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At least 1,675 records · Page 93

Using machine learning to derive cloud condensation nuclei number concentrations from commonly available measurements

Cloud condensation nuclei (CCN) number concentrations are an important aspect of aerosol–cloud interactions and the subsequent climate effects; however, their measurements are very limited. We use a machine learning tool, random decision forests, to develop a random forest regression model (RFRM) to derive CCN at 0.4 % supersaturation ([CCN0.4]) from commonly available measurements. The RFRM is trained on the long-term simulations in a global size-resolved particle microphysics model. Using atmospheric state and composition variables as predictors, through associations of their variabilities, the RFRM is able to learn the underlying dependence of [CCN0.4] on these predictors, which are as follows: eight fractions of PM 2.5 (NH 4 , SO 4 , NO 3, secondary organic aerosol (SOA), black carbon (BC), primary organic carbon (POC), dust, and salt), seven gaseous species (NO x , NH 3 , O 3 , SO 2 , OH, isoprene, and monoterpene), and four meteorological variables (temperature (T), relative humidity (RH), precipitation, and solar radiation). The RFRM is highly robust: it has a median mean fractional bias (MFB) of 4.4 % with ≈96.33 % of the derived [CCN0.4] within a good agreement range of -60% 2.5 speciation (NH 4 , SO 4 , NO 3 , and organic carbon (OC)), NO x , O 3 , SO 2 , T, and RH, as well as [CCN0.4] are available. We modify, optimize, and retrain the developed RFRM to make predictions from 19 to 9 of these available predictors. This retrained RFRM (RFRM-ShortVars) shows a reduction in performance due to the unavailability and sparsity of measurements (predictors); it captures the [CCN0.4] variability and magnitude at SGP with ≈67.02 % of the derived values in the good agreement range. This work shows the potential of using the more commonly available measurements of PM 2.5 speciation to alleviate the sparsity of CCN number concentrations' measurements.

54 ENVIRONMENTAL SCIENCES↗

Spontaneous chiral resolution in two-dimensional systems of patchy particles

Short ranged potentials and their anisotropy produce spontaneous chiral resolution in a two dimensional model of patchy particles introduced in this paper. This model could represent an equimolar binary mixture (racemic mixture) of two kinds of chiral molecules (enantiomers) adsorbed to a bi-dimensional domain where only lateral short ranged interactions are present. Most racemic mixtures undergo chiral resolution due to their spatial anisotropy, the combined effect of long range forces and the thermodynamic conditions. The patchy particles are modeled as a hard disk and four different bonding sites located to produce chirality. Phase behavior and structural properties are analysed using Discontinuous Molecular Dynamics in the canonical ensemble. When the four patchy particles are separated by the angles (60°, 120°, 60°, 120°), spontaneous chiral resolution is produced, given by the formation of homochiral clusters, if started from the corresponding racemic mixture. Gel behavior is also obtained in all the systems for low temperatures and low densities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantum-to-classical correspondence and Hubbard-Stratonovich dynamical systems: A Lie-algebraic approach

We propose a Lie-algebraic duality approach to analyze nonequilibrium evolution of closed dynamical systems and thermodynamics of interacting quantum lattice models (formulated in terms of Hubbard-Stratonovich dynamical systems). The first part of the paper utilizes a geometric Hilbert-space-invariant formulation of unitary time evolution, where a quantum Hamiltonian is viewed as a trajectory in an abstract Lie algebra, while the sought-after evolution operator is a trajectory in a dynamic group, generated by the algebra via exponentiation. The evolution operator is uniquely determined by the time-dependent dual generators that satisfy a system of differential equations, dubbed here dual Schroedinger-Bloch equations, which represent a viable alternative to the conventional Schroedinger formulation. These dual Schroedinger-Bloch equations are derived and analyzed on a number of specific examples. It is shown that deterministic dynamics of a closed classical dynamical system occurs as action of a symmetry group on a classical manifold and is driven by the same dual generators as in the corresponding quantum problem. This represents quantum-to-classical correspondence. In the second part of the paper, we further extend the Lie-algebraic approach to a wide class of interacting many-particle lattice models. A generalized Hubbard-Stratonovich transform is proposed and it is used to show that the thermodynamic partition function of a generic many-body quantum lattice model can be expressed in terms of traces of single-particle evolution operators governed by the dynamic Hubbard-Stratonovich fields. The corresponding Hubbard-Stratonovich dynamical systems are generally nonunitary, which yields a number of notable complications, including breakdown of the global exponential representation. Finally, we derive Hubbard-Stratonovich dynamical systems for the Bose-Hubbard model and a quantum spin model and use the Lie-algebraic approach to obtain new nonperturbative dual descriptions of these theories.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Experimental and Modeling Studies for the Removal of Crystal Violet Dye from Aqueous Solutions using Eco-friendly Gracilaria corticata Seaweed Activated Carbon/Zn/Alginate Polymeric Composite Beads

