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Counter-intuitive to classical notions, quantum conditional entropy can be negative, playing a pivotal role in information-processing tasks. This article delves deeply into quantum channels, emphasizing negative conditional entropy breaking channels (NCEB) and introducing negative conditional entropy annihilating channels (NCEA). We characterize these channels from both topological and information-theoretic perspectives, examining their properties when combined serially and NCEB in parallel. Our exploration extends to complimentary channels associated with NCEB, leading to the introduction of information-leaking channels. Utilizing the parameters of the standard depolarizing channel, we provide tangible examples and further characterization. We demonstrate the relationship of NCEB and NCEA with newly introduced channels like coherent information breaking (CIB) and mutual information breaking (MIB), along with standard channels like zero capacity channels. Preservation of quantum resources is an integral constituent of quantum information theory. Recognizing this, we lay prescriptions to detect channels that do not break the negativity of conditional entropy, ensuring the conservation of this quantum resource., Comment: 14 pages, 5 figures

In this paper, we develop machine learning techniques to identify unknown printers in early modern (c.~1500--1800) English printed books. Specifically, we focus on matching uniquely damaged character type-imprints in anonymously printed books to works with known printers in order to provide evidence of their origins. Until now, this work has been limited to manual investigations by analytical bibliographers. We present a Contrastive Attention-based Metric Learning approach to identify similar damage across character image pairs, which is sensitive to very subtle differences in glyph shapes, yet robust to various confounding sources of noise associated with digitized historical books. To overcome the scarce amount of supervised data, we design a random data synthesis procedure that aims to simulate bends, fractures, and inking variations induced by the early printing process. Our method successfully improves downstream damaged type-imprint matching among printed works from this period, as validated by in-domain human experts. The results of our approach on two important philosophical works from the Early Modern period demonstrate potential to extend the extant historical research about the origins and content of these books., Comment: Proceedings of AAAI 2023

The present work develops a theoretical procedure for obtaining transport coefficients of Yukawa systems from density fluctuations. The dynamics of Yukawa systems are described in the framework of the generalized hydrodynamic model that incorporates strong coupling and visco-elastic memory effects. A hydrodynamic matrix for such a system is exactly derived and then used to obtain an analytic expression for the density autocorrelation function (DAF)- a marker of the time dynamics of density fluctuations. The present approach is validated against a DAF obtained from numerical data of Molecular Dynamics (MD) simulations of a dusty plasma system that is a practical example of a Yukawa system. The MD results and analytic expressions derived from the model equations are then used to obtain various transport coefficients and the latter are compared with values available in the literature from other models. The influence of strong coupling and visco-elastic effects on the transport parameters are discussed. Finally, the utility of our calculations for obtaining reliable estimates of transport coefficients from experimentally determined DAF is pointed out., Comment: This manuscript contains 12 pages and 10 figures

The detection of life beyond Earth is an ongoing scientific endeavour, with profound implications. One approach, known as the search for extraterrestrial intelligence (SETI), seeks to find engineered signals (`technosignatures') that indicate the existence technologically-capable life beyond Earth. Here, we report on the detection of a narrowband signal-of-interest at ~982 MHz, recorded during observations toward Proxima Centauri with the Parkes Murriyang radio telescope. This signal, `BLC1', has characteristics broadly consistent with hypothesized technosignatures and is one of the most compelling candidates to date. Analysis of BLC1 -- which we ultimately attribute to being an unusual but locally-generated form of interference -- is provided in a companion paper (Sheikh et al., 2021). Nevertheless, our observations of Proxima Centauri are the most sensitive search for radio technosignatures ever undertaken on a star target., Comment: 14 pages, 4 figures (+3 supplementary figures). Published open-access in Nature Astronomy

In this work we evaluate a neural based speech intelligibility booster based on spectral shaping and dynamic range compression (SSDRC), referred to as WaveNet-based SSDRC (wSSDRC), using a recently designed Greek Harvard-style corpus. The corpus has been developed according to the format of the Harvard/IEEE sentences and offers the opportunity to apply neural speech enhancement models and examine their performance gain for Greek listeners. wSSDRC has been successfully tested for English material and speakers in the past. In this paper we revisit wSSDRC to perform a full scale evaluation of the model with Greek listeners under the condition of equal energy before and after modification. Both normal hearing (NH) and hearing impaired (HI) listeners evaluated the model under speech shaped noise (SSN) at listener-specific SNRs matching their Speech Reception Threshold (SRT) - a point at which 50 % of unmodified speech is intelligible. The analysis statistics show that the wSSDRC model has produced a median intelligibility boost of 39% for NH and 38% for HI, relative to the plain unprocessed speech.

