Quantum Computing Inc Debuts QGraph Platform

Quantum Computing Inc, a leader in bridging the power of classical and quantum computing, is introducing QGraph, which analyzes graphs (i.e., collections of vertices and edges) with QCI’s cloud-based Qatalyst ready-to-run quantum software.

QGraph together with Qatalyst enables users and analysts to solve the most computationally expensive graph problems—the kind that can benefit the most from quantum computing, that are essential for understanding high-dimensional data in fast moving contexts, and that to date have been prohibitively expensive to compute in practice—quickly and cost-effectively on both classical (CPU) and quantum (QPU) computers.

As part of Qatalyst, QGraph performs the most challenging graph kernels via the powerful Q API, transforms input graphs into constrained optimization problems, and then delivers them to the Qatalyst Core computational engine for CPU and/or QPU processing. The process employs quantum-ready techniques that fuel increases in accuracy and deliver a diversity of valuable results.

Graphs offer a powerful way to analyze heterogeneous data that has many dimensions, is unstructured and has sparse values across all variables. Graphs are also often used to model networks, such as social, metabolic, gene and transportation, as well as molecular structures.

Other business use cases of graph analytics include air traffic control and route optimization for efficiency and lowering fuel consumption. Retailers use graph analytics to determine what products are frequently purchased together and by what type of customer, enabling better marketing and sales intelligence. Healthcare and pharmaceutical companies use graph analytics when examining patient symptoms and outcomes for medical analysis and drug development.

“QGraph takes graph analytics to the next level, leveraging the power of quantum-ready constrained optimization to easily and more cost-effectively solve the most intractable problems,” said Robert Liscouski, CEO of QCI. “SMEs can continue to use well-known graph functions and constructs without any new programming, low-level coding, or changes to their models. We believe this capability makes our ready-to-run quantum software exceptionally valuable and unique.”

QGraph enables SMEs and programmers to work with familiar graphs and functions, including graph partitioning, minimum clique cover, and community detection.

After the graph is submitted to the Qatalyst API, which implements familiar NetworkX-type functions, QGraph automatically transforms the graph into a constrained optimization problem based on the specific requested function. The problem is then submitted to the Qatalyst Core for quantum transformation and processing. When results are returned, QGraph transforms and presents them back to the requesting workflow, application, or SME in a graph-relevant format.

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