Steady state behaviour in atomic three-level lambda and ladder systems with incoherent population pumping

The steady state in three-level lambda and ladder systems is studied. It is well-known that in a lambda system this steady state is the coherent population trapping state, independent of the presence of spontaneous emission. In contrast, the steady state in a ladder system is in general not stable against radiative decay and exhibits a minimum in the population of the ground state. It is shown that incoherent population pumping destroys the stability of the coherent population trapping state in the lambda system and suppresses a previously discovered sharp dip in the steady state response. In the ladder system the observed minimum disappears in the presence of an incoherent pump on the upper transition.Comment: 4 pages, RevTex, 5 figures, to appear in Phys. Rev.

Uncertainty-Aware Organ Classification for Surgical Data Science Applications in Laparoscopy

Objective: Surgical data science is evolving into a research field that aims to observe everything occurring within and around the treatment process to provide situation-aware data-driven assistance. In the context of endoscopic video analysis, the accurate classification of organs in the field of view of the camera proffers a technical challenge. Herein, we propose a new approach to anatomical structure classification and image tagging that features an intrinsic measure of confidence to estimate its own performance with high reliability and which can be applied to both RGB and multispectral imaging (MI) data. Methods: Organ recognition is performed using a superpixel classification strategy based on textural and reflectance information. Classification confidence is estimated by analyzing the dispersion of class probabilities. Assessment of the proposed technology is performed through a comprehensive in vivo study with seven pigs. Results: When applied to image tagging, mean accuracy in our experiments increased from 65% (RGB) and 80% (MI) to 90% (RGB) and 96% (MI) with the confidence measure. Conclusion: Results showed that the confidence measure had a significant influence on the classification accuracy, and MI data are better suited for anatomical structure labeling than RGB data. Significance: This work significantly enhances the state of art in automatic labeling of endoscopic videos by introducing the use of the confidence metric, and by being the first study to use MI data for in vivo laparoscopic tissue classification. The data of our experiments will be released as the first in vivo MI dataset upon publication of this paper.Comment: 7 pages, 6 images, 2 table

Matched Pulse Propagation in a Three-Level System

The B\"{a}cklund transformation for the three-level Maxwell-Bloch equation is presented in the matrix potential formalism. By applying the B\"{a}cklund transformation to a constant electric field background, we obtain a general solution for matched pulses (a pair of solitary waves) which can emit or absorb a light velocity solitary pulse but otherwise propagate with their shapes invariant. In the special case, this solution describes a steady state pulse without emission or absorption, and becomes the matched pulse solution recently obtained by Hioe and Grobe. A nonlinear superposition rule is derived from the B\"{a}cklund transformation and used for the explicit construction of two solitons as well as nonabelian breathers. Various new features of these solutions are addressed. In particular, we analyze in detail the scattering of "invertons", a specific pair of different wavelength solitons one of which moving with the velocity of light. Unlike the usual case of soliton scattering, the broader inverton changes its sign through the scattering. Surprisingly, the light velocity inverton receives time advance through the scattering thereby moving faster than light, which however does not violate causality.Comment: 20 pages, Latex, 12 eps figure files some comments and references are added. postscript file with 12 figures can be obtained at http://photon.kyunghee.ac.kr/~qhpark

Narrowing of EIT resonance in a Doppler Broadened Medium

We derive an analytic expression for the linewidth of EIT resonance in a Doppler broadened system. It is shown here that for relatively low intensity of the driving field the EIT linewidth is proportional to the square root of intensity and is independent of the Doppler width, similar to the laser induced line narrowing effect by Feld and Javan. In the limit of high intensity we recover the usual power broadening case where EIT linewidth is proportional to the intensity and inversely proportional to the Doppler width.Comment: 4 pages, 2 figure

Enhanced four-wave mixing via elimination of inhomogeneous broadening by coherent driving of quantum transition with control fields

We show that atoms from wide velocity interval can be concurrently involved in Doppler-free two-photon resonant far from frequency degenerate four-wave mixing with the aid of auxiliary electromagnetic field. This gives rise to substantial enhancement of the output radiation generated in optically thick medium. Numerical illustrations addressed to typical experimental conditions are given.Comment: LaTeX2e, hyperref, 7 pages, 5 figures, to appear in PRA 1 august 200

Phase-dependent spectra in a driven two-level atom

We propose a method to observe phase-dependent spectra in resonance fluorescence, employing a two-level atom driven by a strong coherent field and a weak, amplitude-fluctuating field. The spectra are similar to those which occur in a squeezed vacuum, but avoid the problem of achieving squeezing over a $4\pi$ solid angle. The system shows other interesting features, such as pronounced gain without population inversion.Comment: 4 pages and 4 figures. Submitted to Phys. Rev. Let

Physiological parameter estimation from multispectral images unleashed

Multispectral imaging in laparoscopy can provide tissue reflectance measurements for each point in the image at multiple wavelengths of light. These reflectances encode information on important physiological parameters not visible to the naked eye. Fast decoding of the data during surgery, however, remains challenging. While model-based methods suffer from inaccurate base assumptions, a major bottleneck related to competing machine learning-based solutions is the lack of labelled training data. In this paper, we address this issue with the first transfer learning-based method to physiological parameter estimation from multispectral images. It relies on a highly generic tissue model that aims to capture the full range of optical tissue parameters that can potentially be observed in vivo. Adaptation of the model to a specific clinical application based on unlabelled in vivo data is achieved using a new concept of domain adaptation that explicitly addresses the high variance often introduced by conventional covariance-shift correction methods. According to comprehensive in silico and in vivo experiments our approach enables accurate parameter estimation for various tissue types without the need for incorporating specific prior knowledge on optical properties and could thus pave the way for many exciting applications in multispectral laparoscopy