IA Scholar Query: Moment closure based parameter inference of stochastic kinetic models.
https://scholar.archive.org/
Internet Archive Scholar query results feedeninfo@archive.orgTue, 02 Aug 2022 00:00:00 GMTfatcat-scholarhttps://scholar.archive.org/help1440Catalyst: Fast Biochemical Modeling with Julia
https://scholar.archive.org/work/rhmtroyk2ncitn7f5fb442zwte
AbstractWe introduce Catalyst.jl, a flexible and feature-filled Julia library for modeling and high performance simulation of chemical reaction networks (CRNs). Catalyst acts as both a domain-specific language and an intermediate representation for symbolically encoding CRN models as Julia-native objects. This enables a pipeline of symbolically specifying, analyzing, and modifying reaction networks; converting Catalyst models to symbolic representations of concrete mathematical models; and generating compiled code for use in numerical solvers. Currently Catalyst supports conversion to symbolic discrete stochastic chemical kinetics (jump process), chemical Langevin (stochastic differential equation), and mass-action reaction rate equation (ordinary differential equation) models. Leveraging ModelingToolkit.jl and Symbolics.jl, Catalyst models can be analyzed, simplified, and compiled into optimized representations for use in a broad variety of numerical solvers. The performance of the numerical solvers Catalyst targets is illustrated across a variety of reaction networks by benchmarking stochastic simulation algorithm and ODE solver performance. We demonstrate the extendability and composability of Catalyst by highlighting both how it can compose with a variety of Julia libraries, and how existing open source projects have extended the intermediate representation. These benchmarks demonstrate significant performance improvements compared to several popular reaction network simulators.Torkel E. Loman, Yingbo Ma, Vasily Ilin, Shashi Gowda, Niklas Korsbo, Nikhil Yewale, Chris Rackauckas, Samuel A. Isaacsonwork_rhmtroyk2ncitn7f5fb442zwteTue, 02 Aug 2022 00:00:00 GMTRandom walks on mated-CRT planar maps and Liouville Brownian motion
https://scholar.archive.org/work/vsyiofri7rao5js3o6hvjrhae4
We prove a scaling limit result for random walk on certain random planar maps with its natural time parametrization. In particular, we show that for γ∈ (0,2), the random walk on the mated-CRT map with parameter γ converges to γ-Liouville Brownian motion, the natural quantum time parametrization of Brownian motion on a γ-Liouville quantum gravity (LQG) surface. Our result applies if the mated-CRT map is embedded into the plane via the embedding which comes from SLE / LQG theory or via the Tutte embedding (a.k.a. the harmonic or barycentric embedding). In both cases, the convergence is with respect to the local uniform topology on curves and it holds in the quenched sense, i.e., the conditional law of the walk given the map converges. Previous work by Gwynne, Miller, and Sheffield (2017) showed that the random walk on the mated-CRT map converges to Brownian motion modulo time parametrization. This is the first work to show the convergence of the parametrized walk. As an intermediate result of independent interest, we derive an axiomatic characterisation of Liouville Brownian motion, for which the notion of Revuz measure of a Markov process plays a crucial role.Nathanael Berestycki, Ewain Gwynnework_vsyiofri7rao5js3o6hvjrhae4Fri, 29 Jul 2022 00:00:00 GMTTurbulence in the outer heliosphere
https://scholar.archive.org/work/pe4rhp3orbagfpr7s52u6jlkei
The solar wind (SW) and local interstellar medium (LISM) are turbulent media. Their interaction is governed by complex physical processes and creates heliospheric regions with significantly different properties in terms of particle populations, bulk flow and turbulence. Our knowledge of the solar wind turbulence \nature and dynamics mostly relies on near-Earth and near-Sun observations, and has been increasingly improving in recent years due to the availability of a wealth of space missions, including multi-spacecraft missions. In contrast, the properties of turbulence in the outer heliosphere are still not completely understood. In situ observations by Voyager and New Horizons, and remote neutral atom measurements by IBEX strongly suggest that turbulence is one of the critical processes acting at the heliospheric interface. It is intimately connected to charge exchange processes responsible for the production of suprathermal ions and energetic neutral atoms. This paper reviews the observational evidence of turbulence in the distant SW and in the LISM, advances in modeling efforts, and open challenges.Federico Fraternale, Laxman Adhikari, Horst Fichtner, Tae K. Kim, Jens Kleimann, Sean Oughton, Nikolai V. Pogorelov, Vadim Roytershteyn, Charles W. Smith, Arcadi V. Usmanov, G P. Zank, Lingling Zhaowork_pe4rhp3orbagfpr7s52u6jlkeiThu, 28 Jul 2022 00:00:00 GMTStatistical-physics approaches to RNA molecules, families and networks
