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Friday 2 October

Chemical Physics

PyCC: A Reference Quantum Chemistry Python Package for Education, Validation, and Rapid Prototyping

T. Daniel Crawford, Benjamin G. Peyton, Zhe Wang et al. (+6 more)

PyCC is a Python-based quantum chemistry package that emphasizes coupled cluster and related methods. Developed over the last five years, PyCC's purpose is to provide a clear reference implementation that will serve as a validation suite for production code, a platform for rapid prototyping and testing of new methods, and an educational resource for newcomers to the field. The package covers both closed- and open-shell single-determinant references in spatial- and spin-orbital formulations for the coupled cluster hierarchy through triples-including methods such as CC3, as well as for MP2 and CI methods. PyCC provides a broad range of molecular properties such as analytic first and second energy derivatives including gradients, Hessians, polarizabilities and atomic polar tensors, as well as non-energy-derivative properties, such as velocity-gauge atomic polar tensors and diagonal Born-Oppenheimer corrections, plus dynamic linear response functions, and excitation energies. The package includes a number of unique capabilities, such as real-time CC propagation (up through CC3), atomic axial tensors for simulating vibrational circular dichroism spectra at the MP2 and CI levels, and local correlation methods including perturbation-aware correlation domains. The code is designed around a shared Wavefunction base and a method-agnostic derivative layer that enables a new method to inherit the full property set once it supplies its reduced densities and their first-order responses. PyCC is fully open source and available on GitHub under the BSD 3-clause license.
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All authors T. Daniel Crawford, Benjamin G. Peyton, Zhe Wang, Aparna Krishnan, Brendan M. Shumberger, Jose Madriaga, Joshua Atta-Kumi, Aaron De Clercq, Ritvik Prabhu

Chemical Physics · Cross-listed from physics.atom-ph

Electrical and optical dipole polarizabilities of two lowest triplet states of the beryllium atom

Tymoteusz Mrozek and Krzysztof Strasburger

High-accuracy static and dynamic polarizabilities of the $2^3P_u$ and $^{3}S_{g}$ states of the neutral beryllium atom are reported. The calculations employed explicitly correlated Gaussian (ECG) basis sets, and first-order wave functions were obtained by minimization of the Hylleraas functional. The final basis sets used for the response-property calculations contained c.a. 7000-8000 functions, depending on the polarizability component and the chosen symmetry. The results cover frequencies from the static limit, \(\omega = 0\), up to the third resonance for the \(2^{3}P_{u}\) state and up to the second resonance for the \(3^{3}S_{g}\) state. To the best of our knowledge, these are the first calculations of dynamic and static polarizabilities for these excited states of the beryllium atom using explicitly correlated basis sets.
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Chemical Physics · Cross-listed from cond-mat.mtrl-sci

Space Charge Layer and Facile Halide Rearrangement Enable Fast Lithium-Ion Transport at Halide Solid Electrolyte Interfaces

Md Salman Rabbi Limon, Matthew Beltran, Boyu Wang et al. (+2 more)

Halide solid electrolytes are promising candidates for energy-dense all-solid-state batteries because they combine high-voltage stability, facile processing, and fast Li-ion conduction. A recent study showed that physically mixing two halide solid electrolytes, Li$_2$ZrCl$_6$ (LZC) and Li$_3$YCl$_6$ (LYC), raises the Li-ion conductivity by 46% and 58% relative to LZC and LYC, respectively, suggesting that halide heterointerfaces offer a new route to faster ion transport; however, the origin of this enhancement remains unknown. Here, we combine density functional theory calculations, defect thermodynamics, machine-learning-driven molecular dynamics, and vibrational and Raman spectroscopy to elucidate Li-ion transport in LZC, LYC, and their heterointerface. Using low-energy ordered supercells that represent the configurational disorder of these halides, we find that Li and Cl interstitials are the dominant charged defects in both materials. Forming an LZC|LYC interface favors the generation of interfacial Li Frenkel pairs, producing Li interstitials in LZC and Li vacancies in LYC, thereby increasing the charge-carrier concentration near the interface. By analyzing the angular orientations of Cl around the metal cations in molecular dynamics trajectories of a coherent interface, we show that the interface creates new stable Cl configurations that accommodate the framework rearrangement accompanying Li hops. Simulated vibrational power spectra and measured Raman spectra indicate lattice softening and octahedral distortion at the interface, consistent with the formation of these Cl configurations. These results support a cooperative mechanism in which space charge layer formation and a dynamically flexible interfacial halide framework enhance Li-ion conduction, providing atomistic design principles for superionic halide heterostructures and multicomponent solid electrolytes.
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All authors Md Salman Rabbi Limon, Matthew Beltran, Boyu Wang, Laisuo Su, Zeeshan Ahmad

Chemical Physics · Cross-listed from cond-mat.soft

Surface Charge–Potential Relation for Spherical Particles in Electrolyte Solutions

