Parameter Space Research Articles

NeuralCMS: A deep learning approach to study Jupiter's interior

NASA's Juno mission provided exquisite measurements of Jupiter's gravity field that together with the Galileo entry probe atmospheric measurements constrains the interior structure of the giant planet. Inferring its interior structure range remains a challenging inverse problem requiring a computationally intensive search of combinations of various planetary properties, such as the cloud-level temperature, composition, and core features, requiring the computation of sim \(10^9\) interior models. We propose an efficient deep neural network (DNN) model to generate high-precision wide-ranged interior models based on the very accurate but computationally demanding concentric MacLaurin spheroid (CMS) method. We trained a sharing-based DNN with a large set of CMS results for a four-layer interior model of Jupiter, including a dilute core, to accurately predict the gravity moments and mass, given a combination of interior features. We evaluated the performance of the trained DNN (NeuralCMS) to inspect its predictive limitations. NeuralCMS shows very good performance in predicting the gravity moments, with errors comparable with the uncertainty due to differential rotation, and a very accurate mass prediction. This allowed us to perform a broad parameter space search by computing only sim \(10^4\) actual CMS interior models, resulting in a large sample of plausible interior structures, and reducing the computation time by a factor of \(10^5\). Moreover, we used a DNN explainability algorithm to analyze the impact of the parameters setting the interior model on the predicted observables, providing information on their nonlinear relation.

Testing meson portal dark sector solutions to the MiniBooNE anomaly at the Coherent CAPTAIN Mills experiment

A solution to the MiniBooNE excess invoking rare three-body decays of the charged pions and kaons to new states in the MeV mass scale was recently proposed as a dark-sector explanation. This class of solution illuminates the fact that, while the charged pions were focused in the target-mode run, their decay products were isotropically suppressed in the beam-dump-mode run in which no excess was observed. This suggests a new physics solution correlated to the mesonic sector. We investigate an extended set of phenomenological models that can explain the MiniBooNE excess as a dark sector solution, utilizing long-lived particles that might be produced in the three-body decays of the charged mesons and the two-body anomalous decays of the neutral mesons. Over a broad set of interactions with the long-lived particles, we show that these scenarios can be compatible with constraints from LSND, KARMEN, and MicroBooNE, and evaluate the sensitivity of the ongoing and future data taken by the Coherent CAPTAIN Mills experiment to a potential discovery in this parameter space. Published by the American Physical Society 2024

Exploring the geometry of the bifurcation sets in parameter space

By studying a nonlinear model by inspecting a p-dimensional parameter space through (p-1)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$(p-1)$$\\end{document}-dimensional cuts, one can detect changes that are only determined by the geometry of the manifolds that make up the bifurcation set. We refer to these changes as geometric bifurcations. They can be understood within the framework of the theory of singularities for differentiable mappings and, in particular, of the Morse Theory. Working with a three-dimensional parameter space, geometric bifurcations are illustrated in two models of neuron activity: the Hindmarsh–Rose and the FitzHugh–Nagumo systems. Both are fast-slow systems with a small parameter that controls the time scale of a slow variable. Geometric bifurcations are observed on slices corresponding to fixed values of this distinguished small parameter, but they should be of interest to anyone studying bifurcation diagrams in the context of nonlinear phenomena.

Detecting boosted dark photons with gaseous detectors

We search for indirect signals of O(keV) dark matter annihilating or decaying into O(eV) dark photons. These dark photons will be highly boosted, predominantly transversely polarized, have decay lengths larger than the Milky Way, and can be absorbed by neutrino or dark matter experiments at a rate dependent on the photon-dark photon kinetic mixing parameter and the optical properties of the experiment. We show that current experiments cannot probe new parameter space, but future large-scale gaseous detectors with low backgrounds (i.e., CYGNUS, NEXT, PANDAX-III) may be sensitive to this signal when the annihilation cross section is especially large. Published by the American Physical Society 2024

