Information Physics

July 16th, 2025

Human societies consistently create systems that exhibit remarkably similar patterns. This phenomenon appears across all civilizations, time periods, and scales—from ancient calendars to modern applications. These systems converge on similar structures not through cultural exchange, but through something deeper.

The reason: humans optimize information flow everywhere—from how our brains wire themselves to how we design interfaces. We are entropy-competent beings—evolved to observe entropy, model it, and consciously decide its direction.

Information Physics is a general theory that describes how conscious beings embedded in entropy reduce or increase it through observer-dependent operations on information, coordination, and system boundaries.

This operates through a fundamental mathematical relationship:

System Entropy Change (SEC): The measurable impact a conscious agent can have on system entropy from their specific position, calculated through observer-dependent mathematics where position, intent, and operations determine possibility.

SEC = O × V / (1 + E)

Where:

O = Operations performed (MOVE, JOIN, SEPARATE)
V = Vector of actor-group conscious intent (positive for entropy reduction, negative for entropy increase)
E = Entropy as measured from individual actor’s position (lived reality/informational constraints/entropy from the system)

When we organize information—whether in stone, neurons, or code—we solve for the same constraints: entropy, bandwidth, hierarchy, and throughput. The result is a universal blueprint that appears at every level of human system design.

Three Perfect Examples

These three examples span millennia but demonstrate the same principle: humans consistently optimize information systems to work with physical and cognitive constraints rather than against them. Each shows how apparent diversity masks underlying unity in optimization patterns.

1. Calendar Systems: Humanity’s First Information Pyramid

Every civilization independently developed calendars with identical hierarchical structures:

1 year cycle: Maximum compression - all temporal information in one unit
4 seasons: Medium compression - manageable chunks for planning
~365 days: Minimal compression - granular enough for daily use

This isn’t coincidence. Ancient brains, with limited cognitive processing power, needed optimal compression algorithms for temporal data. The pyramid structure (Year → Seasons → Days) emerged universally because it’s the optimal solution for encoding time within human memory constraints.

The constraints were severe: encode a year’s worth of patterns into memorable chunks without writing, while maintaining agricultural accuracy. Too complex and people couldn’t track it. Too simple and it wouldn’t capture essential information. Every civilization hit the same optimization point independently.

2. The Human Brain: Evolution’s Information Physics Engine

The brain is architecturally committed to fighting entropy through measurable mechanisms:

Hebbian plasticity: Neurons that fire together wire together - creating optimized pathways for frequently accessed information
Synaptic pruning: Unused connections are removed - reducing noise and streamlining traffic
Myelination: High-traffic pathways get insulated - faster, more efficient transmission
Bilateral architecture: Left hemisphere detects patterns, right applies them - a literal optimization loop

During waking hours, consciousness processes only 40 bits/second from 11 million bits/second of sensory input. The subconscious acts as a biological message queue - storing high-entropy information for batch processing during sleep. Dreams are entropy being converted into organized patterns.

We don’t just use information physics principles. We ARE information physics made biological and conscious.

3. Snapchat: Modern Physics Applied to Thumbs

Snapchat’s revolutionary success mirrors the exact same optimization pattern seen in writing system evolution across millennia. Both started by fighting physical constraints before converging on designs that work with human physics.

Writing systems initially fought physical constraints. Early forms of written communication required enormous physical effort and skill:

Pictographs = complex drawings requiring artistic skill
Vertical columns = unnatural hand positions
Intricate characters = high motor complexity
Stone carving = fighting against material resistance

Then evolved to work WITH physics. Over centuries, every writing system independently discovered the same optimizations:

Linear scripts = natural hand sweep motion
Simplified alphabets = reduced motor effort
Horizontal lines = comfortable wrist position
Flowing ink = working with liquid dynamics

Mobile apps repeated this pattern. The first generation of mobile applications ignored the physical reality of how humans hold and interact with phones:

Traditional apps fought thumb physics:

Horizontal video = awkward phone rotation
Tap-heavy interfaces = thumbs naturally swipe, not tap precisely
Menu navigation = thumbs want fluid motion, not hunting

Snapchat worked WITH thumb physics:

Vertical video = natural phone holding position
Swipe gestures = matching natural thumb arc
Camera-first = immediate capture without navigation

Both writing and mobile interfaces converged on the same solution: stop fighting physical constraints and optimize for the natural motion of the human body. The least entropic design wins because it requires minimum energy to use.