Olga I. Vinogradova and Elena F. Silkina

Predicting the relationship between surface charge density and electrostatic potential for spherical particles remains a fundamental challenge in colloid science. Because the governing non-linear Poisson–Boltzmann equation lacks a general exact analytical solution, researchers typically rely on numerical calculations or various semi-empirical approximations. In this paper, we overcome these limitations by developing a dual-asymptotic framework that provides explicit, closed-form expressions for this surface charge–potential relationship across the entire spectrum of particle curvature. For weakly curved systems, where the Debye length $\lambda_D$ is much smaller than the particle radius $R$ ($\lambda_D/R \ll 1$), a formal mathematical derivation rigorously establishes the Ohshima–Healy–White formula as an exact regular perturbation expansion. Conversely, for highly curved spheres ($R/\lambda_D \ll 1$), we employ singular perturbation analysis using the scaled particle radius as the small parameter. This approach provides a first-principles mathematical justification for the spherical Debye–Hückel theory, proving that its leading-order expansion remains asymptotically exact within the full non-linear Poisson–Boltzmann framework due to the geometric deactivation of non-linearity. Crucially, we map the exact limits of this geometric regulation, demonstrating how non-linear screening re-emerges as the particle radius increases, with the breakdown threshold governed by the interplay between curvature and surface charge density.
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Chemical Physics

CIS(2): a state-specific, size-intensive perturbative correction to configuration interaction singles

Takashi Tsuchimochi

We present a state-specific second-order perturbation theory based on a configuration interaction singles (CIS) reference and its generalized Fock operator. Starting from a fully internally contracted construction, we retain the complete doubles space and internally contracted triples in the first-order wave function. We consider two partitions, Canonical and Block-diagonal, with reference excitation energies given by the Fock excitation gap $\omega^{(0)}$ and the CIS excitation energy $\omega_{\rm CIS}$, respectively. Our analysis establishes that strict size-intensivity is preserved when the contracted-triples denominators use bare Fock gaps and the occupied–virtual Fock block is projected to remove residual spectator coupling. Based on this observation, combining Canonical triples with Block-diagonal doubles yields a size-intensive Hybrid partition. These properties are verified for water with non-interacting helium atoms. Our formulation enables $O(o^3v^2)$ cost per matrix–vector product in a semicanonical basis. On the QUEST\#1 benchmark, Canonical and Block-diagonal show opposite systematic biases, whereas Hybrid gives the best overall accuracy among the three partitions. Its mean absolute errors for singlets and triplets are 0.24 and 0.15~eV, compared with 0.28 and 0.22~eV for CIS(D). The improvement is largest for Rydberg excitations, although CIS(D) remains more accurate for valence singlets.
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Chemical Physics

Uniform instanton theory for bridge-mediated nonadiabatic tunneling

Imaad M. Ansari, George Trenins and Jeremy O. Richardson

Instanton theory provides a semiclassical approximation to nonadiabatic rate constants within a path-integral framework and captures nuclear quantum effects such as tunneling and zero-point energy. Although the simplest reactions proceed directly from reactants to products, a number of important nonadiabatic processes involve three electronic states and react via a concerted mechanism through a virtual bridge state, also referred to as bridge-mediated tunneling or superexchange. In previous work, we have derived an instanton theory to describe such reactions using a dominant tunneling trajectory that propagates on each of the three potential energy surfaces. However, this approach is only valid when the bridge state is sufficiently low in energy. In contrast, in the high-bridge regime, the trajectories on the bridge surface become infinitesimally short, which causes the previous theory to break down. In this work, we derive the appropriate asymptotic approximation for the high-bridge regime and find that the resulting theory reduces to a two-state golden-rule instanton with an effective coupling that describes a nonresonant hop to the virtual bridge state. We further develop a uniform asymptotic instanton theory that eliminates divergences and smoothly connects the high- and low-bridge regimes. In a companion paper, we apply the method to study the quintet-to-singlet transition (via a triplet bridge) of an iron(II) complex.
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Chemical Physics

Electronic Density versus Geometry for Machine-Learned Molecular Absorption Spectra

Siddharth Dhanpal, Peter Elliott, Paolo Emilio Trevisanutto et al. (+2 more)

Molecular optical absorption spectroscopy provides a direct probe of electronic structure and is widely used for molecular identification, interpretation of photophysical behaviour, and planning of spectroscopy experiments. Calculating the absorption spectra using first-principle excited-state methods, however, is computationally demanding, at least compared to ground-state calculations, which limits their routine application across large molecular sets. Machine-learning (ML) surrogates can reduce this cost and allow rapid spectral prediction. However, their performance depends strongly on how molecular information is represented. Here, we compare using the ground-state electron density versus the molecular geometry as inputs to a ML model for predicting absorption spectra, for a training set of 6874 molecules selected from the QM7 dataset. For each of these molecules, the density was calculated using density functional theory (DFT) and the absorption spectrum was calculated using linear-response (LR) time-dependent DFT (TDDFT). Utilizing the ground-state density as the input to the ML model is motivated by the Hohenberg-Kohn and Runge-Gross theorems, and the fact that the ground-state density encodes information about bonding, charge localisation, and electronic delocalisation. Hence, it may be a more judicious starting point for the ML model compared to the geometry, as it effectively decouples the chemistry of the ground-state. The question we test is whether the benefits of using the density outweigh the (notprohibitive) penalty of requiring an additional single-point DFT calculation for the density. We find that the density-based convolutional neural network achieves a validation correlation of 0.9926, compared with 0.9795 for the best geometry-based graph model, reducing the residual decorrelation, by approximately 64%.
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All authors Siddharth Dhanpal, Peter Elliott, Paolo Emilio Trevisanutto, Alin M. Elena, Gilberto Teobaldi

Chemical Physics

Bogoliubov self-consistent $GW$ and second-order Green's function methods for attractive fermionic interactions

