Abstract
Coherent control employing a broadband excitation is applied to a branching reaction in the excited state. In a weak field for an isolated molecule, a control objective is only frequency dependent. This means that phase control of the pulse cannot improve the objective beyond the best frequency selection. Once the molecule is put into a dissipative environment a new timescale emerges. In this study, we demonstrate that the dissipation allows us to achieve coherent control of branching ratios in the excited state. The model studied contains a nuclear coordinate and three electronic states: the ground and two coupled diabatic excited states. The influence of the environment is modeled by the stochastic surrogate Hamiltonian. The excitation is generated by a Gaussian pulse where the phase control introduced a chirp to the pulse. For sufficient relaxation, we find significant control in the weak field depending on the chirp rate. The observed control is rationalized by a timing argument caused by a focused wavepacket. The initial non-adiabatic crossing is enhanced by the chirp. This is followed by energy relaxation which stabilizes the state by having an energy lower than the crossing point.
Highlights
The model describes a molecular system coupled to a radiation field
The primary bath Hamiltonian is composed of a collection of two-level systems (TLS)
Weak field control has been an outstanding issue in recent years
Summary
The model describes a molecular system coupled to a radiation field. It could describe a simplified model of a dye molecule in solution [5]. Primary and secondary bath modes of the same frequency are swapped [16]. In a full swap operation, the primary bath mode is reset to a state φ with thermal amplitudes and random phases: φj =. Bath parameters Number of bath modes Cut-off frequency (ωc) System–bath coupling (γ ) Swap rate ( /λ). Each swap operation resets the phase of the j mode, collapsing the system–bath state to an uncorrelated product with the j mode. Accumulating many such random events is equivalent to dephasing [23]. Convergence of the model is checked by increasing the number of bath modes and the number of stochastic realizations
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
