Results 141 to 150 of about 2,829,604 (309)
Quantum stochastic convolution cocycles II [PDF]
, 2008 Schurmann's theory of quantum Levy processes, and more generally the theory of quantum stochastic convolution cocycles, is extended to the topological context of compact quantum groups and operator space coalgebras.
Skalski, Adam G., Lindsay, J. Martin
core +1 more source
Boosting Classification with Quantum-Inspired Augmentations
CoRRUnderstanding the impact of small quantum gate perturbations, which are common in quantum digital devices but absent in classical computers, is crucial for identifying potential advantages in quantum machine learning. While these perturbations are typically seen as detrimental to quantum computation, they can actually enhance performance by serving as ...
Matthias Tschöpe +5 more
openaire +2 more sources
Advanced Materials, EarlyView.Aqueous Zn(II) Salphen metallofibers decorated with PNIPAM undergo reversible, multi‐stimuli‐responsive hierarchical bundling. This higher‐order structuring kinetically stabilizes the otherwise fragile assemblies against dilution, acidic hydrolysis, and transmetallation, enables selective sorting of responsive fibers, and programs hydrogelation at ...
Merlin R. Stühler +5 more
wiley +1 more source
An Improved Convolutional Neural Networks: Quantum Pseudo-Transposed Convolutional Neural Networks
IEEE AccessRecent advancements in quantum machine learning have spurred the development of hybrid quantum-classical convolutional neural networks (HQCCNNs), which have demonstrated promising potential for image classification tasks.
Li Hai +4 more
doaj +1 more source
On the classification of quantum symmetries
21 pages; minor ...
Gordienko, A. S., Pekarsky, A. I.
openaire +2 more sources
Quantum machine learning for multiclass classification beyond kernel methods
Quantum machine learning is considered one of the current research fields with great potential. In recent years, Havlíček et al. [Nature (London) 567, 209 (2019)10.1038/s41586-019-0980-2] have proposed a quantum machine learning algorithm with quantum ...
Wang, Yaonan +3 more
core +1 more source
Advanced Materials, EarlyView.Mixed‐cation lead mixed‐halide perovskites suffer from structural instabilities linked to nanoscale heterogeneity. To probe this non‐destructively, a low‐dose, concurrent 4D‐STEM and EDX methodology has been developed. Examining a (FA0.83Cs0.17)Pb(I0.8Br0.2)3 film revealed a complex mosaic of coexisting crystal structures. Crucially, local deficiencies
Jinseok Ryu +6 more
wiley +1 more source
Deep learning for classifying quantum emission signals in WS2 monolayers using wavelet transform
Scientific ReportsThis study aimed to develop and evaluate deep learning approaches for the classification of quantum emission signals from WS2 monolayer nanobubbles across multiple spectral bands, addressing challenges in quantum materials characterization and spectral ...
Hossein Najafzadeh +4 more
doaj +1 more source
Data‐Driven Materials Science for Energy‐Sustainable Applications
Advanced Materials, EarlyView.Data‐driven approaches powered by artificial intelligence are transforming materials discovery for energy sustainability. This review examines how auto‐generated high‐quality materials databases and domain‐specific language models accelerate research in photovoltaics, thermoelectrics, batteries and magnetic materials. Applications involve extraction of
Jacqueline M. Cole
wiley +1 more source
Hybrid Quantum–Classical Framework for Urban Traffic State Classification
IEEE AccessThis paper presents a hybrid quantum–classical approach for multiclass traffic state classification using a benchmark urban mobility dataset collected in Daejeon, South Korea.
Hongsuk Yi
doaj +1 more source