What is Marqov?

Marqov is an orchestration engine for hybrid quantum-classical workflows. Write quantum algorithms using Qiskit, Cirq, PennyLane, OpenQASM, or Marqov’s native SDK, and Marqov handles parallelization, multi-backend execution, and real-time monitoring automatically.

Key Features

Automatic parallelization. Decorate your functions with @task and @workflow, and Marqov analyzes the dependency graph to run independent tasks concurrently. No manual threading or async coordination needed.

from marqov import task, workflow
 
@task
def measure_zz(circuit):
    return device.run(circuit, shots=1000)
 
@task
def measure_zi(circuit):
    return device.run(circuit, shots=1000)
 
@workflow
def energy_step(theta):
    circuit = build_ansatz(theta)
    zz = measure_zz(circuit)  # These run in parallel
    zi = measure_zi(circuit)  # automatically
    return compute_energy(zz, zi)

Multi-backend execution. Run the same code on local simulators, AWS Braket (SV1, DM1, IonQ, Rigetti), or Azure Quantum — by changing one parameter.

Temporal-backed durability. Workflows execute on Temporal , giving you automatic retries, timeout handling, and a full execution audit trail.

Real-time execution dashboard. Every workflow run shows a Gantt chart of task execution, summary cards for key results, and per-task timing — all updating live in the browser.

Backend-agnostic circuits. Marqov’s Circuit class converts to Qiskit, Braket, Cirq, PennyLane, or OpenQASM with a single method call.

Who is Marqov for?

• Quantum algorithm researchers who want to focus on algorithms, not infrastructure
• Teams running variational algorithms (VQE, QAOA) across multiple backends
• Organizations that need reproducible, auditable quantum computations

What’s next?

• Quickstart — Write and run your first script in 5 minutes
• Key Concepts — Understand tasks, workflows, and backends