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Understanding and predicting complex dynamics in accelerators is necessary for their successful operation. A grand challenge in accelerator physics is to develop predictive virtual accelerators that mitigate design cost and schedule risk. Data-driven techniques greatly appeal to generating virtual accelerators due to their limited dimensionality compared with first-principle simulation, yet require significant up-front investment and lack interpretability in the context of governing equations. This paper uses an alternative, interpretable, data-driven technique called Sparse Identification of Nonlinear Dynamics (SINDy) developed by University of Washington researchers to study nonlinear beam centroid dynamics excited by realistic beam injection. We propose evolution equations based solely on data analysis and intuition of the underlying lattice structure, without recourse to an underlying first-principles centroid model nor the actual lattice forcing functions. We do this to mimic an application environment where analytic models are inadequate or where detailed lattice forcing functions are unknown. In the context of the accurate centroid model, we report and interpret SINDy's beam evolution equations learned from the training data and show favorable prediction results. We compare with an alternative machine learning model used on the same training data and contrast its prediction ability, computational expense, and interpretability with SINDy's results.

Jupiter's Great Red Spot (GRS) was mapped by the James Webb Space Telescope (JWST)/Mid-Infrared Instrument (4.9-27.9 micron) in July and August 2022. These observations took place alongside a suite of visual and infrared observations from; Hubble, JWST/NIRCam, Very Large Telescope/VISIR and amateur observers which provided both spatial and temporal context across the jovian disc. The stratospheric temperature structure retrieved using the NEMESIS software revealed a series of hot-spots above the GRS. These could be the consequence of GRS-induced wave activity. In the troposphere, the temperature structure was used to derive the thermal wind structure of the GRS vortex. These winds were only consistent with the independently determined wind field by JWST/NIRCam at 240 mbar if the altitude of the Hubble-derived winds were located around 1,200 mbar, considerably deeper than previously assumed. No enhancement in ammonia was found within the GRS but a link between elevated aerosol and phosphine abundances was observed within this region. North-south asymmetries were observed in the retrieved temperature, ammonia, phosphine and aerosol structure, consistent with the GRS tilting in the north-south direction. Finally, a small storm was captured north-west of the GRS that displayed a considerable excess in retrieved phosphine abundance, suggestive of vigorous convection. Despite this, no ammonia ice was detected in this region. The novelty of JWST required us to develop custom-made software to resolve challenges in calibration of the data. This involved the derivation of the "FLT-5" wavelength calibration solution that has subsequently been integrated into the standard calibration pipeline., Comment: 53 pages, 19 figures, 4 tables

Terawatt x-ray free-electron lasers (XFELs) represent the frontier in further development of x-ray sources and require high current densities with strong transverse focusing. In this paper, we investigate the implications/potentialities of TW XFELs on the generation of harmonics at still shorter wavelengths and higher photon energies with variable polarization. The simulations indicate that significant power levels are possible at high harmonics of the XFEL resonance and that these XFELs can be an important coherent source of hard x-rays through the gamma ray spectrum. For this purpose, we use the MINERVA simulation code which self-consistently includes harmonic generation. Both helical and planar undulators are discussed in which the fundamental is at 1.5 {\AA} and study the associated harmonic generation. While tapered undulators are needed to reach TW powers at the fundamental, the taper does not enhance the harmonics because the taper must start before saturation of the fundamental, while the harmonics saturate before this point is reached. Nevertheless, the harmonics reach substantial powers. Simulations indicate that, for the parameters under consideration, peak powers of the order of 180 MW are possible at the fifth harmonic with a photon energy of about 41 keV and still high harmonics may also be generated at substantial powers. Such high harmonic powers are certain to enable a host of enhanced applications, Comment: 7 pages, 12 figures

