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We apply in a simple model derived from quadratic $\mathcal{R}^2$ gravity the technique of Dyson-Schwinger equations to solve for its corresponding quantum theory. Particularly, we solve the classical equations of motion to get a solution to the hierarchy of Dyson-Schwinger equations in the limit of large coupling. The model is obtained by looking for conformally flat solutions. The model admits Higgs-like solutions with a single particle having a finite mass. Assuming a Fubini-Lipatov instanton for the vacuum instead, the spectrum is given by an infinite set of excitations of finite mass. In both cases, the model develops a mass gap due to the presence of the quadratic Ricci scalar, after the breaking of the conformal symmetry., Comment: 16 pages, 2 figures

Climate change significantly impacts public health, driving the emergence and spread of epidemics. Climate health models are essential for assessing and predicting disease outbreaks influenced by climatic variables like temperature and precipitation. For instance, dengue and malaria correlate with temperature changes, while cholera is linked to precipitation anomalies. Advances in AI-enabled weather prediction (AI-NWP) have improved forecasting, but integrating climate models with health systems is hindered by the lack of comprehensive, granular health datasets. This study introduces EpiClim: India's Epidemic-Climate Dataset, the first weekly district-wise dataset for major epidemics in India from 2009 to the present, sourced from the Integrated Disease Surveillance Programme (IDSP). The dataset, covering diseases like dengue, malaria, and acute-diarrheal disease, bridges the gap between climate and health data, enabling the integration of climate forecasts with epidemic prediction models. This work lays the foundation for coupling predictive climate health models with weather and climate models, advancing efforts to mitigate climate-induced public health crises.

This paper explores the idea that information is an essential and distinctive feature of living systems. Unlike non-living systems, living systems actively acquire, process, and use information about their environments to respond to changing conditions, sustain themselves, and achieve other intrinsic goals. We discuss relevant theoretical frameworks such as ``semantic information'' and ``fitness value of information''. We also highlight the broader implications of our perspective for fields such as origins-of-life research and astrobiology. In particular, we touch on the transition to information-driven systems as a key step in abiogenesis, informational constraints as determinants of planetary habitability, and informational biosignatures for detecting life beyond Earth. We briefly discuss experimental platforms which offer opportunities to investigate these theoretical concepts in controlled environments. By integrating theoretical and experimental approaches, this perspective advances our understanding of life's informational dynamics and its universal principles across diverse scientific domains., Comment: 10 pages 4 figures 131 references

Cosmic strings are powerful witnesses to cosmic events including any period of early matter domination. If such a period of matter domination was catalysed by metastable, long-lived particles, then there will be complementary signals to ascertain the nature of dark sector in experiments detecting primordial features in the gravitational wave (GW) power spectrum and laboratory searches for long-lived particles. We give explicit examples of global and local U(1) gauge extended dark sectors to demonstrate such a complementarity as the union of the two experiments reveals more information about the dark sector than either experiment. Demanding that Higgs-portal long-lived scalar be looked for, in various experiments such as DUNE, FASER, FASER-II, MATHUSLA, SHiP, we identify the parameter space which leads to complementary observables for GW detectors such as LISA and ET., Comment: 23 pages + references, 6 figures, comments are welcome

The phase diagram for a lattice system of biaxial molecules possessing $D_{2h}$ symmetry and interacting with Straley's quadrupolar pair potential in Sonnet-Virga-Durand parameterization [A. M. Sonnet, E. G. Virga, and G. E. Durand, Phys. Rev. E {\bf67}, 061701 (2003)] has been determined using Monte Carlo simulation. Our results confirm that the nematogenic model yields both the uniaxial and biaxial nematic macroscopic phases along with a tricritical point in the transition from uniaxial to biaxial nematics as predicted in mean field theory. By analyzing the behavior of a free-energy-like function, derived from the probability distributions of energy, the order of phase transitions is detected. A conclusive numerical evidence in support of the existence of a tricritical point on the uniaxial-biaxial transition line in the phase diagram is reported. Although the nature of the phase diagram is qualitatively identical as obtained in the mean-field study however the location of the triple point differs significantly from theoretical prediction., Comment: 17 pages, 8 figures, 1 table

