Eisenberg. Quantum algorithms for subset finding. Quantum Information and Computation, 5(7):593-604, 2005.Andrew M. Childs and Jason M. Eisenberg. Quantum algorithms for subset finding. Quantum Information And
In addition to Hamiltonian simulation, there are several other broad classes of quantum algorithms, including quantum algorithms for linear systems of equations and differential equations, variational quantum algorithms for machine learning, and quantum algorithms for optimization. These frameworks sometimes co...
In19, the authors studied quantum algorithms for supervised and unsupervised machine learning. This particular work focuses on the problem of cluster assignment and cluster finding via quantum algorithms. As a main conclusion of the work, via the utilization of quantum computers and quantum machine le...
Bernstein, Stacey Jeffery, Tanja Lange, and Alexander Meurer. Quantum algorithms for the subset-sum problem. In PQCrypto 2013, pages 16-33, 2013.Bernstein, D.J., Jeffery, S., Lange, T., Meurer, A.: Quantum algorithms for the subset-sum problem. In: Gaborit, P. (ed.) Post-Quantum ...
Carette, T., Lauriere, M., Magniez, F. Extended Learning Graphs for Triangle Finding. Algorithmica.https://doi.org/10.1007/s00453-019-00627-z Ambainis, A.: Quantum algorithms for formula evaluation. Cornell University. Quantum Physics (2010).arXiv:1006.3651[quant-ph].https://arXiv.org/...
We define the entanglement-gradient routing scheme for quantum repeater networks. The routing framework fuses the fundamentals of swarm intelligence and quantum Shannon theory. Swarm intelligence provides nature-inspired solutions for problem solving. Mo
Computer Science - Data Structures and AlgorithmsMathematics - Group TheoryIn this paper we consider the problem of testing whether two finite groupsare isomorphic. Whereas the case where both groups are abelian is wellunderstood and can be solved efficiently, very little is known about thecomplexity...
The TSP is a well-known NP-hard problem that involves finding the shortest possible route that visits each city exactly once and returns to the starting city. Quantum algorithms, such as the Quantum Approximate Optimization Algorithm (QAOA), can be used to tackle this problem. Quantum Circuit ...
Consistent use of "best in class" standard libraries/algorithms like Intel MKL, ELPA, PETSc, SLEPc, ZMUMPS and FEAST Proprietary sparse matrix library Parallel memory distribution of e.g. the mixing history Automatic adjustment of number of bands above the Fermi level to include ...
Physically motivated quantum algorithms for specific near-term quantum hardware will likely be the next frontier in quantum information science. Here, we show how many of the features of neural networks for machine learning can naturally be mapped into the quantum optical domain by introducing the qu...