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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.

168,695 papers · 148 categories

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65129194258 · May 202619922001200920172026
48 results for controlled mass

The paper proves Zimmer's conjecture for non-uniform lattices by controlling mass escape and Lyapunov exponents.

problem Proving Zimmer's conjecture for non-uniform lattices in higher-rank semisimple Lie groups.
method Establishes finiteness of low-dimensional actions, introduces novel techniques to control mass escape and Lyapunov exponents.
result Proves Zimmer's conjecture for many non-uniform lattices, improving previous results.

The Positive Mass Theorem for special singular initial data.

problem Proving the positive mass theorem for data with a codimension one singularity.
method Using asymptotically flat spin initial data sets with matching Bartnik data condition involving spacetime rotations.
result Established a spacetime positive mass theorem and rigidity statement.

Study shows a mass quantity for C0C^0 metrics that agrees with ADM mass.

problem Understanding ADM mass for C0C^0 metrics and its behavior under Ricci-DeTurck flow.
method Developed a C0C^0 mass quantity and analyzed its behavior under Ricci-DeTurck flow.
result The C0C^0 mass at infinity is independent of coordinate charts and has controlled distortion under Ricci-DeTurck flow.

Study of Brown--York mass for four-dimensional asymptotically flat manifolds.

problem Calculating mass for hypersurfaces in four-dimensional asymptotically flat manifolds.
method Intrinsic definition of mean curvature, expansion analysis for large uniformly convex hypersurfaces.
result Shape-dependent correction to ADM mass for nearly round surfaces vanishes under certain conditions.

The Bartnik mass is a notion of quasi-local mass which is remarkably difficult to compute. Mantoulidis and Schoen [2016] developed a novel technique to construct asymptotically flat extensions of minimal Bartnik data in such a way that the ADM mass of these extensions is well-controlled, and thus, they were able to com…

2019-03-21abs ↗pdf ↗

Study controlled contagion with state-dependent killing, proving a comparison principle.

problem Analyzing controlled McKean--Vlasov contagion with state-dependent killing.
method Proof of a comparison principle using Wasserstein smooth-gauge comparison and killing-jump absorption estimates.
result Established a comparison principle for the two-population killed-particle HJB.

Mantoulidis and Schoen developed a novel technique to handcraft asymptotically flat extensions of Riemannian manifolds (ΣS2,g)(Σ\cong \mathbb{S}^2,g), with gg satisfying λ1=λ1(Δg+K(g))>0λ_1 = λ_1(-Δ_g + K(g))>0, where λ1λ_1 is the first eigenvalue of the operator Δg+K(g)-Δ_g+K(g) and K(g)K(g) is the Gaussian curvature of gg, with control on t…

2019-04-11abs ↗pdf ↗

Constructs initial data for Einstein equations and estimates Bartnik mass outside time-symmetry.

problem Estimating Bartnik mass outside time-symmetry.
method Constructs initial data for Einstein equations and connects Bartnik data to time-symmetric data.
result Obtains estimates for the Bartnik mass outside of time-symmetry.

Estimates the mass gap for domains with integral Ricci curvature bounds.

problem Estimating the mass gap for domains with specific curvature conditions.
method Proving domains are John domains to estimate the first nonzero Neumann eigenvalue.
result Fundamental gap estimates for domains with integral Ricci curvature bounds.

The paper analyzes harmonic maps to flat model spaces to prove geometric stability of the positive mass theorem.

problem Geometric stability of the positive mass theorem and related conjectures.
method Analysis of harmonic maps to flat model spaces under integral curvature bounds.
result Upgrading harmonic maps to diffeomorphisms when conditions are met, proving quantitative closeness to model spaces.

MF-PID uses interacting samples to efficiently transport probability mass.

problem Efficiently transporting probability mass in generative models.
method Introducing Mean-Field Path-Integral Diffusion (MF-PID) where samples become interacting agents.
result MF-PID achieves 19-24% reductions in control energy for demand-response control of energy systems.

Minimizes indecisions in selective classification to control misclassification rates.

problem Controlling misclassification rates in high-risk scenarios.
method Using indecisions to control misclassification rates, even below Bayes optimal.
result Control of misclassification rates to any user-specified level, even below Bayes optimal.

Solves probabilistic Lambert problem connecting astrodynamics with optimal mass transport.

problem Determining spacecraft velocity for given positions with probabilistic constraints.
method Generalized optimal mass transport (OMT) and Schrödinger bridge (SBP) connections.
result Existence and uniqueness of solution for probabilistic Lambert problem.

