Accelerating two-dimensional infrared spectroscopy while preserving lineshapes using GIRAF

Fisher information for smart sampling in time-domain spectroscopy

Time-domain spectroscopy encompasses a wide range of techniques, such as Fourier-transform infrared, pump-probe, Fourier-transform Raman, and two-dimensional electronic spectroscopies. These methods enable various applications, such as molecule characterization, excited state dynamics studies, or spectral classification. Typically, these techniques rarely use sampling schemes that exploit the prior knowledge scientists typically have before the actual experiment. Indeed, not all sampling coordinates carry the same amount of information, and a careful selection of the sampling points may notably affect the resulting performance. In this work, we rationalize, with examples, the various advantages of using an optimal sampling scheme tailored to the specific experimental characteristics and/or expected results. We show that using a sampling scheme optimizing the Fisher information minimizes the variance of the desired parameters. This can greatly improve, for example, spectral classifications and multidimensional spectroscopy. We demonstrate how smart sampling may reduce the acquisition time of an experiment by one to two orders of magnitude, while still providing a similar level of information.

Ultrafast transient vibrational action spectroscopy of cryogenically cooled ions

Ultrafast transient vibrational action spectra of cryogenically cooled Re(CO)3(CH3CN)3+ ions are presented. Nonlinear spectra were collected in the time domain by monitoring the photodissociation of a weakly bound N2 messenger tag as a function of delay times and phases between a set of three infrared pulses. Frequency-resolved spectra in the carbonyl stretch region show relatively strong bleaching signals that oscillate at the difference frequency between the two observed vibrational features as a function of the pump-probe waiting time. This observation is consistent with the presence of nonlinear pathways resulting from underlying cross-peak signals between the coupled symmetric-asymmetric C≡O stretch pair. The successful demonstration of frequency-resolved ultrafast transient vibrational action spectroscopy of dilute molecular ion ensembles provides an exciting, new framework for the study of molecular dynamics in isolated, complex molecular ion systems.

Transparent window 2D IR spectroscopy of proteins

Proteins are complex, heterogeneous macromolecules that exist as ensembles of interconverting states on a complex energy landscape. A complete, molecular-level understanding of their function requires experimental tools to characterize them with high spatial and temporal precision. Infrared (IR) spectroscopy has an inherently fast time scale that can capture all states and their dynamics with, in principle, bond-specific spatial resolution. Two-dimensional (2D) IR methods that provide richer information are becoming more routine but remain challenging to apply to proteins. Spectral congestion typically prevents selective investigation of native vibrations; however, the problem can be overcome by site-specific introduction of amino acid side chains that have vibrational groups with frequencies in the "transparent window" of protein spectra. This Perspective provides an overview of the history and recent progress in the development of transparent window 2D IR of proteins.

Multidimensional electronic spectroscopy in high-definition-Combining spectral, temporal, and spatial resolutions

Over the past two decades, coherent multidimensional spectroscopies have been implemented across the terahertz, infrared, visible, and ultraviolet regions of the electromagnetic spectrum. A combination of coherent excitation of several resonances with few-cycle pulses, and spectral decongestion along multiple spectral dimensions, has enabled new insights into wide ranging molecular scale phenomena, such as energy and charge delocalization in natural and artificial light-harvesting systems, hydrogen bonding dynamics in monolayers, and strong light-matter couplings in Fabry-Pérot cavities. However, measurements on ensembles have implied signal averaging over relevant details, such as morphological and energetic inhomogeneity, which are not rephased by the Fourier transform. Recent extension of these spectroscopies to provide diffraction-limited spatial resolution, while maintaining temporal and spectral information, has been exciting and has paved a way to address several challenging questions by going beyond ensemble averaging. The aim of this Perspective is to discuss the technological developments that have eventually enabled spatially resolved multidimensional electronic spectroscopies and highlight some of the very recent findings already made possible by introducing spatial resolution in a powerful spectroscopic tool.

Improved MUSSELS reconstruction for high-resolution multi-shot diffusion weighted imaging

PURPOSE

MUSSELS is a one-step iterative reconstruction method for multishot diffusion weighted (msDW) imaging. The current work presents an efficient implementation, termed IRLS MUSSELS, that enables faster reconstruction to enhance its utility for high-resolution diffusion MRI studies.

METHODS

The recently proposed MUSSELS reconstruction belongs to a new class of parallel imaging-based methods that recover artifact-free DWIs from msDW data without needing phase compensation. The reconstruction is achieved via structured low-rank matrix completion algorithms, which are computationally demanding due to the large size of the Hankel matrices and their associated computations involving singular value decompositions. Because of this, computational demands of the MUSSELS reconstruction scales as the matrix size and the number of shots increases, which hinders its practical utility for high-resolution applications. In this work, we derive a computationally efficient MUSSELS formulation by modifying the iterative reweighted least squares (IRLS) method that were proposed earlier to solve such problems. Using whole-brain in vivo data, we show the utility of the IRLS MUSSELS for routine high-resolution studies with reduced computational burden.

RESULTS

IRLS MUSSELS provides about five times faster reconstruction for matrix sizes 192 × 192 and 256 × 256 compared to the earlier MUSSELS implementation. The widely employed conjugate symmetry priors can also be incorporated into IRLS MUSSELS to reduce blurring of the partial Fourier acquisitions, without incurring much computational burden.

CONCLUSIONS

The proposed method is observed to be computationally efficient to enable routine high-resolution studies. The computational complexity matches the traditional msDWI reconstruction methods and provides improved reconstruction results with the additional constraints.

Optimized reconstructions of compressively sampled two-dimensional infrared spectra

Compressive sampling has the potential to dramatically accelerate the pace of data collection in two-dimensional infrared (2D IR) spectroscopy. We have previously introduced the Generic Iteratively Reweighted Annihilating Filter (GIRAF) reconstruction algorithm to solve the reconstruction in 2D IR compressive sampling. Here, we report a thorough assessment of this method and comparison to our earlier efforts using the Total Variation (TV) algorithm. We show that the GIRAF algorithm has some distinct advantages over TV. Although it is no better or worse in terms of ameliorating the impacts of compressive sampling on the measured 2D IR line shape, we find that the nature of those effects is different for GIRAF than they were for TV. In addition to assessing the impacts on the line shape of a single oscillator, we also test the ability of the algorithm to reconstruct spectra that have transitions from more than one oscillator, such as the coupled carbonyl oscillators in rhodium dicarbonyl. Finally, and perhaps most importantly, we show that the GIRAF algorithm has a distinct denoising effect on the signal-to-noise ratio (SNR) of the 2D IR spectra that can increase the SNR by as much as 4× without any additional signal averaging and collecting fewer data points, which should further enhance the acceleration of data collection that can be achieved using compressive sampling and enable even more challenging experimental measurements.