Light Rider SDK

The lightrider package provides quantum circuit simulation, stabilizer and surface-code experiments, IQM cloud jobs, quantum random numbers, attested entropy, and QRNG-driven synthetic data.

Current documentation: SDK 1.4.2

Installation

pip install lightrider
pip install "lightrider[pandas]"   # + pandas DataFrame support

Requires Python ≥ 3.9.

Live EMS entropy is included in the official lightrider package. Connect EntropyClient or EntropySource to https://ems.lightriderinc.com with a Light Rider API key.

Quickstart

from lightrider import Circuit, get_backend

# 1. Build a Bell-pair circuit
circ = Circuit(2)
circ.h(0)
circ.cx(0, 1)
circ.measure_all()

# 2. Run it on the local statevector simulator
job = get_backend("statevector").run(circ, shots=1000, seed=42)

# 3. Read the counts (Qiskit convention: clbit 0 is the rightmost character)
print(job.result().counts)   # {'00': 507, '11': 493}

Four core capabilities

• Quantum Circuits — build and run quantum circuits with local simulators or IQM cloud hardware.
• Quantum Error Correction — run circuit-level QEC experiments on surface, repetition, five-qubit, and color codes, with PyMatching decoding.
• Quantum Random Numbers — draw numpy-compatible randomness from real quantum entropy sources.
• Synthetic Data with Provenance — generate tabular synthetic data where every random draw is quantum and attributable.

Prefer a web UI over writing code? The Light Rider Cloud platform covers the same circuit submission through a dashboard, with self-serve API keys for scripting against it directly.