Atomistic Modeling Speeds Quantum Material Discovery for Qub

Image source: semiengineering.com

## Atomistic Simulation Accelerates Development of Quantum Materials

The race to build practical quantum computers hinges on discovering and optimizing new materials exhibiting specific quantum properties. Traditionally, this process has relied on costly and time-consuming experimental trial and error. Now, advanced atomistic modeling is emerging as a powerful tool to **predict the intrinsic physical behavior of new materials *before* they are even synthesized**, potentially accelerating the development of this transformative technology. Recent advancements in quantum computing, including demonstrations of error correction and claims of quantum supremacy, are fueling this demand for faster materials discovery.

## Addressing the Challenges of Qubit Development

Quantum computers leverage **qubits**, which, unlike classical bits, can exist in multiple states simultaneously. Creating and controlling qubits is exceptionally challenging; noise and imperfections readily disrupt their behavior. Precise understanding of underlying material properties is therefore crucial for isolating qubits and minimizing noise—key hurdles in quantum computing development. Atomistic modeling offers a pathway to address these challenges by providing unprecedented insight into the phenomena affecting qubit performance, such as thermal effects and interface scattering.

## Synopsys QuantumATK: A Simulation Platform for the Quantum Era

**Synopsys QuantumATK** is a leading atomistic modeling and simulation software designed to address these materials development needs. Combining techniques like **density functional theory (DFT)** within a unified framework, QuantumATK offers several key features to accelerate research: hardware acceleration via **GPUs** (achieving up to 20X faster training and 5-15X faster execution), integration of **machine learning (ML)** (providing near-quantum accuracy at speeds 1000-100,000X faster than traditional methods), and a flexible application programming interface (API) for custom ML model development. The platform also uniquely supports surface Green’s function techniques for modeling topological insulators and the simulation of complex systems, such as double quantum dots containing over one million atoms.

## Beyond Qubits: Exploring Quantum Phenomena and Future Applications

While primarily focused on qubit development, QuantumATK’s capabilities extend to the study of other fundamental quantum models, such as the **Fermi-Hubbard model**. Recent work presented at the **GOMACTech 2025** conference highlighted its ability to model superconducting tunnel junctions and predict critical temperature enhancements through strain application. As quantum computing matures, hybrid simulation approaches – combining quantum hardware with classical simulations – are expected to play a vital role, and Synopsys QuantumATK is positioned to provide the necessary tools and flexibility to guide the development of next-generation materials for quantum applications and beyond.

Source: https://semiengineering.com/materials-modeling-of-superconducting-qubits-in-quantum-computers/