We propose a new method of the automated identification of current sheets (CSs) that represents a formalization of the visual inspection approach employed in case studies. CSs are often identified by eye via the analysis of characteristic changes in the interplanetary magnetic field (IMF) and plasma parameters. Known visual and semi-automated empirical methods of CS identification are exact but do not allow a comprehensive statistical analysis of CS properties. Existing automated methods partially solve this problem. Meanwhile, these methods suggest an analysis of variations of the IMF and its direction only. In our three-parameter empirical method, we employ both the solar wind plasma and IMF parameters to identify CSs of various types. Derivatives of the IMF strength, the plasma beta and the ratio of the Alfvén speed V_A to the solar wind speed V taken with the one-second cadence are used. We find that the CS daily rate R correlates with the solar wind temperature T rather than with V and is proportional to the sum of the kinetic and thermal energy density ∼V²(N+5N′)+10T(N + N′), where N′ = 2 cm⁻³ is the background level of the solar wind density N. Maxima of R are associated with stream/corotating interaction regions and interplanetary mass ejection sheaths. A multiyear list of CSs identified at 1 AU can be found at https://csdb.izmiran.ru.

中文翻译：

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电流片的自动识别——研究太阳风湍流和间歇性的新工具

我们提出了一种自动识别当前工作表 (CS) 的新方法，该方法代表了案例研究中采用的视觉检查方法的形式化。CS 通常通过分析行星际磁场 (IMF) 和等离子体参数的特征变化来通过肉眼识别。已知的 CS 识别的视觉和半自动经验方法是准确的，但不允许对 CS 特性进行全面的统计分析。现有的自动化方法部分解决了这个问题。同时，这些方法仅建议对 IMF 及其方向的变化进行分析。在我们的三参数经验方法中，我们同时使用太阳风等离子体和 IMF 参数来识别各种类型的 CS。IMF 强度、等离子体β 和阿尔文速度V的比值的导数_使用以一秒节奏获取的太阳风速V 的_A。我们发现 CS 日速率R与太阳风温度T而不是V 相关，并且与动能和热能密度之和成正比 ∼ V ² ( N +5 N' )+10 T ( N  +  N' ) )，其中N'  = 2 cm ^-3是太阳风密度N的背景水平。R的最大值与流/共转相互作用区域和行星际物质抛射鞘有关。可以在 https://csdb.izmiran.ru 找到在 1 AU 处确定的多年 CS 列表。