S
Shang-keng Ma
Researcher at University of California, San Diego
Publications - 24
Citations - 7074
Shang-keng Ma is an academic researcher from University of California, San Diego. The author has contributed to research in topics: Ising model & Phase transition. The author has an hindex of 20, co-authored 24 publications receiving 6760 citations.
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Book
Modern Theory of Critical Phenomena
TL;DR: Ma as mentioned in this paper introduces the beginner to fundamental theoretical concepts such as mean field theory, scaling hypothesis, and renormalization group, with emphasis on the underlying physics and the basic assumptions involved.
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Random-Field Instability of the Ordered State of Continuous Symmetry
Yoseph Imry,Shang-keng Ma +1 more
TL;DR: In this article, it was shown that when the order parameter has a continuous symmetry, the ordered state is unstable against an arbitrarily weak random field in less than four dimensions and the borderline dimensionality above which mean-field-theory results hold is six.
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First-Order Phase Transitions in Superconductors and Smectic- A Liquid Crystals
TL;DR: The superconducting phase transition is predicted to be weakly first order, because of effects of the intrinsic fluctuating magnetic field, according to a Wilson-Fisher $\ensuremath{\epsilon}$expansion analysis, as well as a generalized mean-field calculation appropriate to a type-I superconductor.
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Low-temperature properties of the random Heisenberg antiferromagnetic chain
Chandan Dasgupta,Shang-keng Ma +1 more
TL;DR: In this article, the one-dimensional quantum spin-\textonehalf{} Heisenberg antiferromagnetic model with randomly distributed interaction strengths is solved approximately for several different distributions.
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Random Antiferromagnetic Chain
TL;DR: In this article, the quantum spin-textonehalf{} Heisenberg antiferromagnet in one dimension with randomly distributed coupling constants is solved approximately, and groundstate energies and low-temperature properties are obtained for several distributions of coupling constants (including both singular and nonsingular distributions).