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Choice functions constitute a simple, direct and very general mathematical framework for modelling choice under uncertainty. In particular, they are able to represent the set-valued choices that appear in imprecise-probabilistic decision…

Artificial Intelligence · Computer Science 2019-05-22 Jasper De Bock , Gert de Cooman

In order to analyze the effect of chaos or order on the rate of decoherence in a subsystem we aim to distinguish effects of the two types of dynamics from those depending on the choice of the wave packet. To isolate the former we introduce…

Chaotic Dynamics · Physics 2007-05-23 T. Gorin , T. H. Seligman

Power system coherency refers to the phenomenon that machines in a power network exhibit similar frequency responses after disturbances, and is foundational for model reduction and control design. Despite abundant empirical observations,…

Systems and Control · Electrical Eng. & Systems 2025-11-11 Yixuan Liu , Yingzhu Liu , Pengcheng You

Incoherence in the controlled Hamiltonian is an important limitation on the precision of coherent control in quantum information processing. Incoherence can typically be modelled as a distribution of unitary processes arising from slowly…

Quantum Physics · Physics 2009-11-10 N. Boulant , S. Furuta , J. Emerson , T. F. Havel , D. G. Cory

In this paper we study the price dynamics in a simple model of financial markets with heterogeneous agents. We concentrate on how increases in the total number of active traders influences fluctuations of asset prices. We find that a…

Chaotic Dynamics · Physics 2015-06-26 Taisei Kaizoji

This paper presents an elementary proof of quantitative uniform-in-time propagation of chaos for the Cucker--Smale model under sufficiently strong interaction. The idea is to combine existing finite-time propagation of chaos estimates with…

Probability · Mathematics 2025-11-03 Nicolai Jurek Gerber , Urbain Vaes

Chaos is generic in strongly-coupled recurrent networks of model neurons, and thought to be an easily accessible dynamical regime in the brain. While neural chaos is typically seen as an impediment to robust computation, we show how such…

Neurons and Cognition · Quantitative Biology 2024-09-30 Rishidev Chaudhuri , Vivek Handebagh

In this paper we introduce a class of information-based models for the pricing of fixed-income securities. We consider a set of continuous- time information processes that describe the flow of information about market factors in a monetary…

Pricing of Securities · Quantitative Finance 2010-04-27 Lane P. Hughston , Andrea Macrina

A simplified Heisenberg spin model is studied in order to examine the idea of decoherence in closed quantum systems. For this purpose, we present a quantifiable definition to quantum coherence $\Xi$, and discuss in some detail a general…

Quantum Physics · Physics 2008-05-18 Olavi Dannenberg

The general problem of asset pricing when the discount rate differs from the rate at which an asset's cash flows accrue is considered. A pricing kernel framework is used to model an economy that is segmented into distinct markets, each…

Mathematical Finance · Quantitative Finance 2018-02-19 Andrea Macrina , Obeid Mahomed

Chaos is widely understood as being a consequence of sensitive dependence upon initial conditions. This is the result of an instability in phase space, which separates trajectories exponentially. Here, we demonstrate that this criterion…

Chaotic Dynamics · Physics 2017-06-28 Marc Pradas , Alain Pumir , Greg Huber , Michael Wilkinson

The authors review the evidence for the applicability of random--matrix theory to nuclear spectra. In analogy to systems with few degrees of freedom, one speaks of chaos (more accurately: quantum chaos) in nuclei whenever random--matrix…

Nuclear Theory · Physics 2014-11-18 H. A. Weidenmuller , G. E. Mitchell

We establish a rigorous connection between quantum coherence and quantum chaos by employing coherence measures originating from the resource theory framework as a diagnostic tool for quantum chaos. We quantify this connection at two…

Quantum Physics · Physics 2021-06-21 Namit Anand , Georgios Styliaris , Meenu Kumari , Paolo Zanardi

This paper presents an axiomatic scheme for interest rate models in discrete time. We take a pricing kernel approach, which builds in the arbitrage-free property and provides a link to equilibrium economics. We require that the pricing…

Pricing of Securities · Quantitative Finance 2009-11-05 Lane P. Hughston , Andrea Macrina

A set of zero-range scatterers along its axis lifts the integrability of a harmonic waveguide. Effective solution of the Schr\"odinger equation for this model is possible due to the separable nature of the scatterers and millions of…

Quantum Physics · Physics 2023-12-06 Vladimir A. Yurovsky

It is shown that the time-energy uncertainty relation can be combined into the position-momentum uncertainty relation covariantly in the quark model of hadrons. This leads to a Lorentz-invariant form of the uncertainty relations. This model…

Quantum Physics · Physics 2016-10-26 Y. S. Kim

We speak of chaos in quantum systems if the statistical properties of the eigenvalue spectrum coincide with predictions of random-matrix theory. Chaos is a typical feature of atomic nuclei and other self-bound Fermi systems. How can the…

Nuclear Theory · Physics 2008-11-26 T. Papenbrock , H. A. Weidenmueller

The Polynomial Chaos Expansion (PCE) technique recovers a finite second order random variable exploiting suitable linear combinations of orthogonal polynomials which are functions of a given stochas- tic quantity {\xi}, hence acting as a…

Computational Finance · Quantitative Finance 2016-10-31 Luca Di Persio , Michele Bonollo , Gregorio Pellegrini

In this survey paper we discuss recent advances on short interest rate models which can be formulated in terms of a stochastic differential equation for the instantaneous interest rate (also called short rate) or a system of such equations…

Mathematical Finance · Quantitative Finance 2016-07-19 Zuzana Buckova , Beata Stehlikova , Daniel Sevcovic

The striking fractal geometry of strange attractors underscores the generative nature of chaos: like probability distributions, chaotic systems can be repeatedly measured to produce arbitrarily-detailed information about the underlying…

Machine Learning · Computer Science 2023-01-31 William Gilpin