Quantum Computing for Business Conference Highlights Early Enterprise Adoption
The Quantum Computing for Business Conference returned in-person to Santa Clara, California in December following a virtual event in 2020 due to travel constraints related to the ongoing COVID-19 pandemic. The three-day event featured presentations from dozens of companies across the quantum computing stack – some companies still navigating the practicability of back-to-office policies typically don’t attend in-person events in the meantime. .
As you’d expect from a conference called Quantum Computing for Business, or Q2B, real-world implementation stories were shared by hardware, software, and professional services companies to bolster business readiness. quantum computers, even in the noisy intermediate-scale quantum, or NISQ, era of computing hardware. This report examines a representative sample of use cases presented at the conference.
The prospect of breaking public key encryption is often cited as an example of the future of quantum computers, although it is a relatively negative setting – quantum computers could be used in positive ways to solve problems actual commercial activity in a number of industries, as evidenced by research project activity in a number of industries today. These projects are relatively time-consuming — QCWare Corp.the main organizer of the conference, notes that “advanced” customer projects can take six months from defining the use case to producing a report – and these examples are, typically, summaries of technical papers submitted to academic journals.
It is possible, perhaps likely, that current work in the field of quantum computing is relatively unknown; a transformative breakthrough may be closely watched until the resulting product or business process is well into production to protect a competitive advantage. Likewise, the quantum event horizon is quite broad: this industry is entering the decade of the NISQ era, with several companies focusing on early error-correcting quantum computers towards the end of the decade. That said, the ultimate expression of computing hardware – classical or quantum – is found in the software designed for it. Today, research into problems that can be solved by quantum computers is essential if quantum computers are to one day eclipse the capabilities of classical computers.
QC Ware and German pharmaceutical company Boehringer Ingelheim GmbH collaborated on a project simulating large-scale protein-ligand interactions using hybrid quantum-classical methodology. Their approach uses symmetry-adapted perturbation theory to directly calculate the interaction energy through direct expectation values, rather than calculating the ground state energy of the dimer and monomer systems separately and subtracting both to determine interaction energy, adapting to the capabilities of NISQ-era quantum computers. With classical post-processing, this approach is able to simulate systems with hundreds of atoms and potentially hundreds of basis functions in active space.
QC Ware and Swiss healthcare company Roche Holding AG also investigated the use of two different quantum neural network techniques for medical image classification – first using quantum circuits in training classical neural networks, and second in designing and training neural networks quantum orthogonals. While the researchers note that graphics processing units are extremely efficient at the underlying math (matrix-vector multiplication) in this process, they argue that studying quantum computing may also lead to new training methods. faster classics.
D-Wave Systems Inc. touted his work with a financial services provider PayPal Holdings Inc., bringing PayPal’s Director of AI Research, Vidyut Naware, to the stage to discuss D-Wave’s use of quantum annealing in monitoring fraudulent transactions using feature selection. PayPal claims to process more than $1 billion in user transactions daily, which makes any percentage improvement a valuable business; similarly, the nature of monitoring fraudulent transactions requires constant adaptation as criminals innovate new methods of fraud.
QC Ware and Goldman Sachs Inc. explored a method of amplitude estimation on quantum computers, which would provide quantum acceleration for Monte Carlo methods – useful in circumstances such as derivatives pricing and credit risk calculation. The experiment evaluated maximum likelihood estimation, or MLE, and the Chinese remainder theorem, or CRT, along with the depth-accurate MLE approach and the more noise-sensitive CRT approach.
Fujitsu Ltd. and the Hamburg Port Authority have collaborated on a project to reduce traffic congestion – and, by extension, CO2 emissions – by reducing downtime for ships, trucks and cars. The HPA has indicated up to 9% reduction in CO2 emissions and up to 15% reduction in travel time for cars and trucks in the supply chain. Route planning was performed on Fujitsu’s Digital Annealer 2 quantum-inspired hardware.
QC Ware and AISIN, a unit of Toyota Group, collaborated on a classical-quantum hybrid algorithm for solving vehicle routing problems, finding its performance competitive with the original classical approach. The researchers characterize it as a prototype that can be scaled up and as an avenue for further study on the role of quantum computing in reinforcement learning.
This article was published by S&P Global Market Intelligence and not by S&P Global Ratings, which is a separately managed division of S&P Global.