Related papers: Investigating the effect of non-resonant backgroun…
Coherent anti-Stokes Raman scattering (CARS) microspectroscopy has demonstrated significant potential for biological and materials imaging. To date, however, the primary mechanism of disseminating CARS spectroscopic information is through…
Removing distortions in coherent anti-Stokes Raman scattering (CARS) spectra due to interference with the nonresonant background (NRB) is vital for quantitative analysis. Popular computational approaches, the Kramers-Kronig relation and the…
We report stimulated Raman spectroscopy of the G phonon in both single and multi-layer graphene, through Coherent anti-Stokes Raman Scattering (CARS). The signal generated by the third order nonlinearity is dominated by a vibrationally…
Coherent anti-Stokes Raman scattering (CARS) spectroscopy is a powerful and rapid technique widely used in medicine, material science, and chemical analyses. However, its effectiveness is hindered by the presence of a non-resonant…
Raman spectroscopy has attracted interest as a non-invasive optical technique to study the composition and structure of a wide range of materials at the microscopic level. The intrinsic fluorescence background can be orders of magnitude…
Autonomous Raman instruments on Mars rovers, deep-sea landers, and field robots must interpret raw spectra distorted by fluorescence baselines, peak shifts, and limited ground-truth labels. Using curated subsets of the RRUFF database, we…
Noise manifests ubiquitously in nonlinear spectroscopy, where multiple sources contribute to experimental signals generating interrelated unwanted components, from random point-wise fluctuations to structured baseline signals. Mitigating…
The ability to enhance resonant signals and eliminate the non-resonant background is analyzed for Coherent Anti-Stokes Raman Scattering (CARS). The analysis is done at a specific frequency as well as for broadband excitation using…
Coherent Raman scattering provides highly sensitive vibrational analysis through nonlinear light-matter interactions. However, its application to metal interfaces has remained challenging because the intrinsically large non-resonant…
Kernel ridge regression (KRR) is a foundational tool in machine learning, with recent work emphasizing its connections to neural networks. However, existing theory primarily addresses the i.i.d. setting, while real-world data often exhibits…
CrSBr, a van der Waals material, stands out as an air-stable magnetic semiconductor with appealing intrinsic properties such as crystalline anisotropy, quasi-1D electronic characteristics, layer-dependent antiferromagnetism, and non-linear…
Raman spectroscopy is a powerful experimental technique for characterizing molecules and materials that is used in many laboratories. First-principles theoretical calculations of Raman spectra are important because they elucidate the…
Raman spectroscopy is an effective, low-cost, non-intrusive technique often used for chemical identification. Typical approaches are based on matching observations to a reference database, which requires careful preprocessing, or supervised…
We propose a novel approach using Multiplex-Coherent Anti-Stokes Raman Scattering (M-CARS) for la-bel-free discriminations in biomedical tissues. The strategy is based on the evaluation of the contrast be-tween resonant and nonresonant…
Raman spectroscopy is a powerful analytical tool with applications ranging from quality control to cutting edge biomedical research. One particular area which has seen tremendous advances in the past decade is the development of powerful…
The success of any machine learning system depends critically on effective representations of data. In many cases, it is desirable that a representation scheme uncovers the parts-based, additive nature of the data. Of current representation…
Raman spectroscopy is a powerful and non-invasive method for analysis of chemicals and detection of unknown substances. However, Raman signal is so weak that background noise can distort the actual Raman signal. These baseline shifts that…
We propose a new technique for comparing two Raman active samples. The method employs optical interference of the signals generated via coherent anti-Stokes Raman scattering (CARS) of broadband laser pulses with noisy spectra. It does not…
Broadband coherent anti-Stokes Raman scattering (BCARS) is an advanced Raman spectroscopy method that combines the spectral sensitivity of spontaneous Raman scattering (SR) with the increased signal intensity of single-frequency coherent…
Nonlinear optical methods, such as coherent anti-Stokes Raman scattering (CARS) and stimulated Raman scattering (SRS), are able to perform label free imaging, with chemical bonds specificity. Here, we demonstrate that the use of circularly…