M
Matthias Troyer
Researcher at Microsoft
Publications - 481
Citations - 35590
Matthias Troyer is an academic researcher from Microsoft. The author has contributed to research in topics: Quantum Monte Carlo & Monte Carlo method. The author has an hindex of 86, co-authored 473 publications receiving 28965 citations. Previous affiliations of Matthias Troyer include University of Zurich & ETH Zurich.
Papers
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Journal ArticleDOI
Quantum versus Classical Annealing of Ising Spin Glasses
TL;DR: Santoro et al. as mentioned in this paper revisited the question of when quantum speedup may be expected for Ising spin glass problems, and they found that even though a better scaling compared to simulated classical annealing can be achieved for QMC simulations, this advantage is due to time discretization and measurements which are not possible on a physical quantum-annealing device.
Book ChapterDOI
Parallel Object Oriented Monte Carlo Simulations
TL;DR: This work presents a C++ Monte Carlo class library for the automatic parallelization of Monte Carlo simulations and discusses the advantages of object-oriented design in the development of this library.
Journal ArticleDOI
Hybrid quantum-classical approach to correlated materials
TL;DR: This work shows that by using a hybrid quantum-classical algorithm that incorporates the power of a small quantum computer into a framework of classical embedding algorithms, the electronic structure of complex correlated materials can be efficiently tackled using a quantum computer.
Journal ArticleDOI
Phase Diagram and Critical Exponents of a Dissipative Ising Spin Chain in a Transverse Magnetic Field
TL;DR: It is shown that the character of the quantum phase transition is radically altered from the corresponding nondissipative model and the double well coupled to a dissipative heat bath with linear friction to form a new quantum criticality which is independent of dissipation strength.
Journal ArticleDOI
Complete-graph tensor network states: a new fermionic wave function ansatz for molecules
TL;DR: In this article, a tensor network (CGTN) ansatz is proposed to capture the electron correlation within a molecule of arbitrary structure, which is applied to the energy splitting of states of different spins for methylene and strongly correlated ozone molecule at a transition state structure.