Mauricio Rodríguez-Mayorga, Johannes Tölle and Pierre-François Loos

Describing fermionic systems with attractive interactions, such as superconductors and atomic nuclei, beyond the mean-field level remains a central challenge. In this work, we investigate the performance of Bogoliubov fully self-consistent $GW$ (Bog.~sc$GW$) and second-order Green's function (Bog.~scGF2) methods, implemented within a unified imaginary-time and imaginary-frequency framework. Using the attractive Hubbard model as a benchmark against full configuration interaction (FCI), we find that Bog. scGF2 provides a more accurate description than Bog.~sc$GW$. In particular, Bog.~sc$GW$ systematically overestimates the correlation energy, with errors increasing rapidly as the attractive interaction strength grows. These results highlight the importance of exchange contributions in strongly correlated fermionic systems, even when exchange effects are included only at low order in perturbation theory.
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Chemical Physics · Cross-listed from quant-ph

Pathway-resolved analysis of internal conversion enabled by Gaussian boson sampling

Mikhail Roiz, Rashid Valiev, Jan-Lucas Eickmann et al. (+4 more)

Gaussian Boson Sampling (GBS) has provided strong evidence of quantum advantage, motivating the search for real-world applications. Such applications rely on mapping physical problems to the native GBS output: photon-number patterns sampled from a highly non-trivial probability distribution. Here we derive a GBS-compatible mapping for the rate constant $k_\mathrm{IC}$ of internal conversion (IC), incorporating two important physical effects – Duschinsky rotations and Herzberg–Teller contribution. We validate this framework using sampling simulations of dibenzoterrylene, reproducing reported values of $k_\mathrm{IC}$. Beyond $k_\mathrm{IC}$ reconstruction, we show that the photon-number patterns of GBS encode the vibrational mode combinations responsible for the IC process, which we refer to as non-radiative pathways. This pathway-resolved data can then be grouped in different ways to extract multiple physically motivated observables. In particular, it enables $k_\mathrm{IC}$ analysis at several levels, from individual modes and mode family contributions to recurring vibrational configurations shared by multiple pathways. We find that Duschinsky rotations increase the fraction of $k_\mathrm{IC}$ associated with correlated vibrational pathways from 46% to 86%, and identify the mode combinations with the largest rate contributions. These pathway-resolved insights can guide targeted molecular modifications, including selective deuteration and bond substitution, to control non-radiative decay.
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All authors Mikhail Roiz, Rashid Valiev, Jan-Lucas Eickmann, Theo Kurten, Benjamin Brecht, Michael Stefszky, Christine Silberhorn

Chemical Physics

Explainable Molecular Structure Inference from GC–MS with Diffusion Models and LLM Reranking

Changlin Liu, Tianyu Yi, Chengchun Liu et al. (+2 more)

GC–EI–MS is an important technique for analyzing volatile and semivolatile compounds in complex samples. However, conventional methods rely heavily on reference spectral library matching, limiting their ability to identify compounds absent from these libraries and to infer complete molecular structures directly from fragmentation information. Here, we present DiffGCMS, a spectrum-conditioned discrete graph diffusion model for de novo structure elucidation from GC–EI–MS, and further develop a framework that integrates DiffGCMS with second-stage reasoning by a large language model (LLM). In the first stage, DiffGCMS generates candidate molecular structures from input spectra; in the second stage, the LLM uses mass spectral information to validate, repair, and rerank the candidates and provides interpretable analysis of fragment-ion peaks. This framework can generate plausible molecular structures for compounds absent from reference spectral libraries and provide traceable evidence supporting its decisions. On a test set comprising 13,696 spectra from NIST 20, the generative model achieved Acc@1 and Acc@10 of 6.01% and 15.76%, respectively. On the test subset containing molecules with no more than 10 heavy atoms, LLM-assisted molecular graph repair and reranking increased Acc@1 from 21.28% to 21.95%, Acc@10 from 46.91% to 47.99%, and candidate validity from 91.04% to 100%. These results demonstrate that spectrum-aware postprocessing can correct errors produced by the generative model while providing auditable and traceable explanations for the final ranking.
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All authors Changlin Liu, Tianyu Yi, Chengchun Liu, Boxuan Zhao, Fanyang Mo

Chemical Physics · Cross-listed from quant-ph

Quasiparticle quantum simulation of materials with the Bethe-Salpeter equation

Jielun Chen, Jiace Sun and Garnet Kin-Lic Chan

The first-principles quantum simulation of the full electronic Hamiltonian of a material model of realistic size appears daunting even in a future era of fully fault-tolerant quantum computers. In contrast, classical simulations of material excited states rely on heuristic quasiparticle frameworks, such as the GW approximation and Bethe-Salpeter equation, where only a few quasiparticles are explicitly considered. Here we give a detailed description of quasiparticle quantum simulation for multi-excitonic states within the BSE. We develop an explicit first-quantized, orbital-based block encoding of the multi-exciton BSE Hamiltonian for qubitization, and reduce its cost using integral factorization and crystal symmetries. For a materials model of size $N$, and a fixed number of quasiparticles, the resulting algorithms require $\widetilde{O}(N)$ Toffoli gates and $O(\log N)$ logical qubits, or, using space-time tradeoffs, $\widetilde{O}(\sqrt{N})$ Toffoli gates and $\widetilde{O}(\sqrt{N})$ logical qubits, achieving up to a sixth power reduction in Toffoli count, or up to exponential reduction in qubit count, versus standard full Hamiltonian simulation techniques that have been explored in materials simulation. Resource estimates for the classically challenging problem of triexcitonic eigenvalue estimation across a range of semiconductor models of a realistic physical size of $O(10^3)$ atoms, show that our Toffoli-optimized implementation reduces the Toffoli count by $10^6-10^7$ relative to full Hamiltonian simulation estimates, while a qubit-optimized implementation requires only a few hundred logical qubits. More broadly, these results show that classical heuristic frameworks will be essential in the design of future fault-tolerant quantum algorithms for materials.
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Chemical Physics

