Low-complexity BCH codes with optimized interleavers for DQPSK systems with laser phase noise

The presence of high phase noise in addition to additive white Gaussian noise in coherent optical systems affects the performance of forward error correction (FEC) schemes. In this paper, we propose a simple scheme for such systems, using block interleavers and binary Bose–Chaudhuri–Hocquenghem (BCH) codes. The block interleavers are specifically optimized for differential quadrature phase shift keying modulation. We propose a method for selecting BCH codes that, together with the interleavers, achieve a target post-FEC bit error rate (BER). This combination of interleavers and BCH codes has very low implementation complexity. In addition, our approach is straightforward, requiring only short pre-FEC simulations to parameterize a model, based on which we select codes analytically. We aim to correct a pre-FEC BER of around (Formula presented.). We evaluate the accuracy of our approach using numerical simulations. For a target post-FEC BER of (Formula presented.), codes selected using our method result in BERs around 3(Formula presented.) target and achieve the target with around 0.2 dB extra signal-to-noise ratio.

Gaussian Process Kernels for Cross-Spectrum Analysis in Electrophysiological Time Series

Multi-output Gaussian processes provide a convenient framework for multi-task problems. An illustrative and motivating example of a multi-task problem is multi-region electrophysiological time-series data, where experimentalists are interested in both power and phase coherence between channels. Recently, the spectral mixture (SM) kernel was proposed to model the spectral density of a single task in a Gaussian process framework. This work develops a novel covariance kernel for multiple outputs, called the cross-spectral mixture (CSM) kernel. This new, flexible kernel represents both the power and phase relationship between multiple observation channels. The expressive capabilities of the CSM kernel are demonstrated through implementation of 1) a Bayesian hidden Markov model, where the emission distribution is a multi-output Gaussian process with a CSM covariance kernel, and 2) a Gaussian process factor analysis model, where factor scores represent the utilization of cross-spectral neural circuits. Results are presented for measured multi-region electrophysiological data.

The role of age and emotional valence in word recognition: an ex-Gaussian analysis

The aim of this work is to evaluate the roles of age and emotional valence in word recognition in terms of ex-Gaussian distribution components. In order to do that, a word recognition task was carried out with two age groups, in which emotional valence was manipulated. Older participants did not present a clear trend for reaction times. The younger participants showed significant statistical differences in negative words for target and distracting conditions. Addressing the ex-Gaussian tau parameter, often related to attentional demands in the literature, age-related differences in emotional valence seem not to have an effect for negative words. Focusing on emotional valence for each group, the younger participants only showed an effect on negative distracting words. The older participants showed an effect regarding negative and positive target words, and negative distracting words. This suggests that the attentional demand is higher for emotional words, in particular, for the older participants.

Time series wind power forecasting based on variant Gaussian process and TLBO

Due to the variability and stochastic nature of wind power system, accurate wind power forecasting has an important role in developing reliable and economic power system operation and control strategies. As wind variability is stochastic, Gaussian Process regression has recently been introduced to capture the randomness of wind energy. However, the disadvantages of Gaussian Process regression include its computation complexity and incapability to adapt to time varying time-series systems. A variant Gaussian Process for time series forecasting is introduced in this study to address these issues. This new method is shown to be capable of reducing computational complexity and increasing prediction accuracy. It is further proved that the forecasting result converges as the number of available data approaches innite. Further, a teaching learning based optimization (TLBO) method is used to train the model and to accelerate
the learning rate. The proposed modelling and optimization method is applied to forecast both the wind power generation of Ireland and that from a single wind farm to show the eectiveness of the proposed method.

Non-Gaussian distribution of collective operators in quantum spin chains

We numerically analyse the behavior of the full distribution of collective observables in quantum spin chains. While most of previous studies of quantum critical phenomena are limited to the first moments, here we demonstrate how quantum fluctuations at criticality lead to highly non-Gaussian distributions. Interestingly, we show that the distributions for different system sizes collapse on thesame curve after scaling for a wide range of transitions: first and second order quantum transitions and transitions of the Berezinskii–Kosterlitz–Thouless type. We propose and analyse the feasibility of an experimental reconstruction of the distribution using light–matter interfaces for atoms in optical lattices or in optical resonators.

