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Recent advancements in quantum information and quantum technology have stimulated a good deal of interest in the development of quantum algorithms toward the determination of the energetics and properties of many-fermionic systems. While the variational quantum eigensolver is the most optimal algorithm in the noisy intermediate scale quantum era, it is imperative to develop compact Ansätze with low-depth quantum circuits that are physically realizable in quantum devices. Within the unitary coupled cluster framework, we develop a disentangled Ansatz construction protocol that can dynamically tailor an optimal Ansatz using the one- and two-body cluster operators and a selection of rank-two scatterers. The construction of the Ansatz may potentially be performed in parallel over multiple quantum processors through energy sorting and operator commutativity prescreening. With a significant reduction in the circuit depth toward the simulation of molecular strong correlation, our dynamic Ansatz construction protocol is shown to be highly accurate and resilient to the noisy circumstances of the near-term quantum hardware.
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http://dx.doi.org/10.1063/5.0153182 | DOI Listing |
J Clin Exp Hepatol
August 2025
Dept of Histopathology, PGIMER, Chandigarh, 160012, India.
Artificial intelligence (AI) is a technique or tool to simulate or emulate human "intelligence." Precision medicine or precision histology refers to the subpopulation-tailored diagnosis, therapeutics, and management of diseases with its sociocultural, behavioral, genomic, transcriptomic, and pharmaco-omic implications. The modern decade experiences a quantum leap in AI-based models in various aspects of daily routines including practice of precision medicine and histology.
View Article and Find Full Text PDFFront Comput Neurosci
August 2025
Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States.
Artificial neural networks are limited in the number of patterns that they can store and accurately recall, with capacity constraints arising from factors such as network size, architectural structure, pattern sparsity, and pattern dissimilarity. Exceeding these limits leads to recall errors, eventually leading to catastrophic forgetting, which is a major challenge in continual learning. In this study, we characterize the theoretical maximum memory capacity of single-layer feedforward networks as a function of these parameters.
View Article and Find Full Text PDFRSC Adv
September 2025
Department of Physics, University of Hull Cottingham Road UK
[This corrects the article DOI: 10.1039/D5RA04583E.].
View Article and Find Full Text PDFRSC Adv
September 2025
Instituto de Ciencia de Materiales de Madrid, ICMM-CSIC C/Sor Juana Inés de la Cruz, 3 Madrid 28049 Spain
Perovskite light-emitting diodes (PeLEDs) have emerged as a promising technology for next-generation display and lighting applications, thanks to their remarkable colour purity, tunability, and ease of fabrication. In this work, we explore the incorporation of plasmonic spherical nanoparticles (NPs) directly embedded into the green-emitting CsPbBr perovskite layer in a PeLED as a strategy to enhance both its optical and electrical properties. We find that plasmonic effects directly boost spontaneous emission while also influencing charge carrier recombination dynamics.
View Article and Find Full Text PDFJ Phys Chem C Nanomater Interfaces
October 2024
Department of Chemistry and Biochemistry, Nanoscale & Quantum Phenomena Institute, Ohio University, Athens, Ohio 45701, United States.
Carbon-based quantum dots (CQDs) have been around for a few decades. Low cell toxicity, good water solubility, excellent and tunable fluorescence properties, and the ability to dope and modify the surface of these CQDs make them an incredible choice for the visualization and treatment of various cancers. This perspective analyzes some recent progress on size-color correlation, modification, and cancer treatment applications of CQDs.
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