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Frequency domain nonlinear spectroscopies are a useful probe of linear and non-linear transitions in a variety of biological, chemical, and materials systems. They require scanning of optical parametric amplifiers (OPAs). Each OPA contains multiple motors that move to prerecorded positions to optimize output at each desired color. OPA optimization and color accuracy are crucial for frequency domain experiments, where OPA color is scanned. Such performance is highly sensitive to environmental fluctuations, so motor positions must be regularly optimized and tuned. Despite the widespread availability of motorized OPAs, this frequent maintenance can make frequency domain spectroscopy a cumbersome and time-consuming process. We have found that fully automated approaches to tuning are invaluable when scanning OPAs. Here, we report four algorithms that accurately and robustly tune a variety of ultrafast laser systems—picosecond and femtosecond, homebuilt and commercial OPAs. Using case studies from previously published work, we illustrate how these four algorithms can be combined to tune all motors of an ultrafast laser system. These algorithms are available through open-source software and can be applied to existing instruments, significantly lowering the threshold for executing frequency domain spectroscopy. 

Floquet state spectroscopy is an optical analogue of multiple quantum coherence nuclear magnetic resonance (MQC-NMR). Tunable ultrafast excitation pulses resonantly excite multiple states in a sample to form the Floquet state. The Floquet state emits multiple coherent beams at frequencies and in directions that conserve energy and momenta. The different output beams differ in the time ordering and coherences created by the excitation beams. They correspond to the different methodologies in the NMR family. Isolating a specific beam and monitoring the output intensity as a function of excitation frequencies creates multidimensional spectra containing cross-peaks between coupled states. The frequency range of the multidimensional spectra is limited by phase matching constraints. This paper presents a new, to the best of our knowledge, active phase matching strategy that increases the versatility of multidimensional Floquet state spectroscopy through both longer sample path lengths and larger spectral ranges. 

Studies of entangling and disentangling worms show the role of individual motions in controlling collective dynamics. 

Synopsis Many organisms exhibit collecting and gathering behaviors as a foraging and survival method. Benthic macroinvertebrates are classified as collector–gatherers due to their collection of particulate matter. Among these, the aquatic oligochaete Lumbriculus variegatus (California blackworms) demonstrates the ability to ingest both organic and inorganic materials, including microplastics. However, earlier studies have only qualitatively described their collecting behaviors for such materials. The mechanism by which blackworms consolidate discrete particles into a larger clump remains unexplored quantitatively. In this study, we analyze a group of blackworms in a large arena with an aqueous algae solution (organic particles) and find that their relative collecting efficiency is proportional to population size. We found that doubling the population size (N = 25–N = 50) results in a decrease in time to reach consolidation by more than half. Microscopic examination of individual blackworms reveals that both algae and microplastics physically adhere to the worm’s body and form clumps due to external mucus secretions by the worms. Our observations also indicate that this clumping behavior reduces the worm’s exploration of its environment, possibly due to thigmotaxis. To validate these observed biophysical mechanisms, we create an active polymer model of a worm moving in a field of particulate debris. We simulate its adhesive nature by implementing a short-range attraction between the worm and the nearest surrounding particles. Our findings indicate an increase in gathering efficiency when we add an attractive force between particles, simulating the worm’s mucosal secretions. Our work provides a detailed understanding of the complex mechanisms underlying the collecting–gathering behavior in L. variegatus, informing the design of bioinspired synthetic collector systems, and advances our understanding of the ecological impacts of microplastics on benthic invertebrates. 

Abstract Many organisms utilize group aggregation as a method for survival. The freshwater oligochaete, Lumbriculus variegatus (California blackworms) form tightly entangled structures, or worm “blobs”, that have adapted to survive in extremely low levels of dissolved oxygen (DO). Individual blackworms adapt to hypoxic environments through respiration via their mucous body wall and posterior ciliated hindgut, which they wave above them. However, the change in collective behavior at different levels of DO is not known. Using a closed-loop respirometer with flow, we discover that the relative tail reaching activity flux in low DO is ∼75x higher than in the high-DO condition. Additionally, when flow rate is increased to suspend the worm blobs upward, we find that the average exposed surface area of a blob in low DO is ∼1.4x higher than in high DO. Furthermore, we observe emergent properties that arise when a worm blob is exposed to extreme DO levels. We demonstrate that internal mechanical stress is generated when worm blobs are exposed to high DO levels, allowing them to be physically lifted off from the bottom of a conical container using a serrated endpiece. Our results demonstrate how both collective behavior and the emergent generation of internal mechanical stress in worm blobs change to accommodate differing levels of oxygen. From an engineering perspective, this could be used to model and simulate swarm robots, self-assembly structures, or soft material entanglements.