Results 61 to 70 of about 2,524,518 (253)

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

Rational approximations and quantum algorithms with postselection [PDF]

, 2014
We study the close connection between rational functions that approximate a given Boolean function, and quantum algorithms that compute the same function using post-selection. We show that the minimal degree of the former equals (up to a factor of 2) the
de Wolf, R., Mahadev, Urmila, de Wolf, Ronald, Mahadev, U., Wolf, Ronald, Wolf, R.M. (Ronald) de   +5 more
core   +2 more sources

Comparative assessment of crystallographic and cryo‐EM models in the Protein Data Bank

FEBS Open Bio, EarlyView.
Raw data obtained by X‐ray crystallography or cryo‐EM result in experimental maps, ultimately fitted by atomic models. Although the physical principles are different, the final results can be viewed, compared, and evaluated in the same way. With cryogenic electron microscopy (cryo‐EM) on track to surpass X‐ray crystallography as the preferred method ...
Alexander Wlodawer, Pawel Rubach, Zbigniew Dauter, Wojciech Dec, Dariusz Brzezinski, Marta Kulik, Wladek Minor, Mariusz Jaskolski   +7 more
wiley   +1 more source

A Novel Magnetic Update Operator for Quantum Evolutionary Algorithms

, 2010
Quantum Evolutionary Algorithms (QEA) are novel algorithms proposed for class of combinatorial optimization problems. The probabilistic representation of possible solutions in QEA helps the q-individuals to represent all the search space simultaneously ...
Tayarani Najaran, Mohammad, Prugel-Bennett, Adam   +1 more
core   +1 more source

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

A comprehensive review of post-quantum cryptography: Challenges and advances [PDF]

International Journal of Data and Network Science
One of the most crucial measures to maintain data security is the use of cryptography schemes and digital signatures built upon cryptographic algorithms.
Seyed M. Hosseini, Hossein Pilaram
doaj   +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

Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization

Advanced Engineering Materials, EarlyView.
Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier, Moritz Blum, Luana Caron, Alisa Chirkova, Philipp Cimiano, Basil Ell, Inga Ennen, Michael Feige, Maik Gaerner, Thomas Hilbig, Andreas Hütten, Günter Reiss, Tapas Samanta, Sonja Schöning, Christian Schröder, Lennart Schwan, Chris Taake, Martin Wortmann   +17 more
wiley   +1 more source

Federated Quantum Machine Learning over Satellite Networks: Toward Scalable Distributed Quantum Classification

Entropy
Federated learning enables multiple organizations to collaboratively analyze data while retaining local control over their datasets, making it attractive for applications such as healthcare.
Juan Carlos Boschero, Rares Adrian Oancea, Luca Mazzarella, Hugo Doeleman, Simon Cramer   +4 more
doaj   +1 more source

Is Entanglement Sufficient to Enable Quantum Speedup? [PDF]

, 2012
According to the Gottesman-Knill theorem, any quantum algorithm utilising operations chosen exclusively from a particular restricted set are efficiently simulable by a classical computer.
Cuffaro, Michael
core