Hybridizing Light and Matter - Implications for Material and Molecular Sciences -

Thomas W. Ebbesen

Szilárd Szőke, Hanzhe Liu, Bryce P. Hickam +2 more

Entangled photons exhibit non-classical light–matter interactions that create new opportunities in materials and molecular science.

Dipankar Bhattacharyya, Jyotirmoy Guha

Felipe Herrera, William L. Barnes

Room-temperature cavity quantum electrodynamics with molecular materials in optical cavities offers exciting prospects for controlling electronic, nuclear and photonic degrees of freedom for applications in physics, chemistry and materials science. However, achieving strong coupling with molecular ensembles typically requires high molecular densities and substantial electromagnetic-field confinement. These conditions usually involve a significant degree of molecular disorder and a highly structured photonic density of states. It remains unclear to what extent these additional complexities modify the usual physical picture of strong coupling developed for atoms and inorganic semiconductors. Using a microscopic quantum description of molecular ensembles in realistic multimode optical resonators, we show that the emergence of vacuum Rabi splitting in linear spectroscopy is a necessary but not sufficient metric of coherent admixing between light and matter. In low-finesse multi-mode situations, we find that molecular dipoles can be partially hybridized with photonic dissipation channels associated with off-resonant cavity modes. These vacuum-induced dissipative processes ultimately limit the extent of light-matter coherence that the system can sustain.This article is part of the theme issue 'The quantum theory of light'.

David W. Ball

Malik Khalid

Purpose: The aim of the study was to assess the influence of quantum computing algorithms on molecular simulations in material science in Pakistan. Materials and Methods: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The study found that traditional classical computing methods often struggle with the complex and large-scale calculations required to simulate molecular interactions and properties, leading to approximations that can limit the precision of predictions. Quantum algorithms, particularly those based on quantum annealing and variational quantum eigensolver (VQE), offer the ability to process vast amounts of data simultaneously, making them highly effective for solving problems involving quantum states of matter. Studies have demonstrated that quantum computing can achieve a higher degree of accuracy in predicting molecular structures, reaction mechanisms, and material properties compared to classical approaches. Additionally, quantum computing can significantly reduce the time required for these simulations, thereby accelerating the development of new materials and technologies. Implications to Theory, Practice and Policy: Computational complexity theory, quantum information theory and algorithmic information theory may be used to anchor future studies on assessing the influence of quantum computing algorithms on molecular simulations in material science in Pakistan. In the realm of practical applications, the development of robust quantum computing infrastructure is essential for realizing the full potential of quantum algorithms in molecular simulations. Policymakers have a crucial role in supporting the research and development of quantum computing technologies, particularly in their application to material science.