https://scholar.archive.org/work/35dikoi5b5ayroy54n2xv2j6la
This contribution focuses on the fascinating RNA molecule, its sequence-dependent folding driven by base-pairing interactions, the interplay between these interactions and natural evolution, and its multiple regulatory roles. The four of us have dug into these topics using the tools and the spirit of the statistical physics of disordered systems, and in particular the concept of a disordered (energy/fitness) landscape. After an introduction to RNA molecules and the perspectives they open not only in evolutionary and synthetic biology but also in medicine, we will introduce the important notions of energy and fitness landscapes for these molecules. In Section III we will review some models and algorithms for RNA sequence-to-secondary-structure mapping. Section IV discusses how the secondary-structure energy landscape can be derived from unzipping data. Section V deals with the inference of RNA structure from evolutionary sequence data sampled in different organisms. This will shift the focus from the 'sequence-to-structure' mapping described in Section III to a 'sequence-to-function' landscape that can be inferred from laboratory evolutionary data on DNA aptamers. Finally, in Section VI, we shall discuss the rich theoretical picture linking networks of interacting RNA molecules to the organization of robust, systemic regulatory programs. Along this path, we will therefore explore phenomena across multiple scales in space, number of molecules and time, showing how the biological complexity of the RNA world can be captured by the unifying concepts of statistical physics.Simona Cocco, Andrea De Martino, Andrea Pagnani, Martin Weigtwork_35dikoi5b5ayroy54n2xv2j6laWed, 27 Jul 2022 00:00:00 GMTMulti-Stage Heavy Quark Transport in Ultra-relativistic Heavy-ion Collisions
https://scholar.archive.org/work/asulvlzienfnngbuxvoorj4jay
The quark gluon plasma (QGP) is one of the most interesting forms of matter providing us with insight on quantum chromodynamics (QCD) and the early universe. It is believed that the heavy-ion collision experiments at the Relativistic Heavy Ion Collider (RHIC) and the Large Hadron Collider (LHC) have created the QGP medium by colliding two heavy nuclei at nearly the speed of light. Since the collision happens really fast, we can not observe the QGP directly. Instead, we look at the hundreds or even thousands of final hadrons coming out of the collision. In particular, jet and heavy flavor observables are excellent probes of the transport properties of such a medium. On the theoretical side, computational models are essential to make the connections between the final observables and the plasma. Previously studies have employed a comprehensive multistage modeling approach of both the probes and the medium. In this dissertation, heavy quarks are investigated as probes pf the QGP. First, the framework that describes the evolution of both soft and hard particles during the collision is discussed, which includes initial condition, hydrodynamical expansion, parton transport, hadronization, and hadronic rescattering. It has recently been organized into the Jet Energy-loss Tomography with a Statistically and Computationally Advanced Program Envelope (JETSCAPE) framework, which allows people to study heavy-ion collision in a more systematic manner. To study the energy loss of hard partons inside the QGP medium, the linear Boltzmann transport model (LBT) and in medium DGLAP evolution (implemented in the MATTER model) are combined and have achieved a simultaneous description of both charged hadron, D meson, and inclusive jet observables. To further extract the transport coefficients, a Bayesian analysis is conducted which constrains the parameters in the transport models.Wenkai Fanwork_asulvlzienfnngbuxvoorj4jayMon, 25 Jul 2022 00:00:00 GMTMHD Turbulence: A Biased Review
