Fetching the paper…
Reading the bibliography…
We investigate the problem of predicting the output behavior of unknown quantum channels.
Probabilistic characteristics of graphs with large connectivity
Grigorii Aleksandrovich Margulis · 1974
Earlier work this paper cites.
On the critical percolation probabilities
Lucio Russo · 1981
Earlier work this paper cites.
An approximate zero-one law
Lucio Russo · 1982
Earlier work this paper cites.
Chebyshev polynomials
Theodore J Rivlin · 1990
Earlier work this paper cites.
Improved learning of ac 0 functions
Merrick L Furst, Jeffrey C Jackson, and Sean W Smith · 1991
Earlier work this paper cites.
Learning decision trees using the fourier spectrum
Eyal Kushilevitz and Yishay Mansour · 1991
Earlier work this paper cites.
Constant depth circuits, fourier transform, and learnability
Nathan Linial, Yishay Mansour, and Noam Nisan · 1993
Earlier work this paper cites.
Learning DNF in time 2 O ~ ( n 1 / 3 ) 2^{\tilde{O}(n^{1/3})}
Adam R Klivans and Rocco Servedio · 2001
Earlier work this paper cites.
Black holes as mirrors: quantum information in random subsystems
Patrick Hayden and John Preskill · 2007
Earlier work this paper cites.
Agnostically learning halfspaces
Adam Tauman Kalai, Adam R Klivans, Yishay Mansour, and Rocco A Servedio · 2008
Earlier work this paper cites.
Ashley Montanaro and Tobias J Osborne · 2008
Earlier work this paper cites.
Quantum-process tomography: Resource analysis of different strategies
Masoud Mohseni, Ali T Rezakhani, and Daniel A Lidar · 2008
Earlier work this paper cites.
Analysis of Boolean Functions
Ryan O’Donnell · 2014
Cited alongside, same era.
Foundations of machine learning
Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalkar · 2018
Cited alongside, same era.
Learning the alpha-bits of black holes
Patrick Hayden and Geoffrey Penington · 2019
Cited alongside, same era.
Variational fast forwarding for quantum simulation beyond the coherence time
Cristina Cirstoiu, Zoe Holmes, Joseph Iosue, Lukasz Cincio, Patrick J Coles, and Andrew Sornborger · 2020
Cited alongside, same era.
Efficient learning of quantum noise
Robin Harper, Steven T Flammia, and Joel J Wallman · 2020
Cited alongside, same era.
Predicting many properties of a quantum system from very few measurements
Hsin-Yuan Huang, Richard Kueng, and John Preskill · 2020
Cited alongside, same era.
Quantum talagrand, kkl and friedgut’s theorems and the learnability of quantum boolean functions
Cambyse Rouzé, Melchior Wirth, and Haonan Zhang · 2022
Later among the works it cites.
Nearly optimal algorithms for testing and learning quantum junta channels
Zongbo Bao and Penghui Yao · 2023
Later among the works it cites.
Testing and learning quantum juntas nearly optimally
Thomas Chen, Shivam Nadimpalli, and Henry Yuen · 2023
Later among the works it cites.
Learning to predict arbitrary quantum processes
Hsin-Yuan Huang, Sitan Chen, and John Preskill · 2023
Later among the works it cites.
Quantum and classical low-degree learning via a dimension-free remez inequality
Ohad Klein, Joseph Slote, Alexander Volberg, and Haonan Zhang · 2023
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Pauli error estimation via population recovery
Steven T Flammia and Ryan O’Donnell · 2021
Cited alongside, same era.
Information-theoretic bounds on quantum advantage in machine learning
Hsin-Yuan Huang, Richard Kueng, and John Preskill · 2021
Cited alongside, same era.
Fast estimation of sparse quantum noise
Robin Harper, Wenjun Yu, and Steven T Flammia · 2021
Cited alongside, same era.
Learning low-degree functions from a logarithmic number of random queries
Alexandros Eskenazis and Paata Ivanisvili · 2022
Cited alongside, same era.
Quantum advantage in learning from experiments
Hsin-Yuan Huang, Michael Broughton, Jordan Cotler, Sitan Chen, Jerry Li, Masoud Mohseni, Hartmut Neven, Ryan Babbush, Richard Kueng, John Preskill, et al · 2022
Cited alongside, same era.
Replica wormholes and the black hole interior
Geoff Penington, Stephen H Shenker, Douglas Stanford, and Zhenbin Yang · 2022
Cited alongside, same era.
Shivam Nadimpalli, Natalie Parham, Francisca Vasconcelos, and Henry Yuen · 2023
Later among the works it cites.
Probabilistic error cancellation with sparse pauli–lindblad models on noisy quantum processors
Ewout Van Den Berg, Zlatko K Minev, Abhinav Kandala, and Kristan Temme · 2023
Later among the works it cites.
Noncommutative bohnenblust–hille inequalities
Alexander Volberg and Haonan Zhang · 2023
Later among the works it cites.
The complexity of learning (pseudo) random dynamics of black holes and other chaotic systems
Lisa Yang and Netta Engelhardt · 2023
Later among the works it cites.
Learning low-degree quantum objects
Srinivasan Arunachalam, Arkopal Dutt, Francisco Escudero Gutiérrez, and Carlos Palazuelos · 2024
Closest in time.
Dynamical simulation via quantum machine learning with provable generalization
Joe Gibbs, Zoe Holmes, Matthias C Caro, Nicholas Ezzell, Hsin-Yuan Huang, Lukasz Cincio, Andrew T Sornborger, and Patrick J Coles · 2024
Closest in time.
Learning shallow quantum circuits
Hsin-Yuan Huang, Yunchao Liu, Michael Broughton, Isaac Kim, Anurag Anshu, Zeph Landau, and Jarrod R McClean · 2024
Closest in time.