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11,008 results on '"Lamm AT"'

1. Justice-Centered Mapping Tools for Selecting Electric Vehicle Charger Locations

Author

Alex, Ken, Lamm, Ted, and Kammen, Daniel M.

Abstract

Reducing air pollution from automobiles is a climate and public health imperative. Transportation is the “single largest source of CO2 emissions” in California and the second largest source nationwide. State leaders recognize the need for zero-emission vehicles to achieve statewide carbon neutrality. Millions of electric vehicles (EVs) are expected on American roads in the coming decade. California alone will require over two million publicly accessible EV chargers to support over 15 million EVs by 2035, and nationwide over 28 million total chargers will be needed by 2030. To date, public charging infrastructure investment has not prioritized lower-income and black and brown communities, and electrification has mostly benefitted higher-income, whiter communities. Federal and state funding programs for charging infrastructure have begun directing vehicle and charging investment to lower-income communities, rural communities, and areas at greatest risk of environmental harm, but this investment must be met with equity-oriented decision-making tools.

Published
2024

2. Qudit Gate Decomposition Dependence for Lattice Gauge Theories

Author

Kürkçüoglu, Doga Murat, Lamm, Henry, and Maestri, Andrea

Subjects
Quantum Physics, High Energy Physics - Lattice
Abstract

In this work, we investigate the effect of decomposition basis on primitive qudit gates on superconducting radio-frequency cavity-based quantum computers with applications to lattice gauge theory. Three approaches are tested: SNAP & Displacement gates, ECD & single-qubit rotations $R(\theta,\phi)$, and optimal pulse control. For all three decompositions, implementing the necessary sequence of rotations concurrently rather then sequentially can reduce the primitive gate run time. The number of blocks required for the faster ECD & $R_p(\theta)$ is found to scale $\mathcal{O}(d^2)$, while slower SNAP & Displacement set scales at worst $\mathcal{O}(d)$. For qudits with $d<10$, the resulting gate times for the decompositions is similar, but strongly-dependent on experimental design choices. Optimal control can outperforms both decompositions for small $d$ by a factor of 2-12 at the cost of higher classical resources. Lastly, we find that SNAP & Displacement are slightly more robust to a simplified noise model., Comment: 13 pages, 17 figures

Published
2024

3. The enumeration of doubly symmetric diagrams for strongly positive amphicheiral knots

Author

Lamm, Christoph

Subjects
Mathematics - Geometric Topology
Abstract

This is the second part of the article on doubly symmetric diagrams and strongly positive amphicheiral knots. We develop an enumeration strategy for prime knots given by doubly symmetric diagrams and determine all cases up to 18 crossings in the doubly symmetric diagram. A digression covers the origin of Gauss words for long curves and explains how Gauss marked non-realizable words., Comment: 22 pages, 27 figures; comments are welcome

Published
2024

4. Signal processing and spectral modeling for the BeEST experiment

Author

Kim, Inwook, Bray, Connor, Marino, Andrew, Stone-Whitehead, Caitlyn, Lamm, Amii, Abells, Ryan, Amaro, Pedro, Andoche, Adrien, Cantor, Robin, Diercks, David, Fretwell, Spencer, Gillespie, Abigail, Guerra, Mauro, Hall, Ad, Harris, Cameron N., Harris, Jackson T., Hinkle, Calvin, Hayen, Leendert M., Hervieux, Paul-Antoine, Kim, Geon-Bo, Leach, Kyle G., Lennarz, Annika, Lordi, Vincenzo, Machado, Jorge, McKeen, David, Mougeot, Xavier, Ponce, Francisco, Ruiz, Chris, Samanta, Amit, Santos, José Paulo, Smolsky, Joseph, Taylor, John, Templet, Joseph, Upadhyayula, Sriteja, Wagner, Louis, Warburton, William K., Waters, Benjamin, and Friedrich, Stephan

Subjects
Physics - Instrumentation and Detectors, High Energy Physics - Experiment
Abstract

The Beryllium Electron capture in Superconducting Tunnel junctions (BeEST) experiment searches for evidence of heavy neutrino mass eigenstates in the nuclear electron capture decay of $^7$Be by precisely measuring the recoil energy of the $^7$Li daughter. In Phase-III, the BeEST experiment has been scaled from a single superconducting tunnel junction (STJ) sensor to a 36-pixel array to increase sensitivity and mitigate gamma-induced backgrounds. Phase-III also uses a new continuous data acquisition system that greatly increases the flexibility for signal processing and data cleaning. We have developed procedures for signal processing and spectral fitting that are sufficiently robust to be automated for large data sets. This article presents the optimized procedures before unblinding the majority of the Phase-III data set to search for physics beyond the standard model.

Published
2024

5. Can Visual Language Models Replace OCR-Based Visual Question Answering Pipelines in Production? A Case Study in Retail

Author

Lamm, Bianca and Keuper, Janis

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Most production-level deployments for Visual Question Answering (VQA) tasks are still build as processing pipelines of independent steps including image pre-processing, object- and text detection, Optical Character Recognition (OCR) and (mostly supervised) object classification. However, the recent advances in vision Foundation Models [25] and Vision Language Models (VLMs) [23] raise the question if these custom trained, multi-step approaches can be replaced with pre-trained, single-step VLMs. This paper analyzes the performance and limits of various VLMs in the context of VQA and OCR [5, 9, 12] tasks in a production-level scenario. Using data from the Retail-786k [10] dataset, we investigate the capabilities of pre-trained VLMs to answer detailed questions about advertised products in images. Our study includes two commercial models, GPT-4V [16] and GPT-4o [17], as well as four open-source models: InternVL [5], LLaVA 1.5 [12], LLaVA-NeXT [13], and CogAgent [9]. Our initial results show, that there is in general no big performance gap between open-source and commercial models. However, we observe a strong task dependent variance in VLM performance: while most models are able to answer questions regarding the product brand and price with high accuracy, they completely fail at the same time to correctly identity the specific product name or discount. This indicates the problem of VLMs to solve fine-grained classification tasks as well to model the more abstract concept of discounts.

Published
2024

6. Surrogate Constructed Scalable Circuits ADAPT-VQE in the Schwinger model

Author

Gustafson, Erik, Sherbert, Kyle, Florio, Adrien, Shirali, Karunya, Chen, Yanzhu, Lamm, Henry, Valgushev, Semeon, Weichselbaum, Andreas, Economou, Sophia E., Pisarski, Robert D., and Tubman, Norm M.

Subjects
Quantum Physics, High Energy Physics - Lattice
Abstract

Inspired by recent advancements of simulating periodic systems on quantum computers, we develop a new approach, (SC)$^2$-ADAPT-VQE, to further advance the simulation of these systems. Our approach extends the scalable circuits ADAPT-VQE framework, which builds an ansatz from a pool of coordinate-invariant operators defined for arbitrarily large, though not arbitrarily small, volumes. Our method uses a classically tractable ``Surrogate Constructed'' method to remove irrelevant operators from the pool, reducing the minimum size for which the scalable circuits are defined. Bringing together the scalable circuits and the surrogate constructed approaches forms the core of the (SC)$^2$ methodology. Our approach allows for a wider set of classical computations, on small volumes, which can be used for a more robust extrapolation protocol. While developed in the context of lattice models, the surrogate construction portion is applicable to a wide variety of problems where information about the relative importance of operators in the pool is available. As an example, we use it to compute properties of the Schwinger model - quantum electrodynamics for a single, massive fermion in $1+1$ dimensions - and show that our method can be used to accurately extrapolate to the continuum limit., Comment: 9 pages, 6 figures

Published
2024

7. Highly-efficient quantum Fourier transformations for some nonabelian groups

Author

Murairi, Edison M., Alam, M. Sohaib, Lamm, Henry, Hadfield, Stuart, and Gustafson, Erik

Subjects
Quantum Physics, High Energy Physics - Lattice
Abstract

Quantum Fourier transformations are an essential component of many quantum algorithms, from prime factoring to quantum simulation. While the standard abelian QFT is well-studied, important variants corresponding to \emph{nonabelian} groups of interest have seen less development. In particular, fast nonabelian Fourier transformations are important components for both quantum simulations of field theories as well as approaches to the nonabelian hidden subgroup problem. In this work, we present fast quantum Fourier transformations for a number of nonabelian groups of interest for high energy physics, $\mathbb{BT}$, $\mathbb{BO}$, $\Delta(27)$, $\Delta(54)$, and $\Sigma(36\times3)$. For each group, we derive explicit quantum circuits and estimate resource scaling for fault-tolerant implementations. Our work shows that the development of a fast Fourier transformation can substantively reduce simulation costs by up to three orders of magnitude for the finite groups that we have investigated., Comment: 14 pages, 12 figures, 8 tables; minor typographical corrections

Published
2024

8. Block Encodings of Discrete Subgroups on Quantum Computer

Author

Lamm, Henry, Li, Ying-Ying, Shu, Jing, Wang, Yi-Lin, and Xu, Bin

Subjects
High Energy Physics - Lattice, Quantum Physics
Abstract

We introduce a block encoding method for mapping discrete subgroups to qubits on a quantum computer. This method is applicable to general discrete groups, including crystal-like subgroups such as $\mathbb{BI}$ of $SU(2)$ and $\mathbb{V}$ of $SU(3)$. We detail the construction of primitive gates -- the inversion gate, the group multiplication gate, the trace gate, and the group Fourier gate -- utilizing this encoding method for $\mathbb{BT}$ and for the first time $\mathbb{BI}$ group. We also provide resource estimations to extract the gluon viscosity. The inversion gates for $\mathbb{BT}$ and $\mathbb{BI}$ are benchmarked on the $\texttt{Baiwang}$ quantum computer with estimated fidelities of $40^{+5}_{-4}\%$ and $4^{+5}_{-3}\%$ respectively., Comment: 12 pages, 10 figures

Published
2024

9. Digitization and subduction of $SU(N)$ gauge theories

Author

Assi, Benoît and Lamm, Henry

Subjects
High Energy Physics - Lattice, Quantum Physics
Abstract

The simulation of lattice gauge theories on quantum computers necessitates digitizing gauge fields. One approach involves substituting the continuous gauge group with a discrete subgroup, but the implications of this approximation still need to be clarified. To gain insights, we investigate the subduction of $ SU(2) $ and $ SU(3)$ to discrete crystal-like subgroups. Using classical lattice calculations, we show that subduction offers valuable information based on subduced direct sums, helping us identify additional terms to incorporate into the lattice action that can mitigate the effects of digitization. Furthermore, we compute the static potentials of all irreducible representations of $ \Sigma(360 \times 3) $ at a fixed lattice spacing. Our results reveal a percent-level agreement with the Casimir scaling of ( SU(3) ) for irreducible representations that subduce to a single $ \Sigma(360 \times 3) $ irreducible representation. This provides a diagnostic measure of approximation quality, as some irreducible representations closely match the expected results while others exhibit significant deviations., Comment: 14 pages, 3 figures, additional references

Published
2024

10. Primitive Quantum Gates for an SU(3) Discrete Subgroup: $\Sigma(36\times3)$

Author

Gustafson, Erik J., Ji, Yao, Lamm, Henry, Murairi, Edison M., Perez, Sebastian Osorio, and Zhu, Shuchen

