Results 131 to 140 of about 322,484 (286)

Optimizing Variational Quantum Neural Networks Based on Collective Intelligence

Mathematics
Quantum machine learning stands out as one of the most promising applications of quantum computing, widely believed to possess potential quantum advantages.
Zitong Li, Tailong Xiao, Xiaoyang Deng, Guihua Zeng, Weimin Li   +4 more
doaj   +1 more source

Many-body localization enables iterative quantum optimization. [PDF]

Nat Commun, 2022
Wang H, Yeh HC, Kamenev A.
europepmc   +1 more source

Optimal quantum control of charging quantum batteries

New Journal of Physics
Abstract Quantum control allows us to address the problem of engineering quantum dynamics for special purposes. While recently the field of quantum batteries has attracted much attention, optimization of their charging has not benefited from the quantum control methods. Here we fill this gap by using an optimization method.
R R Rodríguez, B Ahmadi, G Suárez, P Mazurek, S Barzanjeh, P Horodecki   +5 more
openaire   +3 more sources

Trap‐Modified Inverted Organic Photodetectors via Layer‐by‐Layer Processing with Poly(N‐vinylcarbazole) Additives

Advanced Functional Materials, EarlyView.
Trap state engineering in inverted organic photodetectors (OPDs) is achieved via combined layer‐by‐layer (LbL) processing and poly(N‐vinylcarbazole) (PVK) incorporation. LbL reduces the trap density while PVK additives gradually shift trap states from shallow band‐edge to deep mid‐gap levels, tailoring the energy distribution.
Jingwei Yi, Yi Yang, Yusen Pei, Apurva Gadikar, Vahid Mahdikhah, Myratgeldi Kotyrov, Seung Hyun Kim, Kenan Gundogdu, Wei You, Harald Ade, Franky So   +10 more
wiley   +1 more source

Multi-target quantum compilation algorithm

Machine Learning: Science and Technology
Quantum compilation is the process of converting a target unitary operation into a trainable unitary represented by a quantum circuit. It has a wide range of applications, including gate optimization, quantum-assisted compiling, quantum state preparation,
Vu Tuan Hai, Nguyen Tan Viet, Jesus Urbaneja, Nguyen Vu Linh, Lan Nguyen Tran, Le Bin Ho   +5 more
doaj   +1 more source

Quantum gradient descent and Newton’s method for constrained polynomial optimization

New Journal of Physics, 2019
Optimization problems in disciplines such as machine learning are commonly solved with iterative methods. Gradient descent algorithms find local minima by moving along the direction of steepest descent while Newton’s method takes into account curvature ...
Patrick Rebentrost, Maria Schuld, Leonard Wossnig, Francesco Petruccione, Seth Lloyd   +4 more
doaj   +1 more source

Constrained quantum optimization for extractive summarization on a trapped-ion quantum computer. [PDF]

Sci Rep, 2022
Niroula P, Shaydulin R, Yalovetzky R, Minssen P, Herman D, Hu S, Pistoia M.   +6 more
europepmc   +1 more source

DNA‐Templated 2D Heterostructures as Phototriggered Dynamic Nanohybrids: From Releasing Molecular Loads to Controlling Enzyme Biocatalytic Function

Advanced Functional Materials, EarlyView.
DNA strands are employed both as dynamic linkers and nanoscale templates for the integration of Ag2S nanoparticles on MoS2, which in turn imparted photothermal responsiveness; this feature permits the selective cargo (fluorophore, quantum dots or an enzyme) release from the MoS2 surface in response to local heat induced by light irradiation.
Kai Chen, Haosen Miao, Weiying Hong, Matteo Palma   +3 more
wiley   +1 more source

Improving Quantum Optimization Algorithms by Constraint Relaxation

Applied Sciences
Quantum optimization is a significant area of quantum computing research with anticipated near-term quantum advantages. Current quantum optimization algorithms, most of which are hybrid variational-Hamiltonian-based algorithms, struggle to present ...
Tomasz Pecyna, Rafał Różycki
doaj   +1 more source

Publisher Correction: Many-body localization enables iterative quantum optimization. [PDF]

Nat Commun, 2022
Wang H, Yeh HC, Kamenev A.
europepmc   +1 more source