More on the SW-QNM correspondence

We exploit the recently proposed correspondence between gravitational perturbations and quantum Seiberg-Witten curves to compute the spectrum of quasi-normal modes of asymptotically flat Kerr Newman black holes and establish detailed gauge/gravity dictionaries for a large class of black holes, D-branes and fuzzballs in diverse dimensions. QNM frequencies obtained from the quantum periods of SU(2) $$ \mathcal{N} $$ N = 2 SYM with Nf = 3 flavours are compared against numerical results, WKB (eikonal) approximation and geodetic motion showing remarkable agreement. Starting from the master example relating quasi-normal modes of Kerr-Newman black holes in AdS4 to SU(2) gauge theory with Nf = 4, we illustrate the procedure for some simple toy-models that allow analytic solutions. We also argue that the AGT version of the gauge/gravity correspondence may give precious hints as to the physical/geometric origin of the quasi-normal modes/Seiberg-Witten connection and further elucidate interesting properties (such as tidal Love numbers and grey-body factors) that can help discriminating black holes from fuzzballs.

The Multi-Compartment SI(RD) Model with Regime Switching: An Application to COVID-19 Pandemic

We study—with existence and unicity results—a variant of the SIR model for an infectious disease incorporating both the possibility of a death outcome—in a short period of time—and a regime switch that can account for the mitigation measures used to control the spreading of the infections, such as a total lockdown. This model is parametrised by three parameters: the basic reproduction number, the mortality rate of the infected, and the duration of the disease. We discuss a particular example of application to Portuguese COVID-19 data in two short periods just after the start of the epidemic in 4 March 2020, with the first two cases dated that day. We propose a simple and effective method for the estimation of the main parameters of the disease, namely, the basic reproduction number and the mortality rate of the infected. We correct these estimated values to take into account the asymptomatic non-diagnosed members of the population. We compare the outcome of the model in the cases of the existence, or not, of a regime switch, and under three different scenarios, with a remarkable agreement between model and data deaths in the case of our basis scenario. In a final short remark, we deal with the existence of symmetries for the proposed model.

Duality and modular symmetry in the quantum Hall effect from Lifshitz holography

The temperature dependence of quantum Hall conductivities is studied in the context of the AdS/CMT paradigm using a model with a bulk theory consisting of (3+1)-dimensional Einstein-Maxwell action coupled to a dilaton and an axion, with a negative cosmological constant. We consider a solution which has a Lifshitz like geometry with a dyonic black-brane in the bulk. There is an Sl(2,R) action in the bulk corresponding to electromagnetic duality, which maps between classical solutions, and is broken to Sl(2,Z) by Dirac quantisation of dyons. This bulk Sl(2,Z) action translates to an action of the modular group on the 2-dimensional transverse conductivities. The temperature dependence of the infra-red conductivities is then linked to modular forms via gradient flow and the resulting flow diagrams show remarkable agreement with existing experimental data on the temperature flow of both integral and fractional quantum Hall conductivities.

Inflation with non-canonical scalar fields revisited

We revisit inflation with non-canonical scalar fields by applying deformed-steepness exponential potentials. We show that the resulting scenario can lead to inflationary observables, and in particular to scalar spectral index and tensor-to-scalar ratio, in remarkable agreement with observations. Additionally, a significant advantage of the scenario is that the required parameter values, such as the non-canonicality exponent and scale, as well as the potential exponent and scale, do not need to acquire unnatural values and hence can accept a theoretical justification. Hence, we obtain a significant improvement with respect to alternative schemes, and we present distinct correlations between the model parameters that better fit the data, which can be tested in future probes. This combination of observational efficiency and theoretical justification makes the scenario at hand a good candidate for the description of inflation.

Dynamical landscape and multistability of a climate model

We apply two independent data analysis methodologies to locate stable climate states in an intermediate complexity climate model and analyse their interplay. First, drawing from the theory of quasi-potentials, and viewing the state space as an energy landscape with valleys and mountain ridges, we infer the relative likelihood of the identified multistable climate states and investigate the most likely transition trajectories as well as the expected transition times between them. Second, harnessing techniques from data science, and specifically manifold learning, we characterize the data landscape of the simulation output to find climate states and basin boundaries within a fully agnostic and unsupervised framework. Both approaches show remarkable agreement, and reveal, apart from the well known warm and snowball earth states, a third intermediate stable state in one of the two versions of PLASIM, the climate model used in this study. The combination of our approaches allows to identify how the negative feedback of ocean heat transport and entropy production via the hydrological cycle drastically change the topography of the dynamical landscape of Earth’s climate.

