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Chorus waves induce both electron acceleration and loss. In this letter, we provide significantly improved models of electron lifetime due to interactions with chorus waves. The new models fill the gap that previous models have on some magnetic local time (MLT) sectors of the Earth's magnetosphere. This improvement is critical for modeling studies. The lifetime models developed using two different methods are valid for electrons with an energy range from 1 keV to 2 MeV. To facilitate the integration of these new models into different ring current and radiation belt codes, we parameterize the electron lifetime as a function of L$L$ ‐shell and electron kinetic energy at each MLT and geomagnetic activity (Kp). The parameterized electron lifetimes exhibit strong dependencies on L$L$ ‐shell, MLT, and energy. Simulations using these new models demonstrate improved agreement with satellite observations compared to simulations using previous models, advancing our understanding of electron dynamics in the magnetosphere. Plain Language Summary There are a large number of energetic electrons trapped by our Earth's magnetic field in the near‐Earth space. The regions populated by these high energy electrons are called ring current and radiation belts. It is important to understand the dynamics of the energetic electrons because they can be dangerous to satellites and astronauts flying through these regions. Electromagnetic waves in these regions play an important role in the dynamic of ring current and radiation belt electrons. Among these waves, whistler mode chorus wave is an important wave that can cause both acceleration and loss of the energetic electrons. In our previous studies, we calculated diffusion coefficients to quantify the effect of chorus waves on the energetic electrons. Based on these diffusion coefficients, in this study, we estimate the lifetime of energetic electrons due to their interactions with chorus waves. To make this lifetime model more convenient to be used in different ring current and radiation belt models, we apply polynomial fits to the calculated lifetime. Our new lifetime model is more advanced than previous models, especially in the space coverage. We test the new models in simulations and the results agree better with satellite observations than the previous models do. Key Points The new lifetime model provides extended space coverage in comparison to current widely used lifetime models Such parameterized lifetimes are very significant for simulations of the dynamics of radiation belt and ring current electrons Using the new electron lifetime model in simulations improves the agreement between the simulation results and the satellite observations

The dipole configuration of the Earth’s magnetic field allows for the trapping of highly energetic particles, which form the radiation belts. Although significant advances have been made in understanding the acceleration mechanisms in the radiation belts, the loss processes remain poorly understood. Unique observations on 17 January 2013 provide detailed information throughout the belts on the energy spectrum and pitch angle (angle between the velocity of a particle and the magnetic field) distribution of electrons up to ultra-relativistic energies. Here we show that although relativistic electrons are enhanced, ultra-relativistic electrons become depleted and distributions of particles show very clear telltale signatures of electromagnetic ion cyclotron wave-induced loss. Comparisons between observations and modelling of the evolution of the electron flux and pitch angle show that electromagnetic ion cyclotron waves provide the dominant loss mechanism at ultra-relativistic energies and produce a profound dropout of the ultra-relativistic radiation belt fluxes. The processes that lead to losses of highly energetic particles from Earth’s radiation belts remain poorly understood. Here the authors compare observations and models of a 2013 event to show that electromagnetic ioncyclotron waves provide the dominant loss mechanism at ultra-relativistic energies.

Investigations into quasiperiodic (QP) whistler mode emissions within Saturn's magnetosphere have uncovered distinctive characteristics of these emissions, which display a nearly periodic rising tone structure in the wave spectrogram, characterized by modulation periods of several minutes. These QP emissions are predominantly observed at low L‐shells around 5 and near the magnetic equator. Utilizing a quasi‐linear analysis framework, we evaluate the effects of these waves on the dynamics of energetic electrons. Our analysis suggests that these QP emissions can efficiently cause the loss of electrons within the energy range from 10 to 60 keV over a timescale of tens of minutes. By incorporating these findings into Fokker‐Planck simulations, we find minimal acceleration effects. This study is the first to examine QP emissions and their implications for energetic electron dynamics in Saturn's magnetosphere, highlighting their potentially significant contribution to the magnetospheric processes and dynamics. Plain Language Summary This study investigates unique plasma wave patterns, called quasiperiodic (QP) whistler mode emissions, observed in Saturn's magnetospheric environment. These emissions display an interesting pattern of rising tone that occurs periodically, with each lasting several minutes. They are mainly observed in certain areas around Saturn, close to the magnetic equator. To understand how these emissions affect the behavior of energetic electrons in Saturn's magnetosphere, the study adopted the approach called quasi‐linear analysis and performed the computer simulation. It is found that these QP emissions can efficiently cause the loss of electrons with energies between 10 and 60 keV within tens of minutes. However, these emissions did not significantly accelerate these particles. This study suggests that these emissions may play an important role in the overall processes and behavior of Saturn's magnetospheric environment. Key Points Quasi‐periodic (QP) whistler mode emissions were observed in Saturn's magnetosphere Each periodic modulation of QP emissions lasts for several minutes QP emissions can efficiently cause loss of electrons with energy from 10 to 60 keV

Electrons within Earth's radiation belts exhibit large variability in space and time during geomagnetic storms, which could potentially damage satellites and harm astronauts in space. Physics‐based models describe the evolution of energetic electrons in the radiation belts, but they may suffer from uncertainties and errors, particularly in the initial and boundary conditions. Data assimilation can overcome these limitations by combining models with satellite observations, incorporating all available information to create a more reliable reconstruction. This study validates the data‐assimilative three‐dimensional Versatile Electron Radiation Belt code (VERB‐3D) model using data from three independent satellite missions: Arase and GOES for assimilation, and Van Allen Probes for validation. The data sets were cleaned and normalized to ensure their compatibility. The validation shows that the model effectively reproduces the radiation belt dynamics, where the reanalysis remains within a factor of 2 for 88.3% of the time, 98.4% within a factor of 5, and 99.4% within one order of magnitude for 1 MeV electrons. The results highlight the potential of data assimilation for space weather forecasting and as an input for specification models.

