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THE CONSCIOUSNESS ATLAS
Read. Experiment. Follow the evidence.

ConsciousnessLearn · Explore · Joseph Anady

CONSCIOUSNESS DYNAMICS · dΦ/dt

This relation defines dΦ/dt in the source section “CONSCIOUSNESS DYNAMICS · dΦ/dt”. Uses a derivative or gradient to describe a rate of change or a direction of variation. Its interpretation depends on the source’s stated variables and conditions; this record does not…

Implementation mathematicsSource recovered; runtime not executed
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gh-eq-ee7e7288bf48bd00source-comment-equation
dΦ/dt=α(Φtarget−Φ)+β∇2Φ+γξ(t)dΦ/dt = α(Φ_target - Φ) + β∇²Φ + γξ(t)

Read the equation

This relation defines dΦ/dt in the source section “CONSCIOUSNESS DYNAMICS · dΦ/dt”. Uses a derivative or gradient to describe a rate of change or a direction of variation. Its interpretation depends on the source’s stated variables and conditions; this record does not assign an unprovided physical or cognitive meaning to them.

Terms & definitions

The recovered passage does not supply a separate symbol table. Read the source context for the notation used in this version; familiar letters may carry different meanings in other builds.

How it works

  1. Read dΦ/dt as the quantity being defined or updated by this relation.

  2. Uses a derivative or gradient to describe a rate of change or a direction of variation.

  3. Use this version’s variable definitions and update order. The same symbol may be assigned a different meaning in another build.

Assumptions & limits

  • This source expression was recovered from the pinned code revision. Its presence does not establish that the associated program was built, run, or scientifically validated.

Original context

Read the surrounding source passage
        float u2 = (rng_state >> 16) / 65536.0f;

        float z = std::sqrt(-2.0f * std::log(u1)) * std::cos(2.0f * 3.14159265f * u2);
        return z * std::sqrt(dt);
    }

    // Evolve consciousness by one time step
    // dΦ/dt = α(Φ_target - Φ) + β∇²Φ + γξ(t)
    float step() {
        float dW = wiener_increment();

        // Drift term: attraction to target
        float drift = alpha * (phi_target - phi);

        // Diffusion term (approximated as negative feedback on velocity)
        float diffusion = -beta * phi_velocity;

        // Noise term
Exact original notation
dΦ/dt = α(Φ_target - Φ) + β∇²Φ + γξ(t)

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Sources & provenance

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