Advancing Quantum Computers for (and with) Quantum Thermodynamics
While thermodynamics is one of the most well-established physical theories, there is much that remains to be worked out in its extension to the quantum realm. With the miniaturization of electronics down to the nanoscale, along w...
While thermodynamics is one of the most well-established physical theories, there is much that remains to be worked out in its extension to the quantum realm. With the miniaturization of electronics down to the nanoscale, along with the emergence of quantum technologies, it is becoming essential to gain a better understanding of thermodynamics at the quantum level. The emergence of quantum computers (QCs) in the last decade provides a game-changing new tool for research into quantum thermodynamics (QT). Furthermore, still in nascent stages, QCs stand to gain vast improvements in performance from new insights derived from QT. An elegant synergy therefore exists whereby (i) QCs can be used to improve the fundamental understanding of QT and (ii) principles from QT may be used to improve the reliability of QCs. Inspired by this synergy, this proposal includes two thrusts to advance progress along these two fronts. For the first thrust, I aim to develop new algorithms packaged into well-documented, open-source software for simulating thermal properties and behaviors of quantum systems on QCs. This work will culminate in attempting the first-ever experimental validation fluctuation relations (theoretical pillars of QT) for open quantum systems on a QC. For the second thrust I aim to use the principles of QT to implement an algorithmic cooling scheme that can improve the overall performance of qubits for any desired application on a QC. This work will culminate in attempting the first-ever experimental demonstration of algorithmic cooling on a QC. The proposed research requires an interdisciplinary approach encompassing quantum information and computation; thermodynamics and statistical mechanics; and computational science (CS). The complementary expertise and experience of the experienced researcher (in QC and CS) and the supervising host (in QT) will foster a productive two-way transfer of knowledge and facilitate the success of the research goals.ver más
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