GPU-enhanced architectures are now dominant in HPC systems, but message-passing communication involving GPUs with MPI has proven to be both complex and expensive, motivating new approaches that lower such costs. We compare and contrast stream/graph- and kernel-triggered MPI communication abstractions, whose principal purpose is to enhance the performance of communication when GPU kernels create or consume data for transfer through MPI operations. Researchers and practitioners have proposed multiple potential APIs for stream and/or kernel triggering that span various GPU architectures and approaches, including MPI-4 partitioned point-to-point communication, stream communicators, and explicit MPI stream/queue objects. Designs breaking backward compatibility with MPI are duly noted. Some of these strengthen or weaken the semantics of MPI operations. A key contribution of this paper is to promote community convergence toward a stream- and/or kernel-triggering abstraction by highlighting the common and differing goals and contributions of existing abstractions. We describe the design space in which these abstractions reside, their implicit or explicit use of stream and other non-MPI abstractions, their relationship to partitioned and persistent operations, and discuss their potential for added performance, how usable these abstractions are, and where functional and/or semantic gaps exist. Finally, we provide a taxonomy for stream- and kernel-triggered abstractions, including disambiguation of similar semantic terms, and consider directions for future standardization in MPI-5.

Beatnik is a novel open source mini-application that exercises the complex communication patterns often found in production codes but rarely found in benchmarks or mini-applications. It simulates 3D Raleigh-Taylor instabilities based on Pandya and Shkoller's Z-Model formulation using the Cabana performance portability framework. This paper presents both the high-level design and important implementation details about Beatnik along with four benchmark setups for evaluating different aspects of HPC communication system performance. Evaluation results demonstrate both Beatnik's scalability on modern accelerator-based systems using weak and strong scaling tests up to 1024 GPUs, along with Beatnik's ability to expose communication challenges in modern systems and solver libraries.

Spectroscopic phase curves of hot Jupiters measure their emission spectra at multiple orbital phases, thus enabling detailed characterisation of their atmospheres. Precise constraints on the atmospheric composition of these exoplanets offer insights into their formation and evolution. We analyse four phase-resolved emission spectra of the hot Jupiter WASP-43b, generated from a phase curve observed with the MIRI/LRS onboard the JWST, to retrieve its atmospheric properties. Using a parametric 2D temperature model and assuming a chemically homogeneous atmosphere within the observed pressure region, we simultaneously fit the four spectra to constrain the abundances of atmospheric constituents, thereby yielding more precise constraints than previous work that analysed each spectrum independently. Our analysis reveals statistically significant evidence of NH3 (4$\sigma$) in a hot Jupiter's emission spectra for the first time, along with evidence of H2O (6.5$\sigma$), CO (3.1$\sigma$), and a non-detection of CH4. With our abundance constraints, we tentatively estimate the metallicity of WASP-43b at 0.6-6.5$\times$solar and its C/O ratio at 0.6-0.9. Our findings offer vital insights into the atmospheric conditions and formation history of WASP-43b by simultaneously constraining the abundances of carbon, oxygen, and nitrogen-bearing species., Comment: 17 pages, 14 figures, accepted for publication in MNRAS. Comments welcome!

Titan's atmospheric composition and dynamical state have previously been studied over numerous epochs by both ground- and space-based facilities. However, stratospheric measurements remain sparse during Titan's northern summer and fall. The lack of seasonal symmetry in observations of Titan's temperature field and chemical abundances raises questions about the nature of the middle atmosphere's meridional circulation and evolution over Titan's 29-yr seasonal cycle that can only be answered through long-term monitoring campaigns. Here, we present maps of Titan's stratospheric temperature, acetonitrile (or methyl cyanide; CH$_3$CN), and monodeuterated methane (CH$_3$D) abundances following Titan's northern summer solstice obtained with Band 9 ($\sim0.43$ mm) ALMA observations. We find that increasing temperatures towards high-southern latitudes, currently in winter, resemble those observed during Titan's northern winter by the Cassini mission. Acetonitrile abundances have changed significantly since previous (sub)millimeter observations, and we find that the species is now highly concentrated at high-southern latitudes. The stratospheric CH$_3$D content is found to range between 4-8 ppm in these observations, and we infer the CH$_4$ abundance to vary between $\sim0.9-1.6\%$ through conversion with previously measured D/H values. A global value of CH$_4=1.15\%$ was retrieved, lending further evidence to the temporal and spatial variability of Titan's stratospheric methane when compared with previous measurements. Additional observations are required to determine the cause and magnitude of stratospheric enhancements in methane during these poorly understood seasons on Titan., Comment: Accepted for publication in the Planetary Science Journal. 9 Figures, 1 table

