Inadequacy of von Neumann entropy for characterizing extractable work
By Oscar C. O. Dahlsten, Renato Renner, Elisabeth Rieper, Vlatko Vedral. 2009
162 citations recorded by the source corpus.
The lack of knowledge that an observer has about a system limits the amount of work it can extract. This lack of knowledge is normally quantified using the Gibbs/von Neumann entropy. We show that this standard approach is, surprisingly, only correct in very specific circumstances. In general, one should use the recently developed smooth entropy approach. For many common physical situations, including large but internally correlated systems, the resulting values for the extractable work can deviate arbitrarily from those suggested by the standard approach.
Subfields: Cognitive Neuroscience, Statistical and Nonlinear Physics
View Paper: https://www.semanticscholar.org/paper/ff14d59f4983ac0def3626349f7a9807ef296fad
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In Cognitive Neuroscience
In Statistical and Nonlinear Physics
- Mauro Paternostro
- Gabriel T. Landi
- David Jennings
- Matteo Lostaglio
- Terry Rudolph
- Marcus Huber
- Paul Skrzypczyk
- Michal Horodecki
Citations in the corpus
- Fundamental limitations for quantum and nanoscale thermodynamics (2011, background): “The significance of ǫ is that it takes into account the situation where we allow a tiny probability ǫ of failing to draw work[22].”
- Irreversible entropy production: From classical to quantum (2020, background): “(220) is somewhat pathological: It says work can only be extracted when ρS does not have full support (Dahlsten et al., 2011).”
- The role of quantum information in thermodynamics—a topical review (2015, background): “In that case ; r s monotones for this setting are called Schur monotone functions, of which information-theoretical entropy measures are examples [78, 80–83].”
- Quantum coherence, time-translation symmetry and thermodynamics (2014, background): “[10] O.”
- Description of quantum coherence in thermodynamic processes requires constraints beyond free energy (2014, background): “For small systems the distributions involved can be quite broad and structured and so it is arguably more natural to analyse it in finer terms, such as those developed within “single-shot” regimes [42, 67].”