Quantum information and quantum computing (QIQC) systems, relying on the phenomena of superposition and entanglement, offer the potential for vast improvements in certain computations. A practical QC realization requires maintaining the stored information for time-scales long enough to implement algorithms. One primary cause of information loss is decoherence, i.e., the loss of coherence between two energy levels in a quantum system. This work attributes decoherence to dissipation occurring as the system evolves and uses steepest-entropy-ascent quantum thermodynamics (SEAQT) to predict the evolution of system state. SEAQT asserts that, at any instant of time, the system state evolves such that the rate of system entropy change is maximized while conserving system energy. With this principle, the SEAQT equation of motion is applicable to systems in any state, near or far from stable equilibrium, making SEAQT particularly well suited for predicting the dissipation occurring as quantum algorithms are implemented. In the present research, the dynamics of qubits (quantum-bits) using the SEAQT framework are first examined during common quantum gates (combinations of which form algorithms). This is then extended to modeling a system of multiple qubits implementing Shor's algorithm on a nuclear-magnetic-resonance (NMR) QC. Additionally, the SEAQT framework is used to predict experimentally observed dissipation occurring in a two-qubit NMR QC undergoing a so called ``quenching'' process. In addition, several methods for perturbing the density or so-called ``state'' operator used by the SEAQT equation of motion subject to an arbitrary set of expectation value constraints are presented. These are then used as the basis for randomly generating states used in analyzing the dynamics of entangled, non-interacting systems within SEAQT. Finally, a reservoir interaction model is developed for general quantum systems where each system locally experiences a heat interaction with an external reservoir. This model is then used as the basis for developing a decoherence control scheme, which effectively transfers entropy out of the QIQC system as it is generated, thus, reducing the decoherence. Reservoir interactions are modeled for single qubits and the control scheme is employed in modeling an NMR QC and shown to eliminate nearly all of the noise caused by decoherence/dissipation.
Quantum thermodynamics aims to extend standard thermodynamics and non-equilibrium statistical physics to systems with sizes well below the thermodynamic limit. It is a rapidly evolving research field that promises to change our understanding of the foundations of physics, while enabling the discovery of novel thermodynamic techniques and applications at the nanoscale. Thermal management has turned into a major obstacle in pushing the limits of conventional digital computers and could also represent a crucial issue for quantum computers. The practical realization of quantum computers with superconducting loops requires working at cryogenic temperatures to eliminate thermal noise, and ion-trap qubits also need low temperatures to minimize collisional noise. In both cases, the sub-nanometric sizes also bring about the thermal broadening of the quantum states; and even room-temperature photonic computers eventually require cryogenic detectors. A number of thermal and thermodynamic questions, therefore, take center stage, such as quantum re-definitions of work and heat, thermalization and randomization of quantum states, the overlap of quantum and thermal fluctuations, and many others, even including a proper definition of temperature for the small open systems constantly out of equilibrium that are the qubits. This overview provides an introductory perspective on a selection of current trends in quantum thermodynamics and their impact on quantum computers and quantum computing, with language that is accessible to postgraduate students and researchers from different fields.
This paper explores the emerging intersection of quantum thermodynamics and quantum information processing. The core argument presented is that quantum information processing fundamentally relies on the thermodynamic properties of quantum systems and can be significantly advanced by leveraging the principles of quantum thermodynamics. This work establishes a framework for analyzing and designing quantum information protocols through the lens of thermodynamic constraints and efficiencies. We introduce a novel perspective where quantum information tasks are viewed as thermodynamic processes, allowing for a more rigorous understanding of their limitations and potential optimizations. The methodology presented aims to bridge the gap between information theory and thermodynamics, ultimately leading to the development of more robust and efficient quantum information systems. Key concepts explored include quantum work, heat dissipation, entropy production, and their implications for quantum data storage, quantum computation, and quantum communication. This research contributes to a fundamental shift in how we approach quantum information processing, moving beyond purely computational considerations to incorporate the underlying thermodynamic realities of quantum systems.
Thermodynamic trade-off relations dictate fundamental limits on the performance of thermodynamic tasks through costs such as heat dissipation. Here, we propose a framework called thermodynamic recycling to circumvent these limits in quantum processors by exploiting failure branches of quantum algorithms, which are usually discarded. The key component is an athermal bath naturally generated during the resetting of a failure branch. By coupling this bath to a target system prior to relaxation, thermodynamic tasks can be performed beyond conventional thermodynamic limits. We apply this framework to information erasure and derive the reduction in heat dissipation analytically. As a demonstration, we implement our framework on IBM's superconducting quantum processor by combining the Harrow--Hassidim--Lloyd algorithm with three-qubit quantum error correction, thereby reducing the heat dissipated in erasing syndrome information. Despite substantial noise and errors in current hardware, our method achieves erasure with heat dissipation below the Landauer limit. This work establishes an operational connection between quantum computing and quantum thermodynamics for resource-efficient quantum computation.