Quantum software and materials discovery company OTI Lumionics, in collaboration with the Samsung Advanced Institute of Technology (SAIT), has published research benchmarking its proprietary Iterative Qubit Coupled Cluster (iQCC) algorithm in the Journal of the American Chemical Society (JACS). Detailed in the paper (“Large-Scale Quantum Computing Emulation for Accurate Triplet States of Ir(III) and Pt(II) Phosphorescent Emitters“), the team demonstrated 200+ logical qubit quantum algorithm emulations on accessible, non-supercomputing classical hardware to design materials for organic light-emitting diode (OLED) displays.

                    [ OTI Lumionics & SAIT Quantum Emulation Stack ]
                                           │
     ┌─────────────────────────────────────┼─────────────────────────────────────┐
     ▼                                     ▼                                     ▼
  Hardware Efficiency Benchmarks       iQCC Algorithmic Precision          Material Discovery Applications
  • 200+ Qubit Emulation on 1 CPU.     • Mean Absolute Error = 0.05 eV.    • 14 OLED Heavy-Metal Emitters.
  • 32-Core AMD Processor / 800GB RAM. • R² = 0.94 vs. Experiment.       • Ir(III) & Pt(II) Phosphors.
  • NVIDIA Blackwell: 90x Speedup.     • Solves Multireference States.     • T1 ➔ S0 Gap Predictions.

Algorithmic Benchmarks and Hardware Acceleration

The study benchmarked iQCC against classical methods—including Density Functional Theory (DFT), Time-Dependent DFT (TD-DFT), Coupled-Cluster Singles and Doubles (CCSD), and Completely Renormalized Coupled-Cluster (CR-CC(2,3))—across 14 phosphorescent transition-metal organometallic complexes. While standard single-reference classical methods broke down due to spin contamination and multireference character in the triplet (T1) excited states, iQCC maintained variational stability.

Hardware execution efficiency and algorithmic metrics include:

  • Single-CPU Execution: Executed emulations scaling up to 200 logical qubits using an optimized C++ codebase on a single commercial 32-core AMD CPU chip with 800GB of RAM, bypassing the need for high-performance computing (HPC) supercomputer clusters.
  • NVIDIA Blackwell Acceleration: Implementing iQCC on NVIDIA Blackwell system architectures yielded a 90x performance increase over classical CPU environments, reducing complex 112-qubit ground-state calculations to approximately one hour.
  • Predictive Accuracy: Achieved a Mean Absolute Error (MAE) of 0.05 eV and a correlation coefficient (R2) of 0.94 relative to experimental photoluminescence spectra, outperforming CR-CC(2,3) (MAE = 0.29 eV) and DFT variants.
  • Ansatz Scaling: Optimized variational quantum circuits containing over 1.5 million parameters and more than 10 million 2-qubit entangling gates without resorting to orbital partitioning schemes.

By raising the performance baseline for classical emulation of fault-tolerant quantum algorithms, the joint research establishes a rigorous, application-level target for future physical quantum processors to surpass in molecular electronic-structure calculations.

Review the peer-reviewed research in the Journal of the American Chemical Society here, and read the announcement on GlobeNewswire here.

August 18, 2026

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