229 citations · 2.1k across the 110 of their papers we have counts for
7 papers · 1 filter
Quantum Reinforcement Learning for Solving a Stochastic Frozen Lake Environment and the Impact of Quantum Architecture Choices
Theodora-Augustina Drăgan, Maureen Monnet, Christian B. Mendl +1
Quantum reinforcement learning (QRL) models augment classical reinforcement learning schemes with quantum-enhanced kernels. Different proposals on how to construct such models empi…
Riemannian quantum circuit optimization for Hamiltonian simulation
Ayse Kotil, Rahul Banerjee, Qunsheng Huang +1
Hamiltonian simulation, i.e., simulating the real time evolution of a target quantum system, is a natural application of quantum computing. Trotter-Suzuki splitting methods can gen…
On the Optimal Linear Contraction Order of Tree Tensor Networks, and Beyond
Mihail Stoian, Richard Milbradt, Christian B. Mendl
The contraction cost of a tensor network depends on the contraction order. However, the optimal contraction ordering problem is known to be NP-hard. We show that the linear contrac…
Ternary unitary quantum lattice models and circuits in dimensions
Richard Milbradt, Lisa Scheller, Christopher Aßmus +1
We extend the concept of dual unitary quantum gates to quantum lattice models in dimensions, by introducing and studying ternary unitary four-particle gates, which are unit…
Quantum Policy Iteration via Amplitude Estimation and Grover Search -- Towards Quantum Advantage for Reinforcement Learning
Simon Wiedemann, Daniel Hein, Steffen Udluft +1
We present a full implementation and simulation of a novel quantum reinforcement learning method. Our work is a detailed and formal proof of concept for how quantum algorithms can…
Simulating quantum circuits using tree tensor networks
Philipp Seitz, Ismael Medina, Esther Cruz +2
We develop and analyze a method for simulating quantum circuits on classical computers by representing quantum states as rooted tree tensor networks. Our algorithm first determines…