Jonathan Roslund

Wavelength-multiplexed quantum networks with ultrafast frequency combs

Single-step fabrication of a multimode quantum resource from the parametric downconversion of femtosecond frequency combs is demonstrated. Each of the 511 possible bipartitions among ten spectral regions is shown to be entangled. Furthermore, an eigenmode decomposition reveals that eight independent quantum channels (qumodes) are subsumed within the comb.

Resolution of strongly competitive product channels with optimal dynamic discrimination: application to flavins.

Fundamental molecular selectivity limits are probed by exploiting laser-controlled quantum interferences for the creation of distinct spectral signatures in two flavin molecules, erstwhile nearly indistinguishable via steady-state methods. Optimal dynamic discrimination (ODD) uses optimally shaped laser fields to transiently amplify minute molecular variations that would otherwise go unnoticed with linear absorption and fluorescence techniques. ODD is experimentally demonstrated by combining an optimally shaped UV pump pulse with a time-delayed, fluorescence-depleting IR pulse for discrimination amongst riboflavin and flavin mononucleotide in aqueous solution, which are structurally and spectroscopically very similar. Closed-loop, adaptive pulse shaping discovers a set of UV pulses that induce disparate responses from the two flavins and allows for concomitant flavin discrimination of ∼16σ. Additionally, attainment of ODD permits quantitative, analytical detection of the individual constituents in a flavin mixture. The successful implementation of ODD on quantum systems of such high complexity bodes well for the future development of the field and the use of ODD techniques in a variety of demanding practical applications.

Experimental quantum control landscapes: Inherent monotonicity and artificial structure

Unconstrained searches over quantum control landscapes are theoretically predicted to generally exhibit trap-free monotonic behavior. This paper makes an explicit experimental demonstration of this intrinsic monotonicity for two controlled quantum systems: frequency unfiltered and filtered second-harmonic generation (SHG). For unfiltered SHG, the landscape is randomly sampled and interpolation of the data is found to be devoid of landscape traps up to the level of data noise. In the case of narrow-band-filtered SHG, trajectories are taken on the landscape to reveal a lack of traps. Although the filtered SHG landscape is trap free, it exhibits a rich local structure. A perturbation analysis around the top of these landscapes provides a basis to understand their topology. Despite the inherent trap-free nature of the landscapes, practical constraints placed on the controls can lead to the appearance of artificial structure arising from the resultant forced sampling of the landscape. This circumstance and the likely lack of knowledge about the detailed local landscape structure in most quantum control applications suggests that the a priori identification of globally successful (un)constrained curvilinear control variables may be a challenging task.

Quantum control experiments as a testbed for evolutionary multi-objective algorithms

Experimental multi-objective Quantum Control is an emerging topic within the broad physics and chemistry applications domain of controlling quantum phenomena. This realm offers cutting edge ultrafast laser laboratory applications, which pose multiple objectives, noise, and possibly constraints on the high-dimensional search. In this study we introduce the topic of multi-observable quantum control (MOQC), and consider specific systems to be Pareto optimized subject to uncertainty, either experimentally or by means of simulated systems. The latter include a family of mathematical test-functions with a practical link to MOQC experiments, which are introduced here for the first time. We investigate the behavior of the multi-objective version of the covariance aatrix adaptation evolution strategy (MO-CMA-ES) and assess its performance on computer simulations as well as on laboratory closed-loop experiments. Overall, we propose a comprehensive study on experimental evolutionary Pareto optimization in high-dimensional continuous domains, draw some practical conclusions concerning the impact of fitness disturbance on algorithmic behavior, and raise several theoretical issues in the broad evolutionary multi-objective context.

