250+ Early Quantum Applications

Inadequately planned factory layouts can lead to higher operational costs. The planning process is time-consuming and multiple planning parameters must be considered simultaneously, leading to large solution spaces. Automated planning approaches can support the planning team in the early phases of layout planning by generating layout variants that can afterwards be further specified. Recent studies from other disciplines have shown the potential of Quantum Annealing (QA) to solve complex assignment problems within seconds. Consequently, this paper presents a first implementation of a QA-based layout planning approach and demonstrates its advantages regarding scalability, solution quality, and computing time.

With the increase of intermittent renewable generation resources feeding into the electrical grid, Distribution System Operators (DSOs) must find ways to incorporate these new actors and adapt the grid to ensure stability and enable flexibility. Dividing the grid into logical clusters entails several organization and technical benefits, helping overcome these challenges. However, finding the optimal grid partitioning remains a challenging task due to its complexity. Learn how E.ON, a leading German utility company, approached this hard problem with D-Wave technology.

With the increase of intermittent renewable generation resources feeding into the electrical grid, Distribution System Operators (DSOs) must find ways to incorporate these new actors and adapt the grid to ensure stability and enable flexibility. Dividing the grid into logical clusters entails several organization and technical benefits, helping overcome these challenges.However, finding the optimal grid partitioning remains a challenging task due to its complexity. At the same time, a new technology has gained traction in the last decades for its promising speed-up potential in solving non-trivial combinatorial optimization problems: quantum computing. This work explores its application in Graph Partitioning using electrical modularity. We benchmarked several quantum annealing and hybrid methods on IEEE well-known test cases. The results obtained for the IEEE 14-bus test case show that quantum annealing DWaveSampler brings equal solutions or, for the optimal number partitions, a 1% improvement. For the more significant test cases, hybrid quantum annealing shows a relative error of less than 0.02% compared to the classical benchmark and for IEEE 118-bus test case shows time performance speed-up. The increment in performance would enable real time planning and operations of electrical grids in real time. This work intends to be the first step to showcase the potentials of quantum computing towards the modernization and adaption of electrical grids to the decentralized future of energy systems.

With the increase of intermittent renewable generation resources feeding into the electrical grid, Distribution System Operators (DSOs) must find ways to incorporate these new actors and adapt the grid to ensure stability and enable flexibility. Dividing the grid into logical clusters entails several organization and technical benefits, helping overcome these challenges.However, finding the optimal grid partitioning remains a challenging task due to its complexity. At the same time, a new technology has gained traction in the last decades for its promising speed-up potential in solving non-trivial combinatorial optimization problems: quantum computing. This work explores its application in Graph Partitioning using electrical modularity. We benchmarked several quantum annealing and hybrid methods on IEEE well-known test cases. The results obtained for the IEEE 14-bus test case show that quantum annealing DWaveSampler brings equal solutions or, for the optimal number partitions, a 1% improvement. For the more significant test cases, hybrid quantum annealing shows a relative error of less than 0.02% compared to the classical benchmark and for IEEE 118-bus test case shows time performance speed-up. The increment in performance would enable real time planning and operations of electrical grids in real time. This work intends to be the first step to showcase the potentials of quantum computing towards the modernization and adaption of electrical grids to the decentralized future of energy systems.

In this paper we propose a hybrid quantum-classical algorithm for dynamic portfolio optimization with minimal holding period. Our algorithm is based on sampling the near-optimal portfolios at each trading step using a quantum processor, and efficiently post-selecting to meet the minimal holding constraint. We found the optimal investment trajectory in a dataset of 50 assets spanning a one year trading period using the D-Wave 2000Q processor. Our method is remarkably efficient, and produces results much closer to the efficient frontier than typical portfolios. Moreover, we also show how our approach can easily produce trajectories adapted to different risk profiles, as typically offered in financial products. Our results are a clear example of how the combination of quantum and classical techniques can offer novel valuable tools to deal with real-life problems, beyond simple toy models, in current NISQ quantum processors.

Digital transformation is altering our lives in many positive ways. This acceleration of digital transformation, however, has also led to an increased potential risk in identity fraud, as well as social engineering and data theft to businesses, consumers and the broader ecosystem. In this talk, learn how PayPal is tapping advances in quantum computing to innovate on feature selection, a critical step in building powerful models to fight sophisticated fraud.

In this session, the an Mphasis expert will discuss how quantum computing can reduce the execution time for algorithms, achieve better accuracy, identify complex patterns in data to improve accuracy, and help solve complex problems. It will also showcase live quantum computing demos running on quantum hardware to solve targeted industry challenges.

NEC Australia and D-Wave were selected by the Australian Department of Defence to demonstrate the use of hybrid quantum computing technology to solve a “last mile resupply” problem. The technology optimised how autonomous vehicles were used to resupply army forces from a central base. A live demonstration is included in this talk.

Urban Air Mobility (UAM) has been envisioned as a technology that utilizes automated air transportation services to carry people or cargo at lower altitudes in and around urban areas. In this talk, experts from Sumitomo, OneSky Systems, and Tohoku University formulate the problem of discovering the safe and short routes for multiple aircraft to fly as quadratic forms and present a dynamic route planning algorithm for time-dependent simultaneous flight requests.

In this talk, hear a summary of current practices in asset liability modelling (ALM) within the insurance sector and an insight into what ALM may be like in the immediate future by demonstration of how quantum annealing can be used for ALM.

Modelling behaviors in networks is highly complicated but essential for understanding dynamics of the current world, especially the adoption of new technologies. In this talk, experts from Bank of Canada and Multiverse Computing extend Jackson and Watts (2002) to study how firms located in a trade network adopt cryptocurrency as a method of payment

Molecular Docking is an important step of the drug discovery process which aims at calculating the preferred position and shape of one molecule to a second when they are bound to each other. Using D-Wave's quantum system, results and performances are compared with state of art classical solvers.