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At least 235 records · Page 13

Neutrons in Structural Biology: Challenges and Opportunities (Workshop Report)

Gaining a thorough understanding of biological systems requires building our knowledge about biological processes from the level of atoms and electrons, and up to whole organisms. Such comprehensive knowledge will allow for a predictive understanding of complex biological systems behavior. It will guide us in the design and development of novel therapeutics and vaccines to tackle existing health threats and to prepare for future pandemics, and it will provide information necessary to create new biomaterials and bio-inspired technologies through manipulation of biological macromolecules, their assemblies, single cells and even microorganisms. Reaching these goals will require a synergistic combination of multiple experimental techniques with molecular calculations and predictive simulations, and the design and development of new techniques and capabilities that bridge current knowledge and technology gaps. Neutron scattering provides unique information about the biomacromolecular structure and function and can play a major role in achieving these goals. A workshop was held to engage the scientific community in identifying pressing challenges in biochemistry, structural biology, enzymology and structure-guided drug design not solved with the current neutron scattering technologies or utilizing other structural biology techniques such as X-ray crystallography, NMR, and cryo-EM. The workshop brought together structural biology, biochemistry and computational experts, as well as early career researchers and students, creating a forum for discussing scientific advancement and collaboration. The workshop included a one-day satellite training workshop where graduate students and postdoctoral researchers were educated in the application of neutron crystallography and small-angle scattering in structural biology. Furthermore, the Instrument Scientific Advisory Board (ISAB) for the development of a macromolecular neutron diffractometer at ORNL’s Second Target Station was introduced at the workshop. The major outcome was that neutrons can provide atomic-level understanding of biomacromolecular structure, function and dynamics which is of paramount importance for addressing the identified challenges. Neutron crystallography, in particular, can resolve long-standing biochemical issues regarding enzyme function by delineating the underlying chemistry and can have a major impact on the design of small-molecule therapeutics, especially in combination with molecular computation (quantum chemistry and molecular dynamics simulations) and the emerging artificial intelligence (AI)-assisted drug design technologies. The unique properties of neutrons, including their high sensitivity to hydrogen and their non-destructive nature, make them ideal probes of biological matter. There is a palpable need in the scientific community to expand and enhance the impact of neutron sciences on biology. Neutron crystallography is the only structural biology method capable of determining positions of all hydrogen atoms in proteins, nucleic acids and their complexes at near-physiological temperatures and of unstable species at cryogenic temperatures. Moreover, neutron analysis is non-ionizing, non-destructive and does not perturb the structure or redox chemistry of active site metal centers and clusters in proteins, which can be invaluable for studying radiation-sensitive metalloprotein complexes. Further, neutron energies used in scattering applications are similar to atomic motions, permitting neutron spectroscopies to characterize the dynamics of biomacromolecules on the picosecond to microsecond timescales. The different sensitivities of neutrons to protium (H) and deuterium (D) isotopes of hydrogen allow enhanced visibility of specific parts of biological complexes through isotopic labeling. The impact of neutrons will be most powerful when neutron scattering is combined with complementary experimental techniques that use photons and electrons, and with high-performance computing. The interconnection and mutuality of the experimental and theoretical capabilities will drive discoveries in biological and health sciences to generate more complete picture of complex biological systems. The major limitation in the field of biological neutron crystallography has been signal-to-noise, demanding large samples that are difficult to produce for the majority of biomacromolecules and limiting the applicability of this technique in biological sciences. A neutron crystallography instrument at the Second Target Station will revolutionize biological science with neutrons by engaging a large scientific community of structural biologists, enabling successful neutron diffraction experiments from radically smaller biomacromolecular crystals, resolving unanswered biochemical questions, and meaningfully contributing to rational drug design. The meeting highlighted 10 grand challenges that will be addressed with this advanced capability over the next decade and beyond, and the recommendations required to help address them are given below.

