Recent advances in quantum machine learning and quantum state embedding are integrated, providing a resource efficient framework for solutions of linear systems on Noisy Intermediate Scale Quantum (NISQ) machines. A divide and conquer algorithm is used to embed the indexing vector after which the Coherent Variational Quantum Linear Solver (CVQLS) algorithm is used to invert the problem matrix. This integrated procedure has an improved complexity scaling in the quantum resources needed to execute and produces solutions which agree with what is found classically.
2D perovskites have broad technological appeal because of their tunable mechanical, optical, and electrical properties. For flexible optoelectronic applications, it is necessary to determine how mechanical stresses affect their optoelectronic properties. We compare the impact of strain on the photoluminescence (PL) spectra and charge carrier recombination rates of two different 2D perovskite materials, synthesized using either phenethylammonium or butylammonium cations. Both perovskite materials exhibit strong PL enhancement, redshifts of the PL emission wavelength, and longer recombination lifetimes for compressive strains of ≲1%. These results are discussed in relation to the materials’ band structures and trap states.
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