitude Coupling)

Verification: EEG shows γ waves modulate θ waves during reading

Technology-Society Resonance:

Internet propagation frequency (second-level) ↔ Social opinion cycles (day-week)

Mechanism: Exponential diffusion of information cascades

Verification: Twitter data shows hot topic propagation follows power-law distribution

1.3.3 Frequency Selection: Order Degree Optimization

Frequency Version of Price Equation:

$$\Delta \bar{O} = \text{Cov}(w_i, O_i) + \mathbb{E}(w_i \Delta O_i)$$

$w_i$: Fitness of the i-th information gene

$O_i$: Order degree of the i-th information gene

First term: Selection effect (high O retained)

Second term: Mutation effect (generational change in O)

Frequency Mechanism of Natural Selection:

Physics: Minimum energy principle → selects low frequency (stable) structures

Chemistry: Reaction rate → selects medium frequency (active) catalysts

Biology: Metabolic efficiency → selects optimal frequency configurations

Culture: Propagation efficiency → selects easily memorable frequency patterns

Chapter 2: Five-Layer Evolutionary Architecture—From Bits to Civilization

2.1 Level 0: Meta-Information (Bit Layer)

2.1.1 Cosmic Initial State: Perfect Single-Frequency Singularity

Physical Picture:

Moment: $t = 0$ (before Big Bang)

State: All bits in superposition state, $|0\rangle + |1\rangle$

Frequency: Planck frequency $f_P = \frac{c^5}{\hbar G} \approx 1.855 \times 10^{43}$ Hz

Order degree: $O_{freq} \approx 1$ (perfect coherence)

Philosophical Correspondence:

Tao Te Ching: "Tao gives birth to One" (unified frequency field)

Plato: "World of Ideas" (perfect mathematical structure)

2.1.2 Inflation: Exponential Diffusion of Frequency

Time: $10^{-35}$ seconds

Process: Quantum fluctuations → frequency perturbations → exponential amplification

$$\delta f / f_P \sim 10^{-5} \quad \Rightarrow \quad \Delta T / T \sim 10^{-5}$$

(Temperature fluctuations in cosmic microwave background radiation)

Bit Evolution:

t=0: |11111111...⟩ (all bits in phase)
↓ quantum fluctuations
t=10⁻³⁵: |11111011...⟩ (few bits flipped)
↓ inflation amplification
t=10⁻³²: |11010101...⟩ (bit distribution becomes Gaussian)

Frequency Distribution:

Initial: δ function (single frequency)

Post-inflation: Gaussian distribution (narrow band)

Current universe: Power-law distribution (broad band)

2.1.3 Particle Formation: Frequency Quantization

Time: $10^{-6}$ seconds

Temperature: $10^{15}$ K

Process: Quark condensation → protons/neutrons → atomic nuclei

Frequency Mechanism:

$$E = mc^2 = hf \quad \Rightarrow \quad f = \frac{mc^2}{h}$$

| Particle | Mass (kg) | Corresponding Frequency (Hz) | Order Degree |
|----------|-----------|------------------------------|--------------|
| Electron | 9.1×10⁻³¹ | 1.2×10²⁰ | 0.6 |
| Proton | 1.7×10⁻²⁷ | 2.3×10²³ | 0.68 |
| Neutron | 1.7×10⁻²⁷ | 2.3×10²³ | 0.68 |

Key Insights:

Mass = "locked frequency" of bit information

Particle indivisibility = lower limit of frequency quantization

Wave-particle duality = frequency-space uncertainty

2.2 Level 1: Material Information (Structure Layer)

2.2.1 Atoms: Spatial Locking of Frequency

Frequency Interpretation of Bohr Model:

$$E_n = -\frac{13.6 \text{ eV}}{n^2} \quad \Rightarrow \quad f_{nm} = \frac{|E_n - E_m|}{h}$$

Hydrogen Atom Frequency Spectrum:

Lyman series (UV): $f \sim 10^{15}$ Hz

Balmer series (visible light): $f \sim 10^{14}$ Hz

Paschen series (infrared): $f \sim 10^{13}$ Hz

Frequency Stability:

