Hard gluon evolution in warming medium

We describe the energy distribution of hard gluons travelling through a dense quark–gluon plasma whose temperature increases linearly with time, within a probabilistic perturbative approach. The results were applied to the thermalization problem in heavy ion collisions. In the weak coupling picture this thermalization occurs from “the bottom up”: high energy partons, formed early in the collision, radiate low energy gluons which then proceed to equilibrate among themselves, forming a thermal bath that brings the high energy sector to equilibrium. We see that, in this scenario, the dynamic we describe must set in around $$t \sim 0.5$$ t ∼ 0.5 fm/c after the collision in order to reach a fully thermalized state at $$t \sim 1$$ t ∼ 1 fm/c. We then look at the entropy density and average temperature of the soft thermal bath, as the system approaches (local) thermal equilibrium.

Importance of charge self-consistency in first-principles description of strongly correlated systems

First-principles approaches have been successful in solving many-body Hamiltonians for real materials to an extent when correlations are weak or moderate. As the electronic correlations become stronger often embedding methods based on first-principles approaches are used to better treat the correlations by solving a suitably chosen many-body Hamiltonian with a higher level theory. The success of such embedding theories, often referred to as second-principles, is commonly measured by the quality of self-energy Σ which is either a function of energy or momentum or both. However, Σ should, in principle, also modify the electronic eigenfunctions and thus change the real space charge distribution. While such practices are not prevalent, some works that use embedding techniques do take into account these effects. In such cases, choice of partitioning, of the parameters defining the correlated Hamiltonian, of double-counting corrections, and the adequacy of low-level Hamiltonian hosting the correlated subspace hinder a systematic and unambiguous understanding of such effects. Further, for a large variety of correlated systems, strong correlations are largely confined to the charge sector. Then an adequate nonlocal low-order theory is important, and the high-order local correlations embedding contributes become redundant. Here we study the impact of charge self-consistency within two example cases, TiSe2 and CrBr3, and show how real space charge re-distribution due to correlation effects taken into account within a first-principles Green’s function-based many-body perturbative approach is key in driving qualitative changes to the final electronic structure of these materials.

A scale-invariant perturbative approach to study information communication in dynamic brain networks

How communication among neuronal ensembles shapes functional brain dynamics at the large scale is a question of fundamental importance to Neuroscience. To date, researchers have primarily relied on two alternative ways to address this issue 1) in-silico neurodynamical modelling of functional brain dynamics by choosing biophysically inspired non-linear systems, interacting via a connection topology driven by empirical data; and 2) identifying topological measures to quantify network structure and studying them in tandem with functional metrics of interest, e.g. co-variation of time series in brain regions from fast (EEG/ MEG) and slow (fMRI) timescales. While the modelling approaches are limited in scope to only scales of the nervous system for which dynamical models are well defined, the latter approach does not take into account how the network architecture and intrinsic regional node dynamics contribute together to inter-regional communication in the brain. Thus, developing a generalized scale-invariant measure of interaction between network topology and constituent regional dynamics can potentially resolve how transmission of perturbations in brain networks alter function e.g. by neuropathologies, or the intervention strategies designed to mitigate them. In this work, we introduce a recently developed theoretical perturbative framework in network science into a neuroscientific framework, to conceptualize the interaction of regional dynamics and network architecture in a quantifiable manner. This framework further provides insights into the information communication contributions of putative regions and sub-networks in the brain, irrespective of the observational scale of the phenomenon (firing rates to BOLD fMRI time series). The proposed approach can directly quantify network-dynamical interactions without reliance on a specific class of models or response characteristics: linear/nonlinear. By simply gauging the asymmetries in responses to perturbations, we obtain insights into the significance of regions in communication and their influence over the rest of the network. Moreover, coupling perturbations with functional lesions can also answer which regions contribute the most to information spread: a quantity termed Flow. The simplicity of the proposed technique allows translation to an experimental setting where the response asymmetries and flow can inversely act as a window into the dynamics of regions. For proof-of-concept, we apply the perturbative approach on in-silico data generated for human resting state network dynamics, using different established dynamical models that mimic empirical observations. We also apply the perturbation approach at the level of large scale Resting State Networks (RSNs) to gauge the range of network-dynamical interactions in mediating information flow across brain regions.

