org.soulspace.qclojure.application.error-mitigation — org.soulspace/qclojure 0.7.0

Error mitigation strategies for quantum computing.

This namespace provides a comprehensive suite of error mitigation techniques to improve the fidelity of quantum circuit execution on noisy hardware.

Key strategies implemented:

• Zero Noise Extrapolation (ZNE)
• Readout Error Mitigation
• Symmetry Verification
• Virtual Distillation
• Circuit Optimization Integration

The mitigation pipeline analyzes circuits and noise models to automatically select and apply the most effective strategies for each use case.

analyze-circuit-noise-profile clj

(analyze-circuit-noise-profile circuit noise-model)

Analyze circuit characteristics to recommend mitigation strategies.

apply-circuit-optimization clj

(apply-circuit-optimization circuit supported-gates)

Apply circuit optimization as part of error mitigation.

apply-error-mitigation clj

(apply-error-mitigation circuit backend mitigation-config)

Apply comprehensive error mitigation strategies to improve circuit fidelity.

This is the main entry point for error mitigation. It analyzes the circuit and noise model, selects appropriate strategies, and orchestrates their application.

apply-symmetry-verification clj

(apply-symmetry-verification circuit measurement-results)

Apply advanced symmetry verification for error detection.

Production implementation with sophisticated symmetry analysis.

apply-virtual-distillation clj

(apply-virtual-distillation circuit backend num-copies num-shots)

Apply virtual distillation using multiple circuit copies.

Virtual distillation improves fidelity by:

1. Running multiple copies of the circuit
2. Applying post-processing to extract high-fidelity results
3. Using probabilistic error cancellation

Production implementation uses realistic circuit simulation.

compute-parity-expectation clj

(compute-parity-expectation measurement-results num-qubits)

Compute parity expectation values for symmetry verification.

For n qubits, computes <Z₁Z₂...Zₙ> expectation value.

create-calibration-matrix clj

(create-calibration-matrix num-qubits readout-errors)

Create calibration matrix from readout error characterization.

For n qubits, this creates a 2^n x 2^n matrix where element (i,j) represents P(measure state i | prepared state j).

Uses tensor product to properly construct multi-qubit calibration matrices.

create-error-mitigation-backend clj

(create-error-mitigation-backend base-backend mitigation-config)

Create a backend wrapper that applies error mitigation transparently.

This higher-order function wraps any quantum backend to add comprehensive error mitigation capabilities without changing the backend interface.

create-single-qubit-readout-matrix clj

(create-single-qubit-readout-matrix readout-errors)

Create readout error matrix for a single qubit.

Returns 2x2 matrix where element (i,j) = P(measure i | prepared j).

detect-symmetry-violations clj

(detect-symmetry-violations circuit measurement-results)

Detect violations of known circuit symmetries.

Advanced symmetry detection including:

• Parity conservation
• Reflection symmetries
• Permutation symmetries
• Custom symmetry constraints

execute-with-mitigation clj

(execute-with-mitigation circuit backend mitigation-config)

Execute a circuit with comprehensive error mitigation applied.

This is the main integration point that combines circuit optimization, error mitigation, and result post-processing in a single function.

extract-expectation-value clj

(extract-expectation-value measurement-results ideal-states)

Extract an expectation value from measurement results for ZNE.

This could be:

• Probability of success state
• Parity expectation
• Custom observable

For now, uses probability of most likely ideal state.

fit-exponential-decay clj

(fit-exponential-decay data-points)

Fit exponential decay model to ZNE data points.

Model: f(x) = a * exp(-b * x) + c Simple linear fit for demonstration.

generate-state-labels clj

(generate-state-labels num-qubits)

Generate binary state labels for n qubits.

Returns vector of strings like ['00', '01', '10', '11'] for 2 qubits.

get-strategy-info clj

(get-strategy-info strategy)

Get metadata information about a mitigation strategy.

list-available-strategies clj

(list-available-strategies)

List all available error mitigation strategies with their metadata.

mitigate-errors clj

(mitigate-errors circuit backend & [config])

Main API function for applying error mitigation to quantum circuits.

This is the primary entry point for users of the error mitigation system.

mitigate-readout-errors clj

(mitigate-readout-errors measured-counts calibration-matrix num-qubits)

Apply readout error mitigation using calibration matrix.

This inverts the effect of readout errors by solving the linear system: measured_counts = calibration_matrix * true_counts

Production implementation supports arbitrary number of qubits using proper matrix inversion.

scale-noise-model clj

(scale-noise-model noise-model scale-factor)

Scale the noise parameters in a noise model by a given factor.

select-mitigation-strategies clj

(select-mitigation-strategies circuit noise-model constraints)

Select optimal mitigation strategies based on circuit analysis and constraints.

simulate-circuit-execution clj

(simulate-circuit-execution circuit noise-model num-shots)

Simulate realistic quantum circuit execution under noise.

This provides a more realistic simulation for ZNE by modeling:

• Gate-dependent error accumulation
• Readout errors
• Decoherence effects
• Circuit depth impact

Returns measurement results that reflect actual quantum hardware behavior.

strategy-metadata clj

Metadata about available error mitigation strategies.

zero-noise-extrapolation clj

(zero-noise-extrapolation circuit backend noise-scales ideal-states num-shots)

Apply Zero Noise Extrapolation to mitigate coherent errors.

Production implementation using realistic circuit simulation instead of mock data.