Quantum Computing: A Roadmap to the Future

Published on 02 Aug, 2019

With classical computing having reached its limit and advanced computing requirements on the rise owing to the advent of big data and artificial intelligence, quantum computing has turned the need of the hour. However, dealing with the complexities of quantum mechanics is a challenge that many companies are trying to overcome. Although the technology is still at a nascent stage, it is imperative for all industries to begin exploring the potential of quantum computing and develop a road map for customized use cases.

Demand for computation power has grown leaps and bounds with the advent of advanced technologies, such as artificial intelligence (AI) and neural networks, and the inevitable failure of Moore’s law. Consequently, quantum computing (QC) has turned the need of the hour. QC takes advantage of the unique quantum mechanics properties of superposition and entanglement to offer exponentially higher computation power and security than classical computing.

Current Scenario
QC has come a long way in the past few years, supported by the tremendous amount of research and development (R&D) being conducted by various institutes and organizations. IBM’s Q System One, the first integrated universal approximate quantum computing system, which was unveiled at the Consumer Electronics Show (CES) 2019, is the latest proof of these R&D efforts. Google’s demonstration of 72 qubit information processing; China’s quantum satellite-based secure communication over 1200 kilometers; and quantum cloud services launched by Rigetti’s ForestTM, Google’s Cirq, and Alibaba’s Aliyun are some of the examples of the achievements in this domain in the past few years.

The current QC ecosystem has evolved considerably and can be categorized into end-to-end providers (such as IBM, Google, Rigetti, Microsoft, and Alibaba), hardware and system players (such as Intel, IonQ, and QuTech), software and service players (such as 1QBit, QC Ware, Zapata Computing, and CQC), and specialists (such as Q-CTRL, QubitLogic, and Silicon Quantum Computing). This indicates that simultaneous efforts are being made in various aspects related to QC.

Trends, such as growing news coverage since 2017, an increase in the number of qubits achieved (Rigetti announced plans for a 128-qubit quantum chip), a rise in venture capital investments, and advancement in the number of in-house quantum computing projects by tech giants (such as IBM, Google, Microsoft, and Alibaba), indicate a positive acceptance of QC implementations in the next few years.

From a market analysis perspective, the current global QC market size is a few million USD; however, it is expected to reach approximately USD 1 billion by 2030. The market estimation depends heavily on future technology breakthroughs. Early breakthroughs would facilitate quicker market penetration.

Potential Use Cases
In the next 5 to 10 years, QC is expected to offer business benefits in three areas: quantum simulation, quantum optimization, and quantum-based machine learning. The potential use cases of QC exist across various industry sectors, which may be realized sooner than expected. In the high-tech or IT industry, QC would be applied to neural networks, cybersecurity, and bidding strategies for advertisements, and for software verification and validation. IBM, Google, Microsoft, Alibaba, Baidu, and Samsung are some of the companies working in this direction. In the industrial goods sector, Airbus, NASA, BMW, Volkswagen, and Lockheed Martin are some of the companies working toward resolving issues such as traffic simulation, autonomous driving, and airflow modeling of an aircraft wing using QC. Similarly, companies such as BASF, Amgen, JPMorgan Chase & Co., Goldman Sachs, and Commonwealth Bank are attempting to use QC to solve complex problems related to drug discovery, healthcare, financial risk analysis, and more.

Future Roadmap
As QC has a steep learning curve and building in-house competence is time consuming, big companies need to start working toward adopting QC as soon as possible, if they have not already started. They could start by determining how QC would impact some of their specific use cases and how long it would take to realize or implement QC. Over the next 12–18 months, companies could undertake the tasks shown in the figure below.

Based on an initial analysis, companies could evaluate the expected timing for quantum advantage for their specific use case and the corresponding business value, which they can use to decide the next possible steps:

  • Observe the field (longer expected timing and low business value): Periodically monitor the QC ecosystem and analyze the business potential
  • Follow active entities (longer expected timing, but high business value): Gain experience in QC by participating in QC communities, groups, or networks
  • Collaborate with QC leaders (shorter expected timing, but low business value): Lead own effort by engaging with the QC ecosystem
  • Lead the field (shorter expected timing and high business value): Build a superior network by launching new offerings

Any company across any industry can make use of the preceding guidelines to establish themselves in the field of QC. For example, a company operating in the oil and gas industry, interested in a driverless supply chain, could align its objectives with those of QC. It could use the previously mentioned framework to create a strategy to apply QC by determining the processes that need to be optimized from reservoir-to-end-customer (such as extraction or transportation); evaluating the limitations of the current optimization for each supply chain siloed process; estimating the potential untapped value for each separate, locally optimized process; and visualizing how an ideal end-to-end supply chain system would look, among other things.