Monday colloquium: Algorithmic Cooling of Spins -- A Novel Polarization Method
An efficient technique to generate ensembles of spins that are highly polarized by external magnetic fields is the Holy Grail in Nuclear Magnetic Resonance (NMR) spectroscopy. Since spin-half nuclei have Magnetic Resonance (NMR) spectroscopy. Since spin-half nuclei have steady-state polarization biases that increase inversely with temperature, spins exhibiting high polarization biases are considered cool, even when their environment is warm. Existing spin-cooling techniques are highly limited in their efficiency and usefulness.
Algorithmic cooling (Boykin, Mor, Roychowdhury, Vatan and Vrijen, PNAS 2002) is a promising new spin-cooling approach that employs data compression methods in open systems. It reduces the entropy of spins on long molecules to a point far beyond Shannon's bound on reversible entropy manipulations, thus increasing their polarization.
An efficient and experimentally feasible algorithmic cooling technique that cools spins to very low temperatures even on short molecules was later on presented (Fernandez, Lloyd, Mor and Roychowdhury, IJQI, to be published). This practicable algorithmic cooling could lead to breakthroughs in high-sensitivity NMR spectroscopy in the near future, and to the development of scalable NMR quantum computers in the far future. Moreover, while the cooling algorithm itself is classical, it uses quantum gates in its implementation, thus representing the first short-term application of quantum computing devices. As the practicable algorithmic cooling can cool very short molecules (e.g., of three spin-half particles), all the steps of algorithmic cooling were already demonstrated in laboratories; in particular, we demonstrated experimentally how to cool two carbons with the help of one proton.