From the 1 of 7 linked papers with an AI index.
7 papers
Robust quantum state certification and uncertainty principles for total influence
Andrea Coladangelo, Jerry Li, Joseph Slote
The paper demonstrates that nonadaptive single‑qubit Pauli measurements can efficiently certify whether an unknown n‑qubit state is close to a target state using an optimal number…
Separating Oblivious and Adaptive Models of Variable Selection
Ziyun Chen, Jerry Li, Kevin Tian +1
Sparse recovery is among the most well-studied problems in learning theory and high-dimensional statistics. In this work, we investigate the statistical and computational landscape…
Density estimation for Hellinger via minimum-distance estimators: mixtures of Gaussians, log-concave, and more
Spencer Compton, Jerry Li
We study the task of density estimation, where we hope to accurately estimate a probability density from samples. A textbook method for density estimation in total variation di…
Lower Bounds for Learning Hamiltonians from Time Evolution
Ziyun Chen, Jerry Li, Joseph Slote
Learning about a Hamiltonian from its time evolution is a fundamental task in quantum science. A flurry of recent work has developed powerful new algorithms with pro…
The Power of Two Bases: Robust and copy-optimal certification of nearly all quantum states with few-qubit measurements
Andrea Coladangelo, Jerry Li, Joseph Slote +1
A central task in quantum information science is state certification: testing whether an unknown state is -close to a fixed target state, or -far. Recent work has shown…
Rigorous Implications of the Low-Degree Heuristic
Jun-Ting Hsieh, Daniel M. Kane, Pravesh K. Kothari +3
Over the past decade, the low-degree heuristic has been used to estimate the algorithmic thresholds for a wide range of average-case planted vs null distinguishing problems. Such r…