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Artificial Intelligence (AI) can solve complex scientific problems beyond human capabilities, but the resulting solutions offer little insight into the underlying physical principles.
Bell’s theorem without inequalities
Greenberger, D. M., Horne, M. A., Shimony, A., and Zeilinger, A · 1990
Earlier work this paper cites.
Experimental test of quantum nonlocality in three-photon greenberger–horne–zeilinger entanglement
Pan, J.-W., Bouwmeester, D., Daniell, M., Weinfurter, H., and Zeilinger, A · 2000
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Entanglement in the majumdar-ghosh model
Chhajlany, R. W., Tomczak, P., Wójcik, A., and Richter, J · 2007
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Photonic quantum simulators
Aspuru-Guzik, A. and Walther, P · 2012
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Quantum imaging with undetected photons
Lemos, G. B., Borish, V., Cole, G. D., Ramelow, S., Lapkiewicz, R., and Zeilinger, A · 2014
Earlier work this paper cites.
A search algorithm for quantum state engineering and metrology
Knott, P · 2016
Earlier work this paper cites.
Automated search for new quantum experiments
Krenn, M., Malik, M., Fickler, R., Lapkiewicz, R., and Zeilinger, A · 2016
Earlier work this paper cites.
Probing many-body dynamics on a 51-atom quantum simulator
Bernien, H., Schwartz, S., Keesling, A., Levine, H., Omran, A., Pichler, H., Choi, S., Zibrov, A. S., Endres, M., Greiner, M., et al · 2017
Earlier work this paper cites.
Understanding scientific understanding
De Regt, H. W · 2017
Earlier work this paper cites.
Convolutional sequence to sequence learning
Gehring, J., Auli, M., Grangier, D., Yarats, D., and Dauphin, Y. N · 2017
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Attention is all you need
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, Ł., and Polosukhin, I · 2017
Earlier work this paper cites.
Photonic quantum information processing: a review
Flamini, F., Spagnolo, N., and Sciarrino, F · 2018
Earlier work this paper cites.
Inverse design in nanophotonics
Molesky, S., Lin, Z., Piggott, A. Y., Jin, W., Vucković, J., and Rodriguez, A. W · 2018
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Quantum metrology with nonclassical states of atomic ensembles
Pezzè, L., Smerzi, A., Oberthaler, M. K., Schmied, R., and Treutlein, P · 2018
Earlier work this paper cites.
Deep learning for symbolic mathematics
Lample, G. and Charton, F · 2019
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Imaging with quantum states of light
Moreau, P.-A., Toninelli, E., Gregory, T., and Padgett, M. J · 2019
Earlier work this paper cites.
Designing quantum experiments with a genetic algorithm
Nichols, R., Mineh, L., Rubio, J., Matthews, J. C., and Knott, P. A · 2019
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Language models are few-shot learners
Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J. D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., Agarwal, S., Herbert-Voss, A., Krueger, G., Henighan, T., Child, R., Ramesh, A., Ziegler, D. M., Wu, J., Winter, C., Hesse, C., Chen, M., Sigler, E., Litwin, M., Gray, S., Chess, B., Clark, J., Berner, C., McCandlish, S., Radford, A., Sutskever, I., and Amodei, D · 2020
Earlier work this paper cites.
Computer-inspired quantum experiments
Krenn, M., Erhard, M., and Zeilinger, A · 2020
Earlier work this paper cites.
Microscopy with undetected photons in the mid-infrared
Kviatkovsky, I., Chrzanowski, H. M., Avery, E. G., Bartolomaeus, H., and Ramelow, S · 2020
Earlier work this paper cites.
Photonic quantum metrology
Polino, E., Valeri, M., Spagnolo, N., and Sciarrino, F · 2020
Earlier work this paper cites.
Accelerating recurrent ising machines in photonic integrated circuits
Prabhu, M., Roques-Carmes, C., Shen, Y., Harris, N., Jing, L., Carolan, J., Hamerly, R., Baehr-Jones, T., Hochberg, M., Čeperić, V., et al · 2020
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On-chip integrated laser-driven particle accelerator
Sapra, N. V., Yang, K. Y., Vercruysse, D., Leedle, K. J., Black, D. S., England, R. J., Su, L., Trivedi, R., Miao, Y., Solgaard, O., Byer, R. L., and Vučković, J · 2020
Cited alongside, same era.
Machine learning for long-distance quantum communication
Wallnöfer, J., Melnikov, A. A., Dür, W., and Briegel, H. J · 2020
Cited alongside, same era.
On layer normalization in the transformer architecture
Xiong, R., Yang, Y., He, D., Zheng, K., Zheng, S., Xing, C., Zhang, H., Lan, Y., Wang, L., and Liu, T · 2020
Cited alongside, same era.
Toward machine learning optimization of experimental design
Baydin, A. G., Cranmer, K., de Castro Manzano, P., Delaere, C., Derkach, D., Donini, J., Dorigo, T., Giammanco, A., Kieseler, J., Layer, L., Louppe, G., Ratnikov, F., Strong, G., Tosi, M., Ustyuzhanin, A., Vischia, P., and Yarar, H · 2021
Cited alongside, same era.
Linear algebra with transformers
Charton, F · 2021
Cited alongside, same era.
Starcoder: may the source be with you!