Excited state lifetime: $10^{-8}$ seconds (frequency locking time)

Energy level width: $\Delta E \sim \hbar / \tau$ (uncertainty principle)

Order degree: $O_{freq} \approx 0.72$ (based on spectral linewidth)

2.2.2 Molecules: Resonant Coupling of Frequency

Vibrational Frequency of Chemical Bonds:

$$f_{vib} = \frac{1}{2\pi}\sqrt{\frac{k}{\mu}}$$

$k$: Bond force constant (N/m)

$\mu$: Reduced mass (kg)

Typical Chemical Bond Frequencies:

| Bond Type | Frequency (Hz) | Wavenumber (cm⁻¹) | O Value |
|-----------|----------------|-------------------|---------|
| C-H | 8.7×10¹³ | 2900 | 0.88 |
| O-H | 1.0×10¹⁴ | 3300 | 0.85 |
| C=C | 1.5×10¹⁴ | 1650 | 0.92 |
| C≡C | 2.0×10¹⁴ | 2100 | 0.95 |

Frequency Interpretation of Phase Transitions:

Ice→Water: Hydrogen bond frequency from narrow peak ($O=0.85$) → broad band ($O=0.65$)

Water→Steam: Molecular rotational frequency from constrained → free ($O=0.2$)

Experimental Verification:

Infrared spectroscopy: Direct measurement of molecular vibrational frequencies

Raman spectroscopy: Frequency measurement through scattering

Conclusion: Chemical properties = frequency fingerprints

2.2.3 Crystals: Spatial Periodicity of Frequency

Phonons (Lattice Vibrations):

$$\omega = \omega_0 \sin\left(\frac{ka}{2}\right)$$

$a$: Lattice constant

$k$: Wave vector

Diamond's Ultimate Order:

All C-C bonds vibrate at same frequency: $9.3 \times 10^{13}$ Hz

Spectral entropy: $S_{freq} \approx 0.05$

Order degree: $O_{freq} \approx 0.95$

Result: Hardness 10 (Mohs), thermal conductivity 2000 W/(m·K)

Quasicrystal Frequency Mismatch:

Five-fold symmetry → cannot tile space

But locally ordered → $O_{freq} \approx 0.7$

Proof: Order degree ≠ periodicity

2.3 Level 2: Life Information (Gene Layer)

2.3.1 DNA: Digital Frequency of Life

Base Pair Vibrational Frequencies:

A-T: $f_{AT} = 1.2 \times 10^{13}$ Hz (hydrogen bond)

G-C: $f_{GC} = 1.8 \times 10^{13}$ Hz (triple hydrogen bond)

Frequency Ratio: $f_{GC}/f_{AT} = 1.5$ (golden ratio approximation)

Genetic Code Frequency Analysis:

Codon usage bias → frequency optimization

High-expression genes prefer high-frequency codons

Synonymous codons have different tRNA frequencies

DNA Replication Frequency:

Polymerase speed: ~50 bp/s = 50 Hz (information copying rate)

Proofreading frequency: 1 error per $10^9$ bp (error correction rate)

Mutation rate: $10^{-10}$ per bp per generation (frequency drift)

2.3.2 Proteins: Functional Frequency Machines

Enzyme Catalysis Frequency Matching:

Substrate vibrational frequency: $f_s$

Enzyme active site frequency: $f_e$

Catalytic efficiency: $k_{cat} \propto J(f_s, f_e)$ (overlap integral)

Experimental Evidence (Quantum Tunneling):

Alcohol dehydrogenase: H atom tunneling frequency $\sim 10^{13}$ Hz

Isotope effect: D replacing H reduces frequency by $\sqrt{2}$, reaction rate decreases 7-fold

Conclusion: Enzymes reduce activation energy through frequency matching

Photosynthesis Frequency Cascade:

Solar light absorption (5×10¹⁴ Hz)
↓
Exciton transfer (10¹² Hz)
Electron transport chain (10⁶ Hz)
↓
ATP synthesis (10³ Hz)
Calvin cycle (10⁻² Hz)

Quantum Biology Evidence:

