Typical fast thermalization processes in closed many-body systems von Reimann, Peter

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Foundation of statistical mechanics under experimentally realistic conditions von Reimann, Peter

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Eigenstate thermalization: Deutsch's approach and beyond von Reimann, Peter

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Generalization of von Neumann's Approach to Thermalization von Reimann, Peter

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Dynamical Typicality Approach to Eigenstate Thermalization von Reimann, Peter

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Transportless equilibration in isolated many-body quantum systems von Reimann, Peter

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Brownian motors: noisy transport far from equilibrium von Reimann, Peter

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Stalled response near thermal equilibrium in periodically driven systems von Dabelow, Lennart, Reimann, Peter

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Brownian gyrator: a minimal heat engine on the nanoscale von Filliger, Roger, Reimann, Peter

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Conceptualizing Debates in Learning and Educational Research: Toward a Complex Systems Conceptual Framework of Learning von Jacobson, Michael J., Kapur, Manu, Reimann, Peter

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e-Research and learning theory: What do sequence and process mining methods contribute? von Reimann, Peter, Markauskaite, Lina, Bannert, Maria

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Typicality of Pure States Randomly Sampled According to the Gaussian Adjusted Projected Measure von Reimann, Peter

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A circadian clock-regulated toggle switch explains AtGRP7 and AtGRP8 oscillations in Arabidopsis thaliana von Schmal, Christoph, Reimann, Peter, Staiger, Dorothee

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Weak disorder strongly improves the selective enhancement of diffusion in a tilted periodic potential von Reimann, Peter, Eichhorn, Ralf

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Methodological progress in the study of self-regulated learning enables theory advancement von Reimann, Peter

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Nonequilibration, synchronization, and time crystals in isotropic Heisenberg models von Reimann, Peter, Vorndamme, Patrick, Schnack, Jürgen

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Relaxation Theory for Perturbed Many-Body Quantum Systems versus Numerics and Experiment von Dabelow, Lennart, Reimann, Peter

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Typicality of Prethermalization von Reimann, Peter, Dabelow, Lennart

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Canonical thermalization von Reimann, Peter

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Enhancing learning by Open Learner Model (OLM) driven data design von Kay, Judy, Bartimote, Kathryn, Kitto, Kirsty, Kummerfeld, Bob, Liu, Danny, Reimann, Peter

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