Domain wall (DW) networks may have formed in the early universe following the spontaneous breaking of a discrete symmetry. Notably, several particle physics models predict the existence of current-carrying DWs, which can capture and store particles as zero modes on it. In this study, we demonstrate that gravitational waves (GWs) generated by current-carrying DWs with fermionic zeromodes exhibit a novel feature: an additional peak in the GW spectrum resembling mountains, arising from metastable topological remnants, which we term ``spherons.'' This distinct signature could be detectable in upcoming GW observatories such as LISA and ET. The results suggest that DW networks in beyond Standard Model scenarios could emit GW signals that are significantly stronger and with greater detectability than previously expected., Comment: 11 pages, 4 figures

The thermodynamic uncertainty relation (TUR) is a fundamental principle in non-equilibrium thermodynamics that relates entropy production to fluctuations in a system, establishing a trade-off between the precision of an observable and the thermodynamic cost. Investigating TUR violations challenges classical thermodynamic limits, offering the potential for improved precision-entropy trade-offs, which is crucial for enhancing performance and optimization in quantum technologies. In this work, we investigate the thermodynamic uncertainty relation within a quantum collisional model, which offers the advantage of discretizing interactions into successive collisions with auxiliaries, allowing for precise tracking of dynamics and the incorporation of memory effects and non-Markovian behavior. We consider three types of dynamics in the collisional model: one is Markovian evolution, achieved by taking the continuous time limit and imposing the stability condition, while the other two are non-Markovian dynamics - one arising from increasing the collision time between the system and the auxiliaries, and the other from incorporating interactions between the auxiliaries. For the Markovian dynamics, we examine the classical and quantum TUR bounds in the non-equilibrium steady-state regime, and also the finite-time TUR bound. We demonstrate that the classical TUR bound is violated once a certain threshold of collisions with the auxiliaries is exceeded, with the maximum violation observed at the steady state. For the two non-Markovian approaches, we find that the violation of the finite-time TUR bound is highly dependent on the type of non-Markovianity, warranting a detailed comparison., Comment: 17 Pages, 4 Figures

We investigate minimal replicator systems that are able to use information in a functional manner. Specifically, we consider a population of autocatalytic replicators in a flow reactor, subject to fluctuating environments. We derive operational bounds on replicators production in terms of information-theoretic quantities, reflecting contributions from environmental uncertainty, side information, and distribution mismatch. We also derive the optimal strategy, expressed as a function of both intrinsic replicator parameters and environmental statistics. We compare and contrast our findings with existing information-theoretic formalisms such as Kelly gambling. The results are illustrated on a model of real-world self-assembled molecular replicators. For this system, we demonstrate the benefit of internal memory in environments with temporal correlations, and we propose a plausible experimental setup for detecting the signature of functional information. We briefly discuss the role that information processing may play in guiding the evolution of prebiotic replicator networks., Comment: 15 pages, 4 figures

Affleck-Dine (AD) baryogenesis is compelling yet challenging to probe because of the high energy physics involved. We demonstrate that this mechanism can be realized generically with low-energy new physics without supersymmetry while producing detectable gravitational waves (GWs) sourced by parametric resonance of a light scalar field. In viable benchmark models, the scalar has a mass of ${\cal O}(0.1-10)$ GeV, yielding GWs with peak frequencies of ${\cal O}(10-100)$ Hz. This study further reveals a new complementarity between upcoming LIGO-frequency GW detectors and laboratory searches across multiple frontiers of particle physics., Comment: 9 pages, 4 figures including supplemental material

Considering inflationary magnetogenesis induced by time-dependent kinetic and axial couplings of a massless Abelian vector boson field breaking the conformal invariance we show in this Letter that, surprisingly, the spectral shape of the primordial magnetic field power spectrum is insensitive to the post-inflationary history, namely the barotropic parameter ($w$) and the gauge coupling functions of the post-inflationary era., Comment: 5 pages, plus references

