Publisher's Note: Strong algorithmic cooling in large star-topology quantum registers [Phys. Rev. A 
<b>96</b>
, 012330 (2017)]

Pande, Varad R.; Bhole, Gaurav; Mahesh, T. S.

doi:10.1103/physreva.101.019902

Cited by 2 publications

(2 citation statements)

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“…For systems as large as 20-40 qubits, e.g. the experiment in [15], not only it is challenging to implement PPA, but it also seems difficult to find the required permutations. This is in contrast to our technique, where each iteration is already known and there is a specific circuit for implementing it.…”

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confidence: 99%

Novel Technique for Robust Optimal Algorithmic Cooling

2019

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Heat-bath algorithmic cooling (HBAC) provides algorithmic ways to improve the purity of quantum states. These techniques are complex iterative processes that change from each iteration to the next and this poses a significant challenge to implementing these algorithms. Here, we introduce a new technique that on a fundamental level, shows that it is possible to do algorithmic cooling and even reach the cooling limit without any knowledge of the state and using only a single fixed operation, and on a practical level, presents a more feasible and robust alternative for implementing HBAC. We also show that our new technique converges to the asymptotic state of HBAC and that the cooling algorithm can be efficiently implemented; however, the saturation could require exponentially many iterations and remains impractical. This brings HBAC to the realm of feasibility and makes it a viable option for realistic application in quantum technologies.

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confidence: 99%

Novel Technique for Robust Optimal Algorithmic Cooling

2019

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“…We therefore proposed using the quan-tum speed up as a measure of size of the entangled cluster. We find this method to be much simpler compared to spatial phase-encoding method [47] or the temporal phase-encoding method (eg. [48]).…”

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confidence: 99%

NMR investigations of quantum battery using star-topology spin systems

Joshi,

Mahesh

2021

Preprint

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Theoretical explorations have revealed that quantum batteries can exploit quantum correlation to achieve faster charging, thus promising exciting applications in future technologies. Using NMR architecture, here we experimentally investigate various aspects of quantum battery with the help of nuclear spin systems in star-topology configuration. We first carry out numerical analysis to study how charging a quantum battery depends on the relative purity factors of charger and battery spins. By experimentally measuring the polarization of the battery spin undergoing charging, we estimate the battery energy and establish the theoretically predicted quantum advantage. We propose using the quantum advantage, which depends on the entanglement among chargers and battery, as a measure for estimating the size of the entangled cluster. We develop a simple iterative method to realize asymptotic charging avoiding oscillatory behaviour of charging and discharging. Finally, we introduce a load spin and realize a charger-battery-load circuit and experimentally demonstrate battery energy consumption after varying durations of battery storage, for up to two minutes.

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Publisher's Note: Strong algorithmic cooling in large star-topology quantum registers [Phys. Rev. A 96 , 012330 (2017)]

Cited by 2 publications

References 0 publications

Novel Technique for Robust Optimal Algorithmic Cooling

Novel Technique for Robust Optimal Algorithmic Cooling

NMR investigations of quantum battery using star-topology spin systems

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