Eclipsing Binaries in Dynamically Interacting Close, Multiple Systems

Close, compact, hierarchical, and multiple stellar systems, i.e., multiples having an outer orbital period from months to a few years, comprise a small but continuously growing group of the triple and multiple star zoo. Many of them consist of at least one eclipsing pair of stars and, therefore, exhibit readily observable short-term dynamical interactions among the components. Thus, their dynamical and astrophysical properties can be explored with high precision. In this paper we present an overview of the history of the search for additional components around eclipsing binaries from the first serendipitous discoveries to more systematic recent studies. We describe the different observational detection methods and discuss their connections to the different kinds of astrophysical and dynamical information that can be mined from different datasets. Moreover, the connection amongst the observable phenomena and the long-term dynamics of such systems is also discussed.

Rotation Curves in z ∼ 1–2 Star-forming Disks: Comparison of Dark Matter Fractions and Disk Properties for Different Fitting Methods

We present a follow-up analysis examining the dynamics and structures of 41 massive, large star-forming galaxies at z ∼ 0.67 − 2.45 using both ionized and molecular gas kinematics. We fit the galaxy dynamics with models consisting of a bulge, a thick, turbulent disk, and an NFW dark matter halo, using code that fully forward-models the kinematics, including all observational and instrumental effects. We explore the parameter space using Markov Chain Monte Carlo (MCMC) sampling, including priors based on stellar and gas masses and disk sizes. We fit the full sample using extracted 1D kinematic profiles. For a subset of 14 well-resolved galaxies, we also fit the 2D kinematics. The MCMC approach robustly confirms the results from least-squares fitting presented in Paper I: the sample galaxies tend to be baryon-rich on galactic scales (within one effective radius). The 1D and 2D MCMC results are also in good agreement for the subset, demonstrating that much of the galaxy dynamical information is captured along the major axis. The 2D kinematics are more affected by the presence of noncircular motions, which we illustrate by constructing a toy model with constant inflow for one galaxy that exhibits residual signatures consistent with radial motions. This analysis, together with results from Paper I and other studies, strengthens the finding that massive, star-forming galaxies at z ∼ 1 − 2 are baryon-dominated on galactic scales, with lower dark matter fractions toward higher baryonic surface densities. Finally, we present details of the kinematic fitting code used in this analysis.

On the physical nudging equations

In this work we show how it is possible to derive a new set of nudging equations, a tool still used in many data assimilation problems, starting from statistical physics considerations and availing ourselves of stochastic parameterizations that take into account unresolved interactions. The fluctuations used are thought of as Gaussian white noise with zero mean. The derivation is based on the conditioned Langevin dynamics technique. Exploiting the relation between the Fokker–Planck and the Langevin equations, the nudging equations are derived for a maximally observed system that converges towards the observations in finite time. The new nudging term found is the analog of the so called quantum potential of the Bohmian mechanics. In order to make the new nudging equations feasible for practical computations, two approximations are developed and used as bases from which extending this tool to non-perfectly observed systems. By means of a physical framework, in the zero noise limit, all the physical nudging parameters are fixed by the model under study and there is no need to tune other free ad-hoc variables. The limit of zero noise shows that also for the classical nudging equations it is necessary to use dynamical information to correct the typical relaxation term. A comparison of these approximations with a 3DVar scheme, that use a conjugate gradient minimization, is then shown in a series of four twin experiments that exploit low order chaotic models.

A maximum caliber approach for continuum path ensembles

The maximum caliber approach implements the maximum entropy principle for trajectories by maximizing a path entropy under external constraints. The maximum caliber approach can be applied to a diverse set of equilibrium and non-equilibrium problems concerning the properties of trajectories connecting different states of a system. In this review, we recapitulate the basic concepts of the maximum entropy principle and of its maximum caliber implementation for path ensembles, and review recent applications of this approach. In particular, we describe how we recently used this approach to introduce a framework, called here the continuum path ensemble maximum caliber (CoPE-MaxCal) method, to impose kinetic constraints in molecular simulations, for instance to include experimental information about transition rates. Such incorporation of dynamical information can ameliorate inaccuracies of empirical force fields, and lead to improved mechanistic insights. We conclude by offering an outlook for future research. Graphic Abstract