Towards a systematic study of non-thermal leptogenesis from inflaton decays

This paper investigates non-thermal leptogenesis from inflaton decays in the minimal extension of the canonical type-I seesaw model, where a complex singlet scalar ϕ is introduced to generate the Majorana masses of right-handed neutrinos (RHNs) and to play the role of inflaton. First, we systematically study non-thermal leptogenesis with the least model dependence. We give a general classification of the parameter space and find four characteristic limits by carefully examining the interplay between inflaton decay into RHNs and the decay of RHNs into the standard-model particles. Three of the four limits are truly non-thermal, with a final efficiency larger than that of thermal leptogenesis. Two analytic estimates for these three limits are provided with working conditions to examine the validity. In particular, we find that the strongly non-thermal RHNs scenario occupies a large parameter space, including the oscillation-preferred K range, and works well for a relatively-low reheating temperature TRH ≥ 103 GeV, extending the lower bound on the RHN mass to 2 × 107 GeV. The lepton flavor effects are discussed. Second, we demonstrate that such a unified picture for inflation, neutrino masses, and baryon number asymmetry can be realized by either a Coleman-Weinberg potential (for the real part of ϕ) or a natural inflation potential (for the imaginary part of ϕ). The allowed parameter ranges for successful inflation and non-thermal leptogenesis are much more constrained than those without inflationary observations. We find that non-thermal leptogenesis from inflaton decay offers a testable framework for the early Universe. It can be further tested with upcoming cosmological and neutrino data. The model-independent investigation of non-thermal leptogenesis should be useful in exploring this direction.

Absorption of fermionic dark matter via the scalar portal

The absorption of fermionic dark matter has recently been studied as a signature for the direct detection of dark matter. We construct the first UV completion of the scalar effective operator associated with this signature. We calculate the constraints on the model and demonstrate there is viable parameter space which can be probed by a next-generation experiment such as XLZD. We also consider the cosmological history of our model and show that the correct relic abundance can be obtained via freeze-out in the dark sector. However, within this minimal model, we find that the absorption signal is highly suppressed in the parameter space that yields the correct relic abundance. Published by the American Physical Society 2024

Forming off-center massive black hole binaries in dwarf galaxies through Jacobi capture

It is well established that black holes reside in the central regions of virtually all types of known galaxies. Recent observational and numerical studies however challenge this picture, suggesting that intermediate-mass black holes in dwarf galaxies may be found on orbits far from the center. In particular, constant-density cores minimize orbital energy losses due to dynamical friction, and allow black holes to settle on stable off-center orbits. Using controlled simulations, we study the dynamics of off-center black holes in dwarf galaxies with such cores. We propose a new scenario to describe off-center mergers of massive black holes, starting with a Jacobi capture. We focus on initially circular and co-planar black hole orbits and explore a large parameter space of black hole masses and orbital parameters. We find that Jacobi captures are a complex and chaotic phenomenon that occurs in about $13<!PCT!>$ of cases in this simplified setup, and we quantify how the likelihood of capture depends on the simulation parameters. We note that this percentage is likely an upper limit of the general case. Nevertheless, we show that Jacobi captures in cored dwarf galaxies can facilitate the formation of off-center black hole binaries, and that this process is sufficiently common to have a substantial effect on black hole growth. While our setup only allows for temporary captures, we expect dissipative forces from baryons and post-Newtonian corrections to maintain the captures over time and to lead to the formation of stable binary systems. This motivates future studies of the effectiveness of such dissipative forces, within stripped nuclei or globular clusters, in forming stable bound systems.

