Bingxin Lao

                                        Bing-Xin Lao
Address: 45 rue d'Ulm, 75005, Paris | Email: bxlaophysics@gmail.com

Education

2021 - present
Master in Physics, École Normale Supérieure - PSL (Ulm), Paris, France

Admitted through 2021 International Selection (Normalien, 1000 euros/month grant for 3 years)

2017 - 2021
Bachelor degree of Sciences, Physics, University of Science and Technology of China, Hefei, China

Outstanding graduate, Ji-Ci Yan's scholarship

Research Experience

Here I only list research experiences that have resulted in the publication of formal papers.
2023.01 - 2023.06
M2 thesis, Institut des Hautes Études Scientifiques, Paris, France
Supervisor: Slava Rychkov

We apply the conformal perturbation theory to construct the effective Hamiltonian of the transverse field Ising model, numerically demonstrating the state-operator correspondence in a direct way. See Preprint [P2].

2022.02 - 2022.08
M1 thesis, Institut de Physique Théorique, Paris, France
Supervisor: Ruben Minasian

Observe that there exists composite anomaly in 8D minimal supergravity (with 16 supercharges), potentially the anomaly cancellation can help us select the possible consistent theory. We explicitly show that relation between this anomaly and the Borcherds product and point out that the symmetry enhancements are actually accompanied with reflective lattices. See Preprint [P1].

2020.03 - 2021.07
Undergraduate research and Bachelor thesis, Fudan University, Shanghai, China
Supervisor: Ling-Yan Hung

We investigate the Levin-Wen model where we drop the unitary requirement. By studying a concrete example (Galois conjugates of string-net model), we explain how to extract the modular data and entanglement entropy by using tensor network. See Publication [2].

2019.7 - 2019.9
Summer research, Massachusetts Institute of Technology, Boston, USA
Supervisor: Mark Vogelsberger and Aaron Smith

We analytically study the Lyman-alpha radiative process within power-density profile and apply Gridless Monte-Carlo Radiative Transfer (GMCRT) method to numerically demonstrate our new solutions. See Publication [1].