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Volumn 82, Issue 1, 2010, Pages

Numerical tests of nucleation theories for the Ising models

Author keywords

[No Author keywords available]

Indexed keywords

2D ISING MODEL; 3D ISING MODEL; CLASSICAL NUCLEATION THEORY; COARSE GRAINING; DROPLET SIZES; FIELD THEORY; FREE ENERGY FUNCTION; LOGARITHMIC CORRECTIONS; MARKOV CHAIN; NUCLEATION RATE; NUCLEATION THEORY; NUMERICAL RESULTS; NUMERICAL TESTS; POTENTIAL PROBLEMS; REACTION COORDINATES; RING THEORY; SPIN FLIP; SURFACE ENERGIES; TEMPERATURE DEPENDENCE; THREE-DIMENSIONAL (3D);

EID: 77954825434     PISSN: 15393755     EISSN: 15502376     Source Type: Journal    
DOI: 10.1103/PhysRevE.82.011603     Document Type: Article
Times cited : (47)

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    • Here, the word "prefactor" means the factor in front of the exponential term
    • Here, the word "prefactor" means the factor in front of the exponential term.
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    • Crowding of droplets, or interaction among droplets, have been investigated by Pan and Chandler using very high field up to h=1.18J. They have found for the 3D Ising model, even for fields up to h∼0.8J at kB T=0.6 Tc, the critical nucleus size nc obtained by umbrella sampling and the critical nucleus size nk obtained by commitor distribution matches well, indicating the crowding effect is negligible. Because in this paper, we consider field values much lower than 0.8J, the crowding effect should be very small, as also confirmed by our own data on the two critical sizes. Indeed, the population of up-spins is at most 4% for the highest temperature and highest field conditions considered in our study, and is usually less than 2%. The interaction among those sparse up-spins would not affect free energy significantly
    • Crowding of droplets, or interaction among droplets, have been investigated by Pan and Chandler using very high field up to h = 1.18 J. They have found for the 3D Ising model, even for fields up to h ∼ 0.8 J at k B T = 0.6 T c, the critical nucleus size n c obtained by umbrella sampling and the critical nucleus size n k obtained by commitor distribution matches well, indicating the crowding effect is negligible. Because in this paper, we consider field values much lower than 0.8 J, the crowding effect should be very small, as also confirmed by our own data on the two critical sizes. Indeed, the population of up-spins is at most 4% for the highest temperature and highest field conditions considered in our study, and is usually less than 2%. The interaction among those sparse up-spins would not affect free energy significantly.
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    • 2√ πn is the circumference of a circle with area n. However, a real droplet is not compact but consists of a mixture of up and down spins. The percentage of down-spins in the droplet as a function of T is also absorbed in σeff (T).
    • 2 √ π n is the circumference of a circle with area n. However, a real droplet is not compact but consists of a mixture of up and down spins. The percentage of down-spins in the droplet as a function of T is also absorbed in σ eff (T).
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    • This is against the expected temperature dependence of τ due to suppression of shape fluctuation below the roughening temperature, see Sec..
    • This is against the expected temperature dependence of τ due to suppression of shape fluctuation below the roughening temperature, see Sec..
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    • Perini originally introduced the "ledge" term in order to improve the quality of the fit in the range of n<19. However, we found that fitting to the data in the range of n<19 will lead to large discrepancies in the range of n>100. Given that the droplet theory is supposed to work better in the continuum limit of large n, we believe the function should be fitted to data at large n
    • Perini originally introduced the "ledge" term in order to improve the quality of the fit in the range of n < 19. However, we found that fitting to the data in the range of n < 19 will lead to large discrepancies in the range of n > 100. Given that the droplet theory is supposed to work better in the continuum limit of large n, we believe the function should be fitted to data at large n.
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    • Eq. also fits the data at non-zero h. However, the resulting σ eff 3D from the fit slightly increases with h. For example, σ eff 3D increase by about 3% as h changes from 0 to 0.5
    • Eq. also fits the data at non-zero h. However, the resulting σ eff 3 D from the fit slightly increases with h. For example, σ eff 3 D increase by about 3% as h changes from 0 to 0.5.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.