Accurate Quantum Research Articles

Alchemical insights into approximately quadratic energies of iso-electronic atoms.

Accurate quantum mechanics based predictions of property trends are so important for material design and discovery that even inexpensive approximate methods are valuable. We use the alchemical integral transform to study multi-electron atoms and to gain a better understanding of the approximately quadratic behavior of energy differences between iso-electronic atoms in their nuclear charges. Based on this, we arrive at the following simple analytical estimate of energy differences between any two iso-electronic atoms, ΔE≈-(1+2γNe-1)ΔZZ̄. Here, γ ≈ 0.3766 ± 0.0020 Ha corresponds to an empirical constant, and Ne, ΔZ, and Z̄, respectively, to electron number, nuclear charge difference, and average. We compare the formula's predictive accuracy using experimental numbers and non-relativistic, numerical results obtained via density functional theory (pbe0) for the entire periodic table up to Radon. A detailed discussion of the atomic helium-series is included.

UMRSF-TDDFT: Unrestricted Mixed-Reference Spin-Flip-TDDFT.

An unrestricted version of Mixed-Reference Spin-Flip Time-Dependent Density Functional Theory (UMRSF-TDDFT) was developed based on unrestricted Kohn-Sham orbitals (UKS) with a new molecular orbital (MO) reordering scheme. Additionally, a simple yet accurate method for estimating ⟨S2⟩ expectation values was devised. UMRSF-TDDFT was benchmarked against cases where DFT, TDDFT, and SF-TDDFT traditionally fail to provide accurate descriptions. In an application to the ground and excited states of a Be atom, UMRSF-TDDFT successfully recovers the degenerate states, with its energies slightly reduced compared to its RO counterpart, due to the additional variational flexibility of UKS. A clear difference between UMRSF and U-SF-TDDFT is evident in the bond breaking of the hydrogen fluoride system, as the latter misses an important configuration. In the case of the Jahn-Teller distortion of trimethylenemethane (TMM), the relative singlet energy compared to the triplet is lower by 0.1 and 0.2 eV for UMRSF and U-SF-TDDFT, respectively, than that of MRSF-TDDFT. The reduction in UMRSF energy is attributed to spatial orbital relaxations, whereas the reduction in U-SF-TDDFT energy results from spin contamination. Overall, the additional orbital relaxations afforded by unrestricted Kohn-Sham (UKS) orbitals in UMRSF-TDDFT lead to lower total system energies compared to their restricted open-shell counterparts. This enhancement adds a practical and accurate quantum chemical theory to the existing RO variant for addressing challenging systems where traditional quantum theories suffer.

Accurate optimal quantum error correction thresholds from coherent information

Quantum error correcting (QEC) codes protect quantum information from decoherence as long as error rates fall below critical error thresholds. In general, obtaining thresholds implies simulating the QEC procedure using, in general, suboptimal decoding strategies. In a few cases and for sufficiently simple noise models, optimal decoding of QEC codes can be framed as a phase transition in disordered classical spin models. In both situations, accurate estimation of thresholds demands intensive computational resources. Here we use the coherent information of the mixed state of noisy QEC codes to accurately estimate the associated optimal QEC thresholds already from small-distance codes at moderate computational cost. We show the effectiveness and versatility of our method by applying it first to the topological surface and color code under bit-flip and depolarizing noise. We then extend the coherent information based methodology to phenomenological and quantum circuit level noise settings. For all examples considered, we obtain highly accurate estimates of optimal error thresholds from small, low-distance instances of the codes, in close agreement with threshold values reported in the literature. Our findings establish the coherent information as a reliable competitive tool for the calculation of optimal thresholds of state-of-the-art QEC codes under realistic noise models. Published by the American Physical Society 2024

Computational Mechanistic Analysis of the Formation of the Magnesium Silicate Monomers MgSiO3 and Mg2SiO4.

