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Journal Articles
- 2024
[j11]Paolo Braccia, Pablo Bermejo, Lukasz Cincio, Marco Cerezo:
Computing exact moments of local random quantum circuits via tensor networks. Quantum Mach. Intell. 6(2): 54 (2024)- [j10]Samson Wang
, Piotr Czarnik, Andrew Arrasmith, Marco Cerezo, Lukasz Cincio, Patrick J. Coles:
Can Error Mitigation Improve Trainability of Noisy Variational Quantum Algorithms? Quantum 8: 1287 (2024) - 2023
- [j9]M. Bilkis, Marco Cerezo, Guillaume Verdon, Patrick J. Coles, Lukasz Cincio:
A semi-agnostic ansatz with variable structure for variational quantum algorithms. Quantum Mach. Intell. 5(2): 43 (2023) - [j8]Daniel Bultrini, Max Hunter Gordon, Piotr Czarnik, Andrew Arrasmith, Marco Cerezo, Patrick J. Coles, Lukasz Cincio:
Unifying and benchmarking state-of-the-art quantum error mitigation techniques. Quantum 7: 1034 (2023) - [j7]Daniel Bultrini, Samson Wang, Piotr Czarnik, Max Hunter Gordon, Marco Cerezo, Patrick J. Coles, Lukasz Cincio:
The battle of clean and dirty qubits in the era of partial error correction. Quantum 7: 1060 (2023) - [j6]Carlos Bravo-Prieto, Ryan Larose, Marco Cerezo, Yigit Subasi, Lukasz Cincio, Patrick J. Coles:
Variational Quantum Linear Solver. Quantum 7: 1188 (2023) - 2022
- [j5]Marco Cerezo, Guillaume Verdon, Hsin-Yuan Huang, Lukasz Cincio, Patrick J. Coles:
Challenges and opportunities in quantum machine learning. Nat. Comput. Sci. 2(9): 567-576 (2022) - 2021
- [j4]Andrew Arrasmith, Marco Cerezo, Piotr Czarnik, Lukasz Cincio, Patrick J. Coles:
Effect of barren plateaus on gradient-free optimization. Quantum 5: 558 (2021) - [j3]Piotr Czarnik, Andrew Arrasmith, Patrick J. Coles, Lukasz Cincio:
Error mitigation with Clifford quantum-circuit data. Quantum 5: 592 (2021) - 2020
- [j2]Marco Cerezo, Alexander Poremba, Lukasz Cincio, Patrick J. Coles:
Variational Quantum Fidelity Estimation. Quantum 4: 248 (2020) - [j1]Jonas M. Kübler, Andrew Arrasmith, Lukasz Cincio, Patrick J. Coles:
An Adaptive Optimizer for Measurement-Frugal Variational Algorithms. Quantum 4: 263 (2020)
Conference and Workshop Papers
- 2023
- [c4]Alon Kukliansky, Ed Younis, Lukasz Cincio, Costin Iancu:
QFactor: A Domain-Specific Optimizer for Quantum Circuit Instantiation. QCE 2023: 814-824 - [c3]Adrien Suau, Jon Nelson, Marc Vuffray, Andrey Y. Lokhov, Lukasz Cincio, Carleton Coffrin:
Single-Qubit Cross Platform Comparison of Quantum Computing Hardware. QCE 2023: 1369-1377 - 2022
- [c2]Adrien Suau, Marc Vuffray, Andrey Y. Lokhov, Lukasz Cincio, Carleton Coffrin:
Vector Field Visualization of Single-Qubit State Tomography. QCE 2022: 528-534 - 2020
- [c1]Sami Khairy, Ruslan Shaydulin, Lukasz Cincio, Yuri Alexeev, Prasanna Balaprakash:
Learning to Optimize Variational Quantum Circuits to Solve Combinatorial Problems. AAAI 2020: 2367-2375
Informal and Other Publications
- 2024
- [i24]Martin Larocca, Supanut Thanasilp, Samson Wang, Kunal Sharma, Jacob D. Biamonte, Patrick J. Coles, Lukasz Cincio, Jarrod R. McClean, Zoë Holmes, Marco Cerezo:
A Review of Barren Plateaus in Variational Quantum Computing. CoRR abs/2405.00781 (2024) - [i23]Andrew E. Deneris, Pablo Bermejo, Paolo Braccia, Lukasz Cincio, Marco Cerezo:
Exact spectral gaps of random one-dimensional quantum circuits. CoRR abs/2408.11201 (2024) - [i22]Pablo Bermejo, Paolo Braccia, Manuel S. Rudolph, Zoë Holmes, Lukasz Cincio, Marco Cerezo:
Quantum Convolutional Neural Networks are (Effectively) Classically Simulable. CoRR abs/2408.12739 (2024) - [i21]Yuxuan Zhang, Roeland Wiersema, Juan Carrasquilla, Lukasz Cincio, Yong Baek Kim:
Scalable quantum dynamics compilation via quantum machine learning. CoRR abs/2409.16346 (2024) - 2023
- [i20]Marco Cerezo, Guillaume Verdon, Hsin-Yuan Huang, Lukasz Cincio, Patrick J. Coles:
