Geometry optimization in quantum Monte Carlo with solution mapping: Application to formaldehyde

Global Optimization: Quantum Thermal Annealing with Path Integral Monte Carlo

We investigate a new method (QTA-PIMC) for global optimization on complex potential energy surfaces which combines the path integral Monte Carlo method with quantum and thermal annealing. This method is applied to the BLN protein model (Honeycutt, J. D.; Thirumalai, D. Biopolymers 1992, 32, 695). We show that this new approach outperforms simulated (thermal) annealing (SA) and that in fact SA i...

Probability: From Monte Carlo to Geometry

Monte Carlo-based optimization of a gamma probe system for sentinel lymph node mapping

Introduction: Sentinel lymph node biopsy (SLNB) is a standard surgical technique to identify sentinel lymph node (SLN) for the staging of early breast cancer. Nowadays, two methods are used for the identification of SLN: blue dye method aiding visually and radioactive dye using gamma detector. A wide range of gamma probe systems with different design and performance are used in...

Robust wave function optimization procedures in quantum Monte Carlo methods

The energy variance optimization algorithm over a fixed ensemble of configurations in variational Monte Carlo often encounters problems of convergence. Being formally identical to a problem of fitting data, we re-examine it from a statistical maximum-likelihood point of view. We show that the assumption of an underlying Gaussian distribution of the local energy, implicit in the standard varianc...

Aram Harrow - Quantum Monte Carlo vs Tunneling in Adiabatic Optimization

In this talk I'll present a quantum algorithm for solving semidefinite programs (SDPs). It has worst case running time O((nm)^1/2 r), with n and r the dimension and sparsity of the input matrices, respectively, and m the number of constraints. In contrast any classical method requires at least Omega(nm) time to solve the problem. I'll discuss how for some instances the algorithm might offer eve...