Simons Institute Courses

Black-Box Separations in Quantum Cryptography

Explores black-box separations in quantum cryptography, discussing efforts to extend classical results, related problems, and barriers for unconditional separations in the quantum setting.

• YouTube
• 48 minutes
• Self-Paced
• Free Video

Quantum Pseudorandomness in Algorithmica, and Its Implications to Cryptography and Complexity

Explore quantum pseudorandomness, its separation from one-way functions, and implications for cryptography and complexity theory. Discover potential for quantum cryptography without relying on traditional assumptions.

• YouTube
• 46 minutes
• Self-Paced
• Free Video

On the Computational Hardness Needed for Quantum Cryptography

Explores EFI pairs as essential for quantum cryptography, comparing their role to one-way functions in classical cryptography and demonstrating their necessity for various applications.

• YouTube
• 48 minutes
• Self-Paced
• Free Video

Commitments to Quantum States

Exploring quantum state commitments, their definition as erasure of sender's message, and applications in cryptography, including succinct arguments for NP and potentially QMA.

• YouTube
• 48 minutes
• Self-Paced
• Free Video

Quantum Minimalism

Exploring minimal quantum cryptographic assumptions beyond one-way functions, examining their significance and potential implications for future quantum-secure cryptographic systems.

• YouTube
• 34 minutes
• Self-Paced
• Free Video

Cryptography with Certified Deletion

Explore quantum cryptography's certified deletion, enabling verifiable information-theoretic deletion of encrypted secrets, with applications in various cryptosystems and recent advancements in public verification.

• YouTube
• 46 minutes
• Self-Paced
• Free Video

Black-Hole Radiation Decoding as a Cryptographic Assumption

Explore the intriguing connection between black-hole radiation decoding and quantum cryptography, revealing how high-energy physics phenomena can imply the existence of secure cryptographic primitives.

• YouTube
• 47 minutes
• Self-Paced
• Free Video

Random Restrictions and Fourier Concentration - Part 2

Explore advanced concepts in Fourier analysis and random restrictions, focusing on their applications in theoretical computer science and mathematical analysis.

• YouTube
• 56 minutes
• Self-Paced
• Free Video

Random Restrictions and Fourier Concentration - Part 1

Explore random restrictions and Fourier concentration in analysis and theoretical computer science with MIT researcher Esty Kelman.

• YouTube
• 1 hour
• Self-Paced
• Free Video

Introduction to Analysis of Boolean Functions

Explore advanced concepts in Boolean function analysis, including Fourier analysis and applications in theoretical computer science.

• YouTube
• 1 hour 2 minutes
• Self-Paced
• Free Video

Introduction to Analysis of Boolean Functions

Explore foundational concepts in Boolean function analysis, including Fourier analysis and hypercontractivity, with applications in theoretical computer science.

• YouTube
• 1 hour
• Self-Paced
• Free Video

The Problem with Qubits

Explore quantum computing challenges, error rates, and benchmarking methods with insights on quantum supremacy and superconnected qubits from a leading expert.

• YouTube
• 28 minutes
• Self-Paced
• Free Video

Using Theories of Decision-Making Under Uncertainty to Improve Data Visualization

Explore decision-making under uncertainty to enhance data visualization. Learn techniques for improving inductive reasoning, pattern finding, and effect size judgment in visual data analysis and communication.

• YouTube
• 1 hour
• Self-Paced
• Free Video

Debiasing Random Forests for Treatment Effect Estimation

Explore techniques for debiasing random forests in treatment effect estimation, focusing on resource allocation in election campaigns and get-out-the-vote experiments.

• YouTube
• 54 minutes
• Self-Paced
• Free Video

Beyond Worst-Case Analysis - Panel Discussion

Experts discuss advanced algorithmic analysis, exploring beyond worst-case scenarios to improve efficiency and understanding in computer science and machine learning applications.

• YouTube
• 1 hour 10 minutes
• Self-Paced
• Free Video