On 10 June and 27 September 2024, two workshops were held at GFZ Potsdam under the umbrella of the Geo. X Research Network of Geosciences to discuss the unresolved question of the overestimation and lack of scattering of modeled ring current electrons during geomagnetic storms. At the workshops, we discussed the potential contributions to the lack of scattering of electron cyclotron harmonic (ECH) waves, chorus waves, time‐domain‐structures (TDS), the non‐linear effects of wave‐particle interactions, and induced electric fields. A case study shows that the scattering by ECH waves is insufficient to account fully for the missing electron loss. More work must be done to understand the potential effects of inaccuracies in the assumed chorus wave models, TDS, and the non‐linear effects of wave‐particle interactions. Including induced electric fields in ring current simulations is an important step to describe the electron drifts more accurately. Explaining the missing loss process is crucial for space weather applications of surface charging effects, which rely on accurate predictions of ring current electron fluxes. Key Points We investigate several physical mechanisms that may contribute to ring current electron losses not captured by the model Additional scattering by ECH waves is not sufficient to fully explain the missing loss in the simulations Future ring current simulations should include the scattering by time domain structures and inductive electric fields

On 28 July 2021, within the Geospace Environment Modeling Virtual Summer Workshop, a joint panel discussion organized by the “System Understanding of Radiation Belt Particle Dynamics through Multi‐spacecraft and Ground‐based Observations and Modeling” and “ULF wave Modeling, Effects, and Applications” focus groups was held. The panelists, organizers, and the audience discussed the nature and unresolved questions of radiation belt electron flux enhancements. In this commentary we provide the outcomes of this discussion. Key Points The summary of a joint panel discussion of the Geospace Environment Modeling 2021 Virtual Summer Workshop is presented Both radial diffusion and local acceleration are important mechanisms of observed electron flux enhancements and must be considered Advancements can be reached with multi‐point measurements, analysis of phase space density, and new methods to assess diffusion coefficients

Containers have emerged as a more portable and efficient solution than virtual machines for cloud infrastructure providing both a flexible way to build and deploy applications. The quality of service, security, performance, energy consumption, among others, are essential aspects of their deployment, management, and orchestration. Inappropriate resource allocation can lead to resource contention, entailing reduced performance, poor energy efficiency, and other potentially damaging effects. In this paper, we present a set of online job allocation strategies to optimize quality of service, energy savings, and completion time, considering contention for shared on-chip resources. We consider the job allocation as the multilevel dynamic bin-packing problem that provides a lightweight runtime solution that minimizes contention and energy consumption while maximizing utilization. The proposed strategies are based on two and three levels of scheduling policies with container selection, capacity distribution, and contention-aware allocation. The energy model considers joint execution of applications of different types on shared resources generalized by the job concentration paradigm. We provide an experimental analysis of eighty-six scheduling heuristics with scientific workloads of memory and CPU-intensive jobs. The proposed techniques outperform classical solutions in terms of quality of service, energy savings, and completion time by 21.73–43.44%, 44.06–92.11%, and 16.38–24.17%, respectively, leading to a cost-efficient resource allocation for cloud infrastructures.

This paper focuses on a bi-objective experimental evaluation of online scheduling in the Infrastructure as a Service model of Cloud computing regarding income and power consumption objectives. In this model, customers have the choice between different service levels. Each service level is associated with a price per unit of job execution time, and a slack factor that determines the maximal time span to deliver the requested amount of computing resources. The system, via the scheduling algorithms, is responsible to guarantee the corresponding quality of service for all accepted jobs. Since we do not consider any optimistic scheduling approach, a job cannot be accepted if its service guarantee will not be observed assuming that all accepted jobs receive the requested resources. In this article, we analyze several scheduling algorithms with different cloud configurations and workloads, considering the maximization of the provider income and minimization of the total power consumption of a schedule. We distinguish algorithms depending on the type and amount of information they require: knowledge free, energy-aware, and speed-aware. First, to provide effective guidance in choosing a good strategy, we present a joint analysis of two conflicting goals based on the degradation in performance. The study addresses the behavior of each strategy under each metric. We assess the performance of different scheduling algorithms by determining a set of non-dominated solutions that approximate the Pareto optimal set. We use a set coverage metric to compare the scheduling algorithms in terms of Pareto dominance. We claim that a rather simple scheduling approach can provide the best energy and income trade-offs. This scheduling algorithm performs well in different scenarios with a variety of workloads and cloud configurations.

In this paper, we address the problem of power-aware Virtual Machines (VMs) consolidation considering resource contention. Deployment of VMs can greatly influence host performance, especially, if they compete for resources on insufficient hardware. Performance can be drastically reduced and energy consumption increased. We focus on a bi-objective experimental evaluation of scheduling strategies for CPU and memory intensive jobs regarding the quality of service (QoS) and energy consumption objectives. We analyze energy consumption of the IBM System x3650 M4 server, with optimized performance for business-critical applications and cloud deployments built on IBM X-Architecture. We create power profiles for different types of applications and their combinations using SysBench benchmark. We evaluate algorithms with workload traces from Parallel Workloads and Grid Workload Archives and compare their non-dominated Pareto optimal solutions using set coverage and hyper volume metrics. Based on the presented case study, we show that our algorithms can provide the best energy and QoS trade-offs.