Cooling Improves Cosmic Microwave Background Map-making when Low-frequency Noise is Large

In the context of cosmic microwave background data analysis, we study the solution to the equation that transforms scanning data into a map. As originally suggested in “messenger” methods for solving linear systems, we split the noise covariance into uniform and nonuniform parts and adjust their relative weights during the iterative solution. With simulations, we study mock instrumental data with different noise properties, and find that this “cooling” or perturbative approach is particularly effective when there is significant low-frequency noise in the timestream. In such cases, a conjugate gradient algorithm applied to this modified system converges faster and to a higher fidelity solution than the standard conjugate gradient approach. We give an analytic estimate for the parameter that controls how gradually the linear system should change during the course of the solution.

Generalized quantum electrodynamics: One-loop correction

In this paper, we give an update on divergent problems concerning the radiative corrections of quantum electrodynamics in (3[Formula: see text]+[Formula: see text]1) dimensions. In doing so, we introduce a geometric adaptation for the covariant photon propagator by including a higher derivative field. This derivation, so-called generalized quantum electrodynamics, is motivated by the stability and unitarity features. This theory provides a natural and self-consistent extension of the quantum electrodynamics by enlarging the space parameter of spinor-gauge interactions. In particular, Haag’s theorem undermines the perturbative characterization of the interaction picture due to its inconsistency on quantum field theory foundations. To circumvent this problem, we develop our perturbative approach in the Heisenberg picture and use it to investigate the behavior of the operator current at one-loop. We find the two- and three-point correlation functions are ultraviolet finite, electron self-energy and vertex corrections, respectively. On the other hand, we also explain how the vacuum polarization remains ultraviolet divergent only at [Formula: see text] order. Finally, we evaluate the anomalous magnetic moment, which allows us to specify a lower bound value for the Podolsky parameter.

Context-dependent selectivity to natural scenes in the retina

Retina ganglion cells extract specific features from natural scenes and send this information to the brain. In particular, they respond to local light increase (On responses), or decrease (Off). However, it is unclear if this On-Off selectivity, characterized with synthetic stimuli, is maintained when they are stimulated with natural scenes. Here we recorded the responses of ganglion cells of mice and axolotls to stimuli composed of natural images slightly perturbed by patterns of random noise to determine their selectivity during natural stimulation. The On-Off selectivity strongly depended on the natural image. A single ganglion cell can signal luminance increase for one natural image, and luminance decrease for another. Modeling and experiments showed that this was due to the non-linear combination of different pathways of the retinal circuit. Despite the versatility of the On-Off selectivity, a systematic analysis demonstrated that contrast was reliably encoded in these responses. Our perturbative approach thus uncovers the selectivity of retinal ganglion cells to more complex features than initially thought during natural scene stimulation.

Spin dynamic response to a time dependent field

The dynamic response of a parametric system constituted by a spin precessing in a time dependent magnetic field is studied by means of a perturbative approach that unveils unexpected features, and is then experimentally validated. The first-order analysis puts in evidence different regimes: beside a tailorable low-pass-filter behaviour, a band-pass response with interesting potential applications emerges. Extending the analysis to the second perturbation order permits to study the response to generically oriented fields and to characterize several non-linear features in the behaviour of such kind of systems.

Semiclassical approximation meets Keldysh–Schwinger diagrammatic technique: scalar $$\varphi ^4$$

We study the evolution of the non-equilibrium quantum fields from a highly excited initial state in two approaches: the standard Keldysh–Schwinger diagram technique and the semiclassical expansion. We demonstrate explicitly that these two approaches coincide if the coupling constant g and the Plank constant $$\hbar $$ ħ are simultaneously small. Also, we discuss loop diagrams of the perturbative approach, which are summed up by the leading order term of the semiclassical expansion. As an example, we consider shear viscosity for the scalar field theory at the leading semiclassical order. We introduce the new technique that unifies both semiclassical and diagrammatic approaches and open the possibility to perform the resummation of the semiclassical contributions.

Vibration analysis of irregular-shaped plates on simple supports

In this work, we propose a general perturbative approach for modal analysis of irregular-shaped plates of uniform thickness with uniform boundary conditions. Given a plate of irregular boundary, first, a uniform circular plate of identical thickness and area, centred at the centroid, is determined. The irregular boundary is then treated as a perturbation with a suitable smallness parameter, and is expressed as a generalized Fourier series. The frequency parameter, shape function and boundary conditions are then perturbed in terms of the smallness parameter. The homogeneous zeroth-order equation corresponds to the circular plate, which is exactly solvable. We show that the inhomogeneous equations in the higher orders can also be solved exactly using a particular solution structure. We can then construct the exact perturbative solution up to any order. The proposed method is demonstrated through the modal analysis of simply supported super-circular plates. The results are validated using the numerical results obtained from ANSYS ® , which are an excellent match. Interestingly, the supposedly degenerate modes with an even number of nodal diameters of super-circular plates are found to split naturally.