Nonlinear evolution of coarse-grained quantum systems with generalized purity constraints

Constrained quantum dynamics is used to propose a nonlinear dynamical equation for pure states of a generalized coarse-grained system. The relevant constraint is given either by the generalized purity or by the generalized invariant fluctuation, and the coarse-grained pure states correspond to the generalized coherent i.e. generalized nonentangled states. Open system model of the coarse-graining is discussed. It is shown that in this model and in the weak coupling limit the constrained dynamical equations coincide with an equation for pointer states, based on Hilbert-Schmidt distance, that was previously suggested in the context of the decoherence theory

Long-time electron spin storage via dynamical suppression of hyperfine-induced decoherence in a quantum dot

The coherence time of an electron spin decohered by the nuclear spin environment in a quantum dot can be substantially increased by subjecting the electron to suitable dynamical decoupling sequences. We analyze the performance of high-level decoupling protocols by using a combination of analytical and exact numerical methods, and by paying special attention to the regimes of large inter-pulse delays and long-time dynamics, which are outside the reach of standard average Hamiltonian theory descriptions. We demonstrate that dynamical decoupling can remain efficient far beyond its formal domain of applicability, and find that a protocol exploiting concatenated design provides best performance for this system in the relevant parameter range. In situations where the initial electron state is known, protocols able to completely freeze decoherence at long times are constructed and characterized. The impact of system and control non-idealities is also assessed, including the effect of intra-bath dipolar interaction, magnetic field bias and bath polarization, as well as systematic pulse imperfections. While small bias field and small bath polarization degrade the decoupling fidelity, enhanced performance and temporal modulation result from strong applied fields and high polarizations. Overall, we find that if the relative errors of the control parameters do not exceed 5%, decoupling protocols can still prolong the coherence time by up to two orders of magnitude.Comment: 16 pages, 10 figures, submitted to Phys. Rev.

Dynamical control of electron spin coherence in a quantum dot

We investigate the performance of dynamical decoupling methods at suppressing electron spin decoherence from a low-temperature nuclear spin reservoir in a quantum dot. The controlled dynamics is studied through exact numerical simulation, with emphasis on realistic pulse delays and long-time limit. Our results show that optimal performance for this system is attained by a periodic protocol exploiting concatenated design, with control rates substantially slower than expected from the upper spectral cutoff of the bath. For a known initial electron spin state, coherence can saturate at long times, signaling the creation of a stable ``spin-locked'' decoherence-free subspace. Analytical insight on saturation is obtained for a simple echo protocol, in good agreement with numerical results.Comment: 4 pages, 4 figures with 3 of them in colo

Suppression of electron spin decoherence in a quantum dot

The dominant source of decoherence for an electron spin in a quantum dot is the hyperfine interaction with the surrounding bath of nuclear spins. The decoherence process may be slowed down by subjecting the electron spin to suitable sequences of external control pulses. We investigate the performance of a variety of dynamical decoupling protocols using exact numerical simulation. Emphasis is given to realistic pulse delays and the long-time limit, beyond the domain where available analytical approaches are guaranteed to work. Our results show that both deterministic and randomized protocols are capable to significantly prolong the electron coherence time, even when using control pulse separations substantially larger than what expected from the {\em upper cutoff} frequency of the coupling spectrum between the electron and the nuclear spins. In a realistic parameter range, the {\em total width} of such a coupling spectrum appears to be the physically relevant frequency scale affecting the overall quality of the decoupling.Comment: 8 pages, 3 figures. Invited talk at the XXXVII Winter Colloquium on the Physics of Quantum Electronics, Snowbird, Jan 2007. Submitted to J. Mod. Op

Computational Modelling of Water Transport in Hydrocolloid Wound Dressing, DuoDERMⓇ CGF, and Design Recommendations