Preparation sequence controls oxygen partitioning between boron and lithium on tungsten

Predrag S Krstic, Meral Sharkass, Swarit Dwivedi et al. (+3 more)

Classical reactive molecular dynamics of boron- and lithium-conditioned tungsten surfaces show that the order in which boron and oxygen are introduced - not the boron inventory - controls surface chemistry. On a thin engineered tungsten oxide, boron captures 81% of oxygen and consumes the oxide; on an engineered ~2 nm mixed WO3/WO2 film, boron captures only 20% and leaves 52% of reaction-zone tungsten in WO3-like coordination; and in a co-deposited W-B substrate later exposed to oxygen, boron captures only 28% despite a tenfold larger inventory. Adding lithium leaves the oxide-first cases unchanged but transforms the co-deposited case, where lithium becomes the dominant oxygen captor (58%) and a lithium-borate-glass-like network form. We outline the expected, divergent responses of the boron-only and boron-plus-lithium materials to deuterium irradiation.
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All authors Predrag S Krstic, Meral Sharkass, Swarit Dwivedi, Dalia Sayed Ahmed, Yun Kyung Shin, Adri CT van Duin

Chemical Physics · Cross-listed from quant-ph

Correlated memory effect of environment in radical-pair magnetoreception

Shixuan Chen, Yao Wang, Rui-Xue Xu et al. (+1 more)

In the photoreceptor compass model, a light-generated, spin-correlated radical pair undergoes singlet-triplet interconversion driven by Zeeman and anisotropic hyperfine interactions, leading to orientation-dependent reaction yields. In this study, we consider simultaneously the spin environment and the boson environment surrounding the radical-pair system and concentrate on the correlated memory effect of the spin bath. In the linear-response limit, the spin bath is mapped to an effective Gaussian environment. The system dynamics and yields under its influence together with the bosonic bath are propagated uniformly using the hierarchical equations of motion (HEOM) or equivalently the dissipaton equations of motion (DEOM) method. The HEOM/DEOM is non-Markovian and non-perturbative, exact for Gaussian environments. Corresponding results of the Markovian Lindblad master equation are also shown for comparison. Numerical demonstrations highlight the non-Markovian memory effect as a crucial ingredient for radical-pair magnetoreception.
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All authors Shixuan Chen, Yao Wang, Rui-Xue Xu, YiJing Yan

Chemical Physics

Equivariant Flow Matching for Electron Density Prediction

Chenxing Liang, Chengdong Wang, Yuchao Lin et al. (+2 more)

Machine learning surrogates for density functional theory (DFT) have been increasingly used to reduce the cost of first-principles calculations. In this arena, predicting real-space electron densities offers a scalable and transferable initialization for self-consistent field (SCF) procedures. However, current methods face a clear dilemma. That is, grid-based architectures incur a high computational cost, while basis-set methods fail to capture the structural correlations inherent in the coefficient space. Here, we develop OrbFlow, an $\mathrm{SE}(3)$-equivariant generative model that predicts Gaussian-type orbital (GTO) coefficients via flow matching. OrbFlow retains the efficiency of a compact atom-centered basis while replacing pointwise regression with a learned probability path over the full coefficient space. It is trained through a two-phase trajectory curriculum that mitigates discretization drift during numerical integration. OrbFlow achieves state-of-the-art accuracy on QM9, reducing density error by 13.6% relative to the previous best model, and reduces error by 51% to 63% on every molecule of the MD benchmark relative to the strongest prior method sharing its basis. The predicted density also cuts SCF iterations by up to 68% with zero-shot transfer to unseen exchange-correlation functionals and recovers dipole and quadrupole moments to within a few percent of DFT references without any SCF calculation.
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All authors Chenxing Liang, Chengdong Wang, Yuchao Lin, Xiaofeng Qian, Shuiwang Ji

Thursday 1 October

Chemical Physics · Cross-listed from physics.geo-ph

Quantum spin regulates the catalytic cycle beyond binding energy

K. Regenauer-Lieb, W. Li, Z. Xia et al. (+7 more)

Conventional catalytic descriptors evaluate symmetric, dissipative responses ($\mathcal{D}$), remaining blind to the antisymmetric, non-dissipative circulation ($\mathcal{L}$) associated with cyclic catalyst turnover. We address this by applying an augmented Onsager operator, $\mathcal{A} = \mathcal{D} + \mathcal{L}$, to catalytic interfaces. Through Onsager–Casimir parity rules, we show that electron spin governs this non-dissipative circulation within the reduced state space, as antisymmetric coupling necessitates a time-reversal-odd coordinate. We map these multi-physical couplings (Thermo-Hydro-Mechanical-Chemical-Electrical-Spin) using a Hasse diagram and introduce a basis-invariant Gateway number to quantify circulation relative to dissipation, thereby expanding standard one-dimensional volcano plots into a two-dimensional activity surface. Using metal–nitrogen single-atom sites on doped carbon as a model, published electronic-structure calculations supply the static response quantities from which both operator components can be constructed. Finally, we propose an explicitly falsifiable experimental test utilising magnetic field modulation near a spin-crossover to probe the effect of quantum spin on this non-dissipative regime.
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All authors K. Regenauer-Lieb, W. Li, Z. Xia, Y. Jiao, Y. Liu, Y. Chen, Q. Xie, Q. P. Sun, B. Hamblin, V. Calo