Phyllotaxis Models: from the Inhibition Potential to the Real Plant

Previous phyllotaxis models allowed the initiation of new primordia when a threshold of inhibition potential is reached on the meristem front: their adequacy to botanical reality is only qualitative. We formulated the hypothesis that it is not the value of the inhibition threshold that remains constant as the meristem develops, but the difference of the inhibition thresholds during the initiation of two successive primordia. We were thus able to model with accuracy the sequence of plastochron ratios observed by Williams (1975) on the leaf meristem of flax: an outstanding result. More generally, we have shown that the evolution trajectories of the phyllotaxis modes as a function of the plastochron ratios follow the minima of the potential under decreasing plastochron ratios constraint and bifurcate when the number of these minima increases, thus giving physicochemical foundations to the famous van Iterson diagram. This historical representation of rising phyllotaxis shows the trajectories, but doesnt give the velocity of the movement: our plastochron ratio sequence adds this major dynamical information.

The Generalization of the Periodic Orbit Dividing Surface in Hamiltonian Systems with Three or More Degrees of Freedom – I

We present a method that generalizes the periodic orbit dividing surface construction for Hamiltonian systems with three or more degrees of freedom. We construct a torus using as a basis a periodic orbit and we extend this to a ([Formula: see text])-dimensional object in the ([Formula: see text])-dimensional energy surface. We present our methods using benchmark examples for two and three degrees of freedom Hamiltonian systems to illustrate the corresponding algorithm for this construction. Towards this end, we use the normal form quadratic Hamiltonian system with two and three degrees of freedom. We found that the periodic orbit dividing surface can provide us the same dynamical information as the dividing surface constructed using normally hyperbolic invariant manifolds. This is significant because, in general, computations of normally hyperbolic invariant manifolds are very difficult in Hamiltonian systems with three or more degrees of freedom. However, our method avoids this computation and the only information that we need is the location of one periodic orbit.

Changing in the hierarchical organization of local information dynamics during motor decision in the premotor cortex of primates

Despite recent works have investigated functional and effective cortical networks in animal models, the dynamical information transfer among functional modules underneath cognitive control is still largely unknown. Here we addressed the issue by using transfer entropy and graph theory methods on neural activities recorded from a multielectrode (96 recording sites) array in the dorsal premotor cortex of rhesus monkeys. We focused our analysis on the decision time of a stop-signal (countermanding) task. When comparing trials with successful inhibition to those with generated movement we found evidence of heterogeneous interacting modules described by 4 main classes, hierarchically organized. Interestingly, the hierarchical organization resulted different in the two type of trials. Our results suggest that motor decisions are based on the local re-organization of the premotor cortical network

Molecular basis for higher affinity of SARS-CoV-2 spike RBD for human ACE2 receptor

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused substantially more infections, deaths, and economic disruptions than the 2002-2003 SARS-CoV. The key to understanding SARS-CoV-2’s higher infectivity lies partly in its host receptor recognition mechanism. Experiments show that the human ACE2 protein, which serves as the primary receptor for both CoVs, binds to the receptor binding domain (RBD) of CoV-2’s spike protein stronger than SARS-CoV’s spike RBD. The molecular basis for this difference in binding affinity, however, remains unexplained from X-ray structures. To go beyond insights gained from X-ray structures and investigate the role of thermal fluctuations in structure, we employ all-atom molecular dynamics simulations. Microseconds-long simulations reveal that while CoV and CoV-2 spike-ACE2 interfaces have similar conformational binding modes, CoV-2 spike interacts with ACE2 via a larger combinatorics of polar contacts, and on average, makes 45\% more polar contacts. Correlation analysis and thermodynamic calculations indicate that these differences in the density and dynamics of polar contacts arise from differences in spatial arrangements of interfacial residues, and dynamical coupling between interfacial and non-interfacial residues. These results recommend that ongoing efforts to design spike-ACE2 peptide blockers will benefit from incorporating dynamical information as well as allosteric coupling effects.

Phylodynamics for cell biologists

Multicellular organisms are composed of cells connected by ancestry and descent from progenitor cells. The dynamics of cell birth, death, and inheritance within an organism give rise to the fundamental processes of development, differentiation, and cancer. Technical advances in molecular biology now allow us to study cellular composition, ancestry, and evolution at the resolution of individual cells within an organism or tissue. Here, we take a phylogenetic and phylodynamic approach to single-cell biology. We explain how “tree thinking” is important to the interpretation of the growing body of cell-level data and how ecological null models can benefit statistical hypothesis testing. Experimental progress in cell biology should be accompanied by theoretical developments if we are to exploit fully the dynamical information in single-cell data.