Hydrocolloids, and further hydrogels, have arisen as attractive next-generation wound dressings because of their modularity and ability to retain moisture. Hydrocolloids, like DuoDERM Ⓡ CGF, are intended for partial and full thickness wounds. They may be used for minor burns, cuts, tears, abrasions, as well as lacerations, ulcers, and some traumatic or surgical wounds. A computational simulation of water transport in wounds with hydrocolloid dressings was implemented in order to understand the mechanisms of hydrocolloid wound dressings as they relate to water transport. The ideal dressing will maintain the wounded tissue at physiological water content levels while also retaining moisture within the dressing itself to promote re-epithelialization of tissue. This study aims to determine the effectiveness of current wound dressings with respect to retaining moisture and maintaining the skin at physiological levels of water content. This study further seeks to optimize current wound dressing design parameters in order to improve water retention above the wound bed and maintenance of physiological skin water content. To study the transfer of liquid water in skin and an example hydrocolloid wound dressing, a computational model was built in COMSOL Multiphysics Ⓡ Modeling Software using a multifrontal direct solver (MUMPS). This model primarily detailed water transport processes in the skin (stratum corneum, epidermis, and dermis) with an example hydrocolloid dressing DuoDERM Ⓡ CGF (hydrocolloid and polymeric barrier layer). The use of the model can be extended to larger or smaller wound areas as well as different types of hydrocolloid dressings. The parameters of the materials can be easily altered to fit new materials being simulated, however the model is only valid up to the time right before the hydrocolloid would start to degrade. The model considered the skin layers, wound surface, hydrocolloid, and polymeric barrier layer to be a 2D, axisymmetric cylinder. Water (mass) transport was considered diffusion in porous media in the skin and diffusion in the hydrocolloid and polymeric layers. The swelling effect, typical of hydrocolloids, was modeled using deforming geometry. After validating the model, an objective function was created in order to quantify the performance of the model based on its ability to maintain physiological water content in the skin as well as its ability to retain moisture in the hydrocolloid domain above the wound bed. Using this objective function, the material properties of the hydrocolloid dressing were altered in order to obtain an optimal solution, where the dressing would maintain an ideally moist environment. The results confirmed that the hydrocolloid wound dressing retains moisture but does not satisfactorily maintain wounded tissue near physiological levels of water content. The optimization suggested the variation of two hydrocolloid parameters, the diffusivity and the partitioning coefficient between the skin and hydrocolloid, in order to improve its performance. Lowering the diffusivity of the hydrocolloid resulted in a higher water concentration above the wound bed. Decreasing the partition coefficient (an effect observed by increasing the hydrophobicity of the hydrocolloid) reduced the flux of water from the wound to the dressing. The combined effect of a reduced diffusivity and partition coefficient allowed greater regions of the wound to retain physiological water content levels and improved water retention near the wound bed. These results will inform the design of future generations of wound dressings and elucidate difficulties in the use of hydrophilic wound dressings like hydrocolloids and hydrogels

Multi-Instance Multi-Label Learning

In this paper, we propose the MIML (Multi-Instance Multi-Label learning) framework where an example is described by multiple instances and associated with multiple class labels. Compared to traditional learning frameworks, the MIML framework is more convenient and natural for representing complicated objects which have multiple semantic meanings. To learn from MIML examples, we propose the MimlBoost and MimlSvm algorithms based on a simple degeneration strategy, and experiments show that solving problems involving complicated objects with multiple semantic meanings in the MIML framework can lead to good performance. Considering that the degeneration process may lose information, we propose the D-MimlSvm algorithm which tackles MIML problems directly in a regularization framework. Moreover, we show that even when we do not have access to the real objects and thus cannot capture more information from real objects by using the MIML representation, MIML is still useful. We propose the InsDif and SubCod algorithms. InsDif works by transforming single-instances into the MIML representation for learning, while SubCod works by transforming single-label examples into the MIML representation for learning. Experiments show that in some tasks they are able to achieve better performance than learning the single-instances or single-label examples directly.Comment: 64 pages, 10 figures; Artificial Intelligence, 201

Towards a reliable face recognition system.

Face Recognition (FR) is an important area in computer vision with many applications such as security and automated border controls. The recent advancements in this domain have pushed the performance of models to human-level accuracy. However, the varying conditions in the real-world expose more challenges for their adoption. In this paper, we investigate the performance of these models. We analyze the performance of a cross-section of face detection and recognition models. Experiments were carried out without any preprocessing on three state-of-the-art face detection methods namely HOG, YOLO and MTCNN, and three recognition models namely, VGGface2, FaceNet and Arcface. Our results indicated that there is a significant reliance by these methods on preprocessing for optimum performance