Chemical Physics · Cross-listed from cs.LG

DISSOLVR: An Interpretable and Fast Framework for Aqueous and Organic Solubility Prediction

Vansh Ramani, Har Ashish Arora, Dhairya Kuchhal et al. (+2 more)

High-fidelity solubility prediction is fundamental to pharmaceutical development and environmental partitioning, where accurate modeling must couple molecular structure with thermodynamic behavior across diverse chemical environments. However, recent advancements have been dominated by deep learning architectures that often sacrifice physical interpretability for predictive power. We challenge this trend by showing that state-of-the-art performance does not require such non-transparent architectures. To address this, we introduce DISSOLVR, a transparent framework for molecular solubility prediction. In addition, we perform a comprehensive literature review and a benchmarking study against various methods. We show that DISSOLVR approaches the aleatoric limit of experimental uncertainty and achieves OOD generalization through structural invariance, derived by mapping molecules to physically-grounded descriptors. Then, we present an LLM-assisted post-hoc explanation pipeline that bridges the gap between symbolic model artifacts and chemically grounded narratives. Finally, a comparative benchmark of a survey involving 22 expert chemists reveals that expert evaluators provide deep insights.
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All authors Vansh Ramani, Har Ashish Arora, Dhairya Kuchhal, Sayan Ranu, Tarak Karmakar

Chemical Physics

libterachem.py: Modular development of electronic structure methods with graphical processing units

Juncheng Harry Zhang, Ruiyan Wang, Andreas Erbs Hillers-Bendtsen et al. (+1 more)

We present libterachem.py, a Python interface and method framework that facilitates development and prototyping of electronic structure methods while leveraging TeraChem's optimized graphical processing unit (GPU) operations. Direct access to these building blocks and their intermediate quantities allows users to assemble and modify methods within Python while reusing the underlying GPU implementations. A layered architecture, programmable at both the operation level and the method level, supports numerical experimentation, composition of complete electronic structure methods with interchangeable components, and integration with external scientific libraries. We illustrate operation-level use with grid pruning for least-squares tensor hypercontraction and with exchange–correlation functionals supplied through LibXC and by the machine-learned Skala functional. We illustrate method-level use with dispersion corrections, periodic calculations, and geometry optimization with an external optimizer. Python-driven self-consistent-field calculations using libterachem.py incur no significant computational overhead compared to native TeraChem and preserve its multi-GPU scaling. A photoactive yellow protein QM/MM molecular dynamics application further demonstrates throughput comparable to native TeraChem in a workflow composed with external simulation libraries. These results establish libterachem.py as a platform for method development and interoperable molecular simulation that retains the performance of TeraChem's GPU operations.
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All authors Juncheng Harry Zhang, Ruiyan Wang, Andreas Erbs Hillers-Bendtsen, Todd J. Martínez

Chemical Physics · Cross-listed from quant-ph

Polynomial-time classical and quantum simulation of quantum impurity models

Jiaqing Jiang, Nathan Ju, Ojas Parekh et al. (+2 more)

Quantum impurity models are paradigmatic models of interacting quantum matter, as well as key computational primitives for modern electronic-structure methods. They describe a small subsystem of interacting fermions coupled to a large, noninteracting bath. We perform a comprehensive study of the computational complexity of simulating impurity models, delineating the boundary between classical and quantum tractability for this class of problems. Our main finding is that static properties of quantum impurity models can be calculated efficiently on a classical computer. Specifically, we give classical algorithms that (1) estimate the ground-state energy to additive precision $\delta$ in time $\mathrm{poly}(n,\delta^{-1})$, and (2) estimate the partition function at inverse temperature $\beta$ to relative precision $\delta$ in time $\mathrm{poly}(n,\beta,\delta^{-1})$, where $n$ is the system size. These results improve the previous best-known complexity for ground-state energy estimation from quasipolynomial to polynomial time, while establishing for the first time rigorous polynomial-time guarantees for simulating impurity models in thermal equilibrium. On the other hand, we find that simulating dynamical properties of impurity models is hard for classical computers but easy on a quantum computer. As a canonical example, we show that computing their nonequilibrium Green's functions captures the full power of quantum computation, even at finite temperature. Taken together, our results rule out superpolynomial quantum speedups for computing static properties, but provide an avenue for quantum advantage in simulating impurity physics out of equilibrium.
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All authors Jiaqing Jiang, Nathan Ju, Ojas Parekh, Chaithanya Rayudu, Andrew Zhao

Chemical Physics · Cross-listed from cs.LG

BranchIP: Learning Adaptive Equivariant Computation for Interatomic Potentials

Laura Zichi, Gil Harari, Chuin Wei Tan et al. (+6 more)

