内容：

In this talk I will suggest the first near-future application of quantum computing devices, "Algorithmic Cooling". I will explain how simple quantum algorithms, and novel entropy manipulations (that go far beyond Shannon's entropy bound), can be combined in order to improve identification of molecules. Molecules are built from atoms, and the nucleus inside each atom has a property called spin. The spin can be understood as the orientation of the nucleus, and when put in a magnetic field, certain spins are binary, either up (ZERO) or down (ONE). Several such bits (inside one molecule) represent a binary string -- a register. A macroscopic number of such registers/molecules are monitored in parallel, as done, for instance, in Magnetic Resonance Imaging (MRI). The device that monitors and manipulates these bits/spins is considered a simple "computing" device.
Our goal is to improve the molecules' identification process by using the computing device to run "data compression" algorithms that reduce the entropy of certain spins. A bit with lower entropy is considered "cooler", and it provides a better signal when used for identifying molecules. Shannon's entropy bound tells us that the total entropy of the spins in a molecule is preserved. Therefore, cooling one spin is done at the expense of heating the others. Our "Algorithmic Cooling" employs data compression methods in *open systems*, thus reducing the entropy of spins far beyond Shannon's bound. Cooling of short molecules is experimentally feasible -- we recently cooled spins of a three-bit quantum computer beyond Shannon's entropy bound at the Technion NMR lab.
 

人物介绍：