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Algebraic Program Analysis
No full textThis paper is a tutorial on algebraic program analysis. It explains the foundations of algebraic program analysis, its strengths and limitations, and gives examples of algebraic program analyses for numerical invariant generation and termination analysis
Pruning of the People: Ostracism and the Transformation of the Political Space in Ancient Athens
No full textAthenian ostracism has long captured democratic imaginations because it seems to present clear evidence of a people (demos) routinely asserting collective power over tyrannical elites. In recent times, ostracism has been particularly alluring to militant democrats, who see the institution as an ancient precursor to modern militant democratic mechanisms such as social media bans, impeachment measures, and lustration procedures, which serve to protect democratic constitutions from anti- democratic threats. Such a way of conceptualizing ostracism ultimately stems from Aristotle’s “rule of proportion,” or the removal of “outstanding” individuals in a polity who threaten to disturb the achievement of communal eudaimonia (Aris. Pol. 1284a). However, this way of interpreting the institution only presents a truncated view, one which is overly centered on the ultimate expulsion of an individual from the polity, rather than on its broader contextual telos—the transformation of the ostracized individual and of the community. To move past this simplified view, this paper considers all elements of ostracism with equal force, and argues that ostracism offered a shared opportunity and shared space for all members of the polis—citizens, non-citizens, and elite members alike—to reform the character of the subject individual and to instill and reaffirm democratic values in the community
Spreading processes with mutations over multilayer networks
No full textA key scientific challenge during the outbreak of novel infectious diseases is to predict how the course of the epidemic changes under countermeasures that limit interaction in the population. Most epidemiological models do not consider the role of mutations and heterogeneity in the type of contact events. However, pathogens have the capacity to mutate in response to changing environments, especially caused by the increase in population immunity to existing strains, and the emergence of new pathogen strains poses a continued threat to public health. Further, in the light of differing transmission risks in different congregate settings (e.g., schools and offices), different mitigation strategies may need to be adopted to control the spread of infection. We analyze a multilayer multistrain model by simultaneously accounting for i) pathways for mutations in the pathogen leading to the emergence of new pathogen strains, and ii) differing transmission risks in different settings, modeled as network layers. Assuming complete cross-immunity among strains, namely, recovery from any infection prevents infection with any other (an assumption that will need to be relaxed to deal with COVID-19 or influenza), we derive the key epidemiological parameters for the multilayer multistrain framework. We demonstrate that reductions to existing models that discount heterogeneity in either the strain or the network layers may lead to incorrect predictions. Our results highlight that the impact of imposing/lifting mitigation measures concerning different contact network layers (e.g., school closures or work-from-home policies) should be evaluated in connection with their effect on the likelihood of the emergence of new strains
How MagNet: Machine Learning Framework for Modeling Power Magnetic Material Characteristics
No full textThis paper applies machine learning to power magnetics modeling. We first introduce an open-source database – MagNet – which hosts a large amount of experimentally measured excitation data for many materials across a variety of operating conditions, consisting of more than 500,000 data points in its current state. The processes for data acquisition and data quality control are explained. We then demonstrate a few neural network-based power magnetics modeling tools for modeling the core losses and B–H loops. Machine learning allows multiple factors that may influence the magnetic characteristics to be modeled in a unified framework, while provides insights to quantify the complexity of magnetic characteristics and reduce the size of the measurement data required to build a precise model. Neural network models are found to be effective in compressing the measurement data and predicting the material characteristics. The behaviors of a typical power magnetic material (TDK N87) across a wide range of operating conditions (e.g., temperature, waveform, dc-bias) can be well described by a small-scale neural network (204 KB) which is 2,500 times smaller than the raw measured time-series data (512 MB), paving the way for “neural networks as datasheet” to assist power magnetics design
Probing itinerant carrier dynamics at the diamond surface using single nitrogen vacancy centers
No full textColor centers in diamond are widely explored for applications in quantum sensing, computing, and networking. Their optical, spin, and charge properties have extensively been studied, while their interactions with itinerant carriers are relatively unexplored. Here, we show that NV centers situated 10 ± 5 nm of the diamond surface can be converted to the neutral charge state via hole capture. By measuring the hole capture rate, we extract the capture cross section, which is suppressed by proximity to the diamond surface. The distance dependence is consistent with a carrier diffusion model, indicating that the itinerant carrier lifetime can be long, even at the diamond surface. Measuring dynamics of near-surface NV centers offers a tool for characterizing the diamond surface and investigating charge transport in diamond devices
Room-Temperature Photochromism of Silicon Vacancy Centers in CVD Diamond
No full textThe silicon vacancy (SiV) center in diamond is typically found in three stable charge states, SiV0, SiV–, and SiV2–, but studying the processes leading to their formation is challenging, especially at room temperature, due to their starkly different photoluminescence rates. Here, we use confocal fluorescence microscopy to activate and probe charge interconversion between all three charge states under ambient conditions. In particular, we witness the formation of SiV0 via the two-step capture of diffusing, photogenerated holes, a process we expose both through direct SiV0 fluorescence measurements at low temperatures and confocal microscopy observations in the presence of externally applied electric fields. In addition, we show that continuous red illumination induces the converse process, first transforming SiV0 into SiV– and then into SiV2–. Our results shed light on the charge dynamics of SiV and promise opportunities for nanoscale sensing and quantum information processing
In-situ coating of silicon-rich films on tokamak plasma-facing components with real-time Si material injection
No full textExperiments have been conducted in the DIII-D tokamak to explore the in-situ growth of silicon-rich layers as a potential technique for real-time replenishment of surface coatings on plasma-facing components (PFCs) during steady-state long-pulse reactor operation. Silicon (Si) pellets of 1 mm diameter were injected into low- and high-confinement (L-mode and H-mode) plasma discharges with densities ranging from 3.9 − 7.5 × 1019 m−3 and input powers ranging from 5.5 − 9 MW. The small Si pellets were delivered with the impurity granule injector (IGI) at frequencies ranging from 4-16 Hz corresponding to mass flow rates of 5 − 19 mg/s (1 − 4.2 × 1020 Si/s) at cumulative amounts of up to 34 mg of Si per five-second discharge. Graphite samples were exposed to the scrape- off layer and private flux region plasmas through the divertor material evaluation system (DiMES) to evaluate the Si deposition on the divertor targets. The Si II emission at the sample correlates with silicon injection and suggests net surface Si- deposition in measurable amounts. Post-mortem analysis showed Si-rich coatings containing silicon oxides, of which SiO2 is the dominant component. No evidence of SiC was found, which is attributed to low divertor surface temperatures. The in-situ and ex-situ analysis found that Si-rich coatings of at least 0.4 − 1.2 nm thickness have been deposited at 0.4−0.7 nm/s. The technique is estimated to coat a surface area of at least 0.94 m2 on the outer divertor. These results demonstrate the potential of using real-time material injection to form Si-enriched layers on divertor PFCs during reactor operation
A Telecom O-Band Emitter in Diamond
No full textColor centers in diamond are promising platforms for quantum technologies. Most color centers in diamond discovered thus far emit in the visible or near-infrared wavelength range, which are incompatible with long-distance fiber communication and unfavorable for imaging in biological tissues. Here, we report the experimental observation of a new color center that emits in the telecom O-band, which we observe in silicon-doped bulk single crystal diamonds and microdiamonds. Combining absorption and photoluminescence measurements, we identify a zero-phonon line at 1221 nm and phonon replicas separated by 42 meV. Using transient absorption spectroscopy, we measure an excited state lifetime of around 270 ps and observe a long-lived baseline that may arise from intersystem crossing to another spin manifold