QC-SQUARED
Forskningsprojekt, 2022 – 2025

Quantum computing has the potential to provide an exponential speedup compared to classical computers, but the practical
implementation is still in its infancy. Two central questions are: (1) in which field the current noisy intermediate-scale quantum (NISQ)
hardware can provide benefits compared to classical computers and (2) which methods and algorithms enable this advantage? The aim
of this project is to answer these questions by enabling accurate and efficient Quantum Chemistry calculations on current and near-
term Quantum Computers for relevant chemical and physical problems. This paves the road to simulate strongly correlated electron
systems of high scientific and economical interest, where accurate approaches are needed to understand groundbreaking chemical and
physical phenomena, like high-temperature superconductivity, photosynthesis or nitrogen fixation. It will be achieved by developing and implementing novel quantum algorithms based on the combination of the transcorrelated (TC) method and a complete active space self-
consistent field (CASSCF) embedding approach. The TC method will reduce the necessary quantum resources by providing accurate
results for a small strongly correlated region already with small basis sets. While CASSCF will allow to target more realistic systems
by embedding the correlated region self-consistently in a larger environment, which is efficiently described by inexpensive mean-field
approaches. This project has the potential to go beyond the state-of-the-art by: (a) pushing the boundaries of currently possible quantum
chemical calculations, allowing further theoretical understanding and practical design of quantum materials and (b) pave the road toward
scientific and economical relevance of quantum computing already in the NISQ era.

Deltagare

Martin Rahm (kontakt)

Chalmers, Kemi och kemiteknik, Kemi och biokemi

Samarbetspartners

IBM Research

Rüschlikon, Switzerland

Finansiering

Europeiska kommissionen (EU)

Projekt-id: EC/HE/101062864
Finansierar Chalmers deltagande under 2022–2025

Publikationer

2023

Optimizing Jastrow factors for the transcorrelated method

Artikel i vetenskaplig tidskrift

Mer information

Senast uppdaterat

2022-08-30