From Knowledge, Knowability and the Search for Objective Randomness to a New Vision of Complexity

Herein we consider various concepts of entropy as measures of the complexity of phenomena and in so doing encounter a fundamental problem in physics that affects how we understand the nature of reality. In essence the difficulty has to do with our understanding of randomness, irreversibility and unpredictability using physical theory, and these in turn undermine our certainty regarding what we can and what we cannot know about complex phenomena in general. The sources of complexity examined herein appear to be channels for the amplification of naturally occurring randomness in the physical world. Our analysis suggests that when the conditions for the renormalization group apply, this spontaneous randomness, which is not a reflection of our limited knowledge, but a genuine property of nature, does not realize the conventional thermodynamic state, and a new condition, intermediate between the dynamic and the thermodynamic state, emerges. We argue that with this vision of complexity, life, which with ordinary statistical mechanics seems to be foreign to physics, becomes a natural consequence of dynamical processes.Comment: Phylosophica

An efficient binomial approach to the pricing of options on stocks with cash dividends

In this contribution, we consider options written on stocks which pay cash dividends. Dividend payments have an effect on the value of options: high dividends imply lower call premia and higher put premia. While exact solutions to problems of evaluating both European and American call options and European put options are available in the literature, for American-style put options early exercise may be optimal at any time prior to expiration even in the absence of dividends. In this case numerical techniques, such as lattice approaches, are required. Discrete dividends produce a shift in the tree; as a result, the tree is no longer reconnecting beyond any dividend date. Methods based on non-recombining trees give consistent results, but they are computationally expensive. We analyze binomial algorithms and performed some empirical experiments.Options on stocks, discrete dividends, binomial lattices

Simulation techniques for generalized Gaussian densities

This contribution deals with Monte Carlo simulation of generalized Gaussian random variables. Such a parametric family of distributions has been proposed in many applications in science to describe physical phenomena and in engineering, and it seems also useful in modeling economic and financial data. For values of the shape parameter a within a certain range, the distribution presents heavy tails. In particular, the cases a=1/3 and a=1/2 are considered. For such values of the shape parameter, different simulation methods are assessed.Generalized Gaussian density, heavy tails, transformations of rendom variables, Monte Carlo simulation, Lambert W function

Model and performance evaluation of field-effect transistors based on epitaxial graphene on SiC

In view of the appreciable semiconducting gap of 0.26 eV observed in recent experiments, epitaxial graphene on a SiC substrate seems a promising channel material for FETs. Indeed, it is two-dimensional - and therefore does not require prohibitive lithography - and exhibits a wider gap than other alternative options, such as bilayer graphene. Here we propose a model and assess the achievable performance of a nanoscale FET based on epitaxial graphene on SiC, conducting an exploration of the design parameter space. We show that the current can be modulated by 4 orders of magnitude; for digital applications an Ion /Ioff ratio of 50 and a subthreshold slope of 145 mV/decade can be obtained with a supply voltage of 0.25 V. This represents a significant progress towards solid-state integration of graphene electronics, but not yet sufficient for digital applications

Partitioning strategies for the interaction of a fluid with a poroelastic material based on a Nitsche's coupling approach

We develop a computational model to study the interaction of a fluid with a poroelastic material. The coupling of Stokes and Biot equations represents a prototype problem for these phenomena, which feature multiple facets. On one hand it shares common traits with fluid-structure interaction. On the other hand it resembles the Stokes-Darcy coupling. For these reasons, the numerical simulation of the Stokes-Biot coupled system is a challenging task. The need of large memory storage and the difficulty to characterize appropriate solvers and related preconditioners are typical shortcomings of classical discretization methods applied to this problem. The application of loosely coupled time advancing schemes mitigates these issues because it allows to solve each equation of the system independently with respect to the others. In this work we develop and thoroughly analyze a loosely coupled scheme for Stokes-Biot equations. The scheme is based on Nitsche's method for enforcing interface conditions. Once the interface operators corresponding to the interface conditions have been defined, time lagging allows us to build up a loosely coupled scheme with good stability properties. The stability of the scheme is guaranteed provided that appropriate stabilization operators are introduced into the variational formulation of each subproblem. The error of the resulting method is also analyzed, showing that splitting the equations pollutes the optimal approximation properties of the underlying discretization schemes. In order to restore good approximation properties, while maintaining the computational efficiency of the loosely coupled approach, we consider the application of the loosely coupled scheme as a preconditioner for the monolithic approach. Both theoretical insight and numerical results confirm that this is a promising way to develop efficient solvers for the problem at hand

