Bo Peng (Pacific Northwest National Laboratory), QISE Seminar: When Quantum Systems Remember: Fractional Open-System Dynamics via Random Time

Abstract: Real quantum systems are never perfectly isolated: coupling to an environment causes relaxation and decoherence. The standard “memoryless” (Markovian) description—Lindblad dynamics—often predicts simple exponential decay. Yet in many physical settings, environmental correlations persist, producing memory effects and non-exponential relaxation. The key question is not whether history matters, but how memory decays in time. In this talk, I will introduce a fractional-calculus framework that organizes unitary dynamics, Markovian master equations, and long-memory non-Markovian behavior within a single hierarchy. The central idea is “selective memory”: long-time behavior is often governed by a small subset of slowly decaying correlations rather than the full microscopic history. Technically, fractional dynamics can be understood as standard Lindblad evolution running under a randomized clock (Bochner–Phillips subordination), which preserves physical consistency (complete positivity) while generating algebraic long-time tails. I will illustrate how memory alters the shape of relaxation—not just the decay rate—using simple qubit examples and published benchmarks, and I will briefly discuss how the same structure would enable scalable simulation without explicit time-history storage.

Bio: Bo Peng is a computational scientist at Pacific Northwest National Laboratory (PNNL) in the Physical and Computational Sciences Directorate. His research operates at the intersection of many-body electronic structure theory, Green’s-function approaches to spectroscopy and excited states, quantum algorithms for chemistry and materials, and advanced computing/HPC for large-scale simulation. He develops both theoretical frameworks and production-quality computational tools, with contributions ranging from coupled-cluster/downfolding ideas to open quantum dynamics models that incorporate environmental memory. More broadly, his work aims to connect accurate microscopic theory with scalable computation and emerging quantum hardware, enabling predictive simulations of complex molecular and condensed-phase systems. He is also dedicated to mentoring and collaborates widely across national laboratories and academia.