![Enter Quantum logo Enter Quantum logo](https://eu-images.contentstack.com/v3/assets/blt31d6b0704ba96e9d/blt6516d97fe52975ba/6553b0184599ef040ae0a67d/EnterQuantum_Primary_Logo_OnLight_RGB.png?width=700&auto=webp&quality=80&disable=upscale)
Connects decision-makers and solutions creators to what's next in quantum computing
HPE, Classiq Develop Quantum Hybrid Optimization Method
The approach aims to make solving real-world problems using quantum computing more accessible via data centers
![Blue-lit data center racks Blue-lit data center racks](https://eu-images.contentstack.com/v3/assets/blt31d6b0704ba96e9d/bltf04cc451dd25e703/6572154094499d0407960b32/Data_Center_GettyImages-160000854.jpg?width=1280&auto=webp&quality=95&format=jpg&disable=upscale)
Hewlett Packard Enterprise (HPE) and quantum software company Classiq have developed a new method of combining classical high-performance computing (HPC) with quantum computing to solve complex optimization problems faster than either alone.
Large-scale combinatorial optimization problems seek an optimal solution from a set of possible candidates. Examples include the “traveling salesman problem” (finding the best route between a number of points) and the “knapsack problem” (best filling an available space with objects.)
They are extensively used in logistics and supply chain optimization. However, they get exponentially more complex as more factors are added and taking into account all possible options soon becomes intractable by classical computers alone.
As quantum computers become more capable, researchers are trying to find the best way of integrating them with classical HPC to solve important real-world optimization problems.
Classiq and Hewlett Packard Labs, the central research community of HPE, have developed a hybrid approach that combines classical and quantum algorithms to achieve better results.
Their method uses the HPE Cray Supercomputing EX system with the HPE Cray Programming Environment and Classiq’s quantum synthesis engine to develop a type of hybrid algorithm known as quantum approximate optimization algorithm (QAOA).
This method uses smaller problems to find an optimal approach for large-scale optimization challenges by merging classical and quantum algorithms.
According to HPE and Classiq, this method demonstrates a significant improvement in solving real-world problems efficiently. It could represent a step towards integrating quantum computing into mainstream applications via HPC data centers.
“This collaboration is a testament to the power of combining cutting-edge quantum and classical computing technologies,” said Classiq CEO Nir Minerbi.
“We are incredibly proud of the work we have done together, which not only showcases the potential of hybrid computation but also demonstrates tangible efficiency improvements.”
HPE’s venture capital program, Hewlett Packard Pathfinder, invested in Classiq in 2022.
About the Author
You May Also Like