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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.

169,051 papers · 148 categories

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48 results for Critical cases

Estimates for special Lagrangian curvature equations in critical and convex cases.

problem Interior estimates for special Lagrangian curvature equations.
method Establishes a priori interior curvature and gradient estimates.
result Proves interior curvature and gradient estimates for special Lagrangian curvature equations.

This paper identifies critical cases for evaluating PV investment impacts on MV networks efficiently.

problem Challenges in maintaining and controlling voltages in MV distribution networks due to increasing PV generation.
method Clustering MV nodes based on electrical adjacency and time blocks, identifying critical cases for further study.
result A scalable method to time efficiently identify critical cases for PV investment evaluation.

The paper proves new rigidity results for critical metrics of quadratic curvature functionals.

problem Proving rigidity of critical metrics for specific quadratic curvature functionals.
method Rigidity results for conformal vector fields, ODE argument, and new pointwise and integral estimates.
result Critical metrics are rigid under specific conditions.

Actor-critic converges globally in LQR with ergodic cost.

problem Theoretical understanding of actor-critic algorithm's global convergence.
method Nonasymptotic convergence analysis of actor-critic in linear quadratic regulator (LQR) setting.
result Actor-critic finds globally optimal policy and value function at a linear rate.

The paper proves conditions under which critical point metrics are Einstein.

problem Proving that critical point metrics are Einstein under specific curvature constraints.
method Analyzing the traceless Ricci operator and scalar curvature constraints.
result The conjecture that critical point metrics are Einstein is proven under certain curvature conditions.

Critical surfaces are defined by Bachman as topological index 2 surfaces, generalizing incompressible surfaces and strongly irreducible surfaces. In this paper we give a condition to obtain critical Heegaard surfaces by amalgamation. As a special case, we obtain critical Heegaard surfaces by boundary stabilization. It …

2011-09-18abs ↗pdf ↗

Geodesic distance vanishes for critical Sobolev norms on diffeomorphism groups.

problem Analyzing geodesic distance in diffeomorphism groups for critical Sobolev norms.
method Combining techniques from [JM19] and [BHP18]
result Geodesic distance vanishes for Ws,n/sW^{s,n/s} norms when s(0,1)s \in (0,1) and spnsp \le n.

When f : R power n to R power p, is a surjective real analytic map with isolated critical value, we prove that the (m)-regularity condition (in a sense we define) ensures that f ||f|| is a fibration on small spheres, f induces a fibration on the tubes and both fibrations are equivalent. In particular, we make the state…

2016-04-18abs ↗pdf ↗

Study on p-Laplacian problems with critical exponent, focusing on existence of solutions.

problem Existence of least energy solutions for nonlinear p-Laplacian problems with critical exponent.
method Proving existence of solutions through critical point theory and variational methods.
result Significant difference in existence results between p-Laplacian and Laplacian cases.

Let MM be a real hypersurface of a complex space form with constant curvature cc. In this paper, we study the hypersurface MM admitting Miao-Tam critical metric, i.e. the induced metric gg on MM satisfies the equation:(Δgλ)g+g2λλRic=g-(Δ_gλ)g+\nabla^2_gλ-λRic=g, where λλ is a smooth function on MM. At first, for the case wher…

2017-10-18abs ↗pdf ↗

Solves Dirichlet problem for Lagrangian phase equation with critical and supercritical phase.

problem Solving Dirichlet problem for Lagrangian phase equation with critical and supercritical phase.
method Uses interior C2C^2 estimate.
result Result is sharp, showing existence of singular solutions in subcritical phase.

Study on the Euler-Plateau energy with elastic modulus, focusing on minimizers and critical surfaces.

problem Minimizing the Euler-Plateau energy with elastic modulus.
method Analyzing the energy functional and its minimizers, considering different boundary conditions and topological constraints.
result Potential minimizers are highly dependent on physical rigidity parameters, and the area of critical surfaces can be computed from boundary data.

Proposes a deep reinforcement learning framework for dynamic multichannel access.

problem Efficient use of limited spectral resources in dynamic multichannel access.
method Deep actor-critic reinforcement learning framework for both single-user and multi-user scenarios.
result Demonstrates improved performance and adaptive ability compared to existing methods.

The paper calculates critical configurations and Morse indices for polygons on circles or ellipses.

problem Finding critical configurations and their properties for polygons on circles or ellipses.
method Computing Morse indices and gradient vector fields for isolated critical points, relating to eigenvalue questions.
result Computed Morse indices and relationships to eigenvalue questions for polygons on circles or ellipses.