https://scholar.archive.org/work/mjk25fck3vaztfmfmog3yw532m
This review puts the developments of the last few years in the context of the canonical time line (Kolmogorov to Iroshnikov-Kraichnan to Goldreich-Sridhar to Boldyrev). It is argued that Beresnyak's objection that Boldyrev's alignment theory violates the RMHD rescaling symmetry can be reconciled with alignment if the latter is understood as an intermittency effect. Boldyrev's scalings, recovered in this interpretation, are thus an example of a physical theory of intermittency in a turbulent system. Emergence of aligned structures brings in reconnection physics, so the theory of MHD turbulence intertwines with the physics of tearing and current-sheet disruption. Recent work on this by Loureiro, Mallet et al. is reviewed and it is argued that we finally have a reasonably complete picture of MHD cascade all the way to the dissipation scale. This picture appears to reconcile Beresnyak's Kolmogorov scaling of the dissipation cutoff with Boldyrev's aligned cascade. These ideas also enable some progress in understanding saturated MHD dynamo, argued to be controlled by reconnection and to contain, at small scales, a tearing-mediated cascade similar to its strong-mean-field counterpart. On the margins of this core narrative, standard weak-MHD-turbulence theory is argued to require adjustment - and a scheme for it is proposed - to take account of the part that a spontaneously emergent 2D condensate plays in mediating the Alfven-wave cascade. This completes the picture of the MHD cascade at large scales. A number of outstanding issues are surveyed, concerning imbalanced MHD turbulence (for which a new theory is proposed), residual energy, subviscous and decaying regimes of MHD turbulence (where reconnection again features prominently). Finally, it is argued that the natural direction of research is now away from MHD and into kinetic territory.Alexander A. Schekochihinwork_mjk25fck3vaztfmfmog3yw532mTue, 19 Jul 2022 00:00:00 GMTCoupling Quantum Matter and Gravity
https://scholar.archive.org/work/7f5x67aemfg6rgntclhofwkw3m
In this contribution we deal with several issues one encounters when trying to couple quantum matter to classical gravitational fields. We start with a general background discussion and then move on to two more technical sections. In the first technical part we consider the question how the Hamiltonian of a composite two-particle system in an external gravitational field can be computed in a systematic post-Newtonian setting without backreaction. This enables us to reliably estimate the consistency and completeness of less systematic and more intuitive approaches that attempt to solve this problem by adding 'relativistic effects' by hand. In the second technical part we consider the question of how quantum matter may act as source for classical gravitational fields via the semiclassical Einstein equations. Statements to the effect that this approach is fundamentally inconsistent are critically reviewed.Domenico Giulini, André Großardt, Philip K. Schwartzwork_7f5x67aemfg6rgntclhofwkw3mMon, 11 Jul 2022 00:00:00 GMTKinetic Turbulence in Collisionless High-Beta Plasmas
https://scholar.archive.org/work/m4ej6vadczdnnpijac5e4wur2i
We present results from three-dimensional hybrid-kinetic simulations of Alfvénic turbulence in a high-beta, collisionless plasma. The key feature of such turbulence is the interplay between local wave-wave interactions between the fluctuations in the cascade and the non-local wave-particle interactions associated with kinetic micro-instabilities driven by anisotropy in the thermal pressure (namely, firehose, mirror, and ion-cyclotron). We present theoretical estimates for, and calculate directly from the simulations, the effective collisionality and plasma viscosity in pressure-anisotropic high-beta turbulence, demonstrating that, for strong Alfvénic turbulence, the effective parallel viscous scale is comparable to the driving scale of the cascade. Most of the cascade energy (80-90 combination of Landau damping and anisotropic viscous heating. The kinetic-energy spectrum of the turbulence has a slope steeper than -5/3 due to the anisotropic viscous stress. The magnetic-energy spectrum is shallower than -5/3 near the ion-Larmor scale due to fluctuations produced by the firehose instability. Our results have implications for models of particle heating in low-luminosity accretion onto supermassive black holes, the effective viscosity of the intracluster medium, and the interpretation of near-Earth solar-wind observations.Lev Arzamasskiywork_m4ej6vadczdnnpijac5e4wur2iMon, 11 Jul 2022 00:00:00 GMTFermionic Entanglement and Correlation
