Quickstart¶

This page runs three minimal workflows end-to-end plus a circuit equivalence check. Install the package first (installation), then copy the cells below.

Every example in this guide uses Simulator(show_progress=False) so progress bars do not clutter the built documentation.

1. Analog simulation¶

Tensor-network time evolution on an MPS. Attach a NoiseModel for open-system TJM trajectories; without noise, the simulator performs a single unitary trajectory regardless of num_traj:

from mqt.yaqs import AnalogSimParams, Hamiltonian, Observable, Simulator, State

L = 3
state = State(L, initial="zeros")
hamiltonian = Hamiltonian.ising(L, J=1.0, g=0.5)

params = AnalogSimParams(
    observables=[Observable("z", sites=0)],
    elapsed_time=0.5,
    dt=0.1,
    preset="fast",
    num_traj=8,
)

sim = Simulator(show_progress=False)
result = sim.run(state, hamiltonian, params)
print(f"⟨Z₀⟩(t) = {result.expectation_values[0]}")

⟨Z₀⟩(t) = [1.         0.99502079 0.98033073 0.95665832 0.92517106 0.88740864]

2. Digital circuit simulation¶

Noisy or noise-free evolution through a Qiskit circuit on an MPS:

from qiskit.circuit import QuantumCircuit

from mqt.yaqs import Observable, StrongSimParams

qc = QuantumCircuit(3)
qc.h(0)
qc.cx(0, 1)
qc.cx(1, 2)

circuit_state = State(3, initial="zeros")
circuit_params = StrongSimParams(
    observables=[Observable("z", sites=i) for i in range(3)],
    preset="fast",
    num_traj=8,
)

circuit_result = sim.run(circuit_state, qc, circuit_params)
print("Final ⟨Zᵢ⟩:", [float(v[0]) for v in circuit_result.expectation_values])

Final ⟨Zᵢ⟩: [0.0, 0.0, 0.0]

/tmp/ipykernel_2700/1385568565.py:18: ComplexWarning: Casting complex values to real discards the imaginary part
  print("Final ⟨Zᵢ⟩:", [float(v[0]) for v in circuit_result.expectation_values])

3. Equivalence checking¶

Verify that two circuits implement the same unitary (up to global phase) with EquivalenceChecker:

from mqt.yaqs import EquivalenceChecker
from qiskit.circuit import QuantumCircuit

def bell_prep() -> QuantumCircuit:
    qc = QuantumCircuit(2)
    qc.h(0)
    qc.cx(0, 1)
    return qc

# Original vs. transpiled-style rewrite (same unitary on two qubits)
original = bell_prep()
rewritten = QuantumCircuit(2)
rewritten.h(0)
rewritten.cx(0, 1)

checker = EquivalenceChecker(representation="mpo", threshold=1e-6)
equiv = checker.check(original, rewritten)
print(f"Equivalent: {equiv['equivalent']}  (fidelity {equiv['fidelity']:.6f})")

Equivalent: True  (fidelity 1.000000)

For larger circuits, compiler passes, and OpenQASM inputs, see Equivalence Checking.

4. Where to go next¶

Goal	Start here
Open-system dynamics, noise, time grids	Noisy Analog Simulation
Bell-curve (Gaussian) noise strengths	Realistic Noise Models
Circuit observables, mid-circuit sampling, OpenQASM	Noisy Circuit Simulation
Accuracy presets and truncation knobs	Configuring Simulation Parameters
Check two circuits for equivalence	Equivalence Checking

Quickstart¶

1. Analog simulation¶

2. Digital circuit simulation¶

3. Equivalence checking¶

4. Where to go next¶

Related topics¶