European robin magnetoreception: Radical pair quantum entanglement ~ μs

Olfactory "vibration theory": Molecular frequency recognition (Luca Turin, 1996)

2.3.3 Nervous System: Frequency Symphony of Consciousness

Brainwave Spectrum:

| Band | Frequency | Function | S_freq | O Value |
|------|-----------|----------|--------|---------|
| δ | 0.5-4 Hz | Deep sleep | 0.2 | 0.8 |
| θ | 4-8 Hz | Memory | 0.35 | 0.65 |
| α | 8-13 Hz | Relaxation | 0.4 | 0.6 |
| β | 13-30 Hz | Focus | 0.5 | 0.5 |
| γ | 30-100 Hz | Consciousness binding | 0.6 | 0.4 |

"Frequency Binding" Hypothesis of Consciousness (Crick & Koch, 1990):

Different brain regions synchronize through γ waves (40 Hz)

Form unified perceptual experience

Mathematical Model:

$$\Phi = \int_{\text{brain regions}} \text{phase coherence}(40 \text{ Hz}) \, dV$$

Consciousness emerges when $\Phi > \Phi_c$

Meditation Frequency Regulation:

Beginners: Enhanced α waves (single frequency peak)

Advanced practitioners: Reduced all bands + ultra-slow oscillations (<0.1 Hz)

Neuroplasticity: Repeated training changes brain's intrinsic frequencies

2.4 Level 3: Neural Information (Mind Layer)

2.4.1 Memory: Crystallization of Frequency Patterns

Frequency Version of Hebbian Learning:

"Neurons that fire together, wire together"

Frequency Interpretation:

Pre- and post-synaptic neurons fire at same frequency (γ waves)

Triggers LTP (Long-Term Potentiation) → increased synaptic weight

Result: Specific frequency patterns are "carved into" neural networks

Frequency Encoding of Memory:

Working memory: γ wave (40 Hz) sustained oscillations

Long-term memory: θ wave (6 Hz) phase encoding

Episodic memory: Coupling of hippocampal θ waves with neocortical γ waves

2.4.2 Thinking: Combination of Frequency Flows

Scott.cgi's Insight:

"Thinking—is precisely the product of data flowing, absorbing, reorganizing, and randomly freely combining in the (neural network) structure."

Frequency Flow Model:

Sensory input (external frequencies)
↓
Thalamic gating (filtering)
Primary sensory cortex (feature frequencies)
↓
Hierarchical processing
Association cortex (frequency combination)
↓
Working memory (γ wave maintenance)
Prefrontal cortex (frequency selection)
↓
Motor output
Behavior (muscle frequencies)

Frequency Mechanism of Creativity:

Divergent thinking: Low frequency (α waves), loose network coupling

Moment of insight: Sudden high frequency (γ wave bursts)

Convergent thinking: Medium frequency (β waves), strong network coupling

2.4.3 Free Will: Emergence of Frequency Self-Organization

Frequency Reconciliation of Determinism vs Free Will:

Microscopic: Neuronal firing is random (ion channel noise)

Macroscopic: Brain as a whole can produce stable frequency patterns

Key: Self-Organized Criticality (SOC)

Critical Brain Hypothesis:

Brain operates at phase transition critical point (like water's triple point)

Small perturbations can trigger large-scale reorganization (avalanche dynamics)

Meaning: Free will = sensitive dependence of critical state

2.5 Level 4: Cultural Information (Civilization Layer)

2.5.1 Language: Frequency Encoding of Symbols

Acoustic Frequencies of Spoken Language:

Fundamental frequency (F0): 80-250 Hz (gender difference)

Formants (F1-F3): 300-3000 Hz (phoneme distinction)

Tonal languages (Chinese): F0 modulation rate 5-10 Hz

Visual Frequencies of Written Language:

Chinese character recognition: Spatial frequency 2-8 cycles/degree

Reading speed: 250 characters/min ≈ 4 Hz (information reception sampling rate)

Neural correlate: Angular gyrus γ waves (40 Hz) process character forms

Frequency Selection in Language Evolution:

Learnability: Selects natural frequencies of human vocal apparatus

Distinctiveness: Selects frequencies most sensitive to auditory system (1-4 kHz)

