M.Sc Thesis

M.Sc StudentWeinstein Yossi
SubjectQuantum Computation and Algorithmic Cooling by Nuclear
Magnetic Resonance
DepartmentDepartment of Physics
Supervisors ASSOCIATE PROF. Tal Mor


An effective cooling of spins can help in building scalable quantum computers and in improving NMR spectroscopy. Cooling of the nuclear spins can be done via two novel techniques recently developed: An adiabatic cooling scheme has been introduced by Schulman and Vazirani (STOC’99), which solves the scaling problem using data compression tools.This scheme is bounded by Shannon’s bound on entropy-preserving compression, and therefore is limited in its practicality. Later on, Boykin, Mor, Roychowdhury, Vatan and Vrijen (PNAS, March 2002) suggested a recursive algorithm combining data compression and thermalization in order to bypass the Shannon’s bound by opening the system to the environment. This is done by utilizing reset qubits, that is, qubits (spins) which rapidly reach thermal relaxation. The entropy is transformed adiabatically into these qubits, and then is “lost” to the environment due to their fast thermalization. An improved algorithm (due to Fernandez, Lloyd, Mor and Roychowdhury), provides realistic and experimentally achievable algorithmic cooling process.

We performed initial attempts for implementing the algorithm using the spin-half states of two 13C nuclei and one hydrogen nucleus in a Trichloroethylene (TCE) molecule as the computation and reset qubits respectively. To allow experimental algorithmic cooling, the thermalization time of the reset qubit must be much faster than the thermalization of the computation qubits.

We investigated the effect of the paramagnetic salt Chromium Acetylacetonate on the thermaization times of computation qubits (carbons)and reset qubits (hydrogen).We report here the accomplishment of an improved ratio of the thermalization times from T1(H)/T1(C)of approximately

5 to around 15.We then performed an experiment demonstrating non adiabatic cooling by thermalization and bypassing Shannon’s bound on entropy manipulation.