On the efficacy of surface-attached air bubbles as thermal insulators for pressure-driven internal flow

There exists much research examining the role of surface-attached air bubbles in drag reduction. Most of this literature considers isothermal flows and so ignores temperature differences, e.g. with the solid boundary. Here, we relax this assumption and ask whether surface-attached air bubbles may prove useful as thermal insulators, e.g. when the solid temperature differs from that of the cargo liquid (water). Theoretical and numerical solutions, e.g. for the variation of the Nusselt number with bubble thickness, are presented for cases characterized by a uniform surface heat flux (USF). We examine channel and pipe flow geometries, and consider instances where the net mass flow rate within the (continuous) air bubble is zero or non-zero. When the thermal boundary condition is changed to uniform surface temperature (UST), our analysis limits attention to numerical solutions. We identify and discuss a remarkable connection between the drag reduction problem and the USF thermal insulation problem: the proportional change of water temperature with bubble thickness is identical to the proportional change of drag. Also, and although our analysis is conducted in the ‘perfect plastron limit’, we can, e.g. by evaluating hydrodynamic and thermal slip lengths, contrast our work against related studies where heat transfer occurs through the ridges or pillars that affix the air layer in place. This comparison indicates that the oft-applied adiabatic interface assumption may prove restrictive in some regions of the parameter space. We conclude by examining the implications of our work in the context of UST micro-channels, which are relevant to various lab-on-a-chip technologies.

M3DIS - A grid of 3D radiation-hydrodynamics stellar atmosphere models for stellar surveys. I. Procedure, validation, and the Sun

Large-scale stellar surveys, such as SDSS-V, 4MOST, WEAVE, and PLATO, require accurate atmospheric models and synthetic spectra of stars for accurate analyses of fundamental stellar parameters and chemical abundances. The primary goal of our work is to develop a new approach to solve radiation-hydrodynamics (RHD) and generate model stellar spectra in a self-consistent and highly efficient framework. We build upon the Copenhagen legacy RHD code, the MULTI3D non-local thermodynamic equilibrium (NLTE) code, and the DISPATCH high-performance framework. The new approach allows us to calculate 3D RHD models of stellar atmospheres on timescales of a few thousand CPU hours and to perform subsequent spectrum synthesis in local thermodynamic equilibrium (LTE) or NLTE for the desired physical conditions within the parameter space of FGK-type stars. We compare the 3D RHD solar model with other available models and validate its performance against solar observations, including the centre-to-limb variation of intensities and key solar diagnostic lines of H and Fe. We show that the performance of the new code allows to overcome the main bottleneck in 3D NLTE spectroscopy and enables calculations of multi-dimensional grids of synthetic stellar observables for comparison with modern astronomical observations.

Testing the number of neutrino species with a global fit of neutrino data

We present the first experimental constraints on models with many additional neutrino species with a similar Yukawa coupling with their right-handed partners among the additional Higgsed sectors by an analysis of current neutrino data. These types of models are motivated as a solution to the hierarchy problem by lowering the species scale of gravity to TeV. Additionally, they offer a natural mechanism to generate small neutrino masses and provide interesting dark matter candidates. This study analyzes data from DayaBay, KamLAND, MINOS, NOνA, and KATRIN. We do not find evidence for the presence of any additional neutrino species, therefore we report lower bounds on the allowed number of neutrino species realized in nature. For the normal/inverted neutrino mass ordering, we can give a lower bound on the number of neutrino species of O(30) and O(100), respectively, over a large range of the parameter space. Published by the American Physical Society 2024

Custodial symmetry breaking and Higgs boson signatures at the LHC

We discuss the simplest model that predicts a tree-level modification of the ρ parameter from a shift in the W-mass without changing the prediction for the Z mass. This model predicts a new neutral Higgs and two charged Higgses, with very similar masses and suppressed couplings to the Standard Model fermions. We discuss the decay properties of these new scalar bosons, and the main signatures at the Large Hadron Collider. Comparing these signatures for the first time to the latest measurements, we show that while masses around 200 GeV are excluded for some scenarios, over a wide range of model parameter space the new bosons can have a mass close to the electroweak scale without violating existing limits from experimental searches or destroying the agreement with measurements. We investigate the scenario where the new neutral Higgs is fermiophobic and has a large branching ratio into W gauge bosons and/or photons, and show that this could lead to a signal in the diphoton mass spectrum at low Higgs masses. We discuss the different signatures that can motivate new measurements and searches at the Large Hadron Collider. Published by the American Physical Society 2024

