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A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,786 papers · 148 categories

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48 results for two-dimensional renormalization group

Two-dimensional RG acts like Ricci flow to model expanding universe.

problem Modeling the universe's expansion and acceleration phases.
method Two-dimensional renormalization group acting as Ricci flow to derive cosmological metrics.
result The universe expands, decelerates, then accelerates, ending in a big blowup.

The quantum field theory of two-dimensional sigma models with bulk and boundary couplings provides a natural framework to realize and unite different species of geometric flows that are of current interest in mathematics. In particular, the bulk renormalization group equation gives rise to the Ricci flow of target spac…

2007-02-05abs ↗pdf ↗

Study quantifies information flow in neural networks using relative entropy and RG analogy.

problem Quantifying information flow in deep neural networks.
method Explicit computation of relative entropy in Ising models and feedforward neural networks.
result Monotonic increase of relative entropy to an asymptotic value, confirming connection to c-theorem.

We study the evolution of a metric of a two dimensional black hole under the second loop renormalization group fow, the RG-2 fow. Since the black hole metric is noncompact (we consider it asymptotically flat) we adapt some proofs for the compact case to the asymptotically flat case. We found that the appearance of hori…

2019-04-30abs ↗pdf ↗

We interpret the physical BB-field renormalization group flow in the language of Courant algebroids, clarifying the sense in which this flow is the natural "Ricci flow" for generalized geometry. Next we show that the BB-field renormalization group flow preserves T-duality in a natural sense. As corollaries we obtain …

2013-10-18abs ↗pdf ↗

We discuss from a geometric point of view the connection between the renormalization group flow for non--linear sigma models and the Ricci flow. This offers new perspectives in providing a geometrical landscape for 2D quantum field theories. In particular we argue that the structure of Ricci flow singularities suggests…

2010-01-20abs ↗pdf ↗

Researchers calculate spectral dimension of complex networks using renormalization group theory.

problem Understanding diffusion properties in complex systems.
method Renormalization group theory applied to graph Laplacians of simplicial complexes.
result Spectral dimension decreases with randomness in topological structure.

In this article we show that for any given Riemann surface ΣΣ of genus gg, we can bound (from above) the renormalized volume of a (hyperbolic) Schottky group with boundary at infinity conformal to ΣΣ in terms of the genus and the combined extremal lengths on ΣΣ of (g1)(g-1) disjoint, non-homotopic, simple closed comp…

2019-05-08abs ↗pdf ↗

Study examines the geometry of a group of Fourier-integral operators related to Diff(S^1).

problem Investigating the geometry of a specific group of Fourier-integral operators.
method Defined a right-invariant pseudo-Riemannian metric on the group using renormalized traces of pseudo-differential operators.
result Extended the Hilbert-Schmidt Riemannian metric to the group.

This paper improves the neural network-QFT correspondence by nonperturbative renormalization.

problem Understanding neural networks through effective field theory and renormalization.
method Improves Wilsonian renormalization using nonperturbative renormalization group analysis.
result Changing standard deviation in neural networks can be interpreted as a renormalization flow.

A new sampler tackles critical phenomena by leveraging scale invariance.

problem Scale invariance at criticality causes sampling difficulties in Monte Carlo simulations.
method RiGCS combines MLMC-HB with generative models to improve sampling efficiency.
result RiGCS achieves significantly higher effective sample size than existing methods.

New method renormalizes neural network Gaussian processes to identify learnable vs. unlearnable modes.

problem Separating learnable from unlearnable information in neural networks.
method Wilsonian renormalization applied to Gaussian Process Regression.
result Obtains a universal flow of the ridge parameter that becomes input-dependent.

Conformal invariance plays a significant role in many areas of Physics, such as conformal field theory, renormalization theory, turbulence, general relativity. Naturally, it also plays an important role in geometry: theory of Riemannian surfaces, Weyl tensors, QQ-curvature, Yang-Mills fields, etc... We shall be concer…

2012-06-11abs ↗pdf ↗

The group of conformal diffeomorphisms and the group of causal automorphisms on two-dimensional globally hyperbolic spacetimes are clarified. It is shown that if spacetimes have non-compact Cauchy surfaces, then the groups are subgroups of that of two-dimensional Minkowski spacetime, and if spacetimes have compact Cauc…

2015-01-28abs ↗pdf ↗

We present a variational renormalization group (RG) approach using a deep generative model based on normalizing flows. The model performs hierarchical change-of-variables transformations from the physical space to a latent space with reduced mutual information. Conversely, the neural net directly maps independent Gauss…

2018-02-08abs ↗pdf ↗

Defines a new geometric quantity for hyperbolic manifolds, showing it's well-defined and invariant.

problem Defining a mass for asymptotically hyperbolic manifolds under weaker conditions.
method Volume-renormalized mass defined as a linear combination of ADM mass and renormalized volume.
result Volume-renormalized mass is well-defined and diffeomorphism invariant under weaker conditions.