Subjects
High Energy Physics - Lattice, Quantum Physics
Abstract

We construct the primitive gate set for the digital quantum simulation of the 108-element $\Sigma(36\times3)$ group. This is the first time a nonabelian crystal-like subgroup of $SU(3)$ has been constructed for quantum simulation. The gauge link registers and necessary primitives -- the inversion gate, the group multiplication gate, the trace gate, and the $\Sigma(36\times3)$ Fourier transform -- are presented for both an eight-qubit encoding and a heterogeneous three-qutrit plus two-qubit register. For the latter, a specialized compiler was developed for decomposing arbitrary unitaries onto this architecture., Comment: 15 pages, 11 Figures, 6 Tables

Published
2024
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11. Direct Experimental Constraints on the Spatial Extent of a Neutrino Wavepacket

Author

Smolsky, Joseph, Leach, Kyle G, Abells, Ryan, Amaro, Pedro, Andoche, Adrien, Borbridge, Keith, Bray, Connor, Cantor, Robin, Diercks, David, Fretwell, Spencer, Friedrich, Stephan, Gillespie, Abigail, Guerra, Mauro, Hall, Ad, Harris, Cameron N, Harris, Jackson T, Hinkle, Calvin, Lamm, Amii, Hayen, Leendert M, Hervieux, Paul-Antoine, Kim, Geon-Bo, Kim, Inwook, Lennarz, Annika, Lordi, Vincenzo, Machado, Jorge, Marino, Andrew, McKeen, David, Mougeot, Xavier, Ponce, Francisco, Ruiz, Chris, Samanta, Amit, Santos, José Paulo, Stone-Whitehead, Caitlyn, Taylor, John, Templet, Joseph, Upadhyayula, Sriteja, Wagner, Louis, and Warburton, William K

Subjects
Nuclear Experiment, High Energy Physics - Experiment, Quantum Physics
Abstract

Despite their high relative abundance in our Universe, neutrinos are the least understood fundamental particles of nature. They also provide a unique system to study quantum coherence and the wavelike nature of particles in fundamental systems due to their extremely weak interaction probabilities. In fact, the quantum properties of neutrinos emitted in experimentally relevant sources are virtually unknown and the spatial extent of the neutrino wavepacket is only loosely constrained by reactor neutrino oscillation data with a spread of 13 orders of magnitude. Here, we present the first direct limits of this quantity through a new experimental concept to extract the energy width, $\sigma_{\textrm{N},E}$, of the recoil daughter nucleus emitted in the nuclear electron capture (EC) decay of $^7$Be. The final state in the EC decay process contains a recoiling $^7$Li nucleus and an electron neutrino ($\nu_e$) which are entangled at their creation. The $^7$Li energy spectrum is measured to high precision by directly embedding $^7$Be radioisotopes into a high resolution superconducting tunnel junction that is operated as a cryogenic sensor. The lower limit on the spatial uncertainty of the recoil daughter was found to be $\sigma_{\textrm{N}, x} \geq 6.2$\,pm, which implies the final-state system is localized at a scale more than a thousand times larger than the nucleus itself. From this measurement, the first direct lower limits on the spatial extent of the neutrino wavepacket were extracted using two different theoretical methods. These results have wide-reaching implications in several areas including the nature of spatial localization at sub-atomic scales, interpretation of neutrino physics data, and the potential reach of future large-scale experiments., Comment: 20 pages, 3 figures, v3 corrects and updates one of the wavepacket width calculations

Published
2024

12. Are Vision Language Models Texture or Shape Biased and Can We Steer Them?

Author

Gavrikov, Paul, Lukasik, Jovita, Jung, Steffen, Geirhos, Robert, Lamm, Bianca, Mirza, Muhammad Jehanzeb, Keuper, Margret, and Keuper, Janis

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, Quantitative Biology - Neurons and Cognition
Abstract

Vision language models (VLMs) have drastically changed the computer vision model landscape in only a few years, opening an exciting array of new applications from zero-shot image classification, over to image captioning, and visual question answering. Unlike pure vision models, they offer an intuitive way to access visual content through language prompting. The wide applicability of such models encourages us to ask whether they also align with human vision - specifically, how far they adopt human-induced visual biases through multimodal fusion, or whether they simply inherit biases from pure vision models. One important visual bias is the texture vs. shape bias, or the dominance of local over global information. In this paper, we study this bias in a wide range of popular VLMs. Interestingly, we find that VLMs are often more shape-biased than their vision encoders, indicating that visual biases are modulated to some extent through text in multimodal models. If text does indeed influence visual biases, this suggests that we may be able to steer visual biases not just through visual input but also through language: a hypothesis that we confirm through extensive experiments. For instance, we are able to steer shape bias from as low as 49% to as high as 72% through prompting alone. For now, the strong human bias towards shape (96%) remains out of reach for all tested VLMs.