https://scholar.archive.org/work/fhdg2z6uvbfqhaigqdvt33jisi
Entanglement plays a central role in numerous fields of quantum science. However, as one departs from the typical "Alice versus Bob" setting into the world of indistinguishable fermions, it is not immediately clear how the concept of entanglement is defined among these identical particles. Our endeavor to recover the notion of subsystems, or mathematically speaking, the tensor product structure of the Hilbert space, lead to two natural pictures of defining fermionic entanglement: the particle picture and the mode picture. In the particle picture, entanglement characterizes the deviation of a fermionic quantum state from the non-interacting ones, e.g., single Slater determinants. In the mode picture, we recover the notion of subsystems, by referring to the partitioning of the orbital/mode that the fermions occupy, which allows us to naturally adopt the formalism of entanglement between distinguishable constituents. Both pictures reveal essential and interconnected aspects of fermionic entanglement, and thus offer precise tools for studying electron entanglement in highly relevant systems such as atoms and molecules. We showcase here two applications: i) resolving the correlation paradox in the molecular dissociation limit, ii) quantitative electronic structure analysis with orbital entanglement.Lexin Dingwork_fhdg2z6uvbfqhaigqdvt33jisiFri, 08 Jul 2022 00:00:00 GMTSimulating radio synchrotron emission in star-forming galaxies: small-scale magnetic dynamo and the origin of the far infrared-radio correlation
https://scholar.archive.org/work/2aot4tw54jbjzo7lid7ho5pd2y
In star-forming galaxies, the far-infrared (FIR) and radio-continuum luminosities obey a tight empirical relation over a large range of star-formation rates (SFR). We examine magneto-hydrodynamic galaxy simulations with cosmic rays (CRs), accounting for their advective and anisotropic diffusive transport. We show that gravitational collapse of the proto-galaxy generates a corrugated accretion shock, which injects turbulence and drives a small-scale magnetic dynamo. As the shock propagates outwards and the associated turbulence decays, the large velocity shear between the supersonically rotating cool disc with respect to the (partially) pressure-supported hot circumgalactic medium excites Kelvin-Helmholtz surface and body modes. Those inject turbulence and drive multiple small-scale dynamos, which exponentially amplify magnetic fields. They grow in scale to reach equipartition with thermal and CR energies in Milky Way-mass galaxies. In small galaxies, the magnetic energy saturates at the turbulent energy while it fails to reach equipartition with thermal and CR energies. We solve for steady-state spectra of CR protons, secondary electrons/positrons from hadronic CR-proton interactions with the interstellar medium, and primary shock-accelerated electrons at supernovae. The radio-synchrotron emission is dominated by primary electrons, irradiates the magnetised disc, bulge, and bubble-shaped magnetically-loaded outflows of our simulated Milky Way-mass galaxy. Our star-forming and star-bursting galaxies with saturated magnetic fields match the global FIR-radio correlation (FRC) across four orders of magnitude. Its intrinsic scatter arises due to (i) different magnetic saturation levels that result from different seed magnetic fields, (ii) different radio synchrotron luminosities for different specific SFRs at fixed SFR and (iii) a varying radio intensity with galactic inclination. (abridged)Christoph Pfrommer, Maria Werhahn, Rüdiger Pakmor, Philipp Girichidis, Christine M. Simpsonwork_2aot4tw54jbjzo7lid7ho5pd2yTue, 05 Jul 2022 00:00:00 GMTFirst 3D radiation-hydrodynamic simulations of Wolf-Rayet winds
https://scholar.archive.org/work/boqtmz3mqzhj3o3pnmm64pnqqi