The agents in a Multi-Agent System (MAS) make observations about the system and send that information to a fusion center. The fusion center aggregates the information and concludes about the system parameters with as much accuracy as possible. However for the purposes of better efficiency of the system at large, the agents need to append some private parameters to the observed data. In this scenario, the data sent to the fusion center is faced with privacy risks. The data communicated to the fusion center must be secured against data privacy breaches and inference attacks in a decentralized manner. However, this in turn leads to a loss of utility of the data being sent to the fusion center. We quantify the utility and privacy of the system using Cosine similarity. We formulate our MAS problem in terms of deducing a concept for which compression-based methods are there in literature. Next, we propose a novel sanitization mechanism for our MAS using one such compression-based method while addressing the utility-privacy tradeoff problem., Comment: This work has been submitted to the IEEE for possible publication

Non-pharmaceutical interventions (NPIs) aimed at limiting human mobility have demonstrated success in curbing the transmission of airborne diseases. However, their effectiveness in managing vector-borne diseases remains less clear. In this study, we introduce a framework that integrates mobility data with vulnerability matrices to evaluate the differential impacts of mobility-based NPIs on both airborne and vector-borne pathogens. Focusing on the city of Santiago de Cali in Colombia, our analysis illustrates how mobility-based policies previously proposed to contain airborne disease can make cities more prone to the spread of vector-borne diseases. By proposing a simplified synthetic model, we explain the limitations of the latter policies and exploit the synergies between both types of diseases to find new interventions reshaping the mobility network for their simultaneous control. Our results thus offer valuable insights into the epidemiological trade-offs of concurrent disease management, providing a foundation for the design and assessment of targeted interventions that reshape human mobility., Comment: 25 pages, 5 figures, 63 references. Supplementary material included

The Daisy World model has long served as a foundational framework for understanding the self-regulation of planetary biospheres, providing insights into the feedback mechanisms that may govern inhabited exoplanets. In this study, we extend the classic Daisy World model through the lens of Semantic Information Theory (SIT), aiming to characterize the information flow between the biosphere and planetary environment -- what we term the \emph{information architecture} of Daisy World systems. Our objective is to develop novel methodologies for analyzing the evolution of coupled planetary systems, including biospheres and geospheres, with implications for astrobiological observations and the identification of agnostic biosignatures. To operationalize SIT in this context, we introduce a version of the Daisy World model tailored to reflect potential conditions on M-dwarf exoplanets, formulating a system of stochastic differential equations that describe the co-evolution of the daisies and their planetary environment. Analysis of this Exo-Daisy World model reveals how correlations between the biosphere and environment intensify with rising stellar luminosity, and how these correlations correspond to distinct phases of information exchange between the coupled systems. This \emph{rein control} provides a quantitative description of the informational feedback between the biosphere and its host planet. Finally, we discuss the broader implications of our approach for developing detailed ExoGaia models of inhabited exoplanetary systems, proposing new avenues for interpreting astrobiological data and exploring biosignature candidates., Comment: 14 pages, 4 figures, 1 appendix

We investigate the possibility that primordial black holes (PBHs) can be formed from large curvature perturbations generated during the waterfall phase transition in a hybrid inflation model driven by an axion-like particle (ALP) $\phi$. The model predicts a spectral index $n_s \simeq 0.964$ and a tensor-to-scalar ratio $r \simeq 0.003$, in agreement with Planck data and potentially testable by next generation cosmic microwave background (CMB) experiments such as CMB-S4 and LiteBIRD. We find that the PBH mass and the peak of the associated scalar-induced gravitational wave (SIGW) spectrum are correlated with the ALP mass. In particular, PBHs in the mass range $10^{-13}\, M_\odot$ can constitute either the entire dark matter (DM) content of the universe or a significant fraction of it. The predicted second-order GWs from this mechanism are within the sensitivity reach of future observatories like LISA and ET. The typical reheating temperature in the model is around $10^6 - 10^7$ GeV is consistent with Big Bang Nucleosynthesis (BBN) constraints., Comment: 18 pages, 5 figures + Refs

