Quantum algorithms for topological and geometric analysis of data
Extracting useful information from large data sets can be a daunting task. Topological methods for analysing data sets provide a powerful technique for extracting such information. Persistent homology is a sophisticated tool for identifying topological features and for determining how such features...
Main Authors: | Lloyd, Seth (Contributor), Garnerone, Silvano (Author), Zanardi, Paolo (Author) |
---|---|
Other Authors: | Massachusetts Institute of Technology. Department of Mechanical Engineering (Contributor), Massachusetts Institute of Technology. Research Laboratory of Electronics (Contributor) |
Format: | Article |
Language: | English |
Published: |
Nature Publishing Group,
2016-03-18T14:47:34Z.
|
Subjects: | |
Online Access: | Get fulltext |
Similar Items
-
Quantum algorithms for topological and geometric analysis of data
by: Seth Lloyd, et al.
Published: (2016-01-01) -
Symplectic Topology and Geometric Quantum Mechanics
Published: (2011) -
Quantum Algorithm for Data Fitting
by: Wiebe, Nathan, et al.
Published: (2012) -
Geometric and Topological Phases with Applications to Quantum Computation
by: Ericsson, Marie
Published: (2002) -
Topological Quantum Field Theory and the Geometric Langlands Correspondence
by: Setter, Kevin Luke
Published: (2013)