GitHub - gvelesandro/constructor-theory-simulator

3 min read Original article ↗

A Python implementation of David Deutsch’s Constructor Theory framework, exposing key concepts—from simple Tasks and branching substrates to quantum-gravity and electromagnetism—entirely in code. Includes a “universal constructor” that can bootstrap itself from a list of Tasks, demonstrating self-replication and the power of Constructor Theory.

“A demonstration of how constructor theory could be explored in code, not a high-precision physics engine. For the formal definitions, see David Deutsch and Chiara Marletto’s recent paper “Constructor Theory of Time” (May 13, 2025).

🚀 Features

  • Core framework: Attributes, Substrates, Tasks, Constructors

  • Irreversible & quantum tasks: Many-worlds branching, decoherence guards

  • Timers & Clocks: Simulate proper-time, special/general relativity corrections

  • Fungibility & SwapConstructor: Free exchange of identical substrates

  • ASCII visualizer: ascii_branch() for quick text-based branch inspection

  • Continuous dynamics: 1D & 2D substrates, DynamicsTask, RK4 & symplectic integrators

  • Coupling tasks:

    • Gravitational two-body (1D)
    • Coulomb coupling (1D)
    • Lorentz-force (2D) for charged particles in a magnetic field

  • Quantum-Gravity & Electromagnetism: Graviton & Photon emission/absorption Tasks

  • UniversalConstructor: Bootstraps any list of Tasks into a working Constructor

  • Pluggable Backend Architecture: Modular task ontologies for different physics domains

  • Hydrogen atom constructors: Excitation, deexcitation and two-atom collisions

  • Demo scripts:

    • demo.py – shows every constructor in action
    • bootstrap_demo.py – elegant self-replication via the UniversalConstructor
    • backend_demo.py – demonstrates the pluggable backend system

🛠 Getting Started

Prerequisites

  • Python 3.8+
  • (Optional) matplotlib for phase-space plots

Installation

git clone https://github.com/gvelesandro/constructor-theory-simulator.git
cd constructor-theory-simulator

Run Unit Tests

python -m unittest ct_tests.py

Run Demos

python demo.py
python bootstrap_demo.py
python backend_demo.py

Note: If you don’t have matplotlib, the demos will still run; plots will simply be skipped with a warning.

🎯 Usage Example

from ct_framework import (
    Attribute, Substrate,
    PhotonEmissionTask, PhotonAbsorptionTask,
    UniversalConstructor, ascii_branch
)

# 1) Define your “program” of photon Tasks
ELEC = Attribute("charge_site")
prog = [
    PhotonEmissionTask(ELEC, emission_energy=5.0, carry_residual=False),
    PhotonAbsorptionTask(ELEC, absorption_energy=5.0)
]

# 2) Build a Constructor at runtime
uc      = UniversalConstructor()
em_cons = uc.build(prog)

# 3) Emit a photon
atom = Substrate("A", ELEC, energy=20.0)
branches = em_cons.perform(atom)
print(ascii_branch(branches))
# => * charge_site (A)
#    * photon      (A)

# 4) Absorb it back
photon   = next(w for w in branches if w.attr.label=="photon")
restored = em_cons.perform(photon)[0]
print(restored)
# => A:charge_site(E=20.0,Q=0,t=2,F=charge_site)

🔌 Pluggable Backend System

The framework now supports a modular backend architecture for different task ontologies:

from ct_framework import (
    UniversalConstructor, Substrate, Attribute,
    ElectromagnetismBackend, QuantumGravityBackend
)

# 1) Use individual physics backends
uc = UniversalConstructor()

# Pure electromagnetism
em_constructor = uc.build_from_backends(["electromagnetism"])

# Pure quantum gravity  
qg_constructor = uc.build_from_backends(["quantum_gravity"])

# 2) Combine multiple backends
unified_constructor = uc.build_from_backends([
    "electromagnetism", 
    "quantum_gravity", 
    "hydrogen_atoms"
])

# 3) Create custom backends
class CustomPhysicsBackend:
    def get_tasks(self):
        return [/* your custom tasks */]
    
    def get_name(self):
        return "custom_physics"

# 4) Available built-in backends:
# - "electromagnetism": photon emission/absorption
# - "quantum_gravity": graviton emission/absorption  
# - "hydrogen_atoms": H excitation/deexcitation
# - "continuous_dynamics": integrator tasks

Run python backend_demo.py to see the full backend system in action!

🤝 Contributing

This is intended as an educational resource and proof-of-concept. Contributions are very welcome! Please:

  • File issues for missing tasks or physics modules
  • Submit pull requests for new constructors (e.g. chemical reactions, friction)
  • Improve documentation or add more demos

📜 License

Released under the MIT License.

🙏 Acknowledgments

  • Inspired by David Deutsch and Chiara Marletto’s work in Constructor Theory and their May 13, 2025 paper “Constructor Theory of Time.”
  • Thanks to the quantum-foundations community for feedback and discussion.