Context. Classical Wolf-Rayet (WR) stars are direct supernova progenitors undergoing vigorous mass loss. Understanding the dense and fast outflows of such WR stars is thus crucial for understanding advanced stages of stellar evolution and the dynamical feedback of massive stars on their environments, and for characterizing the distribution of black hole masses. Aims. In this paper, we develop the first time-dependent, multidimensional, radiation-hydrodynamical models of the extended optically thick atmospheres and wind outflows of hydrogen-free classical WR stars. Methods. A flux-limiting radiation hydrodynamics approach is used on a finite volume mesh to model WR outflows. The opacities are described using a combination of tabulated Rosseland mean opacities and the enhanced line opacities expected within a supersonic flow. Results. For high-luminosity models, a radiation-driven, dense, supersonic wind is launched from deep subsurface regions associated with peaks in the Rosseland mean opacity. For a model with lower luminosity, on the other hand, the Rosseland mean opacity is not sufficient to sustain a net-radial outflow in the subsurface regions. Instead, what develops in this case, is a "standard" line-driven wind launched from the optically thin regions above an extended, moderately inflated, and highly turbulent atmosphere. We thus find here a natural transition from optically thick outflows of classical WR stars to optically thin winds of hot, compact subdwarfs; in our simulations, this transition occurs approximately at a luminosity that is ∼ 40% of the Eddington luminosity. Because of the changing character of the wind-launching mechanism, this transition is also accompanied by a large drop (on the low-luminosity end) in the average mass-loss rate. Since the subsurface opacity peaks are further associated with convective instabilities, the flows are highly structured and turbulent, consisting of coexisting regions of outflowing, stagnated, and even pockets of infalling gas. Typical velocity dispersions in our 3D models are high, 100-300 km/s, but the clumping factors are rather modest, f cl ≡ ρ 2 / ρ 2 ∼ 2. We further find that, while the low-density gas in our simulations is strongly radiation-driven, the overdense structures are, after their initial launch, primarily advected outward by ram-pressure gradients. This inefficient radiative acceleration of dense "clumps" reflects the inverse dependence of line driving on mass density and leads to a general picture wherein high-density gas parcels move significantly slower than the mean and low-density wind material.N. Moens, L. G. Poniatowski, L. Hennicker, J. O. Sundqvist, I. El Mellah, N. D. Keework_boqtmz3mqzhj3o3pnmm64pnqqiThu, 30 Jun 2022 00:00:00 GMTIdentifying predictors of thoracic aortic dissection in patients with proximal aortopathy
https://scholar.archive.org/work/eilk2wjo3bgynglx5bf6zjurp4
Thoracic aortic aneurysms (TAA) are life-threatening conditions with a rising prevalence in the UK, especially with an ageing population. Progressive vessel dilatation weakens the aortic wall over time leading to a sudden and often fatal acute event: type A acute aortic dissection (TAAD). The diagnostic method for risk stratifying TAA in the clinical setting remains limited to a single diameter measurement from cross sectional imaging. The most up-to-date European and American guidelines cite only aneurysm size as a guide to evaluating the risk of rupture. The diameter threshold recommended (>55mm as measured in cross sectional imaging) is inadequate in many cases (almost half of aortic dissections occur below this cut-off). Meanwhile, the infrastructure and algorithms for the diagnosis and management of AAD remain considerably limited, leading to a persistently high rate of misdiagnosis. In this thesis, I adopted a multimodal approach to characterising TAA in a cohort of patients focusing on four key areas of research: i) computational pathology; ii) targeted genetic sequencing; iii) mechanical characterisation of TAA tissue; and iv) aortic flow dynamics. Through this work, we have demonstrated three key findings. Firstly, medial degeneration occurs in hotspots of disease, affecting the outer curve more so, and microstructural features are directly related to in-vivo measures of mean arterial pressure and pulse wave velocity, as well as a potential link to underlying genomic variances. Secondly, the TAA wall is stiffer in the circumferential direction with a lower peeling force compared to longitudinally orientated aortic wall. Thirdly, wall shear stress (WSS) as deciphered from dynamic imaging, was higher on the outer curve of the aorta, and strongly associated with areas of reduced aortic tissue peeling force and aortic wall degeneration. Most importantly, TAA material properties were unrelated to aneurysm diameter. These findings support the hypothesis of flow mediated degeneration in TAA pathology and set [...]Mohammad Yousuf Bilal Salmasi, Thanos Athanasiou, National Institute For Health Research (Great Britain), Imperial College Londonwork_eilk2wjo3bgynglx5bf6zjurp4Wed, 29 Jun 2022 00:00:00 GMTExtracting Information from Stochastic Trajectories of Gene Expression