Published
2024

13. Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Author

Gemini Team, Georgiev, Petko, Lei, Ving Ian, Burnell, Ryan, Bai, Libin, Gulati, Anmol, Tanzer, Garrett, Vincent, Damien, Pan, Zhufeng, Wang, Shibo, Mariooryad, Soroosh, Ding, Yifan, Geng, Xinyang, Alcober, Fred, Frostig, Roy, Omernick, Mark, Walker, Lexi, Paduraru, Cosmin, Sorokin, Christina, Tacchetti, Andrea, Gaffney, Colin, Daruki, Samira, Sercinoglu, Olcan, Gleicher, Zach, Love, Juliette, Voigtlaender, Paul, Jain, Rohan, Surita, Gabriela, Mohamed, Kareem, Blevins, Rory, Ahn, Junwhan, Zhu, Tao, Kawintiranon, Kornraphop, Firat, Orhan, Gu, Yiming, Zhang, Yujing, Rahtz, Matthew, Faruqui, Manaal, Clay, Natalie, Gilmer, Justin, Co-Reyes, JD, Penchev, Ivo, Zhu, Rui, Morioka, Nobuyuki, Hui, Kevin, Haridasan, Krishna, Campos, Victor, Mahdieh, Mahdis, Guo, Mandy, Hassan, Samer, Kilgour, Kevin, Vezer, Arpi, Cheng, Heng-Tze, de Liedekerke, Raoul, Goyal, Siddharth, Barham, Paul, Strouse, DJ, Noury, Seb, Adler, Jonas, Sundararajan, Mukund, Vikram, Sharad, Lepikhin, Dmitry, Paganini, Michela, Garcia, Xavier, Yang, Fan, Valter, Dasha, Trebacz, Maja, Vodrahalli, Kiran, Asawaroengchai, Chulayuth, Ring, Roman, Kalb, Norbert, Soares, Livio Baldini, Brahma, Siddhartha, Steiner, David, Yu, Tianhe, Mentzer, Fabian, He, Antoine, Gonzalez, Lucas, Xu, Bibo, Kaufman, Raphael Lopez, Shafey, Laurent El, Oh, Junhyuk, Hennigan, Tom, Driessche, George van den, Odoom, Seth, Lucic, Mario, Roelofs, Becca, Lall, Sid, Marathe, Amit, Chan, Betty, Ontanon, Santiago, He, Luheng, Teplyashin, Denis, Lai, Jonathan, Crone, Phil, Damoc, Bogdan, Ho, Lewis, Riedel, Sebastian, Lenc, Karel, Yeh, Chih-Kuan, Chowdhery, Aakanksha, Xu, Yang, Kazemi, Mehran, Amid, Ehsan, Petrushkina, Anastasia, Swersky, Kevin, Khodaei, Ali, Chen, Gowoon, Larkin, Chris, Pinto, Mario, Yan, Geng, Badia, Adria Puigdomenech, Patil, Piyush, Hansen, Steven, Orr, Dave, Arnold, Sebastien M. R., Grimstad, Jordan, Dai, Andrew, Douglas, Sholto, Sinha, Rishika, Yadav, Vikas, Chen, Xi, Gribovskaya, Elena, Austin, Jacob, Zhao, Jeffrey, Patel, Kaushal, Komarek, Paul, Austin, Sophia, Borgeaud, Sebastian, Friso, Linda, Goyal, Abhimanyu, Caine, Ben, Cao, Kris, Chung, Da-Woon, Lamm, Matthew, Barth-Maron, Gabe, Kagohara, Thais, Olszewska, Kate, Chen, Mia, Shivakumar, Kaushik, Agarwal, Rishabh, Godhia, Harshal, Rajwar, Ravi, Snaider, Javier, Dotiwalla, Xerxes, Liu, Yuan, Barua, Aditya, Ungureanu, Victor, Zhang, Yuan, Batsaikhan, Bat-Orgil, Wirth, Mateo, Qin, James, Danihelka, Ivo, Doshi, Tulsee, Chadwick, Martin, Chen, Jilin, Jain, Sanil, Le, Quoc, Kar, Arjun, Gurumurthy, Madhu, Li, Cheng, Sang, Ruoxin, Liu, Fangyu, Lamprou, Lampros, Munoz, Rich, Lintz, Nathan, Mehta, Harsh, Howard, Heidi, Reynolds, Malcolm, Aroyo, Lora, Wang, Quan, Blanco, Lorenzo, Cassirer, Albin, Griffith, Jordan, Das, Dipanjan, Lee, Stephan, Sygnowski, Jakub, Fisher, Zach, Besley, James, Powell, Richard, Ahmed, Zafarali, Paulus, Dominik, Reitter, David, Borsos, Zalan, Joshi, Rishabh, Pope, Aedan, Hand, Steven, Selo, Vittorio, Jain, Vihan, Sethi, Nikhil, Goel, Megha, Makino, Takaki, May, Rhys, Yang, Zhen, Schalkwyk, Johan, Butterfield, Christina, Hauth, Anja, Goldin, Alex, Hawkins, Will, Senter, Evan, Brin, Sergey, Woodman, Oliver, Ritter, Marvin, Noland, Eric, Giang, Minh, Bolina, Vijay, Lee, Lisa, Blyth, Tim, Mackinnon, Ian, Reid, Machel, Sarvana, Obaid, Silver, David, Chen, Alexander, Wang, Lily, Maggiore, Loren, Chang, Oscar, Attaluri, Nithya, Thornton, Gregory, Chiu, Chung-Cheng, Bunyan, Oskar, Levine, Nir, Chung, Timothy, Eltyshev, Evgenii, Si, Xiance, Lillicrap, Timothy, Brady, Demetra, Aggarwal, Vaibhav, Wu, Boxi, Xu, Yuanzhong, McIlroy, Ross, Badola, Kartikeya, Sandhu, Paramjit, Moreira, Erica, Stokowiec, Wojciech, Hemsley, Ross, Li, Dong, Tudor, Alex, Shyam, Pranav, Rahimtoroghi, Elahe, Haykal, Salem, Sprechmann, Pablo, Zhou, Xiang, Mincu, Diana, Li, Yujia, Addanki, Ravi, Krishna, Kalpesh, Wu, Xiao, Frechette, Alexandre, Eyal, Matan, Dafoe, Allan, Lacey, Dave, Whang, Jay, Avrahami, Thi, Zhang, Ye, Taropa, Emanuel, Lin, Hanzhao, Toyama, Daniel, Rutherford, Eliza, Sano, Motoki, Choe, HyunJeong, Tomala, Alex, Safranek-Shrader, Chalence, Kassner, Nora, Pajarskas, Mantas, Harvey, Matt, Sechrist, Sean, Fortunato, Meire, Lyu, Christina, Elsayed, Gamaleldin, Kuang, Chenkai, Lottes, James, Chu, Eric, Jia, Chao, Chen, Chih-Wei, Humphreys, Peter, Baumli, Kate, Tao, Connie, Samuel, Rajkumar, Santos, Cicero Nogueira dos, Andreassen, Anders, Rakićević, Nemanja, Grewe, Dominik, Kumar, Aviral, Winkler, Stephanie, Caton, Jonathan, Brock, Andrew, Dalmia, Sid, Sheahan, Hannah, Barr, Iain, Miao, Yingjie, Natsev, Paul, Devlin, Jacob, Behbahani, Feryal, Prost, Flavien, Sun, Yanhua, Myaskovsky, Artiom, Pillai, Thanumalayan Sankaranarayana, Hurt, Dan, Lazaridou, Angeliki, Xiong, Xi, Zheng, Ce, Pardo, Fabio, Li, Xiaowei, Horgan, Dan, Stanton, Joe, Ambar, Moran, Xia, Fei, Lince, Alejandro, Wang, Mingqiu, Mustafa, Basil, Webson, Albert, Lee, Hyo, Anil, Rohan, Wicke, Martin, Dozat, Timothy, Sinha, Abhishek, Piqueras, Enrique, Dabir, Elahe, Upadhyay, Shyam, Boral, Anudhyan, Hendricks, Lisa Anne, Fry, Corey, Djolonga, Josip, Su, Yi, Walker, Jake, Labanowski, Jane, Huang, Ronny, Misra, Vedant, Chen, Jeremy, Skerry-Ryan, RJ, Singh, Avi, Rijhwani, Shruti, Yu, Dian, Castro-Ros, Alex, Changpinyo, Beer, Datta, Romina, Bagri, Sumit, Hrafnkelsson, Arnar Mar, Maggioni, Marcello, Zheng, Daniel, Sulsky, Yury, Hou, Shaobo, Paine, Tom Le, Yang, Antoine, Riesa, Jason, Rogozinska, Dominika, Marcus, Dror, Badawy, Dalia El, Zhang, Qiao, Wang, Luyu, Miller, Helen, Greer, Jeremy, Sjos, Lars Lowe, Nova, Azade, Zen, Heiga, Chaabouni, Rahma, Rosca, Mihaela, Jiang, Jiepu, Chen, Charlie, Liu, Ruibo, Sainath, Tara, Krikun, Maxim, Polozov, Alex, Lespiau, Jean-Baptiste, Newlan, Josh, Cankara, Zeyncep, Kwak, Soo, Xu, Yunhan, Chen, Phil, Coenen, Andy, Meyer, Clemens, Tsihlas, Katerina, Ma, Ada, Gottweis, Juraj, Xing, Jinwei, Gu, Chenjie, Miao, Jin, Frank, Christian, Cankara, Zeynep, Ganapathy, Sanjay, Dasgupta, Ishita, Hughes-Fitt, Steph, Chen, Heng, Reid, David, Rong, Keran, Fan, Hongmin, van Amersfoort, Joost, Zhuang, Vincent, Cohen, Aaron, Gu, Shixiang Shane, Mohananey, Anhad, Ilic, Anastasija, Tobin, Taylor, Wieting, John, Bortsova, Anna, Thacker, Phoebe, Wang, Emma, Caveness, Emily, Chiu, Justin, Sezener, Eren, Kaskasoli, Alex, Baker, Steven, Millican, Katie, Elhawaty, Mohamed, Aisopos, Kostas, Lebsack, Carl, Byrd, Nathan, Dai, Hanjun, Jia, Wenhao, Wiethoff, Matthew, Davoodi, Elnaz, Weston, Albert, Yagati, Lakshman, Ahuja, Arun, Gao, Isabel, Pundak, Golan, Zhang, Susan, Azzam, Michael, Sim, Khe Chai, Caelles, Sergi, Keeling, James, Sharma, Abhanshu, Swing, Andy, Li, YaGuang, Liu, Chenxi, Bostock, Carrie Grimes, Bansal, Yamini, Nado, Zachary, Anand, Ankesh, Lipschultz, Josh, Karmarkar, Abhijit, Proleev, Lev, Ittycheriah, Abe, Yeganeh, Soheil Hassas, Polovets, George, Faust, Aleksandra, Sun, Jiao, Rrustemi, Alban, Li, Pen, Shivanna, Rakesh, Liu, Jeremiah, Welty, Chris, Lebron, Federico, Baddepudi, Anirudh, Krause, Sebastian, Parisotto, Emilio, Soricut, Radu, Xu, Zheng, Bloxwich, Dawn, Johnson, Melvin, Neyshabur, Behnam, Mao-Jones, Justin, Wang, Renshen, Ramasesh, Vinay, Abbas, Zaheer, Guez, Arthur, Segal, Constant, Nguyen, Duc Dung, Svensson, James, Hou, Le, York, Sarah, Milan, Kieran, Bridgers, Sophie, Gworek, Wiktor, Tagliasacchi, Marco, Lee-Thorp, James, Chang, Michael, Guseynov, Alexey, Hartman, Ale Jakse, Kwong, Michael, Zhao, Ruizhe, Kashem, Sheleem, Cole, Elizabeth, Miech, Antoine, Tanburn, Richard, Phuong, Mary, Pavetic, Filip, Cevey, Sebastien, Comanescu, Ramona, Ives, Richard, Yang, Sherry, Du, Cosmo, Li, Bo, Zhang, Zizhao, Iinuma, Mariko, Hu, Clara Huiyi, Roy, Aurko, Bijwadia, Shaan, Zhu, Zhenkai, Martins, Danilo, Saputro, Rachel, Gergely, Anita, Zheng, Steven, Jia, Dawei, Antonoglou, Ioannis, Sadovsky, Adam, Gu, Shane, Bi, Yingying, Andreev, Alek, Samangooei, Sina, Khan, Mina, Kocisky, Tomas, Filos, Angelos, Kumar, Chintu, Bishop, Colton, Yu, Adams, Hodkinson, Sarah, Mittal, Sid, Shah, Premal, Moufarek, Alexandre, Cheng, Yong, Bloniarz, Adam, Lee, Jaehoon, Pejman, Pedram, Michel, Paul, Spencer, Stephen, Feinberg, Vladimir, Xiong, Xuehan, Savinov, Nikolay, Smith, Charlotte, Shakeri, Siamak, Tran, Dustin, Chesus, Mary, Bohnet, Bernd, Tucker, George, von Glehn, Tamara, Muir, Carrie, Mao, Yiran, Kazawa, Hideto, Slone, Ambrose, Soparkar, Kedar, Shrivastava, Disha, Cobon-Kerr, James, Sharman, Michael, Pavagadhi, Jay, Araya, Carlos, Misiunas, Karolis, Ghelani, Nimesh, Laskin, Michael, Barker, David, Li, Qiujia, Briukhov, Anton, Houlsby, Neil, Glaese, Mia, Lakshminarayanan, Balaji, Schucher, Nathan, Tang, Yunhao, Collins, Eli, Lim, Hyeontaek, Feng, Fangxiaoyu, Recasens, Adria, Lai, Guangda, Magni, Alberto, De Cao, Nicola, Siddhant, Aditya, Ashwood, Zoe, Orbay, Jordi, Dehghani, Mostafa, Brennan, Jenny, He, Yifan, Xu, Kelvin, Gao, Yang, Saroufim, Carl, Molloy, James, Wu, Xinyi, Arnold, Seb, Chang, Solomon, Schrittwieser, Julian, Buchatskaya, Elena, Radpour, Soroush, Polacek, Martin, Giordano, Skye, Bapna, Ankur, Tokumine, Simon, Hellendoorn, Vincent, Sottiaux, Thibault, Cogan, Sarah, Severyn, Aliaksei, Saleh, Mohammad, Thakoor, Shantanu, Shefey, Laurent, Qiao, Siyuan, Gaba, Meenu, Chang, Shuo-yiin, Swanson, Craig, Zhang, Biao, Lee, Benjamin, Rubenstein, Paul Kishan, Song, Gan, Kwiatkowski, Tom, Koop, Anna, Kannan, Ajay, Kao, David, Schuh, Parker, Stjerngren, Axel, Ghiasi, Golnaz, Gibson, Gena, Vilnis, Luke, Yuan, Ye, Ferreira, Felipe Tiengo, Kamath, Aishwarya, Klimenko, Ted, Franko, Ken, Xiao, Kefan, Bhattacharya, Indro, Patel, Miteyan, Wang, Rui, Morris, Alex, Strudel, Robin, Sharma, Vivek, Choy, Peter, Hashemi, Sayed Hadi, Landon, Jessica, Finkelstein, Mara, Jhakra, Priya, Frye, Justin, Barnes, Megan, Mauger, Matthew, Daun, Dennis, Baatarsukh, Khuslen, Tung, Matthew, Farhan, Wael, Michalewski, Henryk, Viola, Fabio, Quitry, Felix de Chaumont, Lan, Charline Le, Hudson, Tom, Wang, Qingze, Fischer, Felix, Zheng, Ivy, White, Elspeth, Dragan, Anca, Alayrac, Jean-baptiste, Ni, Eric, Pritzel, Alexander, Iwanicki, Adam, Isard, Michael, Bulanova, Anna, Zilka, Lukas, Dyer, Ethan, Sachan, Devendra, Srinivasan, Srivatsan, Muckenhirn, Hannah, Cai, Honglong, Mandhane, Amol, Tariq, Mukarram, Rae, Jack W., Wang, Gary, Ayoub, Kareem, FitzGerald, Nicholas, Zhao, Yao, Han, Woohyun, Alberti, Chris, Garrette, Dan, Krishnakumar, Kashyap, Gimenez, Mai, Levskaya, Anselm, Sohn, Daniel, Matak, Josip, Iturrate, Inaki, Chang, Michael B., Xiang, Jackie, Cao, Yuan, Ranka, Nishant, Brown, Geoff, Hutter, Adrian, Mirrokni, Vahab, Chen, Nanxin, Yao, Kaisheng, Egyed, Zoltan, Galilee, Francois, Liechty, Tyler, Kallakuri, Praveen, Palmer, Evan, Ghemawat, Sanjay, Liu, Jasmine, Tao, David, Thornton, Chloe, Green, Tim, Jasarevic, Mimi, Lin, Sharon, Cotruta, Victor, Tan, Yi-Xuan, Fiedel, Noah, Yu, Hongkun, Chi, Ed, Neitz, Alexander, Heitkaemper, Jens, Sinha, Anu, Zhou, Denny, Sun, Yi, Kaed, Charbel, Hulse, Brice, Mishra, Swaroop, Georgaki, Maria, Kudugunta, Sneha, Farabet, Clement, Shafran, Izhak, Vlasic, Daniel, Tsitsulin, Anton, Ananthanarayanan, Rajagopal, Carin, Alen, Su, Guolong, Sun, Pei, V, Shashank, Carvajal, Gabriel, Broder, Josef, Comsa, Iulia, Repina, Alena, Wong, William, Chen, Warren Weilun, Hawkins, Peter, Filonov, Egor, Loher, Lucia, Hirnschall, Christoph, Wang, Weiyi, Ye, Jingchen, Burns, Andrea, Cate, Hardie, Wright, Diana Gage, Piccinini, Federico, Zhang, Lei, Lin, Chu-Cheng, Gog, Ionel, Kulizhskaya, Yana, Sreevatsa, Ashwin, Song, Shuang, Cobo, Luis C., Iyer, Anand, Tekur, Chetan, Garrido, Guillermo, Xiao, Zhuyun, Kemp, Rupert, Zheng, Huaixiu Steven, Li, Hui, Agarwal, Ananth, Ngani, Christel, Goshvadi, Kati, Santamaria-Fernandez, Rebeca, Fica, Wojciech, Chen, Xinyun, Gorgolewski, Chris, Sun, Sean, Garg, Roopal, Ye, Xinyu, Eslami, S. M. Ali, Hua, Nan, Simon, Jon, Joshi, Pratik, Kim, Yelin, Tenney, Ian, Potluri, Sahitya, Thiet, Lam Nguyen, Yuan, Quan, Luisier, Florian, Chronopoulou, Alexandra, Scellato, Salvatore, Srinivasan, Praveen, Chen, Minmin, Koverkathu, Vinod, Dalibard, Valentin, Xu, Yaming, Saeta, Brennan, Anderson, Keith, Sellam, Thibault, Fernando, Nick, Huot, Fantine, Jung, Junehyuk, Varadarajan, Mani, Quinn, Michael, Raul, Amit, Le, Maigo, Habalov, Ruslan, Clark, Jon, Jalan, Komal, Bullard, Kalesha, Singhal, Achintya, Luong, Thang, Wang, Boyu, Rajayogam, Sujeevan, Eisenschlos, Julian, Jia, Johnson, Finchelstein, Daniel, Yakubovich, Alex, Balle, Daniel, Fink, Michael, Agarwal, Sameer, Li, Jing, Dvijotham, Dj, Pal, Shalini, Kang, Kai, Konzelmann, Jaclyn, Beattie, Jennifer, Dousse, Olivier, Wu, Diane, Crocker, Remi, Elkind, Chen, Jonnalagadda, Siddhartha Reddy, Lee, Jong, Holtmann-Rice, Dan, Kallarackal, Krystal, Liu, Rosanne, Vnukov, Denis, Vats, Neera, Invernizzi, Luca, Jafari, Mohsen, Zhou, Huanjie, Taylor, Lilly, Prendki, Jennifer, Wu, Marcus, Eccles, Tom, Liu, Tianqi, Kopparapu, Kavya, Beaufays, Francoise, Angermueller, Christof, Marzoca, Andreea, Sarcar, Shourya, Dib, Hilal, Stanway, Jeff, Perbet, Frank, Trdin, Nejc, Sterneck, Rachel, Khorlin, Andrey, Li, Dinghua, Wu, Xihui, Goenka, Sonam, Madras, David, Goldshtein, Sasha, Gierke, Willi, Zhou, Tong, Liu, Yaxin, Liang, Yannie, White, Anais, Li, Yunjie, Singh, Shreya, Bahargam, Sanaz, Epstein, Mark, Basu, Sujoy, Lao, Li, Ozturel, Adnan, Crous, Carl, Zhai, Alex, Lu, Han, Tung, Zora, Gaur, Neeraj, Walton, Alanna, Dixon, Lucas, Zhang, Ming, Globerson, Amir, Uy, Grant, Bolt, Andrew, Wiles, Olivia, Nasr, Milad, Shumailov, Ilia, Selvi, Marco, Piccinno, Francesco, Aguilar, Ricardo, McCarthy, Sara, Khalman, Misha, Shukla, Mrinal, Galic, Vlado, Carpenter, John, Villela, Kevin, Zhang, Haibin, Richardson, Harry, Martens, James, Bosnjak, Matko, Belle, Shreyas Rammohan, Seibert, Jeff, Alnahlawi, Mahmoud, McWilliams, Brian, Singh, Sankalp, Louis, Annie, Ding, Wen, Popovici, Dan, Simicich, Lenin, Knight, Laura, Mehta, Pulkit, Gupta, Nishesh, Shi, Chongyang, Fatehi, Saaber, Mitrovic, Jovana, Grills, Alex, Pagadora, Joseph, Munkhdalai, Tsendsuren, Petrova, Dessie, Eisenbud, Danielle, Zhang, Zhishuai, Yates, Damion, Mittal, Bhavishya, Tripuraneni, Nilesh, Assael, Yannis, Brovelli, Thomas, Jain, Prateek, Velimirovic, Mihajlo, Akbulut, Canfer, Mu, Jiaqi, Macherey, Wolfgang, Kumar, Ravin, Xu, Jun, Qureshi, Haroon, Comanici, Gheorghe, Wiesner, Jeremy, Gong, Zhitao, Ruddock, Anton, Bauer, Matthias, Felt, Nick, GP, Anirudh, Arnab, Anurag, Zelle, Dustin, Rothfuss, Jonas, Rosgen, Bill, Shenoy, Ashish, Seybold, Bryan, Li, Xinjian, Mudigonda, Jayaram, Erdogan, Goker, Xia, Jiawei, Simsa, Jiri, Michi, Andrea, Yao, Yi, Yew, Christopher, Kan, Steven, Caswell, Isaac, Radebaugh, Carey, Elisseeff, Andre, Valenzuela, Pedro, McKinney, Kay, Paterson, Kim, Cui, Albert, Latorre-Chimoto, Eri, Kim, Solomon, Zeng, William, Durden, Ken, Ponnapalli, Priya, Sosea, Tiberiu, Choquette-Choo, Christopher A., Manyika, James, Robenek, Brona, Vashisht, Harsha, Pereira, Sebastien, Lam, Hoi, Velic, Marko, Owusu-Afriyie, Denese, Lee, Katherine, Bolukbasi, Tolga, Parrish, Alicia, Lu, Shawn, Park, Jane, Venkatraman, Balaji, Talbert, Alice, Rosique, Lambert, Cheng, Yuchung, Sozanschi, Andrei, Paszke, Adam, Kumar, Praveen, Austin, Jessica, Li, Lu, Salama, Khalid, Perz, Bartek, Kim, Wooyeol, Dukkipati, Nandita, Baryshnikov, Anthony, Kaplanis, Christos, Sheng, XiangHai, Chervonyi, Yuri, Unlu, Caglar, Casas, Diego de Las, Askham, Harry, Tunyasuvunakool, Kathryn, Gimeno, Felix, Poder, Siim, Kwak, Chester, Miecnikowski, Matt, Dimitriev, Alek, Parisi, Aaron, Liu, Dangyi, Tsai, Tomy, Shevlane, Toby, Kouridi, Christina, Garmon, Drew, Goedeckemeyer, Adrian, Brown, Adam R., Vijayakumar, Anitha, Elqursh, Ali, Jazayeri, Sadegh, Huang, Jin, Carthy, Sara Mc, Hoover, Jay, Kim, Lucy, Kumar, Sandeep, Chen, Wei, Biles, Courtney, Bingham, Garrett, Rosen, Evan, Wang, Lisa, Tan, Qijun, Engel, David, Pongetti, Francesco, de Cesare, Dario, Hwang, Dongseong, Yu, Lily, Pullman, Jennifer, Narayanan, Srini, Levin, Kyle, Gopal, Siddharth, Li, Megan, Aharoni, Asaf, Trinh, Trieu, Lo, Jessica, Casagrande, Norman, Vij, Roopali, Matthey, Loic, Ramadhana, Bramandia, Matthews, Austin, Carey, CJ, Johnson, Matthew, Goranova, Kremena, Shah, Rohin, Ashraf, Shereen, Dasgupta, Kingshuk, Larsen, Rasmus, Wang, Yicheng, Vuyyuru, Manish Reddy, Jiang, Chong, Ijazi, Joana, Osawa, Kazuki, Smith, Celine, Boppana, Ramya Sree, Bilal, Taylan, Koizumi, Yuma, Xu, Ying, Altun, Yasemin, Shabat, Nir, Bariach, Ben, Korchemniy, Alex, Choo, Kiam, Ronneberger, Olaf, Iwuanyanwu, Chimezie, Zhao, Shubin, Soergel, David, Hsieh, Cho-Jui, Cai, Irene, Iqbal, Shariq, Sundermeyer, Martin, Chen, Zhe, Bursztein, Elie, Malaviya, Chaitanya, Biadsy, Fadi, Shroff, Prakash, Dhillon, Inderjit, Latkar, Tejasi, Dyer, Chris, Forbes, Hannah, Nicosia, Massimo, Nikolaev, Vitaly, Greene, Somer, Georgiev, Marin, Wang, Pidong, Martin, Nina, Sedghi, Hanie, Zhang, John, Banzal, Praseem, Fritz, Doug, Rao, Vikram, Wang, Xuezhi, Zhang, Jiageng, Patraucean, Viorica, Du, Dayou, Mordatch, Igor, Jurin, Ivan, Liu, Lewis, Dubey, Ayush, Mohan, Abhi, Nowakowski, Janek, Ion, Vlad-Doru, Wei, Nan, Tojo, Reiko, Raad, Maria Abi, Hudson, Drew A., Keshava, Vaishakh, Agrawal, Shubham, Ramirez, Kevin, Wu, Zhichun, Nguyen, Hoang, Liu, Ji, Sewak, Madhavi, Petrini, Bryce, Choi, DongHyun, Philips, Ivan, Wang, Ziyue, Bica, Ioana, Garg, Ankush, Wilkiewicz, Jarek, Agrawal, Priyanka, Guo, Danhao, Xue, Emily, Shaik, Naseer, Leach, Andrew, Khan, Sadh MNM, Wiesinger, Julia, Jerome, Sammy, Chakladar, Abhishek, Wang, Alek Wenjiao, Ornduff, Tina, Abu, Folake, Ghaffarkhah, Alireza, Wainwright, Marcus, Cortes, Mario, Liu, Frederick, Maynez, Joshua, Terzis, Andreas, Samangouei, Pouya, Mansour, Riham, Kępa, Tomasz, Aubet, François-Xavier, Algymr, Anton, Banica, Dan, Weisz, Agoston, Orban, Andras, Senges, Alexandre, Andrejczuk, Ewa, Geller, Mark, Santo, Niccolo Dal, Anklin, Valentin, Merey, Majd Al, Baeuml, Martin, Strohman, Trevor, Bai, Junwen, Petrov, Slav, Wu, Yonghui, Hassabis, Demis, Kavukcuoglu, Koray, Dean, Jeff, and Vinyals, Oriol

