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Coming from Cirq

Tested with: Quanta SDK v0.8.1

Why Switch?

Feature Cirq Quanta
Install size ~300 MB ~5 MB (Python + NumPy only)
IBM Hardware ❌ (Google only) ✅ (direct REST API)
Dependencies 15+ packages 2 (numpy, python-dotenv)
Learning curve Moderate (Moment, Circuit, Simulator) Gentle (3 imports to start)
Gate count 60+ 25 (IBM Heron parity)
AI Integration ❌ ✅ (20 MCP tools for Claude/GPT)
QEC Basic Surface code + Color code + decoders

Side-by-Side: 12 Common Patterns

1. Create a Circuit

# ── Cirq ──
import cirq
q0, q1 = cirq.LineQubit.range(2)
circuit = cirq.Circuit([
    cirq.H(q0),
    cirq.CNOT(q0, q1),
    cirq.measure(q0, q1, key="result"),
])

# ── Quanta ──
from quanta import circuit, H, CX, measure
@circuit(qubits=2)
def bell(q):
    H(q[0])
    CX(q[0], q[1])
    return measure(q)

2. Run a Circuit

# ── Cirq ──
simulator = cirq.Simulator()
result = simulator.run(circuit, repetitions=1024)
print(result.histogram(key="result"))

# ── Quanta ──
from quanta import run
result = run(bell, shots=1024)
print(result.counts)  # {'00': 512, '11': 512}

3. Apply Rotation Gates

# ── Cirq ──
import numpy as np
circuit = cirq.Circuit([
    cirq.rx(np.pi/4)(q0),
    cirq.ry(np.pi/3)(q1),
    cirq.rz(np.pi/6)(q0),
])

# ── Quanta ──
RX(np.pi/4)(q[0])
RY(np.pi/3)(q[1])
RZ(np.pi/6)(q[0])

4. Noise Simulation

# ── Cirq ──
noise = cirq.ConstantQubitNoiseModel(cirq.depolarize(p=0.01))
noisy_sim = cirq.DensityMatrixSimulator(noise=noise)
result = noisy_sim.run(circuit, repetitions=1024)

# ── Quanta ──
from quanta.simulator.noise import NoiseModel, Depolarizing
noise = NoiseModel().add(Depolarizing(p=0.01))
result = run(bell, shots=1024, noise=noise)

5. Statevector Access

# ── Cirq ──
result = cirq.Simulator().simulate(circuit)
print(result.final_state_vector)

# ── Quanta ──
result = run(bell, shots=1)
print(result.statevector)  # Always available

6. Circuit Visualization

# ── Cirq ──
print(circuit)
# or
from cirq.contrib.svg import SVGCircuit
SVGCircuit(circuit)

# ── Quanta ──
from quanta.visualize import draw
draw(bell)  # ASCII diagram
# Or SVG:
from quanta.visualize_svg import draw_svg
draw_svg(bell, "circuit.html")

7. Custom Gate

# ── Cirq ──
class MyGate(cirq.Gate):
    def _num_qubits_(self): return 1
    def _unitary_(self):
        return np.array([[0, 1], [1, 0]])
circuit.append(MyGate()(q0))

# ── Quanta ──
from quanta import custom_gate
custom_gate("MyGate", np.array([[0, 1], [1, 0]]))
# Then use: MyGate(q[0])

# ── Cirq ──
# No built-in Grover — must implement manually
# (build oracle + diffuser circuits by hand)

# ── Quanta ──
from quanta.layer3.search import search
result = search(target=5, n_qubits=3)
print(result.found_value)  # 5

9. VQE

# ── Cirq ──
import cirq
from scipy.optimize import minimize
# Build ansatz manually, define cost function,
# run optimizer loop with cirq.Simulator()
# ~50 lines of boilerplate

# ── Quanta ──
from quanta.layer3.vqe import vqe
result = vqe([(-1.05, "ZZ"), (0.39, "XX")], n_qubits=2)
print(result.energy)

10. QAOA Optimization

# ── Cirq ──
# Manual implementation: cost unitaries, mixer unitaries,
# parameter optimization loop
# ~80 lines of code

# ── Quanta ──
from quanta.layer3.optimize import optimize
result = optimize(edges=[(0,1),(1,2),(2,3)], p=2)

11. QEC Surface Code

# ── Cirq ──
# Use cirq-google's experimental QEC module
# Limited to Google hardware topologies

# ── Quanta ──
from quanta.qec.surface_code import SurfaceCode
code = SurfaceCode(distance=3)
result = code.simulate_error_correction(error_rate=0.01)
print(f"Logical error rate: {result.logical_error_rate:.4%}")

12. Export to QASM

# ── Cirq ──
from cirq.qasm_output import QasmOutput
qasm = QasmOutput(circuit, (q0, q1))
print(str(qasm))

# ── Quanta ──
from quanta.export.qasm import to_qasm
qasm_str = to_qasm(bell)
# Both output OPENQASM 3.0

Key Differences

Cirq Quanta
cirq.LineQubit.range(n) @circuit(qubits=n)
cirq.H(q) H(q[0])
cirq.rx(angle)(q) RX(angle)(q[0])
cirq.CNOT(q0, q1) CX(q[0], q[1])
cirq.Simulator().run() run(circuit, shots=N)
cirq.DensityMatrixSimulator Built-in noise support
Google hardware only IBM Quantum + simulators

Cirq Concepts → Quanta

Cirq Concept Quanta Equivalent
Moment Automatic depth tracking
Circuit @circuit decorator
LineQubit / GridQubit q[i] (index-based)
Simulator run() (auto-selected)
cirq.measure() measure(q)
InsertStrategy Automatic DAG scheduling
noise.ConstantQubitNoiseModel NoiseModel().add(...)

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