We analyze pulse self-compression in femtosecond filaments, both experimentally and numerically. We experimentally demonstrate the compression of 45 fs pulses down to a duration of 7.4 fs at millijoule pulse energies. This sixfold compression in a self-generated filament does not require any means for dispersion compensation and is highly efficient. We compare our results to numerical simulations, providing a complete propagation model that accounts for full dispersion, pressure variations, Kerr nonlinearity and plasma generation in multiphoton and tunnel regimes. The equations are numerically integrated and allow for a quantitative comparison with the experiment. Our experiments and numerical simulations reveal a characteristic spectrotemporal structure of the self-compressed pulses, consisting of a compressible blue wing and an incompressible red pedestal. We explain the underlying mechanism that leads to this structure and examine the scalability of filament self-compression with respect to pulse energy and gas pressure.
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http://dx.doi.org/10.1103/PhysRevE.74.056604 | DOI Listing |
BMC Med Res Methodol
January 2025
Division of Public Health Sciences, Washington University in St Louis, 660 S. Euclid Ave, St Louis, MO, 63110, USA.
Background: Propensity Score Matching (PSM) stands as a widely embraced method in comparative effectiveness research. PSM crafts matched datasets, mimicking some attributes of randomized designs, from observational data. In a valid PSM design where all baseline confounders are measured and matched, the confounders would be balanced, allowing the treatment status to be considered as if it were randomly assigned.
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January 2025
School of Civil Engineering, Qingdao University of Technology, Qingdao, 266520, People's Republic of China.
Accurately predicting the phase behavior and properties of reservoir fluid plays an essential role in the simulation of petroleum recovery processes. Similar to the inaccurate liquid-density prediction issue in the isobaric-isothermal (PT) phase equilibrium calculations, an inaccurate pressure prediction issue can also be observed in isothermal-isochoric (VT) phase equilibrium calculations which involves a liquid phase. In this work, a practical methodology is proposed to incorporate a volume-translated equation of state in VT phase equilibrium calculations for more accurate pressure predictions.
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January 2025
Department of Mathematics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, 602105, India.
In this study, we investigate the [Formula: see text]-D Jaulent-Miodek (JM) equation, which is significant due to its energy-based Schrödinger potential and applications in fields such as optics, soliton theory, signal processing, geophysics, fluid dynamics, and plasma physics. Given its broad utility, a rigorous mathematical analysis of the JM equation is essential. The primary objective of this work is to derive exact soliton solutions using the Modified Sub-Equation (MSE) and Modified Auxiliary Equation (MAE) techniques.
View Article and Find Full Text PDFJ R Soc Interface
January 2025
Department of Engineering Mechanics, KTH Royal Institute of Technology, Stockholm, Sweden.
Culturing living cells in three-dimensional environments increases the biological relevance of laboratory experiments, but requires solutes to overcome a diffusion barrier to reach the centre of cellular constructs. We present a theoretical and numerical investigation that brings a mechanistic understanding of how microfluidic culture conditions, including chamber size, inlet fluid velocity and spatial confinement, affect solute distribution within three-dimensional cellular constructs. Contact with the chamber substrate reduces the maximally achievable construct radius by 15%.
View Article and Find Full Text PDFBiomed Phys Eng Express
January 2025
Applied Sciences, Indian Institute of Information Technology Allahabad, Deoghat, Jhalwa, Allahabad, 211012, INDIA.
Photoacoustic tomography (PAT) is a non-destructive, non-ionizing, and rapidly expanding hybrid biomedical imaging technique, yet it faces challenges in obtaining clear images due to limited data from detectors or angles. As a result, the methodology suffers from significant streak artifacts and low-quality images. The integration of deep learning (DL), specifically convolutional neural networks (CNNs), has recently demonstrated powerful performance in various fields of PAT.
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