Integrative proteogenomics for differential expression and splicing variation in a DM1 mouse model

Dysregulated mRNA splicing is involved in the pathogenesis of many diseases including cancer, neurodegenerative diseases, and muscular dystrophies such as myotonic dystrophy type 1 (DM1). Comprehensive assessment of dysregulated splicing on the transcriptome and proteome level have been methodologically challenging, and thus investigations have often been targeting only few genes. Here, we performed a large-scale coordinated transcriptomic and proteomic analysis to characterize a DM1 mouse model (HSALR) in comparison to wild-type. Our integrative proteogenomics approach comprised gene- and splicing-level assessments for mRNAs and proteins. It recapitulated many known instances of aberrant mRNA splicing in DM1 and identified new ones. It enabled the design and targeting of splicing-specific peptides and confirmed the translation of known instances of aberrantly spliced disease-related genes (e.g. Atp2a1, Bin1, Ryr1), complemented by novel findings (e.g. Ywhae, Flnc, Svil). Comparative analysis of large-scale mRNA and protein expression data showed remarkable agreement of differential patterns between disease and wild-type on both the gene and especially the splicing level. We hence believe that our work is suitable as a model for a robust and scalable integrative proteogenomic strategy. This strategy provides investigative approaches, advances our understanding of the disease biology of splicing-based disorders, and helps establish robust splicing-specific biomarkers.

EFT asymptotics: the growth of operator degeneracy

We establish formulae for the asymptotic growth (with respect to the scaling dimension) of the number of operators in effective field theory, or equivalently the number of S-matrix elements, in arbitrary spacetime dimensions and with generic field content. This we achieve by generalising a theorem due to Meinardus and applying it to Hilbert series---partition functions for the degeneracy of (subsets of) operators. Although our formulae are asymptotic, numerical experiments reveal remarkable agreement with exact results at very low orders in the EFT expansion, including for complicated phenomenological theories such as the standard model EFT. Our methods also reveal phase transition-like behaviour in Hilbert series. We discuss prospects for tightening the bounds and providing rigorous errors to the growth of operator degeneracy, and of extending the analytic study and utility of Hilbert series to EFT.

Experimental and Theoretical Characterization of Thio coumarin by NLO single crystal in DFT Calculations

Experimental and theoretical electron densities in thiocoumarin have been analyzed based on the X-ray diffraction data at 90 K. These compound pack in the crystal lattice with weak C-H…O and C-H….π interactions, and variations in charge density properties and derived local energy densities have been investigated in the regions of intermolecular interactions. Theoretical charge density calculations on crystals using the B3LYP/6-311 + + G(d,p) method show remarkable agreement with the derived properties and energy densities from the experiment. The intermolecular interactions follow an exponential dependence of electron density and energy densities at the bond critical points. The Laplacian follows a “Morse-like” dependence on the length of the interaction line. Based on the set of criteria defined using the theory of “atoms in molecules”, it has become possible to distinguish between a hydrogen bond (C-H…O) and a van der Waals interaction (C-H….π). This has resulted in the identification of a “region of overlap” in terms of electron densities, energy densities, and mutual penetration of the hydrogen and acceptor atoms with respect to the interaction length. This approach suggests a possible tool to distinguish between the two types of interactions. High field indicates that this molecule exhibit considerable electrical conductivity in atomic charges.The ESP map is found to be positive throughout the backbone of the molecule. The negative charges have a tendency to drift from left to right. Thermodynamic parameters like heat capacities (Cºp,m), entropies (Sºm) and enthalpies changes (Hºm) are used for various electrical field. Theoretical FT-IR and FT-Raman spectra of the title molecule have been constructed which show good agreement with recorded spectra.

Matching Boundary Conditions for the Euler–Bernoulli Beam

Artificial boundary conditions play a crucial role in the dynamic simulation of infinite Euler–Bernoulli beams. In this paper, a class of artificial boundary conditions, matching boundary conditions (MBCs), is presented to provide effective absorption of incident waves in numerical simulations of the Euler–Bernoulli beam. First, matching boundary conditions are proposed based on the space central difference scheme of the Euler–Bernoulli beam, and then, the specific coefficients of MBCs are determined by matching the dispersion relation. Moreover, reflection coefficient study and numerical tests are carried out to analyze the effectiveness of the proposed MBCs, indicating a remarkable agreement. Taken together, the proposed boundary conditions herein can absorb dispersive waves efficiently and are more compact than previous artificial boundary conditions, particularly suitable for real-time simulation.

Dynamical Landscape and Multistability of a Climate Model

<p>We apply two independent data analysis methodologies to locate stable climate states in an intermediate complexity climate model and analyze their interplay. First, drawing from the theory of quasipotentials, and viewing the state space as an energy landscape with valleys and mountain ridges, we infer the relative likelihood of the identified multistable climate states, and investigate the most likely transition trajectories as well as the expected transition times between them. Second, harnessing techniques from data science, specifically manifold learning, we characterize  the data landscape of the simulation output to find climate states and basin boundaries within a fully agnostic and unsupervised framework. Both approaches show remarkable agreement, and reveal, apart from the well known warm and snowball earth states, a third intermediate stable state in one of the two climate models we consider. The combination of our approaches allows to identify how the negative feedback of ocean heat transport and entropy production via the hydrological cycle drastically change the topography of the dynamical landscape of Earth's climate.</p>