An easy to use cloud-based toolbox, called the Quantum Assisted Design (QAD) Cloud, will enable the simulation of molecules and materials, according to HQS Quantum Simulation.
The development of new materials requires the understanding of material properties at the atomic level, where the laws of physics are determined by quantum mechanics. Quantum mechanical bottom-up design of materials can give access to whole new properties and will unlock vast markets for new materials.
In the future the QAD Cloud will unlock currently impossible simulation capabilities by shifting from conventional to quantum computers.
Predictive simulations are key to the development of materials, as well as their application in structural design. Simulations are a powerful tool to decrease the time-to-market and decrease cost for R&D and product development cycles. The ability to develop new materials using simulation tools has been limited by the lack of sufficient computational power. Therefore, HQS provides a cloud-based solution that can help to master the demanding numerical tasks. In the future the QAD Cloud will unlock currently impossible simulation capabilities by shifting from conventional to quantum computers. All high-end quantum methods, like CASPT2 and DMFT, will be included in the QAD Cloud and quantum methods will be smoothly switched to quantum computers as soon as possible. While it will take a while for quantum computers to overtake existing methods, we intend to allow for the solution of small toy models on the AQT quantum computer.
The QAD Cloud currently provides the SCCE software package. SCCE enables the simulation of fermionic lattice models in 1D and 2D, using a self-consistent cluster-bath approach.
SCCE is a great tool to solve hard problems in highly correlated materials.
The platform uses Self Consistent Cluster Embedding (SCCE) to solve large periodic problems. In the SCCE approach, a lattice model is solved iteratively using a combined system which is divided into a fully interacting cluster coupled to a non-interacting bath. The simulation proceeds until the result is self-consistent. This approach is similar to Dynamical Mean-Field Theory (DMFT) and Density Matrix Embedding Theory (DMET). A detailed description of the method will be published in the near future.
The number of operations to simulate lattice models is relatively small while at the same time, simulating lattice models for strongly correlated systems is very challenging for classical computer. Therefore, we feel that this will be one of the first applications for quantum computers. — Michael Marthaler CEO of HQS Quantum Simulations
“Currently we solve strongly correlated lattice models using DMRG (Density Matrix Renormalization Group). However, no matter how optimized the method may be, classical computers are fundamentally limited”, says Michael Marthaler CEO of HQS Quantum Simulations. “The number of operations to simulate lattice models is relatively small while at the same time, simulating lattice models for strongly correlated systems is very challenging for classical computer. Therefore, we feel that this will be one of the first applications for quantum computers.”
The platform is currently in a beta version and HQS is actively working to expand its capabilities. Currently, each user is granted 100 credits per month, which should be sufficient to gain familiarity with the platform. While the SCCE online platform does not yet support the purchasing of additional credits, users who wish to test the software more extensively should contact HQS directly.
Our team is eager to learn which features would be most useful to our user base, so any feedback is highly encouraged. Depending on this user feedback, we would like to implement the following features in the future:
- Support for 3D lattices: While 3D lattices do not pose a fundamental challenge to the SCCE solver, in practice, the number of sites on a 3D lattice is typically large enough that available computational resources become a limitation.
- Access to the cloud-based tool via an API: In this way, the cloud-based tool can be used directly by calling an API in a python script.
- An automated mapping of real solids to lattice models.
- Support for complete active space (CAS) based methods for the simulation of molecules.
Several global organizations in chemical and pharmaceutical industries constantly face challenges to launch better products faster every year. Modelling and advanced simulation can significantly contribute to speed up the research and development process of companies.
HQS Quantum Simulations has been providing sophisticated services to our customers using advanced modeling and simulation-based techniques to solve challenging problems. Allowing our clients to already tap into the potential of simulations accelerated by quantum computers. With our simulation tools we widen the understanding of chemical and physical interactions which leads to better products and processes and faster development cycles for our customers.