59 BASIC BIOLOGICAL SCIENCES↗

Different Enzyme Conformations Induce Different Mechanistic Traits in HIV‐1 Protease

Abstract The influence of the dynamical flexibility of enzymes on reaction mechanisms is a cornerstone in biological sciences. In this study, we aim to 1) study the convergence of the activation free energy by using the first step of the reaction catalysed by HIV‐1 protease as a case study, and 2) provide further evidence for a mechanistic divergence in this enzyme, as two different reaction pathways were seen to contribute to this step. We used quantum mechanics/molecular mechanics molecular dynamics simulations, on four different initial conformations that led to different barriers in a previous study. Despite the sampling, the four activation free energies still spanned a range of 5.0 kcal ⋅ mol −1 . Furthermore, the new simulations did confirm the occurrence of an unusual mechanistic divergence, with two different mechanistic pathways displaying equivalent barriers. An active‐site water molecule is proposed to influence the mechanistic pathway.

Coimbra, João T. S.↗

Vibronic coupling-driven symmetry breaking and solvation in the photoexcited dynamics of quadrupolar dyes

Quadrupolar dyes, such as acceptor–donor–acceptor molecules, are highly relevant for applications in nonlinear optics and photovoltaics. They are also versatile models for exploring photoinduced charge-transfer dynamics. The interplay between electronic and vibronic couplings in these molecules may break excited-state symmetry, resulting in intramolecular charge separation and pronounced solvatochromism. Experimentally, distinguishing the roles of intramolecular vibronic coupling and solvent reorganization for the initial charge-transfer dynamics has been challenging so far. Here we investigate a prototypical quadrupolar dye in polar and non-polar solvents using ultrafast pump–probe and two-dimensional electronic spectroscopy. Our results reveal that vibronic couplings initiate excited-state symmetry breaking during the first ~50 fs of the photoinduced charge transfer, whereas solvent-induced charge localization sets in at later times. Quantum dynamics and electronic structure simulations support our experimental findings. Our results reveal the details of solvation dynamics in photoexcited molecules and suggest strategies for their manipulation through vibronic couplings.

36 MATERIALS SCIENCE↗

Topological phase transition without single particle gap closing in strongly correlated systems

Here, in this study, we show two models where changing topology does not necessarily close the bulk insulating charge gap as demanded in the standard noninteracting picture. From extensive determinantal and dynamical cluster quantum Monte Carlo simulations of the half-filled and quarter-filled Kane-Mele-Hubbard model, we show that, for sufficiently strong interactions at either half- or quarter-filling, a transition between topological and trivial insulators occurs without the closing of a charge gap. To shed light on this behavior, we illustrate that an exactly solvable model reveals that while the single-particle gap remains, the many-body gap does, in fact, close. These two gaps are the same in the noninteracting system but depart from each other as the interaction turns on. We purport that for interacting systems, the proper probe of topological phase transitions is the closing of the many-body rather than the single-particle gap.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Experimental Realization of Discrete Time Quasicrystals

Floquet (periodically driven) systems can give rise to unique nonequilibrium phases of matter without equilibrium analogs. The most prominent example is the realization of discrete time crystals. An intriguing question emerges: What other novel phases can manifest when the constraint of time periodicity is relaxed? In this study, we explore quantum systems subjected to a quasiperiodic drive. Leveraging a strongly interacting spin ensemble in diamond, we identify the emergence of long-lived discrete time quasicrystals. Unlike conventional time crystals, time quasicrystals exhibit robust subharmonic responses at multiple incommensurate frequencies. Furthermore, we show that the multifrequency nature of the quasiperiodic drive allows for the formation of diverse patterns associated with different discrete time quasicrystalline phases. Our findings demonstrate the existence of nonequilibrium phases in quasi-Floquet settings, significantly broadening the catalog of novel phenomena in driven many-body quantum systems.