Prosody: Selects rhythms harmonious with breathing, heartbeat frequencies (0.5-2 Hz)

Evidence: World languages' fundamental frequency distribution is Gaussian, peaked at 150 Hz (human larynx natural frequency)

2.5.2 Technology: Precise Control of Artificial Frequencies

Technological Evolution = Improvement in Frequency Control Precision:

| Era | Core Technology | Frequency Control | Δf/f | O Value |
|-----|-----------------|-------------------|------|---------|
| Stone | Percussion | No periodicity | - | 0.3 |
| Bronze | Metallurgy | 10⁻² Hz (hours) | 0.5 | 0.5 |
| Mechanical | Clockwork | 1-10 Hz | 10⁻³ | 0.7 |
| Electrical | AC power | 50/60 Hz | 10⁻⁶ | 0.85 |
| Information | CPU | 10⁹ Hz | 10⁻⁹ | 0.9 |
| Quantum | Atomic clock | 10¹⁴ Hz | 10⁻¹⁸ | 0.98 |

Optical Fiber Communication Frequency Fidelity:

Carrier: 1.5 μm = 2×10¹⁴ Hz

Phase noise: <10⁻¹⁵

Transmission loss: 0.2 dB/km (power → frequency stability)

Information entropy increase rate: <1%/1000 km

Quantum Computing: Ultimate Frequency Manipulation:

Qubit frequency: 4-6 GHz (superconducting)

Coherence time: ~100 μs (frequency stability duration)

Gate operation time: ~20 ns (frequency flip speed)

Challenge: Environmental noise destroys frequency coherence

2.5.3 Institutions: Social Frequency Regulation

Institutions = Synchronization mechanisms for behavioral frequencies

Legal Frequency Stability:

Constitution: Amendment cycle 10-50 years (10⁻⁸ Hz)

Laws: Revision cycle 1-5 years (10⁻⁷ Hz)

Precedents: Evolution cycle months-years (10⁻⁶ Hz)

Hierarchy: Low frequency (constitution) constrains high frequency (precedents)

Frequency Decomposition of Economic Cycles:

Kitchin cycle (3-4 years): Inventory, $f \approx 10^{-8}$ Hz

Juglar cycle (8-10 years): Equipment, $f \approx 3 \times 10^{-9}$ Hz

Kuznets cycle (15-25 years): Construction, $f \approx 1.5 \times 10^{-9}$ Hz

Kondratieff cycle (50-60 years): Technology, $f \approx 5 \times 10^{-10}$ Hz

Spectral Analysis for Crisis Prediction:

Before 2008 financial crisis: Abnormal power-law exponent in high-frequency fluctuations

Early warning signal: Sudden enhancement of low-frequency resonance peaks

Mechanism: "Critical slowing down" before system instability

2.5.4 Memes: Frequency Propagation of Cultural Genes

Meme replication = Social transmission of frequency patterns

Frequency Model of Viral Spread:

$$\frac{dI}{dt} = \beta SI - \gamma I$$

$\beta$: Transmission frequency

$\gamma$: Forgetting frequency

Transmission threshold: $\beta / \gamma > 1$

Frequency Resonance of Short Video Algorithms:

Recommendation frequency: 1-5 seconds/item (0.2-1 Hz)

Key: Close to human brain θ waves (4-8 Hz) → cognitive resonance

Result: Addiction (frequency locking) + attention fragmentation (O value 0.7→0.4)

Frequency Democracy in DAO Governance:

Proposal frequency: ~1/week (1.65×10⁻⁶ Hz)

Voting frequency: ~1/day (1.16×10⁻⁵ Hz)

Health indicator: Proposal-voting frequency ratio ∈ [0.1, 1]

Failure signs: Frequency ratio <0.01 (proposal overload) or >10 (insufficient participation)

Chapter 3: Interdisciplinary Verification—Empirical Support for the Theory

3.1 Physics Verification

3.1.1 Quantum Entanglement: Projection of Low-Frequency Information Coherence

Under the information ontology of "everything is bits," the "faster-than-light" phenomenon of quantum entanglement is not physical faster-than-light signal transmission, but rather a projection distortion of low-frequency information coherence at the deeper bit level in the spacetime coordinate system.

