Abstract:

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.