We are utilizing control of molecular processes at the quantum level via the best capabilities of recent laser
technology and recent discoveries in optimal shaping of laser pulses to significantly enhance the standoff
detection of explosives. Optimal dynamic detection of explosives (ODD-Ex) is a methodology whereby laser pulses
are optimally shaped to simultaneously enhance the sensitivity and selectivity of any of a wide variety of
spectroscopic methods for explosives signatures while reducing the influence of noise and environmental
perturbations. We discuss here recent results using complementary ODD-Ex methods.
The detection of explosives is a notoriously difficult problem, especially at stand-off distances, due to their (generally)
low vapor pressure, environmental and matrix interferences, and packaging. We are exploring optimal dynamic
detection to exploit the best capabilities of recent advances in laser technology and recent discoveries in optimal shaping
of laser pulses for control of molecular processes to significantly enhance the standoff detection of explosives. The core
of the ODD-Ex technique is the introduction of optimally shaped laser pulses to simultaneously enhance sensitivity of
explosives signatures while reducing the influence of noise and the signals from background interferents in the field
(increase selectivity). These goals are being addressed by operating in an optimal nonlinear fashion, typically with a
single shaped laser pulse inherently containing within it coherently locked control and probe sub-pulses. With sufficient
bandwidth, the technique is capable of intrinsically providing orthogonal broad spectral information for data fusion, all
from a single optimal pulse.
There are many potential applications for MEMS micromirror devices for femtosecond pulse shaping applications. Their
broadband reflectivity gives them an advantage in comparison to devices such as liquid crystal- and acousto-optical modulators
because of the possibility to directly shape UV pulses in the range 250 - 400 nm, and thus address UV-absorbing
molecules. The identification and discrimination of biomolecules which exhibit almost the same spectra has sparked
some interest in the last years as it allows real-time, environmental and optical monitoring. Here, we present the last
developments using the Fraunhofer IPMS MEMS phase former capable of accomplishing such goals.
Since the initial development of lasers in the 1960's, a longstanding dream has been to utilize these special
intense radiation (light) sources to redirect the outcome of chemical reactions. In the ensuing years, much effort has
gone into attempts at making this dream a reality. Emerging recent successful experiments derive from a confluence
of ultrafast laser technology, control theory concepts, and suitable pattern recognition algorithms all drawn together
to form adaptive machines. The adaptive machines are being used to manipulate chemical bonds, as well as a broad
variety of other atomic and molecular dynamics phenomenon. These advances rest on the ability to delicately shape
laser pulses so that they act as a special type of photonic reagents.
We investigated femtosecond pump-repump depletion excitation in biological fluorescent molecules (tryptophan and flavins) in solutions and in organic fluorescent interferents such as polycyclic hydrocarbons (naphthalene, diesel fuel). If the repump pulse induces in both flavins and Trp a depletion of the excited state, populated by the pump pulse, which leads to a drastic decrease of the fluorescence, such mechanism is ineffective in organic fluorescent interferents. The repump induced depletion is still observed for bacteria containing solutions. This opens interesting perspectives to discriminate biological from non-biological fluorescent particles in air.
Optical techniques are very promising for detecting and identifying bacterial spores. They are potentially superior to the existing “wet chemistry” approaches regarding several important features of an effective alarm system, such as speed, in-field use, continuous monitoring, and reliability. In this paper we discuss the role that computational intelligence (CI) can play in the control and optimization of optical experiments, and in the analysis and interpretation of the large amount of data they provide. After a brief discussion of the use of CI in the classification of optical spectra, we introduce the recently proposed FAST CARS (Femtosecond Adaptive Spectroscopic Techniques for Coherent Anti-Stokes Raman Scattering) technique. Here the role of CI is essential: using an adaptive feedback approach based on genetic algorithms, the hardware system evolves and organizes itself to optimize the intensity of the CARS signal.
An increasing number of experiments have demonstrated that shaped laser pulses can successfully manipulate a broad variety of quantum phenomena. These achievements are drawing on a balance of computational design and high duty cycle closed loop learning control experiments. This paper will consider the special issues involved in best utilizing these capabilities to meet the control objectives. In addition, several topics in the analysis of controlled quantum phenomena will also be considered that draw on these same capabilities.
The impact of control field fluctuations on the optimal manipulation of quantum dynamics phenomena is investigated. The presence of significant field fluctuations is shown to break down the evolution into a sequence of partially coherent robust steps. Robustness occurs because the optimization process reduces sensitivity to noise-driven quantum system fluctuations. This process takes advantage of the observable expectation value being bilinear in the evolution operator and its adjoint. The consequences of this inherent robustness bodes well for the future success of closed loop quantum optimal control experiments.
We discuss a successful application of evolutionary algorithms and femtosecond pulse-shaping technology to the coherent control of quantum phenomena. After a brief review of the field of quantum control, we show how evolutionary algorithms provide an effective and, so far, the only general solution to the problem of managing the complex interplay of interference effects which characterize quantum phenomena. A representative list of experimental results is presented, and some directions for future developments are discussed. The success of evolutionary algorithms in quantum control is seen as a significant step in the evolution of computational intelligence, from evolutionary algorithms, to evolutionary programming, to evolutionary engineering, whereby a hardware system organizes itself and evolves on line to achieve a desired result.
This paper gives an overview of the logic behind current conceptual issues directed towards controlling quantum phenomena. The role of theory to translate these concepts into laboratory designs will be highlighted, along with an explanation of the complexities of achieving realistic designs. As a result, it will be argued that closed-loop feedback control of quantum dynamics in the laboratory is not only feasible, but will typically be a necessity for the achievement of practical control over quantum phenomena.