The focus of this Visualization Viewpoints article is to provide some background on quantum computing (QC), to explore ideas related to how visualization helps in understanding QC, and examine how QC might be useful for visualization with the growth and maturation of both technologies in the future. In a quickly evolving technology landscape, QC is emerging as a promising pathway to overcome the growth limits in classical computing. In some cases, QC platforms offer the potential to vastly outperform the familiar classical computer by solving problems more quickly or that may be intractable on any known classical platform. As further performance gains for classical computing platforms are limited by diminishing Moore's Law scaling, QC platforms might be viewed as a potential successor to the current field of exascale-class platforms. While present-day QC hardware platforms are still limited in scale, the field of quantum computing is robust and rapidly advancing in terms of hardware capabilities, software environments for developing quantum algorithms, and educational programs for training the next generation of scientists and engineers. After a brief introduction to QC concepts, the focus of this article is to explore the interplay between the fields of visualization and QC. First, visualization has played a role in QC by providing the means to show representations of the quantum state of single-qubits in superposition states and multiple-qubits in entangled states. Second, there are a number of ways in which the field of visual data exploration and analysis may potentially benefit from this disruptive new technology though there are challenges going forward.
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http://dx.doi.org/10.1109/MCG.2023.3316932 | DOI Listing |
J Chem Theory Comput
December 2024
Department of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, United States.
We present an application of our new theoretical formulation of quantum dynamics, moment propagation theory (MPT) (Boyer et al., J. Chem.
View Article and Find Full Text PDFJ Mol Model
December 2024
Departamento de Química, Universidad Autónoma Metropolitana-Iztapalapa, Avenida Ferrocarril San Rafael Atlixco, Número 186, Colonia Leyes de Reforma 1A Sección, Alcaldía Iztapalapa, Código Postal 09310, Ciudad de Mexico, Mexico.
Context: Antioxidants are known to play a beneficial role in human health. Caffeic acid has been previously recognized as efficient in this context. However, such a capability can be enhanced through structural modification.
View Article and Find Full Text PDFTomography
November 2024
Department of Diagnostic Radiology, Tokai University School of Medicine, 143 Shimokasuya, Isehara 259-1193, Japan.
Photon-counting detector computed tomography (PCD-CT) offers energy-resolved CT data with enhanced resolution, reduced electronic noise, and improved tissue contrast. This study aimed to evaluate the visibility of intracranial perforating arteries on ultra-high-resolution (UHR) CT angiography (CTA) on PCD-CT. A retrospective analysis of intracranial UHR PCD-CTA was performed for 30 patients.
View Article and Find Full Text PDFNanomaterials (Basel)
December 2024
Theoretical Physical Chemistry, UR MOLSYS, University of Liege, B4000 Liège, Belgium.
Dynamical symmetries, time-dependent operators that almost commute with the Hamiltonian, extend the role of ordinary symmetries. Motivated by progress in quantum technologies, we illustrate a practical algebraic approach to computing such time-dependent operators. Explicitly we expand them as a linear combination of time-independent operators with time-dependent coefficients.
View Article and Find Full Text PDFNanomaterials (Basel)
December 2024
High-Power Converter Systems (HLU), Technical University of Munich (TUM), 80333 Munich, Germany.
In this paper, a new label-free DNA nanosensor based on a top-gated (TG) metal-ferroelectric-metal (MFM) graphene nanoribbon field-effect transistor (TG-MFM GNRFET) is proposed through a simulation approach. The DNA sensing principle is founded on the dielectric modulation concept. The computational method employed to evaluate the proposed nanobiosensor relies on the coupled solutions of a rigorous quantum simulation with the Landau-Khalatnikov equation, considering ballistic transport conditions.
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