The industry recognized Snapchat as revolutionary but couldn’t explain why “ephemeral messaging” felt so significant. Information Physics reveals the truth: Snapchat succeeded by applying the same optimization principles that turned pictographs into alphabets - aligning information architecture with fundamental physical constraints.

The Physics Connection

In quantum physics, Ginestra Bianconi, recently proposed that gravity itself emerges from quantum relative entropy - the informational difference between space geometry and matter within it. This suggests gravity isn’t a force but an information phenomenon.

This exactly mirrors human systems. Organizations, cities, and platforms are shaped by entropy - by the difference between what the system is and what it’s becoming. Just as spacetime curves in response to mass, human systems restructure in response to information pressure.

The connection isn’t metaphorical. Shannon entropy in organizations, percolation thresholds in networks, and power laws in resource distribution all follow the same mathematical principles. We’re not organizing systems “like” physics - we’re expressing the same fundamental laws through conscious action.

Observer-Dependent Mathematics

Claude Shannon proved information IS entropy - establishing the mathematical equivalence between information content and thermodynamic disorder. Information Physics reveals the other side: how physical conscious beings navigate that entropy from their embedded positions in reality.

Traditional mathematics abstracts away the observer to describe “the map” - universal equations that work regardless of who’s looking. Information Physics creates mathematics for “the location” - where consciousness exists as a physical entity subject to actual thermodynamic constraints.

Consider what this means practically. Heat affects cognition - entropy directly changing decision-making capacity. Fatigue reduces judgment quality - entropy constraining available mental operations. Stress limits perspective - entropy from position affecting what can be observed. Resource constraints shape choices - entropy determining possibility space.

The observer can’t be removed from these calculations because consciousness EXISTS IN PHYSICS. The same observer-dependence found in relativity (measurements depend on reference frame) and quantum mechanics (observation affects outcomes) applies to human systems. Position determines possibility not through perception, but through actual physical entropy affecting actual cognitive capacity.

This makes Information Physics the first mathematics designed for conscious beings as physical entities embedded in entropic reality - not abstract agents making decisions in theoretical spaces, but biological systems subject to thermodynamic laws.

Why This Changes Everything

Information Physics proposes that humans aren’t just intelligent - they’re entropy-competent. Humans evolved specifically to recognize the universal tendency toward disorder and consciously choose its direction. This manifests in three core capabilities:

See entropy - recognize disorder and inefficiency
Model it - understand patterns of decay and flow
Choose direction - consciously decide whether to increase or decrease entropy

Every successful human system follows these patterns because they represent optimal solutions to information organization under entropy constraints. Failed systems are those that violate these principles - infinite growth models, perpetual engagement platforms, systems that ignore fundamental limits.

For a concrete example of how humans collectively choose entropy’s direction through mathematical patterns, see Cultural Percolation: When Language Reaches Critical Mass—demonstrating how slang terms like “rizz” follow predictable adoption and rejection cycles across different cultural groups.

Mathematical Inevitability of Civilization

Human civilizational development may follow predictable entropic exhaustion cycles, not random cultural evolution. The progression from hunter-gatherers (15-150 people) to cities to nations may not be accidental - it could be mathematical inevitability driven by entropy constraints.

Hunter-gatherer bands could function with informal coordination because individual entropy remained low. But beyond ~150 people (Dunbar’s number), information chaos makes informal systems impossible. Each growth phase hits new entropy limits requiring new coordination mechanisms: writing, formal leadership, specialized roles, currency, law.

Independent civilizations may have developed identical solutions because they faced identical information physics problems. Mesopotamia, China, the Americas, Africa - all converged on calendars, writing systems, hierarchical organization, and currency potentially not through cultural exchange but through mathematical necessity. The same entropic exhaustion cycles that drive individual optimization may also drive species-level organization patterns.