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

In this report, we introduce the Gemini 1.5 family of models, representing the next generation of highly compute-efficient multimodal models capable of recalling and reasoning over fine-grained information from millions of tokens of context, including multiple long documents and hours of video and audio. The family includes two new models: (1) an updated Gemini 1.5 Pro, which exceeds the February version on the great majority of capabilities and benchmarks; (2) Gemini 1.5 Flash, a more lightweight variant designed for efficiency with minimal regression in quality. Gemini 1.5 models achieve near-perfect recall on long-context retrieval tasks across modalities, improve the state-of-the-art in long-document QA, long-video QA and long-context ASR, and match or surpass Gemini 1.0 Ultra's state-of-the-art performance across a broad set of benchmarks. Studying the limits of Gemini 1.5's long-context ability, we find continued improvement in next-token prediction and near-perfect retrieval (>99%) up to at least 10M tokens, a generational leap over existing models such as Claude 3.0 (200k) and GPT-4 Turbo (128k). Finally, we highlight real-world use cases, such as Gemini 1.5 collaborating with professionals on completing their tasks achieving 26 to 75% time savings across 10 different job categories, as well as surprising new capabilities of large language models at the frontier; when given a grammar manual for Kalamang, a language with fewer than 200 speakers worldwide, the model learns to translate English to Kalamang at a similar level to a person who learned from the same content.

