structure calculations: a cornerstone challenge in quantum chemistry and materials discovery. Harnessing the quantum-mechanical nature of molecular systems, our algorithms provide unmatched accuracy and scalability in predicting electronic properties essential to drug discovery, catalysis, energy storage, and molecular design.
Our mission is to revolutionize the modeling of molecular electronic structure through quantum-native algorithms, enabling scientists to simulate molecular systems with chemical accuracy that far exceeds the limits of traditional methods such as Hartree-Fock or Density Functional Theory (DFT).
we are committed to pushing the boundaries of molecular modeling. Our quantum-first approach empowers R&D teams across chemistry, biotech, and clean tech to explore new molecular landscapes with precision and speed that redefine possibility. We are building the quantum infrastructure for the chemistry of the future.
That Our work is rooted in the latest breakthroughs in quantum chemistry and quantum computing, including:
Cao et al., “Quantum Chemistry in the Age of Quantum Computing” (Chem. Rev., 2019)
• McArdle et al., “Quantum computational chemistry” (Rev. Mod. Phys., 2020) Kandala et al.,
“Hardware-efficient variational quantum eigensolver for small molecules and quantum magnets” (Nature, 2017).
Pharmaceutical Design: Accurate prediction of binding energies, conformational states, and electronic transitions for complex drug molecules.
Catalysis R&D: Modeling transition states and reaction intermediates in homogeneous and heterogeneous catalytic cycles.
Photovoltaics & Optoelectronics: Simulation of excited states and charge transfer mechanisms in organic semiconductors and dye-sensitized solar cells. Green
Chemistry: Exploring electron correlation in molecular systems for low energy reaction pathways and sustainable synthesis.
Advanced Quantum Algorithms: Implementation of Variational Quantum Eigensolvers (VQE), Quantum Phase Estimation (QPE), and qubit-efficient ansätze (e.g., ADAPT-VQE, UCCSD) to solve the Schrödinger equation for molecular systems.
Hybrid Quantum-Classical Workflows: Integration of quantum modules into existing classical pipelines (e.g., MP2, CCSD(T), and DFT) for multi-scale modeling and reaction prediction.
Automated Molecular Simulators: Quantum cloud software that automates basis set selection, ansatz construction, and active space determination for molecular systems.
QuantumNET Solutions is a distinguished network built on precision, scientific rigor, and agile collaboration-uniting deep expertise across technology, business, and science to deliver transformation impact!
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