An official website of the United States government
An approach is presented for simulating multipulse nuclear magnetic resonance (NMR) spectra of polycrystalline solids directly in the frequency domain. The approach integrates the symmetry pathway concept for multipulse NMR with efficient algorithms for calculating spinning sideband amplitudes and performing interpolated finite-element numerical integration over all crystallite orientations in a polycrystalline sample. The numerical efficiency is achieved through a set of assumptions used to approximate the evolution of a sparse density matrix through a pulse sequence as a set of individual transition pathway signals. The utility of this approach for simulating the spectra of complex materials, such as glasses and other structurally disordered materials, is demonstrated.
more »
« less
MRSimulator: A cross-platform, object-oriented software package for rapid solid-state NMR spectral simulation and analysis
The open-source Python package, MRSimulator, is presented as a simple-to-use, fast, versatile, and extendable package capable of simulating one- and higher-dimensional Nuclear Magnetic Resonance (NMR) spectra under static, magic-angle, and variable-angle conditions. High benchmarks in spectral simulations are achieved by assuming that there are no degeneracies in the energy eigenstates, i.e., all dipolar couplings are in the weak limit and that there are no rotational resonances during evolution periods. Under these assumptions, the symmetry pathway formalism is exploited to reduce an NMR method applied to a spin system into a sum of individual transition pathways, whose signals are more efficiently calculated individually than as part of a full-density matrix simulation. To increase numerical efficiencies further, our approach restricts coherence transfer among transitions to pure rotations about an axis in the x–y plane of the rotating frame or through an artificial total mixing operation between selected transitions of adjacent free evolution periods. The assumptions used in this approach are valid for most commonly used solid-state NMR methods. Details of the implementation, along with example code usage, are given, including a least-squares spectral analysis.
more »
« less
- Award ID(s):
- 2107636
- PAR ID:
- 10593749
- Publisher / Repository:
- American Institute of Physics
- Date Published:
- Journal Name:
- The Journal of Chemical Physics
- Volume:
- 161
- Issue:
- 21
- ISSN:
- 0021-9606
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract Protein regions which are intrinsically disordered, exist as an ensemble of rapidly interconverting structures. Cooling proteins to cryogenic temperatures for dynamic nuclear polarization (DNP) magic angle spinning (MAS) NMR studies suspends most of the motions, resulting in peaks that are broad but not featureless. To demonstrate that detailed conformational restraints can be retrieved from the peak shapes of frozen proteins alone, we developed and used a simulation framework to assign peak features to conformers in the ensemble. We validated our simulations by comparing them to spectra of α‐synuclein acquired under different experimental conditions. Our assignments of peaks to discrete dihedral angle populations suggest that structural constraints are attainable under cryogenic conditions. The ability to infer ensemble populations from peak shapes has important implications for DNP MAS NMR studies of proteins with regions of disorder in living cells because chemical shifts are the most accessible measured parameter.more » « less
-
Abstract Current neutrino detectors will observe hundreds to thousands of neutrinos from Galactic supernovae, and future detectors will increase this yield by an order of magnitude or more. With such a data set comes the potential for a huge increase in our understanding of the explosions of massive stars, nuclear physics under extreme conditions, and the properties of the neutrino. However, there is currently a large gap between supernova simulations and the corresponding signals in neutrino detectors, which will make any comparison between theory and observation very difficult. SNEWPY is an open-source software package that bridges this gap. The SNEWPY code can interface with supernova simulation data to generate from the model either a time series of neutrino spectral fluences at Earth, or the total time-integrated spectral fluence. Data from several hundred simulations of core-collapse, thermonuclear, and pair-instability supernovae is included in the package. This output may then be used by an event generator such as sntools or an event rate calculator such as the SuperNova Observatories with General Long Baseline Experiment Simulator (SNOwGLoBES). Additional routines in the SNEWPY package automate the processing of the generated data through the SNOwGLoBES software and collate its output into the observable channels of each detector. In this paper we describe the contents of the package, the physics behind SNEWPY, the organization of the code, and provide examples of how to make use of its capabilities.more » « less
-
Abstract pyspeckitis a toolkit and library for spectroscopic analysis in Python. We describe thepyspeckitpackage and highlight some of its capabilities, such as interactively fitting a model to data, akin to the historically widely-usedsplotfunction inIRAF.pyspeckitemploys the Levenberg–Marquardt optimization method via thempfitandlmfitimplementations, and important assumptions regarding error estimation are described here. Wrappers to usepymcandemceeas optimizers are provided. A parallelized wrapper to fit lines in spectral cubes is included. As part of theastropyaffiliated package ecosystem,pyspeckitis open source and open development, and welcomes input and collaboration from the community.more » « less
-
Friedmann, M (Ed.)Abstract Phylogenetic trees establish a historical context for the study of organismal form and function. Most phylogenetic trees are estimated using a model of evolution. For molecular data, modeling evolution is often based on biochemical observations about changes between character states. For example, there are four nucleotides, and we can make assumptions about the probability of transitions between them. By contrast, for morphological characters, we may not know a priori how many characters states there are per character, as both extant sampling and the fossil record may be highly incomplete, which leads to an observer bias. For a given character, the state space may be larger than what has been observed in the sample of taxa collected by the researcher. In this case, how many evolutionary rates are needed to even describe transitions between morphological character states may not be clear, potentially leading to model misspecification. To explore the impact of this model misspecification, we simulated character data with varying numbers of character states per character. We then used the data to estimate phylogenetic trees using models of evolution with the correct number of character states and an incorrect number of character states. The results of this study indicate that this observer bias may lead to phylogenetic error, particularly in the branch lengths of trees. If the state space is wrongly assumed to be too large, then we underestimate the branch lengths, and the opposite occurs when the state space is wrongly assumed to be too small.more » « less