Published
2024

14. Quantum error thresholds for gauge-redundant digitizations of lattice field theories

Author

Carena, Marcela, Lamm, Henry, Li, Ying-Ying, and Liu, Wanqiang

Subjects
High Energy Physics - Lattice, Quantum Physics
Abstract

In the quantum simulation of lattice gauge theories, gauge symmetry can be either fixed or encoded as a redundancy of the Hilbert space. While gauge-fixing reduces the number of qubits, keeping the gauge redundancy can provide code space to mitigate and correct quantum errors by checking and restoring Gauss's law. In this work, we consider the correctable errors for generic finite gauge groups and design the quantum circuits to detect and correct them. We calculate the error thresholds below which the gauge-redundant digitization with Gauss's law error correction has better fidelity than the gauge-fixed digitization. Our results provide guidance for fault-tolerant quantum simulations of lattice gauge theories., Comment: 16 pages, 7 figures

Published
2024

15. Oncolytic adenoviral therapy plus pembrolizumab in BCG-unresponsive non-muscle-invasive bladder cancer: the phase 2 CORE-001 trial

Author

Li, Roger, Shah, Paras H., Stewart, Tyler F., Nam, Jong Kil, Bivalacqua, Trinity J., Lamm, Donald L., Uchio, Edward M., Geynisman, Daniel M., Jacob, Joseph M., Meeks, Joshua J., Dickstein, Rian, Pearce, Shane M., Kang, Seok Ho, Jung, Seung Il, Kamat, Ashish M., Burke, James M., Keegan, Kirk A., and Steinberg, Gary D.

Published
2024
Full Text
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16. Gemini: A Family of Highly Capable Multimodal Models

