Quantum error correction (QEC) is a method of protecting quantum information from errors due to environmental noise and decoherence. It is an essential element of quantum computing, as it allows for the reliable storage and manipulation of quantum data. QEC uses redundant information to identify and correct errors that occur in quantum data.
There are three main types of QEC at the outset: stabilizer codes, topological codes, and fault-tolerant codes. Stabilizer codes are the most common type of QEC and are based on the mathematical tool of group theory. They are used to protect a single qubit from noise and can be used to store multiple qubits of information. Topological codes are more potent than stabilizer codes and can protect multiple qubits from errors. They use topological properties of the underlying lattice to detect and correct errors. Lastly, fault-tolerant codes are the most powerful type of QEC and are designed to protect against arbitrary errors. They are designed to be robust against any type of noise and are used to ensure accurate computation of quantum algorithms.
Stabilizer codes use the mathematical tool of group theory to protect a single qubit from noise. This type of QEC works by encoding the qubit’s information into two subsystems, each of which is composed of two or more qubits. The qubits in each subsystem interact with each other, and the interactions are governed by a set of rules called “stabilizers.” These stabilizers can be thought of as “checks” that are performed on the qubits to ensure that the information is encoded correctly.
If the qubits in one of the subsystems are affected by noise, the stabilizers will detect the error and signal to the system that an error has occurred. The system can then use the other subsystem to correct the error by adjusting the qubits in the affected subsystem. This error correction process is repeated until the qubits in the affected subsystem are restored to their original state.
Topological codes use the topology of the underlying lattice to detect and correct errors. This type of QEC works by encoding the qubit’s information into two subsystems, each composed of a lattice of qubits. The qubits in each subsystem interact with each other, and the topology of the lattice determines the interactions. If the qubits in one of the subsystems are affected by noise, the topology of the lattice will detect the error and signal to the system that an error has occurred. The system can then use the other subsystem to correct the error by adjusting the qubits in the affected subsystem. This error correction process is repeated until the qubits in the affected subsystem are restored to their original state. Topological codes are more powerful than stabilizer codes, as they can protect multiple qubits from errors.
It’s noteworthy that both topological QEC and Surface code QEC are subsets of lattice-based error correction. However, As explained, topological quantum error correction (QEC) is a type of quantum error correction that uses topological properties of quantum systems to detect and recover from errors. It is based on the idea of encoding qubits in topological quantum systems, such as Majorana zero modes 1, and using interactions between these qubits to detect and correct errors. This technique differs from the more commonly used surface code QEC, which uses a 2D lattice of qubits to detect errors. Topological QEC is significantly more efficient at error correction as it can detect errors in a single qubit, while the surface code requires several qubits to detect an error. Additionally, topological QEC does not rely on the same fault-tolerant operations as the surface code, making it more suitable for use in noisy or low-fidelity systems.
Surface code QEC, in turn, is a technique based on encoding information in a 2D lattice, which is divided into cells, each containing one qubit. The qubits are arranged in a checkerboard pattern, and interactions between these qubits are used to detect errors. To correct an error, a set of operations known as fault-tolerant operations are used to move the information from the affected qubits to unaffected qubits. Surface code QEC is more complex than other types of quantum error correction, but it is also more effective, as it can detect and correct errors in multiple qubits at once.
On the other hand, fault-tolerant codes are the most powerful type of QEC and are designed to protect against arbitrary errors. They are designed to be robust against any type of noise and are used to ensure accurate computation of quantum algorithms. This type of QEC works by encoding the qubit’s information into multiple subsystems, each composed of multiple qubits. The qubits in each subsystem interact with each other, and the interactions are governed by a set of rules called “fault-tolerant codes.” These codes are designed to detect and correct errors that may occur in any of the subsystems. If the qubits in one of the subsystems are affected by noise, the codes will detect the error and signal to the system that an error has occurred. The system can then use the other subsystems to correct the error by adjusting the qubits in the affected subsystem. This error correction process is repeated until the qubits in the affected subsystem are restored to their original state. Fault-tolerant codes are the most reliable type of QEC, as they can protect against any type of noise.
To sum up, Quantum error correction (QEC) protects quantum information from errors due to environmental noise and decoherence. It is composed of three main types: stabilizer codes, topological codes, and fault-tolerant codes. Stabilizer codes use group theory to protect a single qubit from noise, and topological codes use the topology of the underlying lattice to detect and correct errors, and fault-tolerant codes are designed to protect against arbitrary errors. These codes are designed to be robust against any noise and are used to ensure the accurate computation of quantum algorithms.
[1] Majorana zero modes are a theoretical concept that suggests electrons can be split into two distinct parts. This property has the potential to provide a decisive advantage in quantum computing, as it enables qubits to remain protected from local disturbances and perturbations.
Hamed is an innovative and results-driven Chief Scientist with expertise in Quantum Science, Engineering, and AI. He has worked for leading tech companies in Silicon Valley and served as an Adjunct Professor at UC Berkeley and UCLA.