The analysis of non-local regularisations of scalar conservation laws is an active research program. Applications of such equations are found in the modelling of physical phenomena such as traffic flow. In this paper, we propose a novel inviscid, non-local regularisation in non-divergence form. The salient feature of our approach is that we can obtain sharp a priori estimates on the total variation and supremum norm, and justify the singular limit for Lipschitz initial data up to the time of catastrophe. For generic conservation laws, this result is sharp, since we can demonstrate non-convergence when the initial data features simple discontinuities. Conservation laws with linear flux derivative, such as the Burgers equation, behave better in the presence of discontinuities. Hence, we devote special attention to the limiting behaviour of non-local solutions with respect to the Burgers equation for a simple class of discontinuous initial data., Comment: 21 pages

We consider a novel Bayesian approach to estimation, uncertainty quantification, and variable selection for a high-dimensional linear regression model under sparsity. The number of predictors can be nearly exponentially large relative to the sample size. We put a conjugate normal prior initially disregarding sparsity, but for making an inference, instead of the original multivariate normal posterior, we use the posterior distribution induced by a map transforming the vector of regression coefficients to a sparse vector obtained by minimizing the sum of squares of deviations plus a suitably scaled $\ell_1$-penalty on the vector. We show that the resulting sparse projection-posterior distribution contracts around the true value of the parameter at the optimal rate adapted to the sparsity of the vector. We show that the true sparsity structure gets a large sparse projection-posterior probability. We further show that an appropriately recentred credible ball has the correct asymptotic frequentist coverage. Finally, we describe how the computational burden can be distributed to many machines, each dealing with only a small fraction of the whole dataset. We conduct a comprehensive simulation study under a variety of settings and found that the proposed method performs well for finite sample sizes. We also apply the method to several real datasets, including the ADNI data, and compare its performance with the state-of-the-art methods. We implemented the method in the \texttt{R} package called \texttt{sparseProj}, and all computations have been carried out using this package.

Can peer recommendation engines elevate people's creative performances in self-organizing social networks? Answering this question requires resolving challenges in data collection (e.g., tracing inspiration links and psycho-social attributes of nodes) and intervention design (e.g., balancing idea stimulation and redundancy in evolving information environments). We trained a model that predicts people's ideation performances using semantic and network-structural features in an online platform. Using this model, we built SocialMuse, which maximizes people's predicted performances to generate peer recommendations for them. We found treatment networks leveraging SocialMuse outperforming AI-agnostic control networks in several creativity measures. The treatment networks were more decentralized than the control, as SocialMuse increasingly emphasized network-structural features at large network sizes. This decentralization spreads people's inspiration sources, helping inspired ideas stand out better. Our study provides actionable insights into building intelligent systems for elevating creativity.

We propose a unified framework that describes both the curvaton mechanism for generating primordial density fluctuations and the Affleck-Dine (AD) field for baryogenesis. By introducing a complex scalar field (AD field) carrying a baryon/lepton number and its potential consisting of quadratic and quartic terms with a small baryon/lepton-number-violating mass term, we investigate the evolution of the scalar field during the radiation-dominated era following inflation. We set the initial conditions such that the quartic term dominates the scalar potential, and the angular component of the AD field is non-zero. We focus on a scenario where the AD field decays early, ensuring that its energy density never dominates over that of radiation. We show that the radial component of the AD field can be identified with the curvaton to solely produce the Planck normalized scalar power spectrum while the evolution of the angular component is crucial for generating the observed baryon asymmetry of the universe. Additionally, we find that the amplitude of scalar bispectrum $f_{NL}$ is positive, with an amplitude of $\mathcal{O}(1)$, which is consistent with the current Planck data and testable in future observations such as CMB-S4, LiteBIRD, LSS, and 21-cm experiments. In our estimation of the scalar power spectrum and bispectrum, we develop a novel analytical scheme for computing scalar fluctuations based on the $\delta N$ formalism, which allows us to deal with the evolution of curvaton with polynomial potential more accurately in comparison to the existing analytical methods., Comment: 18 pages, 5 figures and 1 table

