Results 71 to 80 of about 1,060,572 (311)
In this study, the mechanical response of Y‐shaped core sandwich beams under compressive loading is investigated, using deep feed‐forward neural networks (DFNNs) for predictive modeling. The DFNN model accurately captures stress–strain behavior, influenced by design parameters and loading rates.
Ali Khalvandi+4 more
wiley +1 more source
Universality in quantum computation [PDF]
We show that in quantum computation almost every gate that operates on two or more bits is a universal gate. We discuss various physical considerations bearing on the proper definition of universality for computational components such as logic gates.
Deutsch, D, Barenco, A, Ekert, A
openaire +5 more sources
Quantum Computing with Dartboards
We present a physically appealing and elegant picture for quantum computing using rules constructed for a game of darts. A dartboard is used to represent the state space in quantum mechanics and the act of throwing the dart is shown to have close similarities to the concept of measurement, or collapse of the wavefunction in quantum mechanics.
Ishaan Ganti, Srinivasan S. Iyengar
openaire +3 more sources
Molecular dynamics simulations are advancing the study of ribonucleic acid (RNA) and RNA‐conjugated molecules. These developments include improvements in force fields, long‐timescale dynamics, and coarse‐grained models, addressing limitations and refining methods.
Kanchan Yadav, Iksoo Jang, Jong Bum Lee
wiley +1 more source
Decoherence is detrimental to quantum key distribution (QKD) over large distances. One of the proposed solutions is to use quantum repeaters, which divide the total distance between the users into smaller segments to minimise the effects of the losses in
Özlem Erkılıç+7 more
doaj +1 more source
Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani+4 more
wiley +1 more source
Optical quantum memories are essential for quantum communications and photonic quantum technologies. Ensemble optical memories based on 3-level interactions are a popular basis for implementing these memories. All such memories, however, suffer from loss
Jesse L Everett+5 more
doaj +1 more source
Two-electron spin correlations in precision placed donors in silicon
Donor impurities in silicon are promising candidates as qubits but in order to create a large-scale quantum computer inter-qubit coupling must be introduced by precise positioning of the donors.
M. A. Broome+10 more
doaj +1 more source
IBM Quantum Computers: Evolution, Performance, and Future Directions [PDF]
Quantum computers represent a transformative frontier in computational technology, promising exponential speedups beyond classical computing limits. IBM Quantum has led significant advancements in both hardware and software, providing access to quantum hardware via IBM Cloud since 2016, achieving a milestone with the world's first accessible quantum ...
arxiv +1 more source
Hybrid Framework Materials: Next‐Generation Engineering Materials
Hybrid organic–inorganic materials merge the unique properties of organic and inorganic compounds, enabling applications in optoelectronics, gas storage, and catalysis. This review explores metal‐organic frameworks, hybrid organic–inorganic perovskites, and the emerging field of hybrid glasses, emphasizing their structures, functionalities, and ...
Jay McCarron+2 more
wiley +1 more source