ryd-gate

Simulation and optimization of Rydberg-atom entangling gates for neutral-atom quantum computing.

This package provides tools for modelling two-photon Rydberg excitation in 87Rb, including hyperfine structure, Rydberg blockade, spontaneous decay, and AC Stark shifts. It uses a SciPy-based Schrodinger-equation solver with pulse-shape optimisation routines for time-optimal (TO) and amplitude-robust (AR) CZ gate protocols.

Features

• 7-level Schrodinger solver in a 49-dimensional two-atom Hilbert space
• Modular architecture: core/, protocols/, solvers/, analysis/ subpackages
• Strategy pattern: TO and AR protocols share a unified ODE solver
• Full error model including spontaneous decay (Rydberg + intermediate), dephasing, and position errors
• Monte Carlo noise analysis for Rydberg dephasing and 3D position fluctuations
• Local addressing simulation with 784nm pinning laser and sweep protocols
• Pulse optimization for TO and AR gate protocols

Installation

# Using uv (recommended)
uv pip install -e ".[dev]"

# Using pip
pip install -e ".[dev]"

Quickstart

from ryd_gate import CZGateSimulator

sim = CZGateSimulator(param_set='our', strategy='TO')

# Time-optimal pulse parameters: [A, w/Omega_eff, phi_0, delta/Omega_eff, theta, T/T_scale]
X_TO = [0.1122, 1.0431, -0.72565603, 0.0, 0.452, 1.219096]
infidelity = sim.gate_fidelity(X_TO)
print(f"Gate infidelity: {infidelity:.2e}")

Direct module imports (recommended for new code)

from ryd_gate.core.atomic_system import create_atomic_system
from ryd_gate.protocols.gate_cz_to import TOProtocol
from ryd_gate.solvers.schrodinger import solve_gate
from ryd_gate.analysis.gate_metrics import average_gate_infidelity

system = create_atomic_system(param_set="our")
protocol = TOProtocol()
infidelity = average_gate_infidelity(system, protocol, X_TO)

Package Layout

src/ryd_gate/
  core/
    atomic_system.py       # AtomicSystem dataclass, Hamiltonian builders, branching ratios
  protocols/
    base.py                # Protocol ABC (CZ gates) + SweepProtocol ABC (addressing)
    gate_cz_to.py          # TOProtocol (cosine phase modulation, 6 params)
    gate_cz_ar.py          # ARProtocol (dual-sine phase modulation, 8 params)
    local_sweep.py         # SweepAddressingProtocol (linear sweep + local pinning)
  solvers/
    schrodinger.py         # solve_gate() for CZ gates + evolve() for generic H(t)
    monte_carlo.py         # MonteCarloEngine (CZ) + AddressingMCEngine (local addressing)
  analysis/
    gate_metrics.py        # average_gate_infidelity, error_budget, state_infidelity
    addressing_metrics.py  # AddressingEvaluator (pinning error, crosstalk, leakage)
  ideal_cz.py             # Backward-compatible CZGateSimulator facade
  blackman.py             # Blackman window pulse shaping

Physical Model

The solver models two 87Rb atoms with:

Parameter	Value	Description
n	70	Rydberg principal quantum number
Omega_eff	2pi x 7 MHz	Effective two-photon Rabi frequency
Delta	2pi x 9.1 GHz	Intermediate state detuning
d	3 um	Interatomic distance
C6	2pi x 874 GHz um^6	van der Waals coefficient

Testing

# Run fast tests only (default, ~1 second)
uv run pytest

# Run all tests including slow ODE-based tests (~15 min)
uv run pytest -m ""

# Run only slow tests
uv run pytest -m slow

# Run with coverage
uv run pytest -m "" --cov=ryd_gate --cov-report=html

Test Files

Test File	Description
test_ideal_cz.py	Schrodinger solver: initialization, Hamiltonian, fidelity, Monte Carlo
test_cz_gate_phase.py	CZ gate phase and SSS state verification
test_blackman.py	Blackman pulse shaping functions
test_init.py	Package-level imports and exports

Documentation

Document	Description
Getting Started	Installation and basic usage
Schrodinger Solver	7-level model theory and API
Error Budget	Error decomposition methodology
Validation	Test suite documentation

Scripts

Script	Description
scripts/calibration_sensitivity.py	Calibration sensitivity analysis
scripts/error_deterministic.py	Deterministic error budget calculation
scripts/error_monte_carlo.py	Monte Carlo error analysis
scripts/generate_mc_data.py	Generate Monte Carlo datasets
scripts/generate_si_tables.py	Generate SI tables for the paper
scripts/opt_bright.py	Optimize bright-detuning parameters
scripts/opt_dark.py	Optimize dark-detuning parameters
scripts/plot_mid_pop.py	Plot intermediate state populations
scripts/plot_population_evolution_sch.py	Plot population evolution
scripts/verify_cz_dark.py	Verify CZ gate with dark-detuning parameters
scripts/run_addressing_sim.py	Local addressing pinning error heatmap

References

• Evered et al., "High-fidelity parallel entangling gates on a neutral-atom quantum computer", Nature 622, 268 (2023).
• Ma et al., "Benchmarking and fidelity response theory of high-fidelity Rydberg entangling gates", PRX Quantum 6, 010331 (2025).

License

MIT