Real‐time topology optimization via learnable mappings

AbstractIn traditional topology optimization, the computing time required to iteratively update the material distribution within a design domain strongly depends on the complexity or size of the problem, limiting its application in real engineering contexts. This work proposes a multi‐stage machine learning strategy that aims to predict an optimal topology and the related stress fields of interest, either in 2D or 3D, without resorting to any iterative analysis and design process. The overall topology optimization is treated as regression task in a low‐dimensional latent space, that encodes the variability of the target designs. First, a fully‐connected model is employed to surrogate the functional link between the parametric input space characterizing the design problem and the latent space representation of the corresponding optimal topology. The decoder branch of an autoencoder is then exploited to reconstruct the desired optimal topology from its latent representation. The deep learning models are trained on a dataset generated through a standard method of topology optimization implementing the solid isotropic material with penalization, for varying boundary and loading conditions. The underlying hypothesis behind the proposed strategy is that optimal topologies share enough common patterns to be compressed into small latent space representations without significant information loss. Results relevant to a 2D Messerschmitt‐Bölkow‐Blohm beam and a 3D bridge case demonstrate the capabilities of the proposed framework to provide accurate optimal topology predictions in a fraction of a second.

Some specific wormhole solutions in extended f(R,G,T) gravity

This research work provides an exhaustive investigation of the viability of different coupled wormhole (WH) geometries with the relativistic matter configurations in the [Formula: see text] extended gravity framework. We consider a specific model in the context of [Formula: see text]-gravity for this purpose. Also, we assume a static spherically symmetric spacetime geometry and a unique distribution of matter with a set of shape functions ([Formula: see text]) for analyzing different energy conditions. In addition to this, we examined WH-models in the equilibrium scenario by employing anisotropic fluid. The corresponding results are obtained using numerical methods and then presented using different plots. In this case, [Formula: see text] gravity generates additional curvature quantities, which can be thought of as gravitational objects that maintain irregular WH-situations. Based on our findings, we conclude that in the absence of exotic matter, WH can exist in some specific regions of the parametric space using modified gravity model as [Formula: see text].

Meromorphic functions with a polar asymptotic value

This paper is part of a general program in complex dynamics to understand parameter spaces of transcendental maps with finitely many singular values. The simplest families of such functions have two asymptotic values and no critical values. These families, up to affine conjugation, depend on two complex parameters. Understanding their parameter spaces is key to understanding families with more asymptotic values, just as understanding quadratic polynomials was for rational maps more generally. The first such families studied were the one-dimensional slices of the exponential family, exp ⁡ ( z ) + a \exp (z) + a , and the tangent family λ tan ⁡ z \lambda \tan z . The exponential case exhibited phenomena not seen for rational maps: Cantor bouquets in both the dynamic and parameter spaces, and no bounded hyperbolic components. The tangent case, with its two finite asymptotic values ± λ i \pm \lambda i , is closer to the rational case, a kind of infinite degree version of the latter. In this paper, we consider a general family that interpolates between exp ⁡ ( z ) + a \exp (z) + a and λ tan ⁡ z \lambda \tan z . Our new family has two asymptotic values and a one-dimensional slice for which one of the asymptotic values is constrained to be a pole, the “polar asymptotic value” of the title. We show how the dynamic and parameter planes for this slice exhibit behavior that is a surprisingly delicate interplay between that of the exp ⁡ ( z ) + a \exp (z) + a and λ tan ⁡ z \lambda \tan z families.

