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This paper suggests a new way to compute the path integral for simple quantum mechanical systems. The new algorithm originated from previous research in string theory. However, its essential simplicity is best illustrated in the case of a…

Quantum Physics · Physics 2009-10-31 S. Ansoldi , A. Aurilia , E. Spallucci

A method is presented which restricts the space of paths entering the path integral of quantum mechanics to subspaces of $C^\alpha$, by only allowing paths which possess at least $\alpha$ derivatives. The method introduces two external…

Quantum Physics · Physics 2015-10-09 Benjamin Koch , Ignacio Reyes

In this paper, we propose an iterative splitting method to solve the partial differential equations in option pricing problems. We focus on the Heston stochastic volatility model and the derived two-dimensional partial differential equation…

Computational Engineering, Finance, and Science · Computer Science 2020-03-31 Hongshan Li , Zhongyi Huang

The phase-integral method (PIM) is an asymptotic method of the geometrical optics or semi-classical type for solving approximately, but in many cases very accurately, a wide class of differential equations in physics. Unlike the related…

Mathematical Physics · Physics 2010-01-05 S. Yngve , B. Thidé

An extension of the classical action principle obtained in the framework of the gauge transformations, is used to describe the motion of a particle. This extension assigns many, but not all, paths to a particle. Properties of the particle…

Quantum Physics · Physics 2007-05-23 S. R. Vatsya

We apply path integration techniques to obtain option pricing with stochastic volatility using a generalized Black-Scholes equation known as the Merton and Garman equation. We numerically simulate the option prices using the technique of…

Condensed Matter · Physics 2007-05-23 Belal E. Baaquie , L. C. Kwek , M. Srikant

A computational technique borrowed from the physical sciences is introduced to obtain accurate closed-form approximations for the transition probability of arbitrary diffusion processes. Within the path integral framework the same technique…

Physics and Society · Physics 2008-12-10 Luca Capriotti

On the basis of the canonical quantization procedure of a system defined on a cubic lattice, we propose a new method, in which resolutions of unity expressed in terms of eigenvectors are naturally provided, to find eigenvectors of field…

High Energy Physics - Theory · Physics 2019-12-06 Seiji Sakoda

The Feynman path integral has revolutionized modern approaches to quantum physics. Although the path integral formalism has proven very successful and spawned several approximation schemes, the direct evaluation of real-time path integrals…

Quantum Physics · Physics 2025-01-28 Job Feldbrugge , Joshua Y. L. Jones

Financial derivative pricing is a significant challenge in finance, involving the valuation of instruments like options based on underlying assets. While some cases have simple solutions, many require complex classical computational methods…

Computational Finance · Quantitative Finance 2025-05-15 Robert Scriba , Yuying Li , Jingbo B Wang

A kink-based path integral method, previously applied to atomic systems, is modified and used to study molecular systems. The method allows the simultaneous evolution of atomic and electronic degrees of freedom. Results for CH$_4 $, NH$_3…

Chemical Physics · Physics 2009-11-11 Randall W. Hall

Path integrals are a ubiquitous tool in theoretical physics. However, their use is sometimes hindered by the lack of control on various manipulations -- such as performing a change of the integration path -- one would like to carry out in…

Statistical Mechanics · Physics 2023-04-21 Thibaut Arnoulx de Pirey , Leticia F. Cugliandolo , Vivien Lecomte , Frédéric van Wijland

This article is the second one in a series on the use of scaling invariance in finance. In the first article (cond-mat/9906048), we introduced a new formalism for the pricing of derivative securities, which focusses on tradable objects…

Condensed Matter · Physics 2007-05-23 Jiri Hoogland , Dimitri Neumann

The Feynman path integral approach to quantum mechanics is examined in the case where the configuration space is curved. It is shown how the ambiguity that is present in the choice of path integral measure may be resolved if, in addition to…

High Energy Physics - Theory · Physics 2007-05-23 David J. Toms

We propose the deep parametric PDE method to solve high-dimensional parametric partial differential equations. A single neural network approximates the solution of a whole family of PDEs after being trained without the need of sample…

Computational Finance · Quantitative Finance 2020-12-14 Kathrin Glau , Linus Wunderlich

A quantum measurement model based upon restricted path-integrals allows us to study measurements of generalized position in various one-dimensional systems of phenomenological interest. After a general overview of the method we discuss the…

Quantum Physics · Physics 2008-02-03 Tommaso Calarco , Roberto Onofrio , Carlo Presilla , Lorenza Viola

We study the heat statistics of a quantum Brownian motion described by the Caldeira-Leggett model. By using the path integral approach, we introduce a novel concept of the quantum heat functional along every pair of Feynman paths. This…

Statistical Mechanics · Physics 2018-07-18 Ken Funo , H. T. Quan

Path integrals for particles in curved spaces can be used to compute trace anomalies in quantum field theories, and more generally to study properties of quantum fields coupled to gravity in first quantization. While their construction in…

High Energy Physics - Theory · Physics 2017-04-26 Fiorenzo Bastianelli , Olindo Corradini , Edoardo Vassura

We make use of point transformations to introduce new canonical variables for systems defined on a finite interval and on the half-line so that new position variables should take all real values from $-\infty$ to $\infty$. The completeness…

High Energy Physics - Theory · Physics 2018-09-05 Seiji Sakoda

The use of random sampling in decision-making and control has become popular with the ease of access to graphic processing units that can generate and calculate multiple random trajectories for real-time robotic applications. In contrast to…

Robotics · Computer Science 2022-03-21 Hyung-Jin Yoon , Chuyuan Tao , Hunmin Kim , Naira Hovakimyan , Petros Voulgaris
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