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arXiv research

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.

168,742 papers · 148 categories

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53106159212 · Jun 202019922001200920172026
48 results for lattice size

Classifies knots by lattice size, finding unknot ratios and crossing numbers.

problem Understanding the distribution of knots within different lattice sizes.
method Introduced a new knot classification by lattice size, analyzed ratios of unknots and knots with more than 10 crossings, and compared with theoretical estimates.
result Ratio of unknots decreases exponentially with lattice size, and computational results match theoretical estimates.

We prove that the rank (that is, the minimal size of a generating set) of lattices in a general connected Lie group is bounded by the co-volume of the projection of the lattice to the semi-simple part of the group. This was proved by Gelander for semi-simple Lie groups and by Mostow for solvable Lie groups. Here we con…

2019-03-12abs ↗pdf ↗

The paper proposes a method to sample quantum field configurations using neural operators and flows.

problem Sampling lattice field configurations from Boltzmann distributions in quantum field theories.
method Approximating a time-dependent neural operator to map between free and target theories, discretizing to a normalizing flow, and training to diffeomorphism.
result The method can generalize to larger lattice sizes when pre-trained on smaller ones, improving efficiency.

SGLRW improves robustness of stochastic gradient MCMC methods.

problem Sensitivity to minibatch size and gradient noise in stochastic-gradient MCMC methods.
method Proposes Stochastic Gradient Lattice Random Walk (SGLRW) with lattice-based discretization.
result SGLRW remains stable in regimes where SGLD fails, including heavy-tailed gradient noise.

Equivariant neural networks improve performance and generalization in lattice field theory tasks.

problem Improving neural network performance and generalization in lattice field theory.
method Investigation of translationally equivariant neural networks in a two-dimensional scalar field model.
result Equivariant neural networks significantly outperform non-equivariant ones in various tasks, including physical parameters and lattice sizes.

New method uses neural maps to efficiently sample lattice QCD distributions.

problem Challenges in sampling Boltzmann distributions of lattice field theories.
method Sparse triangular transport maps exploiting conditional independence structure of lattice graphs.
result Sparse triangular maps achieve efficient sampling with linear time complexity in lattice size.

Improved neural network approximations for statistical systems.

problem Inefficient scaling of neural network approximations in statistical systems.
method Hierarchical autoregressive neural networks with reduced scaling.
result Significant improvement in neural network training quality and free energy approximation.

Study on entanglement complexity of confined ring polymers in lattice tubes.

problem Understanding the entanglement complexity of confined ring polymers in lattice tubes.
method Applied knot theory to extend and prove results about the complexity of 2SAPs.
result Proved that all but exponentially few size m 2SAPs have F complexity that grows at least linearly in m as m approaches infinity.

Data compression speeds up machine learning loss calculations.

problem Computational demand in calculating mean squared error for large datasets.
method Use rank-1 lattices to compress data, assigning weights based on original data and responses.
result Our QMC data compression algorithms can lead to arbitrary high convergence rates for smooth functions.

Study on knotting in very long polymer chains, finding Poisson distribution for prime knot types.

problem Understanding knotting in very long polymer chains.
method Generated and analyzed 243k2^{43-k} polygons of size n=2kn=2^k using tree data structure and pivot algorithm. Used new knot diagram simplification and invariant-free classification.
result Number of prime summands of knot type KK in a random nn-gon is well described by a Poisson distribution.

Translationally equivariant neural networks improve performance and generalization in physics problems.

problem Performance and generalization issues in machine learning applied to physics problems.
method Investigation of translationally equivariant convolutional neural networks for complex scalar field theory on a 2D lattice.
result Translationally equivariant neural networks significantly outperform non-equivariant architectures in various regression and classification tasks.

Research finds bounds for knots in hexagonal lattice and classifies 11-stick knots.

problem Determining the stick number and edge length of knots in a hexagonal lattice.
method Introducing a linear transformation between lattices to prove strict inequalities and classifying knots.
result Only trefoil and figure-eight knots are 11-stick knots in the hexagonal lattice.

We outline the theory of sets with distributive operations: multishelves and multispindles, with examples provided by semi-lattices, lattices and skew lattices. For every such a structure we define multi-term distributive homology and show some of its properties. The main result is a complete formula for the homology o…

2011-11-21abs ↗pdf ↗

We give a simple example showing that a knot or link diagram that lies in the Z2{\mathbb{Z}}^2 lattice is not necessarily the projection of a lattice stick knot or link in the Z3{\mathbb{Z}}^3 lattice, and we give a necessary and sufficient condition for when a knot or link diagram that lies in the Z2{\mathbb{Z}}^2 lat…

2018-03-09abs ↗pdf ↗

Median-of-means sampling outperforms mean-of-means for large sample sizes in numerical integration.

problem Improving numerical integration accuracy in high dimensions.
method Median-of-means sampling compared to mean-of-means using RQMC methods.
result Median-of-means sampling is superior for large sample sizes, while mean-of-means is better for smaller sample sizes.

