Results 71 to 80 of about 41,319 (304)

Explainable representation learning of small quantum states

Machine Learning: Science and Technology
Unsupervised machine learning models build an internal representation of their training data without the need for explicit human guidance or feature engineering.
Felix Frohnert, Evert van Nieuwenburg
doaj   +1 more source

An Experimental High‐Throughput Approach for the Screening of Hard Magnet Materials

Advanced Engineering Materials, EarlyView.
An entire workflow for the high‐throughput characterization and analysis of compositionally graded magnetic films is presented. Characterization protocols, data management tools and data analysis approaches are illustrated with test case Sm(Fe, V)12 based films.
William Rigaut, Pierre Le Berre, Hamdi Jaballah, Lukas Fink, Victor Poline, Richard Haettel, Stéphane Grenier, Gilbert Chahine, Ewen Bellec, Guillaume Buatier, Wilfried Hortschitz, Santa Pile, Thomas Schrefl, Nils Blanc, Yuan Hong, Thibaut Devillers, Nora M. Dempsey   +16 more
wiley   +1 more source

Quantum algorithms and the power of forgetting

CoRR, 2022
The so-called welded tree problem provides an example of a black-box problem that can be solved exponentially faster by a quantum walk than by any classical algorithm. Given the name of a special ENTRANCE vertex, a quantum walk can find another distinguished EXIT vertex using polynomially many queries, though without finding any particular path from ...
Andrew M. Childs, Matthew Coudron, Amin Shiraz Gilani   +2 more
openaire   +4 more sources

A novel quantum algorithm for ant colony optimisation

IET Quantum Communication, 2022
Ant colony optimisation (ACO) is a commonly used meta‐heuristic to solve complex combinatorial optimisation problems like the travelling salesman problem (TSP), vehicle routing problem (VRP) etc.
Mrityunjay Ghosh, Nivedita Dey, Debdeep Mitra, Amlan Chakrabarti   +3 more
doaj   +1 more source

Intermediate Resistive State in Wafer‐Scale Vertical MoS2 Memristors Through Lateral Silver Filament Growth for Artificial Synapse Applications

Advanced Functional Materials, EarlyView.
In MOCVD MoS2 memristors, a current compliance‐regulated Ag filament mechanism is revealed. The filament ruptures spontaneously during volatile switching, while subsequent growth proceeds vertically through the MoS2 layers and then laterally along the van der Waals gaps during nonvolatile switching.
Yuan Fa, Milan Buttberg, Ke Ran, Rana Walied Ahmad, Dennis Braun, Lukas Völkel, Jimin Lee, Sofía Cruces, Bart Macco, Bárbara Canto, Holger Lerch, Thorsten Wahlbrink, Holger Kalisch, Michael Heuken, Andrei Vescan, Joachim Mayer, Zhenxing Wang, Ilia Valov, Stephan Menzel, Max C. Lemme   +19 more
wiley   +1 more source

Quantum Algorithms [PDF]

, 2009
We give a short overview of quantum algorithms. Some famous algorithms such as Deutsch-Jozsa and Simon are covered with more details.
Amini, Seyed Massoud
core  

Optoelectronic Synaptic Devices Using Molecular Telluride Phase‐Change Inks for Three‐Factor Learning

Advanced Functional Materials, EarlyView.
Optoelectronic synaptic devices based on solution‐processed molecular telluride GST‐225 phase‐change inks are demonstrated for three‐factor learning. A global optical signal broadcast through a silicon waveguide induces non‐volatile conductance updates exclusively in locally electrically flagged memristors.
Kevin Portner, Dhananjeya Kumaar, Giacomo Torti, Killian Keller, Till Zellweger, Florian M. Schenk, Christoph Weilenmann, Daniel Chelladurai, Vara Prasad Jonnalagadda, Ghazi Sarwat Syed, Vanessa Wood, Jürg Leuthold, Alexandros Emboras, Maksym Yarema, Mathieu Luisier   +14 more
wiley   +1 more source

Learning density functionals from noisy quantum data

Machine Learning: Science and Technology
The search for useful applications of noisy intermediate-scale quantum (NISQ) devices in quantum simulation has been hindered by their intrinsic noise and the high costs associated with achieving high accuracy.
Emiel Koridon, Felix Frohnert, Eric Prehn, Evert van Nieuwenburg, Jordi Tura, Stefano Polla   +5 more
doaj   +1 more source

Variational quantum compiling with double Q-learning

New Journal of Physics, 2021
Quantum compiling aims to construct a quantum circuit V by quantum gates drawn from a native gate alphabet, which is functionally equivalent to the target unitary U . It is a crucial stage for the running of quantum algorithms on noisy intermediate-scale
Zhimin He, Lvzhou Li, Shenggen Zheng, Yongyao Li, Haozhen Situ   +4 more
doaj   +1 more source

Quantum policy gradient algorithms

CoRR, 2022
Understanding the power and limitations of quantum access to data in machine learning tasks is primordial to assess the potential of quantum computing in artificial intelligence. Previous works have already shown that speed-ups in learning are possible when given quantum access to reinforcement learning environments.
Sofiène Jerbi, Arjan Cornelissen, Maris Ozols, Vedran Dunjko   +3 more
openaire   +4 more sources