CIME4R: Exploring iterative, AI-guided chemical reaction optimization campaigns in their parameter space

Chemical reaction optimization (RO) is an iterative process that results in large, high-dimensional datasets. Current tools allow for only limited analysis and understanding of parameter spaces, making it hard for scientists to review or follow changes throughout the process. With the recent emergence of using artificial intelligence (AI) models to aid RO, another level of complexity has been added. Helping to assess the quality of a model’s prediction and understand its decision is critical to supporting human-AI collaboration and trust calibration. To address this, we propose CIME4R—an open-source interactive web application for analyzing RO data and AI predictions. CIME4R supports users in (i) comprehending a reaction parameter space, (ii) investigating how an RO process developed over iterations, (iii) identifying critical factors of a reaction, and (iv) understanding model predictions. This facilitates making informed decisions during the RO process and helps users to review a completed RO process, especially in AI-guided RO. CIME4R aids decision-making through the interaction between humans and AI by combining the strengths of expert experience and high computational precision. We developed and tested CIME4R with domain experts and verified its usefulness in three case studies. Using CIME4R the experts were able to produce valuable insights from past RO campaigns and to make informed decisions on which experiments to perform next. We believe that CIME4R is the beginning of an open-source community project with the potential to improve the workflow of scientists working in the reaction optimization domain.Scientific contributionTo the best of our knowledge, CIME4R is the first open-source interactive web application tailored to the peculiar analysis requirements of reaction optimization (RO) campaigns. Due to the growing use of AI in RO, we developed CIME4R with a special focus on facilitating human-AI collaboration and understanding of AI models. We developed and evaluated CIME4R in collaboration with domain experts to verify its practical usefulness.

Gravitational wave effects and phenomenology of a two-component dark matter model

We study an extension of the Standard Model (SM) which could have two candidates for dark matter (DM) including a Dirac fermion and a vector dark matter (VDM) under a new U(1) gauge group in the hidden sector. The model is classically scale-invariant and the electroweak symmetry breaks because of loop effects. We investigate the parameter space allowed by current experimental constraints and phenomenological bounds. We probe the parameter space of the model in the mass range 1<MV<5000\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$1< M_V<5000$$\\end{document} GeV and 1<Mψ<5000\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$1<M_{\\psi }<5000$$\\end{document} GeV. It has been shown that there are many points in this mass range that are in agreement with all phenomenological constraints. The electroweak phase transition has been discussed and it has been shown that there is region in the parameter space of the model consistent with DM relic density and direct detection constraints that, at the same time, can lead to first-order electroweak phase transition. The gravitational waves produced during the phase transition could be probed by future space-based interferometers such as LISA and BBO.

Wake structure of an array of cylinders in shallow flow

Although there is a range of approaches for classifying the wake structure behind an array of obstacles, these approaches provide inconsistent results across different array systems. This motivates the present study to integrate and reconcile these approaches into one that is consistent across different systems. This new, transferable classification approach is based on the dimensionless flow blockage of the array and the wake stability parameter. To demonstrate this approach, a series of laboratory experiments was conducted to characterise the wake structure behind an array of emergent cylinders across a practically relevant parameter space that has not previously been explored. Two arrays with the same values of flow blockage and wake stability parameters but different sizes display the same wake structure, demonstrating the controlling influence of these two parameters on the wake structure. This approach classifies four different wake structures, which are distinct in that they display differences in instantaneous and time-averaged flow fields, temporal velocity oscillations, shear layer growth and the length of the steady wake region. The dependence of the wake structure on the two parameters is a consequence of (i) the controlling influence of blockage on the fraction of incident flow passing through the array and (ii) the ability of shallowness to suppress wake instabilities and, to a lesser extent, also influence the velocity through the array. This paper provides a predictive framework for the wake structure based on knowledge of the array geometry, and the depth and velocity of incident flow across the entire relevant practical parameter space.