Li, R., Ben Allal, L., Zi, Y., Muennighoff, N., Kocetkov, D., Mou, C., Marone, M., Akiki, C., Li, J., Chim, J., Liu, Q., Zheltonozhskii, E., Zhuo, T. Y., Wang, T., Dehaene, O., Davaadorj, M., Lamy-Poirier, J., Monteiro, J., Shliazhko, O., Gontier, N., Meade, N., Zebaze, A., Yee, M.-H., Umapathi, L. K., Zhu, J., Lipkin, B., Oblokulov, M., Wang, Z., Murthy, R., Stillerman, J., Patel, S. S., Abulkhanov, D., Zocca, M., Dey, M., Zhang, Z., Fahmy, N., Bhattacharyya, U., Yu, W., Singh, S., Luccioni, S., Villegas, P., Kunakov, M., Zhdanov, F., Romero, M., Lee, T., Timor, N., Ding, J., Schlesinger, C., Schoelkopf, H., Ebert, J., Dao, T., Mishra, M., Gu, A., Robinson, J., Anderson, C. J., Dolan-Gavitt, B., Contractor, D., Reddy, S., Fried, D., Bahdanau, D., Jernite, Y., Ferrandis, C. M., Hughes, S., Wolf, T., Guha, A., von Werra, L., and de Vries, H · 2023
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Optimizing zx-diagrams with deep reinforcement learning
Nägele, M. and Marquardt, F · 2023
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Xlumina: An auto-differentiating discovery framework for super-resolution microscopy
Rodríguez, C., Arlt, S., Möckl, L., and Krenn, M · 2023
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Digital discovery of 100 diverse quantum experiments with pytheus
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Chen, M., Tworek, J., Jun, H., Yuan, Q., Pinto, H. P. d. O., Kaplan, J., Edwards, H., Burda, Y., Joseph, N., Brockman, G., Ray, A., Puri, R., Krueger, G., Petrov, M., Khlaaf, H., Sastry, G., Mishkin, P., Chan, B., Gray, S., Ryder, N., Pavlov, M., Power, A., Kaiser, L., Bavarian, M., Winter, C., Tillet, P., Petroski Such, F., Cummings, D., Plappert, M., Chantzis, F., Barnes, E., Herbert-Voss, A., Guss, W. H., Nichol, A., Paino, A., Tezak, N., Tang, J., Babuschkin, I., Balaji, S., Jain, S., Saunders, W., Hesse, C., Carr, A. N., Leike, J., Achiam, J., Misra, V., Morikawa, E., Radford, A., Knight, M., Brundage, M., Murati, M., Mayer, K., Welinder, P., McGrew, B., Amodei, D., McCandlish, S., Sutskever, I., and Zaremba, W · 2021
Cited alongside, same era.
Conceptual understanding through efficient automated design of quantum optical experiments
Krenn, M., Kottmann, J. S., Tischler, N., and Aspuru-Guzik, A · 2021
Cited alongside, same era.
Deep learning for the design of photonic structures
Ma, W., Liu, Z., Kudyshev, Z. A., Boltasseva, A., Cai, W., and Liu, Y · 2021
Cited alongside, same era.
Reinforcement learning for optimization of variational quantum circuit architectures
Ostaszewski, M., Trenkwalder, L. M., Masarczyk, W., Scerri, E., and Dunjko, V · 2021
Cited alongside, same era.
Data-driven strategies for accelerated materials design
Pollice, R., dos Passos Gomes, G., Aldeghi, M., Hickman, R. J., Krenn, M., Lavigne, C., Lindner-D’Addario, M., Nigam, A., Ser, C. T., Yao, Z., and Aspuru-Guzik, A · 2021
Cited alongside, same era.
Chen, W., Ma, X., Wang, X., and Cohen, W. W · 2022
Cited alongside, same era.
End-to-end symbolic regression with transformers
Kamienny, P.-a., d'Ascoli, S., Lample, G., and Charton, F · 2022
Cited alongside, same era.
Ruiz-Gonzalez, C., Arlt, S., Petermann, J., Sayyad, S., Jaouni, T., Karimi, E., Tischler, N., Gu, X., and Krenn, M · 2023
Later among the works it cites.
Codegeex: A pre-trained model for code generation with multilingual evaluations on humaneval-x
Zheng, Q., Xia, X., Zou, X., Dong, Y., Wang, S., Xue, Y., Wang, Z., Shen, L., Wang, A., Li, Y., Su, T., Yang, Z., and Tang, J · 2023
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Towards a benchmark for scientific understanding in humans and machines
Barman, K. G., Caron, S., Claassen, T., and De Regt, H · 2024
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Cai, T., Merz, G. W., Charton, F., Nolte, N., Wilhelm, M., Cranmer, K., and Dixon, L. J · 2024
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Quantum computation and quantum simulation with ultracold molecules
Cornish, S. L., Tarbutt, M. R., and Hazzard, K. R. A · 2024
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Quantum sensing and metrology for fundamental physics with molecules
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Gemma: Open models based on gemini research and technology
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Inverse design of high-dimensional quantum optical circuits in a complex medium
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Automated discovery of coupled mode setups
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Starcoder 2 and the stack v2: The next generation
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End-to-end variational quantum sensing
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Language models for quantum simulation
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Opening the ai black box: program synthesis via mechanistic interpretability
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Mathematical discoveries from program search with large language models
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Solving olympiad geometry without human demonstrations
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