Quantum Computing Advances: Tackling Errors and Developing Algorithms

The race to develop a fully functional “fault-tolerant” quantum computer is intensifying, with companies and government labs worldwide striving to lead this transformative technology. A truly universal quantum computer capable of executing complex algorithms requires the entanglement of millions of coherent qubits, which are notably fragile and susceptible to errors. Challenges arise from environmental factors, including temperature variations and interference from electronic systems, which can lead to significant operational failures before reaching desired performance levels. Addressing the issue of error correction is crucial for the future of quantum computing.

In quantum systems, errors in qubits cannot be corrected merely by duplicating them as in classical computers. This limitation stems from quantum mechanics, which prohibits copying qubit states while they remain entangled. Instead, new techniques for quantum error correction (QEC) are essential for managing qubit errors effectively. As John Preskill, director of the Institute for Quantum Information and Matter at the California Institute of Technology, explains, “The essential idea of quantum error correction is that if we want to protect a quantum system from damage, then we should encode it in a very highly entangled state.”

The methods for achieving this error correction vary, depending on the connectivity of the qubits. For instance, qubits may be coupled solely to their nearest neighbors or to all others within the device. Regardless of the approach, quick error correction is vital. Michael Cuthbert, founding director of the UK National Quantum Computing Centre, emphasizes the need for error correction mechanisms to operate at speeds that are compatible with gate operations. “There’s no point in doing a gate operation in a nanosecond if it then takes 100 microseconds to do the error correction for the next gate operation,” he states.

Currently, error management primarily focuses on compensation rather than correction. Techniques include retrospective adjustments, such as using algorithms that discard unreliable results, an approach known as “post-selection.” Additionally, efforts are underway to create improved qubits that inherently experience fewer errors.

To safeguard information stored in qubits, numerous unreliable physical qubits must be combined so that if one qubit fails, others can compensate. This process allows for the creation of “logical” qubits that are more resistant to noise. Maria Maragkou, commercial vice-president of the quantum software company Riverlane, highlights the implications of full QEC for machine design, stating, “The shift to support error correction has a profound effect on the way quantum processors themselves are built.”

With advancements in QEC, it is possible to control errors and prevent them from proliferating during computations. This involves combining many physical qubits into a single logical qubit capable of error correction. While this approach introduces considerable overhead, researchers at Google reported significant progress with their 105-qubit Willow quantum chip, which has achieved a break-even threshold where the error rate diminishes as more physical qubits are used. This milestone indicates the potential for scaling up quantum systems without accumulating errors.

The pursuit of fault-tolerant quantum computing is deemed essential by Jay Gambetta, director of IBM research at the company’s centre in Yorktown Heights, New York. He envisions that to conduct transformative quantum calculations, systems must have arrays of at least 100 logical qubits capable of executing over 100 million quantum operations (108 QuOps). Gambetta expresses confidence that IBM will reach these targets by 2029, stating, “I feel more confident than I ever did before that we can achieve a fault-tolerant computer.”

In contrast, others like Steve Brierly, chief executive of Riverlane, anticipate that the first error-corrected quantum computer could emerge even sooner, possibly in 2027. This machine would feature around 10,000 physical qubits supporting 100 logical qubits and could perform a million quantum operations (a megaQuOp). Following this, machines capable of performing gigaQuOp (10^9 QuOps) operations are expected by 2030-2032, with teraQuOps (10^12 QuOps) anticipated by 2035-2037.

Developing effective quantum software poses additional challenges. The creation of truly quantum algorithms hinges on leveraging key properties such as superposition and entanglement, which often depend on the specific hardware utilized. Currently, users must engage with the underlying physics to optimize performance, but the goal is to evolve software that operates independently of the hardware specifics.

As Richard Murray from Orca notes, many platforms necessitate deep knowledge of quantum physics to maximize efficiency. However, as the field matures, the expectation is that developers will abstract these complexities away from users. Maragkou affirms this outlook, stating, “In due time, everything below the logical circuit will be a black box to the app developers.”

Even now, individuals working on quantum software do not necessarily require a physics background. Ashley Montanaro, co-founder of the quantum software company Phasecraft, points out that contributions to quantum computing can come from diverse backgrounds, demonstrating the accessibility of this innovative field.

Looking ahead, Cuthbert from the UK’s NQCC predicts a surge in high-value commercial applications for quantum computers once true error correction is achieved. These applications could significantly enhance areas such as quantum chemistry and materials science. Notably, Chow from IBM emphasizes that quantum methods can already provide advantages in simulations, even when integrated with classical methods.

A recent collaboration between IBM and Japan’s national research laboratory RIKEN illustrates the potential of combining quantum and classical computing. In June 2025, they unveiled the first IBM Quantum System Two outside the US, integrating IBM’s 156-qubit Heron quantum computing system with RIKEN’s supercomputer Fugaku. This partnership exemplifies how quantum and classical systems can work in tandem to tackle complex calculations too intricate for classical systems alone.

As the quantum computing market develops, the path forward remains uncertain. While the technology has demonstrated proof of principle, practical applications that exceed classical capabilities are still in progress. Continued investment is crucial for the growth of this sector. Gambetta believes that the unique capabilities of quantum computers will establish their value as scientific tools, sustaining funding and development.

Looking to the future, Montanaro sees the government playing a pivotal role in nurturing quantum innovation, particularly in areas where private sector investment may be insufficient. He advocates for sustained support for academic research to ensure the ongoing advancement of foundational science in this field.

As IBM charts its course toward achieving a fault-tolerant quantum device by 2029, the company is also focused on developing new algorithms and software to complement hardware advancements. Nonetheless, the demand for individual ownership of quantum machines remains ambiguous. The infrastructure required may lead to a preference for cloud-based services over in-house installations.

Cuthbert underscores the challenge of transitioning from specialized scientific applications to commercially viable machines. The quantum industry is expected to evolve rapidly, drawing parallels to the early days of classical computing. As quantum technologies mature, it is anticipated that applications and services leveraging cloud-based quantum resources will seamlessly integrate with classical computing, potentially revolutionizing how solutions are delivered.

The ultimate goal of quantum computing is to become an invisible, integral part of technology, quietly enhancing our problem-solving capabilities.