The Computational Complexity of Boolean Functions

Target entity: The Computational Complexity of Boolean Functions
Context triple: [Noam Nisan, coAuthorOf, The Computational Complexity of Boolean Functions]

• A. Blum complexity measures
  Blum complexity measures are a formal framework in computational complexity theory that rigorously define and compare the resource usage (such as time or space) of algorithms via axiomatic conditions.
• B. Furst–Saxe–Sipser lower bounds
  Furst–Saxe–Sipser lower bounds are foundational results in circuit complexity theory that established superpolynomial lower bounds for constant-depth Boolean circuits (AC⁰), demonstrating inherent limitations of such circuits for computing certain functions.
• C. Håstad’s switching lemma
  Håstad’s switching lemma is a fundamental result in computational complexity theory that provides powerful bounds on the simplification of Boolean formulas under random restrictions, with major applications in circuit lower bounds.
• D. P, NP, and NP-Completeness: The Basics of Complexity Theory
  "P, NP, and NP-Completeness: The Basics of Complexity Theory" is a foundational textbook by Oded Goldreich that introduces the core concepts, problems, and techniques of computational complexity theory, with a focus on the classes P, NP, and NP-complete problems.
• E. “Almost optimal lower bounds for small depth circuits”
  “Almost optimal lower bounds for small depth circuits” is a seminal theoretical computer science paper by Johan Håstad that establishes near-tight lower bounds on the size of constant-depth Boolean circuits, profoundly influencing circuit complexity theory.
• F. None of above. chosen
• G. Unsure - the case is ambiguous/there is not enough information to decide.

Target entity: The Computational Complexity of Boolean Functions
Target entity description: "The Computational Complexity of Boolean Functions" is a foundational monograph in theoretical computer science that systematically studies the resources required to compute Boolean functions, particularly within circuit complexity.

• A. Blum complexity measures
  Blum complexity measures are a formal framework in computational complexity theory that rigorously define and compare the resource usage (such as time or space) of algorithms via axiomatic conditions.
• B. Furst–Saxe–Sipser lower bounds
  Furst–Saxe–Sipser lower bounds are foundational results in circuit complexity theory that established superpolynomial lower bounds for constant-depth Boolean circuits (AC⁰), demonstrating inherent limitations of such circuits for computing certain functions.
• C. Håstad’s switching lemma
  Håstad’s switching lemma is a fundamental result in computational complexity theory that provides powerful bounds on the simplification of Boolean formulas under random restrictions, with major applications in circuit lower bounds.
• D. P, NP, and NP-Completeness: The Basics of Complexity Theory
  "P, NP, and NP-Completeness: The Basics of Complexity Theory" is a foundational textbook by Oded Goldreich that introduces the core concepts, problems, and techniques of computational complexity theory, with a focus on the classes P, NP, and NP-complete problems.
• E. “Almost optimal lower bounds for small depth circuits”
  “Almost optimal lower bounds for small depth circuits” is a seminal theoretical computer science paper by Johan Håstad that establishes near-tight lower bounds on the size of constant-depth Boolean circuits, profoundly influencing circuit complexity theory.
• F. None of above. chosen