Quantum 3xplorer (Q3), an AI-native quantum simulation engine, is now open source as part of CAMSAI.org, an open, vendor-neutral community for advancing materials science with AI. Q3 is written from scratch by AI coding agents under the direction and supervision of domain scientists. In this approach, scientists define the physics, formulate the models, and set the criteria for validation, while AI agents write, test, and optimize the code. Exabyte Inc. (Mat3ra.com) contributed to its ideation and development.
A preprint on arXiv describes the engine and its validation. Its authors are from Exabyte Inc. (Mat3ra.com), Lawrence Berkeley National Laboratory and its National Energy Research Scientific Computing Center (NERSC), the University of California at Berkeley, Stanford University, SLAC National Accelerator Laboratory, the University of Southern California, Johns Hopkins University, the Air Force Research Laboratory, and NVIDIA Corporation.
As a first validation case, Q3 implements plane-wave pseudopotential density functional theory (DFT), including norm-conserving, ultrasoft, and projector-augmented-wave formalisms, spin polarization, Hubbard U and dispersion corrections, forces, stresses, and structural relaxation. Its layered architecture separates quantum-mechanical concepts from numerical representations, so it can extend to other basis sets and levels of theory. Inputs and outputs follow schema-validated data standards.
“Q3 enables AI-driven quantum theory,” said Timur Bazhirov, CEO of Exabyte Inc. (Mat3ra.com) and the preprint's corresponding author. “We designed it as foundational software infrastructure that turns new theoretical approaches into practical, high-performance tools for predicting the properties of materials with high fidelity, at the speed of AI.”
“We are in conversations with established scientific codebases and see a two-way exchange with Q3, where Q3 both uses them for validation and contributes code back under a permissive license, with clear provenance checks,” Bazhirov added. “Q3 is released through CAMSAI.org, an open, independent consortium that is distinct from any of its current contributors and welcomes community participation. Mat3ra.com has a long history of developing open-source software and will support the effort.”
The preprint has not yet been peer reviewed, and its findings may change.
Availability.
- Preprint: https://arxiv.org/abs/2610.42108
- Code: https://github.com/camsai/q3
- Documentation: https://camsai.github.io/q3/
About CAMSAI.
The Consortium for the Advancement of Materials Science with AI (CAMSAI) develops and sustains open-source software, open data standards, and educational material for materials science. Its website is at camsai.org.
About Mat3ra.com.
Mat3ra.com, developed by Exabyte Inc., is a cloud-based research and development platform driving innovation through the strategic integration of cloud high-performance computing and artificial intelligence for materials science. The platform empowers a community of over 40,000 scientists worldwide to collaborate and generate the high-quality, ground-truth physical data essential for advancing materials AI across the semiconductor, energy, and defense sectors. Mat3ra.com serves a diverse customer base ranging from Global 2000 companies to leading public R&D institutions.
For more information, visit Mat3ra.com.
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