We explore hybrid subgroups of certain non-arithmetic lattices in PU(2,1)\mathrm{PU}(2,1). We show that all of Mostow's lattices are virtually hybrids; moreover, we show that some of these non-arithmetic lattices are hybrids of two non-commensurable arithmetic lattices in PU(1,1)\mathrm{PU}(1,1).

2019-05-29abs ↗pdf ↗

This paper studies the covolumes of nonuniform arithmetic lattices in PU(n, 1). We determine the smallest covolume nonuniform arithmetic lattices for each n, the number of minimal covolume lattices for each n, and study the growth of the minimal covolume as n varies. In particular, there is a unique lattice (up to conj…

2011-07-26abs ↗pdf ↗

The paper finds incommensurable lattices in complex models of Baumslag-Solitar groups.

problem Locally finite 2-complexes and their automorphism groups contain incommensurable lattices.
method Constructing lattices in combinatorial models of Baumslag-Solitar groups and analyzing their properties.
result The constructed lattices are incommensurable and have specific properties like isomorphic Cayley graphs.

Proves a lattice version of the Atiyah-Singer index theorem.

problem Index problems of Wilson-Dirac operators on lattice approximations of manifolds.
method Formulates and proves a KK-theoretic formula for an index-type invariant.
result Main theorem gives a formula for an index-type invariant of operators on lattice approximations of closed integral affine manifolds.

In this paper we use techniques from convex projective geometry to produce many new examples of thin subgroups of lattices in special linear groups that are isomorphic to the fundamental groups of finite volume hyperbolic manifolds. More specifically, we show that for a large class of arithmetic lattices in SO(n,1) it …

2018-09-07abs ↗pdf ↗

We show that the set of even positive definite lattices that arise from smooth, simply-connected 4-manifolds bounded by a fixed homology 3-sphere can depend on more than the ranks of the lattices. We provide two homology 3-spheres with distinct sets of such lattices, each containing a distinct nonempty subset of the ra…

2018-08-30abs ↗pdf ↗

The paper proves residual finiteness of certain lattices and constructs surfaces with specific fundamental groups.

problem Residual finiteness of lattices in PU(2,1)~\widetilde{\mathrm{PU}(2,1)} and existence of smooth projective surfaces.
method Proved residual finiteness of certain lattices and constructed surfaces using central extensions.
result First examples of residually finite lattices in PU(2,1)~\widetilde{\mathrm{PU}(2,1)} and construction of surfaces with specific fundamental groups.

Polynomial-time reachability for LTI systems with TLL NN controllers is achieved.

problem Bounding the reachable set of LTI systems controlled by TLL NN controllers.
method Polynomial-time computation of exact one-step reachable set and tight bounding box via two methods.
result Exact reachability computation in polynomial time for TLL NN controllers.

The cubic lattice stick index of a knot type is the least number of sticks necessary to construct the knot type in the 3-dimensional cubic lattice. We present the cubic lattice stick index of various knots and links, including all (p,p+1)-torus knots, and show how composing and taking satellites can be used to obtain t…

2012-05-23abs ↗pdf ↗

The paper refines transformations of lattice diagrams and introduces dotted diagrams.

problem Investigating transformations and deformations of lattice diagrams and their associated dotted diagrams.
method Introducing dotted diagrams and investigating deformations of these diagrams, relating them to transformations of lattice diagrams.
result Refined results on the relation between deformations of admissible dotted diagrams and transformations of lattice diagrams.

Let GG be a simply connected, solvable Lie group and ΓΓ a lattice in GG. The deformation space D(Γ,G)\mathcal{D}(Γ,G) is the orbit space associated to the action of $\Aut(G)$ on the space X(Γ,G)\mathcal{X}(Γ,G) of all lattice embeddings of ΓΓ into GG. Our main result generalises the classical rigidity theorems of Mal'tsev…

2011-11-23abs ↗pdf ↗

Equivariant neural networks improve performance and generalization in complex scalar field theory tasks.

problem Improving performance and generalization in neural networks for complex scalar field theory tasks.
method Incorporating translational equivariance into neural network architectures.
result Equivariant neural networks significantly outperform non-equivariant networks in various tasks, including those beyond the training set and across different lattice sizes.

We study the arithmeticity of the Couwenberg-Heckman-Looijenga lattices in PU(n,1), and show that they contain a non-arithmetic lattice in PU(3,1) which is not commensurable to the non-arithmetic Deligne-Mostow lattice in PU(3,1).

2017-10-12abs ↗pdf ↗

Improved lattice field theory simulations with local-Autoregressive Conditional Normalizing Flow.

problem Efficiently sampling lattice field theories with computational challenges.
method Integrates locality into autoregressive conditional normalizing flows.
result Autocorrelation times improved by orders of magnitude for φ4φ^{4} theory on a 2D lattice.