Superconducting quantum computing hardware provider Oxford Quantum Circuits (OQC) has released erado, an open-source Python library designed to simulate erasure noise, dual-rail qubit encodings, and post-selection strategies on arbitrary Qiskit circuits. Integrated directly into OQC’s Quantum Computing as a Service (QCaaS) SDK as a 16-qubit AerSimulator backend, the tool allows algorithm developers and researchers to benchmark erasure-aware noise models and evaluate quantum error mitigation techniques ahead of physical execution.
The release is accompanied by a companion research paper titled “The limits of erasure-based postselection for quantum error mitigation“ (Griffiths et al., arXiv:2606.31428). The study demonstrates that postselection can fully mitigate the erasure channel when erasure check error rates remain below 3.0%. Crucially, the authors show that a postselected dual-rail system can surpass the fundamental noise floor at the kiloquop (1,000 quantum operations) scale where a comparable single-rail architecture fails, justifying the approach for Noisy Intermediate-Scale Quantum (NISQ) algorithms prior to full Quantum Error Correction (QEC). Beyond OQC, erasure-detection methodologies and dual-rail architectures are being actively pursued across the ecosystem, including by D-Wave Systems (following its acquisition of Quantum Circuits Inc.) and Q-CTRL.
| [ OQC Erado Simulator Architectural & Configuration Parameters ] | ||
|---|---|---|
| Parameter / Flag | Functional Specification | Simulation Mechanics & Impact |
erasure_rate | Per-gate erasure probability (0.0 to 1.0) | Triggers non-computational state transition; compounds with total erasable gate count. |
post_selection | Boolean filter flag (Default: False) | When enabled, discards detected erasure shots and automatically retries until target shot count is met. |
false_negative_rate | Detector inaccuracy probability (0.0 to 1.0) | Models missed erasures, allowing corrupted state measurements to leak into final results. |
idling_error | Idle period padding via IdlingErrorConfig | Inserts idle gates into circuit layers to model environment-induced decoherence during idle states. |
The library provides two primary simulation modes: CIRCUIT_SAMPLER for exact statevector sampling and TRANSPILER_PASS for memory-efficient execution on larger circuit widths. By providing precise parameter controls over false-positive and false-negative detector rates, erado enables researchers to quantify the exact trade-off boundary where the shot-rejection overhead of post-selection remains computationally profitable compared to standard noisy sampling.
Review the technical deep-dive on OQC Technical Blog here, read the research paper on arXiv (arXiv:2606.31428) here, access the open-source repository on GitHub here, inspect package releases via PyPI here, and view developer documentation on OQC QCaaS SDK Docs here.
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