Making the best possible decisions is critical to the success of most businesses. This is particularly relevant today because companies have access to a large amount of high-quality data and they are interested in using this data to drive their decision making. The science of optimization can help businesses find the best solution among all possible solutions to maximize their performance and minimize their costs.
Many problems in finance take the form of mathematical optimization problems. As an example from portfolio optimization, an asset manager may be tasked with allocating funds across a pool of assets while maximizing the return at a given level of risk. However, conventional approaches often fail when computational resources cannot handle the amount of “noisy” real-world data (i.e., useful data that is corrupted or distorted by other, meaningless data), or extrapolating for missing data, or account for the correlations between all assets.
Quantum computing research and experimentation continues to make progress towards addressing complex computational problems. These include modelling systems in nature as they relate to chemistry and physics. Beyond this, quantum computing research has also shown promise in tackling problems in logistics and finance.