Silicate grains comprise a large fraction of cosmic dust, motivating a need to understand how they form. The current body of work on silicates generally reflects the abundance of silicate grains, yet models for their formation often do not consider silicate chemistry on the smallest scale, which can form species available for dust grain nucleation processes. In order to expand upon previous attempts to bridge this gap in silicate chemistry, novel gas-phase reaction pathways for the magnesium silicate monomers enstatite (MgSiO3) and forsterite (Mg2SiO4) from MgH, H2O, and SiO are presently computed using highly accurate quantum chemical calculations. MgSiO3 and Mg2SiO4 form through a series of reactions that initially excludes silicon addition, creating the elusive species MgOH and Mg2O prior to further reaction. The formation of the two silicate monomers is expected to be efficient with the primary bottleneck being the amount of MgH available for reaction. The addition of these reactions to cosmic chemical networks will add further clarity to the processes that govern dust formation, most significantly for those occurring within stellar outflows of asymptotic giant branch stars.

Optimization of Decoder Priors for Accurate Quantum Error Correction.

Accurate decoding of quantum error-correcting codes is a crucial ingredient in protecting quantum information from decoherence. It requires characterizing the error channels corrupting the logical quantum state and providing this information as a prior to the decoder. We introduce a reinforcement learning inspired method for calibrating these priors that aims to minimize the logical error rate. Our method significantly improves the decoding accuracy in repetition and surface code memory experiments executed on Google's Sycamore processor, outperforming the leading decoder-agnostic method by 16% and 3.3%, respectively. This calibration approach will serve as an important tool for maximizing the performance of both near-term and future error-corrected quantum devices.

Accurate Geometries of Large Molecules at DFT Cost by Semiexperimental and Coupled Cluster Templating Fragments.

Accurate geometries of small semirigid molecules in the gas phase are available thanks to high-resolution spectroscopy and accurate quantum chemical approaches. These results can be employed for validating cheaper low-level quantum chemical models or correcting the corresponding structures of large molecules. On these grounds, in this work, a large panel of semiexperimental equilibrium structures already available in the literature is used to confirm the average error (1 mÅ for bond lengths and 2 mrad for valence angles) of a version of the Pisa composite schemes (PCS2), which is applicable to molecules containing up to about 20 atoms. Then, the geometries of 30 additional medium-sized systems were optimized at the PCS2 level to cover a more balanced chemical space containing moieties poorly represented in SE compilations. The final database is available on a public domain Web site (https://www.skies-village.it/databases/) and can be employed for correcting structures of larger molecules obtained by hybrid or double-hybrid density functionals in the framework of the templating molecule approach. Several examples show that corrections based on the structures of building blocks taken from this database reduce the error of the B3LYP geometrical parameters of large molecules by nearly an order of magnitude without increasing the computational cost. Furthermore, the results of different density functional theory (DFT) or wave function (e.g., MP2) models can be improved in the same way by simply computing both the whole molecule and suitable building blocks at the chosen level. Then, whenever reference structures of some building blocks containing up to about 20 atoms are not available, they can be purposely optimized at the PCS2 level by employing reasonable computer resources. Therefore, a new DFT-cost tool is now available for the accurate characterization of large molecules by experiment-oriented scientists.

Accurate nuclear quantum statistics on machine-learned classical effective potentials.

The contribution of nuclear quantum effects (NQEs) to the properties of various hydrogen-bound systems, including biomolecules, is increasingly recognized. Despite the development of many acceleration techniques, the computational overhead of incorporating NQEs in complex systems is sizable, particularly at low temperatures. In this work, we leverage deep learning and multiscale coarse-graining techniques to mitigate the computational burden of path integral molecular dynamics (PIMD). In particular, we employ a machine-learned potential to accurately represent corrections to classical potentials, thereby significantly reducing the computational cost of simulating NQEs. We validate our approach using four distinct systems: Morse potential, Zundel cation, single water molecule, and bulk water. Our framework allows us to accurately compute position-dependent static properties, as demonstrated by the excellent agreement obtained between the machine-learned potential and computationally intensive PIMD calculations, even in the presence of strong NQEs. This approach opens the way to the development of transferable machine-learned potentials capable of accurately reproducing NQEs in a wide range of molecular systems.

