A toolkit for teaching, learning, and doing research in Boolean function analysis. Fourier analysis, property testing, query complexity, hypercontractivity, pseudorandomness, and more
-
Updated
Sep 21, 2026 - Jupyter Notebook
A toolkit for teaching, learning, and doing research in Boolean function analysis. Fourier analysis, property testing, query complexity, hypercontractivity, pseudorandomness, and more
Framework for empirically exploring query complexity questions
The project applied database principles to a real-world mental health problem, emphasizing reliable data management, and showcased practical solutions to mental health challenges.
Determine in one query whether a 3-bit Boolean function is constant or balanced (oracle: f = x₀ ⊕ x₁ ⊕ x₂).
GraphQL operation guard for a supplied AST: fragment-aware depth limit with cycle guard, per-field complexity scoring, operation allowlist/denylist, and introspection blocking. graphql-js is optional — accepts its document shape structurally, zero hard dependencies.
Quantum memory thresholds for learning Pauli correlations of bounded weight and detecting preserved correlations, with proofs, reproducible checks, and a Watrous learning route.
Exact computational verification for memory under unknown future access
Optimal quantum and classical search laws for hidden Markov oracle omissions, separating query complexity from elapsed oracle time.
Pure Relative Structured Matrix Approximation with Square-Root Matvecs DOI: https://doi.org/10.5281/zenodo.21698599
Analyze and limit the cost of GraphQL queries using configurable field costs
To associate your repository with the query-complexity topic, visit your repo's landing page and select "manage topics."