'physics' 검색 결과

This skill covers detecting sophisticated cyber-physical attacks that follow the Stuxnet attack pattern of modifying PLC logic while spoofing sensor readings to hide the manipulation from operators. It addresses PLC logic integrity monitoring, physics-based process anomaly detection, engineering workstation compromise indicators, USB-borne attack vectors, and multi-stage attack chain detection spanning IT-to-OT lateral movement through to process manipulation.

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This skill covers deploying anomaly detection systems for industrial control environments using machine learning models trained on OT network baselines, physics-based process models, and behavioral analysis of industrial protocol communications. It addresses building normal behavior profiles for SCADA polling patterns, detecting deviations in Modbus/DNP3/OPC UA traffic, identifying rogue devices, and correlating network anomalies with physical process data from historians.

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A collection of methods in an intelligent software structure allows the user to focus on fine-tuning

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Knowledge base from the NASA Probabilistic Risk Assessment Procedures Guide (NASA/SP-2011-3421, 2nd ed.). Use for quantitative PRA of aerospace and safety-critical systems: the risk triplet and scenario logic stack (MLD, ESD, event trees, fault trees, minimal cut sets), Bayesian data collection and parameter estimation, aleatory/epistemic uncertainty modeling and common-cause failure (Alpha Factor, beta-factor, CCBE), human reliability analysis (THERP, CREAM, NARA, SPAR-H), context-based software risk (CSRM), physics-based and structural/phenomenological models (stress-strength, limit states, FORM/SORM, NASGRO, range safety), uncertainty propagation and importance measures (F-V, RAW, Birnbaum, DIM), and launch-abort modeling with worked PRA examples. This is the QUANTITATIVE engine beneath NASA's risk doctrine — for the qualitative RIDM/CRM decision framework use the nasa-risk pack. Thin on programme management, organisational risk governance, and non-aerospace regulatory contexts; aerospace-focused and anchored to the 2011 second edition.

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Build React animations with Motion (Framer Motion) - gestures (drag, hover, tap), scroll effects, spring physics, layout animations, SVG. Bundle: 2.3 KB (mini) to 34 KB (full). Use when: drag-and-drop, scroll animations, modals, carousels, parallax. Troubleshoot: AnimatePresence exit, list performance, Tailwind conflicts, Next.js "use client".

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Core Python library for astronomy and astrophysics workflows that need Astropy APIs, including units/quantities, coordinates, FITS I/O, tables, time systems, WCS, and cosmology. Use when implementing or debugging astronomical data analysis code with Astropy.

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Core Python library for astronomy/astrophysics: units with dimensional analysis, celestial coordinate transforms (ICRS/Galactic/AltAz/FK5), FITS I/O, tables (FITS/HDF5/VOTable/CSV), cosmology (Planck18, distance/age), precise time (UTC/TAI/TT/TDB, Julian, barycentric), WCS pixel-world mapping, model fitting. For general tables use pandas/polars; for radio interferometry use CASA.

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Search and retrieve preprints from arXiv via the Atom API. Use this skill when searching for papers in physics, mathematics, computer science, quantitative biology, quantitative finance, statistics, electrical engineering, or economics by keywords, authors, arXiv IDs, date ranges, or categories.

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Alternative Slowbar coffee intelligence — scientific analysis from seed to cup using First Principle + System Thinking. Covers: varieties, terroir, cultivation, disease diagnosis, processing, roasting physics/chemistry, extraction science, brewing, business strategy, storytelling. ALWAYS trigger for coffee-related questions requiring scientific depth. DO NOT trigger for simple recipes or general food questions. Style: science-driven, farmer-first, quality-obsessed.

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Create multiplayer spatial board games using TabletopKit on visionOS. Use when building tabletop game experiences with boards, pieces, cards, and dice, managing player seats and turns, synchronizing game state over FaceTime with Group Activities, rendering game elements with RealityKit, or implementing piece snapping and physics on a virtual table surface.