This research article describes, an eco-friendly activated carbon prepared from the Gracilaria corticata seaweeds which was employed for the preparation of biodegradable polymeric beads for the efficient removal of crystal violet dye in an aqueous solution. The presence of chemical functional groups in the adsorbent material was detected using FTIR spectroscopy. The morphology and physical phases of the adsorbent materials were analyzed using SEM and XRD studies respectively. Batch mode dye adsorption behavior of the activated carbon/Zn/alginate polymeric beads was investigated as a function of dosage, solution pH, contact time, initial dye concentration and temperature. Maximum dye removal was observed at a pH of 5.0, 1 g of adsorbent dosage with 60 mg/L dye concentration, 50 min of contact time and at 30 °C. The equilibrium modeling studies were analyzed with Freundlich and Langmuir adsorption isotherms and the adsorption dynamics was predicted with Lagergren’s pseudo-first order, pseudo-second order equations and intra particle diffusion models. The process of dye removal followed a pseudo second-order kinetics rather than pseudo first order. The thermodynamic parameters like standard Gibbs free energy change (ΔG°), enthalpy change (ΔH°) and entropy change (ΔS°) were determined and the results imply that the adsorption process was spontaneous, endothermic and increases the randomness between the adsorbent and adsorbate. The results from the experimental and correlation data reveal that the Gracilaria corticata activated carbon/Zn/alginate polymeric beads have proved to be an excellent adsorbent material for the removal of CV dye.

36 MATERIALS SCIENCE↗

Ice rule fragility via topological charge transfer in artificial colloidal ice

Artificial particle ices are model systems of constrained, interacting particles. They have been introduced theoretically to study ice-manifolds emergent from frustration, along with domain wall and grain boundary dynamics, doping, pinning-depinning, controlled transport of topological defects, avalanches, and memory effects. Recently such particle-based ices have been experimentally realized with vortices in nano-patterned superconductors or gravitationally trapped colloids. Here we demonstrate that, although these ices are generally considered equivalent to magnetic spin ices, they can access a novel spectrum of phenomenologies that are inaccessible to the latter. With experiments, theory and simulations we demonstrate that in mixed coordination geometries, entropy-driven negative monopoles spontaneously appear at a density determined by the vertex-mixture ratio. Unlike its spin-based analogue, the colloidal system displays a “fragile ice” manifold, where local energetics oppose the ice rule, which is instead enforced through conservation of the global topological charge. The fragile colloidal ice, stabilized by topology, can be spontaneously broken by topological charge transfer.

36 MATERIALS SCIENCE↗

Non-Targeted Effects Models Predict Significantly Higher Mars Mission Cancer Risk than Targeted Effects Models

Cancer risk is an important concern for galactic cosmic ray (GCR) exposures, which consist of a wide-energy range of protons, heavy ions and secondary radiation produced in shielding and tissues. Relative biological effectiveness (RBE) factors for surrogate cancer endpoints in cell culture models and tumor induction in mice vary considerable, including significant variations for different tissues and mouse strains. Many studies suggest non-targeted effects (NTE) occur for low doses of high linear energy transfer (LET) radiation, leading to deviation from the linear dose response model used in radiation protection. Using the mouse Harderian gland tumor experiment, the only extensive data-set for dose response modelling with a variety of particle types (>4), for the first-time a particle track structure model of tumor prevalence is used to investigate the effects of NTEs in predictions of chronic GCR exposure risk. The NTE model led to a predicted risk 2-fold higher compared to a targeted effects model. The scarcity of data with animal models for tissues that dominate human radiation cancer risk, including lung, colon, breast, liver, and stomach, suggest that studies of NTEs in other tissues are urgently needed prior to long-term space missions outside the protection of the Earth’s geomagnetic sphere.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Direct implicit and explicit energy-conserving particle-in-cell methods for modeling of capacitively coupled plasma devices