We study interaction of a fermion field $\psi$ with a scalar field $\phi$ and analyze the spectrum of the theory obtained in this way. It is shown that due to non-perturbative dynamics in the hidden fermion sector, $\phi$ develops a vacuum expectation value (vev) in the form of a mass gap which triggers the electroweak symmetry breaking (EWSB) and dynamically generates the SM Higgs boson mass. For estimating the non-perturbatively generated mass scale, we solve the hierarchy of Dyson-Schwinger Equations in form of partial differential equations using the exact solution known via a novel technique developed by Bender, Milton and Savage. We employ Jacobi Elliptic function as exact background solution and show that the mass gap that arises in the fermion sector can be transmuted to the EW sector, expressed in terms of fermion mass and the $\phi$ self-quartic. We identify the suitable parameter space where the observed SM Higgs boson can be successfully generated ., Comment: 7 pages plus references, 2 figures, comments are welcome !

We discuss a mechanism of primordial black hole (PBH) formation that does not require specific features in the inflationary potential, revisiting previous literature. In this mechanism, a light spectator field evolves stochastically during inflation and remains subdominant during the post-inflationary era. Even though the curvature power spectrum stays small at all scales, rare perturbations of the field probe a local maximum in its potential, leading to non-Gaussian tails in the distribution of curvature fluctuations, and to copious PBH production. For a concrete axion-like particle (ALP) scenario we analytically determine the distribution of the compaction function for perturbations, showing that it is characterized by a heavy tail, which produces an extended PBH mass distribution. We find the ALP mass and decay constant to be correlated with the PBH mass, for instance, an ALP with a mass $m_a = 5.4 \times 10^{14}$ eV and a decay constant $f_a = 4.6 \times 10^{-5} Mpl$ can lead to PBHs of mass $M_{\rm PBH} = 10^{21}$ g as the entire dark matter (DM) of the universe, and is testable in future PBH observations via lensing in the NGRST and mergers detectable in the LISA and ET Gravitational Waves (GW) detectors. We then extend our analysis to mixed ALP and PBH dark matter and Higgs-like spectator fields. We find that PBHs cluster strongly over all cosmological scales, clashing with CMB isocurvature bounds. We argue that this problem is shared by all PBH production from inflationary models that depend solely on large non-Gaussianity without a peak in the curvature power spectrum and discuss possible remedies., Comment: 30 pages + Appendices, 7 figures; comments are welcome !

Theories of dynamical electroweak symmetry breaking predict a strong first order cosmological phase transition: we compute the resulting signals, primordial black holes and gravitational waves. These theories employ one SM-neutral scalar, plus some extra model-dependent particle to get the desired quantum potential out of classical scale invariance. We consider models where the extra particle is a scalar singlet, or vectors of an extended U(1) or SU(2) gauge sector. In models where the extra particle is stable, it provides a particle Dark Matter candidate with freeze-out abundance that tends to dominate over primordial black holes. These can instead be DM in models without a particle DM candidate. Gravitational waves arise at a level observable in future searches, even in regions where DM cannot be directly tested., Comment: 23 pages. v2: references added, gravitational waves frequency corrected. Webinar presentation: https://youtu.be/36hLkgREOrA

