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The fractal structure of spin clusters and their boundaries in the critical two-dimensional (2D) Ising model is investigated numerically. The fractal dimensions of these geometrical objects are estimated by means of Monte Carlo simulations…

Statistical Mechanics · Physics 2009-11-10 Wolfhard Janke , Adriaan M. J. Schakel

A good generalization of the Euclidean dimension to disordered systems and non crystalline structures is commonly required to be related to large scale geometry and it is expected to be independent of local geometrical modifications. The…

Statistical Mechanics · Physics 2009-10-30 Raffaella Burioni , Davide Cassi

The area-perimeter scaling can be employed to evaluate the fractal dimension of urban boundaries. However, the formula in common use seems to be not correct. By means of mathematical method, a new formula of calculating the boundary…

Physics and Society · Physics 2018-12-20 Yanguang Chen

The diffraction spectrum of coherent waves scattered from fractal supports is calculated exactly. The fractals considered are of the class generated iteratively by successive dilations and translations, and include generalizations of the…

Condensed Matter · Physics 2009-10-28 Daniel A. Hamburger-Lidar

Metric data structures (distance oracles, distance labeling schemes, routing schemes) and low-distortion embeddings provide a powerful algorithmic methodology, which has been successfully applied for approximation algorithms \cite{llr},…

Data Structures and Algorithms · Computer Science 2015-04-08 Michael Elkin , Arnold Filtser , Ofer Neiman

We recently introduced a quantized fluctuational electrodynamics (QFED) formalism that provides a physically insightful definition of an effective position-dependent photon-number operator and the associated ladder operators. However, this…

Quantum Physics · Physics 2017-02-13 Mikko Partanen , Teppo Häyrynen , Jukka Tulkki , Jani Oksanen

In statistical mechanics, evaluating finite-size macroscopic fluctuations typically relies on Edgeworth expansions. However, these perturbative methods append additive polynomial corrections that inevitably break down in the large deviation…

Information Theory · Computer Science 2026-04-15 Hiroki Suyari

Probabilistic solvers for ordinary differential equations (ODEs) have emerged as an efficient framework for uncertainty quantification and inference on dynamical systems. In this work, we explain the mathematical assumptions and detailed…

Machine Learning · Statistics 2021-10-25 Nicholas Krämer , Nathanael Bosch , Jonathan Schmidt , Philipp Hennig

We consider the fractal characteristic of the quantum mechanical paths and we obtain for any universal class of fractons labeled by the Hausdorff dimension defined within the interval 1$ $$ < $$ $$h$$ $$ <$$ $$ 2$, a fractal distribution…

Statistical Mechanics · Physics 2009-11-07 Wellington da Cruz

We investigate how the integrability conditions for conformal anomalies constrain the form of the effective action in even-dimensional quantum geometry. We show that the effective action of four-dimensional quantum geometry (4DQG)…

High Energy Physics - Theory · Physics 2009-10-31 Ken-ji Hamada

Atomization stretches and folds the liquid-gas interface before fragmenting it into ligaments and droplets, making fractal measures a natural descriptor of the breakup state. We examine this idea in two-dimensional volume-of-fluid direct…

Fluid Dynamics · Physics 2026-04-30 Guangnian Ji , Yash Kulkarni , Stéphane Zaleski

We have recently shown that critical Anderson electron in $D=3$ dimensions effectively occupies a spatial region of infrared (IR) scaling dimension $d_\text{IR} \approx 8/3$. Here we inquire about the dimensional substructure involved. We…

Disordered Systems and Neural Networks · Physics 2024-01-11 Ivan Horváth , Peter Markoš

Entropy is useful in statistical problems as a measure of irreversibility, randomness, mixing, dispersion, and number of microstates. However, there remains ambiguity over the precise mathematical formulation of entropy, generalized beyond…

Statistical Mechanics · Physics 2023-08-21 Vladimir Zhdankin

We establish several optimal estimates for exceptional parameters in the projection of fractal measures: (1) For a parametric family of self-similar measures satisfying a transversality condition, the set of parameters leading to a…

Dynamical Systems · Mathematics 2025-10-09 Meng Wu

We establish pointwise and distributional fractal tube formulas for a large class of compact subsets of Euclidean spaces of arbitrary dimensions. These formulas are expressed as sums of residues of suitable meromorphic functions over the…

Mathematical Physics · Physics 2018-09-13 Michel L. Lapidus , Goran Radunović , Darko Žubrinić

We consider the possibility of obtaining emergent properties of physical spaces endowed with structures analogous to that of collective models put forward by classical statistical physics. We show that, assuming that a so-called "metric…

General Physics · Physics 2008-02-03 Pierre Peretto

We introduce a framework for constructing fractal trees via analytic generator fields, replacing discrete affine transformations and symbolic rewriting rules by the integration of smooth vector fields in an internal state space. In this…

Dynamical Systems · Mathematics 2026-02-04 Henk Mulder

In various theories of quantum gravity, one observes a change in the spectral dimension from the topological spatial dimension $d$ at large length scales to some smaller value at small, Planckian scales. While the origin of such a flow is…

High Energy Physics - Theory · Physics 2015-04-22 Gianluca Calcagni , Daniele Oriti , Johannes Thürigen

The fractal or Hausdorff dimension is a measure of roughness (or smoothness) for time series and spatial data. The graph of a smooth, differentiable surface indexed in $\mathbb{R}^d$ has topological and fractal dimension $d$. If the surface…

Methodology · Statistics 2015-03-17 Tilmann Gneiting , Hana Ševčíková , Donald B. Percival

Credal sets, i.e., closed convex sets of probability measures, provide a natural framework to represent aleatoric and epistemic uncertainty in machine learning. Yet how to quantify these two types of uncertainty for a given credal set,…