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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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1234 · Oct 202519922001200920172026
48 results for coexistence

Paper analyzes coexisting hidden and self-excited attractors in an economic system.

problem Existence of coexisting hidden and self-excited attractors in economic systems.
method Integer and fractional order analysis of an economic system.
result Integer-order system exhibits multiple combinations of coexisting hidden and self-excited attractors.

Model shows how multiple markets can coexist or fragment based on trader behavior.

problem Understanding market competition and coexistence among multiple trading venues.
method Stylized model of traders making repeated decisions at three markets, analyzed numerically and analytically.
result Parameters like memory length and choice intensity determine whether markets coexist or fragment.

Individual choices are either based on personal experience or on information provided by peers. The latter case, causes individuals to conform to the majority in their neighborhood. Such herding behavior may be very efficient in aggregating disperse private information, thereby revealing the optimal choice. However if …

2005-06-17abs ↗pdf ↗

This paper analyzes complex equilibria in a networked bivirus epidemic model.

problem Identify conditions for coexistence equilibria in a networked bivirus model.
method Employ Poincaré-Hopf Theorem with modifications and Morse inequalities.
result Establish properties on the local stability/instability of coexistence equilibria.

A method for trust evaluation of devices in human-device coexistence systems.

problem Efficient trust evaluation of devices in systems with diverse physical and social attributes.
method Canonical correlation analysis-enhanced hypergraph self-supervised learning (HSLCCA).
result The proposed HSLCCA method significantly outperforms baseline algorithms in identifying trusted devices.

Over-parameterized models can memorize noisy labels and still generalize well, revealing a hidden structure.

problem Understanding how over-parameterized models can simultaneously memorize noisy labels and generalize well.
method Investigated through modular arithmetic tasks with label noise using two-layer neural networks.
result Over-parameterized models can achieve near-perfect test accuracy with 80% label noise by extracting an internal generalization structure.

In the area of traditional physics the atomic nucleus belongs to the most complex systems. It involves essentially all elements that characterize complexity including the most distinctive one whose essence is a permanent coexistence of coherent patterns and of randomness. From a more interdisciplinary perspective, thes…

2010-09-06abs ↗pdf ↗

FedReLa: A novel data-level approach for imbalanced federated learning

problem Improving accuracy of federated learning models under class imbalance and data heterogeneity
method Re-labeling samples with a feature-dependent label re-allocator
result Significant improvements in accuracy for minority classes and overall accuracy on stepwise-imbalanced and long-tailed datasets

Trust is a collective, self-fulfilling phenomenon that suggests analogies with phase transitions. We introduce a stylized model for the build-up and collapse of trust in networks, which generically displays a first order transition. The basic assumption of our model is that whereas trust begets trust, panic also begets…

2014-09-22abs ↗pdf ↗

Given a branched covering of degree d between closed surfaces, it determines a collection of partitions of d, the branch data. In this work we show that any branch data are realized by an indecomposable primitive branched covering on a connected close surface N with Euler's characteristic less than or equal to 0. This …

2007-07-19abs ↗pdf ↗

We propose a conceptual design for a quantum blockchain. Our method involves encoding the blockchain into a temporal GHZ (Greenberger-Horne-Zeilinger) state of photons that do not simultaneously coexist. It is shown that the entanglement in time, as opposed to an entanglement in space, provides the crucial quantum adva…

2018-04-16abs ↗pdf ↗

Study topological properties of foliations induced by closed 1-forms on orbifolds.

problem Characterize the topology of foliation leaves induced by closed 1-forms on orbifolds.
method Establish criteria for the compactness of foliation leaves and extend a topological result to orbifolds.
result Criteria for the compactness and coexistence of foliation leaves are established.

Novel approach models opponent learning dynamics in multi-agent reinforcement learning.

problem Adaptation and learning of other agents in multi-agent settings cause non-stationarity, challenging existing algorithms.
method Develops a novel approach called Learning to Model Opponent Learning (LeMOL) to accurately model opponent learning dynamics.
result Structured opponent model is more accurate and stable than naive baselines.

The z-transform technique is used to investigate the model for distribution of high-tax payers, which is proposed by two of the authors (K. Y and S. M) and others. Our analysis shows an asymptotic power-law of this model with the exponent -5/2 when a total ``mass'' has a certain critical value. Below the critical value…

2005-10-26abs ↗pdf ↗

Study characterizes points on projective surfaces using a cubic form.

problem Characterize points on projective surfaces and their impact on Euler characteristic.
method Define local indices for umbilics and godrons, use fundamental cubic form.
result Formulas relating indices to Euler characteristic determine coexistences of points.

