Charlie Carlson
PhD
Research Topics
Approximate counting; combinatorial optimization; convex optimization; spectral graph theory; statistical physics; and randomized algorithms
Publications
- Flip Dynamics for Sampling Colorings: Improving (11/6 - ) Using A Simple Metric. With Eric Vigoda. To appear in ACM-SIAM Symposium on Discrete Algorithms (SODA) 2025.
- Optimal Mixing for Randomly Sampling Edge Colorings on Trees Down to the Max Degree. With Xiaoyu Chen, Weiming Feng, and Eric Vigoda. To Appear in ACM-SIAM Symposium on Discrete Algorithms (SODA) 2025.
- Approximately Counting Independent Sets in Dense Bipartite Graphs via Subspace Enumeration. With Ewan Davies, Alexandra Kolla, and Aditya Potukuchi. In 51st International Colloquium on Automata, Languages, and Programming (ICALP) 2024.
- Approximate Counting and Expansion. PhD Thesis 2023.
- Improved Distributed Algorithms for Random Colorings. With Daniel Frishberg and Eric Vigoda. Conference on Principles of Distributed Systems (OPODIS) 2023.
- Efficient algorithms for the Potts model on small-set expanders. With Ewan Davies and Alexandra Kolla. Chicago Journal of Theoretical Computer Science 2024.
- Approximation Algorithm for Norm Multiway Cut. With Jafar Jafarov, Konstantin Markarychev, Yury Makarychev, and Liren Shan. European Symposium of Algorithms (ESA) 2023.
- Algorithms for the ferromagnetic Potts model on expanders. With Ewan Davies, Nicolas Fraiman, Alexandra Kolla, Aditya Potukuchi, and Corrine Yap. Symposium on Foundations of Computer Science (FOCS) 2022.
- Computational Thresholds for the Fixed-Magnetization Ising Model. With Ewan Davies, Alexandra Kolla, and Will Perkins. Symposium of Theory of Computation (STOC) 2022.
- Lower Bounds for Max-Cut via Semidefinite Programming. With Alexandra Kolla, Ray Li, Nitya Mani, Benny Sudakov, and Luca Trevisan. Latin Amerian Theoretical Informatics Symposium (LATIN) 2020.
- Spectral Aspects of Symmetric Matrix Signings. With Karthekeyan Chandrasekaran, Hsien-Chih Chang, and Alexandra Kolla. Mathematical Foundations of Computer Science (MFCS) 2019.
- Improving the Smoothed Complexity of FLIP for Max Cut Problems. With Ali Bibak and Karthekeyan Chandrasekaran. ACM-SIAM Symposium on Discrete Algorithms (SODA) 2019.
- Optimal Lower Bounds for Sketching Graph Cuts. With Alexandra Kolla, Nikhil Srivastava, and Luca Trevisan. ACM-SIAM Symposium on Discrete Algorithms (SODA) 2019.