Fetching the paper…
Reading the bibliography…
Variational Quantum Algorithms (VQAs) and Quantum Machine Learning (QML) models train a parametrized quantum circuit to solve a given learning task.
“Quantum graph neural networks” (2019)
Guillaume Verdon, Trevor McCourt, Enxhell Luzhnica, Vikash Singh, Stefan Leichenauer, and Jack Hidary · 1909
Earlier work this paper cites.
Arthur G Rattew, Shaohan Hu, Marco Pistoia, Richard Chen, and Steve Wood · 1910
Earlier work this paper cites.
“Asymptotic behavior of group integrals in the limit of infinite rank”
Don Weingarten · 1978
Earlier work this paper cites.
“No free lunch theorems for optimization”
David H Wolpert and William G Macready · 1997
Earlier work this paper cites.
“Distributed entanglement”
Valerie Coffman, Joydip Kundu, and William K Wootters · 2000
Earlier work this paper cites.
“Moments and cumulants of polynomial random variables on unitary groups, the Itzykson-Zuber integral, and free probability”
Benoît Collins · 2003
Earlier work this paper cites.
“Renormalization algorithms for quantum-many body systems in two and higher dimensions” (2004)
Frank Verstraete and J Ignacio Cirac · 2004
Earlier work this paper cites.
Linghua Zhu, Ho Lun Tang, George S Barron, Nicholas J Mayhall, Edwin Barnes, and Sophia E Economou · 2005
Earlier work this paper cites.
“Entanglement and the foundations of statistical mechanics”
Sandu Popescu, Anthony J. Short, and Andreas Winter · 2006
Earlier work this paper cites.
“Integration with respect to the haar measure on unitary, orthogonal and symplectic group”
Benoît Collins and Piotr Śniady · 2006
Earlier work this paper cites.
“Matrix product states, projected entangled pair states, and variational renormalization group methods for quantum spin systems”
Frank Verstraete, Valentin Murg, and J Ignacio Cirac · 2008
Earlier work this paper cites.
“Entropy scaling and simulability by matrix product states”
Norbert Schuch, Michael M Wolf, Frank Verstraete, and J Ignacio Cirac · 2008
Earlier work this paper cites.
“The density-matrix renormalization group in the age of matrix product states”
Ulrich Schollwöck · 2011
Earlier work this paper cites.
“Measuring entanglement entropy of a generic many-body system with a quantum switch”
Dmitry A. Abanin and Eugene Demler · 2012
Earlier work this paper cites.
“The church of the symmetric subspace” (2013)
Aram W Harrow · 2013
Earlier work this paper cites.
“A variational eigenvalue solver on a photonic quantum processor”
Alberto Peruzzo, Jarrod McClean, Peter Shadbolt, Man-Hong Yung, Xiao-Qi Zhou, Peter J Love, Alán Aspuru-Guzik, and Jeremy L O’brien · 2014
Earlier work this paper cites.
“A quantum approximate optimization algorithm” (2014)
Edward Farhi, Jeffrey Goldstone, and Sam Gutmann · 2014
Earlier work this paper cites.
“A practical introduction to tensor networks: Matrix product states and projected entangled pair states”
Román Orús · 2014
Earlier work this paper cites.
“A practical introduction to tensor networks: Matrix product states and projected entangled pair states”
Román Orús · 2014
Earlier work this paper cites.
“Local random quantum circuits are approximate polynomial-designs”
Fernando GSL Brandao, Aram W Harrow, and Michał Horodecki · 2016
Earlier work this paper cites.
“Area laws and efficient descriptions of quantum many-body states”
Yimin Ge and Jens Eisert · 2016
Earlier work this paper cites.
“Chaos in quantum channels”
Pavan Hosur, Xiao-Liang Qi, Daniel A. Roberts, and Beni Yoshida · 2016
Earlier work this paper cites.
“Conditional mutual information of bipartite unitaries and scrambling”
Dawei Ding, Patrick Hayden, and Michael Walter · 2016
Earlier work this paper cites.
“Quantum machine learning”
Jacob Biamonte, Peter Wittek, Nicola Pancotti, Patrick Rebentrost, Nathan Wiebe, and Seth Lloyd · 2017
Earlier work this paper cites.
“Unsupervised machine learning on a hybrid quantum computer” (2017)
J. S. Otterbach, R. Manenti, N. Alidoust, A. Bestwick, et al · 2017
Earlier work this paper cites.
“Hardware-efficient variational quantum eigensolver for small molecules and quantum magnets”
Abhinav Kandala, Antonio Mezzacapo, Kristan Temme, Maika Takita, Markus Brink, Jerry M. Chow, and Jay M. Gambetta · 2017
Earlier work this paper cites.
“Chaos, complexity, and random matrices”
Jordan Cotler, Nicholas Hunter-Jones, Junyu Liu, and Beni Yoshida · 2017
Earlier work this paper cites.
