Dear students,
I uploaded on Moodle several papers related to Large Deviation Theory, Fluctuation Theorems, Stochastic Thermodynamics and Information Thermodynamics that could be chosen for your exam projects.
The current list of available exam projects is then reported below (the new projects are from 25 to 29).
I assume that those of you that plan to take the exam within the winter session already chose their project. From now on, I will assign them gouping your requests through two deadlines per month, on 15th and at the end of the month, beginning with January 31st.
Kind regards
Antonio Trovato
--------------------- available exam projects -----------------------------
BOOK SECTIONS
-- Livi-Politi book
6) Interface Roughness: scaling, exponents, self-affinity; general derivation of WE,KPZ equations (5.2, 5.3, 5.4, 5.5)
7) Edwards-Wilkinson equation (5.6)
8) Kardar-Parisi-Zhang equation (5.7)
-- Mezard-Montanari book
9) Introduction to Combinatorial Optimization and Complexity classes (P vs NP): (chapter 3)
10) Proof of the "direct part" of channel coding theorem for a generic channel (6.4,6.8) and of the "converse part" for BST (6.5)
11) Number partitioning (chapter 7)
COMPUTATIONAL PROJECTS
12) Domany-Kinzel model (d=1+1), evaluation of rho(t,p) -> quenched average (q fixed), omogeneous initial conditions: find p_c and critical exponent using phenomenological scaling -> fig. 20 Hinrichsen 2001
13) Contact processes (1+1) DP vs. DyP (p2 = 0; p2>0): find transition point and critical exponents for Dyp
14) Parity conserving model (1+1): PC vs DP; find transition point and critical exponents
16) TASEP model with open boundary conditions: (random or zero initial conditions) find asymptotic stationary density profiles in the different phases
17) BRIDGE model: (random or zero initial conditions) find asymptotic stationary density profiles in the different phases
16) TASEP model with open boundary conditions: (random or zero initial
conditions) find asymptotic stationary density profiles in the
different phases
17) BRIDGE model: (random or zero initial conditions) find asymptotic
stationary density profiles in the different phases
SCIENTIFIC PAPERS
21) Review Maximum entropy methods to study protein sequences: Weigt
22) Review KPZ: Corwin
23) Review of Reaction-Diffusion models: Frey, Luthey-Schulten
24) Non equilibrium statistical physics: Van den Broek
25) Information thermodynamics; a very recent book (2019) where concepts from information theory and stochastic thermodynamics (including fluctuation theorems) are put together to discuss topics such as the Landauer principle and the experimental realization of Maxwell demon.
a) chapter 1 (Lent): a broad introduction to the connection between
information theory and thermodynamics, focusing on entropy and the Landauer
principle, also for quantum systems
b) chapter 3,4 (Sagawa and Porod); second law, entropy production and
reversibility in "computation thermodynamics"
c) chapter 5 (Ciliberto and Lutz): experimental information physics:
from Maxwell to Landauer
26) Fluctuation theorems
a) section 3.3.2 and all section 4 from Ritort review: FT for NESS with a specific example for a gaussian trapping potential (the solution of FP equation with a quadratic potential is obtained in Livi-Politi 1.6.3 -elastic force, Ornstein-Uhlenbeck process -; section 4.1.1. in RItort review is the same as 1.6.5 in Livi-Politi); section 4.2.3 is particularly relevant (efficient strategies to extract free energy measurements from non-equlibrium experiments)
b) all section 5 from Ritort review: use of FT and JE to construct a generalized thermodynamics in path space; large deviation theory is also used
27) Quantum fluctuations theorems
a) Wojcik 2004: classical and quantum FT derived in the case of heat exchange between to objects kept at different temperatures
b) Morillo 2008: Microcanonical quantum FT
c) Sagawa 2018: general review on quantum FT
28) Stochastic Ther,modynamics:
Seifert 2018; this review deals with FT as well as with information thermodynamics, in particular with the very recent topic of thermodynamic uncertainty relations
29) Large Deviations:
a) Touchette 2018: a review on large deviations for dynamical observable in Markov processes
b) Gherardini 2019: large deviations for quantum observables