We study the coarse-graining approach to derive a generator for the evolution of an open quantum system over a finite time interval. The approach does not require a secular approximation but nevertheless generally leads to a Lindblad-Gorini-Kossakowski-Sudarshan generator. By combining the formalism with full counting statistics, we can demonstrate a consistent thermodynamic framework, once the switching work required for the coupling and decoupling with the reservoir is included. Particularly, we can write the second law in standard form, with the only difference that heat currents must be defined with respect to the reservoir. We exemplify our findings with simple but pedagogical examples.
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http://dx.doi.org/10.3390/e22050525 | DOI Listing |
Polymers (Basel)
January 2025
Micron School of Material Science and Engineering, Boise State University, Boise, ID 83725, USA.
Carbon-fiber composites with thermoplastic matrices offer many processing and performance benefits in aerospace applications, but the long relaxation times of polymers make it difficult to predict how the structure of the matrix depends on its chemistry and how it was processed. Coarse-grained models of polymers can enable access to these long-time dynamics, but can have limited applicability outside the systems and state points that they are validated against. Here we develop and validate a minimal coarse-grained model of the aerospace thermoplastic poly(etherketoneketone) (PEKK).
View Article and Find Full Text PDFCurr Opin Struct Biol
January 2025
Department of Chemistry, Chicago Center for Theoretical Chemistry, James Franck Institute, and Institute for Biophysical Dynamics, The University of Chicago, Chicago, IL 60637, USA. Electronic address:
Machine-learning methods have gained significant attention in the computational chemistry community as a viable approach to molecular modeling and analysis. Recent successes in utilizing neural networks to learn atomistic force-fields which 'coarse-grain' electronic structure have inspired similar applications to the thermodynamic coarse-graining of chemical and biological systems. In this review, we discuss the current viability and challenges in using machine-learning methods to represent coarse-grained force-fields, as well as the utility of machine-learning in various aspects of coarse-grained modeling.
View Article and Find Full Text PDFCrit Care
December 2024
Brain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
Background: Entropy quantifies the level of disorder within a system. Low entropy reflects increased rigidity of homeostatic feedback systems possibly reflecting failure of protective physiological mechanisms like cerebral autoregulation. In traumatic brain injury (TBI), low entropy of heart rate and intracranial pressure (ICP) predict unfavorable outcome.
View Article and Find Full Text PDFPhys Rev Lett
November 2024
SISSA, via Bonomea 265, 34136 Trieste, Italy.
We study thermodynamic phase transitions between integrable and chaotic dynamics. We do so by analyzing models that interpolate between the chaotic double scaled Sachdev-Ye-Kitaev (SYK) and the integrable p-spin systems, in a limit where they are described by chord diagrams. We develop a path integral formalism by coarse graining over the diagrams, which we use to argue that the system has two distinct phases: one is continuously connected to the chaotic system, and the other to the integrable.
View Article and Find Full Text PDFJ Chem Theory Comput
December 2024
Computer, Computational, and Statistical Sciences Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States.
Coarse-graining is a molecular modeling technique in which an atomistic system is represented in a simplified fashion that retains the most significant system features that contribute to a target output while removing the degrees of freedom that are less relevant. This reduction in model complexity allows coarse-grained molecular simulations to reach increased spatial and temporal scales compared with corresponding all-atom models. A core challenge in coarse-graining is to construct a force field that represents the interactions in the new representation in a way that preserves the atomistic-level properties.
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