Exotic phases of matter↗

Quantum Application Specifications and Benchmarks

This software describes computational tasks for quantum computers that are derived from LANL basic science research applications such as the modeling of materials, chemicals and compounds at atomic scales. The computations focus on quantum simulation tasks, such as quantum dynamics, thermal state preparation and ground state estimation. The primary function of the software is to develop estimates of the requirements for large-scale fault-tolerant quantum computers to solve these scientific computations. The secondary focus of the software are codes for assessing the limitations of conducting quantum computations on classical computers.

Coffrin, Carleton↗

Rational Design of High-Performing Electrodes in Energy Storage Devices

Rational design of interfaces with proper physico-chemical properties is necessary to optimize the performance of electrochemical devices, which requires fundamental understanding of the interfaces. In this project, we leveraged quantum mechanical and molecular dynamics simulations as well as machine learning (ML) technique to correlate the relationships between structure and properties including ion transport and electronic structures of cathode host materials in lithium-sulfur (Li-S) and carbon anode in sodium (Na) batteries for improved electrochemical performance.

25 ENERGY STORAGE↗

Computational methods based on density functional theory for reactions and processes involving electronic spin (Final Technical Report)

This award supports one post-doctoral researcher for 1.5 years. Publications that acknowledge this grant: Refs. 1–14. Refs. 3,10,12 assess current methodology for the evaluation of magnetic exchange couplings in transition metal complexes. In particular, Ref. 10 validates the use of an approximate (non-iterative) Green’s function approach for the calculation of magnetic exchange couplings and will be the foundation for Thrust 2 in this proposal. Refs. 3 and 12 focus on widely used density functional approaches based on the standard energy differences methodology for the particular case of oxo-bridged Fe(III) complexes. Refs. 2,4–7,11 apply current methodologies to problems of practical interest in molecular magnetism. Ref. 13 presents a methodology to explicitly simulate the dynamics of open quantum systems within density functional theory (DFT) calculations based on the Liouville-von Neumann equation of motion for quantum systems driven out-of-equilibrium. Ref. 8 uses non-collinear spin DFT to explain the mechanical behavior of magnetic mono-atomic Pt wires produced in break-junction experiments in the presence of a magnetic field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modeling prebiotic chemistries with quantum accuracy at classical costs

Molecular Dynamics (MD) simulations using classical force-fields are commonly employed in numerous scientific investigations. However, many natural processes involve bond breaking and quantum forces. This complexity is compounded by the presence of multiple competing length and timescales. For example, accurately modeling the thermodynamics and dynamics of a chemical reaction requires accounting for the concerted movements of numerous solvent molecules and ions with their own fast or slow timescales. While widely used static Density Functional Theory (DFT) calculations at 0 temperature can be beneficial for such investigations, they do not account for dynamics, and lack precision in describing the molecular environments. They particularly fail at correct, rigorous treatments of finite-temperature fluctuations, and thus generalization to experimentally relevant conditions. In PNAS Benayad et al develop a scalable, generalizable approach for designing Neural Network Potentials (NNPs) that can handle chemical reactivity in solvated systems with quantum accuracy at classical costs. Specifically, they study phosphoester bond formation and rupture, which is fundamentally relevant to the Phosphorus-Oxygen bond formation central to life, and especially for the RNA world hypothesis. The framework developed here has the potential to generalize to different chemical reactions of energy and biological relevance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantum Simulation of Polarized Light-Induced Electron Transfer with a Trapped-Ion Qutrit System

Electron transfer within and between molecules is crucial in chemistry, biochemistry, and energy science. Here this study describes a quantum simulation method that explores the influence of light polarization on electron transfer between two molecules. By implementing precise and coherent control among the quantum states of trapped atomic ions, we can induce quantum dynamics that mimic the electron-transfer dynamics in molecules. We use three-level systems (qutrits), rather than traditional two-level systems (qubits), to enhance the simulation efficiency and realize high-fidelity simulations of electron-transfer dynamics. We treat the quantum interference between the electron coupling pathways from a donor with two degenerate excited states to an acceptor and analyze the transfer efficiency. We also examine the potential error sources that enter the quantum simulations. The trapped-ion systems have favorable scalings with system size compared to those of classical computers, promising access to richer electron-transfer simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantum computing universal thermalization dynamics in a (2 + 1)D Lattice Gauge Theory