Evidence accumulation models (EAMs) are the dominant framework for modeling response time (RT) data from speeded decision-making tasks. While providing a good quantitative description of RT data in terms of abstract perceptual representations, EAMs do not explain how the visual system extracts these representations in the first place. To address this limitation, we introduce the visual accumulator model (VAM), in which convolutional neural network models of visual processing and traditional EAMs are jointly fitted to trial-level RTs and raw (pixel-space) visual stimuli from individual subjects. Models fitted to large-scale cognitive training data from a stylized flanker task captured individual differences in congruency effects, RTs, and accuracy. We find evidence that the selection of task-relevant information occurs through the orthogonalization of relevant and irrelevant representations, demonstrating how our framework can be used to relate visual representations to behavioral outputs. Together, our work provides a probabilistic framework for both constraining neural network models of vision with behavioral data and studying how the visual system extracts representations that guide decisions.

High peak and average power free-electron lasers (FELs) in the terahertz region (THz) require small diameter, low-emittance, and high voltage electron beams. This paper presents two 1.5-2 MV, 100-200 A, thermionic cathode electron source approaches for compact megawatt range peak power, multi-kilowatt average power, high repetition rate, THz FELs. The preferred beam generation system includes grading electrodes and is quite compact compared to the other standard diode gun approaches. Both provide highly compressed beams at the waist having low values of normalized rms emittance. In particular, the new injector approach with grading electrodes, operating at a body voltage of 1.5-2 MV and 100 A, has a normalized rms emittance of roughly 10 mm-mrad at the beam waist. Power supply switching considerations are considered in the paper as well as considerations for very high-voltage multi-stage depressed collectors for device efficiency enhancement. Based on these designs, we provide performance estimates for FELs operating in the THz spectral region.

We use FIRE-2 zoom simulations of Milky Way size disk galaxies to derive easy-to-use relationships between the observed circular speed of the Galaxy at the Solar location, $v_\mathrm{c}$, and dark matter properties of relevance for direct detection experiments: the dark matter density, the dark matter velocity dispersion, and the speed distribution of dark matter particles near the Solar location. We find that both the local dark matter density and 3D velocity dispersion follow tight power laws with $v_\mathrm{c}$. Using this relation together with the observed circular speed of the Milky Way at the Solar radius, we infer the local dark matter density and velocity dispersion near the Sun to be $\rho = 0.42\pm 0.06\ \mathrm{GeV}\,\mathrm{cm^{-3}}$ and $\sigma_{\rm 3D} = 280^{+19}_{-18}\,\mathrm{km\,s^{-1}}$. We also find that the distribution of dark matter particle speeds is well-described by a modified Maxwellian with two shape parameters, both of which correlate with the observed $v_{\rm c}$. We use that modified Maxwellian to predict the speed distribution of dark matter near the Sun and find that it peaks at a most probable speed of $257\,\mathrm{km\,s^{-1}}$ and begins to truncate sharply above $470\,\mathrm{km\,s^{-1}}$. This peak speed is somewhat higher than expected from the standard halo model, and the truncation occurs well below the formal escape speed to infinity, with fewer very-high-speed particles than assumed in the standard halo model., Comment: 25 pages, 12 figures, 3 tables; JCAP accepted version

