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Quantum Distance Approximation for Persistence Diagrams
Topological Data Analysis methods can be useful for classification and clustering tasks in many different fields as they can provide two dimensional persistence diagrams that summarize important information about the shape of potentially complex and high dimensional data sets.
On the Computational Cost of Stochastic Security
We investigate whether long-run persistent chain Monte Carlo simulation of Langevin dynamics improves the quality of the representations achieved by energy-based models (EBM).
Quantum Persistent Homology for Time Series
Persistent homology, a powerful mathematical tool for data analysis, summarizes the shape of data through tracking topological features across changes in different scales.
Impact of Graph Structures for QAOA on MaxCut
The quantum approximate optimization algorithm (QAOA) is a promising method of solving combinatorial optimization problems using quantum computing.
Combinatorial Optimization
Quantum Physics