We study the stability of the Positive Mass Theorem (PMT) in the case where a sequence of regions of manifolds with positive scalar curvature UTiMi3U_T^i\subset M_i^3 are foliated by a smooth solution to Inverse Mean Curvature Flow (IMCF) which may not be uniformly controlled near the boundary. Then if $\partial U_T^i = Σ_…

2018-07-23abs ↗pdf ↗

Study shows how to learn optimal policies quickly in stochastic control problems.

problem Learning optimal policies in large, continuous state and action spaces with limited data.
method Analyzes three geometric exponents to quantify fast policy regret convergence.
result Shows that fast policy regret convergence is induced by specific geometric structures.

Agents learn and control complex mechanical systems through shared memories.

problem Controlling multi-joint dynamical systems.
method Coupled autoregressive active inference agents using Bayesian filtering and minimizing expected free energy.
result Demonstrated learning and control of a double mass-spring-damper system.

We quantify forgetting in post-training models, distinguishing mass and drift.

problem Understanding and preventing forgetting in post-training generative models.
method Developed theoretical results under a two-mode mixture abstraction, formalizing mass and drift forgetting.
result Forgetting can be precisely quantified based on divergence direction, geometric overlap, and training regime.

This paper constructs charged Riemannian manifolds to test Penrose inequality.

problem Testing the Riemannian Penrose Inequality with charged manifolds.
method Constructing asymptotically hyperbolic or Euclidean extensions with electric charge.
result Suggests instability of the generalized Riemannian Penrose Inequality.

We study the stability of the Positive Mass Theorem (PMT) and the Riemannian Penrose Inequality (RPI) in the case where a region of an asymptotically hyperbolic manifold M3M^3 can be foliated by a smooth solution of Inverse Mean Curvature Flow (IMCF) which is uniformly controlled. We consider a sequence of regions of a…

2017-07-28abs ↗pdf ↗

We study the inverse optimal control problem in social sciences: we aim at learning a user's true cost function from the observed temporal behavior. In contrast to traditional phenomenological works that aim to learn a generative model to fit the behavioral data, we propose a novel variational principle and treat user …

2018-05-22abs ↗pdf ↗

EHR-MPC optimizes sepsis treatment using digital twins and inference-time control.

problem Optimal sepsis treatment policies are contested and difficult to adapt during inference.
method EHR-MPC decouples learning patient dynamics from treatment optimization, enabling inference-time control over learned digital twins.
result EHR-MPC achieves comparable off-policy performance and improved simulation performance compared to RL baselines.

The paper studies nonlinear mass concepts in 3-manifolds with nonnegative scalar curvature.

problem Nonlinear isocapacitary mass in 3-manifolds with nonnegative scalar curvature.
method Derives positive mass theorems and shows mass coincides with ADM mass under mild conditions.
result Nonlinear masses coincide with ADM mass and prove the Penrose inequality.

A new pricing controller handles resource constraints to infer target prices effectively.

problem Resource constraints prevent fixed-price inference, leading to support exclusion.
method Formalizes support-exclusion failure, designs a target-aware controller, and uses a realized information clock.
result The controller can certify feasible target bands and log continuous local densities, leading to polynomial rates of inference.

In this paper, we introduce Symplectic ODE-Net (SymODEN), a deep learning framework which can infer the dynamics of a physical system, given by an ordinary differential equation (ODE), from observed state trajectories. To achieve better generalization with fewer training samples, SymODEN incorporates appropriate induct…

2019-09-26abs ↗pdf ↗

We present a methodology to extract the backbone of complex networks based on the weight and direction of links, as well as on nontopological properties of nodes. We show how the methodology can be applied in general to networks in which mass or energy is flowing along the links. In particular, the procedure enables us…

2009-02-05abs ↗pdf ↗

We prove directly without using a density theorem that (i) the ADM mass defined in the usual way on an asymptotically flat manifold is equal to the mass defined intrinsically using Ricci tensor; (ii) the Hamiltonian formulation of center of mass and the center of mass defined intrinsically using Ricci tensor are the sa…

2014-08-18abs ↗pdf ↗

Study explores warped geometries of tensor manifolds, finding non-geodesic connections for some parameters.

problem Investigate non-geodesic connections in warped Segre-Veronese manifolds.
method Investigate a one-parameter family of warped geometries, presenting closed expressions for maps and distance.
result Segre-Veronese manifolds are not geodesically connected in Euclidean geometry but can be for some warping parameters.

The paper examines mass aspects at future null infinity and limits of quasilocal mass.

problem Understanding mass aspects and limits of quasilocal mass at future null infinity.
method Review and extension of Bondi mass and mass loss formula in Bondi-Sachs coordinate system.
result New results about the limit of quasilocal mass of unit spheres at null infinity.