The geometric evolution equations provide new ways to address a variety of non-linear problems in Riemannian geometry, and, at the same time, they enjoy numerous physical applications, most notably within the renormalization group analysis of non-linear sigma models and in general relativity. They are divided into clas…

2005-11-04abs ↗pdf ↗

In prior work the authors introduced a parabolic flow for pluriclosed metrics, referred to as pluriclosed flow. We also demonstrated that this flow, after certain gauge transformations, gives a class of solutions to the renormalization group flow of the nonlinear sigma model with B-field. Using these transformations, w…

2011-09-02abs ↗pdf ↗

A new RG approach connects discrete and continuous time descriptions of Gaussian processes.

problem Discretization of continuous stochastic processes for accurate simulation or model inference.
method Renormalization Group (RG) approach for Gaussian time series generated by auto-regressive models.
result RG fixed points correspond to discretizations of linear SDEs, providing insights into process accuracy.

Review of sigma models on flag manifolds, linking to spin chains and integrable theories.

problem Understanding phase transitions and anomalies in spin chains and sigma models.
method Analyzing topological angles, discrete 't Hooft anomalies, and integrable models.
result Gapless phases in certain spin chains can be explained by discrete anomalies in continuum theories.

In this paper we study the topology of conformally compact Einstein 4-manifolds. When the conformal infinity has positive Yamabe invariant and the renormalized volume is also positive we show that the conformally compact Einstein 4-manifold will have at most finite fundamental group. Under the further assumption that t…

2003-05-06abs ↗pdf ↗

After analyzing renormalization schemes on a Poincaré-Einstein manifold, we study the renormalized integrals of scalar Riemannian invariants. The behavior of the renormalized volume is well-known, and we show any scalar Riemannian invariant renormalizes similarly. We consider characteristic forms and their behavior und…

2005-04-08abs ↗pdf ↗

Simplified Ricci curvature for spherical fluid dynamics models.

problem Studying stability in incompressible fluid dynamics on a sphere.
method Definition and calculation of Ricci curvature for two-dimensional hydrodynamics using finite-dimensional Zeitlin models.
result Strong numerical evidence suggests convergence of finite-dimensional approximations to infinite-dimensional limit, indicating average instability for high-frequency modes.

Finite-width neural networks use non-Gaussian priors, extending Gaussian process theory.

problem Understanding the behavior of neural networks with finite width.
method Perturbative extension of Gaussian process theory to finite-width neural networks, tracking preactivation distributions.
result Non-Gaussian processes as priors in finite-width neural networks.

Study uses renormalized area to determine metric expansion from minimal surfaces.

problem Recovering the expansion of asymptotically hyperbolic metrics from minimal surfaces.
method Uses renormalized area functional on minimal submanifolds to recover metric expansion.
result Proves rigidity for log-analytic metrics and determines obstruction tensor.

The paper studies Riemannian metrics on Lie groups with specific commutator subgroups.

problem Investigating Riemannian metrics on Lie groups with commutator subgroups of dimensions 1 and 2.
method Explicitly provided Levi-Civita connection, sectional curvature, and Ricci curvature; computed necessary and sufficient conditions for Ricci solitons; characterized Ricci solitons on Lie groups with one-dimensional commutator subgroups; examined indecomposable Lie groups with two-dimensional commutator subgroups.
result Characterization of all Ricci solitons on Lie groups with one-dimensional commutator subgroups and examination of indecomposable Lie groups with two-dimensional commutator subgroups.

Defines renormalized volume for bounded regions in asymptotically hyperbolic Einstein spaces.

problem Calculating the volume of bounded regions in complex geometries.
method Defines renormalized volume, proves Gauss-Bonnet theorem, computes derivative under variations.
result Derives a Gauss-Bonnet theorem for the renormalized volume.

We revisit the subject of perturbatively quantizing the nonlinear sigma model in two dimensions from a rigorous, mathematical point of view. Our main contribution is to make precise the cohomological problem of eliminating potential anomalies that may arise when trying to preserve symmetries under quantization. The sym…

2014-08-19abs ↗pdf ↗

Study calculates the renormalized area of catenoids in hyperbolic spaces.

problem Calculating the renormalized area of catenoids in hyperbolic spaces.
method Variational characterization and Chern--Gauss--Bonnet formulas for locally conformally flat manifolds.
result Renormalized area of catenoids varies continuously from negative infinity to twice the area of totally geodesic hypersurfaces.

Defines and proves properties of weighted renormalized volume coefficients.

problem None explicitly stated; focuses on mathematical definitions and proofs.
method Defines weighted renormalized volume coefficients and proves their variational nature and polynomial representation.
result Weighted renormalized volume coefficients are variational and can be expressed as polynomials of specific tensors.

We study the critical points of the renormalized volume for acylindrical geometrically finite hyperbolic 3-manifolds that include rank-1 cusps, and show that the renormalized volume is locally convex around these critical points. We give a modified definition of the renormalized volume that is additive under gluing, an…

2015-05-03abs ↗pdf ↗

For a strictly pseudoconvex domain in a complex manifold we define a renormalized volume with respect to the approximately Einstein complete Kähler metric of Fefferman. We compute the conformal anomaly in complex dimension two and apply the result to derive a renormalized Chern--Gauss--Bonnet formula. Relations between…

2004-04-26abs ↗pdf ↗