Time-Independent Discrete Gaussian Sampling for Post-Quantum Cryptography

As the development of a viable quantum computer nears, existing widely used public-key cryptosystems, such as RSA, will no longer be secure. Thus, significant effort is being invested into post-quantum cryptography (PQC). Lattice-based cryptography (LBC) is one such promising area of PQC, which offers versatile, efficient, and high performance security services. However, the vulnerabilities of these implementations against side-channel attacks (SCA) remain significantly understudied. Most, if not all, lattice-based cryptosystems require noise samples generated from a discrete Gaussian distribution, and a successful timing analysis attack can render the whole cryptosystem broken, making the discrete Gaussian sampler the most vulnerable module to SCA. This research proposes countermeasures against timing information leakage with FPGA-based designs of the CDT-based discrete Gaussian samplers with constant response time, targeting encryption and signature scheme parameters. The proposed designs are compared against the state-of-the-art and are shown to significantly outperform existing implementations. For encryption, the proposed sampler is 9x faster in comparison to the only other existing time-independent CDT sampler design. For signatures, the first time-independent CDT sampler in hardware is proposed. 

Riprogettazione di mozzi ruota per una vettura di Formula SAE

Con questa tesi si vuole illustrare e riordinare il lavoro da me svolto sulla progettazione di mozzi ruota e di altri componenti ad esso associati, relativi alla vettura del team di Formula SAE dell’Università di Bologna. Dopo una prima fase di studio del particolare componente tesa a definire quali caratteristiche fossero richieste al fine di raggiungere gli obbiettivi, si è passati allo sviluppo del progetto con lo svolgimento di primi calcoli a mano, per definire in linea di massima le sollecitazioni, per poi affinare il dimensionamento con le simulazioni FEM. Il componente è stato infine realizzato in lega d'alluminio ad elevate prestazioni.

Realizzazione e messa a punto degli impianti di raffreddamento e lubrificazione per una vettura di Formula SAE tramite analisi termofluidodinamica e acquisizione di telemetria in pista

L’obiettivo di questa tesi è illustrare quali siano stati i metodi di studio e le soluzioni adottate per ottimizzare gli impianti di raffreddamento e lubrificazione della monoposto da competizione sviluppata dal team Unibo Motorsport, in preparazione alla stagione di gara 2016 della Formula SAE®. Inizialmente saranno analizzate le principali problematiche di entrambi gli impianti attraverso simulazioni CFD (Computational Fluid Dynamics) e dati telemetrici degli anni passati. In seguito, saranno mostrati i diversi procedimenti di progettazione e il completamento degli impianti unitamente ad una loro valutazione economica. Infine, per verificare l’effettivo successo delle operazioni svolte a bordo vettura, verranno mostrate acquisizioni telemetriche relative alle gare ed altre simulazioni relative alle nuove geometrie sviluppate. Un altro obiettivo della trattazione è mettere a disposizione dei futuri membri del reparto motore un documento che contenga tutte le considerazioni fatte a riguardo degli impianti studiati. Questo è fondamentale all’interno di un ambiente come un team di Formula SAE®, dove ogni anno si ha il ricambio di una buona parte dei membri. Se gli studi svolti sugli impianti venissero persi, i nuovi arrivati si troverebbero a mettere le mani su un qualcosa di sconosciuto e lo sviluppo della vettura negli anni si troverebbe enormemente rallentato. Il “learning by doing” che ha sempre caratterizzato questo progetto viene infatti affiancato con armonia dalla possibilità di consultare esperienze pregresse relative al caso di studio considerato.

Floating s- and p-type Gaussian Orbitals

The advantages of including a small number of p-type gaussian functions in a floating spherical gaussian orbital calculation are pointed out and illustrated by calculations on molecules which previously have proved to be troublesome. These include molecules such as F2 with multiple lone pairs and C2H2 with multiple bonds. A feature of the results is the excellent correlation between the orbital energies and those of a double zeta calculation reported by Snyder and Basch.

Gaussian entanglement for quantum key distribution from a single-mode squeezing source

We report the suitability of an Einstein-Podolsky-Rosen entanglement source for Gaussian continuous-variable quantum key distribution at 1550 nm. Our source is based on a single continuous-wave squeezed vacuum mode combined with a vacuum mode at a balanced beam splitter. Extending a recent security proof, we characterize the source by quantifying the extractable length of a composable secure key from a finite number of samples under the assumption of collective attacks. We show that distances in the order of 10 km are achievable with this source for a reasonable sample size despite the fact that the entanglement was generated including a vacuum mode. Our security analysis applies to all states having an asymmetry in the field quadrature variances, including those generated by superposition of two squeezed modes with different squeezing strengths.