Equivariant machine learning interatomic potentials (MLIPs) have revolutionized atomistic modeling, but accurate treatment of complex materials and molecular systems demands expensive models. This limits simulation length- and time-scales, with tensor products a key computational bottleneck. The recent emergence of foundation-scale MLIPs further exacerbates this challenge. We present Branch Interatomic Potential (BranchIP), a single-model framework for learned adaptive tensor product computation, trained with a novel distillation loss. In our experiments on two systems of physical interest, a heterogeneous catalysis system and a proton-conducting solid acid electrolyte, BranchIP accelerates MLIPs across model sizes by up to $2.4\times$ while reducing memory usage by up to $2.6\times$. This is achieved while maintaining physical fidelity. Furthermore, the learned adaptive computation provides model interpretability by revealing which interactions demand deeper computation and showing how computational depth relates to chemical complexity and dynamics.
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All authors Laura Zichi, Gil Harari, Chuin Wei Tan, Marc L. Descoteaux, Albert Zhu, Menghang Wang, Yoel Zimmermann, H.T. Kung, Boris Kozinsky

Chemical Physics · Cross-listed from quant-ph

Hardware-Efficient Ground-State Preparation using Variational Imaginary-Time Majorana Evolution

Federico Santona, Manuel G. Algaba, Aeishah Ameera Anuar et al. (+3 more)

Compact ground-state preparation circuits are essential for early fault-tolerant quantum chemistry. We introduce Variational Imaginary-time Majorana Evolution (VIME), a classical pre-training algorithm that extends operator-projected variational quantum imaginary-time evolution (OVQITE) to molecular electronic structure using a single compiled Majorana-propagation (MP) surrogate graph. We pair VIME with a compressed tiled Unitary Product State (c-tUPS) ansatz that we develop to reduce both classical simulation and quantum state-preparation costs. In the strongly correlated ruthenium complex TLD-1411, active-space calculations requiring up to 52 qubits achieve chemical precision against DMRG reference energies, with energy errors approximately $400\times$ smaller than those from ADAPT-VQE-based variational Majorana-propagation (ADAPT-VMPE). Across the strongly multireference acene series up to heptacene (60 qubits), VIME matches or improves on the MP-reported energy accuracy of the ADAPT-VMPE comparison points with up to $26\times$ fewer CNOTs and $167\times$ lower two-qubit depth. These results establish imaginary-time classical pre-training of compressed variational ansätze as a promising route to resource-efficient molecular ground-state preparation.
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All authors Federico Santona, Manuel G. Algaba, Aeishah Ameera Anuar, Anna M. Wernbacher, Prachi Sharma, Fedor Šimkovic IV

Chemical Physics · Cross-listed from cond-mat.mes-hall

Symmetry considerations in chirality-induced spin selectivity

Dmitry Budker and Angela Wittmann

The chirality-induced spin selectivity (CISS) effect, the coupling between structural chirality and electron spin polarization, has been experimentally observed across many diverse systems. However, despite extensive theoretical effort, a unified mechanistic understanding remains elusive. In this perspective, we demonstrate how some of the basic properties of the fascinating effects of CISS can be understood based on straightforward symmetry considerations commonly employed in fundamental particle physics. In particular, we show that CISS does not violate any fundamental symmetries including parity and time-reversal. By anchoring CISS within the universal language of symmetry, we offer a robust conceptual foundation for interpreting experiments and guiding future theoretical and experimental designs.
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Chemical Physics

Nonadiabatic Quantum Dynamics of Hexatriene via the Extended Hubbard-Peierls Model and Time-Dependent DMRG

Timothy N. Georges, Darren J. Valentine and William Barford

Propagating the electronic and nuclear degrees of freedom of a molecule simultaneously is a challenging task, because the number of vibronic states grows exponentially with system size. We use the adaptive time-dependent density matrix renormalization group to perform simulations of the extended Hubbard-Peierls Hamiltonian, in which both the electronic and nuclear degrees of freedom are quantized. We describe our approach, and demonstrate it through converged calculations of the nonadiabatic dynamics of hexatriene. This simulation predicts a lifetime of the `bright' $\mathrm{1B_u}$ electronic state of approximately 40 fs. Our predictions for the population of the $\mathrm{1B_u}$ electronic state are in qualitative agreement with those obtained using the linear vibronic coupling model derived from the extended Hubbard-Peierls Hamiltonian in previous work.
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Chemical Physics

PyCDFT: A Python-scriptable library for analytical evaluation of orbital conceptual density (matrix) functional theory

Bin Wang, Paul Geerlings, Paul W. Ayers et al. (+1 more)

Conceptual density functional theory (CDFT) defines chemical reactivity descriptors as derivatives of the electronic energy with respect to the number of electrons and the external potential, or combinations thereof; in practice, however, researchers almost always replace these derivatives with finite-difference and frontier-orbital approximations, and no common software exists for their analytical evaluation. We present PyCDFT, to our knowledge, the first standardized, open-source, and scriptable code that analytically computes the descriptors of conceptual density (matrix) functional theory for ground and excited states up to second order, including the orbital hardness, the Fukui function and Fukui matrix, and the linear response function, from a single converged mean-field wavefunction imported from virtually any electronic-structure package. The descriptors are obtained from matrix-free, preconditioned Krylov-subspace solutions of the coupled-perturbed self-consistent-field equations for both spin-unpolarized and spin-polarized references, with the work distributed over MPI ranks and all data flowing through a single HDF5 checkpoint file that supports restart, post-processing, and the export of real-space descriptors as cube files for visualization. The design delegates integrals, grids, and exchange-correlation kernels to PySCF and Libxc, keeping the library compact, user-friendly, and interoperable. Worked examples on the ground state of H$_2$O and a broken-symmetry $\Delta$SCF excited state of NH$_3$ show that a complete second-order CDFT analysis requires only a few lines of user code.
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All authors Bin Wang, Paul Geerlings, Paul W. Ayers, Frank De Proft

