Software infrastructure for experimental quantum error correction

Adeeb Kabir, Steven Nguyen, Sohan Ghosh +5 more

Quantum computers have steadily improved over the last decade, but developing fault-tolerant quantum computing (FTQC) techniques, required for useful, universal computation remains an ongoing effort. Key elements of FTQC such as error-correcting codes and decoding are supported by a rich bed of stabilizer simulation software such as Stim and CHP, which are essential for numerically characterizing these protocols at realistic scales. Recently, experimental groups have built nascent high-dimensional quantum hardware, known as qudits, which have a myriad of attractive properties for algorithms and FTQC. Despite this, there are no widely available qudit stabilizer simulators. We introduce the first open-source realization of such a simulator for all dimensions. We demonstrate its correctness against existing state vector simulations and benchmark its performance in evaluating and sampling quantum circuits. This simulator is the essential computational infrastructure to explore novel qudit error correction as earlier stabilizer simulators have been for qubits.

Daniel A. Lidar, Todd A. Brun

John Chiaverini, Dietrich G. Leibfried, Tobias Schaetz +9 more

Youssef Adel, Hassan Soubra, Tuna Hacaloğlu +3 more

As quantum computing has progressed toward fault-tolerant implementations, quantum error correction (QEC) for quantum hardware and software has become a dominant concern. While conventional QEC measurements, such as qubit overhead, code distance, and error thresholds, quantify physical resource costs, they do not capture the software-level functionality introduced by error detection, correction, and fault-tolerant gate protocols. This study investigated the QEC contribution to the functional size of quantum software and demonstrated that this contribution can be systematically measured using the COSMIC Functional Size Measurement method. A gate-level sizing approach, known as Gates’ Occurrences, was used to quantify functional user requirements (FUR) associated with QEC processes, including logical encoding, syndrome extraction, and recovery operations. A prototype measurement tool, implemented in Qiskit (Version 0.7.2), enables the automated calculation of COSMIC Function Points (CFP) from annotated circuit representations. Case studies involving Bell state preparation, Grover’s search algorithm, and 15-to-1 magic state distillation revealed that QEC-related functionality can account for 70–85% of the total functional size, even under simplified encoding assumptions. The results underscore the importance of QEC for the functional size of quantum software. These findings offer a reproducible foundation for functional sizing and future fault-tolerant quantum applications.

Emmanouil Giortamis, Felix Gust, Aleksandra Świerkowska +7 more

Distributed Quantum Computing (DQC) and Quantum Error Correction (QEC) rely on dynamic circuits that include Mid-Circuit Measurements (MCMs) and classical feedback. These operations present a major bottleneck: MCMs suffer from high error rates that lead to real-time branching errors, while MCM and classical feedback latencies amplify decoherence errors. Current hardware controllers, qubit-state discriminators, and software error mitigation techniques fail to address these challenges holistically. We propose MCMit, a hardware-software co-design to mitigate branching and latency-induced errors. MCMit introduces a scalable, constant-latency multi-control branch instruction for faster classical feedback and two qubit-state discriminators, a transformer, and a CNN, with high accuracy even under short measurement durations. On the software side, static MCM elimination and stochastic branching complement the hardware by mitigating residual branching errors that persist despite hardware improvements. We implement MCMit on Qubic and evaluate it using experimentally extracted QPU readout traces. Our branch instruction reduces feedback latency by up to 70\%, improving circuit depths by up to $7\times$ over Qubic. Our CNN discriminator achieves up to 62\% higher accuracy for short measurement durations than the baselines, driving $1.2-9.4\times$ lower logical error rates in QEC. Last, our software mitigation improves fidelity by 18--30\% over baseline methods in DQC workloads.

Farhan Feroz, A. B. M. Alim Al Islam

Quantum error correction comes from the marriage of quantum mechanics with the theory of error-correcting codes, which is still at the rudimentary stage tackling only 1 qubit to date. As, unlike the classical world, the extent of error in the quantum world is substantially high and unavoidable, scaling up the quantum error correction from 1 qubit to higher is of utmost significane. Therefore, to achive the scaling up, we present a general quantum error correction code that can be adapted for any number of quantum errors (bit-flip error to be specific in our case). This generalized code for bit-flip error correction realizes a delicate blending of using controlled-NOT gates with the notion of quantum entanglement. We augment the blending with majority voting in the final stage of the error correction. We demonstrate efficacy of our proposed error correction code through real experimentation in IBM Qiskit. Our experimental results up to 3-qubit bit-flip errors in the available Qiskit infrastructure confirm a total escape from errors using our proposed error correction code.