High-fidelity remote entanglement between superconducting fixed-frequency qubits

Abstract Highly accurate quantum state transfer and remote entanglement between superconducting fixed-frequency qubits have not yet been realized. In this study, we calculate the characteristics of a transmission path with a 1- or 0.25 m superconducting coaxial cable and use the characteristics to perform time evolution simulations of quantum state transfer and remote entanglement between superconducting fixed-frequency qubits. We find that remote entanglement, or half-quantum state transfer, can achieve a high fidelity > 99 % even in the presence of a qubit frequency detuning caused by manufacturing fluctuations, while a small qubit frequency detuning substantially reduces the efficiency of quantum state transfer. Quantum circuit simulations modeling proposed remote entanglement demonstrate that teleportation of a logical qubit with a 3 × 3 surface code, as an example of computation using remote entanglement, attains nearly the same fidelity as in-node computation for both 1- and 0.25 m cable lengths.

Quantum nuclear motion in silicene: Assessing structural and vibrational properties through path-integral simulations

This paper explores the interplay between quantum nuclear motion and anharmonicity, which causes nontrivial effects on the structural and dynamical characteristics of silicene, a two-dimensional (2D) allotrope of silicon with interesting electronic and mechanical properties. Employing path-integral molecular dynamics (PIMD) simulations, we investigate the quantum delocalization of nuclei, unraveling its impact on the behavior of silicene at the atomic scale. Our study reveals that this delocalization induces significant deviations in the structural parameters of silicene, influencing in-plane surface area, bond lengths, angles, compressibility, and overall lattice dynamics. Through extensive simulations, we delve into the temperature-dependent behavior between 25 and 1200 K, unveiling the role of quantum nuclear fluctuations in dictating thermal expansion and phonon spectra. The extent of nuclear quantum effects is assessed by comparing results of PIMD simulations using an efficient tight-binding Hamiltonian, with those obtained from classical molecular dynamics simulations. The observed quantum effects showcase non-negligible deviations from classical predictions, emphasizing the need for accurate quantum treatments in understanding the material’s behavior at finite temperatures. At low T, the 2D compression modulus of silicene decreases by a 14% due to quantum nuclear motion. We compare the magnitude of quantum effects in this material with those in other related 2D crystalline solids, such as graphene and SiC monolayers.

Exploring Protonation State, Ion Binding, and Photoactivated Channel Opening of an Anion Channelrhodopsin by Molecular Simulations.

Channelrhodopsins are light-gated ion channels with a retinal chromophore found in microbes and are widely used in optogenetics, a field of neuroscience that utilizes light to regulate neuronal activity. GtACR1, an anion conducting channelrhodopsin derived from Guillardia theta, has attracted attention for its application as a neuronal silencer in optogenetics because of its high conductivity and selectivity. However, atomistic mechanisms of channel photoactivation and ion conduction have not yet been elucidated. In the present study, we investigated the molecular characteristics of GtACR1 and its photoactivation processes by molecular simulations. The QM/MM RWFE-SCF method which combines highly accurate quantum chemistry calculations with long-time molecular dynamics (MD) simulations were used to model protein structures of the wild-type and mutants with different protonation states of key groups and to calculate absorption energies for verification of the models. The QM/MM modeling together with MD simulations of free-energy calculations favors protonation of a key counterion carboxyl group of Asp234 with a strong binding of a chloride ion in the extracellular pocket in the dark state. A channel open state was also successfully modeled by the QM/MM RWFE-SCF free-energy optimizations, providing atomistic insights into the channel activation mechanism.

