Yossi Weinstein

Heat-bath cooling of spins in two amino acids

Abstract Heat-bath cooling is a component of practicable algorithmic cooling of spins, an approach which might be useful for in vivo 13 C spectroscopy, in particular for prolonged metabolic processes where substrates that are hyperpolarized ex-vivo are not effective. We applied heat-bath cooling to 1, 2- 13 C 2 -amino acids, using the α protons to shift entropy from selected carbons to the environment. For glutamate and glycine, both carbons were cooled by about 2.5-fold, and in other experiments the polarization of C1 nearly doubled while all other spins had equilibrium polarization, indicating reduction in total entropy. The effect of adding Magnevist®, a gadolinium contrast agent, on heat-bath cooling of glutamate was investigated.

Algorithmic cooling in liquid-state nuclear magnetic resonance

Algorithmic cooling is a method that employs thermalization to increase the qubits’ purification level, namely it reduces the qubit-system’s entropy. We utilized gradient ascent pulse engineering (GRAPE), an optimal control algorithm, to implement algorithmic cooling in liquid state nuclear magnetic resonance. Various cooling algorithms were applied onto the three qubits of C2trichloroethylene, cooling the system beyond Shannon’s entropy bound in several different ways. For example, in one experiment a carbon qubit was cooled by a factor of 4.61. This work is a step towards potentially integrating tools of NMR quantum computing into in vivo magnetic resonance spectroscopy.

Quantum computing gates via optimal control

We demonstrate the use of optimal control to design two entropy-manipulating quantum gates which are more complex than the corresponding, commonly used, gates, such as CNOT and Toffoli (CCNOT): A two-qubit gate called polarization exchange (PE) and a three-qubit gate called polarization compression (COMP) were designed using GRAPE, an optimal control algorithm. Both gates were designed for a three-spin system. Our design provided efficient and robust nuclear magnetic resonance (NMR) radio frequency (RF) pulses for 13C2-trichloroethylene (TCE), our chosen three-spin system. We then experimentally applied these two quantum gates onto TCE at the NMR lab. Such design of these gates and others could be relevant for near-future applications of quantum computing devices.

PARAMAGNETIC MATERIALS AND PRACTICAL ALGORITHMIC COOLING FOR NMR QUANTUM COMPUTING

Algorithmic cooling is a method that uses novel data compression techniques and simple quantum computing devices to improve NMR spectroscopy, and to offer scalable NMR quantum computers. The algorithm recursively employs two steps. A reversible entropy compression of computation quantum-bits (qubits) of the system and an irreversible heat transfer from the system to the environment through a set of reset qubits that reach thermal relaxation rapidly. Is it possible to experimentally demonstrate algorithmic cooling using existing technology? To allow experimental algorithmic cooling, the thermalization time of the reset qubits must be much shorter than the thermalization time of the computation qubits. However, such high thermalization-times ratios have yet to be reported. We investigate here the effect of a paramagnetic salt on the thermalization-times ratio of computation qubits (carbons) and a reset qubit (hydrogen). We show that the thermalization-times ratio is improved by approximately three-fold. Based on this result, an experimental demonstration of algorithmic cooling by thermalization and magnetic ions has been performed by the authors and collaborators.

Heat-Bath Algorithmic Cooling with Correlated-Qubits Relaxation

Pure states are needed for many quantum algorithms and in particular for quantum error correction. Algorithmic cooling has been shown to purify qubits by a controlled redistribution of entropy and multiple contact with a heat-bath. In previous heat-bath algorithmic cooling work, it was assumed that each qubit undergoes thermal relaxation independently. In this paper we remove this constraint, and introduce an additional tool for cooling algorithms which we call “state-reset”. State-reset can occur when the coupling to the environment is generalized from individual-qubits relaxation to correlated-qubits relaxation. We present several improved cooling algorithms which lead to an increase of polarization beyond the ones all previous work believed to be optimal, and we relate our results to an effect in chemical physics, known as the Nuclear Overhauser Effect.