Chemical Physics

State-selective molecular orientation by vibrational Autler-Townes adiabatic passage

Meng-Yi Yu, Ya-Nan Lv, Cun-Feng Cheng et al. (+1 more)

Control of molecular angular momentum orientation enables state-resolved studies of molecular interactions and provides a basis for quantum information processing. Here we propose all-optical Autler-Townes state-selective adiabatic passage (ASAP) to prepare molecules in a single $|J,M\rangle$ sublevel. An Autler-Townes branch created by a strong coupling field is selectively populated and adiabatically mapped onto the target vibrational state. We resolve detuning-dependent rovibrational Autler-Townes splitting in $^{13}$CO$_2$, establishing the spectroscopic basis for the selective excitation of the target dressed branch. The density-matrix model calibrated by these spectra predicts transfer approaching 90%. The scheme can exploit millisecond vibrational radiative lifetimes within the electronic ground state and extend to polar and nonpolar molecules with infrared-active vibrational modes.
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All authors Meng-Yi Yu, Ya-Nan Lv, Cun-Feng Cheng, Shui-Ming Hu

Chemical Physics

Relativistic Hirshfeld atoms in a molecule: An information-theoretic view, with application to Drude oscillator dispersion models

Keegan Paice and John M. Herbert

Several ad hoc dispersion models for density-functional theory are based on the use of Hirshfeld (or "stockholder") partition of a molecular charge density, which provides an in situ definition of atomic size. We show that a recently introduced "optimized" quantum Drude oscillator model for dispersion admits a closed-form solution in terms of the Lambert $W$ function, whose branches identify the compact and diffuse oscillator solutions. The compact solution determines the $C_8$ (dipole-quadrupole) dispersion coefficient analytically from the free-atom polarizability, $C_6$ coefficient, and van der Waals radius, without any reference $C_8$ data. Next, we provide a formal basis for a relativistic version of the atoms-in-molecule Hirshfeld partition. Using four-component Dirac-Hartree-Fock densities for isolated atoms defines a strictly positive deformation field that carries the relativistic changes in atomic density into the Hirshfeld partition. A uniqueness theorem for the non-relativistic case is extended to relativistic Hirshfeld atoms and admits an asymptotic expansion through quadratic order in the fine-structure constant. Normalization requires the relativistic density correction to reshape the reference atom while preserving its population. Finally, four-component polarizabilities and C6 coefficients are reported for closed-shell atoms and ions, which supply the reference data required to extend atoms-in-molecules dispersion models into the heavy-element regime. Periodic trends are observable in a scalar contraction factor that measures relativistic effects.
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Chemical Physics

Numerical integration of intracule pair densities with optimized multicenter grids

Markel Ylla, Jesus M. Ugalde, Eduard Matito et al. (+1 more)

Intracule pair densities provide insight into electron correlation, but their routine analysis in extended systems is limited by the cost of numerical integration and the restriction of analytical methods to Gaussian basis functions. We present an efficient multicenter integration scheme for intracule densities and their moments. By adapting the topological fuzzy Voronoi cell formalism, we partition intracule space around interatomic displacement vectors, concentrating quadrature points near secondary density maxima that standard single-center grids poorly resolve. Benchmarks on linear alkanes show improved convergence with increasing molecular size, achieving relative errors below 0.02% in electron-electron repulsion energies with fewer quadrature points than single-center methods. The partitioning also enables the decomposition of global two-electron properties into spatial contributions associated with short- and long-range electron-pair separations. Coupling the multicenter grid with kernel density estimation reconstructs smooth radial intracule distributions at large interelectronic distances without the dense angular grids required by conventional surface integration. Validation on the S22 dataset supports the reliability of the method across diverse molecular systems. These developments facilitate intracule analysis in polyatomic systems and the investigation of electron correlation and dispersion interactions.
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All authors Markel Ylla, Jesus M. Ugalde, Eduard Matito, Eloy Ramos-Cordoba

Chemical Physics · Cross-listed from quant-ph

Molecular Dynamics with Nuclear Effects on Quantum Computers

Lukas Haßfurth, Juliane Heitkämper, Elias Walter et al. (+1 more)

Nuclear quantum effects are critical for describing proton transfer and hydrogen bonding, but their incorporation into quantum chemistry calculations is often computationally prohibitive on classical hardware. A promising alternative are quantum computers due to their linear scaling in the space requirements with system size. We introduce a novel hybrid quantum-classical algorithm for ab-initio molecular dynamics that incorporates nuclear quantum effects via the nuclear-electronic orbital method. The proposed algorithm evaluates ground state energies and forces on the quantum computer using a variational quantum eigensolver, while the molecular geometries are updated classically. We validate our approach through simulations of $\text{H}_2$, $\text{H}_2\text{O}$ and the Zundel ion $\text{H}_5\text{O}_2^+$, comparing the simulated vibrational spectra with experimental data. Upon inclusion of nuclear quantum effects, the proton shuttling movement in the Zundel ion becomes effectively barrierless, and errors in the simulated frequencies improve significantly. Employing compact hardware-efficient ansatz circuits we achieve results comparable to the more accurate UCCSD ansatzes, which hints towards the feasibility of executing our algorithm on near-term quantum devices.
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All authors Lukas Haßfurth, Juliane Heitkämper, Elias Walter, Birger Horstmann

