$ID = get_the_ID();
add_post_meta($ID, 'Author', 'L. Peliti', True);
add_post_meta($ID, 'Credits', '2', True);
$AUTHOR = get_post_meta(get_the_ID(),'Author',True);
$CREDITS = get_post_meta(get_the_ID(),'Credits',True);
echo "
by $AUTHOR ($CREDITS credits)
“;
?>
Starting date: Friday, 20 April 2018
When: all fridays, 11:00-13:00
Where: SISSA, First Floor, Room 138
Number of lectures: 6
Programme
1. Motivation:
- Entropy and information, from Boltzmann to Gibbs to Shannon
- Information devices as non-equilibrium statistical systems
2. Stochastic thermodynamics:
- Basic structure
- Relation with ordinary thermodynamics and statistical mechanics
3. Prerequisites:
- Equilibrium thermodynamics
- Equilibrium statistical mechanics
- Basics of information theory:
– Shannon entropy
– Kullback-Leibler divergence
– Mutual and conditional information - Basics of large-deviation theory
4. Basic concepts of stochastic thermodynamics:
- Systems in stochastic thermodynamics
- Work and heat in stochastic thermodynamics
- Mesoscopic and calorimetric heat
- Fluctuating entropy
- Multiple baths
5. Fluctuation relations:
- Irreversibility and entropy production
- Fluctuation relations: Integral and detailed
- Jarzynski and Crooks relations and their use
- Hatano-Sasa relation
6. Thermodynamics of information:
- Thermodynamical computation systems
- Reversibility:
– In thermodynamics
– In computation
– In stochastic thermodynamics - Entropy balance in computation and feedback
- Speed-accuracy tradeoffs
7. Experimental Maxwell demons:
- Sagawa-Ueda-Sano Maxwell staircase
- Landauer principle
- Sensing
8. Ramifications:
- Analogy between work extraction, gambling and population dynamics
- Statistical physics of adaptation
- Historical (retrospective) fitness
