System Status: Online // RIT Framework v2.0
THE BIG IDEA

What If Time Is Computation?

This framework proposes a radical idea: time isn't a mysterious backdrop to the universe—it's the rate at which physical systems process information.

Think about a clock. What does it actually do? It ticks. Each tick is a state change—a transition from one configuration to another. That's all time is: counting distinguishable changes.

1
Clocks Count Changes

Every clock—atomic, pendulum, or biological—works by transitioning between distinct states. No transitions = no time.

2
Physics Limits Speed

Quantum mechanics says there's a maximum rate you can compute: more energy = faster ticking (Margolus-Levitin bound).

3
Information Has Weight

Information requires energy to exist (Bekenstein bound). Concentrated information creates gravitational potential.

Time Slows Near Mass

Dense information = slower computation = slower time. This is time dilation—not postulated, but derived.

See Time Dilation In Action
1.000
Time flows at normal rate (no information density)
Empty Space Near Black Hole
The Core Equation:
dτ/dt = √(1 − λS)
Proper time rate = √(1 − 4 × information density)
What This Framework Does
  • Explains gravitational time dilation

    Clocks run slower near massive objects because information is denser there

  • Matches GPS observations

    Predicts 38.4 μs/day drift, observed: 38.6 μs/day

  • Makes testable predictions

    High-energy light should arrive slightly later from distant sources

HOW IT WORKS

The Chain of Reasoning

This isn't speculation—it follows from established physics. Here's the logical chain:

Axiom 1
Quantum Mechanics

Systems evolve via the Schrödinger equation. This is the most tested theory in physics.

Status: Empirically verified
Axiom 2
Margolus-Levitin Bound

There's a minimum time to flip between distinguishable states: τ ≥ πℏ/2E. Energy caps computation speed.

Status: Proven theorem
Axiom 3
Observers Are Physical

Clocks, brains, measurement devices—all are made of atoms with finite information capacity.

Status: Operational assumption
Axiom 4
Time = Transitions

Proper time is the count of distinguishable state changes. This is what "experiencing time" means.

Status: Definitional
Axiom 5
Holographic Principle

Maximum information in a region is bounded by its surface area: I_max = A/4ℓ_P²

Status: From black hole thermodynamics
Axiom 6
Lorentz Invariance

Locally, physics respects special relativity. The speed of light is the universal speed limit.

Status: Tested to 10⁻²³ precision

The Derivation (Simplified)

Information has mass-energy (Bekenstein bound)
E = Iℏc/(2πR)
Mass-energy creates gravitational potential
Φ = −GM/R
Gravitational potential slows clocks (weak-field redshift)
dτ/dt = √(1 + 2Φ/c²)
Therefore: information density slows time
dτ/dt = √(1 − 4S)
where S = ρ_I · ℓ_P³ (dimensionless information density)

Why λ = 4?

At a black hole horizon, two things happen simultaneously:

Time stops: dτ/dt → 0
📊
Information saturates: S = 1/4

Setting √(1 − λ × 1/4) = 0 gives λ = 4. The coupling constant is calibrated, not fitted.

TRY IT YOURSELF

Photon Arrival Time Calculator

If spacetime has discrete microstructure, high-energy photons should travel slightly slower than low-energy ones. Adjust the parameters below to calculate the predicted time delay.

What You're Calculating

Imagine a gamma-ray burst billions of light-years away. Two photons leave at the same instant—one high-energy (TeV), one low-energy (GeV). If spacetime is discrete at scale ℓ_I, the high-energy photon probes that structure more and travels slightly slower. Over cosmic distances, this creates a measurable time delay.

Simulation Parameters

Distance to Source
1.0 Gpc (billions of light-years)
Discreteness Scale (log₁₀ ℓ_I/ℓ_P)
6.0
0 = Planck length, 6 = million × Planck length
High Energy Photon
1.0 TeV
Low Energy Photon
100 GeV
Predicted Time Delay
0.000 ms
The high-energy photon arrives this much later than the low-energy photon.
Time delay vs. discreteness scale (current value shown as orange dot)
THE TEST

CTA Monte Carlo Simulator

2027: The Cherenkov Telescope Array (CTA) will have the precision to detect millisecond-scale delays in gamma-ray bursts from across the universe. This simulator models what CTA might observe.

If delay detected

Spacetime is discrete at ℓ_I ~ 10⁻²⁸ m. Information leaves fingerprints on light.

If no delay

ℓ_I pushed below 10⁻²⁸ m. Framework survives; this specific scale constrained.

If opposite sign

High-energy faster = this dispersion model ruled out. Different microphysics needed.

Simulator Config
Telescope Scenario
Photons per trial: 2000
Monte Carlo Trials: 200
Timing Jitter (ms): 1.0
Detector timing uncertainty
IDLE
Analysis Results

The simulator generates fake gamma-ray bursts with the predicted delay, adds realistic noise, then tries to recover the delay. A "3σ detection" means we can distinguish the delay from noise with 99.7% confidence.

Recovered Delay
-
What the analysis measured
True Delay
-
What we put in
Significance (σ)
-
Statistical confidence
3σ Detection Rate
-
How often we'd detect it
Photon arrival times: Low energy High energy (delayed)
LEARN MORE
[ FULL PAPER ] [ SOURCE CODE ]
Scientific Status: This is a coherent theoretical framework with explicit assumptions, not established physics. The coupling constant λ = 4 is calibrated by horizon saturation. The dispersion prediction is model-dependent. The framework invites scrutiny and experimental test.