Statistical Mechanics
Entanglement renders free riding redundant in the thermodynamic limit (1808.05149v4)
Shubhayan Sarkar, Colin Benjamin
2018-08-14
The free rider problem is one of the most well-studied problems in economics. The solution proposed mainly is punitive in order to deter people from free riding. In this work, we introduce quantum strategies and study the problem in the thermodynamic limit by drawing analogies with the 1D Ising model. We observe that for maximum entanglement, irrespective of the payoffs, quantum strategy is the equilibrium solution, solving the free rider problem.
Subsystem Trace Distance in Quantum Field Theory (1901.10993v1)
Jiaju Zhang, Paola Ruggiero, Pasquale Calabrese
2019-01-30
We develop a systematic method to calculate the trace distance between two reduced density matrices in 1+1 dimensional quantum field theories. The approach exploits the path integral representation of the reduced density matrices and an ad hoc replica trick. We then extensively apply this method to the calculation of the distance between reduced density matrices of one interval of length in eigenstates of conformal field theories. When the interval is short, using the operator product expansion of twist operators, we obtain a universal form for the leading order in of the trace distance. We compute the trace distances among the reduced density matrices of several low lying states in two-dimensional free massless boson and fermion theories. We compare our analytic conformal results with numerical calculations in XX and Ising spin chains finding perfect agreement.
Critical states in Political Trends. How much reliable is a poll on Twitter? A study by means of the Potts Model (1901.10984v1)
Lucas Nicolao, Massimo Ostilli
2019-01-30
In recent years, Twitter data related to political trends have tentatively been used to make predictions (poll) about several electoral events. Given candidates for an election and a time-series of Twitts (short messages), one can extract the mean trends and the Twitt-to-Twitt correlations, and look for the statistical models that reproduce these data. On the base of several electoral events and assuming a stationary regime, we find out the following: i) the maximization of the entropy singles out a microscopic model (single-Twitt-level) that coincides with a -state Potts model having suitable couplings and external fields to be determined via an inverse problem from the two sets of data; ii) correlations decay as , where is a small fraction of the mean number of Twitts; iii) the simplest statistical models that reproduce these correlations are the multinomial distribution (MD), characterized by external fields, and the mean-field Potts model (MFP), characterized by one coupling; iv) remarkably, this coupling turns out to be always close to its critical value. This results in a MD or MFP model scenario that discriminates between cases in which polls are reliable and not reliable, respectively. More precisely, predictions based on polls should be avoided whenever the data maps to a MFP because anomalous large fluctuations (if ) or sudden jumps (if ) in the trends might take place as a result of a second-order or a first-order phase transition of the MFP, respectively.
Multithermal-multibaric molecular simulations from a variational principle (1811.08253v3)
Pablo M. Piaggi, Michele Parrinello
2018-11-20
We present a method for performing multithermal-multibaric molecular dynamics simulations that sample entire regions of the temperature-pressure (TP) phase diagram. The method uses a variational principle [Valsson and Parrinello, Phys. Rev. Lett. 113, 090601 (2014)] in order to construct a bias that leads to a uniform sampling in energy and volume. The intervals of temperature and pressure are taken as inputs and the relevant energy and volume regions are determined on the fly. In this way the method guarantees adequate statistics for the chosen TP region. We show that our multithermal-multibaric simulations can be used to calculate all static physical quantities for all temperatures and pressures in the targeted region of the TP plane. We illustrate our approach by studying the density anomaly of TIP4P/Ice water.
Incorporating particle flexibility in a density functional description of nematics and cholesterics (1801.10601v8)
Maxime M. C. Tortora, Jonathan P. K. Doye
2018-01-31
We describe a general implementation of the Fynewever-Yethiraj density functional theory (DFT) for the investigation of nematic and cholesteric self-assembly in arbitrary solutions of semi-flexible polymers. The basic assumptions of the theory are discussed in the context of other generalised Onsager descriptions for flexible polyatomic systems. The location of the isotropic-to-nematic phase transition is found to be in good agreement with molecular simulations for elongated chains up to relatively high polymer flexibilities, although the predictions of the theory in the nematic regime lead to gradual underestimations of order parameters with decreasing particle stiffness. This shortcoming is attributed to increasing overestimations of the molecular conformational entropy in higher-density phases, which may not be easily addressed in the formalism of DFT for realistic particle models. Practical consequences of these limitations are illustrated through the application of DFT to systems of near-persistence-length DNA duplexes, whose cholesteric behaviour is found to be strongly contingent on their detailed accessible conformational space in concentrated solutions.
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