Assessing and managing laser system stability for quantum control experiments

Stable laser operation, which is essential for quantum control experiments as well as many other phase dependent processes, is investigated with respect to the influence of amplitude and spectral phase noise. Simulations are first performed and an easy to implement experimental method is presented to monitor the amplitude and phase stability of an ultrafast laser system. As an illustration of this stability assessment technique, the data monitoring is used to guide the identification and elimination of fluctuations in the laser amplification process. Through a number of practical alterations of the amplifier configuration, the stability of the laser system was greatly and consistently improved. Fluctuations on different time scales were eliminated, with special emphasis given to maintaining a stable spectral phase.

Spectral noise correlations of an ultrafast frequency comb.

Cavity-based noise detection schemes are combined with ultrafast pulse shaping as a means to diagnose the spectral correlations of both the amplitude and phase noise of an ultrafast frequency comb. The comb is divided into ten spectral regions, and the distribution of noise as well as the correlations between all pairs of spectral regions are measured against the quantum limit. These correlations are then represented in the form of classical noise matrices, which furnish a complete description of the underlying comb dynamics. Their eigendecomposition reveals a set of theoretically predicted, decoupled noise modes that govern the dynamics of the comb. These matrices also contain the information necessary to deduce macroscopic noise properties of the comb.

Control of nitromethane photoionization efficiency with shaped femtosecond pulses.

The applicability of adaptive femtosecond pulse shaping is studied for achieving selectivity in the photoionization of low-density polyatomic targets. In particular, optimal dynamic discrimination (ODD) techniques exploit intermediate molecular electronic resonances that allow a significant increase in the photoionization efficiency of nitromethane with shaped near-infrared femtosecond pulses. The intensity bias typical of high-photon number, nonresonant ionization is accounted for by reference to a strictly intensity-dependent process. Closed-loop adaptive learning is then able to discover a pulse form that increases the ionization efficiency of nitromethane by ∼150%. The optimally induced molecular dynamics result from entry into a region of parameter space inaccessible with intensity-only control. Finally, the discovered pulse shape is demonstrated to interact with the molecular system in a coherent fashion as assessed from the asymmetry between the response to the optimal field and its time-reversed counterpart.

Optimal dynamic detection of explosives

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.

Optimization of networks for measurement-based quantum computation

This work introduces optimization strategies to continuous variable measurement based quantum computation (MBQC) at different levels. We provide a recipe for mitigating the effects of finite squeezing, which affect the production of cluster states and the result of a traditional MBQC. These strategies are readily implementable by several experimental groups. Furthermore, a more general scheme for MBQC is introduced that does not necessarily rely on the use of ancillary cluster states to achieve its aim, but rather on the detection of a resource state in a suitable mode basis followed by digital post-processing. A recipe is provided to optimize the adjustable parameters that are employed within this framework.

Evolutionary multi-objective quantum control experiments with the covariance matrix adaptation

Experimental multi-objective Quantum Control is an emerging topic within the broad physics and chemistry application domain of controlling quantum phenomena. This realm offers cutting edge ultrafast laser laboratory applications, which pose multiple objectives, noise, and possibly constraints on the high-dimensional search. In this study we introduce the topic of Multi-Objective Quantum Control (MOQC), and consider specific systems to be Pareto optimized subject to uncertainty (noise), either experimentally or by means of simulated systems. Unlike the vast majority of other reported systems, the current modeling of noise considers additive Gaussian noise on the input (decision) parameters, which propagates in an unknown manner to the observable (fitness) values. We employ the multi-objective version of the CMA-ES (MO-CMA), which, to the best of our knowledge, is applied here for the first time to a real-world experimental problem, and assess its performance on the investigated systems. In particular, we study its empirical behavior on the MOQC noisy systems, as well as on the Multi-Sphere model landscape, in light of previous theoretical studies on single-objective single-parent Evolution Strategies, and draw some practical conclusions concerning the projection of fitness disturbance on the perceived Pareto front and the need for parental fitness reevaluation in elitist strategies. We show that elitism diminishes the value of the archived Pareto set, even when the perceived Pareto front is well approximated to the true front.