https://scholar.archive.org/work/uoaplswbyzh3pownhjxht4d5fa
Gene expression is a stochastic process in which cells produce biomolecules essential to the function of life. Modern experimental methods allow for the measurement of biomolecules at single-cell and single-molecule resolution over time. Mathematical models are used to make sense of these experiments. The codesign of experiments and models allows one to use models to design optimal experiments, and to find experiments which provide as much information as possible about relevant model parameters. Here, we provide a formulation of Fisher information for trajectories sampled from the continuous time Markov processes often used to model biological systems, and apply the result to potentially correlated measurements of stochastic gene expression. We validate the result on two commonly used models of gene expression and show it can be used to optimize measurement periods for simulated single-cell fluorescence microscopy experiments. Finally, we use a connection between Fisher information and mutual information to derive channel capacities of nonlinearly regulated gene expression.Zachary R Foxwork_uoaplswbyzh3pownhjxht4d5faWed, 29 Jun 2022 00:00:00 GMTAn introduction to infinite-dimensional differential geometry
https://scholar.archive.org/work/px2ibh7vibdndczfno3c37er2a
The present document is the draft of a book which presents an introduction to infinite-dimensional differential geometry beyond Banach manifolds. As is well known the usual calculus breaks down in this setting. Hence, we replace it by the more general Bastiani calculus which is built using directional derivatives. We then focus on two main areas of infinite-dimensional geometry: 1. infinite-dimensional Lie groups, and 2. weak Riemannian geometry. Both topics are developed and connected to manifolds of (smooth) mappings. These manifolds are studied in detail to construct important examples such as diffeomorphism groups, loop groups and Riemannian metrics for shape analysis. Manifolds of mappings are prime examples for surprising connections between finite and infinite-dimensional geometry. However, also pathologies occurring in infinite-dimensions will be highlighted in many examples. The geometric techniques developed will then be showcased in modern applications of geometry such as geometric hydrodynamics, higher geometry in the guise of Lie groupoids and rough path theory.Alexander Schmedingwork_px2ibh7vibdndczfno3c37er2aSun, 26 Jun 2022 00:00:00 GMTQuantifying biochemical reaction rates from static population variability within incompletely observed complex networks
https://scholar.archive.org/work/kfx4zxz4fvdqvbg5zkthep54nu
Quantifying biochemical reaction rates within complex cellular processes remains a key challenge of systems biology even as high-throughput single-cell data have become available to characterize snapshots of population variability. That is because complex systems with stochastic and non-linear interactions are difficult to analyze when not all components can be observed simultaneously and systems cannot be followed over time. Instead of using descriptive statistical models, we show that incompletely specified mechanistic models can be used to translate qualitative knowledge of interactions into reaction rate functions from covariability data between pairs of components. This promises to turn a globally intractable problem into a sequence of solvable inference problems to quantify complex interaction networks from incomplete snapshots of their stochastic fluctuations.Timon Wittenstein, Nava Leibovich, Andreas Hilfingerwork_kfx4zxz4fvdqvbg5zkthep54nuWed, 22 Jun 2022 00:00:00 GMTA directed walk in probability space that locates mean field solutions to spin models
