演讲人:Michele Orrù [CNRS] 时间: 14:00-15:00, Mar 12, 2026 (Thu)地点: RM 1-222, FIT Building内容:We study a new Fiat-Shamir transformation based on an ideal permutation that minimizes permutation calls and aligns more closely with deployed systems. We show concrete bounds for soundness, knowledge soundness, and zero knowledge, revealing that indifferentiability -- the standard notion used ...
演讲人:Binyi Chen时间:14:00-15:00, Feb 28, 2026 (Sat)地点: RM 1-222, FIT Building内容:In an era of AI and digitalization, we face a dual challenge in building trust while preserving privacy. For example, social platforms are flooded with unverifiable AI-generated content, and online services require users to excessively expose their personal data. Zero-Knowledge Succinct Proofs (ZK-SNARKs) ...
演讲人:孙向恺 [Caltech] 时间:10:00-12:00, Feb 27, 2026 (Fri)地点: Lecture Hall, FIT Building内容:The fidelity of entangling operations is a key figure of merit in quantum information processing, especially in the context of quantum error correction. High-fidelity entangling gates in neutral atom arrays have seen remarkable advancement recently. A full understanding of error sources and thei...
演讲人:罗迪 [清华大学]时间:14:00-15:30, Feb 2, 2026 (Mon)地点: RM S527, MMW Building内容:Recent advancements in continuous-variable (CV) quantum systems are opening up growing opportunities for applications in both quantum learning and quantum simulation. In this talk, I will first discuss machine-learning approaches to multi-mode quantum tomography, enabling efficient reconstruction and ch...
演讲人:张宇轩时间:10:00-11:30, Jan 15, 2026 (Thu)地点: 蒙民伟科技大楼南楼527会议室内容:Over a decade after its proposal, the idea of using quantum computers to sample hard distributions has remained a key path to demonstrating quantum advantage. Yet a severe drawback remains: the anti-concentrated distributions believed to be hard to classically simulate are typically hard to verify without...
演讲人:Yian Ma (马易安) [University of California, San Diego]时间:13:30-15:00, Dec 26, 2025 (Fri)地点:RM 1-222, FIT Building内容:In the first part of the talk, I will discuss an interesting phenomenon in multiagent learning, that the mixed Nash equilibria are uniformly stable if and only if they are collectively rational. This justifies the effusive use of multi-agent learning systems and r...