The gravitational wave (GW) interferometers LISA and ET are expected to be functional in the next decade(s), possibly around the same time. They will operate over different frequency ranges, with similar integrated sensitivities to the amplitude of a stochastic GW background (SGWB). We investigate the synergies between these two detectors, in terms of a multi-band detection of a cosmological SGWB characterised by a large amplitude, and a broad frequency spectrum. By investigating various examples of SGWBs, such as those arising from cosmological phase transition, cosmic string, primordial inflation, we show that LISA and ET operating together will have the opportunity to assess more effectively the characteristics of the GW spectrum produced by the same cosmological source, but at separate frequency scales. Moreover, the two experiments in tandem can be sensitive to features of early universe cosmic expansion before big-bang nucleosynthesis (BBN), which affects the SGWB frequency profile, and which would not be possible to detect otherwise, since two different frequency ranges correspond to two different pre-BBN (or post-inflationary) epochs. Besides considering the GW spectrum, we additionally undertake a preliminary study of the sensitivity of LISA and ET to soft limits of higher order tensor correlation functions. Given that these experiments operate at different frequency bands, their synergy constitutes an ideal direct probe of squeezed limits of higher order GW correlators, which can not be measured operating with a single instrument only., Comment: 44 pages, 10 figures

Intracorporeal needle-based therapeutic ultrasound (NBTU) is a minimally invasive option for intervening in malignant brain tumors, commonly used in thermal ablation procedures. This technique is suitable for both primary and metastatic cancers, utilizing a high-frequency alternating electric field (up to 10 MHz) to excite a piezoelectric transducer. The resulting rapid deformation of the transducer produces an acoustic wave that propagates through tissue, leading to localized high-temperature heating at the target tumor site and inducing rapid cell death. To optimize the design of NBTU transducers for thermal dose delivery during treatment, numerical modeling of the acoustic pressure field generated by the deforming piezoelectric transducer is frequently employed. The bioheat transfer process generated by the input pressure field is used to track the thermal propagation of the applicator over time. Magnetic resonance thermal imaging (MRTI) can be used to experimentally validate these models. Validation results using MRTI demonstrated the feasibility of this model, showing a consistent thermal propagation pattern. However, a thermal damage isodose map is more advantageous for evaluating therapeutic efficacy. To achieve a more accurate simulation based on the actual brain tissue environment, a new finite element method (FEM) simulation with enhanced damage evaluation capabilities was conducted. The results showed that the highest temperature and ablated volume differed between experimental and simulation results by 2.1884{\deg}C (3.71%) and 0.0631 cm$^3$ (5.74%), respectively. The lowest Pearson correlation coefficient (PCC) for peak temperature was 0.7117, and the lowest Dice coefficient for the ablated area was 0.7021, indicating a good agreement in accuracy between simulation and experiment., Comment: 9 pages, 9 figures, 7 tables

Cosmological collider signals of primordial non-Gaussianity arise at tree level when an extra scalar has Hubble mass during inflation. We critically review the formalism finding that a large class of inflationary theories, based on Planck-scale physics, predict a scalar bi-spectrum around the gravitational floor level. This mild signal arises for example in $R^2$ gravity, in the regime where its gravitational scalar has Hubble-scale mass. Signals much above the gravitational floor arise in theories where scalars undergo multiple turns during inflation, thanks to sub-Planckian physics., Comment: 33 pages, 7 figures. v2: version to appear on JHEP, references added. Webinar presentation: https://youtu.be/KweuhqBxhuE

We compute the second moment of the Riemann zeta function for shifted arguments over a domain that extends the ones in the literature. We use the Riemann-Siegel formula for the error term in the approximate functional equation and take the products of all the terms into account. We also show that, as a function of imaginary shifts on the critical line, the the second moment behaves like a Fourier-Cauchy type kernel on a class of functions. This is reminiscent of orthogonal functions., Comment: 17 pages