“Symbolic integration with respect to the haar measure on the unitary groups”
Zbigniew Puchala and Jaroslaw Adam Miszczak · 2017
Earlier work this paper cites.
“Quantum computing in the nisq era and beyond”
John Preskill · 2018
Earlier work this paper cites.
“Barren plateaus in quantum neural network training landscapes”
Jarrod R McClean, Sergio Boixo, Vadim N Smelyanskiy, Ryan Babbush, and Hartmut Neven · 2018
Earlier work this paper cites.
“Strategies for quantum computing molecular energies using the unitary coupled cluster ansatz”
Jonathan Romero, Ryan Babbush, Jarrod R McClean, Cornelius Hempel, Peter J Love, and Alán Aspuru-Guzik · 2018
Earlier work this paper cites.
“IBM Q 16 Rueschlikon backend specification” (2018)
2018
Cited alongside, same era.
“Quantum circuit learning”
Kosuke Mitarai, Makoto Negoro, Masahiro Kitagawa, and Keisuke Fujii · 2018
Cited alongside, same era.
“Entanglement, quantum randomness, and complexity beyond scrambling”
Zi-Wen Liu, Seth Lloyd, Elton Zhu, and Huangjun Zhu · 2018
Cited alongside, same era.
“Quantum supremacy using a programmable superconducting processor”
Frank Arute, Kunal Arya, Ryan Babbush, Dave Bacon, et al · 2019
Cited alongside, same era.
“Supervised learning with quantum-enhanced feature spaces”
Vojtěch Havlíček, Antonio D Córcoles, Kristan Temme, Aram W Harrow, Abhinav Kandala, Jerry M Chow, and Jay M Gambetta · 2019
Cited alongside, same era.
“Quantum convolutional neural networks”
Iris Cong, Soonwon Choi, and Mikhail D Lukin · 2019
Cited alongside, same era.
“Noise-induced barren plateaus in variational quantum algorithms”
Samson Wang, Enrico Fontana, Marco Cerezo, Kunal Sharma, Akira Sone, Lukasz Cincio, and Patrick J Coles · 2021
Later among the works it cites.
“Limitations of optimization algorithms on noisy quantum devices”
Daniel Stilck França and Raul Garcia-Patron · 2021
Later among the works it cites.
“The controlled SWAP test for determining quantum entanglement”
Steph Foulds, Viv Kendon, and Tim Spiller · 2021
Later among the works it cites.
“Computable and operationally meaningful multipartite entanglement measures”
Jacob L. Beckey, N. Gigena, Patrick J. Coles, and M. Cerezo · 2021
Later among the works it cites.
“Random Matrix Theory of the Isospectral twirling”
Salvatore F. E. Oliviero, Lorenzo Leone, Francesco Caravelli, and Alioscia Hamma · 2021
Later among the works it cites.
“Isospectral twirling and quantum chaos”
Lorenzo Leone, Salvatore F. E. Oliviero, and Alioscia Hamma · 2021
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
“From the quantum approximate optimization algorithm to a quantum alternating operator ansatz”
Stuart Hadfield, Zhihui Wang, Bryan O’Gorman, Eleanor G Rieffel, Davide Venturelli, and Rupak Biswas · 2019
Cited alongside, same era.
“Quantum-assisted quantum compiling”
Sumeet Khatri, Ryan LaRose, Alexander Poremba, Lukasz Cincio, Andrew T Sornborger, and Patrick J Coles · 2019
Cited alongside, same era.
“Implementation of swap test for two unknown states in photons via cross-kerr nonlinearities under decoherence effect”
Min-Sung Kang, Jino Heo, Seong-Gon Choi, Sung Moon, and Sang-Wook Han · 2019
Cited alongside, same era.
“Evaluating analytic gradients on quantum hardware”
Maria Schuld, Ville Bergholm, Christian Gogolin, Josh Izaac, and Nathan Killoran · 2019
Cited alongside, same era.
“Strong bound between trace distance and hilbert-schmidt distance for low-rank states”
Patrick J Coles, M Cerezo, and Lukasz Cincio · 2019
Cited alongside, same era.
“Hartree-fock on a superconducting qubit quantum computer”
Frank Arute, Kunal Arya, Ryan Babbush, Dave Bacon, Joseph C Bardin, Rami Barends, Sergio Boixo, Michael Broughton, Bob B Buckley, David A Buell, et al · 2020
Cited alongside, same era.
Later among the works it cites.
“Quantum Chaos is Quantum”
Lorenzo Leone, Salvatore F. E. Oliviero, You Zhou, and Alioscia Hamma · 2021
Later among the works it cites.
“Transitions in entanglement complexity in random quantum circuits by measurements”
Salvatore F.E. Oliviero, Lorenzo Leone, and Alioscia Hamma · 2021
Later among the works it cites.