Model of tunneling transistors based on graphene on SiC

Recent experiments shown that graphene epitaxially grown on Silicon Carbide (SiC) can exhibit a energy gap of 0.26 eV, making it a promising material for electronics. With an accurate model, we explore the design parameter space for a fully ballistic graphene-on-SiC Tunnel Field-Effect Transistors (TFETs), and assess the DC and high frequency figures of merit. The steep subthreshold behavior can enable I_{ON}/I_{OFF} ratios exceeding 10^4 even with a low supply voltage of 0.15 V, for devices with gatelength down to 30 nm. Intrinsic transistor delays smaller than 1 ps are obtained. These factors make the device an interesting candidate for low-power nanoelectronics beyond CMOS

Fathoming the kynurenine pathway in migraine: why understanding the enzymatic cascades is still critically important

Kynurenine pathway, the quantitatively main branch of tryptophan metabolism, has been long been considered a source of nicotinamide adenine dinucleotide, although several of its products, the so-called kynurenines, are endowed with the capacity to activate glutamate receptors, thus potentially influencing a large group of functions in the central nervous system (CNS). Migraine, a largely unknown pathology, is strictly related to the glutamate system in the CNS pathologic terms. Despite the large number of studies conducted on migraine etio-pathology, the kynurenine pathway has been only recently linked to this disease. Nonetheless, some evidence suggests an intriguing role for some kynurenines, and an exploratory study on the serum kynurenine level might be helpful to better understand possible alterations of the kynurenine pathway in patients suffering from migrain

Exhaust Energy Recovery with Variable Geometry Turbine to Reduce Fuel Consumption for Microcars

The objective proposed by EU to reduce by about 4%/year CO2 emission of internal combustion engines for the next years up to 2030, requires to increase the engine efficiency and accordingly improving the technology. In this framework, hybrid powertrains can have the possibility of a deep market penetration since they may recover energy during brake, allow the engine to operate in better efficiency conditions and with less transients, Moreover, they can recover a large amount of energy lost through the exhaust and use it to reduce fuel consumption. This paper concerns the modification of a conventional two in-line cylinders Diesel engine (440 cm3) adding a variable geometry turbine (VGT) coupled with a generator. The turbine is used to recover exhaust gas energy that otherwise would be lost. The generator, connected to the turbo shaft, converts mechanical energy into electrical energy and is used to charge the vehicle battery or the auxiliaries. The aim of this work is reducing fuel consumption by replacing the alternator with a kind of electric turbo-compounding system to drive vehicle auxiliaries. If the selected turbine recovers enough energy to power auxiliaries, the alternator, which usually has low efficiency, can be removed. Along these lines, fuel consumption savings can be achieved. At a later stage, a microcar has been tested on WLTC (Class 1) driving cycle. The results show fuel consumption reduction of 6 to 9%, depending on VGT size. Indeed, four different VGT sizes have been analyzed to choose the optimal configuration that reflects a compromise between energy recovery and fuel consumption reductions

Testing chirality of primordial gravitational waves with Planck and future CMB data: no hope from angular power spectra

We use the 2015 Planck likelihood in combination with the Bicep2/Keck likelihood (BKP and BK14) to constrain the chirality, $\chi$, of primordial gravitational waves in a scale-invariant scenario. In this framework, the parameter $\chi$ enters theory always coupled to the tensor-to-scalar ratio, $r$, e.g. in combination of the form $\chi \cdot r$. Thus, the capability to detect $\chi$ critically depends on the value of $r$. We find that with present data set $\chi$ is \textit{de facto}unconstrained. We also provide forecasts for $\chi$ from future CMB experiments, including COrE+, exploring several fiducial values of $r$. We find that the current limit on $r$ is tight enough to disfavor a neat detection of $\chi$. For example, in the unlikely case in which $r\sim0.1(0.05)$, the maximal chirality case, i.e. $\chi = \pm1$, could be detected with a significance of $\sim2.5(1.5)\sigma$ at best. We conclude that the two-point statistics at the basis of CMB likelihood functions is currently unable to constrain chirality and may only provide weak limits on $\chi$ in the most optimistic scenarios. Hence, it is crucial to investigate the use of other observables, e.g. provided by higher order statistics, to constrain these kind of parity violating theories with the CMB.Comment: 15 pages, 3 figures. Updated to match published versio