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This work introduces an approach rooted in quantum thermodynamics to enhance sampling efficiency in quantum machine learning (QML). We propose conceptualizing quantum supervised learning as a thermodynamic cooling process. Building on this…

Quantum Physics · Physics 2025-01-07 Nayeli A. Rodríguez-Briones , Daniel K. Park

Algorithmic Cooling is a method that uses novel data compression techniques and simplecquantum computing devices to improve NMR spectroscopy, and to offer scalable NMR quantum computers. The algorithm recursively employs two steps. A…

Quantum Physics · Physics 2009-11-11 Jose M. Fernandez , Tal Mor , Yossi Weinstein

Predicting observables in equilibrium states is a central yet notoriously hard question in quantum many-body systems. In the physically relevant thermodynamic limit, certain mathematical formulations of this task have even been shown to…

Quantum Physics · Physics 2025-08-15 Hamza Fawzi , Omar Fawzi , Samuel O. Scalet

Dissipation and the accompanying fluctuations are often seen as detrimental for quantum systems, since they are associated with fast relaxation and loss of phase coherence. However, it has been proposed that a pure state can be prepared if…

Quantum computing raises the possibility of solving a variety of problems in physics that are presently intractable. A number of such problems involves the physics of systems in or near thermal equilibrium. There are two main ways to…

Quantum Physics · Physics 2023-08-16 Carter Ball , Thomas D. Cohen

Quantum manipulation of macroscopic mechanical systems is of great interest in both fundamental physics and applications ranging from high-precision metrology to quantum information processing. A crucial goal is to cool the mechanical…

Quantum Physics · Physics 2014-11-17 Yong-Chun Liu , Yu-Wen Hu , Chee Wei Wong , Yun-Feng Xiao

Noise and errors are unavoidable in any realistic quantum process, including processes designed to reduce noise and errors in the first place. In particular, quantum thermodynamical protocols for cooling can be significantly affected,…

Quantum Physics · Physics 2026-01-26 Jian Li , Xiaoyang Wang , Marcus Huber , Nicolai Friis , Pharnam Bakhshinezhad

We present here algorithmic cooling (via polarization-heat-bath)- a powerful method for obtaining a large number of highly polarized spins in liquid nuclear-spin systems at finite temperature. Given that spin-half states represent (quantum)…

Quantum Physics · Physics 2009-11-07 P. Oscar Boykin , Tal Mor , Vwani Roychowdhury , Farrokh Vatan , Rutger Vrijen

We propose a quantum information based scheme to reduce the temperature of quantum many-body systems, and access regimes beyond the current capability of conventional cooling techniques. We show that collective measurements on multiple…

Designing cooling protocols is believed to require knowledge of the system spectrum. In contrast, cooling in nature occurs whenever the system is coupled to a cold bath. How does nature know how to cool? A natural cold bath can be mimicked…

We study the problem of dynamic cooling whereby a target qubit is cooled at the expense of heating up $N-1$ further identical qubits, by means of a global unitary operation. A standard back-of-the-envelope high temperature estimate…

Quantum Physics · Physics 2024-09-26 Lindsay Bassman Oftelie , Antonella De Pasquale , Michele Campisi

Owing to the computational complexity of electronic structure algorithms running on classical digital computers, the range of molecular systems amenable to simulation remains tightly circumscribed even after many decades of work. Quantum…

Quantum Physics · Physics 2022-05-18 Alexis Ralli , Michael I. Williams , Peter V. Coveney

Interesting problems in quantum computation take the form of finding low-energy states of (pseudo)spin systems with engineered Hamiltonians that encode the problem data. Motivated by the practical possibility of producing very…

Quantum Physics · Physics 2022-05-11 Jiajin Feng , Biao Wu , Frank Wilczek

Quantum computing not only holds the potential to solve long-standing problems in quantum physics, but also to offer speed-ups across a broad spectrum of other fields. However, due to the noise and the limited scale of current quantum…

Quantum Physics · Physics 2024-03-05 Julien Gacon

A quantum thermodynamic system is described by a Hamiltonian and a list of conserved, non-commuting charges, and a fundamental goal is to determine the minimum energy of the system subject to constraints on the charges. Recently, [Liu et…

A quantum system coupled to a bath at some fixed, finite temperature converges to its Gibbs state. This thermalization process defines a natural, physically-motivated model of quantum computation. However, whether quantum computational…

Quantum Physics · Physics 2025-01-15 Thiago Bergamaschi , Chi-Fang Chen , Yunchao Liu

Heat-Bath Algorithmic Cooling techniques (HBAC) are techniques that are used to purify a target element in a quantum system. These methods compress and transfer entropy away from the target element into auxiliary elements of the system. The…

Quantum Physics · Physics 2022-02-23 Zahra Farahmand , Reyhaneh Aghaei Saem , Sadegh Raeisi

Quantum computing provides a new way for approaching problem solving, enabling efficient solutions for problems that are hard on classical computers. It is based on leveraging how quantum particles behave. With researchers around the world…

Quantum Physics · Physics 2021-09-29 Ahmed Shokry , Moustafa Youssef

Quantum simulation is a potentially powerful application of quantum computing, holding the promise to be able to emulate interesting quantum systems beyond the reach of classical computing methods. Despite such promising applications, and…

Quantum Physics · Physics 2022-10-07 Kaelyn J. Ferris , A. J. Rasmusson , Nicholas T. Bronn , Olivia Lanes

Algorithmic cooling is a method that employs thermalization to increase qubit purification level, namely it reduces the qubit-system's entropy. We utilized gradient ascent pulse engineering (GRAPE), an optimal control algorithm, to…

Quantum Physics · Physics 2016-01-20 Yosi Atia , Yuval Elias , Tal Mor , Yossi Weinstein