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Pushes interfaces past conventional limits with technically ambitious implementations — shaders, spring physics, scroll-driven reveals, 60fps animations. Use when the user wants to wow, impress, go all-out, or make something that feels extraordinary.

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3D game development principles. Rendering, shaders, physics, cameras.

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2D game development principles. Sprites, tilemaps, physics, camera.

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当需求还只是"帮我写个东西""让 AI 做这个任务"这种一句话时使用。用至多 3–5 个高杠杆追问把它补成一份可交付的任务简报——目标、产物、受众、已有素材、约束、验收标准、不做什么、待确认假设，外加一段可直接粘贴的执行 prompt。简报的九个标题保持英文（内容用什么语言都行），字段完整性由 scripts/check_brief.py 校验。产出不绑定任何一家模型，人或 Agent 都能照着执行。不适用于：写歌交给 lyric-concept-builder，复习计划交给 deadline-to-study-plan，建模题交给 modeling-problem-reading-coach，物理题交给 physics-problem-router；使用者坚持直接要成品、一个问题都不肯答时也不用本 skill。

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当机制清单已经排好、需要给每个机制配数值锚点并合成一个站得住的量级结论时使用。把估算写成显式的因子分解，每个因子给低／中／高三值与证据档位，算出区间而不是装饰性的小数位，再与参考区间和守恒量核对。worksheet 的结构与算术由 scripts/check_estimate.py 校验。不负责发现或排序机制——那是 physics-mechanism-decomposer 的事。

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当使用者贴出一道物理题、一个实验现象、一份竞赛材料或一句"这个怎么解释"，还没想好从哪一步下手时使用。先定三件事——问题类型（计算/建模/科研/开放现象）、目标产物（数值答案/可检验模型/机制解释）、卡在哪一步——再分流到下游物理 skill；专门检出"要的产物与问题类型不匹配"和"其实该先回去读题"两种走错门。不解题，不给答案，不替使用者选机制。

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当面对一个开放现象、说不清"为什么会这样"时使用——IYPT 题目、实验里看到的奇怪行为、科研中待解释的观测。把现象拆成候选机制清单，用守恒量收支表检查有没有漏，为每个机制写出带指数的标度律，用同量纲的量级比较排出主导、次导与可忽略，再为每个机制配一个能真正分辨它的观测量（判据是指数或符号不同，不是系数不同）。产出的是可检验命题与实验建议，不是结论。

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This skill covers detecting sophisticated cyber-physical attacks that follow the Stuxnet attack pattern of modifying PLC logic while spoofing sensor readings to hide the manipulation from operators. It addresses PLC logic integrity monitoring, physics-based process anomaly detection, engineering workstation compromise indicators, USB-borne attack vectors, and multi-stage attack chain detection spanning IT-to-OT lateral movement through to process manipulation.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

This skill covers deploying anomaly detection systems for industrial control environments using machine learning models trained on OT network baselines, physics-based process models, and behavioral analysis of industrial protocol communications. It addresses building normal behavior profiles for SCADA polling patterns, detecting deviations in Modbus/DNP3/OPC UA traffic, identifying rogue devices, and correlating network anomalies with physical process data from historians.

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Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip.

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Hamiltonian mechanics — symplectic integrators (leapfrog, Yoshida), Hamilton's equations, Poisson brackets, canonical transformations, action-angle variables, and KAM theory analysis. Use for energy-conserving long-time integration of conservative systems.

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Bayesian parameter estimation with MCMC (emcee) and probabilistic programming (PyMC). Posterior distributions, corner plots, model evidence, convergence diagnostics. Use when you need full posterior distributions, not just point estimates.

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Discover conserved quantities and symmetries from trajectory data. Identifies energy, momentum, angular momentum, and custom invariants using neural networks and symbolic methods. Inspired by Noether's theorem.

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Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.

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