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Published on: November 11, 2013
A fractional calculus framework for open quantum dynamics: From Liouville to Lindblad to memory kernels
1Physical and Computational Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99354, USA.
Fractional calculus offers a new way to model quantum systems with long memory, bridging Markovian and non-Markovian dynamics. This framework provides a rigorous and efficient method for understanding complex quantum behaviors in chemical physics.
Area of Science:
- Quantum Dynamics
- Open Quantum Systems
- Fractional Calculus
Background:
- Open quantum systems display diverse dynamics, from unitary evolution to irreversible dissipation.
- The Gorini-Kossakowski-Sudarshan-Lindblad equation describes Markovian, completely positive and trace-preserving (CPTP) evolution.
- Many systems exhibit non-Markovian features like algebraic relaxation and coherence backflow, requiring advanced modeling.
Purpose of the Study:
- To develop a unified framework for modeling non-Markovian quantum dynamics using fractional calculus.
- To embed fractional master equations within existing open-system formalisms.
- To provide a computationally efficient and rigorous approach for simulating long-memory effects in quantum systems.
Main Methods:
- Developed a unified framework incorporating fractional master equations into open-system formalisms.
- Utilized Bochner-Phillips subordination to ensure a CPTP representation via averaging over Lindblad semigroups.
- Connected fractional dynamics to established non-Markovian approaches like Nakajima-Zwanzig kernels and hierarchical equations of motion.
Main Results:
- Fractional equations form a structured subclass of memory-kernel models, reducing to the Lindblad form at unit order.
- The framework admits a CPTP representation, ensuring physical consistency.
- Fractional dynamics provide a compact and efficient surrogate for long-memory effects in quantum systems.
Conclusions:
- Fractional calculus offers a rigorous and practical language for modeling non-Markovian quantum dynamics.
- The proposed framework is CPTP-preserving and computationally efficient.
- This approach is particularly valuable for simulating condensed-phase environments with significant long-time memory and dissipation in chemical and physical chemistry.
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