ADVANCED QCVV

State-of-the-art QCVV.
Without the state-of-the-art effort.

Research-grade quantum characterization, packaged as routine experiments. The physics gets harder. The experiment does not.

Close-up of a quantum processor.

THE BASICS ARE THE START

Every control stack can measure coherence.
Pelagic starts where the basics end.

T₁, T₂ and echo remain essential. But modern processors need tools that expose coherent errors, gate processes, circuit performance and multi-qubit correlations.

Combined T1, T2 and echo characterization
Combined T₁, T₂* and T₂ echo coherence measurements.

01 / TOMOGRAPHY

Reconstruct the operation.
Not just a single number.

Choose the operation. Pelagic handles the experiment sequence and acquisition without turning tomography into a custom software project.

Process tomography circuit

The same experiment continues directly into reconstruction, giving you the process rather than reducing the result to a single benchmark number.

Process tomography reconstructed data
Reconstructed process tomography response.
  1. SELECT QUBITS
  2. CONFIGURE
  3. RUN
  4. ANALYZE

02 / ERROR DIAGNOSIS

Resolve the errors
that averages hide.

Robust phase estimation and deterministic benchmarking expose repeatable coherent error structure instead of averaging it away into a single fidelity number.

Robust phase estimation result
Robust phase-estimation response resolving coherent phase error.

Robust phase estimation turns small phase offsets into a directly resolvable signal, making coherent calibration errors easier to isolate.

Deterministic benchmarking then exposes repeatable coherent error structure instead of averaging it away into a single fidelity number.

Deterministic benchmarking result
Deterministic benchmarking response revealing repeatable coherent error structure.

03 / BENCHMARKING

From gates to circuits.
Benchmark what matters.

Cycle benchmarking and interleaved CRB make gate performance measurable in context. The same Pelagic experiment pattern carries from one protocol to the next.

Cycle benchmarking result
Cycle-benchmarking result for the repeated operation.

Cycle benchmarking establishes the repeated operation. Interleaved CRB then resolves the contribution of a target operation relative to that reference.

Interleaved cycle randomized benchmarking result
Interleaved cycle randomized benchmarking of the target operation.

04 / CROSS-ENTROPY BENCHMARKING

Get Pelagic today.
Run XEB tomorrow.

The physics gets harder. The experiment does not. Pelagic builds and runs the circuit inside the same experiment framework.

Cross-entropy benchmarking circuit

Acquisition and analysis follow in the same workflow, turning the circuit-level experiment into an immediately usable result.

Cross-entropy benchmarking data
Cross-entropy benchmarking result from the measured circuit ensemble.

05 / MULTI-QUBIT VALIDATION

Scale beyond
isolated gates.

Weight-2 and weight-4 stabilizers bring correlated multi-qubit measurements into the same familiar Pelagic experiment workflow.

WEIGHT-2 STABILIZER

Start with the stabilizer sequence itself.

Weight-2 stabilizer circuit

Then carry the same run directly into the measured response.

Weight-2 stabilizer data
Measured response of the weight-2 stabilizer experiment.

WEIGHT-4 STABILIZER

Scale the sequence to the larger multi-qubit measurement.

Weight-4 stabilizer circuit

Pelagic keeps the workflow unchanged while the experiment becomes more sophisticated.

Weight-4 stabilizer data
Measured response of the weight-4 stabilizer experiment.

06 / THE RESULT

Advanced physics.
Routine experiments.

Pelagic turns methods at the frontier of quantum characterization into tools that belong in the everyday lab workflow.

The same stack carries the experiment from device diagnostics to multi-qubit preparation and a reconstructed GHZ state.

Reconstructed GHZ density matrix
Reconstructed density matrix of the prepared GHZ state.
GHZ experiment
QUA / PELAGIC
qubits = [q1, q2, q3, q4, q5]

with pelagic.experiment("ghz") as exp:
    exp.prepare(ghz(qubits))
    result = exp.measure(
        qubits,
        shots=10_000,
    )

rho = result.tomography()
rho.plot_density_matrix()

One experiment. The whole result.

Keep preparation, measurement, and reconstruction together in one readable workflow.

A starting point for your physics.

Extend an experiment class to adapt its sequence or analysis to your device.

Explore experiment classes