All use cases
Energy & R&D

Drug discovery & molecular ground-state estimation

Ground-state energy estimation for candidate molecules, with R&D direction kept as confidential as the IP it is.

Who
A pharmaceutical or materials R&D team studying candidate molecules.
The problem
Computing the ground-state energy of candidate molecular conformations to identify stable structures, binding affinities, or reaction pathways. The exponential scaling of classical methods limits accessible molecule sizes.
What ArcaQ does
VQE on the molecular Hamiltonian, with the in-enclave model constructing the Hamiltonian from molecular specifications and interpreting the resulting energy and wavefunction data.
Expected result (published benchmarks)
Chemical accuracy on small molecules (H2, LiH, BeH2) is demonstrated today at 4–12 qubits; accessible molecule sizes grow with quantum hardware scale. Practical value today is in benchmarking methods and exploring novel ansatz designs.
Why confidentiality matters
Molecular candidates, target indications, and R&D direction are among the highest-value intellectual property in pharma and materials science. They never leave attested compute.
Tier fit
Reserve or Grand Reserve.

The performance ranges below are drawn from published academic and industry benchmarks for the relevant problem class — QAOA portfolio-optimization studies, VQE chemistry benchmarks, and quantum-annealing logistics case studies. They are not ArcaQ measurements. Results vary substantially with problem size, constraint density, and the specific algorithm and hardware used. ArcaQ-specific results will be published after hardware validation.

Drug discovery & molecular ground-state estimation — ArcaQ