Eric Ricardo ANSCHUETZ
PhD, Massachusetts Institute of Technology, USA (2023)
Assistant Professor, NUS Presidential Young Professorship
Email: e-ans@nus.edu.sg
Office: S12-03-10
Current Research
- I use methods from statistical physics to understand the average-case complexity of optimisation, learning, and sampling problems, both for traditional (“classical”) algorithms and for algorithms which take advantage of quantum mechanical effects (“quantum algorithms”). This has led to new characterizations of spin glass phases in quantum many-body systems. I also work on understanding what features of a problem might make it more amenable to quantum algorithms than classical algorithms using ideas from quantum foundations theory.
Selected Publications
- Eric R. Anschuetz, “Quantum Glassiness from Efficient Learning,” Commun. Math. Phys. 407, 30 (2026), Quantum Information Processing (2026)
- Eric R. Anschuetz, “A Unified Theory of Quantum Neural Network Loss Landscapes,” in International Conference on Learning Representations (2026) pp. 97859–97918
- Eric R. Anschuetz, Chi-Fang Chen, Bobak T. Kiani, and Robbie King, “Strongly Interacting Fermions Are Nontrivial yet Nonglassy,” Phys. Rev. Lett. 135, 030602 (2025), Quantum Information Processing (2025)
- Eric R. Anschuetz and Bobak T. Kiani, “Quantum variational algorithms are swamped with traps,” Nat. Commun. 13, 7760 (2022)
- Eric R. Anschuetz, “Critical Points in Quantum Generative Models,” in International Conference on Learning Representations (2022)