Liouville quantum gravity with matter central charge in (1,25)(1,25): a probabilistic approach

There is a substantial literature concerning Liouville quantum gravity (LQG) in two dimensions with conformal matter field of central charge ${\mathbf{c}}_{\mathrm M}\in(-\infty,1]$. Via the DDK ansatz, LQG can equivalently be described as the random geometry obtained by exponentiating $\gamma$ times a variant of the planar Gaussian free field (GFF), where $\gamma\in(0,2]$ satisfies $\mathbf c_{\mathrm M}=25-6(2/\gamma+\gamma/2)^2$. Physics considerations suggest that LQG should also make sense in the regime when $\mathbf c_{\mathrm M}>1$. However, the behavior in this regime is rather mysterious in part because the corresponding value of $\gamma$ is complex, so analytic continuations of various formulas give complex answers which are difficult to interpret in a probabilistic setting. We introduce and study a discretization of LQG which makes sense for all values of $\mathbf c_{\mathrm M}\in(-\infty,25)$. Our discretization consists of a random planar map, defined as the adjacency graph of a tiling of the plane by dyadic squares which all have approximately the same "LQG size" with respect to the GFF. We prove that several formulas for dimension-related quantities are still valid for $\mathbf c_{\mathrm M}\in(1,25)$, with the caveat that the dimension is infinite when the formulas give a complex answer. In particular, we prove an extension of the (geometric) KPZ formula for $\mathbf c_{\mathrm M}\in(1,25)$, which gives a finite quantum dimension iff the Euclidean dimension is at most $(25-\mathbf c_{\mathrm M})/12$. We also show that the graph distance between typical points with respect to our discrete model grows polynomially whereas the cardinality of a graph distance ball of radius $r$ grows faster than any power of $r$ (which suggests that the Hausdorff dimension of LQG is infinite for $\mathbf c_{\mathrm M}\in(1,25)$). We include a substantial list of open problems.Comment: 53 pages, 6 figure

Efficient Computer Simulation of Polymer Conformation. I. Geometric Properties of the Hard-Sphere Model

A system of efficient computer programs has been developed for simulating the conformations of macromolecules. The conformation of an individual polymer is defined as a point in conformation space, whose mutually orthogonal axes represent the successive dihedral angles of the backbone chain. The statistical-mechanical average of any property is obtained as the usual configuration integral over this space. A Monte Carlo method for estimating averages is used because of the impossibility of direct numerical integration. Monte Carlo corresponds to the execution of a Markoffian random walk of a representative point through the conformation space. Unlike many previous Monte Carlo studies of polymers, which sample conformation space indiscriminately, importance sampling increases efficiency because selection of new polymers is biased to reflect their Boltzmann probabilities in the canonical ensemble, leading to reduction of sampling variance and hence to greater accuracy! in given computing time. The simulation is illustrated in detail. Overall running time is proportional to n^(5/4), where n is the chain length. Results are presented for a hard-sphere linear polymer of n atoms, with free dihedral rotation, with n = 20-298. The fraction of polymers accepted in the importance sampling scheme, fA, is fit to a Fisher-Sykes attrition relation, giving an effective attrition constant of zero. fA is itself an upper bound to the partition function, Q, relative to the unrestricted walk. The mean-squared end-to-end distance and radius of gyration exhibit the expected exponential dependence, but with exponent for the radius of gyration significantly greater than that of the end-to-end distance. The 90% confidence limits calculated for both exponents did not include either 6/5 or 4/3, the lattice and zero-order perturbation values, respectively. A self-correcting scheme for generating coordinates free of roundoff error is given in an Appendix

