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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.

168,694 papers · 148 categories

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96192287383 · May 202619922001200920172026
48 results for delocalization condition

The paper proves universality in optimization problems with i.i.d. random vectors.

problem Optimization problems with i.i.d. random vectors and their projections.
method Proves universality of empirical risk minimization under specific conditions.
result The minimum value of the optimization problem is universal and depends only on the mean and covariance of the random vectors.

We define extensions of the L2L^2-analytic invariants of closed manifolds, called delocalized L2L^2-invariants. These delocalized invariants are constructed in terms of a nontrivial conjugacy class of the fundamental group. We show that in many cases, they are topological in nature. We show that the marked length spect…

1996-12-02abs ↗pdf ↗

In this paper we state and prove Morse type inequalities for Morse functions as well as for closed differential 1-forms. These inequalities involve delocalized Betti numbers. As an immediate consequence, we prove the vanishing of delocalized Betti numbers of manifolds fibering over the circle.

2008-07-31abs ↗pdf ↗

Study delocalized eta invariants for signature operators on proper manifolds.

problem Define and analyze delocalized eta invariants for signature operators on proper manifolds.
method Develop detailed heat-kernel analysis and apply to proper manifolds with boundary.
result Prove index formulas relating delocalized eta invariants to Atiyah-Patodi-Singer indices.

The paper defines higher invariants for groups of polynomial growth and proves their convergence.

problem Defining and proving convergence of higher invariants for groups of polynomial growth.
method Using delocalized cyclic cocycles and a determinant map construction.
result A well-defined pairing between delocalized cyclic cocyles and K-theory classes of C*-algebraic secondary higher invariants.

The unadjusted Langevin algorithm converges faster for some variables in high dimensions.

problem Sampling probability distributions in high-dimensional settings.
method Analysis of the unadjusted Langevin algorithm for strongly log-concave distributions.
result The delocalization of bias effect allows for faster convergence for a small number of variables.

New method controls bias in unadjusted Hamiltonian Monte Carlo and underdamped Langevin.

problem Bias in unadjusted Hamiltonian Monte Carlo and underdamped Langevin samplers.
method Delocalization of bias technique applied to these samplers.
result Control W2W_2 bias with O(K)O(\sqrt{K}) integration steps for high-dimensional distributions.

A new model explains protein interactions via electron delocalization.

problem Understanding how protein interactions affect each other.
method Quantized discrete differential geometry of n-simplices.
result Allosteric regulation follows from the model of interactions.

Non-Abelian actions are resolved using equivariant K-theory and delocalized cohomology.

problem Resolving non-Abelian actions on manifolds.
method Using equivariant K-theory and delocalized cohomology, the structure of the quotient space is described.
result A new model for non-Abelian equivariant K-theory and cohomology is developed.

Improved sampling from complex distributions with reduced bias.

problem Reducing bias in high-dimensional sampling algorithms.
method Hierarchical entropy analysis to weaken assumptions and expand scope.
result Bias reduction in low-dimensional marginals scales with lower dimension, not full dimension.

For any closed complex manifold XX, we calculate the Poincaré and Hodge polynomials of the delocalized equivariant cohomology H(Xn,Sn)H^*(X^n, S_n) with a grading specified by physicists. As a consequence, we recover a special case of a formula for the elliptic genera of symmetric products in Dijkgraaf-Moore-Verlinde-Verlin…

1999-10-05abs ↗pdf ↗

Let G be a finitely generated discrete group. In this paper we establish vanishing results for rho-invariants associated to (i) the spin-Dirac operator of a spin manifold with positive scalar curvature (ii) the signature operator of the disjoint union of a pair of homotopy equivalent oriented manifolds with fundamental…

2004-07-22abs ↗pdf ↗

New method detects global factors near BBP phase transition in high-dimensional data.

problem Detecting the number of global factors in noisy high-dimensional correlation matrices.
method Iterative Global Factor (IGF) algorithm combining adaptive edge recalibration and PR delocalization filter.
result IGF algorithm successfully detects global factors near BBP transition, improving over eigenvalue-only methods.