We show that any noncompact oriented surface is homeomorphic to the leaf of a minimal foliation of a closed 33-manifold. These foliations are (or are covered by) suspensions of continuous minimal actions of surface groups on the circle. Moreover, the above result is also true for any prescription of a countable family…

2019-10-30abs ↗pdf ↗

Many complex systems exhibit extreme events far more often than expected for a normal distribution. This work examines how self-similar bursts of activity across several orders of magnitude can emerge from first principles in systems that adapt to information. Surprising connections are found between two apparently unr…

2015-11-11abs ↗pdf ↗

New algorithm detects cores in graphs with community structure, improving vertex selection for better clustering.

problem Understanding and detecting core-periphery structures in graphs with community structure.
method Introduces relative centrality to detect cores in graphs with community and core-periphery structures.
result Relative centrality solves bias issues in core detection, leading to better vertex selection and improved clustering performance.

Minimal hyperbolic foliations on 3-manifolds have non-simply connected generic leaves.

problem Characterizing surfaces with minimal hyperbolic foliations.
method Analyzing codimension one foliations on closed 3-manifolds.
result Noncompact surfaces satisfying a specific condition are homeomorphic to the leaf of a minimal foliation with non-simply connected generic leaf.

The existence of a phase transition with diverging susceptibility in batch Minority Games (MGs) is the mark of informationally efficient regimes and is linked to the specifics of the agents' learning rules. Here we study how the standard scenario is affected in a mixed population game in which agents with the `optimal'…

2007-12-03abs ↗pdf ↗

It has been assumed that arbitrage profits are not possible in efficient markets, because future prices are not predictable. Here we show that predictability alone is not a sufficient measure of market efficiency. We instead propose to measure inefficiencies of markets in terms of the maximal profit an ideal trader can…

2004-03-24abs ↗pdf ↗

Econometric framework integrates heavy-tailed distributions with behavioral probability weighting for better asset pricing.

problem Underestimation of Value-at-Risk by traditional models in asset pricing.
method Developed an econometric framework combining heavy-tailed Student's tt distributions with behavioral probability weighting.
result Student's tt specifications outperform Gaussian models in 88.4% of cases, reducing underestimation of Value-at-Risk by 16.5 percentage points.

A theory of exceptional extreme events, characterized by their abnormal sizes compared with the rest of the distribution, is presented. Such outliers, called "dragon-kings", have been reported in the distribution of financial drawdowns, city-size distributions (e.g., Paris in France and London in the UK), in material f…

2012-05-07abs ↗pdf ↗

The study of limit cones for multi-Fuchsian representations in (PSL2R)d(\mathrm{PSL}_2\mathbf{R})^d.

problem Characterizing the structure of limit cones for multi-Fuchsian representations.
method Analysis of normalized multi-lengths and convex cones in R0d\mathbf{R}^d_{\geq 0}.
result Different regimes of limit cones exist, with some having finite sides and others dense extremal rays.

Fluctuation scaling is observed phenomenon from complex networks through finance to ecology. It means that the variance and the mean of a specific quantity are related as $\ev{σ^2|n}\propto \ev{n|A}^{2α}$ with 1/2α11/2\geq α\geq 1 when a parameter AA (usually the system size) is varied. AA can be the strength of the nod…

2007-03-12abs ↗pdf ↗

R. Schwartz's inequality provides an upper bound for the Schwarzian derivative of a parameterization of a circle in the complex plane and on the potential of Hill's equation with coexisting periodic solutions. We prove a discrete version of this inequality and obtain a version of the planar Blaschke-Santalo inequality …

2010-06-07abs ↗pdf ↗

Study validates Michor-Mumford conjecture in infinite dimensional Hilbertian H-type groups.

problem Validation of Michor-Mumford conjecture in infinite dimensional Hilbertian H-type groups.
method Introduced infinite dimensional Hilbertian H-type groups with weak, graded, left invariant Riemannian metrics and proved the vanishing of geodesic distance and local unboundedness of sectional curvature.
result Validation of Michor-Mumford conjecture linking geodesic distance vanishing to local unboundedness of sectional curvature.

Machine learning predicts phase behavior in active matter suspensions.

problem Predicting phase behavior in active matter systems using machine learning.
method Used deep learning techniques, including fully connected networks and graph neural networks, to predict motility-induced phase separation (MIPS) in ABP suspensions.
result Strong agreement between machine learning predictions and MIPS binodal from simulations, suggesting machine learning as an effective method for phase behavior determination.