https://scholar.archive.org/work/tjasytloo5bafgup4ec3ek664a
Despite their formal simplicity, most lattice spin models cannot be easily solved, even under the simplifying assumptions of mean field theory. In this manuscript, we present a method for generating mean field solutions to classical continuous spins. We focus our attention on systems with non-local interactions and non-periodic boundaries, which require careful handling with existing approaches, such as Monte Carlo sampling. Our approach utilizes functional optimization to derive a closed-form optimality condition and arrive at self-consistent mean field equations. We show that this approach significantly outperforms conventional Monte Carlo sampling in convergence speed and accuracy. To convey the general concept behind the approach, we first demonstrate its application to a simple system - a finite one-dimensional dipolar chain in an external electric field. We then describe how the approach naturally extends to more complicated spin systems and to continuum field theories. Furthermore, we numerically illustrate the efficacy of our approach by highlighting its utility on nonperiodic spin models of various dimensionality.Yizhi Shen, Adam P. Willardwork_tjasytloo5bafgup4ec3ek664aTue, 21 Jun 2022 00:00:00 GMTMulti-Scale Modeling of Plastic Waste Gasification: Opportunities and Challenges
https://scholar.archive.org/work/wacrxr56hbfd3lvhbutfrzd6qy
Among the different thermo-chemical recycling routes for plastic waste valorization, gasification is one of the most promising, converting plastic waste into syngas (H2+CO) and energy in the presence of an oxygen-rich gas. Plastic waste gasification is associated with many different complexities due to the multi-scale nature of the process, the feedstock complexity (mixed polyolefins with different contaminations), intricate reaction mechanisms, plastic properties (melting behavior and molecular weight distribution), and complex transport phenomena in a multi-phase flow system. Hence, creating a reliable model calls for an extensive understanding of the phenomena at all scales, and more advanced modeling approaches than those applied today are required. Indeed, modeling of plastic waste gasification (PWG) is still in its infancy today. Our review paper shows that the thermophysical properties are rarely properly defined. Challenges in this regard together with possible methodologies to decently define these properties have been elaborated. The complexities regarding the kinetic modeling of gasification are numerous, compared to, e.g., plastic waste pyrolysis, or coal and biomass gasification, which are elaborated in this work along with the possible solutions to overcome them. Moreover, transport limitations and phase transformations, which affect the apparent kinetics of the process, are not usually considered, while it is demonstrated in this review that they are crucial in the robust prediction of the outcome. Hence, possible approaches in implementing available models to consider these limitations are suggested. Finally, the reactor-scale phenomena of PWG, which are more intricate than the similar processes—due to the presence of molten plastic—are usually simplified to the gas-solid systems, which can result in unreliable modeling frameworks. In this regard, an opportunity lies in the increased computational power that helps improve the model's precision and allows us to include those complexities within the multi-scale PWG modeling. Using the more accurate modeling methodologies in combination with multi-scale modeling approaches will, in a decade, allow us to perform a rigorous optimization of the PWG process, improve existing and develop new gasifiers, and avoid fouling issues caused by tar.Sepehr Madanikashani, Laurien Vandewalle, Steven De Meester, Juray De Wilde, Kevin Van Geemwork_wacrxr56hbfd3lvhbutfrzd6qyTue, 14 Jun 2022 00:00:00 GMTCherenkov radiation with massive bosons and quantum friction
https://scholar.archive.org/work/2iu5ofenizf35guym4vu2fekla
