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Item type:Publication, Access status: without files , Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance informationWe consider the problem of estimating the energy of a quantum state preparation for a given Hamiltonian in Pauli decomposition. For various quantum algorithms, in particular, in the context of quantum chemistry, it is crucial to have energy estimates with error bounds, as captured by guarantees on the problem's sampling complexity. In particular, when limited to Pauli basis measurements, the smallest sampling complexity guarantee comes from a simple single-shot estimator via a straightforward argument based on Hoeffding's inequality. In this work, we construct an adaptive estimator using the state's actual variance. Technically, our estimation method is based on the empirical Bernstein stopping (EBS) algorithm and grouping schemes, and we provide a rigorous tail bound, which leverages the state's empirical variance. In a numerical benchmark of estimating ground-state energies of several Hamiltonians, we demonstrate that EBS consistently improves upon elementary readout guarantees up to 1 order of magnitude.Publicationtype: Journal Article28 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Maximum Entropy-Mediated Liquid-to-Solid Nucleation and Transition(American Chemical Society (ACS), 2025-02-12); ; ; Molecular dynamics (MD) simulations are a powerful tool for studying matter at the atomic scale. However, to simulate solids, an initial atomic structure is crucial for the successful execution of MD simulations but can be difficult to prepare due to insufficient atomistic information. At the same time, wide-angle X-ray scattering (WAXS) measurements can determine the radial distribution function (RDF) of atomic structures. However, the interpretation of RDFs is often challenging. Here, we present an algorithm that can bias MD simulations with RDFs by combining the information on the MD atomic interaction potential and the RDF under the principle of maximum relative entropy. We show that this algorithm can be used to adjust the RDF of one liquid model, e.g., the TIP3P water model, to reproduce the RDF and improve the angular distribution function (ADF) of another model, such as the TIP4P/2005 water model. In addition, we demonstrate that the algorithm can initiate crystallization in liquid systems, leading to both stable and metastable crystalline states defined by the RDF, e.g., crystallization of water to ice and liquid TiO2 to rutile or anatase. Finally, we discuss how this method can be useful for improving interaction models, studying crystallization processes, interpreting measured RDFs, or training machine-learned potentials.Publicationtype: Journal Article29 42 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , Comparison and Validation of Force Fields for Deep Eutectic Solvents in Combination with Water and Alcohol Dehydrogenase(2021-08-10); ; ; ; Deep eutectic solvents (DESs) have become popular as environmental-friendly solvents for biocatalysis. Molecular dynamics (MD) simulations offer an in-depth analysis of enzymes in DESs, but their performance depends on the force field chosen. Here, we present a comprehensive validation of three biomolecular force fields (CHARMM, Amber, and OPLS) for simulations of alcohol dehydrogenase (ADH) in DESs composed of choline chloride and glycerol/ethylene glycol with varying water contents. Different properties (e.g., protein structure and flexibility, solvation layer, and H-bonds) were used for validation. For two properties (viscosity and water activity) also experiments were performed. The viscosity was calculated with the periodic perturbation method, whereby its parameter dependency is disclosed. A modification of Amber was identified as the best-performing model for low water contents, whereas CHARMM outperforms the other models at larger water concentrations. An analysis of ADH's structure and interactions with the DESs revealed similar predictions for Amber and CHARMM.Publicationtype: Journal ArticleScopus© Citations 17 99 203 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Rigorous lower bounds for the ground state energy of molecules by employing necessary N-representability conditions(2020-11-13); ; ; ; Electronic structure calculations, in particular the computation of the ground state energy, lead to challenging problems in optimization. These problems are of enormous importance in quantum chemistry for calculations of properties of solids and molecules. Minimization methods for computing the ground state energy can be developed by employing a variational approach, where the second-order reduced density matrix defines the variable. This concept leads to large-scale semidefinite programming problems that provide a lower bound for the ground state energy. Upper bounds of the ground state energy can be calculated for example with the Hartree–Fock method or numerically more exact for a given basis set by full CI. However, Nakata et al. ( J. Chem. Phys.200111482828292) observed that due to numerical errors the semidefinite solver produced erroneous results with a lower bound significantly larger than the full CI energy. For the LiH, CH–, NH–, OH, OH–, and HF molecules violations within one mhartree were observed. We applied the software VSDP which takes all numerical errors due to floating-point arithmetic operations into consideration. For two test libraries VSDP provides tight rigorous error bounds lower than full CI energies reported with an accuracy of 0.1 to 0.01 mhartree. Only little computation work must be spent in order to compute close rigorous error bounds for the ground state energy.Publicationtype: Journal Article97 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Molecular modeling of triton X micelles: force field parameters, self-assembly, and partition equilibriaNonionic surfactants of the Triton X-series find various applications in extraction processes and as solubilizing agents for the purification of membrane proteins. However, so far no optimized parameters are available to perform molecular simulations with a biomolecular force field. Therefore, we have determined the first optimized set of CHARMM parameters for the Triton X-series, enabling all-atom molecular dynamics (MD) simulations. In order to validate the new parameters, micellar sizes (aggregation numbers) of Triton X-114 and Triton X-100 have been investigated as a function of temperature and surfactant concentration. These results are comparable with experimental results. Furthermore, we have introduced a new algorithm to obtain micelle structures from self-assembly MD simulations for the COSMOmic method. This model allows efficient partition behavior predictions once a representative micelle structure is available. The predicted partition coefficients for the systems Triton X-114/water and Triton X-100/water are in excellent agreement with experimental results. Therefore, this method can be applied as a screening tool to find optimal solute-surfactant combinations or suitable surfactant systems for a specific application.Publicationtype: Journal Article68