Tan · wovepaper

most citedClassification for the universal scaling of Néel temperature and staggered magnetization density of three-dimensional dimerized spin-1/2 antiferromagnets

7 citations · 9 across the 3 of their papers we have counts for

collaborators

3 papers

cond-mat.dis-nn2021★ 1 cited

A universal neural network for learning phases and criticalities

D. -R. Tan, J. -H. Peng, Y. -H. Tseng +1

A universal supervised neural network (NN) relevant to compute the associated criticalities of real experiments studying phase transitions is constructed. The validity of the built…

cond-mat.str-el2021★ 1 cited

Quantum criticality at finite temperature for two-dimensional $J Q_{3}$ models on the square and the honeycomb lattices

J. -H. Peng, D. -R. Tan, L. -W. Huang +1

We study the quantum criticality at finite temperature for three two-dimensional (2D) $J Q_{3}$ models using the first principle nonperturbative quantum Monte Carlo calculations (QMC)…

cond-mat.str-el2017★ 7 cited

Classification for the universal scaling of Néel temperature and staggered magnetization density of three-dimensional dimerized spin-1/2 antiferromagnets

D. -R. Tan, C. -D. Li, F. -J. Jiang

Inspired by the recently theoretical development relevant to the experimental data of TlCuCl $_{3}$ , particularly those associated with the universal scaling between the Néel temperat…

A universal neural network for learning phases and criticalities

Quantum criticality at finite temperature for two-dimensional JQ3​ models on the square and the honeycomb lattices

Classification for the universal scaling of Néel temperature and staggered magnetization density of three-dimensional dimerized spin-1/2 antiferromagnets

Quantum criticality at finite temperature for two-dimensional $J Q_{3}$ models on the square and the honeycomb lattices