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Adriaan M. J. Schakel

Publications and source records attributed to Adriaan M. J. Schakel.

At least 19 recordsLinked to original sources

Controlled Experiments for Word Embeddings

An experimental approach to studying the properties of word embeddings is proposed. Controlled experiments, achieved through modifications of the training corpus, permit the demonstration of direct relations between word properties and word vector direction and length. The approach is demonstrated using the word2vec CBOW model with experiments that independently vary word frequency and word co-occurrence noise. The experiments reveal that word vector length depends more or less linearly on both word frequency and the level of noise in the co-occurrence distribution of the word. The coefficients of linearity depend upon the word. The special point in feature space, defined by the (artificial) word with pure noise in its co-occurrence distribution, is found to be small but non-zero.

cs.CL↗

Measuring Word Significance using Distributed Representations of Words

Distributed representations of words as real-valued vectors in a relatively low-dimensional space aim at extracting syntactic and semantic features from large text corpora. A recently introduced neural network, named word2vec (Mikolov et al., 2013a; Mikolov et al., 2013b), was shown to encode semantic information in the direction of the word vectors. In this brief report, it is proposed to use the length of the vectors, together with the term frequency, as measure of word significance in a corpus. Experimental evidence using a domain-specific corpus of abstracts is presented to support this proposal. A useful visualization technique for text corpora emerges, where words are mapped onto a two-dimensional plane and automatically ranked by significance.

cs.CL↗

Critical Line of the O($N$) Loop Model on the Square Lattice

An efficient algorithm is presented to simulate the O(N) loop model on the square lattice for arbitrary values of $N>0$. The scheme combines the worm algorithm with a new data structure to resolve both the problem of loop crossings and the necessity of counting the number of loops at each Monte Carlo update. With the use of this scheme, the line of critical points (and other properties) of the O($N$) model on the square lattice for $0<N\le 2$ have been determined.

cond-mat.stat-mech↗

Derivation of the effective action of a dilute Fermi gas in the unitary limit of the BCS-BEC crossover

The effective action describing the gapless Nambu-Goldstone, or Anderson-Bogoliubov, mode of a zero-temperature dilute Fermi gas at unitarity is derived up to next-to-leading order in derivatives from the microscopic theory. Apart from a next-to-leading order term that is suppressed in the BCS limit, the effective action obtained in the strong-coupling unitary limit is proportional to that in the weak-coupling BCS limit.

cond-mat.quant-gas↗

Tan Relations in Dilute Bose Gasses

The exact relations for strongly interacting Fermi gasses, recently derived by Tan, are shown to first order in the loop expansion to also apply to dilute Bose gasses. A simple thermodynamic argument is put forward to support their validity. As an application, the second-order correction to the depletion of the condensate is determined to logarithmic accuracy.

cond-mat.quant-gas↗

Holographic interpretation of two-dimensional O(N) models coupled to quantum gravity

Various two-dimensional O(N) models coupled to Euclidean quantum gravity, whose intrinsic dimension is four, are shown to belong to universality classes of nongravitating statistical models in a lower number of dimensions. It is speculated that the matching critical behaviors in the gravitating and dimensionally reduced models may be manifestations of the holographic principle.

cond-mat.stat-mech↗

Critical Loop Gases and the Worm Algorithm

The loop gas approach to lattice field theory provides an alternative, geometrical description in terms of fluctuating loops. Statistical ensembles of random loops can be efficiently generated by Monte Carlo simulations using the worm update algorithm. In this paper, concepts from percolation theory and the theory of self-avoiding random walks are used to describe estimators of physical observables that utilize the nature of the worm algorithm. The fractal structure of the random loops as well as their scaling properties are studied. To support this approach, the O(1) loop model, or high-temperature series expansion of the Ising model, is simulated on a honeycomb lattice, with its known exact results providing valuable benchmarks.

cond-mat.stat-mech↗

Percolation of Vortices in the 3D Abelian Lattice Higgs Model

The compact Abelian Higgs model is simulated on a cubic lattice where it possesses vortex lines and pointlike magnetic monopoles as topological defects. The focus of this high-precision Monte Carlo study is on the vortex network, which is investigated by means of percolation observables. In the region of the phase diagram where the Higgs and confinement phases are separated by a first-order transition, it is shown that the vortices percolate right at the phase boundary, and that the first-order nature of the transition is reflected by the network. In the crossover region, where the phase boundary ceases to be first order, the vortices are shown to still percolate. In contrast to other observables, the percolation observables show finite-size scaling. The exponents characterizing the critical behavior of the vortices in this region are shown to fall in the random percolation universality class.

