Insider Brief
- Qunova Computing has made its HI-VQE hybrid quantum-classical chemistry algorithm available on AWS Marketplace, enabling users to run advanced chemistry applications through Amazon Braket on multiple quantum hardware platforms.
- The hardware-agnostic HI-VQE algorithm targets complex molecular modeling and materials simulation problems and has been validated across several quantum modalities on systems with up to 56 qubits.
- Qunova is offering subscription and usage-based pricing options and plans to demonstrate quantum advantage for advanced chemistry computations using HI-VQE in the near term.
PRESS RELEASE — Qunova Computing, a developer of software applications designed with the goal of bringing quantum advantage to the chemical, pharmaceutical, and industrial engineering sectors, today announced that its HI-VQE algorithm is now available on AWS Marketplace. This distribution channel expands HI-VQE’s reach to thousands of potential users and provides convenient access to Amazon Braket, AWS’s fully managed quantum computing service that supports multiple quantum processors, including IonQ, IQM, QuEra, AQT, and Rigetti.
HI-VQE is designed to solve complex chemistry problems used in pharmaceuticals, materials science, petrochemicals, and related industries. These applications include molecular modeling and materials reaction simulation, among others. The algorithm uses a hybrid approach that combines classical and quantum computing, leveraging the strengths of each while circumventing the limitations of both. This enables users to tackle highly complex computations that remain beyond the reach of classical computing alone, offering a tangible quantum advantage for industrial users.
“We have consistently shown that HI-VQE delivers value for users in the fields of chemistry, materials science, and related sectors,” said Kevin Rhee, CEO and founder of Qunova Computing. “AWS has recognized this and elected to make our product available to its large user base as it continues to enhance its offering in the quantum space. This is another proud moment for our company. This vote of confidence from AWS represents further evidence that HI-VQE delivers. We thank the team at AWS for their confidence as we continue our quest to deliver real quantum advantage to our users.”
Qunova’s HI-VQE algorithm is hardware-agnostic and has demonstrated consistent results across multiple quantum computing modalities. Its availability through AWS’s quantum service significantly expands both the pool of users with access to the algorithm and the range of quantum computers available for execution. AWS customers can now discover, purchase, and deploy HI-VQE directly within their AWS accounts, streamlining integration with existing workflows. The algorithm can also be integrated into broader professional service offerings available through the AWS ecosystem. Industrial users, researchers, and other stakeholders can access the Marketplace autonomously, making HI-VQE one of the most accessible quantum computing algorithms available for advanced chemistry computations.
To further support adoption, Qunova is offering a range of pricing plans, including annual subscriptions, pay-as-you-go options, and custom subscription plans for short-term projects. Over the past year, the company has validated its capabilities across multiple quantum modalities on systems with up to 56 qubits. Qunova is also introducing a new algorithm designed to solve optimization problems with up to 100,000 combinatorial variables on today’s noisy intermediate-scale quantum (NISQ) computers. Both algorithms provide significant value for industries that require highly complex computational solutions.
Qunova expects to demonstrate quantum advantage for advanced chemistry computations using HI-VQE within the coming weeks. The algorithm’s effectiveness stems from its hybrid quantum-classical design, which reduces resource demands while improving processing speed and delivering chemical accuracy.
Click here for a brief demonstration of how to use the HI-VQE algorithm through AWS Marketplace.
