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Towards Quantum Advantage in Chemistry

Scott N. Genin, Ohyun Kwon, Seyyed Mehdi Hosseini Jenab, Seon-Jeong Lim, Taehyung Kim, Tae-Gon Kim, Rami Gherib, Angela F. Harper, Ilya G. Ryabinkin, Michael G. Helander

TL;DR

The paper develops and benchmarks the iterative qubit coupled-cluster (iQCC) quantum solver, demonstrating scalable emulation up to about $200$ logical qubits and millions of entangling gates on classical hardware. By computing the $T_1\rightarrow S_0$ gaps for Ir(III) and Pt(II) phosphorescent emitters and applying perturbative corrections, iQCC achieves state-of-the-art agreement with experiment (MAE $\approx$ 0.05 eV; $R^2$ $\approx$ 0.94–0.97), outperforming leading classical methods. The authors show near-linear scaling of runtime with respect to the product of qubits and entanglers via a parallel, bit-partitioned architecture, enabling large active-space simulations such as CAS$(100,100)$ with $\sim$1.5 million parameters and $\sim$10 million two-qubit gates. They also demonstrate a quantum-utility study for OLED materials, highlighting the potential of quantum-native methods in materials design while outlining future work on strongly correlated regimes and fault-tolerant hardware.

Abstract

Molecular simulations are widely regarded as leading candidates to demonstrate quantum advantage--defined as the point at which quantum methods surpass classical approaches in either accuracy or scale. Yet the qubit counts and error rates required to realize such an advantage remain uncertain; resource estimates for ground-state electronic structure span orders of magnitude, and no quantum-native method has been validated at a commercially relevant scale. Here we address this uncertainty by executing the iterative qubit coupled-cluster (iQCC) algorithm, designed for fault-tolerant quantum hardware, at unprecedented scale using a quantum solver on classical processors, enabling simulations of transition organo-metallic complexes requiring hundreds of logical qubits and millions of entangling gates. Using this approach, we compute the lowest triplet excited state (T$_1$) energies of Ir(III) and Pt(II) phosphorescent organometallic compounds and show that iQCC achieves the lowest mean absolute error (0.05 eV) and highest R$^2$ (0.94) relative to experiment, outperforming leading classical methods. We find these systems remain classically tractable up to $\sim$200 logical qubits, establishing the threshold at which quantum advantage in computational chemistry may emerge and clarifying resource requirements for future quantum computers.

Towards Quantum Advantage in Chemistry

TL;DR

The paper develops and benchmarks the iterative qubit coupled-cluster (iQCC) quantum solver, demonstrating scalable emulation up to about logical qubits and millions of entangling gates on classical hardware. By computing the gaps for Ir(III) and Pt(II) phosphorescent emitters and applying perturbative corrections, iQCC achieves state-of-the-art agreement with experiment (MAE 0.05 eV; 0.94–0.97), outperforming leading classical methods. The authors show near-linear scaling of runtime with respect to the product of qubits and entanglers via a parallel, bit-partitioned architecture, enabling large active-space simulations such as CAS with 1.5 million parameters and 10 million two-qubit gates. They also demonstrate a quantum-utility study for OLED materials, highlighting the potential of quantum-native methods in materials design while outlining future work on strongly correlated regimes and fault-tolerant hardware.

Abstract

Molecular simulations are widely regarded as leading candidates to demonstrate quantum advantage--defined as the point at which quantum methods surpass classical approaches in either accuracy or scale. Yet the qubit counts and error rates required to realize such an advantage remain uncertain; resource estimates for ground-state electronic structure span orders of magnitude, and no quantum-native method has been validated at a commercially relevant scale. Here we address this uncertainty by executing the iterative qubit coupled-cluster (iQCC) algorithm, designed for fault-tolerant quantum hardware, at unprecedented scale using a quantum solver on classical processors, enabling simulations of transition organo-metallic complexes requiring hundreds of logical qubits and millions of entangling gates. Using this approach, we compute the lowest triplet excited state (T) energies of Ir(III) and Pt(II) phosphorescent organometallic compounds and show that iQCC achieves the lowest mean absolute error (0.05 eV) and highest R (0.94) relative to experiment, outperforming leading classical methods. We find these systems remain classically tractable up to 200 logical qubits, establishing the threshold at which quantum advantage in computational chemistry may emerge and clarifying resource requirements for future quantum computers.

Paper Structure

This paper contains 15 sections, 18 equations, 6 figures, 9 tables.

Table of Contents

  1. Introduction
  2. Results
  3. Summary of iQCC
  4. Scalability Analysis and Benchmarking
  5. Quantum Utility Study: Estimating the peak PL emission of OLED materials
  6. Discussion
  7. Methods and Materials
  8. Qubit Hamiltonian and QCC ansatz
  9. Iterative QCC and generator selection
  10. Outline of the iQCC iteration.
  11. Parallel iQCC implementation
  12. Perturbative a posteriori energy corrections
  13. Simulation Protocols
  14. Synthesis and Measurement
  15. Acknowledgments

Figures (6)

  • Figure 1: Overview of the computational study for Ir(III) and Pt(II) phosphorescent emitters. (a) Schematic representation of the parallel workflow showing CPU-level Hamiltonian partitioning. (b) Scaling behavior of the parallel for H$_2$O, and (c) scaling behavior of total runtime for a 200 qubit system, Q1, as a function of both qubits, and normalized qubits $\times$ the number of entanglers required to converge the Hamiltonian as shown in Table \ref{['tab:Z']}. Dashed lines show a linear fit relative to the scaling data, indicating that with respect to Qubits $\times$ Number of Entanglers, iQCC scales approximately linearly. (d) Convergence of the 200 qubit Q1 molecule at CAS(100,100) (200 qubits) with 33 steps converges to the value, and the + surpasses the value.
  • Figure 2: Molecular structures of Ir (III) and Pt (II) complexes used in the benchmarking of . Q1 through Q7 are Ir (III) complexes and Q8 through Q14 are Pt (II) complexes.
  • Figure 3: of the T$_1$$\rightarrow$ S$_0$ gap computed using each method referenced in Table \ref{['tab:Y']} relative to the experimental T$_1$$\rightarrow$ S$_0$ gap obtained from the spectrum at 77 K. Red bars highlight the and + methods. The + and corresponding standard deviation are lowest of all the methods tested.
  • Figure 4: Absolute values of calculated T$_1$$\rightarrow$ S$_0$ gap for selected methods from Table \ref{['tab:Y']} relative to the experimental gap extracted from spectra at 77 K. The dashed black line shows a perfect agreement between the experimental and computed gap. and are shown at the bottom left, and exhibit a red shift (lower calculated gap than experiment), whereas several methods , TD-CAM-B3LYP, and RO-$\omega$B97X, all exhibit a blue shift (higher calculated gap than experiment). Results for are not shown, and are given in Table \ref{['tab:Y']}.
  • Figure SI.4-1: Circuit diagram for diatomic nitrogen generated from QISKIT javadi2024quantum
  • ...and 1 more figures