July 3, 2022

Multibillion-dollar quantum opportunities if error rate recedes


Viable commercial quantum computing is probably not on the immediate horizon for many IT chiefs. However, McKinsey has urged CIOs to start thinking about what is likely to happen over the next eight years when quantum computer systems are set to become fault-tolerant.

In a paper, Quantum computing: An emerging ecosystem and industry use cases, the management consulting firm looked at the opportunities to use quantum computing in the pharmaceutical, chemicals, automotive and finance sectors.

While multiple quantum computing hardware platforms are under development, the most important milestone will be the achievement of fully error-corrected, fault-tolerant quantum computing.

According to the authors of the paper, without fully error-corrected, fault-tolerant quantum computing, a quantum computer would be unable to provide exact, mathematically accurate results.

“Experts disagree on whether quantum computers can create significant business value before they are fully fault tolerant,” they stated in the paper. However, McKinsey also noted that some experts believe imperfect fault tolerance does not necessarily make quantum-computing systems unusable.

In the pharmaceutical sector, McKinsey said that quantum computing could accelerate research and development by making target identification, drug design and toxicity testing less dependent on trial and error and therefore more efficient.

Given that it is a $1.5tn sector, McKinsey estimated that an improvement of 1% to 5% would result in $15bn to $75bn of additional revenue and would improve more patients’ quality of life and production, logistics and supply chain across the pharmaceutical sector.

In the chemicals sector, McKinsey sees a role for quantum computing in enabling chemical companies to improve catalyst designs. Such catalysts offer the potential to improve production efficiency and help to tackle climate change by reducing the need for petrochemicals or directly act to lower CO2 emissions.

The paper’s authors wrote: “In the context of the chemicals industry, which spends $800bn on production every year (half of which relies on catalysis), a realistic 5% to 10% efficiency gain would mean a gain of $20bn to $40bn in value.”

Looking at the automotive sector, McKinsey said that there were opportunities to use quantum computing in R&D, product design, supply chain management, production, and mobility and traffic management.

The paper’s authors said that the technology could be applied to decrease manufacturing process-related costs and shorten cycle times by optimising elements such as path planning in complex multi-robot processes (the path a robot follows to complete a task) including welding, gluing and painting. Given that the automotive industry spends $500bn per year on manufacturing costs, according to McKinsey, quantum computing could create $10bn to $25bn of value per year.

In finance, Mckinsey said: “The most promising use cases of quantum computing in finance are in portfolio and risk management.” One example the authors of the paper gave is efficiently quantum-optimised loan portfolios that focus on collateral. For McKinsey, such optimisation could enable lenders to improve their offerings, possibly lowering interest rates and freeing up capital.

While there are opportunities across the sectors McKinsey looked at, the authors of the paper warned that hardware remains a significant bottleneck in the ecosystem. The hardware challenge is both technical and structural.

According to McKinsey there are two main barriers. First, there is the ability to scale the number of qubits in a quantum computer while achieving a sufficient level of qubit quality. The second is the high barrier to entry.

“It requires a rare combination of capital, experience in experimental and theoretical quantum physics, and deep knowledge – especially domain knowledge of the relevant options for implementation,” the report stated.



Source link

Leave a Reply

Your email address will not be published.