Google researchers have achieved a significant milestone in quantum error correction, a development that could potentially revolutionize quantum computing. Their new method allows quantum bits, or qubits, to store and manipulate data with greater accuracy and longevity, paving the way for more reliable quantum computers. Quantum computers have the potential to transform various scientific fields such as particle physics, drug discovery, and materials science.
However, one of the main challenges has been the high rate of errors in these systems, which disrupts the execution of long and complex algorithms. The new technique introduced by Google Quantum AI, in collaboration with academic partners, involves adding more components to the quantum computer to reduce errors. Historically, adding components often introduced more errors due to engineering limitations.
This breakthrough, however, demonstrates that error correction can effectively improve a quantum computer’s performance. Kenneth Brown, a physicist at Duke University, explained that this research solidifies the idea that error correction is a feasible path toward constructing useful quantum computers. Michael Newman, a member of the Google team, shared similar optimism on social media.
Quantum computers operate on principles of quantum mechanics, storing information in “superpositions” rather than just binary states like conventional computers. These superpositions, manipulated through quantum interactions such as entanglement, enable new types of algorithms. However, errors in maintaining these states have been a significant hurdle.
Assessing Google’s quantum progress
Google’s new approach encodes information across multiple physical qubits to form a single “logical” qubit, effectively creating a more robust unit of information. This system uses a surface code algorithm to correct errors within the logical qubit by leveraging its constituent physical qubits.
The research showed that a logical qubit composed of 105 physical qubits was more effective at suppressing errors than one composed of 72 qubits, suggesting that increasing physical qubits in a logical qubit can significantly reduce errors. Jay Gambetta, IBM’s vice president of quantum computing, noted that Google’s work is an important step towards reliable quantum memory. However, he emphasized the need to perform logical operations on the stored data to build practical quantum circuits.
IBM is also actively pursuing quantum error correction but with a different approach known as low-density parity-check code. This method aims to achieve comparable error suppression rates with fewer physical qubits. By 2026, IBM plans to demonstrate a system with 12 logical qubits using 244 physical qubits.
The field of quantum computing remains in its developmental phase, with researchers exploring various materials and methods. For instance, the Boston-based company QuEra uses neutral atoms as physical qubits and has demonstrated algorithms using up to 48 logical qubits made of rubidium atoms. While these advancements are promising, experts like Brown urge patience, noting that achieving a highly functional quantum computer capable of performing a billion logical operations is still a long way off.
QuEra aims to develop a quantum computer with 100 logical qubits by 2026, which could simulate complex phenomena beyond the reach of classical computers. The next critical step for Google and other researchers will be to demonstrate practical applications of these high-quality logical qubits, moving beyond theoretical improvements to tangible outcomes in quantum computing.