I. Physical Level: Entanglement ≈ Extreme Form of "Frequency Phase-Locking"

The essence of entanglement is that two quantum systems achieve a global phase lock at the coherence level, with their wave functions becoming an inseparable whole. This state can be understood as a deep, macroscopic, steady-state "background synchronization," rather than high-frequency, local signal propagation.

High-frequency fluctuations mean local, transient, unstable energy disturbances.

Low-frequency resonance means deep, macroscopic, steady-state "background synchronization."

Therefore, entanglement is a deep low-frequency coherent resonance state that does not transmit energy at high speed, but maintains synchronization of slow-frequency information across space.

II. Information Theory Level: Non-locality = Information Layer Synchronization

In the information gene philosophy framework, the speed of light constrains the "phenomenal layer" (energy and spacetime propagation), while entanglement reveals the characteristics of the "ontological layer" (information frequency resonance).

High frequency: Local high-energy states, particle-level disturbances.

Low frequency: System-wide stable order (such as gravitational fields, vacuum zero-point fields).

The apparent "faster-than-light" effect is actually a sampling bias that occurs when high-frequency measurement tools (such as particle detectors) observe a low-frequency, non-local coherent process.

III. Theoretical Model: Source of Observational Error

When we forcibly map a coordinate-independent, globally coherent information process (low-frequency resonance) into a local spacetime coordinate system, the "faster-than-light" illusion appears in observation.

This can be expressed as:

$$V_{obs} > c \Rightarrow \text{Mapping Error (Information Projection Distortion)}$$

$$\text{Entanglement coherence} = f_{low}(\text{Information fundamental frequency resonance})$$

$$c = f_{proj}(\text{Projection upper limit of information propagation})$$

IV. Summary: "Low-Frequency Coherence Model" of Entanglement

| Level | Ontological Description | Corresponding Phenomenon | Theoretical Relationship |
|-------|------------------------|-------------------------|-------------------------|
| Information layer (bits) | Low-frequency coherence | Quantum entanglement | Non-local, holistic |
| Energy layer (light speed) | High-frequency propagation | Electromagnetic signals | Local, causal |
| Phenomenal layer (observation) | Projection error | "Faster-than-light" illusion | Spacetime mismatch |

Conclusion: If "everything is bits," then entanglement does not violate the speed of light law, but rather the speed of light law itself only constrains high-frequency energy propagation processes at the phenomenal layer. True "synchronicity" exists in the low-frequency coherence domain at the bit substrate.

3.1.2 Black Hole Information Paradox: Frequency Encoding at the Event Horizon

Hawking Radiation Frequency:

$$f_H = \frac{c^3}{8\pi GMk_B} \approx 10^{-8} \text{ Hz (solar mass)}$$

Frequency Version of Holographic Principle:

Black hole surface area (number of bits) ~ entropy

Each Planck area ~ 1 bit

Inference: 3D information encoded in 2D frequency distribution (gravitational wave modes)

Gravitational Wave Spectrum Carries Information:

LIGO observation: Frequency evolution of black hole mergers (30-250 Hz)

Frequency "chirp" → mass, spin, distance

Verification: Frequency = physical carrier of information

3.1.3 Frequency Nature of Time

Time = reciprocal of frequency:

$$\Delta t = \frac{1}{\Delta f} \quad \text{(uncertainty principle)}$$

Atomic Clock Time Definition:

1 second = 9,192,631,770 periods of cesium-133 hyperfine transition

Essence: Time is defined by frequency, not vice versa

Frequency Interpretation of Time Dilation:

$$\Delta t' = \gamma \Delta t = \frac{\Delta t}{\sqrt{1-v^2/c^2}}$$

Motion reduces intrinsic frequency (Doppler redshift)

Gravity reduces photon frequency (gravitational redshift)

Unification: Spacetime curvature = geometry of frequency field

3.1.4 Deep Unification in Physics: Frequency Interpretation of Gravity and Quantum Fields

Fracture Point Analysis: Why Gravity Field (Continuous) and Photon Field (Discrete) Must Be Unified

The core contradiction of modern physics lies in the mathematical and philosophical incompatibility between general relativity (describing continuous gravitational fields) and quantum field theory (describing discrete particle fields like photons). Information gene philosophy argues that this fracture stems from treating "fields" and "particles" as different ontologies, when in fact they are different manifestations of information frequency fields at different scales.