On dynamical system modeling of Learned Primal-Dual with a linear operator $\mathcal{K}$: Stability and convergence properties

Abstract Learned Primal-Dual (LPD) is a deep learning based method for composite optimization problems that is based on unrolling/unfolding the primal-dual hybrid gradient algorithm. While achieving great successes in applications, the mathematical interpretation of LPD as a truncated iterative scheme is not necessarily sufficient to fully understand its properties. In this paper, we study the LPD with a general linear operator. We model the forward propagation of LPD as a system of difference equations and a system of differential equations in discrete- and continuous-time settings (for primal and dual variables/trajectories), which are named discrete-time LPD and continuous-time LPD, respectively. Forward analyses such as stabilities and the convergence of the state variables of the discrete-time LPD to the solution of continuous-time LPD are given. Moreover, we analyze the learning problems with/without regularization terms of both discrete-time and continuous-time LPD from the optimal control viewpoint. We prove convergence results of their optimal solutions with respect to the network state initialization and training data, showing in some sense the topological stability of the learning problems. We also establish convergence from the solution of the discrete-time LPD learning problem to that of the continuous-time LPD learning problem through a piecewise linear extension, under some appropriate assumptions on the space of learnable parameters. This study demonstrates theoretically the robustness of the LPD structure and the associated training process, and can induce some future research and applications.

Passive bionic motion of a flexible film in the wake of a circular cylinder: chaos and periodicity, flow–structure interactions and energy evolution

The self-sustained interactions between a flexible film and periodic vortices epitomize the spirit of fish swimming and flag flapping in nature, involving intricate patterns of flow–structure coupling. Here, we comprehensively investigate the multiple coupling states of a film in the cylinder wake mainly with experiments, complemented by theoretical solutions and nonlinear dynamical analyses. Four regimes of film motion states are identified in the parameter space spanned by the reduced velocity and the length ratio. These regimes are (i) keeping stationary, (ii) deflection flutter, (iii) hybrid flutter and (iv) periodic large-amplitude flapping, each governed by a distinct coupling mechanism, involving regular and irregular Kármán vortices, local instability of the elongated shear layers and 2P mode vortex shedding. The film futtering in regimes (ii) and (iii) is substantiated to be chaotic and bears a resemblance to the ‘entraining state’ of fish behind an obstacle in the river. The periodic flapping in regime (iv) manifests itself in an amalgam of standing and travelling waves, and has intrinsic relations to the ‘Kármán gaiting’ of fish in periodic vortices. With the spatiotemporal reconstruction for the periodic flapping, we procure the energy distributions on the film, revealing the energy transfer processes between the film and the large-scale vortices. The findings unequivocally indicate that the flow–structure interaction during the energy-release stage of the film is more intense than that during the energy-extraction stage. Given the similarities, the mathematical and physical methods presented in this work are also applicable to the research on biological undulatory locomotion.

Optimal parameter-space for stabilizing the ferroelectric phase of Hf0.5Zr0.5O2 thin-films under strain and electric fields

Abstract Hafnia-based ferroelectric materials, like Hf0.5Zr0.5O2 (HZO), have received tremendous attention owing to their potentials for building ultra-thin ferroelectric devices. The orthorhombic(O)-phase of HZO is ferroelectric but metastable in its bulk form under ambient conditions, which poses a considerable challenge to maintaining the operation performance of HZO-based ferroelectric devices. Here, we theoretically addressed this issue that provides parameter spaces for stabilizing the O-phase of HZO thin-films under various conditions. Three mechanisms were found to be capable of lowering the relative energy of the O-phase, namely, more significant surface-bulk portion of (111) surfaces, compressive c-axis strain, and positive electric fields. Considering these mechanisms, we plotted two ternary phase diagrams for HZO thin-films where the strain was applied along the in-plane uniaxial and biaxial, respectively. These diagrams indicate the O-phase could be stabilized by solely shrinking the film-thickness below 12.26 nm, ascribed to its lower surface energies. All these results shed considerable light on designing more robust and higher-performance ferroelectric devices.