activity
20152025
most citedDiscovering physical concepts with neural networks

473 citations · 1.1k across the 13 of their papers we have counts for

collaborators

13 papers

physics.comp-ph2025★ 1 cited

Interpretable Machine Learning in Physics: A Review

Sebastian Johann Wetzel, Seungwoong Ha, Raban Iten +2

Machine learning is increasingly transforming various scientific fields, enabled by advancements in computational power and access to large data sets from experiments and simulatio…

quant-ph2020★ 1 cited

Relations between different quantum Rényi divergences

Raban Iten

Quantum generalizations of Rényi's entropies are a useful tool to describe a variety of operational tasks in quantum information processing. Two families of such generalizations tu…

quant-ph2020★ 46 cited

Quantum Circuits for Sparse Isometries

Emanuel Malvetti, Raban Iten, Roger Colbeck

We consider the task of breaking down a quantum computation given as an isometry into C-NOTs and single-qubit gates, while keeping the number of C-NOT gates small. Although several…

quant-ph2020★ 25 cited

Operationally meaningful representations of physical systems in neural networks

Hendrik Poulsen Nautrup, Tony Metger, Raban Iten +5

To make progress in science, we often build abstract representations of physical systems that meaningfully encode information about the systems. The representations learnt by most…

quant-ph2019★ 41 cited

Exact and practical pattern matching for quantum circuit optimization

Raban Iten, Romain Moyard, Tony Metger +2

Quantum computations are typically compiled into a circuit of basic quantum gates. Just like for classical circuits, a quantum compiler should optimize the quantum circuit, e.g. by…

quant-ph2019★ 226 cited

Option Pricing using Quantum Computers

Nikitas Stamatopoulos, Daniel J. Egger, Yue Sun +4

We present a methodology to price options and portfolios of options on a gate-based quantum computer using amplitude estimation, an algorithm which provides a quadratic speedup com…

quant-ph2019★ 33 cited

Computing Quantum Channel Capacities

Navneeth Ramakrishnan, Raban Iten, Volkher B. Scholz +1

The capacity of noisy quantum channels characterizes the highest rate at which information can be reliably transmitted and it is therefore of practical as well as fundamental impor…

quant-ph2019★ 15 cited

Introduction to UniversalQCompiler

Raban Iten, Oliver Reardon-Smith, Emanuel Malvetti +5

We introduce an open source software package UniversalQCompiler written in Mathematica that allows the decomposition of arbitrary quantum operations into a sequence of single-qubit…

quant-ph2018★ 473 cited

Discovering physical concepts with neural networks

Raban Iten, Tony Metger, Henrik Wilming +2

Despite the success of neural networks at solving concrete physics problems, their use as a general-purpose tool for scientific discovery is still in its infancy. Here, we approach…

math-ph2016★ 2 cited

Smooth manifold structure for extreme channels

Raban Iten, Roger Colbeck

A quantum channel from a system of dimension to a system of dimension is a completely positive trace-preserving map from complex to $d_B\times d…

quant-ph2016★ 33 cited

Quantum Circuits for Quantum Channels

Raban Iten, Roger Colbeck, Matthias Christandl

We study the implementation of quantum channels with quantum computers while minimizing the experimental cost, measured in terms of the number of Controlled-NOT (C-NOT) gates requi…

quant-ph2016★ 24 cited

Pretty good measures in quantum information theory

Raban Iten, Joseph M. Renes, David Sutter

Quantum generalizations of Renyi's entropies are a useful tool to describe a variety of operational tasks in quantum information processing. Two families of such generalizations tu…

quant-ph2015★ 219 cited

Quantum Circuits for Isometries

Raban Iten, Roger Colbeck, Ivan Kukuljan +2

We consider the decomposition of arbitrary isometries into a sequence of single-qubit and Controlled-NOT (C-NOT) gates. In many experimental architectures, the C-NOT gate is relati…