Current understanding of the ammonia distribution in Jupiter's atmosphere is provided by observations from major ground-based facilities and spacecraft, and analyzed with sophisticated retrieval models that recover high fidelity information, but are limited in spatial and temporal coverage. Here we show that the ammonia abundance in Jupiter's upper troposphere, which tracks the overturning atmospheric circulation, can be simply, but reliably determined from continuum-divided ammonia and methane absorption-band images made with a moderate-sized Schmidt-Cassegrain telescope (SCT). In 2020-21, Jupiter was imaged in the 647-nm ammonia absorption band and adjacent continuum bands with a 0.28-m SCT, demonstrating that the spatially-resolved ammonia optical depth could be determined with such a telescope. In 2022-23, a 619 nm methane-band filter was added to provide a constant reference against which to correct the ammonia abundances (column-averaged mole fraction) for cloud opacity variations. These 0.28-m SCT results are compared with observations from: a) the MUSE instrument on ESO's Very Large Telescope (VLT) b) TEXES mid-infrared spectrometer used on the NASA's InfraRed Telescope Facility (IRTF); and c) the Gemini telescopes, and are shown to provide reliable maps of ammonia abundance. Meridional and longitudinal features are examined, including the Equatorial Zone (EZ) ammonia enhancement, the North Equatorial Belt (NEB) depletion, depletion above the Great Red Spot (GRS), and longitudinal enhancements in the northern EZ. This work demonstrates meaningful ammonia monitoring can be achieved with small telescopes that can complement spacecraft and major ground-based facility observations., Comment: 27 pages, 8 figures

Spectral observations of Neptune made in 2019 with the MUSE instrument at the Very Large Telescope in Chile have been analysed to determine the spatial variation of aerosol scattering properties and methane abundance in Neptune's atmosphere. The darkening of the South Polar Wave (SPW) at $\sim$ 60$^\circ$S, and dark spots such as the Voyager 2 Great Dark Spot is concluded to be due to a spectrally-dependent darkening ($\lambda < 650$nm) of particles in a deep aerosol layer at $\sim$ 5 bar and presumed to be composed of a mixture of photochemically-generated haze and H$_2$S ice. We also note a regular latitudinal variation of reflectivity at wavelengths of very low methane absorption longer than $\sim$ 650 nm, with bright zones latitudinally separated by $\sim$ 25$^\circ$. This feature, similar to the spectral characteristics of a discrete deep bright spot DBS-2019 found in our data, is found to be consistent with a brightening of the particles in the same $\sim$5-bar aerosol layer at $\lambda > 650 $ nm. We find the properties of an overlying methane/haze aerosol layer at $\sim$ 2 bar are, to first-order, invariant with latitude, while variations in the opacity of an upper tropospheric haze layer reproduce the observed reflectivity at methane-absorbing wavelengths, with higher abundances found at the equator and also in a narrow `zone' at $80^\circ$S. Finally, we find the mean abundance of methane below its condensation level to be 6--7% at the equator reducing to $\sim$3% south of $\sim$25$^\circ$S, although the absolute abundances are model dependent., Comment: 32 pages, 13 figures. Accepted in JGR: Planets

The traditional picture of solid-solid phase transformations assumes an ordered parent phase transforms into an ordered daughter phase via a single unique pathway. Zirconium and its prototypical phase transition from hexagonal close-packed (hcp) to simple hexagonal (hex-3) structure has generated considerable controversy over several decades regarding which mechanism mediates the transformation. However, a lack of in situ measurements over the relevant atomistic timescales has hindered our ability to identify the true pathway. In this study, we exploit femtosecond X-ray diffraction coupled with nanosecond laser compression to give unprecedented insights into the complexities of how materials transform at the lattice level. We observe single-crystal zirconium changing from hcp to a hex-3 structure via not one but three competing pathways simultaneously. Concurrently, we also observe a broad diffuse background underlying the sharp Bragg diffraction during the transition. We corroborate our observation of the diffuse signal with multimillion-atom molecular dynamics simulations using a machine-learned interatomic potential. Our study demonstrates that the traditional mechanistic view of transitions may fail for even an elemental metal and that the mechanisms by which materials transform are far more intricate than generally thought.

