q-Analog of Gelfand-Graev Basis for the Noncompact Quantum Algebra U_q(u(n,1))

For the quantum algebra U_q(gl(n+1)) in its reduction on the subalgebra U_q(gl(n)) an explicit description of a Mickelsson-Zhelobenko reduction Z-algebra Z_q(gl(n+1),gl(n)) is given in terms of the generators and their defining relations. Using this Z-algebra we describe Hermitian irreducible representations of a discrete series for the noncompact quantum algebra U_q(u(n,1)) which is a real form of U_q(gl(n+1)), namely, an orthonormal Gelfand-Graev basis is constructed in an explicit form.Comment: Invited talk given by V.N.T. at XVIII International Colloquium "Integrable Systems and Quantum Symmetries", June 18--20, 2009, Prague, Czech Republi

Determination of tip transfer function for quantitative MFM using frequency domain filtering and least squares method

Magnetic force microscopy has unsurpassed capabilities in analysis of nanoscale and microscale magnetic samples and devices. Similar to other Scanning Probe Microscopy techniques, quantitative analysis remains a challenge. Despite large theoretical and practical progress in this area, present methods are seldom used due to their complexity and lack of systematic understanding of related uncertainties and recommended best practice. Use of the Tip Transfer Function (TTF) is a key concept in making Magnetic Force Microscopy measurements quantitative. We present a numerical study of several aspects of TTF reconstruction using multilayer samples with perpendicular magnetisation. We address the choice of numerical approach, impact of non-periodicity and windowing, suitable conventions for data normalisation and units, criteria for choice of regularisation parameter and experimental effects observed in real measurements. We present a simple regularisation parameter selection method based on TTF width and verify this approach via numerical experiments. Examples of TTF estimation are shown on both 2D and 3D experimental datasets. We give recommendations on best practices for robust TTF estimation, including the choice of windowing function, measurement strategy and dealing with experimental error sources. A method for synthetic MFM data generation, suitable for large scale numerical experiments is also presented

Round robin comparison on quantitative nanometer scale magnetic field measurements by magnetic force microscopy

Magnetic force microscopy (MFM) can be considered as a standard tool for nano-scale investigation of magnetic domain structures by probing the local stray magnetic field landscape of the measured sample. However, this generally provides only qualitative data. To quantify the stray magnetic fields, the MFM system must be calibrated. To that end, a transfer function (TF) approach was proposed, that, unlike point probe models, fully considers the finite extent of the MFM tip. However, albeit being comprehensive, the TF approach is not yet well established, mainly due to the ambiguities concerning the input parameters and the measurement procedure. Additionally, the calibration process represents an ill-posed problem which requires a regularization that introduces further parameters. In this paper we propose a guideline for quantitative stray field measurements by standard MFM tools in ambient conditions. All steps of the measurement and calibration procedure are detailed, including reference sample and sample under test (SUT) measurements and the data analysis. The suitability of the reference sample used in the present work for calibrated measurements on a sub-micron scale is discussed. A specific regularization approach based on a Pseudo-Wiener Filter is applied and combined with criteria for the numerical determination of a unique regularization parameter. To demonstrate the robustness of such a defined approach, a round robin comparison of magnetic field measurements was conducted by four laboratories. The guideline, the reference sample and the results of the round robin are discussed

New calix[4]arene-based amides - Their synthesis, conformation, complexation

New chiral calix[4]arene-based diol-diamides 1a, 1b, tetraamides 2a, 2b and 7 as well as achiral diamide 3 and tetraamides 4-6 were prepared. The conformation of 1 has been studied in solution by NMR and in solid state by X-ray crystallography. The pinched-cone conformation of the calix[4]arene skeleton in 1 was found to be stabilized by a circular array of hydrogen bonds formed by two phenolic O-H and two amidic N-H bonds at lower rim. Whereas no significant complexation of Na+ was observed in solution for diamides 1 and 3, tetraamides 2, 4, 5, and 6 give strong complexes with Na+ as confirmed by NMR titrations of 2 and 4. The influence of anions and the solvents used on complexation ability of 2 towards Na+ is negligible

A review of k-NN algorithm based on classical and Quantum Machine Learning

[EN] Artificial intelligence algorithms, developed for traditional computing, based on Von Neumann’s architecture, are slow and expen- sive in terms of computational resources. Quantum mechanics has opened up a new world of possibilities within this field, since, thanks to the basic properties of a quantum computer, a great degree of parallelism can be achieved in the execution of the quantum version of machine learning algorithms. In this paper, a study has been carried out on these proper- ties and on the design of their quantum computing versions. More specif- ically, the study has been focused on the quantum version of the k-NN algorithm that allows to understand the fundamentals when transcribing classical machine learning algorithms into its quantum versions

Psychology of Fragrance Use: Perception of Individual Odor and Perfume Blends Reveals a Mechanism for Idiosyncratic Effects on Fragrance Choice