Achieving large-scale kinetic modeling is a crucial task for the development and optimization of modern plasma devices. With the trend of decreasing pressure in applications, such as plasma etching, kinetic simulations are necessary to self-consistently capture the particle dynamics. The standard, explicit, electrostatic, momentum-conserving particle-in-cell method suffers from restrictive stability constraints on spatial cell size and temporal time step, requiring resolution of the electron Debye length and electron plasma period, respectively. This results in a very high computational cost, making the technique prohibitive for large volume device modeling. We investigate the direct implicit algorithm and the explicit energy conserving algorithm as alternatives to the standard approach, both of which can reduce computational cost with a minimal (or controllable) impact on results. These algorithms are implemented into the well-tested EDIPIC-2D and LTP-PIC codes, and their performance is evaluated via 2D capacitively coupled plasma discharge simulations. The investigation reveals that both approaches enable the utilization of cell sizes larger than the Debye length, resulting in a reduced runtime, while incurring only minor inaccuracies in plasma parameters. The direct implicit method also allows for time steps larger than the electron plasma period; however, care must be taken to avoid numerical heating or cooling. It is demonstrated that by appropriately adjusting the ratio of cell size to time step, it is possible to mitigate this effect to an acceptable level.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Strategy and performance of the CMS long-lived particle trigger program in proton-proton collisions at $\sqrt{s}$ = 13.6 TeV

In the physics program of the CMS experiment during the CERN LHC Run 3, which started in 2022, the long-lived particle triggers have been improved and extended to expand the scope of the corresponding searches. These dedicated triggers and their performance are described in this paper, using several theoretical benchmark models that extend the standard model of particle physics. The results are based on proton-proton collision data collected with the CMS detector during 2022$-$2024 at a center-of-mass energy of 13.6 TeV, corresponding to integrated luminosities of up to 123 fb$^{-1}$.

FOS: Physical sciences↗

Summary of 2016 Light Microscopy Module (LMM) Physical Science Experiments on ISS. Update of LMM Science Experiments and Facility Capabilities

This presentation will feature a series of short, entertaining, and informative videos that describe the current status and science support for the Light Microscopy Module (LMM) facility on the International Space Station. These interviews will focus on current experiments and provide an overview of future capabilities. The recently completed experiments include nano-particle haloing, 3-D self-assembly with Janus particles and a model system for nano-particle drug delivery. The videos will share perspectives from the scientists, engineers, and managers working with the NASA Light Microscopy program.

Sicker, Ronald J.↗

Methodology of modeling and measuring computer architectures for plasma simulations

A brief introduction to plasma simulation using computers and the difficulties on currently available computers is given. Through the use of an analyzing and measuring methodology - SARA, the control flow and data flow of a particle simulation model REM2-1/2D are exemplified. After recursive refinements the total execution time may be greatly shortened and a fully parallel data flow can be obtained. From this data flow, a matched computer architecture or organization could be configured to achieve the computation bound of an application problem. A sequential type simulation model, an array/pipeline type simulation model, and a fully parallel simulation model of a code REM2-1/2D are proposed and analyzed. This methodology can be applied to other application problems which have implicitly parallel nature.

Wang, L. P. T.↗

Differentiable Preisach Modeling for Characterization and Optimization of Particle Accelerator Systems with Hysteresis

Future improvements in particle accelerator performance are predicated on increasingly accurate online modeling of accelerators. Hysteresis effects in magnetic, mechanical, and material components of accelerators are often neglected in online accelerator models used to inform control algorithms, even though reproducibility errors from systems exhibiting hysteresis are not negligible in high precision accelerators. Here, we combine the classical Preisach model of hysteresis with machine learning techniques to efficiently create nonparametric, high-fidelity models of arbitrary systems exhibiting hysteresis. We experimentally demonstrate how these methods can be used in situ, where a hysteresis model of an accelerator magnet is combined with a Bayesian statistical model of the beam response, allowing characterization of magnetic hysteresis solely from beam-based measurements. Finally, we explore how using these joint hysteresis-Bayesian statistical models allows us to overcome optimization performance limitations that arise when hysteresis effects are ignored.

