Particle-semantic, cybernetic quantum programming

Most quantum programming languages describe computation as a sequence of gates. That’s a useful abstraction, but it hides what real devices actually do: physical subsystems interact, evolve over time under controlled dynamics, are disturbed by noise, and are steered by measurement and feedback.

This idea proposes a quantum programming language where the “atoms” of the language are closer to physics: subsystems/modes + interactions + time evolution + measurement. Instead of writing “apply these gates,” you describe which interactions exist, how you control them over time, and what you want the interaction to achieve.

On top of this, the language treats computation as controlled transfer of information ("meaning"). You define meaning as explicit contracts: invariants and constraints the program should respect (for example: "stay in this symmetry sector," "don't leak outside a subspace," "keep the error below eps," "finish within T microseconds," "only local couplings allowed"). The runtime model is naturally cybernetic: observe -> update -> act, optionally in a closed loop.

The goal is not to replace existing quantum ecosystems. The practical goal is to define a higher-level semantic layer that can compile into what hardware actually accepts: dynamic circuits, pulse programs, or analog Hamiltonian schedules, while checking contracts and reporting when constraints cannot be met.

Major points

Physics-native primitives

• Subsystems/modes (qubits, atoms on a lattice, fermion/boson modes, etc.)
• Interactions (couplings) and controlled dynamics over time
• Measurement with explicit post-measurement effects

Meaning as contracts

• "What must remain true" (symmetry, locality, leakage bound)
• "What must be bounded" (error budget, time budget, depth, energy/power)
• Contracts are checked/estimated by the compiler, not left implicit

Cybernetic control is first-class

• Programs can include feedback loops: measure -> decide -> apply next control
• This matches real workflows (calibration, stabilization, adaptive protocols)

Compiler = synthesis

• Not just "translate text to gates"
• Instead: choose/optimize control parameters and lower to an executable form
• Emit artifacts for different targets rather than locking into one platform

Illustrative code snippet

This is still hypothetical/pseudocode.

# Illustrative pseudocode for a particle/interaction-first quantum DSL.

from qsem import System, Contract, Program, compile_to

# 1) Define the physical system (atoms/modes on a lattice)
sys = System.neutral_atoms(lattice="square", size=4)

# 2) Declare contracts ("meaning" + constraints)
contract = Contract(
    locality="nearest_neighbors_only",
    preserve="excitation_parity",  # example invariant
    leakage_max=1e-4,              # stay inside intended subspace
    error_budget=1e-3,             # target fidelity / error tolerance
    time_max_us=5.0                # total runtime constraint
)

# 3) Declare the interaction model (Hamiltonian template)
#    Controls are symbolic knobs the compiler/runtime will realize as pulses/schedules.
H = sys.hamiltonian(
    detuning="Delta(t)",           # time-dependent detuning control
    drive="Omega(t)",              # time-dependent Rabi drive control
    interaction="V * blockade_edges"  # fixed interaction structure from geometry
)

# 4) Define a feedback policy: what to do after a measurement
def stabilize(obs):
    # obs is classical information extracted from measurement
    if obs["parity"] == "odd":
        return {"Delta(t)": "shift_up", "Omega(t)": "strong_drive"}
    return {"Delta(t)": "nominal", "Omega(t)": "nominal"}

# 5) Write the program as controlled evolution + measurement + feedback loop
p = Program(sys, contract=contract)

p.prepare("ground_state")

for _ in range(6):
    p.evolve(H, duration_us=0.6, controls={"Delta(t)": "nominal", "Omega(t)": "nominal"})
    obs = p.measure(readout="parity", on="all_sites")
    p.apply_controls(stabilize(obs))  # cybernetic step: observe -> act

# 6) Compile to an execution target (dynamic circuits, pulses, or analog schedule)
artifact = compile_to(p, target="openqasm3")  # or "pulser", "ahs", "qua", etc.
print(artifact)