Novel Technique for Robust Optimal Algorithmic Cooling

Abstract

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.

5 pages, 3 figures + SM (5 pages, 2 figures)

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Cited by in corpus (10)

• Autonomous Temporal Probability Concentration: Clockworks and the Second Law of Thermodynamics
• Exponential improvement for quantum cooling through finite-memory effects
• Dynamic Cooling on Contemporary Quantum Computers
• Quantum Computing by Cooling
• Thermodynamics of a minimal algorithmic cooling refrigerator
• Breaking the limits of purification: Postselection enhances heat-bath algorithmic cooling
• No-go Theorem of Purification
• Quantum noise can enhance algorithmic cooling
• State-independent robust heat-bath algorithmic cooling of nuclear spins
• Thermalization of finite complexity and its application to heat bath algorithmic cooling