hep-lat↗

Geometric Properties of the Three-Dimensional Ising and XY Models

The fractal structure of high-temperature graphs of the three-dimensional Ising and XY models is investigated by simulating these graphs directly on a cubic lattice and analyzing them with the help of percolation observables. The Ising graphs are shown to percolate right at the Curie critical point. The diverging length scale relevant to the graphs in the vicinity of the percolation threshold is shown to be provided by the spin correlation length. The fractal dimension of the high-temperature graphs at criticality is estimated to be $D = 1.7349(65)$ for the Ising and $D = 1.7626(66)$ for the XY model.

cond-mat.stat-mech↗

Spacetime Approach to Phase Transitions

In these notes, the application of Feynman's sum-over-paths approach to thermal phase transitions is discussed. The paradigm of such a spacetime approach to critical phenomena is provided by the high-temperature expansion of spin models. This expansion, known as the hopping expansion in the context of lattice field theory, yields a geometric description of the phase transition in these models, with the thermal critical exponents being determined by the fractal structure of the high-temperature graphs. The graphs percolate at the thermal critical point and can be studied using purely geometrical observables known from percolation theory. Besides the phase transition in spin models and in the closely related $ϕ^4$ theory, other transitions discussed from this perspective include Bose-Einstein condensation, and the transitions in the Higgs model and the pure U(1) gauge theory.

cond-mat.stat-mech↗

Two-Dimensional Critical Potts and its Tricritical Shadow

These notes give examples of how suitably defined geometrical objects encode in their fractal structure thermal critical behavior. The emphasis is on the two-dimensional Potts model for which two types of spin clusters can be defined. Whereas the Fortuin-Kasteleyn clusters describe the standard critical behavior, the geometrical clusters describe the tricritical behavior that arises when including vacant sites in the pure Potts model. Other phase transitions that allow for a geometrical description discussed in these notes include the superfluid phase transition and Bose-Einstein condensation.

cond-mat.stat-mech↗

Fractal Structure of High-Temperature Graphs of O($N$) Models in Two Dimensions

The fractal structure and critical properties of the high-temperature graphs of the two-dimensional O($N)$ model close to criticality are investigated. Based on Monte Carlo simulations, De Gennes' results for polymer chains, corresponding to the limit $N \to 0$, are generalized to random loops for arbitrary $-2 \leq N \leq 2$. The loops are also studied close to their tricritical point, known as the $Θ$ point in the context of polymers, where they collapse. The corresponding fractal dimensions are argued to be in one-to-one correspondence with those at the critical point, leading to an analytic prediction for the magnetic scaling dimension at the O($N)$ tricritical point.

cond-mat.stat-mech↗

Anomalous Scaling and Fractal Dimensions

The relation between critical exponents, characterizing a continuous phase transition, and the fractal structure of physical lines, proliferating at the critical point, is established by considering the two-dimensional O($N$) spin model for which many exact results are available.

cond-mat.stat-mech↗

Geometrical Phase Transitions

The geometrical approach to phase transitions is illustrated by simulating the high-temperature representation of the Ising model on a square lattice.

cond-mat.stat-mech↗

Kertesz Line in the Three-Dimensional Compact U(1) Lattice Higgs Model

The three-dimensional lattice Higgs model with compact U(1) gauge symmetry and unit charge is investigated by means of Monte Carlo simulations. The full model with fluctuating Higgs amplitude is simulated, and both energy as well as topological observables are measured. The data show a Higgs and a confined phase separated by a well-defined phase boundary, which is argued to be caused by proliferating vortices. For fixed gauge coupling, the phase boundary consists of a line of first-order phase transitions at small Higgs self-coupling, ending at a critical point. The phase boundary then continues as a Kertesz line across which thermodynamic quantities are nonsingular. Symmetry arguments are given to support these findings.

cond-mat.str-el↗

Fractal Structure of Spin Clusters and Domain Walls in 2D Ising Model

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 on relatively small lattices through standard finite-size scaling. The obtained results are in excellent agreement with theoretical predictions and partly provide significant improvements in precision over existing numerical estimates.

cond-mat.stat-mech↗

Geometrical vs. Fortuin-Kasteleyn Clusters in the Two-Dimensional $q$-State Potts Model

The tricritical behavior of the two-dimensional $q$-state Potts model with vacancies for $1\leq q \leq4$ is argued to be encoded in the fractal structure of the geometrical spin clusters of the pure model. The close connection between the critical properties of the pure model and the tricritical properties of the diluted model is shown to be reflected in an intimate relation between Fortuin-Kasteleyn and geometrical clusters: The same transformation mapping the two critical regimes onto each other also maps the two cluster types onto each other. The map conserves the central charge, so that both cluster types are in the same universality class. The geometrical picture is supported by a Monte Carlo simulation of the high-temperature representation of the Ising model ($q=2$). In this new numerical approach, closed graph configurations are generated by means of a Metropolis update algorithm, involving single plaquettes.

cond-mat.stat-mech↗