Author

Gemini Team, Anil, Rohan, Borgeaud, Sebastian, Alayrac, Jean-Baptiste, Yu, Jiahui, Soricut, Radu, Schalkwyk, Johan, Dai, Andrew M., Hauth, Anja, Millican, Katie, Silver, David, Johnson, Melvin, Antonoglou, Ioannis, Schrittwieser, Julian, Glaese, Amelia, Chen, Jilin, Pitler, Emily, Lillicrap, Timothy, Lazaridou, Angeliki, Firat, Orhan, Molloy, James, Isard, Michael, Barham, Paul R., Hennigan, Tom, Lee, Benjamin, Viola, Fabio, Reynolds, Malcolm, Xu, Yuanzhong, Doherty, Ryan, Collins, Eli, Meyer, Clemens, Rutherford, Eliza, Moreira, Erica, Ayoub, Kareem, Goel, Megha, Krawczyk, Jack, Du, Cosmo, Chi, Ed, Cheng, Heng-Tze, Ni, Eric, Shah, Purvi, Kane, Patrick, Chan, Betty, Faruqui, Manaal, Severyn, Aliaksei, Lin, Hanzhao, Li, YaGuang, Cheng, Yong, Ittycheriah, Abe, Mahdieh, Mahdis, Chen, Mia, Sun, Pei, Tran, Dustin, Bagri, Sumit, Lakshminarayanan, Balaji, Liu, Jeremiah, Orban, Andras, Güra, Fabian, Zhou, Hao, Song, Xinying, Boffy, Aurelien, Ganapathy, Harish, Zheng, Steven, Choe, HyunJeong, Weisz, Ágoston, Zhu, Tao, Lu, Yifeng, Gopal, Siddharth, Kahn, Jarrod, Kula, Maciej, Pitman, Jeff, Shah, Rushin, Taropa, Emanuel, Merey, Majd Al, Baeuml, Martin, Chen, Zhifeng, Shafey, Laurent El, Zhang, Yujing, Sercinoglu, Olcan, Tucker, George, Piqueras, Enrique, Krikun, Maxim, Barr, Iain, Savinov, Nikolay, Danihelka, Ivo, Roelofs, Becca, White, Anaïs, Andreassen, Anders, von Glehn, Tamara, Yagati, Lakshman, Kazemi, Mehran, Gonzalez, Lucas, Khalman, Misha, Sygnowski, Jakub, Frechette, Alexandre, Smith, Charlotte, Culp, Laura, Proleev, Lev, Luan, Yi, Chen, Xi, Lottes, James, Schucher, Nathan, Lebron, Federico, Rrustemi, Alban, Clay, Natalie, Crone, Phil, Kocisky, Tomas, Zhao, Jeffrey, Perz, Bartek, Yu, Dian, Howard, Heidi, Bloniarz, Adam, Rae, Jack W., Lu, Han, Sifre, Laurent, Maggioni, Marcello, Alcober, Fred, Garrette, Dan, Barnes, Megan, Thakoor, Shantanu, Austin, Jacob, Barth-Maron, Gabriel, Wong, William, Joshi, Rishabh, Chaabouni, Rahma, Fatiha, Deeni, Ahuja, Arun, Tomar, Gaurav Singh, Senter, Evan, Chadwick, Martin, Kornakov, Ilya, Attaluri, Nithya, Iturrate, Iñaki, Liu, Ruibo, Li, Yunxuan, Cogan, Sarah, Chen, Jeremy, Jia, Chao, Gu, Chenjie, Zhang, Qiao, Grimstad, Jordan, Hartman, Ale Jakse, Garcia, Xavier, Pillai, Thanumalayan Sankaranarayana, Devlin, Jacob, Laskin, Michael, Casas, Diego de Las, Valter, Dasha, Tao, Connie, Blanco, Lorenzo, Badia, Adrià Puigdomènech, Reitter, David, Chen, Mianna, Brennan, Jenny, Rivera, Clara, Brin, Sergey, Iqbal, Shariq, Surita, Gabriela, Labanowski, Jane, Rao, Abhi, Winkler, Stephanie, Parisotto, Emilio, Gu, Yiming, Olszewska, Kate, Addanki, Ravi, Miech, Antoine, Louis, Annie, Teplyashin, Denis, Brown, Geoff, Catt, Elliot, Balaguer, Jan, Xiang, Jackie, Wang, Pidong, Ashwood, Zoe, Briukhov, Anton, Webson, Albert, Ganapathy, Sanjay, Sanghavi, Smit, Kannan, Ajay, Chang, Ming-Wei, Stjerngren, Axel, Djolonga, Josip, Sun, Yuting, Bapna, Ankur, Aitchison, Matthew, Pejman, Pedram, Michalewski, Henryk, Yu, Tianhe, Wang, Cindy, Love, Juliette, Ahn, Junwhan, Bloxwich, Dawn, Han, Kehang, Humphreys, Peter, Sellam, Thibault, Bradbury, James, Godbole, Varun, Samangooei, Sina, Damoc, Bogdan, Kaskasoli, Alex, Arnold, Sébastien M. R., Vasudevan, Vijay, Agrawal, Shubham, Riesa, Jason, Lepikhin, Dmitry, Tanburn, Richard, Srinivasan, Srivatsan, Lim, Hyeontaek, Hodkinson, Sarah, Shyam, Pranav, Ferret, Johan, Hand, Steven, Garg, Ankush, Paine, Tom Le, Li, Jian, Li, Yujia, Giang, Minh, Neitz, Alexander, Abbas, Zaheer, York, Sarah, Reid, Machel, Cole, Elizabeth, Chowdhery, Aakanksha, Das, Dipanjan, Rogozińska, Dominika, Nikolaev, Vitaliy, Sprechmann, Pablo, Nado, Zachary, Zilka, Lukas, Prost, Flavien, He, Luheng, Monteiro, Marianne, Mishra, Gaurav, Welty, Chris, Newlan, Josh, Jia, Dawei, Allamanis, Miltiadis, Hu, Clara Huiyi, de Liedekerke, Raoul, Gilmer, Justin, Saroufim, Carl, Rijhwani, Shruti, Hou, Shaobo, Shrivastava, Disha, Baddepudi, Anirudh, Goldin, Alex, Ozturel, Adnan, Cassirer, Albin, Xu, Yunhan, Sohn, Daniel, Sachan, Devendra, Amplayo, Reinald Kim, Swanson, Craig, Petrova, Dessie, Narayan, Shashi, Guez, Arthur, Brahma, Siddhartha, Landon, Jessica, Patel, Miteyan, Zhao, Ruizhe, Villela, Kevin, Wang, Luyu, Jia, Wenhao, Rahtz, Matthew, Giménez, Mai, Yeung, Legg, Keeling, James, Georgiev, Petko, Mincu, Diana, Wu, Boxi, Haykal, Salem, Saputro, Rachel, Vodrahalli, Kiran, Qin, James, Cankara, Zeynep, Sharma, Abhanshu, Fernando, Nick, Hawkins, Will, Neyshabur, Behnam, Kim, Solomon, Hutter, Adrian, Agrawal, Priyanka, Castro-Ros, Alex, Driessche, George van den, Wang, Tao, Yang, Fan, Chang, Shuo-yiin, Komarek, Paul, McIlroy, Ross, Lučić, Mario, Zhang, Guodong, Farhan, Wael, Sharman, Michael, Natsev, Paul, Michel, Paul, Bansal, Yamini, Qiao, Siyuan, Cao, Kris, Shakeri, Siamak, Butterfield, Christina, Chung, Justin, Rubenstein, Paul Kishan, Agrawal, Shivani, Mensch, Arthur, Soparkar, Kedar, Lenc, Karel, Chung, Timothy, Pope, Aedan, Maggiore, Loren, Kay, Jackie, Jhakra, Priya, Wang, Shibo, Maynez, Joshua, Phuong, Mary, Tobin, Taylor, Tacchetti, Andrea, Trebacz, Maja, Robinson, Kevin, Katariya, Yash, Riedel, Sebastian, Bailey, Paige, Xiao, Kefan, Ghelani, Nimesh, Aroyo, Lora, Slone, Ambrose, Houlsby, Neil, Xiong, Xuehan, Yang, Zhen, Gribovskaya, Elena, Adler, Jonas, Wirth, Mateo, Lee, Lisa, Li, Music, Kagohara, Thais, Pavagadhi, Jay, Bridgers, Sophie, Bortsova, Anna, Ghemawat, Sanjay, Ahmed, Zafarali, Liu, Tianqi, Powell, Richard, Bolina, Vijay, Iinuma, Mariko, Zablotskaia, Polina, Besley, James, Chung, Da-Woon, Dozat, Timothy, Comanescu, Ramona, Si, Xiance, Greer, Jeremy, Su, Guolong, Polacek, Martin, Kaufman, Raphaël Lopez, Tokumine, Simon, Hu, Hexiang, Buchatskaya, Elena, Miao, Yingjie, Elhawaty, Mohamed, Siddhant, Aditya, Tomasev, Nenad, Xing, Jinwei, Greer, Christina, Miller, Helen, Ashraf, Shereen, Roy, Aurko, Zhang, Zizhao, Ma, Ada, Filos, Angelos, Besta, Milos, Blevins, Rory, Klimenko, Ted, Yeh, Chih-Kuan, Changpinyo, Soravit, Mu, Jiaqi, Chang, Oscar, Pajarskas, Mantas, Muir, Carrie, Cohen, Vered, Lan, Charline Le, Haridasan, Krishna, Marathe, Amit, Hansen, Steven, Douglas, Sholto, Samuel, Rajkumar, Wang, Mingqiu, Austin, Sophia, Lan, Chang, Jiang, Jiepu, Chiu, Justin, Lorenzo, Jaime Alonso, Sjösund, Lars Lowe, Cevey, Sébastien, Gleicher, Zach, Avrahami, Thi, Boral, Anudhyan, Srinivasan, Hansa, Selo, Vittorio, May, Rhys, Aisopos, Konstantinos, Hussenot, Léonard, Soares, Livio Baldini, Baumli, Kate, Chang, Michael B., Recasens, Adrià, Caine, Ben, Pritzel, Alexander, Pavetic, Filip, Pardo, Fabio, Gergely, Anita, Frye, Justin, Ramasesh, Vinay, Horgan, Dan, Badola, Kartikeya, Kassner, Nora, Roy, Subhrajit, Dyer, Ethan, Campos, Víctor Campos, Tomala, Alex, Tang, Yunhao, Badawy, Dalia El, White, Elspeth, Mustafa, Basil, Lang, Oran, Jindal, Abhishek, Vikram, Sharad, Gong, Zhitao, Caelles, Sergi, Hemsley, Ross, Thornton, Gregory, Feng, Fangxiaoyu, Stokowiec, Wojciech, Zheng, Ce, Thacker, Phoebe, Ünlü, Çağlar, Zhang, Zhishuai, Saleh, Mohammad, Svensson, James, Bileschi, Max, Patil, Piyush, Anand, Ankesh, Ring, Roman, Tsihlas, Katerina, Vezer, Arpi, Selvi, Marco, Shevlane, Toby, Rodriguez, Mikel, Kwiatkowski, Tom, Daruki, Samira, Rong, Keran, Dafoe, Allan, FitzGerald, Nicholas, Gu-Lemberg, Keren, Khan, Mina, Hendricks, Lisa Anne, Pellat, Marie, Feinberg, Vladimir, Cobon-Kerr, James, Sainath, Tara, Rauh, Maribeth, Hashemi, Sayed Hadi, Ives, Richard, Hasson, Yana, Noland, Eric, Cao, Yuan, Byrd, Nathan, Hou, Le, Wang, Qingze, Sottiaux, Thibault, Paganini, Michela, Lespiau, Jean-Baptiste, Moufarek, Alexandre, Hassan, Samer, Shivakumar, Kaushik, van Amersfoort, Joost, Mandhane, Amol, Joshi, Pratik, Goyal, Anirudh, Tung, Matthew, Brock, Andrew, Sheahan, Hannah, Misra, Vedant, Li, Cheng, Rakićević, Nemanja, Dehghani, Mostafa, Liu, Fangyu, Mittal, Sid, Oh, Junhyuk, Noury, Seb, Sezener, Eren, Huot, Fantine, Lamm, Matthew, De Cao, Nicola, Chen, Charlie, Mudgal, Sidharth, Stella, Romina, Brooks, Kevin, Vasudevan, Gautam, Liu, Chenxi, Chain, Mainak, Melinkeri, Nivedita, Cohen, Aaron, Wang, Venus, Seymore, Kristie, Zubkov, Sergey, Goel, Rahul, Yue, Summer, Krishnakumaran, Sai, Albert, Brian, Hurley, Nate, Sano, Motoki, Mohananey, Anhad, Joughin, Jonah, Filonov, Egor, Kępa, Tomasz, Eldawy, Yomna, Lim, Jiawern, Rishi, Rahul, Badiezadegan, Shirin, Bos, Taylor, Chang, Jerry, Jain, Sanil, Padmanabhan, Sri Gayatri Sundara, Puttagunta, Subha, Krishna, Kalpesh, Baker, Leslie, Kalb, Norbert, Bedapudi, Vamsi, Kurzrok, Adam, Lei, Shuntong, Yu, Anthony, Litvin, Oren, Zhou, Xiang, Wu, Zhichun, Sobell, Sam, Siciliano, Andrea, Papir, Alan, Neale, Robby, Bragagnolo, Jonas, Toor, Tej, Chen, Tina, Anklin, Valentin, Wang, Feiran, Feng, Richie, Gholami, Milad, Ling, Kevin, Liu, Lijuan, Walter, Jules, Moghaddam, Hamid, Kishore, Arun, Adamek, Jakub, Mercado, Tyler, Mallinson, Jonathan, Wandekar, Siddhinita, Cagle, Stephen, Ofek, Eran, Garrido, Guillermo, Lombriser, Clemens, Mukha, Maksim, Sun, Botu, Mohammad, Hafeezul Rahman, Matak, Josip, Qian, Yadi, Peswani, Vikas, Janus, Pawel, Yuan, Quan, Schelin, Leif, David, Oana, Garg, Ankur, He, Yifan, Duzhyi, Oleksii, Älgmyr, Anton, Lottaz, Timothée, Li, Qi, Yadav, Vikas, Xu, Luyao, Chinien, Alex, Shivanna, Rakesh, Chuklin, Aleksandr, Li, Josie, Spadine, Carrie, Wolfe, Travis, Mohamed, Kareem, Das, Subhabrata, Dai, Zihang, He, Kyle, von Dincklage, Daniel, Upadhyay, Shyam, Maurya, Akanksha, Chi, Luyan, Krause, Sebastian, Salama, Khalid, Rabinovitch, Pam G, M, Pavan Kumar Reddy, Selvan, Aarush, Dektiarev, Mikhail, Ghiasi, Golnaz, Guven, Erdem, Gupta, Himanshu, Liu, Boyi, Sharma, Deepak, Shtacher, Idan Heimlich, Paul, Shachi, Akerlund, Oscar, Aubet, François-Xavier, Huang, Terry, Zhu, Chen, Zhu, Eric, Teixeira, Elico, Fritze, Matthew, Bertolini, Francesco, Marinescu, Liana-Eleonora, Bölle, Martin, Paulus, Dominik, Gupta, Khyatti, Latkar, Tejasi, Chang, Max, Sanders, Jason, Wilson, Roopa, Wu, Xuewei, Tan, Yi-Xuan, Thiet, Lam Nguyen, Doshi, Tulsee, Lall, Sid, Mishra, Swaroop, Chen, Wanming, Luong, Thang, Benjamin, Seth, Lee, Jasmine, Andrejczuk, Ewa, Rabiej, Dominik, Ranjan, Vipul, Styrc, Krzysztof, Yin, Pengcheng, Simon, Jon, Harriott, Malcolm