The Discrete Adjoint Method: Efficient Derivatives for Functions of Discrete Sequences

2020/02/02 by Michael Betancourt, Charles C. Margossian, Betancourt, Michael +3 · 1 citation
Mathematics · Physics and Astronomy · #Computation (stat.CO) #FOS: Computer and information sciences #Markov Chains and Monte Carlo Methods #Mathematical Approximation and Integration #Scientific Research and Discoveries

paper · pdf · doi:10.48550/arxiv.2002.00326

openalex publication_date 2020/02/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Gradient-based techniques are becoming increasingly critical in quantitative fields, notably in statistics and computer science. The utility of these techniques, however, ultimately depends on how efficiently we can evaluate the derivatives of the complex mathematical functions that arise in applications. In this paper we introduce a discrete adjoint method that efficiently evaluates derivatives for functions of discrete sequences.

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• High-Order Hermite Optimization: Fast and Exact Gradient Computation in Open-Loop Quantum Optimal Control using a Discrete Adjoint Approach

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