A recent publication from IBM titled ‘The Quantum Decade, A playbook for achieving awareness, readiness and advantage’ is a 140 page analysis of the ‘weird but wonderful realm of quantum mechanics’ and how harnessing the power of qubits should allow future quantum computers to perform more powerful computations than traditional computers. IBM expects practical applications that exhibit the ‘quantum advantage’ in this decade with widespread adoption expected by 2030. It’s all about the number of qubits. In 2020, the state of the art in quantum computing was an IBM system with 65 qubits. A 1,000 qubit machine is forecast for 2023.
BP’s VP Digital Technology Richard Debney believes that, ‘Moore’s Law is coming to an end and classical computing is reaching its limits just as our demand [for compute power] is starting to surge.’ To harness the power of quantum computers, programming needs to adapt. As Debney explained, ‘Quantum computing is not just an expansion of classical computing. We can’t just port problems to quantum computers. We need to break them down and build communities that can effectively apply this technology to the right problems.’
Last year IBM identified a potential use for quantum computing in deep learning, using ‘quantum kernels’ to solve ML problems that are hard for classical methods. Woodside Energy is working with IBM’s quantum researchers to investigate practical applications of quantum kernels in machine learning workflows. The ongoing research, a ‘pathfinder project’ for Woodside, addresses, inter alia, petrophysical analysis of well log data.
Another focus for quantum research is materials discovery, in pharmaceuticals and petroleum refinery catalysis. Here Doug Kushnerick, formerly with ExxonMobil Research says, ‘[Today] the materials discovery process is unbearably slow. Companies don’t have time to experiment endlessly. Quantum computing can give us an exponential leap in discovery.’ ExxonMobil is also investigating the use of quantum computing to optimize journeys of its tanker fleet, a problem which, at-scale is said to be ‘intractable’ for classical computers. This led ExxonMobil to join the IBM Quantum Network to get access to advanced quantum computing systems and tools including the open source Qiskit quantum optimization module to test quantum algorithms. The outcome? ‘Depending on the aspects of the problem, some heuristic quantum algorithms performed slightly better than others, and variational quantum eigensolver-based optimization performed better depending on the choice of the ansatz.’ So there you have it!
Heightened expectations of quantum computing are evidenced in a paper on the EOS website where researchers Annarita Giani (General Electric Research) and Zachary Goff-Eldredge (US Department of Energy) explain how quantum computing can tackle climate and energy challenges. Climate modeling, in particular, ‘simulating the nuanced effects of ever-shifting clouds on climate’, is apparently ‘proving intractable to classical computing’ . Quantum computing may be able to solve the nonlinear differential equations that are key for working on fluid dynamics problems. We have asked the authors if this means that they are calling into question the current climate model from the IPCC. So far no reply!
© Oil IT Journal - all rights reserved.