Rose, Bansal, Mudit, Robsky, Alexei, Bacon, Geoff, Greene, David, Mirylenka, Daniil, Zhou, Chen, Sarvana, Obaid, Goyal, Abhimanyu, Andermatt, Samuel, Siegler, Patrick, Horn, Ben, Israel, Assaf, Pongetti, Francesco, Chen, Chih-Wei "Louis", Selvatici, Marco, Silva, Pedro, Wang, Kathie, Tolins, Jackson, Guu, Kelvin, Yogev, Roey, Cai, Xiaochen, Agostini, Alessandro, Shah, Maulik, Nguyen, Hung, Donnaile, Noah Ó, Pereira, Sébastien, Friso, Linda, Stambler, Adam, Kuang, Chenkai, Romanikhin, Yan, Geller, Mark, Yan, ZJ, Jang, Kane, Lee, Cheng-Chun, Fica, Wojciech, Malmi, Eric, Tan, Qijun, Banica, Dan, Balle, Daniel, Pham, Ryan, Huang, Yanping, Avram, Diana, Shi, Hongzhi, Singh, Jasjot, Hidey, Chris, Ahuja, Niharika, Saxena, Pranab, Dooley, Dan, Potharaju, Srividya Pranavi, O'Neill, Eileen, Gokulchandran, Anand, Foley, Ryan, Zhao, Kai, Dusenberry, Mike, Liu, Yuan, Mehta, Pulkit, Kotikalapudi, Ragha, Safranek-Shrader, Chalence, Goodman, Andrew, Kessinger, Joshua, Globen, Eran, Kolhar, Prateek, Gorgolewski, Chris, Ibrahim, Ali, Song, 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Eric, Lai, Jonathan, Chung, Raynald, Yang, Kai, Balani, Nihal, Bražinskas, Arthur, Sozanschi, Andrei, Hayes, Matthew, Alcalde, Héctor Fernández, Makarov, Peter, Chen, Will, Stella, Antonio, Snijders, Liselotte, Mandl, Michael, Kärrman, Ante, Nowak, Paweł, Wu, Xinyi, Dyck, Alex, Vaidyanathan, Krishnan, R, Raghavender, Mallet, Jessica, Rudominer, Mitch, Johnston, Eric, Mittal, Sushil, Udathu, Akhil, Christensen, Janara, Verma, Vishal, Irving, Zach, Santucci, Andreas, Elsayed, Gamaleldin, Davoodi, Elnaz, Georgiev, Marin, Tenney, Ian, Hua, Nan, Cideron, Geoffrey, Leurent, Edouard, Alnahlawi, Mahmoud, Georgescu, Ionut, Wei, Nan, Zheng, Ivy, Scandinaro, Dylan, Jiang, Heinrich, Snoek, Jasper, Sundararajan, Mukund, Wang, Xuezhi, Ontiveros, Zack, Karo, Itay, Cole, Jeremy, Rajashekhar, Vinu, Tumeh, Lara, Ben-David, Eyal, Jain, Rishub, Uesato, Jonathan, Datta, Romina, Bunyan, Oskar, Wu, Shimu, Zhang, John, Stanczyk, Piotr, Zhang, Ye, Steiner, David, Naskar, Subhajit, Azzam, Michael, Johnson, Matthew, Paszke, Adam, Chiu, Chung-Cheng, Elias, Jaume Sanchez, Mohiuddin, Afroz, Muhammad, Faizan, Miao, Jin, Lee, Andrew, Vieillard, Nino, Park, Jane, Zhang, Jiageng, Stanway, Jeff, Garmon, Drew, Karmarkar, Abhijit, Dong, Zhe, Lee, Jong, Kumar, Aviral, Zhou, Luowei, Evens, Jonathan, Isaac, William, Irving, Geoffrey, Loper, Edward, Fink, Michael, Arkatkar, Isha, Chen, Nanxin, Shafran, Izhak, Petrychenko, Ivan, Chen, Zhe, Jia, Johnson, Levskaya, Anselm, Zhu, Zhenkai, Grabowski, Peter, Mao, Yu, Magni, Alberto, Yao, Kaisheng, Snaider, Javier, Casagrande, Norman, Palmer, Evan, Suganthan, Paul, Castaño, Alfonso, Giannoumis, Irene, Kim, Wooyeol, Rybiński, Mikołaj, Sreevatsa, Ashwin, Prendki, Jennifer, Soergel, David, Goedeckemeyer, Adrian, Gierke, Willi, Jafari, Mohsen, Gaba, Meenu, Wiesner, Jeremy, Wright, Diana Gage, Wei, Yawen, Vashisht, Harsha, Kulizhskaya, Yana, Hoover, Jay, Le, Maigo, Li, Lu, Iwuanyanwu, Chimezie, Liu, Lu, Ramirez, Kevin, Khorlin, Andrey, Cui, Albert, LIN, Tian, Wu, Marcus, Aguilar, Ricardo, Pallo, Keith, Chakladar, Abhishek, Perng, Ginger, Abellan, Elena Allica, Zhang, Mingyang, Dasgupta, Ishita, Kushman, Nate, Penchev, Ivo, Repina, Alena, Wu, Xihui, van der Weide, Tom, Ponnapalli, Priya, Kaplan, Caroline, Simsa, Jiri, Li, Shuangfeng, Dousse, Olivier, Piper, Jeff, Ie, Nathan, Pasumarthi, Rama, Lintz, Nathan, Vijayakumar, Anitha, Andor, Daniel, Valenzuela, Pedro, Lui, Minnie, Paduraru, Cosmin, Peng, Daiyi, Lee, Katherine, Zhang, Shuyuan, Greene, Somer, Nguyen, Duc Dung, Kurylowicz, Paula, Hardin, Cassidy, Dixon, Lucas, Janzer, Lili, Choo, Kiam, Feng, Ziqiang, Zhang, Biao, Singhal, Achintya, Du, Dayou, McKinnon, Dan, Antropova, Natasha, Bolukbasi, Tolga, Keller, Orgad, Reid, David, Finchelstein, Daniel, Raad, Maria Abi, Crocker, Remi, Hawkins, Peter, Dadashi, Robert, Gaffney, Colin, Franko, Ken, Bulanova, Anna, Leblond, Rémi, Chung, Shirley, Askham, Harry, Cobo, Luis C., Xu, Kelvin, Fischer, Felix, Xu, Jun, Sorokin, Christina, Alberti, Chris, Lin, Chu-Cheng, Evans, Colin, Dimitriev, Alek, Forbes, Hannah, Banarse, Dylan, Tung, Zora, Omernick, Mark, Bishop, Colton, Sterneck, Rachel, Jain, Rohan, Xia, Jiawei, Amid, Ehsan, Piccinno, Francesco, Wang, Xingyu, Banzal, Praseem, Mankowitz, Daniel J., Polozov, Alex, Krakovna, Victoria, Brown, Sasha, Bateni, MohammadHossein, Duan, Dennis, Firoiu, Vlad, Thotakuri, Meghana, Natan, Tom, Geist, Matthieu, Girgin, Ser tan, Li, Hui, Ye, Jiayu, Roval, Ofir, Tojo, Reiko, Kwong, Michael, Lee-Thorp, James, Yew, Christopher, Sinopalnikov, Danila, Ramos, Sabela, Mellor, John, Sharma, Abhishek, Wu, Kathy, Miller, David, Sonnerat, Nicolas, Vnukov, Denis, Greig, Rory, Beattie, Jennifer, Caveness, Emily, Bai, Libin, Eisenschlos, Julian, Korchemniy, Alex, Tsai, Tomy, Jasarevic, Mimi, Kong, Weize, Dao, Phuong, Zheng, Zeyu, Liu, Frederick, Zhu, Rui, Teh, Tian Huey, Sanmiya, Jason, Gladchenko, Evgeny, Trdin, Nejc, Toyama, Daniel, Rosen, Evan, Tavakkol, Sasan, Xue, Linting, Elkind, Chen, Woodman, Oliver, Carpenter, John, Papamakarios, George, Kemp, Rupert, Kafle, Sushant, Grunina, Tanya, Sinha, Rishika, Talbert, Alice, Wu, Diane, Owusu-Afriyie, Denese, Thornton, Chloe, Pont-Tuset, Jordi, Narayana, Pradyumna, Li, Jing, Fatehi, Saaber, Wieting, John, Ajmeri, Omar, Uria, Benigno, Ko, Yeongil, Knight, Laura, Héliou, Amélie, Niu, Ning, Gu, Shane, Pang, Chenxi, Li, Yeqing, Levine, Nir, Stolovich, Ariel, Santamaria-Fernandez, Rebeca, Goenka, Sonam, Yustalim, Wenny, Strudel, Robin, Elqursh, Ali, Deck, Charlie, Lee, Hyo, Li, Zonglin, Levin, Kyle, Hoffmann, Raphael, Holtmann-Rice, Dan, Bachem, Olivier, Arora, Sho, Koh, Christy, Yeganeh, Soheil Hassas, Põder, Siim, Tariq, Mukarram, Sun, Yanhua, Ionita, Lucian, Seyedhosseini, Mojtaba, Tafti, Pouya, Liu, Zhiyu, Gulati, Anmol, Liu, Jasmine, Ye, Xinyu, Chrzaszcz, Bart, Wang, Lily, Sethi, Nikhil, Li, Tianrun, Brown, Ben, Singh, Shreya, Fan, Wei, Parisi, Aaron, Stanton, Joe, Koverkathu, Vinod, Choquette-Choo, Christopher A., Li, Yunjie, Lu, TJ, Shroff, Prakash, Varadarajan, Mani, Bahargam, Sanaz, Willoughby, Rob, Gaddy, David, Desjardins, Guillaume, Cornero, Marco, Robenek, Brona, Mittal, Bhavishya, Albrecht, Ben, Shenoy, Ashish, Moiseev, Fedor, Jacobsson, Henrik, Ghaffarkhah, Alireza, Rivière, Morgane, Walton, Alanna, Crepy, Clément, Parrish, Alicia, Zhou, Zongwei, Farabet, Clement, Radebaugh, Carey, Srinivasan, Praveen, van der Salm, Claudia, Fidjeland, Andreas, Scellato, Salvatore, Latorre-Chimoto, Eri, Klimczak-Plucińska, Hanna, Bridson, David, de Cesare, Dario, Hudson, Tom, Mendolicchio, Piermaria, Walker, Lexi, Morris, Alex, Mauger, Matthew, Guseynov, Alexey, Reid, Alison, Odoom, Seth, Loher, Lucia, Cotruta, Victor, Yenugula, Madhavi, Grewe, Dominik, Petrushkina, Anastasia, Duerig, Tom, Sanchez, Antonio, Yadlowsky, Steve, Shen, Amy, Globerson, Amir, Webb, Lynette, Dua, Sahil, Li, Dong, Bhupatiraju, Surya, Hurt, Dan, Qureshi, Haroon, Agarwal, Ananth, Shani, Tomer, Eyal, Matan, Khare, Anuj, Belle, Shreyas Rammohan, Wang, Lei, Tekur, Chetan, Kale, Mihir Sanjay, Wei, Jinliang, Sang, Ruoxin, Saeta, Brennan, Liechty, Tyler, Sun, Yi, Zhao, Yao, Lee, Stephan, Nayak, Pandu, Fritz, Doug, Vuyyuru, Manish Reddy, Aslanides, John, Vyas, Nidhi, Wicke, Martin, Ma, Xiao, Eltyshev, Evgenii, Martin, Nina, Cate, Hardie, Manyika, James, Amiri, Keyvan, Kim, Yelin, Xiong, Xi, Kang, Kai, Luisier, Florian, Tripuraneni, Nilesh, Madras, David, Guo, Mandy, Waters, Austin, Wang, Oliver, Ainslie, Joshua, Baldridge, Jason, Zhang, Han, Pruthi, Garima, Bauer, Jakob, Yang, Feng, Mansour, Riham, Gelman, Jason, Xu, Yang, Polovets, George, Liu, Ji, Cai, Honglong, Chen, Warren, Sheng, XiangHai, Xue, Emily, Ozair, Sherjil, Angermueller, Christof, Li, Xiaowei, Sinha, Anoop, Wang, Weiren, Wiesinger, Julia, Koukoumidis, Emmanouil, Tian, Yuan, Iyer, Anand, Gurumurthy, Madhu, Goldenson, Mark, Shah, Parashar, Blake, MK, Yu, Hongkun, Urbanowicz, Anthony, Palomaki, Jennimaria, Fernando, Chrisantha, Durden, Ken, Mehta, Harsh, Momchev, Nikola, Rahimtoroghi, Elahe, Georgaki, Maria, Raul, Amit, Ruder, Sebastian, Redshaw, Morgan, Lee, Jinhyuk, Zhou, Denny, Jalan, Komal, Li, Dinghua, Hechtman, Blake, Schuh, Parker, Nasr, Milad, Milan, Kieran, Mikulik, Vladimir, Franco, Juliana, Green, Tim, Nguyen, Nam, Kelley, Joe, Mahendru, Aroma, Hu, Andrea, Howland, Joshua, Vargas, Ben, Hui, Jeffrey, Bansal, Kshitij, Rao, Vikram, Ghiya, Rakesh, Wang, Emma, Ye, Ke, Sarr, Jean Michel, Preston, Melanie Moranski, Elish, Madeleine, Li, Steve, Kaku, Aakash, Gupta, Jigar, Pasupat, Ice, Juan, Da-Cheng, Someswar, Milan, M., Tejvi, Chen, Xinyun, Amini, Aida, Fabrikant, Alex, Chu, Eric, Dong, Xuanyi, Muthal, Amruta, Buthpitiya, Senaka, Jauhari, Sarthak, Khandelwal, Urvashi, Hitron, Ayal, Ren, Jie, Rinaldi, Larissa, Drath, Shahar, Dabush, Avigail, Jiang, Nan-Jiang, Godhia, Harshal, Sachs, Uli, Chen, Anthony, Fan, Yicheng, Taitelbaum, Hagai, Noga, Hila, Dai, Zhuyun, Wang, James, Hamer, Jenny, Ferng, Chun-Sung, Elkind, Chenel, Atias, Aviel, Lee, Paulina, Listík, Vít, Carlen, Mathias, van de Kerkhof, Jan, Pikus, Marcin, Zaher, Krunoslav, Müller, Paul, Zykova, Sasha, Stefanec, Richard, Gatsko, Vitaly, Hirnschall, Christoph, Sethi, Ashwin, Xu, Xingyu Federico, Ahuja, Chetan, Tsai, Beth, Stefanoiu, Anca, Feng, Bo, Dhandhania, Keshav, Katyal, Manish, Gupta, Akshay, Parulekar, Atharva, Pitta, Divya, Zhao, Jing, Bhatia, Vivaan, Bhavnani, Yashodha, Alhadlaq, Omar, Li, Xiaolin, Danenberg, Peter, Tu, Dennis, Pine, Alex, Filippova, Vera, Ghosh, Abhipso, Limonchik, Ben, Urala, Bhargava, Lanka, Chaitanya Krishna, Clive, Derik, Li, Edward, Wu, Hao, Hongtongsak, Kevin, Li, Ianna, Thakkar, Kalind, Omarov, Kuanysh, Majmundar, Kushal, Alverson, Michael, Kucharski, Michael, Patel, Mohak, Jain, Mudit, Zabelin, Maksim, Pelagatti, Paolo, Kohli, Rohan, Kumar, Saurabh, Kim, Joseph, Sankar, Swetha, Shah, Vineet, Ramachandruni, Lakshmi, Zeng, Xiangkai, Bariach, Ben, Weidinger, Laura, Vu, Tu, Andreev, Alek, He, Antoine, Hui, Kevin, Kashem, Sheleem, Subramanya, Amar, Hsiao, Sissie, Hassabis, Demis, Kavukcuoglu, Koray, Sadovsky, Adam, Le, Quoc, Strohman, Trevor, Wu, Yonghui, Petrov, Slav, Dean, Jeffrey, and Vinyals, Oriol