43 PARTICLE ACCELERATORS↗

A variance deconvolution estimator for efficient uncertainty quantification in Monte Carlo radiation transport applications

Monte Carlo simulations are at the heart of many high-fidelity simulations and analyses for radiation transport systems. As is the case with any complex computational model, it is important to propagate sources of input uncertainty and characterize how they affect model output. Unfortunately, uncertainty quantification (UQ) is made difficult by the stochastic variability that Monte Carlo transport solvers introduce. The standard method to avoid corrupting the UQ statistics with the transport solver noise is to increase the number of particle histories, resulting in very high computational costs. In this contribution, we propose and analyze a sampling estimator based on the law of total variance to compute UQ variance even in the presence of residual noise from Monte Carlo transport calculations. Here, we rigorously derive the statistical properties of the new variance estimator, compare its performance to that of the standard method, and demonstrate its use on neutral particle transport model problems involving both attenuation and scattering physics. We illustrate, both analytically and numerically, the estimator’s statistical performance as a function of available computational budget and the distribution of that budget between UQ samples and particle histories. We show analytically and corroborate numerically that the new estimator is unbiased, unlike the standard approach, and is more accurate and precise than the standard estimator for the same computational budget.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Status and prospects of Muon g-2 experiment

This article reviews the muon g-2 experiment, a cornerstone in precision tests of the Standard Model of particle physics. The experiment measures the anomalous magnetic moment of the muon with unprecedented accuracy, seeking potential discrepancies between theoretical predictions and experimental results that might indicate physics beyond the Standard Model. We trace the evolution of this measurement from its beginnings at CERN in the 1960s to the current state-of-the-art experiment at Fermilab, highlighting the remarkable engineering achievements required to achieve parts-per-billion precision. Recent results from Runs 1-3 have achieved a systematic uncertainty of 70 ppb, exceeding design goals, while ongoing theoretical calculations continue to refine predictions. Despite these advances, the analysis remains statistics-limited, with continued data collection and novel experimental approaches at MUonE and J-PARC promising further insights into this fundamental physical quantity.

Karuza, Marin [INFN, Trieste; Rijeka U.] (ORCID:00↗

Analysis of IUE observations of hydrogen in comets

The large body of hydrogen Lyman-alpha observations of cometary comae obtained with the International Ultraviolet Explorer satellite has gone generally unanalyzed because of two main modeling complications. First, the inner comae of many bright (gas productive) comets are often optically thick to solar Lyman-alpha radiation. Second, even in the case of a small comet (low gas production) the large IUE aperture is quite small as compared with the immense size of the hydrogen coma, so an accurate model which properly accounts for the spatial distribution of the coma is required to invert the inferred brightnesses to column densities and finally to H atom production rates. Our Monte Carlo particle trajectory model (MPTM), which for the first time provides the realistic full phase space distribution of H atoms throughout the coma was used as the basis for the analysis of IUE observations of the inner coma. The MCPTM includes the effects of the vectorial ejection of the H atoms upon dissociation of their parent species (H2O and OH) and of their partial collisional thermalization. Both of these effects are crucial to characterize the velocity distribution of the H atoms. A new spherical radiative transfer calculation based on our MCPTM was developed to analyze IUE observations of optically thick H comae. The models were applied to observations of comets P/Giacobini-Zinner and P/Halley.

Combi, Michael R.↗

Analysis of IUE Observations of Hydrogen in Comets

The 15-years worth of hydrogen Lyman-alpha observations of cometary comae obtained with the International Ultraviolet Explorer (IUE) satellite had gone generally unanalyzed because of two main modeling complications. First, the inner comae of many bright (gas productive) comets are often optically thick to solar Lyman-alpha radiation. Second, even in the case of a small comet (low gas production) the large IUE aperture is quite small as compared with the immense size of the hydrogen coma, so an accurate model which properly accounts for the spatial distribution of the coma is required to invert the infrared brightnesses to column densities and finally to H atom production rates. Our Monte Carlo particle trajectory model (MCPTM), which for the first time provides the realistic full phase space distribution of H atoms throughout the coma has been used as the basis for the analysis of IUE observations of the inner coma. The MCPTM includes the effects of the vectorial ejection of the H atoms upon dissociation of their parent species (H2O and OH) and of their partial collisional thermalization. Both of these effects are crucial to characterize the velocity distribution of the H atoms. This combination of the MCPTM and spherical radiative transfer code had already been shown to be successful in understanding the moderately optically thick coma of comet P/Giacobini-Zinner and the coma of comet Halley that varied from being slightly to very optically thick. Both of these comets were observed during solar minimum conditions. Solar activity affects both the photochemistry of water and the solar Lyman-alpha radiation flux. The overall plan of this program here was to concentrate on comets observed by IUE at other time during the solar cycle, most importantly during the two solar maxima of 1980 and 1990. Described herein are the work performed and the results obtained.