Actor-critic methods solve reinforcement learning problems by updating a parameterized policy known as an actor in a direction that increases an estimate of the expected return known as a critic. However, existing actor-critic methods only use values or gradients of the critic to update the policy parameter. In this pa…

2017-05-22abs ↗pdf ↗

The paper studies a flow equation on even-dimensional manifolds, proving convergence under critical conditions.

problem Proving convergence of the prescribed QQ-curvature flow equation in critical cases.
method Analyzes the flow equation on arbitrary even-dimensional closed Riemannian manifolds, proving convergence under specific geometric hypotheses.
result Proves convergence of the flow equation when the integral of QQ equals (n1)!Vol(Sn)(n-1)!Vol(S^n), extending previous results.

We develop a topology data analysis-based method to detect early signs for critical transitions in financial data. From the time-series of multiple stock prices, we build time-dependent correlation networks, which exhibit topological structures. We compute the persistent homology associated to these structures in order…

2017-01-21abs ↗pdf ↗

We prove sharp pointwise decay estimates for critical Dirac equations on Rn\mathbb{R}^n with n2n\geq 2. They appear for instance in the study of critical Dirac equations on compact spin manifolds, describing blow-up profiles, and as effective equations in honeycomb structures. For the latter case, we find excited state…

2018-09-05abs ↗pdf ↗

The Hawking energy is nonnegative and rigid on area-constrained surfaces in general relativity.

problem The rigidity and positivity of the Hawking energy on specific surfaces in general relativity.
method Evaluation of the Hawking energy on area-constrained critical surfaces under the dominant energy condition.
result The Hawking energy is nonnegative and rigid on area-constrained surfaces, including charged and cosmological constant variants.

It is known that a closed polygon P is a critical point of the oriented area function if and only if P is a cyclic polygon, that is, PP can be inscribed in a circle. Moreover, there is a short formula for the Morse index. Going further in this direction, we extend these results to the case of open polygonal chains, or…

2012-01-26abs ↗pdf ↗

The Brasselet number helps calculate function germs with one-dimensional critical sets.

problem Calculating topological information of function germs with nonisolated singularities.
method Using the Brasselet number, the paper presents formulas for function germs with a one-dimensional critical locus.
result Formulas for function germs with a one-dimensional critical locus.

New foliations found for critical surfaces of Hawking energy, resolving discrepancies.

problem Finding consistent critical surfaces for the Hawking energy in non-totally geodesic spacelike hypersurfaces.
method Constructing a unique local foliation of area constrained critical surfaces of the Hawking energy in the general case of non-totally geodesic spacelike hypersurfaces.
result Discrepancy found in the small sphere limit of the Hawking energy, explained and resolved.

Stability of biharmonic maps in critical dimension proven.

problem Stability of biharmonic maps between manifolds in critical dimension.
method Generalization of Morse stability theory to biharmonic maps, development of strong energy quantization method.
result Strong energy quantization in a wide class of problems in geometric analysis.

We introduce ZZ-critical connections for holomorphic vector bundles and prove their existence under stability conditions.

problem Existence of ZZ-critical connections for holomorphic vector bundles.
method Associated geometric PDEs to Bridgeland stability conditions and used infinite dimensional moment maps.
result In the large volume limit, a sufficiently smooth holomorphic vector bundle admits a ZZ-critical connection if and only if it is asymptotically ZZ-stable.

Single-timescale actor-critic finds globally optimal policy.

problem Finding globally optimal policy in reinforcement learning.
method Simultaneous actor and critic updates with linear or deep neural network approximations.
result Actor sequence converges to globally optimal policy at O(K1/2)O(K^{-1/2}) rate.

The paper explores the critical point equation on Kenmotsu and almost Kenmotsu manifolds.

problem Investigating the critical point equation on specific types of manifolds.
method Analyzing Kenmotsu and almost Kenmotsu manifolds with nullity conditions.
result Complete Kenmotsu metrics satisfying the CPE are Einstein and locally isometric to H2n+1.

Machine learning predicts critical points for directed percolation models.

problem Determining critical points for directed percolation models.
method Supervised and unsupervised machine learning algorithms (CNN and DBSCAN) were used.
result Machine learning accurately predicts critical points for both models.