Entanglement dynamics of two mesoscopic objects with gravitational interaction

We analyse the entanglement dynamics of the two particles interacting through gravity in the recently proposed experiments aiming at testing quantum signatures for gravity [Phy. Rev. Lett 119, 240401 & 240402 (2017)]. We consider the open dynamics of the system under decoherence due to the environmental interaction. We show that as long as the coupling between the particles is strong, the system does indeed develop entanglement, confirming the qualitative analysis in the original proposals. We show that the entanglement is also robust against stochastic fluctuations in setting up the system. The optimal interaction duration for the experiment is computed. A condition under which one can prove the entanglement in a device-independent manner is also derived.Comment: 5 pages, 3 figures; comments are welcome

Improving the Value of the Coconut with Biotechnology

The fruit of the coconut tree is perhaps the most useful plant resource in the tropics. All parts of the coconut fruit have traditional uses that have been developed commercially in recent times (Foale 2003, Dayrit and Dayrit 2013). Due to its widespread household use, trade and industry statistics on coconut products reflect only part of the actual importance of the coconut. Today, coconut-based products have gone beyond the tropics and are consumed in many temperate countries and global regions such as Australia, China, Europe, North America, and the Middle East (Costello 2018). Coconut milk is the basic ingredient of traditional cuisines and desserts worldwide in the Asian tropics, while coconut flour is used in confectionery and bakery products. Coconut oil is widely used as cooking oil, hair and cosmetic oil, and domestic remedies for burns and skin ailments and in soap-making and preparation of traditional medicine. Coconut water can be either consumed fresh or converted into vinegar and nata de coco. The residues of these processes are used for animal feed and soil enhancer. The young inflorescences can be tapped directly to obtain coconut sap. This natural honey-like product can then be evaporated to prepare coco sugar or fermented to produce coconut sap wine and vinegar. These products are markedly distinct from those produced from coconut water. However, if the sap is collected, the harvest of nuts is lost. Nondairy products from the coconut, such as margarines, yoghurts, and cheese, have become more and more popular in the global market. This chapter will deal mainly with the products that can be obtained from the fruit

Towards Robust FastSpeech 2 by Modelling Residual Multimodality

State-of-the-art non-autoregressive text-to-speech (TTS) models based on FastSpeech 2 can efficiently synthesise high-fidelity and natural speech. For expressive speech datasets however, we observe characteristic audio distortions. We demonstrate that such artefacts are introduced to the vocoder reconstruction by over-smooth mel-spectrogram predictions, which are induced by the choice of mean-squared-error (MSE) loss for training the mel-spectrogram decoder. With MSE loss FastSpeech 2 is limited to learn conditional averages of the training distribution, which might not lie close to a natural sample if the distribution still appears multimodal after all conditioning signals. To alleviate this problem, we introduce TVC-GMM, a mixture model of Trivariate-Chain Gaussian distributions, to model the residual multimodality. TVC-GMM reduces spectrogram smoothness and improves perceptual audio quality in particular for expressive datasets as shown by both objective and subjective evaluation.Comment: Accepted at INTERSPEECH 202

Consistency tests of field level inference with the EFT likelihood

Analyzing the clustering of galaxies at the field level in principle promises access to all the cosmological information available. Given this incentive, in this paper we investigate the performance of field-based forward modeling approach to galaxy clustering using the effective field theory (EFT) framework of large-scale structure (LSS). We do so by applying this formalism to a set of consistency and convergence tests on synthetic datasets. We explore the high-dimensional joint posterior of LSS initial conditions by combining Hamiltonian Monte Carlo sampling for the field of initial conditions, and slice sampling for cosmology and model parameters. We adopt the Lagrangian perturbation theory forward model from [1], up to second order, for the forward model of biased tracers. We specifically include model mis-specifications in our synthetic datasets within the EFT framework. We achieve this by generating synthetic data at a higher cutoff scale $\Lambda_0$, which controls which Fourier modes enter the EFT likelihood evaluation, than the cutoff $\Lambda$ used in the inference. In the presence of model mis-specifications, we find that the EFT framework still allows for robust, unbiased joint inference of a) cosmological parameters - specifically, the scaling amplitude of the initial conditions - b) the initial conditions themselves, and c) the bias and noise parameters. In addition, we show that in the purely linear case, where the posterior is analytically tractable, our samplers fully explore the posterior surface. We also demonstrate convergence in the cases of nonlinear forward models. Our findings serve as a confirmation of the EFT field-based forward model framework developed in [2-7], and as another step towards field-level cosmological analyses of real galaxy surveys.Comment: 31 + 13 pages, 15 figures; Added 3 new figures, text cleanup and fix typos; matching the version to be published in JCA