Structural and Electronic Evolution of Ethanolamine upon Microhydration: Insights from Hyperfine Resolved Rotational Spectroscopy

AbstractEthanolamine hydrates containing from one to seven water molecules were identified via rotational spectroscopy with the aid of accurate quantum chemical methods considering anharmonic vibrational corrections. Ethanolamine undergoes significant conformational changes upon hydration to form energetically favorable hydrogen bond networks. The final structures strongly resemble the pure (H2O)3–9 complexes reported before when replacing two water molecules by ethanolamine. The 14N nuclear quadrupole coupling constants of all the ethanolamine hydrates have been determined and show a remarkable correlation with the strength of hydrogen bonds involving the amino group. After addition of the seventh water molecule, both hydrogen atoms of the amino group actively contribute to hydrogen bond formation, reinforcing the network and introducing approximately 21–27 % ionicity towards the formation of protonated amine. These findings highlight the critical role of microhydration in altering the electronic environment of ethanolamine, enhancing our understanding of amine hydration dynamics.

Structural and Electronic Evolution of Ethanolamine upon Microhydration: Insights from Hyperfine Resolved Rotational Spectroscopy.

Ethanolamine hydrates containing from one to seven water molecules were identified via rotational spectroscopy with the aid of accurate quantum chemical methods considering anharmonic vibrational corrections. Ethanolamine undergoes significant conformational changes upon hydration to form energetically favorable hydrogen bond networks. The final structures strongly resemble the pure (H2O)3-9 complexes reported before when replacing two water molecules by ethanolamine. The 14N nuclear quadrupole coupling constants of all the ethanolamine hydrates have been determined and show a remarkable correlation with the strength of hydrogen bonds involving the amino group. After addition of the seventh water molecule, both hydrogen atoms of the amino group actively contribute to hydrogen bond formation, reinforcing the network and introducing approximately 21-27 % ionicity towards the formation of protonated amine. These findings highlight the critical role of microhydration in altering the electronic environment of ethanolamine, enhancing our understanding of amine hydration dynamics.

Quantum neural network approach to Markovian dissipative dynamics of many-body open quantum systems.

Numerous variational methods have been proposed for solving quantum many-body systems, but they often face exponentially increasing computational complexity as the Hilbert space dimension grows. To address this, we introduce a novel approach using quantum neural networks to simulate the dissipative dynamics of many-body open quantum systems. This method combines neural-network quantum state representation with the time-dependent variational principle, both implemented via quantum algorithms. This results in accurate open quantum dynamics described by the Lindblad quantum master equation, exemplified by the spin-boson and transverse field Ising models. Our approach avoids the computational expense of classical algorithms and demonstrates the potential advantages of quantum computing for many-body simulations. To reduce measurement errors, we introduce a projection reset procedure, which could benefit other quantum simulations. In addition, our approach can be extended to simulate non-Markovian quantum dynamics.

Fidelity-dissipation relations in quantum gates

Accurate quantum computing relies on the precision of quantum gates. However, quantum gates in practice are generally affected by dissipative environments, which can significantly reduce their fidelity. In this paper, we elucidate the fundamental relations between the average fidelity of generic quantum gates and the dissipation that occurs during the computing processes. Considering scenarios in which a quantum gate is subject to Markovian environments, we rigorously derive fidelity-dissipation relations that hold for arbitrary operational times. Intriguingly, when the quantum gate undergoes thermal relaxation, the result can be used as a valuable tool for estimating dissipation through experimentally measurable fidelity, without requiring detailed knowledge of the dissipative structure. For the case of arbitrary environments, we uncover a trade-off relation between the average fidelity and energy dissipation, implying that these quantities cannot be large simultaneously. Our results unveil the computational limitations imposed by thermodynamics, shedding light on the profound connection between thermodynamics and quantum computing. Published by the American Physical Society 2024

