Increasing Pump-Probe Signal toward Asymptotic Limits.

Optimization of pump-probe signal requires a complete understanding of how signal scales with experimental factors. In simple systems, signal scales quadratically with molar absorptivity, and linearly with fluence, concentration, and path length. In practice, scaling factors weaken beyond certain thresholds (e.g., OD > 0.1) due to asymptotic limits related to optical density, fluence and path length. While computational models can accurately account for subdued scaling, quantitative explanations often appear quite technical in the literature. This Perspective aims to present a simpler understanding of the subject with concise formulas for estimating absolute magnitudes of signal under both ordinary and asymptotic scaling conditions. This formulation may be more appealing for spectroscopists seeking rough estimates of signal or relative comparisons. We identify scaling dependencies of signal with respect to experimental parameters and discuss applications for improving signal under broad conditions. We also review other signal enhancement methods, such as local-oscillator attenuation and plasmonic enhancement, and discuss respective benefits and challenges regarding asymptotic limits that signal cannot exceed.

Least-Squares Fitting of Multidimensional Spectra to Kubo Line-Shape Models.

We report a comprehensive study of the efficacy of least-squares fitting of multidimensional spectra to generalized Kubo line-shape models and introduce a novel least-squares fitting metric, termed the scale invariant gradient norm (SIGN), that enables a highly reliable and versatile algorithm. The precision of dephasing parameters is between 8× and 50× better for nonlinear model fitting compared to that for the centerline-slope (CLS) method, which effectively increases data acquisition efficiency by 1-2 orders of magnitude. Whereas the CLS method requires sequential fitting of both the nonlinear and linear spectra, our model fitting algorithm only requires nonlinear spectra but accurately predicts the linear spectrum. We show an experimental example in which the CLS time constants differ by 60% for independent measurements of the same system, while the Kubo time constants differ by only 10% for model fitting. This suggests that model fitting is a far more robust method of measuring spectral diffusion than the CLS method, which is more susceptible to structured residual signals that are not removable by pure solvent subtraction. Statistical analysis of the CLS method reveals a fundamental oversight in accounting for the propagation of uncertainty by Kubo time constants in the process of fitting to the linear absorption spectrum. A standalone desktop app and source code for the least-squares fitting algorithm are freely available, with example line-shape models and data. We have written the MATLAB source code in a generic framework where users may supply custom line-shape models. Using this application, a standard desktop fits a 12-parameter generalized Kubo model to a 106 data-point spectrum in a few minutes.

Edge-pixel referencing suppresses correlated baseline noise in heterodyned spectroscopies.

Referencing schemes are commonly used in heterodyned spectroscopies to mitigate correlated baseline noise arising from shot-to-shot fluctuations of the local oscillator. Although successful, these methods rely on careful pixel-to-pixel matching between the two spectrographs. A recent scheme introduced by Feng et al. [Opt. Express 27(15), 20323-20346 (2019)] employed a correlation matrix to allow free mapping between dissimilar spectrographs, leading to the first demonstration of floor noise limited detection on a multichannel array used in heterodyned spectroscopy. In addition to their primary results using a second reference spectrometer, Feng et al. briefly demonstrated the flexibility of their method by referencing to same-array pixels at the two spectral edges (i.e., edge-pixel referencing). We present a comprehensive study of this approach, which we term edge-pixel referencing, including optimization of the approach, assessment of the performance, and determination of the effects of background responses. We show that, within some limitations, the distortions due to background signals will not affect the 2D IR line shape or amplitude and can be mitigated by band narrowing of the pump beams. We also show that the performance of edge-pixel referencing is comparable to that of referencing to a second spectrometer in terms of noise suppression and that the line shapes and amplitudes of the spectral features are, within the measurement error, identical. Altogether, these results demonstrate that edge-pixel referencing is a powerful approach for noise suppression in heterodyned spectroscopies, which requires no new hardware and, so, can be implemented as a software solution for anyone performing heterodyned spectroscopy with multichannel array detectors already.

On the Conflicting Estimations of Pigment Site Energies in Photosynthetic Complexes: A Case Study of the CP47 Complex.

We focus on problems with elucidation of site energies [Formula: see text] for photosynthetic complexes (PSCs) in order to raise some genuine concern regarding the conflicting estimations propagating in the literature. As an example, we provide a stern assessment of the site energies extracted from fits to optical spectra of the widely studied CP47 antenna complex of photosystem II from spinach, though many general comments apply to other PSCs as well. Correct values of [Formula: see text] for chlorophyll (Chl) a in CP47 are essential for understanding its excitonic structure, population dynamics, and excitation energy pathway(s). To demonstrate this, we present a case study where simultaneous fits of multiple spectra (absorption, emission, circular dichroism, and nonresonant hole-burned spectra) show that several sets of parameters can fit the spectra very well. Importantly, we show that variable emission maxima (690-695 nm) and sample-dependent bleaching in nonresonant hole-burning spectra reported in literature could be explained, assuming that many previously studied CP47 samples were a mixture of intact and destabilized proteins. It appears that the destabilized subpopulation of CP47 complexes could feature a weakened hydrogen bond between the 13(1)-keto group of Chl29 and the PsbH protein subunit, though other possibilities cannot be entirely excluded, as discussed in this work. Possible implications of our findings are briefly discussed.

Trajectory-profile-guided single molecule tracking for assignment of one-dimensional diffusion trajectories.

A variety of algorithms exist for optical single molecule tracking in two and three dimensions. One general class of algorithms employs cost-functionals to link the individual fluorescent spots, produced by a molecule in sequential video frames, into trajectories. This method has also been used to track one-dimensional (1D) molecular motions for relatively low diffusion rates (i.e., D < 1 µm(2)/s). At high diffusion rates, the cost-functional approach often fails to accurately reproduce 1D trajectories, particularly when the molecules are closely spaced. In this paper, we present a new algorithm called trajectory-profile-guided (TPG) tracking that is designed specifically for 1D trajectories. TPG tracking involves an initial search for one-dimensionally aligned fluorescent spots (i.e., candidate molecules). Qualifying candidates are subsequently identified and linked into trajectories based on several criteria. We test the TPG algorithm's accuracy and precision against cost-functional based tracking using both simulated and experimental video data. The results show that TPG tracking more accurately reproduces the actual 1D trajectories, particularly at higher diffusion rates. TPG tracking is also shown to produce longer trajectories and more accurate estimates of trajectory aspect ratios (i.e., their dimensionality), molecular diffusion coefficients, and order parameters for aligned 1D trajectories over a wide range of diffusion coefficients.