# A Validation Framework for Quantum Simulation of Spin Dynamics against Inelastic Neutron Scattering and Classical Simulation

**Authors:** Gilles Buchs, Elaine Wong, Anshumitra Baul, Kathleen E. Hamilton, Arnab Banerjee, Stephan Eidenbenz, Gábor B. Halász, Keerthi Kumaran, Thomas Maier, Thomas Naughton, Elijah Pelofske, Vincent Russo, Allen Scheie, Yigit Subasi, D. Alan Tennant, Akram Touil, Travis S. Humble, Andrew T. Sornborger  
**arXiv:** [2607.01568](https://arxiv.org/abs/2607.01568)  
**Date:** 2026-07-02  
**Summary page:** https://www.summarizepaper.com/en/arxiv-id/2607.01568v1/

## Key points

- Challenges in validating results from experiments, classical simulations, and quantum simulations in the field of quantum simulations of dynamical spin response
- Development of a cross-pipeline validation framework to address discrepancies in simulation results
- Inclusion of techniques for uncertainty propagation to ensure accurate comparisons between different simulation methods
- Utilization of a range of complementary metrics for comprehensive assessment of simulation accuracy and reliability at different levels

## Summary

, , , , 


In the field of quantum simulations of dynamical spin response, quantitative validation remains a challenge due to discrepancies in native observables produced by experiments, classical simulations, and quantum simulations. As quantum simulation protocols advance towards hardware-level benchmarking against neutron-scattering data, the need for validation in potentially classically intractable regimes becomes more pressing. To address this issue, a cross-pipeline validation framework has been developed using inelastic neutron scattering and classical many-body simulation as anchors. This framework incorporates explicit forward and inverse observable maps, uncertainty propagation techniques, robustness tests for structured distortion, and a hierarchy of complementary metric families. In the field of quantum simulations of dynamical spin response, there are challenges with validating results from experiments, classical simulations, and quantum simulations. The focus is on simulating dynamical spin response using various methods. A cross-pipeline validation framework has been developed to address discrepancies in results from different simulation methods. The framework includes techniques for propagating uncertainties to ensure accurate comparisons between different simulation methods. A range of complementary metrics is used to provide a comprehensive assessment of simulation accuracy and reliability at different levels.