“Quantum computational advantage with a programmable photonic processor”
Lars S Madsen, Fabian Laudenbach, Mohsen Falamarzi Askarani, Fabien Rortais, Trevor Vincent, Jacob FF Bulmer, Filippo M Miatto, Leonhard Neuhaus, Lukas G Helt, Matthew J Collins, et al · 2022
Closest in time.
“Noisy intermediate-scale quantum algorithms”
Kishor Bharti, Alba Cervera-Lierta, Thi Ha Kyaw, Tobias Haug, Sumner Alperin-Lea, Abhinav Anand, Matthias Degroote, Hermanni Heimonen, Jakob S Kottmann, Tim Menke, et al · 2022
Closest in time.
“Generalization in quantum machine learning from few training data”
Matthias C Caro, Hsin-Yuan Huang, Marco Cerezo, Kunal Sharma, Andrew Sornborger, Lukasz Cincio, and Patrick J Coles · 2022
Closest in time.
“Provably efficient machine learning for quantum many-body problems”
Hsin-Yuan Huang, Richard Kueng, Giacomo Torlai, Victor V. Albert, and John Preskill · 2022
Closest in time.
“Challenges and opportunities in quantum machine learning”
M Cerezo, Guillaume Verdon, Hsin-Yuan Huang, Lukasz Cincio, and Patrick J Coles · 2022
Closest in time.
“Group-invariant quantum machine learning”
Martín Larocca, Frédéric Sauvage, Faris M. Sbahi, Guillaume Verdon, Patrick J. Coles, and M. Cerezo · 2022
Closest in time.
“Equivariant quantum circuits for learning on weighted graphs” (2022)
Andrea Skolik, Michele Cattelan, Sheir Yarkoni, Thomas Bäck, and Vedran Dunjko · 2022
Closest in time.
“Representation theory for geometric quantum machine learning” (2022)
Michael Ragone, Quynh T. Nguyen, Louis Schatzki, Paolo Braccia, Martin Larocca, Frederic Sauvage, Patrick J. Coles, and M. Cerezo · 2022
Closest in time.
“Trainability of dissipative perceptron-based quantum neural networks”
Kunal Sharma, Marco Cerezo, Lukasz Cincio, and Patrick J Coles · 2022
Closest in time.
“Connecting ansatz expressibility to gradient magnitudes and barren plateaus”
Zoë Holmes, Kunal Sharma, M. Cerezo, and Patrick J Coles · 2022
Closest in time.
“Equivalence of quantum barren plateaus to cost concentration and narrow gorges”
Andrew Arrasmith, Zoë Holmes, Marco Cerezo, and Patrick J Coles · 2022
Closest in time.
“Stabilizer Rényi entropy”
Lorenzo Leone, Salvatore F. E. Oliviero, and Alioscia Hamma · 2022
Closest in time.
“Measuring magic on a quantum processor”
Salvatore F. E. Oliviero, Lorenzo Leone, Alioscia Hamma, and Seth Lloyd · 2022
Closest in time.
“Optimized low-depth quantum circuits for molecular electronic structure using a separable-pair approximation”
Jakob S. Kottmann and Alán Aspuru-Guzik · 2022
Closest in time.
“Variational quantum linear solver”
Carlos Bravo-Prieto, Ryan LaRose, Marco Cerezo, Yigit Subasi, Lukasz Cincio, and Patrick J Coles · 2023
Closest in time.
“A semi-agnostic ansatz with variable structure for variational quantum algorithms”
Matias Bilkis, Marco Cerezo, Guillaume Verdon, Patrick J Coles, and Lukasz Cincio · 2023
Closest in time.
“Exploiting symmetry in variational quantum machine learning”
Johannes Jakob Meyer, Marian Mularski, Elies Gil-Fuster, Antonio Anna Mele, Francesco Arzani, Alissa Wilms, and Jens Eisert · 2023
Closest in time.
“Subtleties in the trainability of quantum machine learning models”
Supanut Thanasilp, Samson Wang, Nhat A. Nghiem, Patrick J. Coles, and M. Cerezo · 2023
Closest in time.
“Approximate unitary t-designs by short random quantum circuits using nearest-neighbor and long-range gates”
Aram W Harrow and Saeed Mehraban · 2023
Closest in time.
“Scalable measures of magic resource for quantum computers”
Tobias Haug and MS Kim · 2023
Closest in time.
“Building spatial symmetries into parameterized quantum circuits for faster training”
Frederic Sauvage, Martin Larocca, Patrick J Coles, and Marco Cerezo · 2024
Closest in time.
“Theory for equivariant quantum neural networks”
Quynh T. Nguyen, Louis Schatzki, Paolo Braccia, Michael Ragone, Patrick J. Coles, Frédéric Sauvage, Martín Larocca, and M. Cerezo · 2024
Closest in time.
“Theoretical guarantees for permutation-equivariant quantum neural networks”
Louis Schatzki, Martín Larocca, Quynh T. Nguyen, Frédéric Sauvage, and M. Cerezo · 2024
Closest in time.