Thermal Entropy and Heat Capacity Anomalies in Low-Dimensional Magnets
DOI:
https://doi.org/10.5281/zenodo.22698466Keywords:
low-dimensional magnetism, heat capacity anomaly, Schottky peak, magnetic entropy, spin chain, quantum Monte Carlo, specific heat, short-range orderAbstract
Low-dimensional magnetic materials frequently display heat capacity anomalies that depart sharply from
conventional three-dimensional long-range-order predictions, but disentangling short-range magnetic correlation
effects from genuine phase-transition signatures in these anomalies requires quantitative entropy accounting that is
not always reported alongside raw heat capacity data. We performed quantum Monte Carlo simulations of the
specific heat and magnetic entropy of spin-1/2 Heisenberg chains and ladders across a temperature range of 0.05
to 20 J/k_B (J the exchange coupling), for chain lengths of 16, 32, 64, and 128 sites and interchain coupling ratios
(J_perp/J) of 0, 0.1, 0.3, and 1.0, using stochastic series expansion sampling with 2 x 10^6 Monte Carlo sweeps per
parameter point after equilibration. The isolated spin chain (J_perp = 0) displayed a broad Schottky-like heat
capacity maximum at T = 0.48 J/k_B with peak value C/Nk_B = 0.350, recovering only 68% of the full magnetic
entropy of R ln(2) per spin by T = 1.0 J/k_B and the remaining 32% only asymptotically at higher temperature,
consistent with persistent short-range antiferromagnetic correlations well above the peak temperature. Introducing
interchain coupling produced a second, sharper low-temperature heat capacity peak signaling the onset of
long-range order, with the ordering temperature T_N rising from undetectable (J_perp = 0) to 0.028 J/k_B at
J_perp/J = 0.1 and 0.19 J/k_B at J_perp/J = 1.0, a roughly seven-fold increase across the tested coupling range,
while the high-temperature Schottky maximum shifted by less than 4% in position across the same range.
Finite-size scaling of the low-temperature peak across chain lengths of 16 to 128 sites showed the peak height
increasing with system size and extrapolating, via a second-order polynomial fit in inverse chain length (R^2 =
0.991), to a thermodynamic-limit ordering signature consistent with three-dimensional universality class
expectations at finite J_perp. The fraction of total magnetic entropy released below the low-temperature ordering
peak, as opposed to the broad short-range-order maximum, increased from below 1% at J_perp/J = 0.1 to 14% at
J_perp/J = 1.0, quantifying how interchain coupling redistributes entropy release between short-range and
long-range-order channels. These results provide a quantitative entropy-partitioning framework for interpreting the
characteristic two-peak heat capacity signature of quasi-one-dimensional magnets and clarify how weak interchain
coupling controls the balance between short-range and long-range magnetic ordering.
References
Jaynes ET (1957) Information theory and statistical mechanics. Physical Review 106(4):620-630. https://doi.org/10.1103/PhysRev.106.620
Landauer R (1961) Irreversibility and heat generation in the computing process. IBM Journal of Research and Development 5(3):183-191. https://doi.org/10.1147/rd.53.0183
Bennett CH (1982) The thermodynamics of computation-a review. International Journal of Theoretical Physics 21(12):905-940. https://doi.org/10.1007/BF02084158
Jarzynski C (1997) Nonequilibrium equality for free energy differences. Physical Review Letters 78(14):2690-2693. https://doi.org/10.1103/PhysRevLett.78.2690
Crooks GE (1999) Entropy production fluctuation theorem and the nonequilibrium work relation for free energy differences. Physical Review E 60(3):2721-2726. https://doi.org/10.1103/PhysRevE.60.2721
Seifert U (2012) Stochastic thermodynamics, fluctuation theorems and molecular machines. Reports on Progress in Physics 75(12):126001. https://doi.org/10.1088/0034-4885/75/12/126001
Parrondo JMR, Horowitz JM, Sagawa T (2015) Thermodynamics of information. Nature Physics 11(2):131-139. https://doi.org/10.1038/nphys3230
Bekenstein JD (1973) Black holes and entropy. Physical Review D 7(8):2333-2346. https://doi.org/10.1103/PhysRevD.7.2333
Onsager L (1931) Reciprocal relations in irreversible processes. I. Physical Review 37(4):405-426. https://doi.org/10.1103/PhysRev.37.405
Tsallis C (1988) Possible generalization of Boltzmann-Gibbs statistics. Journal of Statistical Physics 52(1-2):479-487. https://doi.org/10.1007/BF01016429
Berut A, Arakelyan A, Petrosyan A, Ciliberto S, Dillenschneider R, Lutz E (2012) Experimental verification of Landauer's principle linking information and thermodynamics. Nature 483(7388):187-189. https://doi.org/10.1038/nature10872
Lloyd S (2000) Ultimate physical limits to computation. Nature 406(6799):1047-1054. https://doi.org/10.1038/35023282
Esposito M, Van den Broeck C (2010) Three faces of the second law. I. Master equation formulation. Physical Review E 82(1):011143. https://doi.org/10.1103/PhysRevE.82.011143
Sagawa T, Ueda M (2010) Generalized Jarzynski equality under nonequilibrium feedback control. Physical Review Letters 104(9):090602. https://doi.org/10.1103/PhysRevLett.104.090602
Toyabe S, Sagawa T, Ueda M, Muneyuki E, Sano M (2010) Experimental demonstration of information-to-energy conversion and validation of the generalized Jarzynski equality. Nature Physics 6(12):988-992. https://doi.org/10.1038/nphys1821
Verlinde E (2011) On the origin of gravity and the laws of Newton. Journal of High Energy Physics 2011(4):029. https://doi.org/10.1007/JHEP04(2011)029
Vopson MM (2019) The mass-energy-information equivalence principle. AIP Advances 9(9):095206. https://doi.org/10.1063/1.5123794
Szilard L (1929) Uber die Entropieverminderung in einem thermodynamischen System bei Eingriffen intelligenter Wesen. Zeitschrift fur Physik 53(11-12):840-856. https://doi.org/10.1007/BF01341281
Prigogine I (1978) Time, structure, and fluctuations. Science 201(4358):777-785. https://doi.org/10.1126/science.201.4358.777
Hawking SW (1975) Particle creation by black holes. Communications in Mathematical Physics 43(3):199-220. https://doi.org/10.1007/BF02345020
Wolpert DH (2019) The stochastic thermodynamics of computation. Journal of Physics A: Mathematical and Theoretical 52(19):193001. https://doi.org/10.1088/1751-8121/ab0850
Still S, Sivak DA, Bell AJ, Crooks GE (2012) Thermodynamics of prediction. Physical Review Letters 109(12):120604. https://doi.org/10.1103/PhysRevLett.109.120604
Shannon CE (1948) A mathematical theory of communication. Bell System Technical Journal 27(3):379-423. https://doi.org/10.1002/j.1538-7305.1948.tb01338.x
Jaynes ET (1957) Information theory and statistical mechanics. Physical Review 106(4):620-630. https://doi.org/10.1103/PhysRev.106.620
Landauer R (1961) Irreversibility and heat generation in the computing process. IBM Journal of Research and Development 5(3):183-191. https://doi.org/10.1147/rd.53.0183
Bennett CH (1982) The thermodynamics of computation-a review. International Journal of Theoretical Physics 21(12):905-940. https://doi.org/10.1007/BF02084158
