Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 2610.42108

Quantum 3xplorer: AI-Native Engine for Next-Generation Quantum Materials Modeling

Vsevolod Biryukov·Sergey V. Barabash·Pranab Kumar Das·Jack Deslippe·Mauro Del Ben·Felipe H. da Jornada·Yuming Shi·Johannes Voss·Zhenglu Li·Piero Altoe·Kamal Choudhary·Ruth Pachter·Steven G. Louie·Marvin L. Cohen·Timur Bazhirov
View original source ↗Read source document ↗Export metadata ↓

Abstract

Quantum-mechanical approaches, such as density functional theory (DFT), underpin much of modern computational materials science and are the primary source of data for AI-driven discovery. Yet the established electronic-structure codes today represent decades-old software architectures, making new physical models slow and costly to implement, validate, and deploy on emerging hardware. We present Quantum 3xplorer (Q3, pronounced "Quantum Explorer"), an AI-native quantum simulation engine written from scratch by AI coding agents under the direction and supervision of domain scientists. As a first and demanding validation case, we implement plane-wave pseudopotential DFT end to end: norm-conserving, ultrasoft, and projector-augmented-wave formalisms, spin polarization, DFT+U, and dispersion corrections, together with forces, stresses, structural relaxation, and electronic-structure analysis. Q3 reproduces established reference implementations, runs faster on a single core in representative benchmarks, and scales across GPU-accelerated supercomputers. It was developed in weeks rather than years. Its layered, physics-first architecture separates abstract quantum-mechanical concepts from their numerical representations, making its framework extendable beyond plane waves to other basis sets and levels of theory. Its inputs and outputs follow structured, schema-validated data standards, making every result AI-ready. Q3 is open source under Apache 2.0 and built to be reused, extended, and improved by the research community. Q3 points to a paradigm shift in how computational quantum science is done. Scientists define the physics, formulate the models, and set the criteria for validation; AI agents write, test, and optimize the code. The decades-long path from a new theory to a trusted, high-performance implementation can thus collapse to days, significantly accelerating scientific discovery.

Explore related subjects

cond-mat.mtrl-sci

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Vsevolod Biryukov, Sergey V. Barabash, Pranab Kumar Das, Jack Deslippe, Mauro Del Ben, Felipe H. da Jornada, Yuming Shi, Johannes Voss, Zhenglu Li, Piero Altoe, Kamal Choudhary, Ruth Pachter, Steven G. Louie, Marvin L. Cohen, Timur Bazhirov. 2026-10-30. Quantum 3xplorer: AI-Native Engine for Next-Generation Quantum Materials Modeling. https://arxiv.org/abs/2610.42108

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Impact of electron--spin coupling on exchange coupling parameters: a nonperturbative approach

Exchange coupling parameters $J_{ij}$ in the Heisenberg model are crucial for describing magnetic behavior at the atomic level. In magnetic materials, spin fluctuations can be accompanied by a self-consistent electronic response, i.e., electron--spin coupling in the sense of electronic feedback to finite spin rotations. However, the quantitative importance of this coupling in extracting reliable $J_{ij}$ has not been fully clarified. Here, using fully self-consistent, nonperturbative evaluations, we show that finite-angle spin rotations induce such electronic feedback and quantify how strongly it renormalizes the extracted $J_{ij}$. We examine systems of both fundamental and practical interest, including perovskite SrMnO$_3$, Nd-based permanent-magnet compounds (Nd$_2$Fe$_{14}$B and Nd$_2$Co$_{14}$B), and elemental 3$d$ transition metals. The nonperturbative approach yields exchange couplings that remain consistent over a wide range of rotation angles. Moreover, when the sampled configurations represent the magnetic disorder near the transition, spin models parameterized in this way give reasonable agreement with experimental magnetic phase-transition temperatures. Overall, our results demonstrate the quantitative impact of electron--spin coupling on the exchange coupling parameters $J_{ij}$ and provide a nonperturbative route to effective $J_{ij}$ for a specified regime of magnetic disorder.

cond-mat.mtrl-sci↗
arXiv2026

Benchmarking and advancing machine-learning interatomic potentials for 3C-SiC across equilibrium and extreme conditions

Several machine-learning interatomic potentials (MLIPs) have been developed for cubic silicon carbide (3C-SiC). Here, we benchmark seven existing MLIPs against a common set of structural, thermal, defect, radiation-damage, disordered-phase, and computational-performance tests. We also introduce two complementary MLIPs trained on DFT-labeled crystalline, liquid, amorphous, and defective configurations. TGAP, a Gaussian approximation potential based on the \verb|soap_turbo| descriptor, provides consistently high accuracy across the sampled configurational space. MTP, a custom moment tensor potential, retains good accuracy across these regimes while offering substantially lower computational cost, GPU acceleration, and access to multi-million-atom simulations. As an application-level test, both potentials remain stable in displacement cascades spanning short-range repulsion, transient disorder, and recrystallization. Overall, MTP emerges as a particularly strong accuracy--cost compromise for large-scale and strongly non-equilibrium simulations of 3C-SiC.

cond-mat.mtrl-sci↗
arXiv2026

Loss of altermagnetic order and smooth restoration of Kramers' spin degeneracy with increasing temperature in CrSb and MnTe

We describe how thermally induced spin fluctuations modify the electronic structures of two prototypical altermagnets, CrSb and MnTe, via application of the disordered local moment picture. For both materials, our self-consistent, ab initio calculations demonstrate that local magnetic moments persist on Cr and Mn atoms in their paramagnetic states, necessitating a spin-polarised description of the electronic structure even above the Néel temperature, $T_\mathrm{N}$. Moreover, Kramers' spin degeneracy, which is broken for both materials in their altermagnetic ground states, is shown to be smoothly restored - on the average - as the local moments thermally disorder. In metallic CrSb, this occurs at temperatures well below $T_\mathrm{N}$ and the signature effects of its altermagnetism are lost as the magnetic disorder induces heavy smearing of strongly dispersive electronic states around the Fermi energy. By contrast, in semiconducting MnTe, with its band gap largely unaffected by magnetic disorder, the spin degeneracy only returns at temperatures close to and above $T_\mathrm{N}$. We quantify the temperature dependence of the altermagnetic order parameter and the underlying electronic structures of both materials, with implications for their spin transport and spectroscopic properties.

cond-mat.mtrl-sci↗