We investigate conformally extended Standard Model with a hidden scalar $\phi$. It is shown that due to non-perturbative dynamics in the hidden sector, $\phi$ develops a vacuum expectation value (vev) in the form of a mass gap which triggers the electroweak symmetry breaking (EWSB) and dynamically generates the SM Higgs boson mass. For estimating the non-perturbatively generated mass scale, we solve the hierarchy of Dyson-Schwinger Equations in form of partial differential equations using the exact solution known via a novel technique developed by Bender, Milton and Savage. We employ Jacobi Elliptic function as exact background solution and show that the mass gap that arises in the hidden sector can be transmuted to the EW sector, expressed in terms of Higgs-portal mixed quartic coupling $\beta$ and self interaction quartic coupling $\lambda_{\phi}$ of $\phi$. We identify the suitable parameter space where the observed SM Higgs boson can be successfully generated . Finally, we discuss how this idea of non-perturbative EW scale generation can serve as a new starting point for better realistic model building in the context of resolving the hierarchy problem in the Standard Model., Comment: 23 pages, 3 figures

We propose a novel pathway to generate the electroweak (EW) scale via non-perturbative dynamics of a conformally invariant scalar sector at the classical level. We provide a method to estimate the non-perturbative EW scale generation using the exact solution of the background equations of motion in a scalar theory via the Dyson-Schwinger approach. Particularly, we find an analytical result for the Higgs mass in the strongly coupled regime in terms of its quartic self interaction term and the cut-off scale of the theory. We also show that the Higgs sector is an essential part of the Standard Model as, without it, a Yang--Mills gauge theory cannot acquire mass even if a self-interaction term is present. Our analysis lead to a more realistic model building with possible solutions to the gauge hierarchy problem and, in general, to the dynamical generation of any scales scales in nature, be it the visible sector or the dark sector., Comment: 4 pages + Appedix + References, 1 Figure; comments are welcome

We investigate the possibility that primordial black holes (PBHs) can be formed from large curvature perturbations generated during the waterfall phase transition in a supersymmetric scenario where sneutrino is the inflaton in a hybrid inflationary framework. We obtain a spectral index ($n_s \simeq 0.966$), and a tensor-to-scalar ratio ($r\simeq 0.0056-10^{-11}$), consistent with the current Planck data satisfying PBH as dark matter (DM) and detectable Gravitational Wave (GW) signal. Our findings show that the mass of PBH and the peak in the GW spectrum is correlated with the right-handed (s)neutrino mass. We identify parameter space where PBHs can be the entire DM candidate of the universe (with mass $10^{-13}\, M_\odot$) or a fraction of it. This can be tested in future observatories, for example, with amplitude $\Omega_{\rm GW}h^2$ $\sim 10^{-9}$ and peak frequency $f\sim 0.1$ Hz in LISA and $\Omega_{\rm GW}h^2 \sim 10^{-11}$ and peak frequency of $\sim 10$ Hz in ET via second-order GW signals. We study two models of sneutrino inflation: Model$-1$ involves canonical sneutrino kinetic term which predicts the sub-Planckian mass parameter $M$, while the coupling between a gauge singlet and the waterfall field, $\beta$, needs to be quite large whereas, for the model$-2$ involving $\alpha-$attractor canonical sneutrino kinetic term, $\beta$ can take a natural value. Estimating explicitly, we show that both models have mild fine-tuning. We also derive an analytical expression for the power spectrum in terms of the microphysics parameters of the model like (s)neutrino mass, etc. that fits well with the numerical results. The typical reheat temperature for both the models is around $10^{7}-10^{8}$~GeV suitable for non-thermal leptogenesis., Comment: Analysis on non-gaussianity added, results remain same, version matches the published version in PRD

Nearest neighbor classifier is arguably the most simple and popular nonparametric classifier available in the literature. However, due to the concentration of pairwise distances and the violation of the neighborhood structure, this classifier often suffers in high-dimension, low-sample size (HDLSS) situations, especially when the scale difference between the competing classes dominates their location difference. Several attempts have been made in the literature to take care of this problem. In this article, we discuss some of these existing methods and propose some new ones. We carry out some theoretical investigations in this regard and analyze several simulated and benchmark datasets to compare the empirical performances of proposed methods with some of the existing ones.

