A Digital Spreading Framework for Quantum Expectation Computation Without Rotation Gates or Arithmetic Circuits

TL;DR

This paper introduces Digital Spreading (DS), a digital quantum computing framework that avoids rotation gates and complex arithmetic, achieving high precision in quantum weighted-average calculations for financial applications.

Contribution

The study presents DS, a novel digital quantum framework using a pruned ripple-carry architecture that eliminates rotation gates and reduces complexity for quantum expectation computations.

Findings

DS achieves a relative error of 0.0001% in option pricing simulations.

DS outperforms rotation-based and calibration methods in accuracy.

The framework is compact, robust, and suitable for NISQ-era quantum devices.

Abstract

In the pursuit of quantum advantage for financial engineering, researchers face a critical dilemma: analog rotation gates suffer from inherent 'sine-to-square' biases and error magnification, while digital arithmetic circuits (e.g., WeightedAdder) incur prohibitive quadratic complexity that exceeds NISQ capabilities. This study introduces Digital Spreading (DS), a fully digital quantum computing framework designed to resolve this trade-off. DS overcomes these limitations by utilizing a pruned Cuccaro ripple-carry architecture that avoids costly multiplication and eliminates rotation gates entirely. The proposed circuit employs integer comparison operations on superposed quantum states, mapping multi-qubit outcomes onto the probability of a single target qubit. Experiments based on a random walk model for option pricing demonstrate that DS achieves floating-point precision with a relative error as low as 0.0001%, outperforming JP Morgan's rotation-based method (1.43%), as well as ITRI's analog calibration (1.43%) and digital calibration approaches (19.14%). Overall, DS provides a compact, robust, and accurate framework for quantum weighted-average computation.