  Simulations of quantum chemistry and quantum materials are believed to be
among the most important potential applications of quantum information
processors, but realizing practical quantum advantage for such problems is
challenging. Here, we introduce a simulation framework for strongly correlated
quantum systems that can be represented by model spin Hamiltonians. Our
approach leverages reconfigurable qubit architectures to programmably simulate
real-time dynamics and introduces an algorithm for extracting chemically
relevant spectral properties via classical co-processing of quantum measurement
results. We develop a digital-analog simulation toolbox for efficient
Hamiltonian time evolution utilizing digital Floquet engineering and
hardware-optimized multi-qubit operations to accurately realize complex
spin-spin interactions, and as an example present an implementation proposal
based on Rydberg atom arrays. Then, we show how detailed spectral information
can be extracted from these dynamics through snapshot measurements and
single-ancilla control, enabling the evaluation of excitation energies and
finite-temperature susceptibilities from a single-dataset. To illustrate the
approach, we show how this method can be used to compute key properties of a
polynuclear transition-metal catalyst and 2D magnetic materials.
