Research
On-device research index

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

Trend · papers per month

25.0%50.0%75.0%100.0% · Jun 199319922001200920182026
48 results for second order flow

We introduce the discrete Einstein metrics as critical points of discrete energy on triangulated 3-manifolds, and study them by discrete curvature flow of second (fourth) order. We also study the convergence of the discrete curvature flow. Discrete curvature flow of second order is an analogue of smooth Ricci flow.

2013-12-03abs ↗pdf ↗

Study shows how macroeconomic news affects intraday price and order flow dynamics.

problem Understanding how macroeconomic news impacts intraday price and order flow dynamics.
method Structural VAR model identified through heteroskedasticity, estimated at one-second frequency for each 15-minute interval.
result Macroeconomic news announcements reshape price-flow dynamics, with significant impacts on price and flow impacts at the one-second horizon.

We prove a general result about the short time existence and uniqueness of second order geometric flows transverse to a Riemannian foliation on a compact manifold. Our result includes some flows already existing in literature, as the transverse Ricci flow, the Sasaki-Ricci flow and the Sasaki J-flow and motivates the s…

2015-05-13abs ↗pdf ↗

The study provides interior estimates for QkQ_k-flows and translators in Rn+1\mathbb{R}^{n+1}.

problem Estimating QkQ_k-flows and translators in Rn+1\mathbb{R}^{n+1}.
method Proved interior gradient and second order estimates.
result Non-existence of QkQ_k-translators asymptotic to o(x)o(|x|).

Study a flow for curve energy, proving existence for various p.

problem Evolution of closed curves under energy minimization.
method Second order flow decreasing p-elastic energy, proving existence via minimizing movements.
result Existence of solutions for p(1,)p \in (1, \infty), long-time existence for p=2p = 2.

We consider the local solution to the Calabi flow for C^αinitial metric. We also prove that the Calabi flow on compact Kaehler surfaces can be extended once the metrics along the flow are bounded in L^\infty sense. This can be viewed as obtaining higher order derivative estimates from second order derivatives for a fou…

2009-04-06abs ↗pdf ↗

We study the determination of the second-order normal form for perturbed Hamiltonians Hε=H0+εH1+ε22H2H_ε=H_0 +εH_1 +\frac{ε^2}{2} H_2, relative to the periodic flow of the unperturbed Hamiltonian H0H_0. The formalism presented here is global, and can be easily implemented in any CAS. We illustrate it by means of two examples: the H…

2013-01-15abs ↗pdf ↗

New method learns population dynamics from snapshots, outperforming existing models.

problem Capturing periodic and other dynamical properties of population dynamics.
method Wasserstein Lagrangian Mechanics (WLM) for learning second-order dynamics from observed marginals.
result WLM outperforms existing methods across various dynamics, including vortex dynamics, embryonic development, and flocking.

Improved stock price prediction model using generalized order flow imbalance.

problem Improving stock price prediction models using new order flow imbalance indicators.
method Proposed a generalized order flow imbalance construction method and applied it to CSI 500 stocks.
result Generalized Stationarized Order Flow Imbalance (log-GOFI) shows significant improvement in explaining stock price changes.

Regularities and stability shown for a specific type of complex parallelizable manifolds.

problem Stability and regularity of Chern-flat metrics on complex parallelizable manifolds.
method Study of Hermitian metrics governed by the second Chern-Ricci form on compact complex manifolds.
result Chern-flat metrics are dynamically stable on compact complex parallelizable manifolds.

The paper introduces a geometric flow for Lagrangian submanifolds that preserves Hamiltonian isotopy.

problem Finding stationary solutions for Hamiltonian stationary Lagrangian submanifolds.
method Introducing a geometric flow that is a gradient flow for volume and corresponds to a fourth order strictly parabolic scalar equation.
result Established short-time existence, uniqueness, and higher order estimates for compact initial Lagrangian immersions with uniformly bounded second fundamental forms.

Paper proves higher-order flow matching preserves optimality in generative modeling.

problem Theoretical guarantees for higher-order flow matching in generative modeling.
method Neural network approximations with controlled depth, width, and sparsity.
result Proves worst case optimality for second-order flow matching.

We consider classical curvature flows: 1-parameter families of convex embeddings of the 2-sphere into Euclidean 3-space which evolve by an arbitrary (non-homogeneous) function of the radii of curvature. The associated flow of the radii of curvature is a second order system of partial differential equations which we sho…

2015-03-06abs ↗pdf ↗

Paper transforms a complex equation into simpler forms for analysis.

problem Analyzing a fourth-order dispersive flow equation on Kähler manifolds.
method Developed the generalized Hasimoto transformation to simplify the equation.
result Explicit expressions derived for three examples of compact Kähler manifolds.