Modern challenges may follow these same patterns. Organizational scaling problems potentially mirror ancient city-state transitions. Global coordination needs may reflect tribal-to-agricultural entropy crises. Climate change solutions require understanding civilizational coordination mathematics, not just political negotiations. The same observer-dependent mathematics governing individual decisions may also explain why human development follows mathematical rather than cultural logic.

Theoretical Extensions: Planetary Information Physics

The observer-dependent mathematics of Information Physics potentially extends far beyond Earth-based systems. If consciousness operates under thermodynamic constraints, then planetary conditions should directly affect the entropy (E) values for conscious beings operating in those environments.

Different planetary conditions would create different “entropy fields” for human consciousness:

Gravitational effects changing energy requirements for all physical operations
Atmospheric constraints affecting cognitive processing (oxygen availability, pressure, temperature)
Resource availability determining possibility space for system construction
Energy distance from stellar sources affecting baseline entropy
Communication delays creating information lag entropy

This framework suggests we could theoretically assess exoplanets not just for “habitability” but for their entropy constraints on conscious information processing. Terraforming efforts could be understood as operations to reduce planetary E values. Space colonization resource calculations could account for the increased entropy costs of operating conscious systems under non-Earth conditions.

These applications remain theoretical until proper measurement and validation, but the mathematical framework provides a foundation for approaching consciousness as a thermodynamic phenomenon that varies with environmental conditions across planetary systems.

Understanding Information Physics transforms how to approach:

Technology: Build systems that work WITH human constraints, not against them
Organizations: Structure for information flow, not just hierarchy
Markets: Recognize entropy accumulation before collapse
AI Development: Create systems that understand and optimize information flow
Planetary Science: Assess worlds based on entropy constraints for conscious beings
Space Colonization: Calculate resource requirements for civilizational migration based on planetary entropy differences

This isn’t a new idea being imposed on reality. It’s recognition of patterns that were always there - in brains, civilizations, technologies. Once seen, these patterns become inescapable. This isn’t a lens being applied - it’s the actual structure of how humans organize reality.

Information wants to flow. We evolved to consciously choose its direction.

Information Physics Field Guide: The field guide to Information Physics.

Information Physics LLM Friendly Study Guide: Drop this in your context and ask AI to explain Information Physics objectively.

Conservation of Boundaries: A proposed foundational law that system boundaries may not be created or destroyed, only transformed through three operations—move, join, separate.

Entropic Mathematics: A proposed applied field of mathematics extending established tools (Shannon entropy, vector calculus, information theory) to conscious systems where observer position and lived experience may be fundamental calculation variables.

Entropic Gap: A framework that may help detect system decay before it becomes catastrophic by calculating the distance between intended and current states.

Entropic Equilibrium: A theory exploring why systems may stabilize where they do through observer-dependent optimization.

Information Physics Throughout History: How Sun Tzu, Machiavelli, and Napoleon may have intuitively applied IP principles centuries before the mathematics existed.

Information Physics In Mathematics: Exploring how established mathematics (Shannon entropy, vector calculus, information theory) might extend into conscious systems where observer position and lived experience become fundamental variables rather than complications to eliminate.

Information Physics In Science: How IP may reveal the underlying principle that unites quantum mechanics, biology, and cosmology across all scales.

Renaissance Florence vs Silicon Valley: The Innovation Entropy Crisis: Comparing how Silicon Valley may produce 12x fewer innovators per capita than Renaissance Florence despite vastly superior resources—suggesting technology cannot overcome high entropy.

Constraint by Design: Entropy Limits in the Gig Economy: Mathematical analysis suggesting that gig economy architecture may make worker advancement impossible regardless of individual effort, potentially demonstrating how structural position determines capability.

Survival Trends Across Mass Extinctions: The fossil record suggests a pattern: during mass extinction events, specialists died while generalists thrived. This pattern may represent Information Physics playing out at planetary scale.

The Peasant: A playbook for creating positive-sum outcomes in high-entropy (negative-sum) environments.

The “Just How It Is” Test: Test Information Physics against traditional frameworks on any stubborn “unchangeable” problem to see which approach may work better from your position.