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.
RC flow learns molecular kinetics in low dimensions.
Novel deep learning method predicts reaction coordinates and future MD trajectories.
We use the formalism of Geometrothermodynamics to describe chemical reactions in the context of equilibrium thermodynamics. Any chemical reaction in a closed system is shown to be described by a geodesic in a dimensional manifold that can be interpreted as the equilibrium space of the reaction. We first show this i…
Efficiently simulates Langevin dynamics on manifold using diffusion maps and finite volume schemes.
We study the phase field method for the volume preserving mean curvature flow. Given an initial hypersurface we proved the existence of the weak solution for the volume preserving mean curvature flow via the reaction diffusion equation with a nonlocal term. We also show the monotonicity formula and the density up…
Bounds on chemical reaction network relaxation rates using convex analysis.
New formulas derived for scalar curvature in generalized Ricci flow.
The study distills news sources to analyze stock reactions, finding sentiment has asymmetric and sector-specific effects.
This work improves chemistry modeling by jointly learning reaction progress variables and look-up models.
Derives variance kernel for reaction boundary in financial models.
Derives operational-time variance kernel for reaction boundaries in financial markets.
We study data-driven assistants that provide congestion forecasts to users of shared facilities (roads, cafeterias, etc.), to support coordination between them, and increase efficiency of such collective systems. Key questions are: (1) when and how much can (accurate) predictions help for coordination, and (2) which as…
Unified analytic account of correlation emergence and Epps effect in coupled limit order books
Computing equilibrium states in condensed-matter many-body systems, such as solvated proteins, is a long-standing challenge. Lacking methods for generating statistically independent equilibrium samples in "one shot", vast computational effort is invested for simulating these system in small steps, e.g., using Molecular…
In this article we define new flows on the Hitchin components for PGL(V). Special examples of these flows are associated to simple closed curves on the surface and give generalized twist flows. Other examples, so called eruption flows, are associated to pair of pants in S and capture new phenomena which are not present…
CRNN discovers chemical reaction pathways from data.
MEGAN models chemical reactions as graph edits, improving synthesis planning.
Upper bound on CRN reaction rates derived using information geometry.
Framework uses optimal transport for neural architecture search.
Graphs predict reaction conditions for organic chemistry.
Chemical reactions can be described as the stepwise redistribution of electrons in molecules. As such, reactions are often depicted using `arrow-pushing' diagrams which show this movement as a sequence of arrows. We propose an electron path prediction model (ELECTRO) to learn these sequences directly from raw reaction …
Paper studies Laplace operator estimates in harmonic map heat flows.
METRO predicts reactions using minimal templates, reducing computational overhead and achieving state-of-the-art results.
Chemical networks outperform spiking neural networks in classification tasks.
New Hermite approximations accelerate convergence with adaptive coordinate transformations.
We introduce an atlas adapted to the Toda flow on the manifold of full flags of any non-compact real semisimple Lie algebra, and on its Hessenberg-type submanifolds. In our local coordinates the Toda flow becomes linear. We use these new coordinates to show that the Toda flow on the manifold of full flags is Morse-Smal…
Constructs coordinates to diagonalize Toda flow on matrices with simple spectrum.
Bayesian inference for biochemical reaction networks using jump-diffusion approximations.
USD algorithm transports distributions with or without mass conservation.
Extends earthquake and horocycle flows to new measures.
The Almost Hermitian Curvature flow was introduced by Streets and Tian in order to study almost hermitian structures, with a particular interest in symplectic structures. This flow is given by a diffusion-reaction equation. Hence it is natural to ask the following: which almost hermitian structures are dynamically stab…
Study inverse curve shortening flow on hyperbolic plane, classifying solitons.
Green bond leaks impact equity markets, altering investor reactions.
We generalize the reaction-diffusion model A + B -> 0 in order to study the impact of an excess of A (or B) at the reaction front. We provide an exact solution of the model, which shows that linear response breaks down: the average displacement of the reaction front grows as the square-root of the imbalance. We argue t…
In the vector space of algebraic curvature operators we study the reaction ODE $$\frac{dR}{dt} = R^2+R^{#}= Q(R)$$ which is associated to the evolution equation of the Riemann curvature oper- ator along the Ricci flow. More precisely, we analyze the stability of a special class of zeros of this ODE up to suitable norma…
This paper aims to systematically and comprehensively initiate a foundation for using concepts from computational differential geometry as instruments for power flow computing and research. At this point we focus our discussion on the static case, with power flow equations given by quadratic functions defined on voltag…
Characterizes parabolic flute surfaces with specific parameters.
The prediction of organic reaction outcomes is a fundamental problem in computational chemistry. Since a reaction may involve hundreds of atoms, fully exploring the space of possible transformations is intractable. The current solution utilizes reaction templates to limit the space, but it suffers from coverage and eff…
New PINN architectures learn high-frequency features using Fourier features.
New method uses machine learning to analyze catalyst reactions.
We consider inverse curvature flows in warped product manifolds, which are constrained subject to local terms of lower order, namely the radial coordinate and the generalized support function. Under various assumptions we prove longtime existence and smooth convergence to a coordinate slice. We apply this result to ded…
The growing ubiquity of Social Media data offers an attractive perspective for improving the quality of machine learning-based models in several fields, ranging from Computer Vision to Natural Language Processing. In this paper we focus on Facebook posts paired with reactions of multiple users, and we investigate their…
Reaction prediction remains one of the major challenges for organic chemistry, and is a pre-requisite for efficient synthetic planning. It is desirable to develop algorithms that, like humans, "learn" from being exposed to examples of the application of the rules of organic chemistry. We explore the use of neural netwo…
Considered an important macroeconomic indicator, the Purchasing Managers' Index (PMI) on Manufacturing generally assumes that PMI announcements will produce an impact on stock markets. International experience suggests that stock markets react to negative PMI news. In this research, we empirically investigate the stock…
In this paper, we study the herding phenomena in financial markets arising from the combined effect of (1) non-coordinated collective interactions between the market players and (2) concurrent reactions of market players to dynamic market signals. By interpreting the expected rate of return of an asset and the favorabi…
In this paper, we consider the heat flow for Yang-Mills connections on . In the equivariant setting, the Yang-Mills heat equation reduces to a single semilinear reaction-diffusion equation for which an explicit self-similar blowup solution was found by Weinkove \cite{Wei04}. We prove …
Study geodesic flow on symmetric surfaces to determine parabolic type.
Study the singular limit of a boundary reaction equation, showing energy concentration and varifold support.