The goals for error correction in near-term systems are as follows: (i) using a small number of qubits for encoding, and (ii) keeping cost of circuits for
In this paper we introduce the \texttt{topological\_codes} module of Qiskit-Ignis, which is designed to provide the tools necessary to perform such tests.
To build a universal quantum computer, one may implement a set of universal gates to approximate any quantum algorithm in the circuit model.
Though not a true example of quantum error correction—it uses physical qubits to encode a logical *bit*, rather than a qubit—it serves as a simple guide to all the basic concepts in any quantum error correcting code. Specifically, we will use the topological\_codes module of Qiskit-Ignis, which provides tools to create the quantum circuits required for simple quantum error correcting codes, as well as process the results. Instead of using the form shown above, with the final measurement of the code qubits on the left and the outputs of the syndrome measurement rounds on the right, we use the process\_results method of the code object to rewrite them in a different form. The resulting object then contains the circuits corresponding to the given code encoding simple logical qubit states (such as $\left\vert 0\right\rangle $ and $\left\vert 1\right\rangle $), and then running the procedure of error detection for a specified number of rounds, before final readout in a straightforward logical basis (typically a standard $\left\vert 0\right\rangle $/$\left\vert 1\right\rangle $ measurement).
IBM scientists published the discovery of new codes that work with ten times fewer qubits. We also require a code that works on relatively noisy qubits.
In addition, fault-tolerant execution (specifically, execution using QEC strategies that mathematically guarantee certain error-scaling properties) often runs thousands to millions of times slower than uncorrected circuits, severely restricting the feasibility of large-scale quantum computations. *Figure 2: Applicability of error suppression, mitigation, and correction across quantum task types, workloads, and example use cases.*. For workloads involving 100s to 1,000s of circuits, error suppression keeps total quantum execution times essentially unchanged—ranging from seconds or minutes for small tasks to only a few hours for the largest workloads. Assume that we wish to use the probabilistic error cancellation (PEC) error mitigation method for such a use case, and each such circuit requires 1 execution hour due to overhead (a conservative estimate since such circuits tend to be deep). | Use case and field | Description | Task type and workload size (excluding overhead) | Applicable error-reduction strategies |.
A proposed recipe for quantum error correction removes the need for time-consuming measurements of qubits, replacing them with copying and feedback steps
# Quantum Report Says Error Correction Now The Industry’s Defining Challenge. Real-time quantum error correction has become the industry’s defining engineering hurdle, reshaping national strategies, private investment, and company roadmaps as the race for utility-scale quantum computers tightens, according to a new technical study spearheaded by Riverlane. The *Quantum Error Correction Report 2025*, written in partnership with Resonance, indicates that quantum computing has crossed a turning point. The report, based on interviews with 25 global quantum computing and QEC experts, including 2025 Nobel laureate John Martinis, finds that all major quantum companies are now pursuing error correction and that a growing share treat it as a competitive edge rather than a research milestone. The report identifies real-time quantum error correction as the industry’s main bottleneck. The report projects demand for error-correction specialists to grow severalfold by 2030, driven by the need for real-time systems, expanded decoding hardware, and cross-disciplinary expertise in machine learning, signal processing, and chip design.