Results for “measurement-system-analysis”

Quantum mechanics simulations and analysis using QuTiP (Quantum Toolbox in Python). Use when working with quantum systems including: (1) quantum states (kets, bras, density matrices), (2) quantum operators and gates, (3) time evolution and dynamics (Schrödinger, master equations, Monte Carlo), (4) open quantum systems with dissipation, (5) quantum measurements and entanglement, (6) visualization (Bloch sphere, Wigner functions), (7) steady states and correlation functions, or (8) advanced methods (Floquet theory, HEOM, stochastic solvers). Handles both closed and open quantum systems across various domains including quantum optics, quantum computing, and condensed matter physics.

Analyzes global market conditions across US, European, and Asian indices, forex, commodities, and economic indicators to produce structured market reports with risk sentiment assessment.

Use when studying biomechanics.

Mass spectrometry analysis. Process mzML/MGF/MSP, spectral similarity (cosine, modified cosine), metadata harmonization, compound ID, for metabolomics and MS data processing.

Process and analyze mass spectrometry data: import spectra from MGF, mzML, MSP, and JSON formats; apply 40+ filters for metadata harmonization and peak cleaning; compute spectral similarities (cosine, modified cosine) for compound identification; build reproducible processing pipelines.

Mass spectrometry analysis. Process mzML/MGF/MSP, spectral similarity (cosine, modified cosine), metadata harmonization, compound ID, for metabolomics and MS data processing.

Analyzes production code to find gaps in existing tests by reasoning about hypothetical mutations and checking whether tests would catch them.

Analyzes type design for encapsulation, invariant expression, usefulness, and enforcement, providing scores and improvement suggestions.

Battery Management System reference — cell balancing, SOC estimation, thermal management, and protection circuits. Use when designing BMS for lithium-ion packs, evaluating battery safety, or understanding cell monitoring.

Analyze AMS waveform data using Mixed-Signal Blockset utilities: phase noise measurement, clock jitter, anti-aliased resampling, timing measurements, lock time, INL/DNL, ADC/DAC calibration, HSpice import. Use when analyzing time-domain voltage from PLL/VCO/clock simulations, measuring phase noise from variable-step solver output, computing jitter, or resampling non-uniform data.

Analyze proteomics and metabolomics mass spectrometry data with PyOpenMS: read/write MS file formats, process spectra, detect and quantify features, identify peptides and proteins, and run end-to-end LC-MS/MS pipelines using ready-to-run scripts.

Analyze product health across acquisition, activation, engagement, retention, quality, and monetization.

Use when evaluating, measuring, or comparing the performance of systems, functions, or services. This skill provides a framework for establishing baselines, measuring performance, and validating that changes meet performance requirements.

Mass spectrometry analysis. Process mzML/MGF/MSP, spectral similarity (cosine, modified cosine), metadata harmonization, compound ID, for metabolomics and MS data processing.

Configures monitoring systems, implements structured logging pipelines, creates Prometheus/Grafana dashboards, defines alerting rules, and instruments distributed tracing.

E1-Quantitative Analysis Guide with Code Generation & Sensitivity Analysis VS-Enhanced with Full 5-Phase process: Avoids obvious analyses, explores innovative methodologies Expanded to include qualitative analysis (thematic, grounded theory, content, narrative) Absorbed E4 (Analysis Code Generator) and E5 (Sensitivity Analysis - Primary Study) capabilities Use when: selecting statistical/qualitative methods, interpreting results, checking assumptions, generating code, sensitivity analysis Triggers: statistical analysis, ANOVA, regression, t-test, power analysis, assumption checking, effect size, thematic analysis, grounded theory, content analysis, narrative analysis, NVivo, ATLAS.ti, coding, qualitative data, R code, Python code, SPSS syntax, sensitivity analysis, robustness check

Perform a detailed SWOT analysis — strengths, weaknesses, opportunities, and threats with actionable recommendations. Use when doing strategic assessment, competitive analysis, or evaluating a product or business position.

Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md. Identifying inconsistencies, duplications, ambiguities, and underspecified items.

Design and implement evaluation harnesses for models, agents, and code. Use when creating benchmarks, designing eval metrics, or comparing system outputs.

Python interface to OpenMS for mass spectrometry data analysis. Use for LC-MS/MS proteomics and metabolomics workflows including file handling (mzML, mzXML, mzTab, FASTA, pepXML, protXML, mzIdentML), signal processing, feature detection, peptide identification, and quantitative analysis. Apply when working with mass spectrometry data, analyzing proteomics experiments, or processing metabolomics datasets.

Conduct gap analyses between current and desired states. TRIGGERS - Use when user needs help with gap-analysis related tasks.

Analyze complex systems through stocks, flows, and feedback loops to find high-leverage interventions. For organizational, environmental, social, and technical systems exhibiting circular causality. NOT for linear problems or simple cause-effect chains.

Quantum mechanics simulations and analysis using QuTiP (Quantum Toolbox in Python). Use when working with quantum systems including: (1) quantum states (kets, bras, density matrices), (2) quantum operators and gates, (3) time evolution and dynamics (Schrödinger, master equations, Monte Carlo), (4) open quantum systems with dissipation, (5) quantum measurements and entanglement, (6) visualization (Bloch sphere, Wigner functions), (7) steady states and correlation functions, or (8) advanced methods (Floquet theory, HEOM, stochastic solvers). Handles both closed and open quantum systems across various domains including quantum optics, quantum computing, and condensed matter physics.