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Quantum Phase Estimation (QPE) can yield the exact ground state energy of molecules, but current implementations still require a large number of qubits and quantum gates. In this talk, I will present QC Ware's recent work in partnership with Boehringer Ingelheim exploring current performance bottlenecks in QPE and how to improve them. First, QPE requires the efficient preparation of a state with high overlap with the targeted eigenstate. We show how classical pre-processing can yield to a significant increase in this overlap without requiring any quantum resources, thereby boosting the success probability of the algorithm. Second, the quantum resources required by QPE depend on the Hamiltonian 1-norm. We introduce a hierarchy of symmetry-aware spectral bounds on the 1-norm which limit the maximum performance of QPE. In the third part of the talk, we introduce a symmetry-aware Hamiltonian compression algorithm and present numerical results showing decreased quantum resource requirements compared to previous art. I will conclude by reviewing some recent results in the literature in the same direction. Bio: Jérôme Gonthier obtained his PhD in theoretical chemistry at EPFL, Lausanne (Switzerland) with Prof. Corminboeuf studying intermolecular interactions. He then moved to the USA for a post-doc, first at GeorgiaTech with Prof. Sherrill and then at U.C. Berkeley with Prof. Head-Gordon. During this time, he studied various methods to decompose intermolecular interactions into physical components. In 2019, he moved to the quantum computing industry, working with customers to find how to best apply quantum computing technology to their chemistry problems. He is now leading the quantum computing team for chemistry and materials applications at QC Ware. Host: Akram Touil (T-4) |