arXiv subjects

Nayeli A. Rodríguez-Briones

Publications and source records attributed to Nayeli A. Rodríguez-Briones.

6 recordsLinked to original sources

arXiv2025

Efficiently Cooling Quantum Systems with Finite Resources: Insights from Thermodynamic Geometry

Landauer's limit on heat dissipation during information erasure is critical as devices shrink, requiring optimal pure-state preparation to minimise errors. However, Nernst's third law states this demands infinite resources in energy, time, or control complexity. We address the challenge of cooling quantum systems with finite resources. Using Markovian collision models, we explore resource trade-offs and present efficient cooling protocols (that are optimal for qubits) for coherent and incoherent control. Leveraging thermodynamic length, we derive bounds on heat dissipation for swap-based strategies and discuss the limitations of preparing pure states efficiently.

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arXiv2025

Improving Quantum Machine Learning via Heat-Bath Algorithmic Cooling

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 concept, we develop a quantum refrigerator protocol that enhances sample efficiency during training and prediction without the need for Grover iterations or quantum phase estimation. Inspired by heat-bath algorithmic cooling protocols, our method alternates entropy compression and thermalization steps to decrease the entropy of qubits, increasing polarization towards the dominant bias. This technique minimizes the computational overhead associated with estimating classification scores and gradients, presenting a practical and efficient solution for QML algorithms compatible with noisy intermediate-scale quantum devices.

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arXiv2024

Schmidt quantum compressor

This work introduces the Schmidt quantum compressor, an innovative approach to quantum data compression that leverages the principles of Schmidt decomposition to encode quantum information efficiently. In contrast to traditional variational quantum autoencoders, which depend on stochastic optimization and face challenges such as shot noise, barren plateaus, and non-convex optimization landscapes, our deterministic method substantially reduces the complexity and computational overhead of quantum data compression. We evaluate the performance of the compressor through numerical experiments, demonstrating its ability to achieve high fidelity in quantum state reconstruction compared to variational quantum algorithms. Furthermore, we demonstrate the practical utility of the Schmidt quantum compressor in one-class classification tasks.

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arXiv2024

Thermodynamic Analysis of Algorithmic Cooling Protocols: Efficiency Metrics and Improved Designs

Algorithmic cooling (AC) protocols have been predominantly studied for their cooling capabilities, with limited attention paid to their thermodynamic properties. This work explores a novel perspective by analyzing a broad family of AC protocols from a thermodynamic standpoint. First, we give an in-depth review and formal classification of standard AC protocols. Leveraging the transfer matrix formalism, we achieve a consistent calculation of performance metrics, encompassing both cooling limits and target state evolution. We obtained a unification of these diverse cooling limits into a single, coherent mathematical expression, streamlining comparative analyses. Then, to assess the efficiency of coherent cooling protocols, we introduce two generic metrics: the coefficient of performance $K$ and the Landauer Ratio $R_L$, and establish a direct interrelation. Applying these metrics, we thoroughly evaluate selected AC protocols, highlighting their relative strengths. Finally, we propose improved versions of AC protocols that exhibit enhanced thermodynamic performance, achieving desired target temperatures with lower work inputs. This research contributes to a deeper understanding of AC protocols and provides valuable insights for designing efficient cooling strategies in various applications.

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arXiv2023

Experimental Activation of Strong Local Passive States with Quantum Information

Strong local passivity is a property of multipartite quantum systems from which it is impossible to extract energy locally. Surprisingly, if the strong local passive state displays entanglement, it could be possible to locally activate energy density by adding classical communication between different partitions of the system, through so-called "quantum energy teleportation" protocols. Here, we report both the first experimental observation of local activation of energy density on an entangled state and the first realization of a quantum energy teleportation protocol using nuclear magnetic resonance on a bipartite quantum system.

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arXiv2016

Achievable polarization for Heat-Bath Algorithmic Cooling

Pure quantum states play a central role in applications of quantum information, both as initial states for many algorithms and as resources for quantum error correction. Preparation of highly pure states that satisfy the threshold for quantum error correction remains a challenge, not only for ensemble implementations like NMR or ESR but also for other technologies. Heat-Bath Algorithmic Cooling is a method to increase the purity of set of qubits coupled to a bath. We investigated the achievable polarization by analyzing the state when no more entropy can be extracted. In particular we give an analytic form for the maximum polarization of the purified qubit and corresponding state of the whole system for the case when the initial state of the qubits is totally mixed. It is however possible to reach higher polarization while starting with other states with higher polarization, thus our result provides an achievable lower bound. We also give an upper bound of the number of steps needed to get a certain required polarization.

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