This work is devoted to several translation-invariant models in non-relativistic quantum field theory (QFT), describing a non-relativistic quantum particle interacting with a quantized relativistic field of bosons. In this setting, we aim at the rigorous study of Cherenkov radiation or friction effects at small disorder, which amounts to the metastability of the embedded mass shell of the free non-relativistic particle when the coupling to the quantized field is turned on. Although this problem is naturally approached by means of Mourre's celebrated commutator method, important regularity issues are known to be inherent to QFT models and restrict the application of this method. In this perspective, we introduce a novel non-standard construction procedure for Mourre conjugate operators, which differs from second quantization and allows to circumvent regularity issues. To show its versatility, we apply this construction to the Nelson model with massive bosons, to Fr\"ohlich's polaron model, and to a quantum friction model with massless bosons introduced by Bruneau and De Bi\'evre: for each of these examples, we improve on previous results.Mitia Duerinckx, Christopher Shirleywork_2iu5ofenizf35guym4vu2feklaMon, 13 Jun 2022 00:00:00 GMTMIXED-INTEGER OPTIMIZATION FOR NANOMATERIAL DESIGN AND OPTIMIZATION UNDER UNCERTAINTY FOR NONLINEAR PROCESS MODELS
https://scholar.archive.org/work/l6mmsoietfhgnfa6pfdoziqipe
In the first part of this work, we consider small nanoparticles, a.k.a. nanoclusters, of transition metals. Transition metal nanoclusters have been studied extensively for a wide range of applications due to their highly tunable properties dependent on size, structure, and composition. For these small particles, there has been considerable effort towards theoretically predicting what is the most energetically favorable arrangement of atoms. To that end, we develop a computational framework that couples density-functional theory calculations with mathematical optimization modeling to identify highly stable, mono-metallic transition metal nanoclusters at various sizes. Next, we devise a novel computational framework for the robust optimization of highly nonlinear, non-convex models that possess uncertain data. The proposed method is a generalization of a robust cutting-set algorithm that can handle models containing irremovable equality constraints, as is often the case with models in the process systems engineering domain. Additionally, we accommodate general forms of decision rules to facilitate recourse in second-stage degrees of freedom. Our proposed approach is demonstrated on three process flowsheet models, including a relatively complex model for amine-based CO2 capture. Finally, we propose an open-source robust optimization solver implementation of our cutting-set approach called PyROS. PyROS is a Python-based robust optimization meta-solver for solving non-convex, two-stage optimization models using adjustable robust optimization. The PyROS solver enables facile robust optimization tasks given a deterministic model and description of uncertainty. With each of the applications presented here, we illustrate that mathematical optimization modeling and algorithms can be effectively utilized to address open problems in engineering.Natalie Isenbergwork_l6mmsoietfhgnfa6pfdoziqipeThu, 09 Jun 2022 00:00:00 GMTInformation-theoretic formulation of dynamical systems: causality, modeling, and control
https://scholar.archive.org/work/2zcjr4bh2jegvk7nvoaxyn2w54
The problems of causality, modeling, and control for chaotic, high-dimensional dynamical systems are formulated in the language of information theory. The central quantity of interest is the Shannon entropy, which measures the amount of information in the states of the system. Within this framework, causality is quantified by the information flux among the variables of interest in the dynamical system. Reduced-order modeling is posed as a problem related to the conservation of information in which models aim at preserving the maximum amount of relevant information from the original system. Similarly, control theory is cast in information-theoretic terms by envisioning the tandem sensor-actuator as a device reducing the unknown information of the state to be controlled. The new formulation is used to address three problems about the causality, modeling, and control of turbulence, which stands as a primary example of a chaotic, high-dimensional dynamical system. The applications include the causality of the energy transfer in the turbulent cascade, subgrid-scale modeling for large-eddy simulation, and flow control for drag reduction in wall-bounded turbulence.Adrián Lozano-Durán, Gonzalo Arranzwork_2zcjr4bh2jegvk7nvoaxyn2w54Tue, 31 May 2022 00:00:00 GMT