A refined form of the `Folk Theorem' that a smooth action by a compact Lie group can be (canonically) resolved, by iterated blow up, to have unique isotropy type was established by the authors in the context of manifolds with corners; the canonical construction induces fibrations on the boundary faces of the resolution…

2010-12-28abs ↗pdf ↗

We give a description of the delocalized twisted cohomology of an orbifold and the Chern character of a twisted vector bundle in terms of supersymmetric Euclidean field theories. This includes the construction of a twist functor for 111|1-dimensional EFTs from the data of a gerbe with connection.

2018-01-09abs ↗pdf ↗

Uniform K-homology theory applied to elliptic operators on manifolds with boundary.

problem Developing a theory to study boundary conditions for elliptic operators on non-compact manifolds.
method Theory of relative uniform K-homology, developing a relative index map.
result Uniform K-homology classes of boundary conditions and their connection to the higher ρ-invariant.

A multi-scale model predicts atomic-scale properties using both local and long-range information.

problem Inability of machine-learning schemes to capture long-range physical effects.
method Combines local and non-local information in a multipole expansion framework.
result Demonstrates the ability to model electrostatics, polarization, and dispersion.

Let G be a discrete group, and let M be a closed spin manifold of dimension m>3 with pi_1(M)=G. We assume that M admits a Riemannian metric of positive scalar curvature. We discuss how to use the L2-rho invariant and the delocalized eta invariant associated to the Dirac operator on M in order to get information about t…

2006-04-13abs ↗pdf ↗

Let ΓΓ be a discrete group. Assuming rational injectivity of the Baum-Connes assembly map, we provide new lower bounds on the rank of the positive scalar curvature bordism group and the relative group in Stolz' positive scalar curvature sequence for BΓ\mathrm{B} Γ. The lower bounds are formulated in terms of the part …

2017-09-21abs ↗pdf ↗

The smooth action of a compact Lie group on a compact manifold can be resolved to an iterated space, as made explicit by Pierre Albin and the second author. On the resolution the lifted action has fixed isotropy type, in an iterated sense, with connecting fibrations and this structure descends to a resolution of the qu…

2018-07-22abs ↗pdf ↗

We show that the emergence of systemic risk in complex systems can be understood from the evolution of functional networks representing interactions inferred from fluctuation correlations between macroscopic observables. Specifically, we analyze the long-term collective dynamics of the New York Stock Exchange between 1…

2018-07-09abs ↗pdf ↗

New method reduces memory usage for high-dimensional variable selection.

problem Scalability issues in high-dimensional variable selection, especially in genomics.
method Adaptive sampling of null features to eliminate dummy matrix materialization.
result Reduces memory and runtime by several orders of magnitude while preserving FDR control.

Let ΓΓ be a f.g. discrete group and let M~\tilde M be a Galois ΓΓ-covering of a smooth closed manifold MM. Let SΓ(M~)S_*^Γ(\tilde{M}) be the analytic structure group, appearing in the Higson-Roe analytic surgery sequence SΓ(M~)K(M)K(CrΓ)\to S_*^Γ(\tilde M)\to K_*(M)\to K_*(C_r^*Γ)\to. We prove that for an arbitrary discrete group ΓΓ

2019-05-28abs ↗pdf ↗

Geometric formula derived for Lefschetz pairing on Γ-proper manifolds.

problem Deriving a geometric formula for Lefschetz pairing on Γ-proper manifolds.
method Heat-kernel techniques applied to geometric pairing of index classes and delocalized cyclic cocycles.
result Proof of a geometric formula for the pairing of the index class with delocalized cyclic cocycles on fixed point manifold.

The `Folk Theorem' that a smooth action by a compact Lie group can be (canonically) resolved, by iterated blow up, to have unique isotropy type is proved in the context of manifolds with corners. This procedure is shown to capture the simultaneous resolution of all isotropy types in a `resolution tower' which projects …

2009-07-20abs ↗pdf ↗

We analyze a class of conical G_2 metrics admitting two commuting isometries, together with a certain one-parameter family of G_2 deformations which preserves these symmetries. Upon using recent results of Calderbank and Pedersen, we write down the explicit G_2 metric for the most general member of this family and extr…

2002-05-08abs ↗pdf ↗

The paper analyzes high-dimensional linear regression using parametric empirical Bayes methods.

problem Estimation of i.i.d. priors in high-dimensional Bayesian linear regression with random design.
method Parametric empirical Bayes estimation, variational lower bound maximization, phase transition analysis.
result The vEB estimator is information theoretically optimal up to p=o(n2/3)p=o(n^{2/3}) but sub-optimal in higher dimensions.