The increased adoption of digital assistants makes text-to-speech (TTS) synthesis systems an indispensable feature of modern mobile devices. It is hence desirable to build a system capable of generating highly intelligible speech in the presence of noise. Past studies have investigated style conversion in TTS synthesis, yet degraded synthesized quality often leads to worse intelligibility. To overcome such limitations, we proposed a novel transfer learning approach using Tacotron and WaveRNN based TTS synthesis. The proposed speech system exploits two modification strategies: (a) Lombard speaking style data and (b) Spectral Shaping and Dynamic Range Compression (SSDRC) which has been shown to provide high intelligibility gains by redistributing the signal energy on the time-frequency domain. We refer to this extension as Lombard-SSDRC TTS system. Intelligibility enhancement as quantified by the Intelligibility in Bits (SIIB-Gauss) measure shows that the proposed Lombard-SSDRC TTS system shows significant relative improvement between 110% and 130% in speech-shaped noise (SSN), and 47% to 140% in competing-speaker noise (CSN) against the state-of-the-art TTS approach. Additional subjective evaluation shows that Lombard-SSDRC TTS successfully increases the speech intelligibility with relative improvement of 455% for SSN and 104% for CSN in median keyword correction rate compared to the baseline TTS method., Comment: Accepted in INTERSPEECH 2020

Convolutional neural network (CNN) modules are widely being used to build high-end speech enhancement neural models. However, the feature extraction power of vanilla CNN modules has been limited by the dimensionality constraint of the convolution kernels that are integrated - thereby, they have limitations to adequately model the noise context information at the feature extraction stage. To this end, adding recurrency factor into the feature extracting CNN layers, we introduce a robust context-aware feature extraction strategy for single-channel speech enhancement. As shown, adding recurrency results in capturing the local statistics of noise attributes at the extracted features level and thus, the suggested model is effective in differentiating speech cues even at very noisy conditions. When evaluated against enhancement models using vanilla CNN modules, in unseen noise conditions, the suggested model with recurrency in the feature extraction layers has produced a segmental SNR (SSNR) gain of up to 1.5 dB, an improvement of 0.4 in subjective quality in the Mean Opinion Score scale, while the parameters to be optimized are reduced by 25%., Comment: 5 pages

In this paper, we suggest a new parallel, non-causal and shallow waveform domain architecture for speech enhancement based on FFTNet, a neural network for generating high quality audio waveform. In contrast to other waveform based approaches like WaveNet, FFTNet uses an initial wide dilation pattern. Such an architecture better represents the long term correlated structure of speech in the time domain, where noise is usually highly non-correlated, and therefore it is suitable for waveform domain based speech enhancement. To further strengthen this feature of FFTNet, we suggest a non-causal FFTNet architecture, where the present sample in each layer is estimated from the past and future samples of the previous layer. By suggesting a shallow network and applying non-causality within certain limits, the suggested FFTNet for speech enhancement (SE-FFTNet) uses much fewer parameters compared to other neural network based approaches for speech enhancement like WaveNet and SEGAN. Specifically, the suggested network has considerably reduced model parameters: 32% fewer compared to WaveNet and 87% fewer compared to SEGAN. Finally, based on subjective and objective metrics, SE-FFTNet outperforms WaveNet in terms of enhanced signal quality, while it provides equally good performance as SEGAN. A Tensorflow implementation of the architecture is provided at 1 ., Comment: 5 pages

Classical double copy is an intriguing relationship between classical solutions to a gravity theory and solutions to classical Yang-Mills equations. Although formally inspired by the double copy relation between (quantum) scattering amplitudes in QCD and perturbative gravity, a direct proof of the former from the latter continues to be under investigation. In this paper, we attempt to prove classical double copy from the color-kinematics duality symmetry of QCD amplitudes in a restricted setting. That is we consider radiative solutions with classical scattering sources in Yang-Mills theory and perturbative gravity in D > 4 spacetime dimensions. We show that when the frequency of radiation is much smaller than the characteristic frequency of the process, then at the subleading order in frequency, the classical double copy relating radiative gluon field to radiative gravitational field can be proved from the color-kinematics duality of QCD amplitudes., Comment: 47 pages, minor changes and citations added

Outer space is a harsh environment harbouring multiple forms of stress like cosmic radiation, space vacuum, extreme temperature and pressure, UV radiations, and altered gravity. Earth’s atmosphere has several layers that expose microbial and terrestrial life to harsh external environments. In order to study the limits of survival of microbial life in extremes, it is imperative to study the response of micro-organisms to space-related stress. The present chapter summarizes the various balloon and flight experiments performed to investigate the presence and response of microbial life in space. Studying the microbiome in the ISS is important as pathogenic bacteria can present a major risk to astronaut health in a closed environment. Hence, studying occurrence, ecology, diversity, response, and adaptations of microbial life in space is crucial to understanding the limits of organismic survival in inhospitable conditions. Studying microbial life in space also helps predict the plausible survival and endurance of microbial travel between planets, crucial to lithopanspermia theories and planetary protection.