Chemical Physics

Deciphering the internal conversion and triplet formation in thymine via time-resolved multi-center X-ray photoelectron spectroscopy

Xiaojun Wang, Woojin Park, Dennis Mayer et al. (+12 more)

The photostability of DNA nucleobases relies on ultrafast nonradiative relaxation following ultraviolet excitation. In thymine, the competition between internal conversion (IC) and intersystem crossing (ISC) determines the balance between ultrafast energy dissipation and potentially long-lived photochemistry. However, the precise molecular mechanisms linking early singlet-state electronic and structural evolution to the formation of long-lived triplet dark states remain unresolved. Here, we investigate the gas-phase photodynamics of thymine using time-resolved multi-center X-ray photoelectron spectroscopy (tr-mc-XPS) supported by state-of-the-art ab initio quantum calculations. By simultaneously probing multiple carbon 1s core levels, we track site-specific electronic and nuclear dynamics. We discover that the long-lived dark state is not initially a pure triplet; rather, it exists as a mixture of singlet and triplet states for the first 240 ps before transitioning fully to the $^3\pi\pi^*$ state. On the femtosecond timescale, we resolve atom-specific vibrational coherence at $\sim$730 cm$^{-1}$ (a ring-breathing mode with a period of 46 fs) that survives the initial $^1\pi\pi^*$ to $^1n\pi^*$ IC. Furthermore, we identify a critical dual role for the methyl group (C9H$_3$). During singlet relaxation, the methyl group acts as an inertia spectator, and its mass hinders direct internal conversion to the ground state. Upon $^3\pi\pi^*$ state formation, however, state-dependent hyperconjugation couples the methyl group to the pyrimidine ring, turning it into a highly sensitive electronic reporter of ISC. These findings establish tr-mc-XPS as a powerful approach for disentangling the complex, multi-timescale photodynamics governing nucleobase stability.
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All authors Xiaojun Wang, Woojin Park, Dennis Mayer, Fabiano Lever, Giovanni Cirmi, Michele Di Fraia, Benjamin Erk, Marion Kuhlmann, Zane Phelps, Oksana Plekan, Federico Pressacco, Sebastian Schulz, Cheol Ho Choi, Miquel Huix-Rotllant, Markus Gühr

Chemical Physics

SupraTITO: Transferable Generative Molecular Dynamics for Supramolecular Systems

Weilong Chen, Nuno Costa and Julija Zavadlav

Peptide sequence governs both the structures formed through supramolecular assembly and the dynamics by which they emerge, but predicting either requires resolving slow collective processes among many interacting molecules. Molecular dynamics (MD) provides microscopic insight into these processes, yet the long timescales of assembly and the vast peptide sequence space make systematic exploration computationally demanding. We introduce SupraTITO, a transferable generative molecular dynamics (GenMD) framework for supramolecular systems, demonstrated through peptide self-assembly. SupraTITO learns transferable implicit transfer operators (TITO) conditioned on peptide sequence, molecular topology, and periodic geometry, allowing configurations to be propagated over physical intervals much longer than an MD integration step. On a comprehensive dipeptide benchmark, SupraTITO generalizes to held-out sequences and reproduces sequence-dependent structures and dynamics while maintaining molecular integrity over long rollouts. Compared with direct ensemble prediction trained on the same trajectory data, SupraTITO more accurately reproduces assembly structures while also resolving their temporal evolution. The learned dynamics generalize across peptide concentrations, including dilute conditions not represented during training. These results extend transferable GenMD to collective dynamics in periodic supramolecular systems and provide a foundation for modeling related processes beyond peptide assembly.
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Chemical Physics

Toward Long-Range Correlation Energies from Charge Fluctuations: Incorporating Exact Exchange into ACKS2$\omega$

YingXing Cheng

Long-range electronic correlation can be represented in terms of coupled fluctuations of atomic charges and higher multipoles, motivating a density-response description beyond local dipolar polarization, particularly in low-dimensional, conducting, and small-gap systems where collective electronic fluctuations become important. We extend the frequency-dependent polarizable force field ACKS2$\omega$ to electronic-structure references containing exact exchange by deriving both the static and additional frequency-dependent exchange contributions, with particular attention to HFsrPBE, which combines long-range Hartree–Fock exchange with short-range PBE exchange and correlation. Numerical validation of ACKS2$\omega$ using dipole polarizabilities and $C_6$ dispersion coefficients for the 27 molecules of the TS27 set, with HF, PBE, B3LYP, and HFsrPBE as the underlying electronic-structure references, shows that including the exchange contributions and enriching the response basis improve agreement with the corresponding orbital-space linear-response calculations, although finite-response-basis errors remain molecule dependent. Long-range correlation energies evaluated through the adiabatic-connection fluctuation-dissipation theorem using the ACKS2$\omega$ parameters reproduce the corresponding HFsrPBE orbital-space results for small test molecules when the response basis is made complete within the chosen orbital basis, while a local multipole decomposition resolves the finite-basis energies into monopole–monopole, mixed, dipole–dipole, and remaining higher-multipole contributions, providing a route to evaluating long-range correlation energies in terms of charge fluctuations within atom-condensed models.
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