Unified Information Frequency Field Framework:

Gravity = Low-frequency large-scale phase curvature state:
The gravitational field is not a geometric property of spacetime, but an ultra-low-frequency, long-wave mode of the universal background information field. Mass is a region of energy concentration in this field, causing gradient changes in surrounding phase information, manifesting as spacetime curvature.

Photons = High-frequency microscale local rotation state:
Photons and other fundamental particles are localized energy excitations of the information field in the high-frequency band, with phases exhibiting periodic rotation, manifesting as discrete quantized states.

Information Interpretation of Spin:
Spin is no longer an intrinsic, inexplicable angular momentum of particles, but an angular momentum representation of local information coherence. It describes the vortex state of phase flow at the Planck scale. The phase flow vortex of photon spin, in the limit of continuization at macroscopic scales, manifests as spacetime curvature.

Conjecture for Unified Field Equation:
All field behaviors can be described by a unified information field equation, possibly of the form:

$$\nabla^2\phi = f(\omega, S, O)$$

where $\phi$ represents the information field potential, whose changes are jointly determined by frequency ($\omega$), spectral entropy ($S$), and order degree ($O$).

Frequency Manifold:
Replace spacetime curvature with frequency gradients; the spacetime metric tensor $g_{\mu\nu}$ can be defined by frequency gradients of the information field:

$$g_{\mu\nu} = f(\partial_\mu \omega, \partial_\nu \omega)$$

Key Breakthrough Points:

Ontological unification: Eliminates particle-field dualism; both are different modes of information frequency fields.

Spin-curvature unification: Establishes scale transition relationship between microscopic local rotation (spin) and macroscopic global curvature (gravity).

Verifiable Predictions:

Gravitational wave frequency upper limit: There exists an upper limit for gravitational wave frequency determined by Planck frequency (~10⁴³ Hz).

Frequency quantization in strong gravitational fields: In extreme gravitational environments like near black holes, spacetime (i.e., low-frequency information field) itself may exhibit observable quantization effects.

Black hole event horizon = frequency singularity surface: The black hole event horizon is a phase transition interface where information frequency undergoes abrupt changes.

3.2 Biology Verification

3.2.1 Frequency Selection in Evolution

Neutral vs Adaptive Evolution:

Neutral mutations: No significant frequency change ($\Delta O < 0.01$)

Adaptive mutations: Frequency optimization ($\Delta O > 0.05$)

Frequency Evolution of Galápagos Finches:

Beak shape gene frequency: $f_{beak}$

Food hardness selection pressure: $P(hardness)$

Observation: During drought years, beak shape frequency shifts toward "hard-food type"

O value change: 0.83 → 0.85 (order degree increase = fitness increase)

3.2.2 Frequency Regulation in Epigenetics

DNA Methylation = Frequency Switch:

Methylation sites: Local frequency reduction ($O \approx 0.82$)

Demethylation: Local frequency restoration ($O \approx 0.85$)

Function: Frequency gating of gene expression

Frequency Encoding of Histone Modifications:

Acetylation (Ac): Chromatin relaxation → high-frequency accessibility

Methylation (Me): Chromatin compaction → low-frequency suppression

Combinatorial encoding: H3K4me3 + H3K27ac = active promoter

3.2.3 Frequency Networks in Ecosystems

Food Chain Frequency Cascade:

Primary producers (plants): Annual cycle (10⁻⁷ Hz)
↓ Energy transfer 10%
Primary consumers (herbivores): Monthly cycle (10⁻⁶ Hz)
↓ Energy transfer 10%
Secondary consumers (carnivores): Weekly cycle (10⁻⁵ Hz)

Species Diversity = Frequency Diversity:

