In this work, we combine several advances to electronic structure calculation for molecular systems, resulting in a 2-orders-of-magnitude speedup of estimated runtimes over prior-art algorithms run on comparable quantum devices…

Exploring low-cost applications is paramount to creating value in early fault-tolerant quantum computers. Here, we optimize both gate and qubit counts of recent algorithms for simulating the Fermi-Hubbard model…

Our latest research tackles one of quantum computing’s biggest challenges: making high-precision molecular simulations of observable estimation practical for future hardware.

Simulating complex dynamical systems—like plasma behavior, fluid flow, or coupled oscillators—is one of the biggest computational challenges in science and engineering. Classical computers struggle with these problems due to the curse of dimensionality: as systems grow larger and more complex, the computational resources required scale exponentially.

Traditional methods can estimate total interaction energies, but breaking these down into components such as electrostatics, exchange, induction, and dispersion provides valuable insight for rational drug design. Symmetry-adapted perturbation theory (SAPT) is a well-established method for this type of energy decomposition, though it can be computationally demanding for strongly correlated molecules.

Our recent paper introduces the first quantum algorithm for calculating SAPT observables on a fault-tolerant quantum computer. By combining tensor factorizations and block-encodings, the method achieves Heisenberg-limited precision and provides concrete resource estimates for benchmark molecules.