In this paper we define K-theoretic secondary invariants attached to a Lie groupoid GG. The K-theory of Cr(Gad0)C^*_r(G_{ad}^0) (where Gad0G_{ad}^0 is the adiabatic deformation GG restricted to the interval [0,1)[0,1)) is the receptacle for K-theoretic secondary invariants. We give a Lie groupoid version of construction given b…

2016-09-26abs ↗pdf ↗

Stochastic gradient descent converges to universal limits in high dimensions.

problem Statistical tasks in high dimensions with specific data projections.
method Stochastic gradient descent applied to mixture distributions, proving universality of limits.
result The ODE limits are universal for mixtures of arbitrary product distributions.

In this paper, we study the space of metrics of positive scalar curvature using methods from coarse geometry. Given a closed spin manifold M with fundamental group G, Stephan Stolz introduced the positive scalar curvature exact sequence, in analogy to the surgery exact sequence in topology. It calculates a structure gr…

2012-10-25abs ↗pdf ↗

This thesis studies positive scalar curvature metrics on G-proper spaces and pseudomanifolds.

problem Understanding positive scalar curvature metrics on G-proper spaces and pseudomanifolds.
method Adapting Stolz' positive scalar curvature sequence to (G, F)-spaces and manifolds with non-isolated singularities, using localization algebras and K-theory.
result Established an isomorphism between R-groups for spaces with isomorphic fundamental functors and a universal space.

Defines and computes geometric pairings for discrete groups using Baum-Connes assembly map.

problem Defining and computing geometric pairings for discrete countable groups.
method Constructs explicit morphisms and the Chern-Baum-Connes assembly map.
result Explicit formulation of a Chern-Connes pairing with the periodic cyclic cohomology of the group algebra.

The paper develops a new approach to conditional risk measures using modular convex analysis.

problem Developing a new method for conditional risk measures.
method Random modular approach to conditional certainty equivalents and niveloids in the conditional LL^{\infty}-space.
result Retrieves a conditional variational formula for optimized certainty equivalents and applies it to the conditional entropic risk measure.

Paper constructs solutions to Bogomolny equations with specific boundary and asymptotic conditions.

problem Constructing solutions to Bogomolny equations with given boundary and asymptotic conditions.
method Using generalized Nahm pole boundary condition and real symmetry breaking condition.
result Solutions analogous to instanton solutions, satisfying different asymptotic conditions.

We extend probabilistic programming to handle conditioning on marginal distributions.

problem Conditioning probabilistic programs on marginal distributions of observable variables.
method We define and implement stochastic conditioning, allowing inference in probabilistic programs conditioned on marginal distributions.
result We demonstrate the effectiveness of stochastic conditioning in various real-life scenarios.

Paper finds necessary condition for logarithmic Minkowski problem in higher dimensions.

problem Logarithmic Minkowski problem in higher dimensions.
method Established a necessary condition through generalization and refinement of previous work.
result Generalizes and refines necessary condition for logarithmic Minkowski problem.

This paper introduces a neural operator for probabilistic conditioning.

problem Probabilistic conditioning of random variables XX given YY.
method Develops a single operator that maps any joint density to its conditional, approximated by neural operators.
result Neural operators can approximate the conditioning operator to arbitrary accuracy.

CSI method learns conditional distributions by estimating flow equations.

problem Learning conditional distributions in generative models.
method Estimates probability flow equations to transport reference to target distribution.
result Derives explicit expressions for conditional drift and score functions.

New conditional risk measures called conditional generalized quantiles defined and characterized.

problem Developing new risk measures for dynamic risk assessment.
method Propose and characterize conditional generalized quantiles using expected utility model and equivalent conditions.
result Characterized conditional generalized quantiles as well-defined and equivalent to a conditional first order condition.