Abstract: The eigenmode theory, which uses the modal currents solved from surface differential equations (SDEs) as the basis functions of the method of moment (MoM), has been applied to the analysis ...

Quantum computers are expected to potentially impact on various fields, including finance, quantum chemistry, optimization problems, and machine learning 1. So far, research has primarily focused on ...

I'm very often asked to recommend books to get started on quantification in risk management and strategy. This is really hard to do in general as that journey depends very much on where you start - ...

Distributions: Normal, Gamma, Non-Central Chi-Squared (some functions are delegated to Apache commons-math). Models: Black Scholes, Bachelier, SABR, ZABR, CEV, etc. The library is available for Java ...

Brownian motion (BM) is a stochastic model that has been extensively studied in physics, finance, and engineering. However, its potential use in cryptographic applications remains underexplored. This ...

Silent data errors are raising concerns in large data centers, where they can propagate through systems and wreak havoc on long-duration programs like AI training runs. SDEs, also called silent data ...

Silent data corruption errors in large server farms have become a major concern of cloud users, hyperscalers, processor manufacturers and the test community. Silent data errors (also called silent ...

For example, ML models can help identify early signs of interest rate volatility, allowing risk managers to take action before large movements occur. By leveraging data streams, financial institutions ...

The model equations are as follows. $$ \begin{align*} \dfrac{\mathrm dS}{\mathrm dt} &= -\frac{\beta c S I}{N}, \\ \dfrac{\mathrm dI}{\mathrm dt} &= \frac{\beta c S I ...

Abstract: We consider the problem of estimating the expectation over a convex polyhedron specified by a set of linear inequalities. This problem encompasses a multitude of financial applications ...

Sampling from a given probability distribution is fundamental across various disciplines, including physics, signal processing, and artificial intelligence. In recent years, the ascendancy of flow, ...