Results 81 to 90 of about 4,977,477 (349)
Crossing complexity of space-filling curves reveals entanglement of S-phase DNA.
PLoS ONE, 2020 Space-filling curves have been used for decades to study the folding principles of globular proteins, compact polymers, and chromatin. Formally, space-filling curves trace a single circuit through a set of points (x,y,z); informally, they correspond to a
Nick Kinney +3 more
doaj +1 more source
Dynamics for holographic codes
Journal of High Energy Physics, 2020 We describe how to introduce dynamics for the holographic states and codes introduced by Pastawski, Yoshida, Harlow and Preskill. This task requires the definition of a continuous limit of the kinematical Hilbert space which we argue may be achieved via ...
Tobias J. Osborne, Deniz E. Stiegemann
doaj +1 more source
Electron-hole generations: A numerical approach to interacting fermion systems
, 2002 A new approach, motivated by Fock space localization, for constructing a reduced many-particle Hilbert space is proposed and tested. The self-consistent Hartree-Fock (SCHF) approach is used to obtain a single-electron basis from which the many-particle ...
Abrahams +25 more
core +1 more source
Advanced Science, EarlyView.A quantum kernel‐aligned regressor (QKAR) is developed for modeling Ohmic contact formation in GaN HEMT fabrication. Leveraging experimental data and a Pauli‐Z feature map enhanced with a quantum kernel alignment (QKA) layer, the model achieves superior predictive performance over classical methods.
Zeheng Wang +7 more
wiley +1 more source
Sahand Communications in Mathematical Analysis, 2018 Frames which can be generated by the action of some operators (e.g. translation, dilation, modulation, ...) on a single element $f$ in a Hilbert space, called coherent frames.
Ataollah Askari Hemmat +2 more
doaj +1 more source
Advanced Intelligent Discovery, EarlyView.Feature selection combined with machine learning and high‐throughput experimentation enables efficient handling of high‐dimensional datasets in emerging photovoltaics. This approach accelerates material discovery, improves process optimization, and strengthens stability prediction, while overcoming challenges in data quality and model scalability to ...
Jiyun Zhang +5 more
wiley +1 more source
A General Approach to Dropout in Quantum Neural Networks
Advanced Quantum Technologies, EarlyView., 2023 Randomly dropping artificial neurons and all their connections in the training phase reduces overfitting issues in classical neural networks, thus improving performances on previously unseen data. The authors introduce different dropout strategies applied to quantum neural networks, learning models based on parametrized quantum circuits.
Francesco Scala +3 more
wiley +1 more source
Journal of Physics: Conference Series, 2007 We present a method of constructing the tomographic probability distributions describing quantum states in parallel with density operators in abstract Hilbert spaces. After the study of an infinite dimensional example, the well known Husimi-Kano quasi-distribution is reconsidered in the new setting and a new tomographic scheme based on coherent states ...
MARMO, GIUSEPPE +2 more
openaire +3 more sources
Advanced Intelligent Systems, EarlyView.This study uses iterative learning control and voice coil motor to keep normal force constant in curved surface polishing. A mechanism‐data fusion model adjusts robotic posture via real‐time feedback for adaptive tracking control of normal force vector direction.
Jiale Xu +3 more
wiley +1 more source
Benefits of Open Quantum Systems for Quantum Machine Learning
Advanced Quantum Technologies, EarlyView., 2023 Quantum machine learning (QML), poised to transform data processing, faces challenges from environmental noise and dissipation. While traditional efforts seek to combat these hindrances, this perspective proposes harnessing them for potential advantages. Surprisingly, under certain conditions, noise and dissipation can benefit QML.
María Laura Olivera‐Atencio +2 more
wiley +1 more source