Computational methods in string and field theory

Thesis is submitted in fulfilment of the requirements for the degree of Doctor of Philosophy to the University of the Witwatersrand, Faculty of Science, School of Physics, University of the Witwatersrand, Johannesburg, 2018Like any field or topic of research, significant advancements can be made with increasing computational power - string theory is no exception. In this thesis, an analysis is performed within three areas: Calabi–Yau manifolds, cosmological inflation and application of conformal field theory. Critical superstring theory is a ten dimensional theory. Four of the dimensions refer to the spacetime dimensions we see in nature. To account for the remaining six, Calabi-Yau manifolds are used. Knowing how the space of Calabi-Yau manifolds is distributed gives valuable insight into the compactification process. Using computational modeling and statistical analysis, previously unseen patterns of the distribution of the Hodge numbers are found. In particular, patterns in frequencies exhibit striking new patterns - pseudo-Voigt and Planckian distributions with high confidence and exact fits for many substructures. The patterns indicate typicality within the landscape of Calabi–Yau manifolds of various dimensions. Inflation describes the exponential expansion of the universe after the Big Bang. Finding a successful theory of inflation centres around building a potential of the inflationary field, such that it satisfies the slow-roll conditions. The numerous ways this can be done, coupled with the fact that each model is highly sensitive to initial conditions, means an analytic approach is often not feasible. To bypass this, a statistical analysis of a landscape of thousands of random single and multifield polynomial potentials is performed. Investigation of the single field case illustrates a window in which the potentials satisfy the slow-roll conditions. When there are two scalar fields, it is found that the probability depends on the choice of distribution for the coefficients. A uniform distribution yields a 0.05% probability of finding a suitable minimum in the random potential whereas a maximum entropy distribution yields a 0.1% probability. The benefit of developing computational tools extends into the interdisciplinary study between conformal field theory and the theory of how wildfires propagate. Using the two dimensional Ising model as a basis of inspiration, computational methods of analyzing how fires propagate provide a new tool set which aids in the process of both modeling large scale wildfires as well as describing the emergent scale invariant structure of these fires. By computing the two point and three point correlations of fire occurrences in particular regions within Botswana and Kazakhstan, it is shown that this proposed model gives excellent fits, with the model amplitude being directly proportional to the total burn area of a particular year.EM201

Regularity Properties and Pathologies of Position-Space Renormalization-Group Transformations

We reconsider the conceptual foundations of the renormalization-group (RG) formalism, and prove some rigorous theorems on the regularity properties and possible pathologies of the RG map. Regarding regularity, we show that the RG map, defined on a suitable space of interactions (= formal Hamiltonians), is always single-valued and Lipschitz continuous on its domain of definition. This rules out a recently proposed scenario for the RG description of first-order phase transitions. On the pathological side, we make rigorous some arguments of Griffiths, Pearce and Israel, and prove in several cases that the renormalized measure is not a Gibbs measure for any reasonable interaction. This means that the RG map is ill-defined, and that the conventional RG description of first-order phase transitions is not universally valid. For decimation or Kadanoff transformations applied to the Ising model in dimension $d \ge 3$, these pathologies occur in a full neighborhood $\{ \beta > \beta_0 ,\, |h| < \epsilon(\beta) \}$ of the low-temperature part of the first-order phase-transition surface. For block-averaging transformations applied to the Ising model in dimension $d \ge 2$, the pathologies occur at low temperatures for arbitrary magnetic-field strength. Pathologies may also occur in the critical region for Ising models in dimension $d \ge 4$. We discuss in detail the distinction between Gibbsian and non-Gibbsian measures, and give a rather complete catalogue of the known examples. Finally, we discuss the heuristic and numerical evidence on RG pathologies in the light of our rigorous theorems.Comment: 273 pages including 14 figures, Postscript, See also ftp.scri.fsu.edu:hep-lat/papers/9210/9210032.ps.

Non-local meta-conformal invariance, diffusion-limited erosion and the XXZ chain

Diffusion-limited erosion is a distinct universality class of fluctuating interfaces. Although its dynamical exponent $z=1$, none of the known variants of conformal invariance can act as its dynamical symmetry. In $d=1$ spatial dimensions, its infinite-dimensional dynamic symmetry is constructed and shown to be isomorphic to the direct sum of three loop-Virasoro algebras, with the maximal finite-dimensional sub-algebra $\mathfrak{sl}(2,\mathbb{R})\oplus\mathfrak{sl}(2,\mathbb{R})\oplus\mathfrak{sl}(2,\mathbb{R})$. The infinitesimal generators are spatially non-local and use the Riesz-Feller fractional derivative. Co-variant two-time response functions are derived and reproduce the exact solution of diffusion-limited erosion. The relationship with the terrace-step-kind model of vicinal surfaces and the integrable XXZ chain are discussed.Comment: Latex 2e, 28 pp, 4 figures (revised, with 2 new figures