Shannon diversity index ~ spectral entropy $S_{freq}$

Niche differentiation = different species occupy different frequency bands

Verification: Coral reefs (high diversity) spectral entropy > polar regions (low diversity)

3.3 Neuroscience Verification

3.3.1 Brainwaves and Cognitive Functions

Working Memory Capacity = Number of γ Wave Frequency Cycles:

Miller's Law: 7±2 items

Frequency interpretation: γ waves (40 Hz) + θ waves (6 Hz) nesting

One θ cycle (167 ms) can accommodate 6-7 γ cycles

Prediction: Training to enhance γ wave frequency → improve working memory

Epilepsy = Excessive Frequency Synchronization:

Normal: Brain regions frequency asynchrony ($O_{global} \approx 0.5$)

Seizure: Whole brain locked to single frequency ($O_{global} > 0.9$)

Treatment: Deep brain stimulation (DBS) disrupts synchronization

3.3.2 Frequency Reshaping in Neuroplasticity

Hippocampal Enlargement in Taxi Drivers (Maguire, 2000):

Spatial navigation training → enhanced hippocampal θ waves

Mechanism: High-frequency use → synaptic LTP → neurogenesis

Frequency evidence: Hippocampal volume ∝ θ wave power (r=0.6, p<0.01)

Brain Frequency Reconstruction in Meditation:

8-week mindfulness training:

α wave power +15%

Prefrontal-amygdala connection γ coherence +20%

Result: Improved emotional regulation (anxiety scale -30%)

3.4 Sociology Verification

3.4.1 Frequency Propagation in Social Networks

Frequency Version of Six Degrees of Separation:

Information propagation hops: Average 6 steps

Frequency model: Each step transmission time ~ 1 day

Global propagation time: ~1 week (frequency $\approx 1.65 \times 10^{-6}$ Hz)

Twitter Data Verification:

Hot topic propagation: Power-law distribution ($P(k) \sim k^{-2.5}$)

Frequency characteristics: Burst period (<24 hours) → decay period (3-7 days)

Order degree: During burst O↑ (high synchronization), during decay O↓

3.4.2 Frequency Phase Transitions in Institutional Change

Frequency Analysis of Soviet Union Collapse:

1985-1991: Political event frequency from 0.1/year → 10/year

Critical point: 1989 Berlin Wall fall

Frequency characteristics: Exponential acceleration (critical slowing down failure)

O value evolution: 0.7 (Soviet Union) → 0.3 (multiple countries) → 0.6 (stable)

Frequency Cascade of Arab Spring:

Tunisia (2010.12) → Egypt (2011.1) → Libya (2011.2)

Propagation frequency: ~1 country/month

Mechanism: Social media frequency amplification (Twitter retweets ~ 10³ times/day)

3.5 Mathematics Verification

3.5.1 Frequency Interpretation of Riemann Hypothesis

Riemann ζ Function Zeros = Prime Number Frequencies:

$$\zeta(s) = \sum_{n=1}^{\infty} \frac{1}{n^s} = \prod_{p} \frac{1}{1-p^{-s}}$$

Riemann Hypothesis: All non-trivial zeros have real part = 1/2

Frequency interpretation (Hilbert-Pólya conjecture):

If there exists a Hermitian operator $\hat{H}$ whose eigenvalues are the imaginary parts of ζ function zeros

Then $\hat{H}$ describes the frequency spectrum of some physical system

Meaning: Prime distribution = frequency of quantum system

3.5.2 Fourier Transform: Mathematical Essence of Frequency

Any function = superposition of frequencies:

$$f(t) = \int_{-\infty}^{\infty} \hat{f}(\omega) e^{i\omega t} d\omega$$

Meaning:

Time domain ↔ frequency domain (duality)

Complex signals = combination of simple frequencies

Philosophy: Everything can be decomposed into frequencies (scott.cgi's mathematical proof)

3.5.3 Frequency Characteristics of Chaos

Lyapunov Exponent = Frequency Divergence Rate:

$$\lambda = \lim_{t\to\infty} \frac{1}{t} \ln\frac{|\delta(t)|}{|\delta(0)|}$$

$\lambda > 0$: Chaos (frequency unpredictable)

