Related papers: Bayesian modelling and quantification of Raman spe…
Optical detection and spectroscopy of single molecules has become an indispensable tool in biological imaging and sensing. Its success is based on fluorescence of organic dye molecules under carefully engineered laser illumination. In this…
Magnetic resonance spectroscopy (MRS) is an important technique in biomedical research and it has the unique capability to give a non-invasive access to the biochemical content (metabolites) of scanned organs. In the literature, the…
We describe an efficient Monte Carlo algorithm for a restricted class of scattering problems in radiation transfer. This class includes many astrophysically interesting problems, including the scattering of ultraviolet and visible light by…
Raman spectroscopy is an important tool in the study of vibrational properties and composition of molecules, peptides and even proteins. Raman spectra can be simulated based on the change of the electronic polarizability with vibrations,…
In Cowell et al. (2007), a Bayesian network for analysis of mixed traces of DNA was presented using gamma distributions for modelling peak sizes in the electropherogram. It was demonstrated that the analysis was sensitive to the choice of a…
Variational ab-initio methods in quantum chemistry stand out among other methods in providing direct access to the wave function. This allows in principle straightforward extraction of any other observable of interest, besides the energy,…
Quantum entanglement has emerged as a great resource for interactions between molecules and radiation. We propose a new paradigm of stimulated Raman scattering with entangled photons. A quantum ultrafast Raman spectroscopy is developed for…
We present a Bayesian approach to probabilistically infer vertical activity profiles within a radioactive waste drum from segmented gamma scanning (SGS) measurements. Our approach resorts to Markov chain Monte Carlo (MCMC) sampling using…
Propagation of light in a highly scattering medium is among the most fascinating optical effect that everyone experiences on an everyday basis and possesses a number of fundamental problems which have yet to be solved. Conventional wisdom…
Light scattering limits the penetration depth of non-invasive Raman spectroscopy in biological media. While safe levels of irradiation may be adequate to analyze superficial tissue, scattering of the pump beam reduces the Raman signal to…
Non-invasive light scattering methods provide data on biological macromolecules (i.e. proteins, nucleic acids, as well as assemblies and larger entities composed of them) that are complementary with those of size exclusion chromatography,…
Raman lasers are used as a spectroscopic probe of the state of atoms confined in a shallow 1D vertical lattice. For long enough laser pulses, resolved transitions in the bottom band of the lattice between Wannier Stark states corresponding…
In general, most of the substances in nature exist in mixtures, and the noninvasive identification of mixture composition with high speed and accuracy remains a difficult task. However, the development of Raman spectroscopy, machine…
One of the key challenges in identifying nonlinear and possibly non-Gaussian state space models (SSMs) is the intractability of estimating the system state. Sequential Monte Carlo (SMC) methods, such as the particle filter (introduced more…
Raman spectroscopy is a promising technique used for noninvasive analysis of samples in various fields of application due to its ability for fingerprint probing of samples at the molecular level. Chemometrics methods are widely used…
Collinear laser spectroscopy of fast atomic beams has been established as one of the main tools to perform precision experiments with atoms containing short-lived nuclei. Although highly sensitive, the spectral resolution of these…
Monte Carlo simulations have been performed in order to evaluate the efficiencies of several light ions identification techniques. The detection system was composed with layers of scintillating material to measure either the deposited…
Bayesian inference in deep neural networks is challenging due to the high-dimensional, strongly multi-modal parameter posterior density landscape. Markov chain Monte Carlo approaches asymptotically recover the true posterior but are…
Precision measurements of nucleons provide constraints on the Standard Model and can discern the signatures predicted for particles beyond the Standard Model (BSM). Knowing the Standard Model inputs to nucleon matrix elements will be…
The application of molecular dynamics (MD) simulations to the interpretation of Raman scattering spectra is hindered by inability of atomistic simulations to account for the dynamic evolution of electronic polarizability, requiring the use…