IDTechEx Asks How Gate-Based Quantum Computers Will Scale-Up - Seite 2

One method of overcoming the impact of noise and decoherence is quantum error correction (QEC). In simple terms, this requires creating abstracted, error-free, logical qubits from a collection of noisy physical qubits. In oversimplified terms, by comparing the properties of the group, enough information about the noise can be extracted to correct it. It is analogous to playing a game of broken telephone enough times to decode the original message. The exact mathematical approaches to large-scale error correction remain a highly active area of research – particularly by the likes of experts at Riverlane. Yet the conclusion is clear: the number of logical qubits per system is becoming a more important benchmark for quantum computer hardware's long-term potential for success.

Strikingly, it is apparent that the required ratio of physical to logical qubit varies dramatically between qubit modalities. Evidence suggests that for photonic, it could be as low as 2:1, for neutral atom and trapped ion nearer 10:1 – while superconducting could require more than 1000:1. To some extent, this has temporarily leveled the playing field in the quantum computing market, seeing challengers such as QuEra catch up, if not overtake, giants like IBM and Google in the race for high numbers of logical qubits.

Overall, the need to now transition into a 'logical era' is clear. This is well evidenced by the focus on this benchmark in the latest roadmaps by multiple players across the industry. Yet, unfortunately, solely optimizing system design towards reducing errors will not be enough to secure long-term success. For this, the impact on overall size and power consumption must also be considered.

Reduced Infrastructure burden

Overcoming the infrastructure limitations associated with scaling quantum computer hardware is no easy task. Almost all systems today require cooling, whether it be using cryostats or lasers. It is often the cooling system that can be the most demanding on space. However, as efforts to increase logical qubit number increase – space per cooling system to house them is running out.

As a result, today, many hardware roadmaps show a modular approach with multiple systems connected. On the one hand, quantum computing is designed for high-value problems – to be solved over the cloud, and so requiring a large footprint within a data center is not necessarily a huge barrier to adoption. However, in some instances, the associated power demand for this approach for an LSFT machine is calculated to be in the Mega Watts, which is enough to warrant its own small modular reactor. To truly follow the trend of classical computing from vacuum tube to smart phone, it's time to start making components smaller before capabilities can get bigger.