Machine learning has recently entered into the mainstream of coarse-grained (CG) molecular modeling and simulation. While a variety of methods for incorporating deep learning into these models exist, many of them involve training neural networks to act directly as the CG force field. This has several benefits, the most significant of which is accuracy. Neural networks can inherently incorporate multi-body effects during the calculation of CG forces, and a well-trained neural network force field outperforms pairwise basis sets generated from essentially any methodology. However, this comes at a significant cost. First, these models are typically slower than pairwise force fields even when accounting for specialized hardware which accelerates the training and integration of such networks. The second, and the focus of this paper, is the need for the considerable amount of data needed to train such force fields. It is common to use 10s of microseconds of molecular dynamics data to train a single CG model, which approaches the point of eliminating the CG models usefulness in the first place. As we investigate in this work, this data-hunger trap from neural networks for predicting molecular energies and forces can be remediated in part by incorporating equivariant convolutional operations. We demonstrate that for CG water, networks which incorporate equivariant convolutional operations can produce functional models using datasets as small as a single frame of reference data, while networks without these operations cannot.

Previous observations of dark vortices in Neptune's atmosphere, such as Voyager-2's Great Dark Spot, have been made in only a few, broad-wavelength channels, which has hampered efforts to pinpoint their pressure level and what makes them dark. Here, we present Very Large Telescope (Chile) MUSE spectrometer observations of Hubble Space Telescope's NDS-2018 dark spot, made in 2019. These medium-resolution 475 - 933 nm reflection spectra allow us to show that dark spots are caused by a darkening at short wavelengths (< 700 nm) of a deep ~5-bar aerosol layer, which we suggest is the H$_2$S condensation layer. A deep bright spot, named DBS-2019, is also visible on the edge of NDS-2018, whose spectral signature is consistent with a brightening of the same 5-bar layer at longer wavelengths (> 700 nm). This bright feature is much deeper than previously studied dark spot companion clouds and may be connected with the circulation that generates and sustains such spots., Comment: 1 table. 3 figures. Nature Astronomy (2023)

Let $\Gamma$ be a {Conway 99-graph}, that is, a strongly regular graph with parameters $(99,14,1,2)$. In Makhnev and Minakova (On automorphisms of strongly regular graphs with parameters $\lambda =1$, $\mu= 2$, Discrete Math.\ Appl.\ 14 (2) (2004) 201-210), the authors prove that the automorphism group $G$ of $\Gamma$ must have order dividing $2\cdot 3^3\cdot 7\cdot 11$. They further show that if $|G|$ is divisible by $2$ then $|G|$ must divide $42$. In the present paper, we refine these results by proving that divisibility by $7$ implies $G \cong\mathbb Z_7$. As a consequence, divisibility by $2$ implies $|G|$ divides $6$, \ie $G$ is isomorphic to one of $\mathbb Z_2, \mathbb Z_6, S_3$., Comment: 19 pages, 10 figures, 1 table

We present a study of the long term variability of Jupiter's mid-infrared auroral CH4 emissions. 7.7 - 7.9 micron images of Jupiter recorded by Earth-based telescopes over the last three decades were collated in order to quantify the magnitude and timescales over which the northern auroral hotspot's CH4 emissions varies. We find that the ratio of the radiance of the poleward northern auroral emissions to a lower-latitude zonal mean, henceforth 'Relative Poleward Radiance' or RPR, exhibits a 37% variability over a range of timescales. We searched for patterns of variability in order to test whether seasonally-varying solar insolation, the 11-year solar cycle, or short-term solar wind variability at Jupiter's magnetopause could explain the observed evolution. The variability of the RPR exhibits a weak (r < 0.2) correlation with the solar insolation received at Jupiter's high-northern latitudes. This rules out the hypothesis suggested in previous work (e.g. Sinclair et al., 2017a) that shortwave solar heating of aurorally-produced haze particles is the dominant heating mechanism in the lower stratosphere. We also find the variability exhibits negligible (r < 0.18) correlation with the monthly-mean sunspot number, which rules out variability associated with the solar cycle. On shorter timescales, we find moderate correlations of the RPR with solar wind conditions at Jupiter in the preceding days before images were recorded. For example, we find correlations of r = 0.45 and r = 0.51 of the RPR with the mean and standard deviation on the solar wind dynamical pressure in the preceding 7 days. The moderate correlation suggests that either: 1) only a subset of solar wind compressions lead to brighter, poleward, CH4 emissions and/or 2) a subset of CH4 emission brightening events are driven by internal magnetospheric and independent of the solar wind.

