Fractional Fokker-Planck Equation for Ultraslow Kinetics

Several classes of physical systems exhibit ultraslow diffusion for which the mean squared displacement at long times grows as a power of the logarithm of time ("strong anomaly") and share the interesting property that the probability distribution of particle's position at long times is a double-sided exponential. We show that such behaviors can be adequately described by a distributed-order fractional Fokker-Planck equations with a power-law weighting-function. We discuss the equations and the properties of their solutions, and connect this description with a scheme based on continuous-time random walks

Detecting the Stimulated Decay of Axions at Radio Frequencies

Assuming axion-like particles account for the entirety of the dark matter in the Universe, we study the possibility of detecting their decay into photons at radio frequencies. We discuss different astrophysical targets, such as dwarf spheroidal galaxies, the Galactic Center and halo, and galaxy clusters. The presence of an ambient radiation field leads to a stimulated enhancement of the decay rate; depending on the environment and the mass of the axion, the effect of stimulated emission may amplify the photon flux by serval orders of magnitude. For axion-photon couplings allowed by astrophysical and laboratory constraints(and possibly favored by stellar cooling), we find the signal to be within the reach of next-generation radio telescopes such as the Square Kilometer Array.Comment: Minor changes, references added, matches published versio

From Diffusion to Anomalous Diffusion: A Century after Einstein's Brownian Motion

Einstein's explanation of Brownian motion provided one of the cornerstones which underlie the modern approaches to stochastic processes. His approach is based on a random walk picture and is valid for Markovian processes lacking long-term memory. The coarse-grained behavior of such processes is described by the diffusion equation. However, many natural processes do not possess the Markovian property and exhibit to anomalous diffusion. We consider here the case of subdiffusive processes, which are semi-Markovian and correspond to continuous-time random walks in which the waiting time for a step is given by a probability distribution with a diverging mean value. Such a process can be considered as a process subordinated to normal diffusion under operational time which depends on this pathological waiting-time distribution. We derive two different but equivalent forms of kinetic equations, which reduce to know fractional diffusion or Fokker-Planck equations for waiting-time distributions following a power-law. For waiting time distributions which are not pure power laws one or the other form of the kinetic equation is advantageous, depending on whether the process slows down or accelerates in the course of time

The seesaw path to leptonic CP violation

Future experiments such as SHiP and high-intensity $e^+ e^-$ colliders will have a superb sensitivity to heavy Majorana neutrinos with masses below $M_Z$. We show that the measurement of the mixing to electrons and muons of one such state could imply the discovery of leptonic CP violation in the context of seesaw models. We quantify in the minimal model the CP discovery potential of these future experiments, and demonstrate that a 5$\sigma$ CL discovery of leptonic CP violation would be possible in a very significant fraction of parameter space.Comment: An error has been fixed, main conclusions unchange

On Myosin II dynamics in the presence of external loads

We address the controversial hot question concerning the validity of the loose coupling versus the lever-arm theories in the actomyosin dynamics by re-interpreting and extending the phenomenological washboard potential model proposed by some of us in a previous paper. In this new model a Brownian motion harnessing thermal energy is assumed to co-exist with the deterministic swing of the lever-arm, to yield an excellent fit of the set of data obtained by some of us on the sliding of Myosin II heads on immobilized actin filaments under various load conditions. Our theoretical arguments are complemented by accurate numerical simulations, and the robustness of the model is tested via different choices of parameters and potential profiles.Comment: 6 figures, 8 tables, to appear on Biosystem

Analyzing real options and flexibility in engineering systems design using decision rules and deep reinforcement learning

Engineering systems provide essential services to society e.g., power generation, transportation. Their performance, however, is directly affected by their ability to cope with uncertainty, especially given the realities of climate change and pandemics. Standard design methods often fail to recognize uncertainty in early conceptual activities, leading to rigid systems that are vulnerable to change. Real Options and Flexibility in Design are important paradigms to improve a system’s ability to adapt and respond to unforeseen conditions. Existing approaches to analyze flexibility, however, do not leverage sufficiently recent developments in machine learning enabling deeper exploration of the computational design space. There is untapped potential for new solutions that are not readily accessible using existing methods. Here, a novel approach to analyze flexibility is proposed based on Deep Reinforcement Learning (DRL). It explores available datasets systematically and considers a wider range of adaptability strategies. The methodology is evaluated on an example waste-toenergy system. Low and high flexibility DRL models are compared against stochastically optimal inflexible and flexible solutions using decision rules. The results show highly dynamic solutions, with action space parametrized via artificial neural network. They show improved expected economic value up to 69% compared to previous solutions. Combining information from action space probability distributions along expert insights and risk tolerance helps make better decisions in real-world design and system operations. Out of sample testing shows that the policies are generalizable, but subject to tradeoffs between flexibility and inherent limitations of the learning process

Pulsation Period Changes as a Tool to Identify Pre-Zero Age Horizontal Branch Stars

One of the most dramatic events in the life of a low-mass star is the He flash, which takes place at the tip of the red giant branch (RGB) and is followed by a series of secondary flashes before the star settles into the zero-age horizontal branch (ZAHB). Yet, no stars have been positively identified in this key evolutionary phase, mainly for two reasons: first, this pre-ZAHB phase is very short compared to other major evolutionary phases in the life of a star; and second, these pre-ZAHB stars are expected to overlap the loci occupied by asymptotic giant branch (AGB), HB and RGB stars observed in the color-magnitude diagram (CMD). We investigate the possibility of detecting these stars through stellar pulsations, since some of them are expected to rapidly cross the Cepheid/RR Lyrae instability strip in their route from the RGB tip to the ZAHB, thus becoming pulsating stars along the way. As a consequence of their very high evolutionary speed, some of these stars may present anomalously large period change rates. We constructed an extensive grid of stellar models and produced pre-ZAHB Monte Carlo simulations appropriate for the case of the Galactic globular cluster M3 (NGC 5272), where a number of RR Lyrae stars with high period change rates are found. Our results suggest that some -- but certainly not all -- of the RR Lyrae stars in M3 with large period change rates are in fact pre-ZAHB pulsators.Comment: Conference Proceedings HELAS Workshop on 'Synergies between solar and stellar modelling', Rome, June 2009, Astrophys. Space Sci., in the pres

Age, Metallicity, and the Distance to the Magellanic Clouds From Red Clump Stars

We show that the luminosity dependence of the red clump stars on age and metallicity can cause a difference of up to < ~0.6 mag in the mean absolute I magnitude of the red clump between different stellar populations. We show that this effect may resolve the apparent ~0.4 mag discrepancy between red clump-derived distance moduli to the Magellanic Clouds and those from, e.g., Cepheid variables. Taking into account the population effects on red clump luminosity, we determine a distance modulus to the LMC of 18.36 +/- 0.17 mag, and to the SMC of 18.82 +/- 0.20 mag. Our alternate red clump LMC distance is consistent with the value (m-M){LMC} = 18.50 +/- 0.10 adopted by the HST Cepheid Key Project. We briefly examine model predictions of red clump luminosity, and find that variations in helium abundance and core mass could bring the Clouds closer by some 0.10--0.15 mag, but not by the ~0.4 mag that would result from setting the mean absolute I-magnitude of the Cloud red clumps equal to the that of the Solar neighborhood red clump.Comment: Accepted for publication in The Astrophysical Journal Letters, AASTeX 4.0, 10 pages, 1 postscript figur