Simulating Non-Markovian Dynamics in Multidimensional Electronic Spectroscopy via Quantum Algorithm

Journal of Chemical Theory and Computation, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 25, 2024

Including the effect of molecular environment in numerical modeling time-resolved electronic spectroscopy remains an important challenge computational spectroscopy. In this contribution, we present a general approach for simulation optical response multichromophore systems structured and its implementation as quantum algorithm. A key step procedure is pseudomode embedding system-environment problem resulting finite set states evolving according to Markovian master equation. This formulation then solved by collision model integrated into algorithm designed simulate linear nonlinear functions. The workflow validated simulating spectra prototypical excitonic dimer interacting with fast (memoryless) finite-memory environments. results demonstrate, on one hand, potential dynamical features spectroscopy, including lineshape, spectral diffusion, relaxations along delay times. On other explicit synthesis circuits provides fully protocol harnessing efficient many-body dynamics promised future generation fault-tolerant computers.

Language: Английский

Modeling Heterogeneous Catalysis Using Quantum Computers: An Academic and Industry Perspective

Journal of Chemical Information and Modeling, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 29, 2024

Heterogeneous catalysis plays a critical role in many industrial processes, including the production of fuels, chemicals, and pharmaceuticals, research to improve current catalytic processes is important make chemical industry more sustainable. Despite its importance, challenge identifying optimal catalysts with required activity selectivity persists, demanding detailed understanding complex interactions between reactants at various length time scales. Density functional theory (DFT) has been workhorse modeling heterogeneous for than three decades. While DFT instrumental, this review explores application quantum computing algorithms catalysis, which could bring paradigm shift our approach interfaces. Bridging academic perspectives by focusing on emerging materials, such as multicomponent alloys, single-atom catalysts, magnetic we delve into limitations capturing strong correlation effects spin-related phenomena. The also presents their applications relevant showcase advancements field. Additionally, embedding strategies where handle strongly correlated regions, while traditional chemistry address remainder, thereby offering promising large-scale modeling. Looking forward, ongoing investments academia reflect growing enthusiasm computing's potential research. concludes envisioning future seamlessly integrate workflows, propelling us new era computational reshaping landscape catalysis.

Language: Английский

Federated quantum machine learning for drug discovery and healthcare

Annual reports in computational chemistry, Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 1, 2024

Language: Английский