The paper proves gap results for self-shrinkers in rr-mean curvature flow.

problem Understanding the gap in properties of self-shrinkers in rr-mean curvature flow.
method Proving gap results using a modified second fundamental form and a differential operator.
result Proper self-shrinkers are parabolic for a certain second-order differential operator.

In this paper we derive a second order approximation for an infinite dimensional limit order book model, in which the dynamics of the incoming order flow is allowed to depend on the current market price as well as on a volume indicator (e.g.~the volume standing at the top of the book). We study the fluctuations of the …

2017-08-24abs ↗pdf ↗

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 ↗

In this paper we consider the Ricci flow on manifolds with boundary with appropriate control on its mean curvature and conformal class. We obtain higher order estimates for the curvature and second fundamental form near the boundary, similar to Shi's local derivative estimates. As an application, we prove a version of …

2013-11-13abs ↗pdf ↗

Let (M,g)(\mathcal{M},g) be a closed Riemannian manifold. The  second order approximation\textit{ second order approximation} to the perturbative renormalization group flow for the nonlinear sigma model (RG-2 flow) is given by : \[ \frac{\partial }{\partial t} \, g(t) \, =\, -2 \mathrm{Ric}(t) \, -\, \fracα{2} \mathrm{Rm}^2(t), \] where $ g = \ma…

2018-05-24abs ↗pdf ↗

We examine the fixed points to first-order RG flow of a non-linear sigma model with background metric, dilaton and tachyon fields. We show that on compact target spaces, the existence of fixed points with non-zero tachyon is linked to the sign of the second derivative of the tachyon potential V(T)V''(T) (this is the anal…

2006-05-23abs ↗pdf ↗

A novel framework extracts essential factors from order flow data for high-frequency trading.

problem Challenges in extracting and utilizing order flow data due to its large volume and limitations of traditional techniques.
method Proposes a Context Encoder and Factor Extractor for unsupervised learning of important signals from order flow data.
result Extracts superior factors from order flow data, improving stock trend prediction and order execution tasks.

JKO scheme adds deceleration in rapidly changing metric curvature directions.

problem Understanding the implicit bias of the JKO scheme in Wasserstein gradient flow.
method Characterized the implicit bias of the JKO scheme at second order in η, modifying the energy functional.
result JKO scheme adds deceleration in directions where metric curvature of J is rapidly changing.

Study geometric flows of G2-structures, determining curvature and torsion invariants.

problem Investigate geometric flows of G2-structures and their invariants.
method Explicitly compute differential invariants, decompose curvature and torsion, analyze principal symbols.
result Established short-time existence and uniqueness for geometric flows of G2-structures.

The paper classifies periodic solitons in curve flows on the light-cone.

problem Investigating periodic solitons in curve flows on the light-cone.
method Deriving Harnack inequality for heat flow, classifying space-periodic solitons for a third-order curvature flow.
result Closed soliton solutions form a family of transcendental curves with specific rotation indices.

A new RL method using SSD compares action uncertainties to manage aleatoric uncertainty.

problem Managing aleatoric uncertainty in RL environments.
method Distributional RL based on SSD, mapping to Wasserstein gradient flow.
result Optimal particle-based algorithm for SSD policy demonstrates better uncertainty balancing.

Advances geometric structure flows, proving short-time existence and uniqueness for various flows.

problem Analyzing flows of geometric structures, focusing on non-isometric flows and specific subgroups.
method Developed algebra and compared two flows: negative gradient and Ricci-harmonic. Proved existence and uniqueness for Ricci-harmonic flow.
result Proved short-time existence and uniqueness for Ricci-harmonic flow for arbitrary lower-order torsion-quadratic terms.

The paper proves an inequality and describes a curve flow in centro-affine geometry.

problem Proving the isoperimetric inequality in centro-affine plane geometry.
method Investigating a curve flow with centro-affine curvature, expressed as a nonlinear parabolic equation.
result Closed convex curves may converge to ellipses under the described flow.

Causal autoregressive flows enable accurate causal inference and prediction.

problem Causal discovery and interventional predictions in machine learning.
method Autoregressive normalizing flows with fixed variable orderings.
result Causal models derived from autoregressive flows are identifiable and allow for accurate interventional and counterfactual predictions.