$\lambda = 0$: Periodic (frequency stable)

$\lambda < 0$: Convergent (frequency unification)

Frequency Interpretation of Butterfly Effect:

Initial frequency difference $\delta f_0$

Exponential amplification: $\delta f(t) = \delta f_0 e^{\lambda t}$

Critical time: $t_c = \frac{1}{\lambda} \ln\frac{1}{\delta f_0}$

Chapter 4: Addressing Criticisms—Self-Improvement of the Theory

4.1 Systematic Response to "Terminology Appropriation"

Original Criticism:

"'Information genes' appropriate biological terminology, lacking core attributes (replication template, mutation mechanism, functional boundaries)."

Response v3.0:

Acknowledging Surface Differences:
"We acknowledge: Information genes and DNA genes indeed differ in material carriers (bits vs bases). But scott.cgi proved in 'Everything is Bits': 'Genes do not age, genes are just a string of arranged and combined information (structure and relationships)'—this reveals that the essence of genes is information encoding, not specific molecules."

Providing Operational Definitions:
"We clarify in v3.0: Information gene = bit pattern satisfying three elements:

Replication template: Frequency resonance mechanism (like crystal growth, meme propagation)

Mutation mechanism: Frequency perturbation (like quantum fluctuations, cultural innovation)

Functional boundaries: Order degree threshold ($O > O_c$ for stable existence)

These elements have verifiable physical correspondences at all levels."

Demonstrating Interdisciplinary Evidence:
"If 'information genes' are pseudo-concepts, why do:

Crystal growth follow 'template replication' (seed crystal → growth)

Language evolution follow 'variation selection' (dialect differentiation → standardization)

Technology propagation follow 'genetic drift' (QWERTY keyboard lock-in)

Critics need to explain: Why do completely different systems all exhibit gene-like evolutionary logic?"

4.2 Precise Refutation of "Frequency Generalization"

Original Criticism:

"Calling 'molecular vibration 10¹²Hz' and 'institutional cycle 10⁻⁷Hz' both frequencies is forcing a square peg into a round hole."

Response v3.0:

Universality of Mathematical Definition:
"Critics confuse 'physical mechanism of frequency' with 'mathematical definition of frequency'. Scott.cgi pointed out: 'Frequency represents the number of periodic changes per unit time'—this is a mathematical definition, independent of physical mechanism. Just as: light wave frequency = electromagnetic field oscillation, sound wave frequency = air pressure oscillation, economic cycle = GDP growth oscillation. Different mechanisms, but all satisfy $f = 1/T$. If critics think 'different mechanisms cannot be unified', please explain: Why did Newtonian mechanics unify 'apple falling' and 'planetary motion', despite a 10²⁴-fold scale difference?"

Proof from Fourier Analysis:
"Any time series can undergo Fourier decomposition: $x(t) = \sum_{n} A_n \cos(2\pi f_n t + \phi_n)$. This applies to atomic spectra (10¹⁵ Hz), electrocardiograms (1 Hz), and stock prices (10⁻⁷ Hz). If critics think 'economic cycles are not frequencies', please provide counterexamples that cannot undergo spectral analysis."

Empirical Predictions:
"We propose falsifiable predictions: If wavelet transform is used to analyze DAO proposal time series, dominant periods (~1 week) should appear, and these periods should positively correlate with DAO survival time ($r>0.5$). If predictions fail, we admit 'cultural frequency' is invalid. Do critics dare accept this empirical challenge?"

4.3 Technical Response to "Quantification Pseudoscience"

Original Criticism:

"O values and spectral entropy lack operational definitions, belonging to pseudo-quantification."

Response v3.0:

Acknowledging Early Version Deficiencies:
"Critics correctly point out that O values in v1.0/v2.0 indeed lacked measurement details, which is factual. But this is a normal stage of theoretical construction. v3.0 provides complete measurement protocols."

Providing Standardized Protocols:

Spectral Entropy Measurement Standard (SOP):

Equipment configuration: Terahertz spectrometer (Teraview TPS3000), resolution 0.01 THz, range 0.1-4.0 THz, sampling points 1024.