Hybrid Computing to Accelerate Quantum Adoption Through 2023

Technology research and consultancy firm Omdia predicts that solutions using quantum computing paired with classical computing in hybrid solutions will be an important focus for industry in the short term.

In its “2023 Trends to Watch: Quantum Computing” report, Omdia says connecting developers, data scientists and classical computers will be the first stage in the commercialization of quantum computing.

However, technical challenges remain, with one of the most significant being the ability to transfer information between the classical computer and the quantum computer due to their radically different architectures.

The report recommends that enterprises seeking to adopt a quantum solution should first understand that finding an effective and standardized method for assessing system performance is still a challenge. This makes comparing potential vendors and technologies difficult.

Similarly, adopters may know the term “quantum supremacy” means a quantum computer performing a given task faster than a classical computer but not whether any solution is close to achieving this for their industry.

Despite this, Omdia analysts say they expect increasing announcements of “quantum advantage” being achieved in various industries for specific uses in the short term.

Related:Public Sector Leads Quantum Adoption

According to the report, much of the work vendors carry out with customers in the next two to four years will be in helping them to experiment with quantum computing and learn how quantum computing will eventually apply to their specific challenges.

“The quantum computing industry may be several years away from demonstrating a definite advantage over classical computers for problems of commercial interest, but Omdia strongly advises potential adopters to jump in now to learn about the technology, and more specifically, how quantum computing can address their specific use case needs,” Omdia chief quantum computing analyst Sam Lucero told Enter Quantum.