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 # Demonstration of SQD using the Qiskit C API
 
-This demo shows how to post-process noisy quantum samples to approximate the ground state energy of the Fe₄S₄ cluster, using the [Sample-based Quantum Diagonalization (SQD) algorithm](https://www.science.org/doi/10.1126/sciadv.adu9991).
+This code demonstrates an **end-to-end compiled hybrid quantum/classical computation** that uses [Sample-based Quantum Diagonalization (SQD)](https://www.science.org/doi/10.1126/sciadv.adu9991) to approximate the ground state energy of the Fe₄S₄ cluster. Unlike earlier demonstrations, this code compiles to a single executable which can be run across many nodes of a supercomputer while also leveraging quantum resources.  The workflow performs the following steps:
 
+1. Build a circuit.
+2. Transpile that circuit for a target hardware device.
+3. Execute the transpiled circuit on hardware.
+4. Perform classical post-processing according to the [Sample-based Quantum Diagonalization (SQD) algorithm](https://www.science.org/doi/10.1126/sciadv.adu9991).
+
+Steps 1 and 2 demonstrate features of the [Qiskit C API](https://quantum.cloud.ibm.com/docs/en/api/qiskit-c) that were introduced in Qiskit 2.1 and 2.2, respectively.
+
+Step 3 is mediated by the [Quantum Resource Management Interface](https://github.com/qiskit-community/qrmi) (QRMI), which is a thin middleware for controlling quantum resources.
+
+Step 4 is enabled by a new [HPC-ready SQD addon](https://github.com/Qiskit/qiskit-addon-sqd-hpc) for Qiskit, together with the [SBD eigensolver](https://github.com/r-ccs-cms/sbd) developed by RIKEN.
 
 ## Features
 
-- HPC-ready implementation using modern C++17 and MPI.
+- HPC-ready implementation using modern C++17, MPI, and OpenMP.
 - Integration with Qiskit C++, QRMI, and qiskit-addon-sqd-hpc.
 - Support for hybrid quantum-classical workflows, including:
   - Quantum sampling on real backends.