Quantum Computing Inc. (QCI) has announced a software package called QGraph that helps to analyze problems specified as graphs, a collection of nodes and vertices. These types of problems are very common in logistics problems in areas such as route optimization, package delivery services, network optimization, sales intelligence and many others. To solve this type of problem the QGraph package coverts a problem specified as a graph to a constrained optimization problem and then submits it to QCI’s previously announced Qatalyst software which can solve constrained optimization problems on a variety of different computers, both classical and quantum.
One of the biggest challenges for getting end users to utilize quantum computers for their real world problems is that quantum software requires completely different programming models and algorithms than classical computers. One cannot simply take an old classical program, recompile it for use with a quantum backend and have it run significantly faster, like they can do when changing to a different brand of microprocessor. Traditionally, end users have had to learn programming quantum algorithms at the gate level and learn about Hadamard gates, CNOT gates, and all the other low level techniques to create programs that could run on a quantum machine.
More recently, the industry is working to make it much easier for end users to take advantage of quantum, by starting to offer higher level interfaces and programming libraries, automatic optimizers and other techniques so speed the path from problem identification to solution. The ideal would be to have an end user just specify their problem and have the quantum hardware and software system figure out the best way to solve it and provide a good solution. IBM has a term for this called “frictionless quantum computing” and QCI is working to achieve this with their software offerings.