It’s been a research subject for more than three decades; however, scientists and engineers had difficulty building an actual quantum computer.
That’s changed. In the last five years, we’ve seen hardware and software capability move out of university labs and into real-world business products. Still, the technology needs to mature to become fully enterprise-ready and deliver meaningful, cost-effective results.
Accenture Labs examines the science behind quantum computing, potential use cases by industry and recommended steps for business leaders who want to be best positioned when this emerging technology reaches maturity.
Information representation—In classical computing, a computer runs on bits that have a value of either 0 or 1. Quantum bits, or “qubits,” are similar, in that for practical purposes, we read them as a value of 0 or 1, but they can also hold much more complex information, or even be negative values.
Information processing—In a classical computer, bits are processed sequentially, which is similar to the way a person would solve a math problem by hand. In quantum computation, qubits are entangled together, so changing the state of one qubit influences the state of others regardless of their physical distance. This allows quantum computers to intrinsically converge on the right answer to a problem very quickly.
Interpreting results—In classical computing, only specifically defined results are available, inherently limited by algorithm design. Quantum answers are probabilistic, meaning that because of superposition and entanglement, multiple possible answers are considered in a given computation. Problems are run multiple times, giving a sample of possible answers and increasing confidence in the best answer provided.
Research partnerships between large companies and top universities are forming, most notably Google and the University of California-Santa Barbara; Lockheed Martin and University of Maryland; and Intel and Delft University of Technology.
Governments around the world are forging ahead with quantum computing initiatives as well:
Australia’s government in early 2016 announced an AUD$25 million investment over five years toward the development of a silicon quantum integrated circuit.
The United States, based on a 2016 report from the National Science and Technology Council, “recommends significant and sustained investment in quantum information science by engaging with academia, industry and government.”
The European Commission plans to launch a $1.13 billion project in 2018 to support a range of quantum technologies.
Quantum computing is best suited to solving problems using three types of algorithms: optimization, sampling and machine learning.
In collaboration with 1QBit, Accenture Labs has mapped 150+ use cases for quantum computing with a focus on finding those that are the most promising in various industries.
The goal was to identify and validate the problems where a quantum algorithm will outpace existing computing methods and improve results.
Portfolio risk optimization and fraud detection.
Protein folding and drug discovery.
Supply chain and purchasing.
Asset degradation modeling and utility system distribution optimization.
MEDIA AND TECHNOLOGY
Advertising scheduling and ad revenue maximization systems.
You can start by learning more about the fast-evolving market, identifying where quantum will impact the business and preparing with quantum-ready applications.
We’re already experimenting with clients to help them gain unique insights into how quantum computing can be applied to their enterprises.
Those who move ahead with experimentation and innovation will be prepared to capitalize on opportunities that the quantum revolution is sure to bring.