At Company QNS We Deliver Quantum Algorithm For a Solution TO Specific Problems In Material Sciences Throughout The OpenVQA

PACKAGE : Custom Quantum Algorithms: Tailored implementations of Variational Quantum Eigensolvers (VQE), Quantum Phase Estimation (QPE), and unitary coupled cluster (UCC) & other possible techniques for simulating molecular and condensed matter systems. Our Work concerns: 

Hybrid Quantum-Classical Workflows

 Optimized frameworks combining classical numerical methods (e.g., DFT, GW) with quantum subroutines to push the limits of computational performance. 

Cloud-Based Simulation Platforms

Seamless integration with quantum hardware providers (IBM Q, IonQ, Rigetti) and simulation backends for testing and deployment Applications. 

Battery Materials

 Design of next-generation electrode and electrolyte compounds with enhanced ionic transport and chemical stability.

Quantum Catalysis

 Modeling of reaction mechanisms and activation energies to engineer more efficient catalytic systems.

Superconductors and Magnetic Materials

Accurate prediction of emergent quantum phenomena using many-body quantum simulation techniques.

References

Our solutions are informed by and built upon the most advanced theoretical developments in quantum computing and quantum chemistry, including:
• McArdle et al., “Quantum computational
chemistry” (Rev. Mod. Phys., 2020) • Cao et al., “Quantum Chemistry in the Age of Quantum Computing” (Chem. Rev., 2019)
• Bauer et al., “Quantum Algorithms for Quantum Chemistry and Quantum Materials Science” (Chem. Rev., 2020)