Simulating non-equilibrium phenomena in strongly-interacting quantum many-body systems, including thermalization, is a promising application of near-term and future quantum computation. By performing experiments on a digital quantum computer consisting of fully-connected optically-controlled trapped ions, we study the role of entanglement in the thermalization dynamics of a Z 2 lattice gauge theory in 2+1 spacetime dimensions. Using randomized-measurement protocols, we efficiently learn a classical approximation of non-equilibrium states that yields the gap-ratio distribution and the spectral form factor of the entanglement Hamiltonian. These observables exhibit universal early-time signals for quantum chaos, a prerequisite for thermalization. Our work, therefore, establishes quantum computers as robust tools for studying universal features of thermalization in complex many-body systems, including in gauge theories.

97 MATHEMATICS AND COMPUTING↗

Quantum mechanics based non-bonded force field functions for use in molecular dynamics simulations of materials and systems: The nitrogen and oxygen columns

Accurate Force Fields (FFs) are essential for Molecular Dynamics (MD) simulations of the dynamics of realistic materials in terms of atomic-level interactions. The FF parameters of short-range valence interactions can be derived through Quantum Mechanical (QM) calculations on model systems practical for QM (<300 atoms). Similarly, the dynamic electrostatic interactions can be described with methods such as QEq or PQEq that allow charges and polarization to adjust dynamically. However, accurately extracting long-range van der Waals (vdW) interactions from QM calculations poses challenges due to the absence of a definitive method to distinguish between the different energetic components of electrostatics, polarization, vdW, hydrogen bonding, and valence interactions. To do this we use the Perdew–Burke–Ernzerhof flavor of Density Functional Theory, including empirical D3 vdW corrections, to predict the Equation of State for each element (keeping any covalent bonds fixed), from which we obtain the two-body vdW nonbond potential. Here, we extend these calculations to include non-bonded parameters for the N and O columns of the periodic table so that we now describe columns 15 (N), 16 (O), 17 (F), and 18 (Ne) of the periodic table. For these 20 elements, we find that the two-body vdW potentials can all be mapped to a single universal two-body curve, with just three scaling parameters: Re, De, and L. We refer to this as the Universal NonBond (UNB) potential. We expect this to be useful for new MD simulations and a helpful starting point to obtain UNB parameters for the remainder of the periodic table.

Chemistry↗

Simulating non-native cubic interactions on noisy quantum machines

As a milestone for general-purpose computing machines, we demonstrate that quantum processors can be programed to efficiently simulate dynamics that are not native to the hardware. Moreover, on noisy devices without error correction, we show that simulation results are significantly improved when the quantum program is compiled using modular gates instead of a restricted set of standard gates. We demonstrate the general methodology by solving a cubic interaction problem, which appears in nonlinear optics, gauge theories, as well as plasma and fluid dynamics. To encode the non-native Hamiltonian evolution, we decompose the Hilbert space into a direct sum of invariant subspaces in which the nonlinear problem is mapped to a finite-dimensional Hamiltonian simulation problem. Furthermore, in a three-states example, the resultant unitary evolution is realized by a product of approximately 20 standard gates, using which approximately ten simulation steps can be carried out on state-of-the-art quantum hardware before results are corrupted by decoherence. In comparison, the simulation depth is improved by more than an order of magnitude when the unitary evolution is realized as a single cubic gate, which is compiled directly using optimal control. Alternatively, parametric gates may also be compiled by interpolating control pulses. Modular gates thus obtained provide high-fidelity building blocks for quantum Hamiltonian simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Nonadiabatic molecular dynamics simulation of C2H22+ in a strong laser field*

We investigate the alignment dependence of the strong laser dissociation dynamics of molecule C 2 H 2 2 + in the frame of real-time and real-space time-dependent density function theory coupled with nonadiabatic quantum molecular dynamics (TDDFT-MD) simulation. This work is based on a recent experiment study “ultrafast electron diffraction imaging of bond breaking in di-ionized acetylene” [Wolter et al , Science 354 , 308–312 (2016)]. Our simulations are in excellent agreement with the experimental data and the analysis confirms that the alignment dependence of the proton dissociation dynamics comes from the electron response of the driving laser pulse. Our results validate the ability of the TDDFT-MD method to reveal the underlying mechanism of experimentally observed and control molecular dissociation dynamics.