On the Formation and Detectability of H2CNCN and Its Progenitors

New highly exothermic formation pathways incorporating both thermodynamic and kinetic control for the newly astronomically detected H2CNCN molecule are paired with extremely accurate quantum chemical rovibrational spectroscopic computations. The reactions between astronomically known CH2CN/CH2CCH + HNCN follow effectively identical pathways and proceed through stable intermediates and over deeply submerged transition states to form H2CNCN and HCN/HCCH coproducts. Similarly, the reaction between CH2CN and NCN− can also form H2CNCN, although this pathway first requires the initial formation of NCN−, which is currently undetected in space, via HNCN + CN−. This two-step mechanism uses the highly abundant CN− as the catalyst. Incredibly accurate quantum chemical spectroscopic data are reported for all reactants and products of these reactions, with errors between experimental values and the computations herein on the order of 0.1% or less. Anharmonic vibrational frequencies and intensities are also reported in order to guide experimental and observational searches for these molecules that have mostly been detected in the radio but may now be detectable via JWST.

Automatic molecular fragmentation by evolutionary optimisation

Molecular fragmentation is an effective suite of approaches to reduce the formal computational complexity of quantum chemistry calculations while enhancing their algorithmic parallelisability. However, the practical applicability of fragmentation techniques remains hindered by a dearth of automation and effective metrics to assess the quality of a fragmentation scheme. In this article, we present the Quick Fragmentation via Automated Genetic Search (QFRAGS), a novel automated fragmentation algorithm that uses a genetic optimisation procedure to generate molecular fragments that yield low energy errors when adopted in Many Body Expansions (MBEs). Benchmark testing of QFRAGS on protein systems with less than 500 atoms, using two-body (MBE2) and three-body (MBE3) MBE calculations at the HF/6-31G* level, reveals mean absolute energy errors (MAEE) of 20.6 and 2.2 kJ mol-1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\hbox {mol}^{-1}$$\\end{document}, respectively. For larger protein systems exceeding 500 atoms, MAEEs are 181.5 kJ mol-1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\hbox {mol}^{-1}$$\\end{document} for MBE2 and 24.3 kJ mol-1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\hbox {mol}^{-1}$$\\end{document} for MBE3. Furthermore, when compared to three manual fragmentation schemes on a 40-protein dataset, using both MBE and Fragment Molecular Orbital techniques, QFRAGS achieves comparable or often lower MAEEs. When applied to a 10-lipoglycan/glycolipid dataset, MAEs of 7.9 and 0.3 kJ mol-1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\hbox {mol}^{-1}$$\\end{document} were observed at the MBE2 and MBE3 levels, respectively.Scientific Contribution This Article presents the Quick Fragmentation via Automated Genetic Search (QFRAGS), an innovative molecular fragmentation algorithm that significantly improves upon existing molecular fragmentation approaches by specifically addressing their lack of automation and effective fragmentation quality metrics. With an evolutionary optimisation strategy, QFRAGS actively pursues high quality fragments, generating fragmentation schemes that exhibit minimal energy errors on systems with hundreds to thousands of atoms. The advent of QFRAGS represents a significant advancement in molecular fragmentation, greatly improving the accessibility and computational feasibility of accurate quantum chemistry calculations.

Getting the intermolecular forces correct: introducing the ASTA strategy for a water model.

Having a force field for water providing good bulk properties is paramount for modern studies of most biological systems. Some of the most common three-site force fields are TIP3, SPC/ε or OPC3, providing a decent range of bulk properties. That does not mean though, that they have realistic inter-atomic forces. These force fields have been parameterized with a top-down approach, meaning, by fitting the force field parameters to the experimental bulk properties. This approach has been the governing strategy also for many variants of four- and more-site models. We test a bottom-up approach, in which the force field is parameterized by optimizing the non-bonded inter-atomic forces. Our philosophy is that correct inter-atomic forces lead to correct geometrical and dynamical properties. The first system we try to optimize with the accurately system tailored atomic (ASTA) approach is water, but we aim to eventually probe other systems in the future as well. We applied our ASTA strategy to find a good set of parameters providing accurate bulk properties for the simple three-site force field forms, and also for AMOEBA, a more detailed and polarizable force field. Even though our bottom-up approach did not provide satisfactory results for the simple three-site force fields (with fixed charges), for the case of the AMOEBA force field it led to a modification of the original strategy, giving very good intra- and inter-molecular forces, as compared to accurate quantum chemically calculated reference forces. At the same time, important bulk properties, in this study restricted to the density and diffusion, were accurately reproduced with respect to the experimental values.

