activity
20072020
most citedMachine Learning for Precise Quantum Measurement

197 citations · 465 across the 11 of their papers we have counts for

collaborators

11 papers

cs.DC2020★ 10 cited

Flow: Separating Consensus and Compute -- Block Formation and Execution

Alexander Hentschel, Yahya Hassanzadeh-Nazarabadi, Ramtin Seraj +2

Most current blockchains require all full nodes to execute all tasks limits the throughput of existing blockchains, which are well documented and among the most significant hurdles…

cs.DC2019★ 1 cited

Flow: Separating Consensus and Compute -- Execution Verification

Alexander Hentschel, Dieter Shirley, Layne Lafrance +1

Throughput limitations of existing blockchain architectures are well documented and are one of the most significant hurdles for their wide-spread adoption. In our previous proof-of…

cs.DC2019★ 3 cited

Flow: Separating Consensus and Compute

Alexander Hentschel, Dieter Shirley, Layne Lafrance

Throughput limitations of existing blockchain architectures are one of the most significant hurdles for their wide-spread adoption. Attempts to address this challenge include layer…

cs.AI2017★ 47 cited

A Benchmark Environment Motivated by Industrial Control Problems

Daniel Hein, Stefan Depeweg, Michel Tokic +4

In the research area of reinforcement learning (RL), frequently novel and promising methods are developed and introduced to the RL community. However, although many researchers are…

cs.LG2017★ 9 cited

Batch Reinforcement Learning on the Industrial Benchmark: First Experiences

Daniel Hein, Steffen Udluft, Michel Tokic +3

The Particle Swarm Optimization Policy (PSO-P) has been recently introduced and proven to produce remarkable results on interacting with academic reinforcement learning benchmarks…

cs.NE2016★ 76 cited

Particle Swarm Optimization for Generating Interpretable Fuzzy Reinforcement Learning Policies

Daniel Hein, Alexander Hentschel, Thomas Runkler +1

Fuzzy controllers are efficient and interpretable system controllers for continuous state and action spaces. To date, such controllers have been constructed manually or trained aut…

cs.LG2016★ 4 cited

Introduction to the "Industrial Benchmark"

Daniel Hein, Alexander Hentschel, Volkmar Sterzing +2

A novel reinforcement learning benchmark, called Industrial Benchmark, is introduced. The Industrial Benchmark aims at being be realistic in the sense, that it includes a variety o…

quant-ph2011★ 100 cited

An Efficient Algorithm for Optimizing Adaptive Quantum Metrology Processes

Alexander Hentschel, Barry C. Sanders

Quantum-enhanced metrology infers an unknown quantity with accuracy beyond the standard quantum limit (SQL). Feedback-based metrological techniques are promising for beating the SQ…

math-ph2010★ 9 cited

Ordered Measurements of Permutationally-Symmetric Qubit Strings

Alexander Hentschel, Barry C. Sanders

We show that any sequence of measurements on a permutationally-symmetric (pure or mixed) multi-qubit string leaves the unmeasured qubit substring also permutationally-symmetric. In…

quant-ph2009★ 197 cited

Machine Learning for Precise Quantum Measurement

Alexander Hentschel, Barry C. Sanders

Adaptive feedback schemes are promising for quantum-enhanced measurements yet are complicated to design. Machine learning can autonomously generate algorithms in a classical settin…

hep-th2007★ 9 cited

Testing the nested light-cone Bethe equations of the AdS_5 x S^5 superstring

Alexander Hentschel, Jan Plefka, Per Sundin

We perform a detailed test of the quantum integrability of the AdS_5 x S^5 superstring in uniform light-cone gauge in its near plane-wave limit. For this we establish the form of t…