Cross-culturally, fragrances are used to modulate body odor, but the psychology of fragrance choice has been largely overlooked. The prevalent view is that fragrances mask an individual's body odor and improve its pleasantness. In two experiments, we found positive effects of perfume on body odor perception. Importantly, however, this was modulated by significant interactions with individual odor donors. Fragrances thus appear to interact with body odor, creating an individually-specific odor mixture. In a third experiment, the odor mixture of an individual's body odor and their preferred perfume was perceived as more pleasant than a blend of the same body odor with a randomly-allocated perfume, even when there was no difference in pleasantness between the perfumes. This indicates that fragrance use extends beyond simple masking effects and that people choose perfumes that interact well with their own odor. Our results provide an explanation for the highly individual nature of perfume choice

The Born supremacy: quantum advantage and training of an Ising Born machine

The search for an application of near-term quantum devices is widespread. Quantum Machine Learning is touted as a potential utilisation of such devices, particularly those which are out of the reach of the simulation capabilities of classical computers. In this work, we propose a generative Quantum Machine Learning Model, called the Ising Born Machine (IBM), which we show cannot, in the worst case, and up to suitable notions of error, be simulated efficiently by a classical device. We also show this holds for all the circuit families encountered during training. In particular, we explore quantum circuit learning using non-universal circuits derived from Ising Model Hamiltonians, which are implementable on near term quantum devices. We propose two novel training methods for the IBM by utilising the Stein Discrepancy and the Sinkhorn Divergence cost functions. We show numerically, both using a simulator within Rigetti's Forest platform and on the Aspen-1 16Q chip, that the cost functions we suggest outperform the more commonly used Maximum Mean Discrepancy (MMD) for differentiable training. We also propose an improvement to the MMD by proposing a novel utilisation of quantum kernels which we demonstrate provides improvements over its classical counterpart. We discuss the potential of these methods to learn `hard' quantum distributions, a feat which would demonstrate the advantage of quantum over classical computers, and provide the first formal definitions for what we call `Quantum Learning Supremacy'. Finally, we propose a novel view on the area of quantum circuit compilation by using the IBM to `mimic' target quantum circuits using classical output data only.Comment: v3 : Close to journal published version - significant text structure change, split into main text & appendices. See v2 for unsplit version; v2 : Typos corrected, figures altered slightly; v1 : 68 pages, 39 Figures. Comments welcome. Implementation at https://github.com/BrianCoyle/IsingBornMachin

The Distribution of Toxoplasma gondii Cysts in the Brain of a Mouse with Latent Toxoplasmosis: Implications for the Behavioral Manipulation Hypothesis

reportedly manipulates rodent behavior to enhance the likelihood of transmission to its definitive cat host. The proximate mechanisms underlying this adaptive manipulation remain largely unclear, though a growing body of evidence suggests that the parasite-entrained dysregulation of dopamine metabolism plays a central role. Paradoxically, the distribution of the parasite in the brain has received only scant attention. at six months of age and examined 18 weeks later. The cysts were distributed throughout the brain and selective tropism of the parasite toward a particular functional system was not observed. Importantly, the cysts were not preferentially associated with the dopaminergic system and absent from the hypothalamic defensive system. The striking interindividual differences in the total parasite load and cyst distribution indicate a probabilistic nature of brain infestation. Still, some brain regions were consistently more infected than others. These included the olfactory bulb, the entorhinal, somatosensory, motor and orbital, frontal association and visual cortices, and, importantly, the hippocampus and the amygdala. By contrast, a consistently low incidence of tissue cysts was recorded in the cerebellum, the pontine nuclei, the caudate putamen and virtually all compact masses of myelinated axons. Numerous perivascular and leptomeningeal infiltrations of inflammatory cells were observed, but they were not associated with intracellular cysts. distribution stems from uneven brain colonization during acute infection and explains numerous behavioral abnormalities observed in the chronically infected rodents. Thus, the parasite can effectively change behavioral phenotype of infected hosts despite the absence of well targeted tropism

Distract yourself: prediction of salient distractors by own actions and external cues.

Distracting sensory events can capture attention, interfering with the performance of the task at hand. We asked: is our attention captured by such events if we cause them ourselves? To examine this, we employed a visual search task with an additional salient singleton distractor, where the distractor was predictable either by the participant's own (motor) action or by an endogenous cue; accordingly, the task was designed to isolate the influence of motor and non-motor predictive processes. We found both types of prediction, cue- and action-based, to attenuate the interference of the distractor-which is at odds with the "attentional white bear" hypothesis, which states that prediction of distracting stimuli mandatorily directs attention towards them. Further, there was no difference between the two types of prediction. We suggest this pattern of results may be better explained by theories postulating general predictive mechanisms, such as the framework of predictive processing, as compared to accounts proposing a special role of action-effect prediction, such as theories based on optimal motor control. However, rather than permitting a definitive decision between competing theories, our study highlights a number of open questions, to be answered by these theories, with regard to how exogenous attention is influenced by predictions deriving from the environment versus our own actions