Spectroscopic phase curves of transiting hot Jupiters are spectral measurements at multiple orbital phases, giving a set of disc-averaged spectra that probe multiple hemispheres. By fitting model phase curves to observations, we can constrain the atmospheric properties of hot Jupiters such as molecular abundance, aerosol distribution and thermal structure, which offer insights into their dynamics, chemistry, and formation. In this work, we propose a novel 2D temperature scheme consisting of a dayside and a nightside to retrieve information from near-infrared phase curves, and apply the scheme to phase curves of WASP-43b observed by HST/WFC3 and Spitzer/IRAC. In our scheme, temperature is constant on isobars on the nightside and varies with cos$^n$(longitude/$\epsilon$) on isobars on the dayside, where $n$ and $\epsilon$ are free parameters. We fit all orbital phases simultaneously using the radiative transfer package NEMESISPY coupled to a Bayesian inference code. We first validate the performance of our retrieval scheme with synthetic phase curves generated from a GCM, and find our 2D scheme can accurately retrieve the latitudinally-averaged thermal structure and constrain the abundance of H$_2$O and CH$_4$. We then apply our 2D scheme to the observed phase curves of WASP-43b and find: (1) the dayside temperature-pressure profiles do not vary strongly with longitude and are non-inverted; (2) the retrieved nightside temperatures are extremely low, suggesting significant nightside cloud coverage; (3) the H$_2$O volume mixing ratio is constrained to $5.6\times10^{-5}$--$4.0\times10^{-4}$, and we retrieve an upper bound for CH$_4$ at $\sim$10$^{-6}$., Comment: 23 pages, 20 figures, 3 tables, accepted for publication in MNRAS

Early-bird communication is a communication/computation overlap technique that combines fine-grained communication with partitioned communication to improve application run-time. Communication is divided among the compute threads such that each individual thread can initiate transmission of its portion of the data as soon as it is complete rather than waiting for all of the threads. However, the benefit of early-bird communication depends on the completion timing of the individual threads. In this paper, we measure and evaluate the potential overlap, the idle time each thread experiences between finishing their computation and the final thread finishing. These measurements help us understand whether a given application could benefit from early-bird communication. We present our technique for gathering this data and evaluate data collected from three proxy applications: MiniFE, MiniMD, and MiniQMC. To characterize the behavior of these workloads, we study the thread timings at both a macro level, i.e., across all threads across all runs of an application, and a micro level, i.e., within a single process of a single run. We observe that these applications exhibit significantly different behavior. While MiniFE and MiniQMC appear to be well-suited for early-bird communication because of their wider thread distribution and more frequent laggard threads, the behavior of MiniMD may limit its ability to leverage early-bird communication.

ESA's Jupiter Icy Moons Explorer (JUICE) will provide a detailed investigation of the Jovian system in the 2030s, combining a suite of state-of-the-art instruments with an orbital tour tailored to maximise observing opportunities. We review the Jupiter science enabled by the JUICE mission, building on the legacy of discoveries from the Galileo, Cassini, and Juno missions, alongside ground- and space-based observatories. We focus on remote sensing of the climate, meteorology, and chemistry of the atmosphere and auroras from the cloud-forming weather layer, through the upper troposphere, into the stratosphere and ionosphere. The Jupiter orbital tour provides a wealth of opportunities for atmospheric and auroral science: global perspectives with its near-equatorial and inclined phases, sampling all phase angles from dayside to nightside, and investigating phenomena evolving on timescales from minutes to months. The remote sensing payload spans far-UV spectroscopy (50-210 nm), visible imaging (340-1080 nm), visible/near-infrared spectroscopy (0.49-5.56 $\mu$m), and sub-millimetre sounding (near 530-625\,GHz and 1067-1275\,GHz). This is coupled to radio, stellar, and solar occultation opportunities to explore the atmosphere at high vertical resolution; and radio and plasma wave measurements of electric discharges in the Jovian atmosphere and auroras. Cross-disciplinary scientific investigations enable JUICE to explore coupling processes in giant planet atmospheres, to show how the atmosphere is connected to (i) the deep circulation and composition of the hydrogen-dominated interior; and (ii) to the currents and charged particle environments of the external magnetosphere. JUICE will provide a comprehensive characterisation of the atmosphere and auroras of this archetypal giant planet., Comment: 83 pages, 24 figures, accepted to Space Science Reviews special issue on ESA's JUICE mission