Challenges and Opportunities in Quantum Machine Learning. CoRR abs/2303.09491 (2023) - [i19]Elijah Pelofske, Andreas Bärtschi, Lukasz Cincio, John K. Golden, Stephan J. Eidenbenz:
Scaling Whole-Chip QAOA for Higher-Order Ising Spin Glass Models on Heavy-Hex Graphs. CoRR abs/2312.00997 (2023) - 2022
- [i18]Max Hunter Gordon, Marco Cerezo, Lukasz Cincio, Patrick J. Coles:
Covariance matrix preparation for quantum principal component analysis. CoRR abs/2204.03495 (2022) - [i17]Matthias C. Caro, Hsin-Yuan Huang, Nicholas Ezzell, Joe Gibbs, Andrew T. Sornborger, Lukasz Cincio, Patrick J. Coles, Zoë Holmes:
Out-of-distribution generalization for learning quantum dynamics. CoRR abs/2204.10268 (2022) - [i16]Joe Gibbs, Zoë Holmes, Matthias C. Caro, Nicholas Ezzell, Hsin-Yuan Huang, Lukasz Cincio, Andrew T. Sornborger, Patrick J. Coles:
Dynamical simulation via quantum machine learning with provable generalization. CoRR abs/2204.10269 (2022) - [i15]Andi Gu, Lukasz Cincio, Patrick J. Coles:
Practical Black Box Hamiltonian Learning. CoRR abs/2206.15464 (2022) - [i14]Charles Moussa, Max Hunter Gordon, Michal Baczyk, Marco Cerezo, Lukasz Cincio, Patrick J. Coles:
Resource frugal optimizer for quantum machine learning. CoRR abs/2211.04965 (2022) - 2021
- [i13]Joe Gibbs, Kaitlin Gili, Zoë Holmes, Benjamin Commeau, Andrew Arrasmith, Lukasz Cincio, Patrick J. Coles, Andrew T. Sornborger:
Long-time simulations with high fidelity on quantum hardware. CoRR abs/2102.04313 (2021) - [i12]Xiaoyuan Liu, Anthony Angone, Ruslan Shaydulin, Ilya Safro, Yuri Alexeev, Lukasz Cincio:
Layer VQE: A Variational Approach for Combinatorial Optimization on Noisy Quantum Computers. CoRR abs/2102.05566 (2021) - [i11]M. Bilkis, Marco Cerezo, Guillaume Verdon, Patrick J. Coles, Lukasz Cincio:
A semi-agnostic ansatz with variable structure for quantum machine learning. CoRR abs/2103.06712 (2021) - [i10]Samson Wang, Piotr Czarnik, Andrew Arrasmith, Marco Cerezo, Lukasz Cincio, Patrick J. Coles:
Can Error Mitigation Improve Trainability of Noisy Variational Quantum Algorithms? CoRR abs/2109.01051 (2021) - [i9]Matthias C. Caro, Hsin-Yuan Huang, Marco Cerezo, Kunal Sharma, Andrew T. Sornborger, Lukasz Cincio, Patrick J. Coles:
Generalization in quantum machine learning from few training data. CoRR abs/2111.05292 (2021) - 2020
- [i8]Marco Cerezo, Akira Sone, Tyler Volkoff, Lukasz Cincio, Patrick J. Coles:
Cost-Function-Dependent Barren Plateaus in Shallow Quantum Neural Networks. CoRR abs/2001.00550 (2020) - [i7]Kunal Sharma, Marco Cerezo, Lukasz Cincio, Patrick J. Coles:
Trainability of Dissipative Perceptron-Based Quantum Neural Networks. CoRR abs/2005.12458 (2020) - [i6]Kunal Sharma, Marco Cerezo, Zoë Holmes, Lukasz Cincio, Andrew T. Sornborger, Patrick J. Coles:
Reformulation of the No-Free-Lunch Theorem for Entangled Data Sets. CoRR abs/2007.04900 (2020) - [i5]Samson Wang, Enrico Fontana, Marco Cerezo, Kunal Sharma, Akira Sone, Lukasz Cincio, Patrick J. Coles:
Noise-Induced Barren Plateaus in Variational Quantum Algorithms. CoRR abs/2007.14384 (2020) - [i4]Andrew Arrasmith, Marco Cerezo, Piotr Czarnik, Lukasz Cincio, Patrick J. Coles:
Effect of barren plateaus on gradient-free optimization. CoRR abs/2011.12245 (2020) - [i3]Marco Cerezo, Andrew Arrasmith, Ryan Babbush, Simon C. Benjamin, Suguru Endo, Keisuke Fujii, Jarrod R. McClean, Kosuke Mitarai, Xiao Yuan, Lukasz Cincio, Patrick J. Coles:
Variational Quantum Algorithms. CoRR abs/2012.09265 (2020) - 2019
- [i2]Sami Khairy, Ruslan Shaydulin, Lukasz Cincio, Yuri Alexeev, Prasanna Balaprakash:
Reinforcement-Learning-Based Variational Quantum Circuits Optimization for Combinatorial Problems. CoRR abs/1911.04574 (2019) - [i1]Sami Khairy, Ruslan Shaydulin, Lukasz Cincio, Yuri Alexeev, Prasanna Balaprakash:
Learning to Optimize Variational Quantum Circuits to Solve Combinatorial Problems. CoRR abs/1911.11071 (2019)
Coauthor Index
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