1 citations · 2 across the 4 of their papers we have counts for
13 papers
Ensemble Markov chain Monte Carlo with teleporting walkers
Michael Lindsey, Jonathan Weare, Anna Zhang
We introduce an ensemble Markov chain Monte Carlo approach to sampling from a probability density with known likelihood. This method upgrades an underlying Markov chain by allowing…
Scalable semidefinite programming approach to variational embedding for quantum many-body problems
Yuehaw Khoo, Michael Lindsey
In quantum embedding theories, a quantum many-body system is divided into localized clusters of sites which are treated with an accurate `high-level' theory and glued together self…
Committor functions via tensor networks
Yian Chen, Jeremy Hoskins, Yuehaw Khoo +1
We propose a novel approach for computing committor functions, which describe transitions of a stochastic process between metastable states. The committor function satisfies a back…
Multiscale semidefinite programming approach to positioning problems with pairwise structure
Yian Chen, Yuehaw Khoo, Michael Lindsey
We consider the optimization of pairwise objective functions, i.e., objective functions of the form fo…
Towards sharp error analysis of extended Lagrangian molecular dynamics
Dong An, Lin Lin, Michael Lindsey
The extended Lagrangian molecular dynamics (XLMD) method provides a useful framework for reducing the computational cost of a class of molecular dynamics simulations with constrain…
Enhancing robustness and efficiency of density matrix embedding theory via semidefinite programming and local correlation potential fitting
Xiaojie Wu, Michael Lindsey, Tiangang Zhou +2
Density matrix embedding theory (DMET) is a powerful quantum embedding method for solving strongly correlated quantum systems. Theoretically, the performance of a quantum embedding…