Physics↗

Testing the mean field theory of scalar field dark matter

Scalar field dark matter offers an interesting alternative to the traditional WIMP dark matter picture. Astrophysical and cosmological simulations are useful to constraining the mass of the dark matter particle in this model. This is particularly true at low mass where the wavelike nature of the dark matter particle manifests on astrophysical scales. These simulations typical use a classical field approximation. In this work, we look at extending these simulations to include quantum corrections. We look into both the ways in which large corrections impact the predictions of scalar field dark matter, and the timescales on which these corrections grow large. Corrections tend to lessen density fluctuations and increase the effect of “quantum pressure”. During collapse, these corrections grow exponentially, quantum corrections would become important in about \sim 30 ∼ 30 dynamical times. This implies that the predictions of classical field simulations may differ from those with quantum corrections for systems with short dynamical times.

Eberhardt, Andrew↗

Absence of Fibonacci anyons in Rydberg chains

Recent experiments have focused attention on the properties of chains of atoms in which the atoms are either in their ground states or in highly excited Rydberg states which block similar excitations in their immediate neighbors. As the low-energy Hilbert space of such chains is isomorphic to that of a chain of Fibonacci anyons, they have been proposed as a platform for topological quantum computation and for simulating anyon dynamics. In this work, we show that generic local operators in the Rydberg chain correspond to nonlocal anyonic operators that do not preserve a topological symmetry of the physical anyons. Consequently, we argue that Rydberg chains do not yield Fibonacci anyons and quantum computation with Rydberg atoms is not topologically protected.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Learning Conservation Laws in Unknown Quantum Dynamics

We present a learning algorithm for discovering conservation laws given as sums of geometrically local observables in quantum dynamics. This includes conserved quantities that arise from local and global symmetries in closed and open quantum many-body systems. The algorithm combines the classical shadow formalism for estimating expectation values of observable and data analysis techniques based on singular value decompositions and robust polynomial interpolation to discover all such conservation laws in unknown quantum dynamics with rigorous performance guarantees. Our method can be directly realized in quantum experiments, which we illustrate with numerical simulations, using closed and open quantum system dynamics in a ℤ 2 gauge theory and in many-body localized spin chains.

Machine learning↗

Many-body reactive force field development for carbon condensation in C/O systems under extreme conditions

In this paper, we describe the development of a reactive force field for C/O systems under extreme temperatures and pressures, based on the many-body Chebyshev Interaction Model for Efficient Simulation (ChIMES). The resulting model, which targets carbon condensation under thermodynamic conditions of 6500 K and 2.5 g cm –3 , affords a balance between model accuracy, complexity, and training set generation expense. We show that the model recovers much of the accuracy of density functional theory for the prediction of structure, dynamics, and chemistry when applied to dissociative condensed phase systems at 1:1 and 1:2 C:O ratios, as well as molten carbon. Our C/O modeling approach exhibits a 104 increase in efficiency for the same system size (i.e., 128 atoms) and a linear system size scalability over standard quantum molecular dynamics methods, allowing the simulation of significantly larger systems than previously possible. We find that the model captures the condensed-phase reaction-coupled formation of carbon clusters implied by recent experiments, and that this process is susceptible to strong finite size effects. Overall, we find the present ChIMES model to be well suited for studying chemical processes and cluster formation at pressures and temperatures typical of shock waves. We expect that the present C/O modeling paradigm can serve as a template for the development of a broader high pressure–high temperature force-field for condensed phase chemistry in organic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