Hypersonic boundary layer transition using high-order methods for direct numerical simulations (DNS) is largely unexplored, although a few references exist in the literature. Experimental data in the hypersonic regime are scarce, while almost all existing hypersonic codes have low-order accuracy, which could lead to erroneous results in long-time integration and at high Reynolds numbers. Here, we focus on the transition from laminar to turbulent flow, where the Nusselt number may be five times or higher than the Nusselt number in the turbulent regime. The hypersonic flow regime must be modeled accurately using realistic chemistry to predict heat flux on the surface correctly. In this study, we simulate hypersonic boundary layer transition on a flat plate to compute the thermal and shear stresses on the wall. The domain is initialized with a laminar Blasius solution of compressible boundary layer equations. The transition to turbulence is induced using suction and blowing from a thin strip on the wall. Sponge regions are defined at the inflow and outflow boundaries to eliminate the solution contamination due to the reflections of the boundary conditions. In the spanwise direction, periodic boundary conditions are imposed. The numerical method applied here is a sixth-order compact finite difference in the interior of the domain coupled with a fourth-order Runge-Kutta time-stepping scheme for a structured Cartesian grid using staggered variables. The base finite difference code can perform simulations of non-equilibrium hypersonic flows. The numerical scheme is stabilized using the approximate deconvolution model (ADM) and artificial diffusion coefficients. We investigated the effect of non-equilibrium chemistry on the non-linear instability growth with hypersonic boundary layers. We also quantify thermal loads during the boundary layer laminar to turbulent transition for Mach number 10.

People often stick to their existing beliefs, ignoring contradicting evidence or only interacting with those who reinforce their views. Social media platforms often facilitate such tendencies of homophily and echo-chambers as they promote highly personalized content to maximize user engagement. However, increased belief rigidity can negatively affect real-world policy decisions such as leading to climate change inaction and increased vaccine hesitancy. To understand and effectively tackle belief rigidity on online social networks, designing and evaluating various intervention strategies is crucial, and increasing randomization in the network can be considered one such intervention. In this paper, we empirically quantify the effects of a randomized social network structure on belief rigidity, specifically examining the potential benefits of introducing randomness into the network. We show that individuals' beliefs are positively influenced by peer opinions, regardless of whether those opinions are similar to or differ from their own by passively sensing belief rigidity through our experimental framework. Moreover, people incorporate a slightly higher variety of different peers (based on their opinions) into their networks when the recommendation algorithm provides them with diverse content, compared to when it provides them with similar content. Our results indicate that in some cases, there might be benefits to randomization, providing empirical evidence that a more randomized network could be a feasible way of helping people get out of their echo-chambers. Our findings have broader implications in computing and platform design of social media, and can help combat overly rigid beliefs in online social networks.

Neural networks are universal approximators that traditionally have been used to learn a map between function inputs and outputs. However, recent research has demonstrated that deep neural networks can be used to approximate operators, learning function-to-function mappings. Creating surrogate models to supplement computationally expensive hypersonic aerothermodynamic models in characterizing the response of flow fields at different angles of attack (AoA) is an ideal application of neural operators. We investigate the use of neural operators to infer flow fields (volume and surface quantities) around a geometry based on a 3D waverider model based on experimental data measured at the Arnold Engineering Development Center (AEDC) Hypervelocity Wind Tunnel Number 9. We use a DeepONet neural operator which consists of two neural networks, commonly called a branch and a trunk network. The final output is the inner product of the output of the branch network and the output of the trunk net. Because the flow field contains shocks across the entire volume, we conduct a two-step training approach of the DeepONet that facilitates accurate approximation of solutions even in the presence of discontinuities. We train various DeepONet models to understand and predict pressure $(p)$, density $(\rho)$, velocity $(u)$, heat flux $(Q_w)$, and total shear stress $(\tau_{w})$ for the AEDC waverider geometry at Ma=7.36 across AoA that range from $-10^{\circ}$ to $10^{\circ}$ for surface quantities and from $-14^{\circ}$ to $14^{\circ}$ for volume quantities., Comment: 71st JANNAF Propulsion Meeting, Oklahoma City, OK, 6-10 May 2024, 10 pages, 6 figures