We present mid-infrared spectroscopy of Jupiter's mid-to-high latitudes using Gemini-North/TEXES (Texas Echelon Cross Echelle Spectrograph) on March 17-19, 2017. These observations capture Jupiter's hydrocarbon auroral emissions before, during and after the arrival of a solar wind compression on March 18th, which highlights the coupling between the polar stratosphere and external space environment. In comparing observations on March 17th and 19th, we observe a brightening of the CH$_4$, C$_2$H$_2$ and C$_2$H$_4$ emissions in regions spatially coincident with the northern, duskside main auroral emission (henceforth, MAE). In inverting the spectra to derive atmospheric information, we determine that the duskside brightening results from an upper stratospheric (p < 0.1 mbar/z > 200 km) heating (e.g. $\Delta T$ = 9.1 $\pm$ 2.1 K at 9 $\mu$bar at 67.5$^\circ$N, 162.5$^\circ$W) with negligible heating at deeper pressures. Our interpretation is that the arrival of the solar wind enhancement drove magnetospheric dynamics through compression and/or viscous interactions on the flank. These dynamics accelerated currents and/or generated higher Poynting fluxes, which ultimately warmed the atmosphere through Joule heating and ion-neutral collisions. Poleward of the southern MAE, temperature retrievals demonstrate that auroral-related heating penetrates as deep as the 10-mbar level, in contrast to poleward of the northern MAE, where heating is only observed as deep as $\sim$3 mbar. We suggest this results from the south having higher Pedersen conductivities, and therefore stronger currents and acceleration of the neutrals, as well as the poleward heating overlapping with the apex of Jupiter's circulation thereby inhibiting efficient horizontal mixing/advection.

One of the most mysterious astrophysical states is the common envelope (CE) phase of binary evolution, in which two stars are enshrouded by the envelope shed by one of them. Interactions between the stars and the envelope shrinks the orbit. The CE can lead to mergers or to a subsequent phase of interactions. Mergers may involve any combination of two compact objects and/or stars. Some involving white dwarfs, may produce Type Ia supernovae, while merging neutron stars may yield gamma-ray bursts, and merging compact objects of all kinds produce gravitational radiation. Since CEs can arise from a variety of different initial conditions, and due to the complexity of the processes involved, it is difficult to predict their end states. When many systems are being considered, as in population synthesis calculations, conservation principles are generally employed. Here we use angular momentum in a new way to derive a simple expression for the final orbital separation. This method provides advantages for the study of binaries and is particularly well-suited to higher order multiples, now considered to be important in the genesis of potential mergers. Here we focus on CEs in binaries, and the follow-up paper extends our formalism to multiple star systems within which a CE occurs., Comment: Accepted for publication in the Astrophysical Journal, 23 pages, 13 figures

Coarse-grained (CG) models parameterized using atomistic reference data, i.e., 'bottom up' CG models, have proven useful in the study of biomolecules and other soft matter. However, the construction of highly accurate, low resolution CG models of biomolecules remains challenging. We demonstrate in this work how virtual particles, CG sites with no atomistic correspondence, can be incorporated into CG models within the context of relative entropy minimization (REM) as latent variables. The methodology presented, variational derivative relative entropy minimization (VD-REM), enables optimization of virtual particle interactions through a gradient descent algorithm aided by machine learning. We apply this methodology to the challenging case of a solvent-free CG model of a 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC) lipid bilayer and demonstrate that introduction of virtual particles captures solvent-mediated behavior and higher-order correlations which REM alone cannot capture in a more standard CG model based only on the mapping of collections of atoms to the CG sites., Comment: 35 pages, 9 figures