International School for Advanced Studies

About: International School for Advanced Studies is a education organization based out in Trieste, Friuli-Venezia Giulia, Italy. It is known for research contribution in the topics: Galaxy & Dark matter. The organization has 3751 authors who have published 13433 publications receiving 588454 citations. The organization is also known as: SISSA & Scuola Internazionale Superiore di Studi Avanzati.

Entanglement entropy dynamics of Heisenberg chains

Abstract: By means of the time dependent density matrix renormalization group algorithm we study the zero-temperature dynamics of the Von Neumann entropy of a block of spins in a Heisenberg chain after a sudden quench in the anisotropy parameter. In the absence of any disorder the block entropy increases linearly with time and then saturates. We analyse the velocity of propagation of the entanglement as a function of the initial and final anisotropies and compare our results, wherever possible, with those obtained by means of conformal field theory. In the disordered case we find a slower (logarithmic) evolution which may signal the onset of entanglement localization.

Cosmological parameters from supernova observations: A critical comparison of three data sets

Abstract: We extend our previous analysis of cosmological supernova type Ia data (Padmanabhan & Choudhury 2003) to include three recent compilation of data sets. Our analysis ignores the possible correlations and systematic effects present in the data and concentrates mostly on some key theoretical issues. Among the three data sets, the first set consists of 194 points obtained from various observations while the second discards some of the points from the first one because of large uncertainties and thus consists of 142 points. The third data set is obtained from the second by adding the latest 14 points observed through HST. A careful comparison of these different data sets help us to draw the following conclusions: (i) All the three data sets strongly rule out non-accelerating models. Interestingly, the first and the second data sets favour a closed universe; if Ωtot ≡ Ωm +Ω Λ, then the probability of obtaining models with Ωtot > 1i s>0.97. Hence these data sets are in mild disagreement with the "concordance" flat model. However, this disagreement is reduced (the probability of obtaining models with Ωtot > 1 being ≈0.9) for the third data set, which includes the most recent points observed by HST around 1 0.34) redshift supernova, it turns out that these two subsets, individually, admit non-accelerating models with zero dark energy because of different magnitude zero-point values for the different subsets. This can also be seen when the data is analysed while allowing for possibly different magnitude zero-points for the two redshift subsets. However, the non-accelerating models seem to be ruled out using only the low redshift data for the other two data sets, which have less uncertainties. (iii) We have also found that it is quite difficult to measure the evolution of the dark energy equation of state wX(z) though its present value can be constrained quite well. The best-fit value seems to mildly favour a dark energy component with current equation of state wX 0.2.

The Role and Perspective of Ab Initio Molecular Dynamics in the Study of Biological Systems

Abstract: Ab initio molecular dynamics (MD) allows realistic simulations to be performed without adjustable parameters. In recent years, the technique has been used on an increasing number of applications to biochemical systems. Here we describe the principles on which ab initio MD is based. We focus on the most popular implementation, based on density functional theory and plane wave basis set. By a survey of recent applications, we show that despite the current limitations of size and time scale, ab initio MD (and hybrid ab initio MD/MM approaches) can play an important role for the modeling of biological systems. Finally, we provide a perspective for the advancement of methodological approaches which may further expand the scope of ab initio MD in biomolecular modeling.

Using metadynamics to explore complex free-energy landscapes

Abstract: Metadynamics is an atomistic simulation technique that allows, within the same framework, acceleration of rare events and estimation of the free energy of complex molecular systems. It is based on iteratively ‘filling’ the potential energy of the system by a sum of Gaussians centred along the trajectory followed by a suitably chosen set of collective variables (CVs), thereby forcing the system to migrate from one minimum to the next. The power of metadynamics is demonstrated by the large number of extensions and variants that have been developed. The first scope of this Technical Review is to present a critical comparison of these variants, discussing their advantages and disadvantages. The effectiveness of metadynamics, and that of the numerous alternative methods, is strongly influenced by the choice of the CVs. If an important variable is neglected, the resulting estimate of the free energy is unreliable, and predicted transition mechanisms may be qualitatively wrong. The second scope of this Technical Review is to discuss how the CVs should be selected, how to verify whether the chosen CVs are sufficient or redundant, and how to iteratively improve the CVs using machine learning approaches. Metadynamics is a technique to enhance the probability of observing rare events, such as chemical reactions and phase transitions, in molecular dynamics simulations. This Technical Review surveys the technique, addressing the critical issues that are met in practical applications.