Combi, Michael R.↗

Searches for New Physics With Muon Conversion at Fermilab and Triboson Production at the LHC

We report on several efforts to search for physics beyond the standard model of particle physics at broad energy scales. The Mu2e experiment at Fermilab will search for charged lepton flavor violation via the muon to electron conversion process, which is suppressed in the Standard Model. Mu2e will be operated at a low energy, yet can probe New Physics at very high mass scales (O(1e3 - 1e4 ) TeV). At high energies, the CMS experiment at the CERN LHC continues to deliver an impressive suite of Standard Model measurements and limits on a variety of New Physics signatures. Mu2e is under construction and slated to collect its first physics data in the coming years. This thesis describes work done during the construction phase of Mu2e and focuses on two critical areas: magnetic field modeling and statistical analysis. We describe a novel method for field modeling which we validate using a simulated dataset representing the expected magnetic field in the Detector Solenoid. This method blends a standard least-squares fitting technique that utilizes physically motivated analytical model functions with a novel physics informed network that is constructed to obey Maxwell’s equations. We show the technique can model the field with an accuracy of 10−7 despite the presence of injected noise in the pseudo-measurements at the 10−5 level. We then present preliminary results of the calibration of 3D Hall probes at the sub-10−4 level. These probes will be used to directly measure the Mu2e Detector Solenoid magnetic field on a sparse grid; these measurements serve as the input to the field model fitting. Finally, we describe the first implementation of both an unbinned shape analysis and a Bayesian interpretation applied to Mu2e pseudo-data. Up to 20% tighter limits can be set by the shape analysis compared to a standard cut & count analysis. The AlCap experiment collected data at PSI in 2015 to measure several important quantities related to nuclear muon capture on an aluminum target, which is a significant background process for Mu2e. The neutron emission from muon capture can introduce background hits in the Mu2e detectors and can increase radiation damage in various elements of the apparatus. We present measurements of the neutron group fluence and mean neutron multiplicity for muon capture on aluminum nuclei. Finally, we discuss an analysis of triboson production at CMS using an Effective Field Theory framework. Standard Model triboson production, which was first observed at CMS in 2020, has a relatively small cross section and provides direct access to both anomalous triple gauge couplings and quartic gauge couplings. These couplings, interpreted in the Standard Model Effective Field Theory, are studied in the present work. We target the boosted regime where the background rate is low and yields are enhanced when dimension-6 and dimension-8 Wilson coefficients are non-zero. We do not observe an excess in the data and therefore set bounds on the Wilson coefficients. For dimension-6 coefficients the tightest observed (expected) bounds are set on cW /Λ2 where Λ is the mass scale of new physics; the bounds are [−0.13, 0.12] TeV−2 ([−0.12, 0.12] TeV−2 ) at 95% CL. The tightest bounds in dimension-8 are set on fT,0 / Λ4 ; the observed (expected) bounds at 95% CL are [−0.63, 0.69] TeV−4 ([−0.54, 0.62] TeV−4 ). Additional results are presented which include scenarios where multiple Wilson coefficients are non-zero, the application of signal model clipping to address unitarity violation in Effective Field Theories, and a novel template fit developed for easier reinterpretation of our results.

Kampa, Cole Erik [Northwestern U. (main)] (ORCID:0↗

Comprehensive computer model for magnetron sputtering. II. Charged particle transport

Discharges for magnetron sputter thin film deposition systems involve complex plasmas that are sensitively dependent on magnetic field configuration and strength, working gas species and pressure, chamber geometry, and discharge power. The authors present a numerical formulation for the general solution of these plasmas as a component of a comprehensive simulation capability for planar magnetron sputtering. This is an extensible, fully three-dimensional model supporting realistic magnetic fields and is self-consistently solvable on a desktop computer. The plasma model features a hybrid approach involving a Monte Carlo treatment of energetic electrons and ions, along with a coupled fluid model for thermalized particles. Validation against a well-known one-dimensional system is presented. Various strategies for improving numerical stability are investigated as is the sensitivity of the solution to various model and process parameters. In particular, the effect of magnetic field, argon gas pressure, and discharge power are studied.

36 MATERIALS SCIENCE↗