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{

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  "template": {

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    "name": "SIAM Article Template",

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    "slug": "article-siam",

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    "version": "1.0.0",

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    "category": "article",

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    "subcategory": "journal",

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    "discipline": "applied-mathematics",

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    "description": "Professional SIAM-style article template with integrated PythonTeX for numerical mathematics and scientific computing research",

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    "keywords": [

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      "siam latex template",

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      "siam journal template",

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      "applied mathematics latex template",

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      "siam review latex",

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      "numerical analysis latex template",

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      "computational mathematics template",

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      "siam optimization latex template",

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      "siam scientific computing latex",

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      "matrix analysis latex template"

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    ],

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    "features": [

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      "SIAM single-column formatting",

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      "Comprehensive theorem environments",

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      "PythonTeX integration",

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      "Numerical analysis examples",

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      "Iterative method implementations",

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      "Convergence analysis",

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      "Professional mathematical typesetting",

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      "Reproducible numerical experiments"

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    ],

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    "dependencies": [

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      "pythontex",

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      "numpy",

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      "matplotlib",

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      "scipy",

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      "amsthm"

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    ],

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    "compile_method": "pdflatex + pythontex",

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    "shell_escape": true,

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    "estimated_compile_time": "60-90 seconds",

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    "output_pages": 6,

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    "license": "MIT"

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  },

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  "cocalc": {

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    "tested": true,

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    "timetravel_compatible": true,

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    "collaboration_ready": true,

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    "ai_integration": true,

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    "shell_escape_required": true

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  },

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  "seo": {

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    "primary_keywords": ["siam latex template", "siam journal template", "applied mathematics latex template"],

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    "secondary_keywords": ["siam review latex", "numerical analysis latex template", "computational mathematics template"],

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    "long_tail_keywords": ["siam optimization latex template", "siam scientific computing latex", "matrix analysis latex template"],

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    "target_audience": "applied mathematicians, numerical analysts, SIAM journal authors, computational scientists"

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  },

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  "examples": {

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    "numerical_methods": "Classical and accelerated conjugate gradient comparison",

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    "python_integration": "Matrix generation, iterative solvers, convergence analysis",

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    "performance_analysis": "Average 15% iteration reduction with statistical validation",

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    "mathematical_content": "Theorems, proofs, algorithms, convergence bounds",

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    "figures": "Convergence plots, spectral analysis, performance comparisons"

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  }

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}

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