A Perspective on the Investigation of Spectroscopy and Kinetics of Complex Molecular Systems with Semiclassical Approaches.

In this Perspective we show that semiclassical methods provide a rigorous hierarchical way to study the vibrational spectroscopy and kinetics of complex molecular systems. The time averaged approach to spectroscopy and the semiclassical transition state theory for kinetics, which have been first adopted and then further developed in our group, provide accurate quantum results on rigorous physical grounds and can be applied even when dealing with a large number of degrees of freedom. In spectroscopy, the multiple coherent, divide-and-conquer, and adiabatically switched semiclassical approaches have practically permitted overcoming issues related to the convergence of results. In this Perspective we demonstrate the possibility of studying the semiclassical vibrational spectroscopy of a molecule adsorbed on an anatase (101) surface, a system made of 51 atoms. In kinetics, the semiclassical transition state theory is able to account for anharmonicity and the coupling between the reactive and bound modes. Our group has developed this technique for practical applications involving the study of phenomena like kinetic isotope effect, heavy atom tunneling, and elusive conformer lifetimes. Here, we show that our multidimensional anharmonic quantum approach is able to tackle on-the-fly the thermal kinetic rate constant of a 135 degree-of-freedom system. Overall, semiclassical methods open up the possibility to describe at the quantum mechanical level systems characterized by hundreds of degrees of freedom leading to the accurate spectroscopic and kinetic description of biomolecules and complex molecular systems.

Evidence of ferroelectric features in low-density supercooled water from ab initio deep neural-network simulations

Over the last decade, an increasing body of evidence has emerged, supporting the existence of a metastable liquid-liquid critical point in supercooled water whereby two distinct liquid phases of different densities coexist. Analyzing long molecular dynamics simulations performed using deep neural-network force fields trained to accurate quantum mechanical data, we demonstrate that the low-density liquid phase displays a strong propensity toward spontaneous polarization, as witnessed by large and long-lived collective dipole fluctuations. Our findings suggest that the dynamical stability of the low-density phase, and hence the transition from high-density to low-density liquid, is triggered by a collective process involving an accumulation of rotational angular jumps, which could ignite large dipole fluctuations. This dynamical transition involves subtle changes in the electronic polarizability of water molecules which affects their rotational mobility within the two phases. These findings hold the potential for catalyzing activity in the search for dielectric-based probes of the putative second critical point.

A Globally Accurate Neural Network Potential Energy Surface and Quantum Dynamics Studies on Be+(2S) + H2/D2 → BeH+/BeD+ + H/D Reactions.

Chemical reactions between Be+ ions and H2 molecules have significance in the fields of ultracold chemistry and astrophysics, but the corresponding dynamics studies on the ground-state reaction have not been reported because of the lack of a global potential energy surface (PES). Herein, a globally accurate ground-state BeH2+ PES is constructed using the neural network model based on 18,657 ab initio points calculated by the multi-reference configuration interaction method with the aug-cc-PVQZ basis set. On the newly constructed PES, the state-to-state quantum dynamics calculations of the Be+(2S) + H2(v0 = 0; j0 = 0) and Be+(2S) + D2(v0 = 0; j0 = 0) reactions are performed using the time-dependent wave packet method. The calculated results suggest that the two reactions are dominated by the complex-forming mechanism and the direct abstraction process at relatively low and high collision energies, respectively, and the isotope substitution has little effect on the reaction dynamics characteristics. The new PES can be used to further study the reaction dynamics of the BeH2+ system, such as the effects of rovibrational excitations and alignment of reactant molecules, and the present dynamics data could provide an important reference for further experimental studies at a finer level.