9,490 research outputs found
A graph theoretical analysis of the energy landscape of model polymers
In systems characterized by a rough potential energy landscape, local
energetic minima and saddles define a network of metastable states whose
topology strongly influences the dynamics. Changes in temperature, causing the
merging and splitting of metastable states, have non trivial effects on such
networks and must be taken into account. We do this by means of a recently
proposed renormalization procedure. This method is applied to analyze the
topology of the network of metastable states for different polypeptidic
sequences in a minimalistic polymer model. A smaller spectral dimension emerges
as a hallmark of stability of the global energy minimum and highlights a
non-obvious link between dynamic and thermodynamic properties.Comment: 15 pages, 15 figure
The structure of the hard sphere solid
We show that near densest-packing the perturbations of the HCP structure
yield higher entropy than perturbations of any other densest packing. The
difference between the various structures shows up in the correlations between
motions of nearest neighbors. In the HCP structure random motion of each sphere
impinges slightly less on the motion of its nearest neighbors than in the other
structures.Comment: For related papers see:
http://www.ma.utexas.edu/users/radin/papers.htm
Optimization by Quantum Annealing: Lessons from Simple Cases
This paper investigates the basic behavior and performance of simulated
quantum annealing (QA) in comparison with classical annealing (CA). Three
simple one dimensional case study systems are considered, namely a parabolic
well, a double well, and a curved washboard. The time dependent Schr\"odinger
evolution in either real or imaginary time describing QA is contrasted with the
Fokker Planck evolution of CA. The asymptotic decrease of excess energy with
annealing time is studied in each case, and the reasons for differences are
examined and discussed. The Huse-Fisher classical power law of double well CA
is replaced with a different power law in QA. The multi-well washboard problem
studied in CA by Shinomoto and Kabashima and leading classically to a
logarithmic annealing even in the absence of disorder, turns to a power law
behavior when annealed with QA. The crucial role of disorder and localization
is briefly discussed.Comment: 16 pages, 9 figure
Weak first order transition in the three-dimensional site-diluted Ising antiferromagnet in a magnetic field
We perform intensive numerical simulations of the three-dimensional
site-diluted Ising antiferromagnet in a magnetic field at high values of the
external applied field. Even if data for small lattice sizes are compatible
with second-order criticality, the critical behavior of the system shows a
crossover from second-order to first-order behavior for large system sizes,
where signals of latent heat appear. We propose "apparent" critical exponents
for the dependence of some observables with the lattice size for a generic
(disordered) first-order phase transition.Comment: Final version, accepted for publicatio
Microcanonical finite-size scaling in specific heat diverging 2nd order phase transitions
A Microcanonical Finite Site Ansatz in terms of quantities measurable in a
Finite Lattice allows to extend phenomenological renormalization (the so called
quotients method) to the microcanonical ensemble. The Ansatz is tested
numerically in two models where the canonical specific-heat diverges at
criticality, thus implying Fisher-renormalization of the critical exponents:
the 3D ferromagnetic Ising model and the 2D four-states Potts model (where
large logarithmic corrections are known to occur in the canonical ensemble). A
recently proposed microcanonical cluster method allows to simulate systems as
large as L=1024 (Potts) or L=128 (Ising). The quotients method provides
extremely accurate determinations of the anomalous dimension and of the
(Fisher-renormalized) thermal exponent. While in the Ising model the
numerical agreement with our theoretical expectations is impressive, in the
Potts case we need to carefully incorporate logarithmic corrections to the
microcanonical Ansatz in order to rationalize our data.Comment: 13 pages, 8 figure
Data clustering and noise undressing for correlation matrices
We discuss a new approach to data clustering. We find that maximum likelihood
leads naturally to an Hamiltonian of Potts variables which depends on the
correlation matrix and whose low temperature behavior describes the correlation
structure of the data. For random, uncorrelated data sets no correlation
structure emerges. On the other hand for data sets with a built-in cluster
structure, the method is able to detect and recover efficiently that structure.
Finally we apply the method to financial time series, where the low temperature
behavior reveals a non trivial clustering.Comment: 8 pages, 5 figures, completely rewritten and enlarged version of
cond-mat/0003241. Submitted to Phys. Rev.
Scaling Analysis of the Site-Diluted Ising Model in Two Dimensions
A combination of recent numerical and theoretical advances are applied to
analyze the scaling behaviour of the site-diluted Ising model in two
dimensions, paying special attention to the implications for multiplicative
logarithmic corrections. The analysis focuses primarily on the odd sector of
the model (i.e., that associated with magnetic exponents), and in particular on
its Lee-Yang zeros, which are determined to high accuracy. Scaling relations
are used to connect to the even (thermal) sector, and a first analysis of the
density of zeros yields information on the specific heat and its corrections.
The analysis is fully supportive of the strong scaling hypothesis and of the
scaling relations for logarithmic corrections.Comment: 15 pages, 3 figures. Published versio
A genetic-based algorithm for personalized resistance training
Association studies have identified dozens of genetic variants linked to training responses and sport-related traits. However, no intervention studies utilizing the idea of personalised training based on athlete’s genetic profile have been conducted. Here we propose an algorithm that allows achieving greater results in response to high- or low-intensity resistance training programs by predicting athlete’s potential for the development of power and endurance qualities with the panel of 15 performance-associated gene polymorphisms. To develop and validate such an algorithm we performed two studies in independent cohorts of male athletes (study 1: athletes from different sports (n=28); study 2: soccer players (n=39)). In both studies athletes completed an eight-week high- or low-intensity resistance training program, which either matched or mismatched their individual genotype. Two variables of explosive power and aerobic fitness, as measured by the countermovement jump (CMJ) and aerobic 3-min cycle test (Aero3) were assessed pre and post 8 weeks of resistance training. In study 1, the athletes from the matched groups (i.e. high-intensity trained with power genotype or low-intensity
trained with endurance genotype) significantly increased results in CMJ (P=0.0005) and Aero3 (P=0.0004). Whereas, athletes from the mismatched group (i.e. high-intensity trained with endurance genotype or lowintensity trained with power genotype) demonstrated non-significant improvements in CMJ (P=0.175) and less prominent results in Aero3 (P=0.0134). In study 2, soccer players from the matched group also demonstrated significantly greater (P<0.0001) performance changes in both tests compared to the mismatched group. Among non- or low responders of both studies, 82% of athletes (both for CMJ and Aero3) were from the mismatched group (P<0.0001). Our results indicate that matching the individual’s genotype with the appropriate training modality leads to more effective resistance training. The developed algorithm may be used to guide individualised resistance-training interventions
Ising exponents in the two-dimensional site-diluted Ising model
We study the site-diluted Ising model in two dimensions with Monte Carlo
simulations. Using finite-size scaling techniques we compute the critical
exponents observing deviations from the pure Ising ones. The differences can be
explained as the effects of logarithmic corrections, without requiring to
change the Universality Class.Comment: 7 pages, 2 postscript figures. Reference correcte
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