Results 51 to 60 of about 283,757 (265)

The Effect of "Quantum Learning" Model Using "Mind Mapping" Technique to Eight Grade Students’ Creative Thinking Ability

MEJ (Mathematics Education Journal), 2020
This study aims to determine how the effect of the Quantum Learning model using Mind Mapping techniques to students' creative thinking abilities. The type of research used is experiment and quantitative approach with research design using posttest only ...
Erik Eriyanto, Siti Inganah, Dwi Priyo Utomo   +2 more
doaj   +1 more source

Quantum channel learning

Physical Review E
The unitary learning from arXiv:2405.10263 is generalized to density matrices and quantum channels.
Mikhail Gennadievich Belov, Victor Victorovich Dubov, Alexey Vladimirovich Filimonov, Vladislav Gennadievich Malyshkin   +3 more
openaire   +3 more sources

Quantum Reinforcement Learning with Quantum Photonics

Photonics, 2021
Quantum machine learning has emerged as a promising paradigm that could accelerate machine learning calculations. Inside this field, quantum reinforcement learning aims at designing and building quantum agents that may exchange information with their ...
Lucas Lamata
doaj   +1 more source

Building quantum neural networks based on swap test [PDF]

, 2019
Artificial neural network, consisting of many neurons in different layers, is an important method to simulate humain brain. Usually, one neuron has two operations: one is linear, the other is nonlinear.
Guo, Guang-Can, Guo, Guo-Ping, Shao, Chang-Peng, Wu, Yu-Chun, Zhang, Yuan-Hang, Zhao, Jian   +5 more
core   +3 more sources

YAQQ: yet another quantum quantizer design space exploration of quantum gate sets using novelty search

New Journal of Physics
The standard model of quantum computation is based on quantum circuits, where the number and quality of the quantum gates composing the circuit influence the runtime and fidelity of the computation. The fidelity of the decomposition of quantum algorithms,
Aritra Sarkar, Akash Kundu, Matthew Steinberg, Sibasish Mishra, Sebastiaan Fauquenot, Tamal Acharya, Jarosław A Miszczak, Sebastian Feld   +7 more
doaj   +1 more source

Revealing quantum chaos with machine learning

, 2020
Understanding properties of quantum matter is an outstanding challenge in science. In this paper, we demonstrate how machine-learning methods can be successfully applied for the classification of various regimes in single-particle and many-body systems ...
Fedorov, A. K., Karazeev, A. A., Kharkov, Y. A., Kiktenko, E. O., Sotskov, V. E.   +4 more
core   +1 more source

Quantum curriculum learning

Physical Review A
Quantum machine learning (QML) requires significant quantum resources to address practical real-world problems. When the underlying quantum information exhibits hierarchical structures in the data, limitations persist in training complexity and generalization.
Quoc Hoan Tran, Yasuhiro Endo, Hirotaka Oshima   +2 more
openaire   +2 more sources

Advancing Electronic Application of Coordination Solids: Enhancing Electron Transport and Device Integration via Surface‐Mounted MOFs (SURMOFs)

Advanced Functional Materials, EarlyView.
The layer‐by‐layer (LbL) assembly of coordination solids, enabled by the surface‐mounted metal‐organic framework (SURMOF) platform, is on the cusp of generating the organic counterpart of the epitaxy of inorganics. The programmable and sequential SURMOF protocol, optimized by machine learning (ML), is suited for accessing high‐quality thin films of ...
Zhengtao Xu, Christof Wöll, Stefan Bräse   +2 more
wiley   +1 more source

Quantum Learning: Learn Without Learning

International Business & Economics Research Journal (IBER), 2011
Quantum Education is the natural way to learn---motivating and exciting people to take responsibility for their own education.. The Montessori Model represents the closest example of Quantum Education, where the environment is prepared with didactic materials for the children to absorb at their own pace.
Victor Selman, Ruth Corey Selman, Jerry Selman   +2 more
openaire   +2 more sources

Electroactive Metal–Organic Frameworks for Electrocatalysis

Advanced Functional Materials, EarlyView.
Electrocatalysis is crucial in sustainable energy conversion as it enables efficient chemical transformations. The review discusses how metal–organic frameworks can revolutionize this field by offering tailorable structures and active site tunability, enabling efficient and selective electrocatalytic processes.
Irena Senkovska, Yutong Luo, Ruyan Zhao, Jianjun Zhang, Mingchao Wang, Xinliang Feng, Eike Brunner, Stefan Kaskel   +7 more
wiley   +1 more source