Seth Lloyd, Massachusetts Institute of Technology
Wednesday 10/12/2014 at 15:00
Amphitheatre VA1, Civil Engineering Building, IST
Machine learning algorithms look for patterns in data. Frequently, that data comes in the form of large arrays of high-dimensional vectors. Quantum computers are adept at manipulating large arrays of high-dimensional vectors. This talk presents a series of quantum algorithms for big data analysis. The ability of quantum computers to perform Fourier transforms, find eigenvectors and eigenvalues, and invert matrices translates into quantum algorithms for clustering, principal component analysis, and for identifying topological features such as numbers of connected components, holes and voids. These quantum algorithms are exponentially faster than their classical counterparts: complex patterns in datasets of size N can be identified in time O(logN). The talk will discuss methods for implementing quantum machine learning algorithms on the current generation of quantum information processors.
Fedor Jelezko, University of Ulm
Room P9, Mathematics Building, IST
Recently, atom-like impurities in diamond (colour centers) have emerged as an exceptional system for quantum physics in solid state. In this talk I will discuss recent developments transforming quantum control tools into quantum technologies based on single colour centers. Specially, realization of quantum optical interface between spins and photons and scalable quantum registers in diamond will be presented. New applications of diamond qubits involving nanoscale magnetic resonance and force measurements will be shown. I will discuss single spin NMR paving the way to ultrasensitive MRI and structure determination of single biomolecules. The detection of proteins using nanodiamond sensors will be presented. I will also highlight future directions of research including combination of quantum error correction and sensing protocols and quantum enabled sensing and imaging in living cells.
Quantum Computation and Information Seminar
Support: Phys-Info (IT), SQIG (IT), CFIF and CAMGSD, with support from FCT, FEDER and EU FP7, namely via the Doctoral Programme in the Physics and Mathematics of Information (DP-PMI), and projects PEst-OE/EEI/LA0008/2013, QuSim, CQVibes, Landauer (318287) and PAPETS (323901). More Information..