GroverGPT: A Large Language Model with 8 Billion Parameters for Quantum Searching

Shor, P. Algorithms for quantum computation: discrete logarithms and factoring. Proceedings 35th Annual Symposium On Foundations Of Computer Science

1994

Earlier work this paper cites.

Grover, L. A fast quantum mechanical algorithm for database search. Proceedings Of The Twenty-eighth Annual ACM Symposium On Theory Of Computing

1996

Earlier work this paper cites.

G. Vidal, “Efficient classical simulation of slightly entangled quantum computations,” Physical Review Letters

2003

Earlier work this paper cites.

M. A. Nielsen and I. L. Chuang, Quantum Computation and Quantum Information

2010

Earlier work this paper cites.

Grassl, M., Langenberg, B., Roetteler, M. & Steinwandt, R. Applying Grover’s algorithm to AES: quantum resource estimates. International Workshop On Post-Quantum Cryptography

2016

Earlier work this paper cites.

Biamonte, J., Wittek, P., Pancotti, N., Rebentrost, P., Wiebe, N. & Lloyd, S. Quantum machine learning. Nature

2017

Earlier work this paper cites.

Cross, A., Bishop, L., Smolin, J. & Gambetta, J. Open quantum assembly language. ArXiv Preprint ArXiv:1707.03429

Original

2017

Earlier work this paper cites.

Chakrabarty, I., Khan, S., & Singh, V. Dynamic Grover search: Applications in recommendation systems and optimization problems. Quantum Information Processing

2017

Earlier work this paper cites.

J. Preskill, “Quantum computing in the NISQ era and beyond,” Quantum

2018

Earlier work this paper cites.

Mavroeidis, V., Vishi, K., Zych, M. & Jøsang, A. The impact of quantum computing on present cryptography. ArXiv Preprint ArXiv:1804.00200

Original

2018

Earlier work this paper cites.

F. Arute, K. Arya, R. Babbush, D. Bacon, J. C. Bardin, R. Barends, R. Biswas, S. Boixo, F. G. S. L. Brandao, D. A. Buell, et al

2019

Earlier work this paper cites.

Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A. & Others Language models are few-shot learners. Advances In Neural Information Processing Systems

2020

Cited alongside, same era.

Ajagekar, A. & You, F. Quantum computing assisted deep learning for fault detection and diagnosis in industrial process systems. Computers & Chemical Engineering

2020

Cited alongside, same era.

Ajagekar, A. & You, F. Quantum computing based hybrid deep learning for fault diagnosis in electrical power systems. Applied Energy

2021

Cited alongside, same era.

F. Pan, K. Chen, and P. Zhang, “Solving the sampling problem of the Sycamore quantum circuits,” Physical Review Letters

2022

Cited alongside, same era.

Cross, A., Javadi-Abhari, A., Alexander, T., De Beaudrap, N., Bishop, L., Heidel, S., Ryan, C., Sivarajah, P., Smolin, J., Gambetta, J. & Others OpenQASM 3: A broader and deeper quantum assembly language. ACM Transactions On Quantum Computing

Dubey, A., Jauhri, A., Pandey, A., Kadian, A., Al-Dahle, A., Letman, A., Mathur, A., Schelten, A., Yang, A., Fan, A. & Others The llama 3 herd of models. ArXiv Preprint ArXiv:2407.21783

Original

2024

Closest in time.

Vavekanand, R. & Sam, K. Llama 3.1: An in-depth analysis of the next-generation large language model. (ResearchGate,2024)

2024

Closest in time.

Yang, Rui, Gu, Yuntian, Wang, Ziruo, Liang, Yitao, and Li, Tongyang. "QCircuitNet: A Large-Scale Hierarchical Dataset for Quantum Algorithm Design." arXiv preprint arXiv:2410.07961

Original

2024

Closest in time.

Yao, Jian, and You, Yi-Zhuang. "ShadowGPT: Learning to Solve Quantum Many-Body Problems from Randomized Measurements." arXiv preprint arXiv:2411.03285

Original

2024

Closest in time.

Fitzek, David, Teoh, Yi Hong, Fung, Hin Pok, Dagnew, Gebremedhin A., Merali, Ejaaz, Moss, M. Schuyler, MacLellan, Benjamin, and Melko, Roger G. "RydbergGPT." arXiv preprint arXiv:2405.21052