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Shang-keng Ma

Bio: 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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01 May 1976
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.
Abstract: An important contributor to our current understanding of critical phenomena, Ma introduces the beginner--especially the graduate student with no previous knowledge of the subject-to fundamental theoretical concepts such as mean field theory, the scaling hypothesis, and the renormalization group. He then goes on to apply the renormalization group to selected problems, with emphasis on the underlying physics and the basic assumptions involved.

2,300 citations

Journal ArticleDOI
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.
Abstract: Phase transitions are considered in systems where the field conjugate to the order parameter is static and random. It is demonstrated 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. The borderline dimensionality above which mean-field-theory results hold is six. (auth)

1,911 citations

Journal ArticleDOI
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.
Abstract: 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. Similar results hold for the phase transition from a smectic-$A$ to a nematic liquid crystal.

653 citations

Journal ArticleDOI
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.
Abstract: The one-dimensional quantum spin-\textonehalf{} Heisenberg antiferromagnetic model with randomly distributed interaction strengths is solved approximately for several different distributions. Ground-state energy and low-temperature properties are evaluated. Universal qualitative features are found in the specific heat and the magnetic susceptibility, which display a power-law dependence on temperature. Such features hold for nonsingular distributions as well as for distributions with power-law divergence at the origin. The approximate method of solution is based on successive eliminations of spins coupled by the maximum coupling constant.

370 citations

Journal ArticleDOI
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).
Abstract: The quantum spin-\textonehalf{} Heisenberg antiferromagnet in one dimension with randomly distributed coupling constants is solved approximately. Ground-state energies and low-temperature properties are obtained for several distributions of coupling constants (including both singular and nonsingular distributions). Power-law temperature dependence in specific heat and in susceptibility are found for all distributions studied.

314 citations


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TL;DR: In this paper, a simple model based on the power-law degree distribution of real networks was proposed, which was able to reproduce the power law degree distribution in real networks and to capture the evolution of networks, not just their static topology.
Abstract: The emergence of order in natural systems is a constant source of inspiration for both physical and biological sciences. While the spatial order characterizing for example the crystals has been the basis of many advances in contemporary physics, most complex systems in nature do not offer such high degree of order. Many of these systems form complex networks whose nodes are the elements of the system and edges represent the interactions between them. Traditionally complex networks have been described by the random graph theory founded in 1959 by Paul Erdohs and Alfred Renyi. One of the defining features of random graphs is that they are statistically homogeneous, and their degree distribution (characterizing the spread in the number of edges starting from a node) is a Poisson distribution. In contrast, recent empirical studies, including the work of our group, indicate that the topology of real networks is much richer than that of random graphs. In particular, the degree distribution of real networks is a power-law, indicating a heterogeneous topology in which the majority of the nodes have a small degree, but there is a significant fraction of highly connected nodes that play an important role in the connectivity of the network. The scale-free topology of real networks has very important consequences on their functioning. For example, we have discovered that scale-free networks are extremely resilient to the random disruption of their nodes. On the other hand, the selective removal of the nodes with highest degree induces a rapid breakdown of the network to isolated subparts that cannot communicate with each other. The non-trivial scaling of the degree distribution of real networks is also an indication of their assembly and evolution. Indeed, our modeling studies have shown us that there are general principles governing the evolution of networks. Most networks start from a small seed and grow by the addition of new nodes which attach to the nodes already in the system. This process obeys preferential attachment: the new nodes are more likely to connect to nodes with already high degree. We have proposed a simple model based on these two principles wich was able to reproduce the power-law degree distribution of real networks. Perhaps even more importantly, this model paved the way to a new paradigm of network modeling, trying to capture the evolution of networks, not just their static topology.

18,415 citations

Journal ArticleDOI
TL;DR: The renormalization group theory has been applied to a variety of dynamic critical phenomena, such as the phase separation of a symmetric binary fluid as mentioned in this paper, and it has been shown that it can explain available experimental data at the critical point of pure fluids, and binary mixtures, and at many magnetic phase transitions.
Abstract: An introductory review of the central ideas in the modern theory of dynamic critical phenomena is followed by a more detailed account of recent developments in the field. The concepts of the conventional theory, mode-coupling, scaling, universality, and the renormalization group are introduced and are illustrated in the context of a simple example---the phase separation of a symmetric binary fluid. The renormalization group is then developed in some detail, and applied to a variety of systems. The main dynamic universality classes are identified and characterized. It is found that the mode-coupling and renormalization group theories successfully explain available experimental data at the critical point of pure fluids, and binary mixtures, and at many magnetic phase transitions, but that a number of discrepancies exist with data at the superfluid transition of $^{4}\mathrm{He}$.

4,980 citations

Journal ArticleDOI
TL;DR: In this article, the most characteristic properties of spin glass systems are described, and related phenomena in other glassy systems (dielectric and orientational glasses) are mentioned, and a review summarizes recent developments in the theory of spin glasses, as well as pertinent experimental data.
Abstract: This review summarizes recent developments in the theory of spin glasses, as well as pertinent experimental data. The most characteristic properties of spin glass systems are described, and related phenomena in other glassy systems (dielectric and orientational glasses) are mentioned. The Edwards-Anderson model of spin glasses and its treatment within the replica method and mean-field theory are outlined, and concepts such as "frustration," "broken replica symmetry," "broken ergodicity," etc., are discussed. The dynamic approach to describing the spin glass transition is emphasized. Monte Carlo simulations of spin glasses and the insight gained by them are described. Other topics discussed include site-disorder models, phenomenological theories for the frozen phase and its excitations, phase diagrams in which spin glass order and ferromagnetism or antiferromagnetism compete, the Ne\'el model of superparamagnetism and related approaches, and possible connections between spin glasses and other topics in the theory of disordered condensed-matter systems.

3,926 citations

Journal ArticleDOI
TL;DR: In this paper, the modern formulation of the renormalization group is explained for both critical phenomena in classical statistical mechanics and quantum field theory, and the expansion in ϵ = 4−d is explained [ d is the dimension of space (statistical mechanics) or space-time (quantum field theory)].

3,882 citations

Journal ArticleDOI
TL;DR: Block copolymers are macromolecules composed of sequences, or blocks, of chemically distinct repeat units that make possible the sequential addition of monomers to various carbanion-ter­ minated ("living") linear polymer chains.
Abstract: Block copolymers are macromolecules composed of sequences, or blocks, of chemically distinct repeat units. The development of this field originated with the discovery of termination-free anionic polymerization, which made possible the sequential addition of monomers to various carbanion-ter­ minated ("living") linear polymer chains. Polymerization of just two dis­ tinct monomer types (e.g. styrene and isoprene) leads to a class of materials referred to as AB block copolymers. Within this class, a variety of molec­ ular architectures is possible. For example, the simplest combination, obtained by the two-step anionic polymerization of A and B monomers, is an (A-B) dioblock copolymer. A three-step reaction provides for the preparation of (ABA) or (BAB) triblock copolymer. Alternatively, "living" diblock copolymers can be reacted with an n-functional coupling agent to produce (A-B)n star-block copolymers, where n = 2 constitutes a triblock copolymer. Several representative (A-B)n block copolymer architectures

3,475 citations