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition
Abstract

This report introduces a new family of multimodal models, Gemini, that exhibit remarkable capabilities across image, audio, video, and text understanding. The Gemini family consists of Ultra, Pro, and Nano sizes, suitable for applications ranging from complex reasoning tasks to on-device memory-constrained use-cases. Evaluation on a broad range of benchmarks shows that our most-capable Gemini Ultra model advances the state of the art in 30 of 32 of these benchmarks - notably being the first model to achieve human-expert performance on the well-studied exam benchmark MMLU, and improving the state of the art in every one of the 20 multimodal benchmarks we examined. We believe that the new capabilities of the Gemini family in cross-modal reasoning and language understanding will enable a wide variety of use cases. We discuss our approach toward post-training and deploying Gemini models responsibly to users through services including Gemini, Gemini Advanced, Google AI Studio, and Cloud Vertex AI.

Published
2023

17. Primitive Quantum Gates for an $SU(2)$ Discrete Subgroup: Binary Octahedral

Author

Gustafson, Erik J., Lamm, Henry, and Lovelace, Felicity

Subjects
High Energy Physics - Lattice, Quantum Physics
Abstract

We construct a primitive gate set for the digital quantum simulation of the 48-element binary octahedral ($\mathbb{BO}$) group. This nonabelian discrete group better approximates $SU(2)$ lattice gauge theory than previous work on the binary tetrahedral group at the cost of one additional qubit -- for a total of six -- per gauge link. The necessary primitives are the inversion gate, the group multiplication gate, the trace gate, and the $\mathbb{BO}$ Fourier transform., Comment: 8 pages, 5 figures

Published
2023

18. Theory and implementation of inelastic Constitutive Artificial Neural Networks

Author

Holthusen, Hagen, Lamm, Lukas, Brepols, Tim, Reese, Stefanie, and Kuhl, Ellen

Subjects
Computer Science - Machine Learning, Condensed Matter - Materials Science, 65, 74, I.6, J.2
Abstract

Nature has always been our inspiration in the research, design and development of materials and has driven us to gain a deep understanding of the mechanisms that characterize anisotropy and inelastic behavior. All this knowledge has been accumulated in the principles of thermodynamics. Deduced from these principles, the multiplicative decomposition combined with pseudo potentials are powerful and universal concepts. Simultaneously, the tremendous increase in computational performance enabled us to investigate and rethink our history-dependent material models to make the most of our predictions. Today, we have reached a point where materials and their models are becoming increasingly sophisticated. This raises the question: How do we find the best model that includes all inelastic effects to explain our complex data? Constitutive Artificial Neural Networks (CANN) may answer this question. Here, we extend the CANNs to inelastic materials (iCANN). Rigorous considerations of objectivity, rigid motion of the reference configuration, multiplicative decomposition and its inherent non-uniqueness, restrictions of energy and pseudo potential, and consistent evolution guide us towards the architecture of the iCANN satisfying thermodynamics per design. We combine feed-forward networks of the free energy and pseudo potential with a recurrent neural network approach to take time dependencies into account. We demonstrate that the iCANN is capable of autonomously discovering models for artificially generated data, the response of polymers for cyclic loading and the relaxation behavior of muscle data. As the design of the network is not limited to visco-elasticity, our vision is that the iCANN will reveal to us new ways to find the various inelastic phenomena hidden in the data and to understand their interaction. Our source code, data, and examples are available at doi.org/10.5281/zenodo.10066805, Comment: 54 pages, 14 figures, 14 tables

Published
2023
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22. The International Climate Psychology Collaboration: Climate change-related data collected from 63 countries

Author

Doell, Kimberly C., Todorova, Boryana, Vlasceanu, Madalina, Bak Coleman, Joseph B., Pronizius, Ekaterina, Schumann, Philipp, Azevedo, Flavio, Patel, Yash, Berkebile-Wineberg, Michael M., Brick, Cameron, Lange, Florian, Grayson, Samantha J., Pei, Yifei, Chakroff, Alek, van den Broek, Karlijn L., Lamm, Claus, Vlasceanu, Denisa, Constantino, Sara M., Rathje, Steve, Goldwert, Danielle, Fang, Ke, Aglioti, Salvatore Maria, Alfano, Mark, Alvarado-Yepez, Andy J., Andersen, Angélica, Anseel, Frederik, Apps, Matthew A. J., Asadli, Chillar, Awuor, Fonda Jane, Basaglia, Piero, Bélanger, Jocelyn J., Berger, Sebastian, Bertin, Paul, Białek, Michał, Bialobrzeska, Olga, Blaya-Burgo, Michelle, Bleize, Daniëlle N. M., Bø, Simen, Boecker, Lea, Boggio, Paulo S., Borau, Sylvie, Borau, Sylvie, Bos, Björn, Bouguettaya, Ayoub, Brauer, Markus, Brik, Tymofii, Briker, Roman, Brosch, Tobias, Buchel, Ondrej, Buonauro, Daniel, Butalia, Radhika, Carvacho, Héctor, Chamberlain, Sarah A. E., Chan, Hang-Yee, Chow, Dawn, Chung, Dongil, Cian, Luca, Cohen-Eick, Noa, Contreras-Huerta, Luis Sebastian, Contu, Davide, Cristea, Vladimir, Cutler, Jo, D’Ottone, Silvana, De keersmaecker, Jonas, Delcourt, Sarah, Delouvée, Sylvain, Diel, Kathi, Douglas, Benjamin D., Drupp, Moritz A., Dubey, Shreya, Ekmanis, Jānis, Elbaek, Christian T., Elsherif, Mahmoud, Engelhard, Iris M., Escher, Yannik A., Etienne, Tom W., Farage, Laura, Farias, Ana Rita, Feuerriegel, Stefan, Findor, Andrej, Freira, Lucia, Friese, Malte, Gains, Neil Philip, Gallyamova, Albina, Geiger, Sandra J., Genschow, Oliver, Gjoneska, Biljana, Gkinopoulos, Theofilos, Goldberg, Beth, Goldenberg, Amit, Gradidge, Sarah, Grassini, Simone, Gray, Kurt, Grelle, Sonja, Griffin, Siobhán M., Grigoryan, Lusine, Grigoryan, Ani, Grigoryev, Dmitry, Gruber, June, Guilaran, Johnrev, Hadar, Britt, Hahnel, Ulf J. J., Halperin, Eran, Harvey, Annelie J., Haugestad, Christian A. P., Herman, Aleksandra M., Hershfield, Hal E., Himichi, Toshiyuki, Hine, Donald W., Hofmann, Wilhelm, Howe, Lauren, Huaman-Chulluncuy, Enma T., Huang, Guanxiong, Ishii, Tatsunori, Ito, Ayahito, Jia, Fanli, Jost, John T., Jovanović, Veljko, Jurgiel, Dominika, Kácha, Ondřej, Kankaanpää, Reeta, Kantorowicz, Jaroslaw, Kantorowicz-Reznichenko, Elena, Mintz, Keren Kaplan, Kaya, Ilker, Kaya, Ozgur, Khachatryan, Narine, Klas, Anna, Klein, Colin, Klöckner, Christian A., Koppel, Lina, Kosachenko, Alexandra I., Kothe, Emily J., Krebs, Ruth, Krosch, Amy R., Krouwel, Andre P. M., Kyrychenko, Yara, Lagomarsino, Maria, Cunningham, Julia Lee, Lees, Jeffrey, Leung, Tak Yan, Levy, Neil, Lockwood, Patricia L., Longoni, Chiara, Ortega, Alberto López, Loschelder, David D., Lu, Jackson G., Luo, Yu, Luomba, Joseph, Lutz, Annika E., Majer, Johann M., Markowitz, Ezra, Marsh, Abigail A., Mascarenhas, Karen Louise, Mbilingi, Bwambale, Mbungu, Winfred, McHugh, Cillian, Meijers, Marijn H. C., Mercier, Hugo, Mhagama, Fenant Laurent, Michalaki, Katerina, Mikus, Nace, Milliron, Sarah G., Mitkidis, Panagiotis, Monge-Rodríguez, Fredy S., Mora, Youri L., Morais, Michael J., Moreau, David, Motoki, Kosuke, Moyano, Manuel, Mus, Mathilde, Navajas, Joaquin, Nguyen, Tam Luong, Nguyen, Dung Minh, Nguyen, Trieu, Niemi, Laura, Nijssen, Sari R. R., Nilsonne, Gustav, Nitschke, Jonas P., Nockur, Laila, Okura, Ritah, Öner, Sezin, Özdoğru, Asil Ali, Palumbo, Helena, Panagopoulos, Costas, Panasiti, Maria Serena, Pärnamets, Philip, Paruzel-Czachura, Mariola, Pavlov, Yuri G., Payán-Gómez, César, Pearson, Adam R., da Costa, Leonor Pereira, Petrowsky, Hannes M., Pfattheicher, Stefan, Pham, Nhat Tan, Ponizovskiy, Vladimir, Pretus, Clara, Rêgo, Gabriel G., Reimann, Ritsaart, Rhoads, Shawn A., Riano-Moreno, Julian, Richter, Isabell, Röer, Jan Philipp, Rosa-Sullivan, Jahred, Ross, Robert M., Sabherwal, Anandita, Saito, Toshiki, Sarrasin, Oriane, Say, Nicolas, Schmid, Katharina, Schmitt, Michael T., Schoenegger, Philipp, Scholz, Christin, Schug, Mariah G., Schulreich, Stefan, Shreedhar, Ganga, Shuman, Eric, Sivan, Smadar, Sjåstad, Hallgeir, Soliman, Meikel, Soud, Katia, Spampatti, Tobia, Sparkman, Gregg, Spasovski, Ognen, Stanley, Samantha K., Stern, Jessica A., Strahm, Noel, Suko, Yasushi, Sul, Sunhae, Syropoulos, Stylianos, Taylor, Neil C., Tedaldi, Elisa, Tinghög, Gustav, Huynh, Luu Duc Toan, Travaglino, Giovanni Antonio, Tsakiris, Manos, Tüter, İlayda, Tyrala, Michael, Uluğ, Özden Melis, Urbanek, Arkadiusz, Valko, Danila, van der Linden, Sander, van Schie, Kevin, van Stekelenburg, Aart, Vanags, Edmunds, Västfjäll, Daniel, Vesely, Stepan, Vintr, Jáchym, Vranka, Marek, Wanguche, Patrick Otuo, Willer, Robb, Wojcik, Adrian Dominik, Xu, Rachel, Yadav, Anjali, Zawisza, Magdalena, Zhao, Xian, Zhao, Jiaying, Żuk, Dawid, and Van Bavel, Jay J.

Published
2024
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23. Evaluation of FluSight influenza forecasting in the 2021–22 and 2022–23 seasons with a new target laboratory-confirmed influenza hospitalizations

Author

Mathis, Sarabeth M., Webber, Alexander E., León, Tomás M., Murray, Erin L., Sun, Monica, White, Lauren A., Brooks, Logan C., Green, Alden, Hu, Addison J., Rosenfeld, Roni, Shemetov, Dmitry, Tibshirani, Ryan J., McDonald, Daniel J., Kandula, Sasikiran, Pei, Sen, Yaari, Rami, Yamana, Teresa K., Shaman, Jeffrey, Agarwal, Pulak, Balusu, Srikar, Gururajan, Gautham, Kamarthi, Harshavardhan, Prakash, B. Aditya, Raman, Rishi, Zhao, Zhiyuan, Rodríguez, Alexander, Meiyappan, Akilan, Omar, Shalina, Baccam, Prasith, Gurung, Heidi L., Suchoski, Brad T., Stage, Steve A., Ajelli, Marco, Kummer, Allisandra G., Litvinova, Maria, Ventura, Paulo C., Wadsworth, Spencer, Niemi, Jarad, Carcelen, Erica, Hill, Alison L., Loo, Sara L., McKee, Clifton D., Sato, Koji, Smith, Claire, Truelove, Shaun, Jung, Sung-mok, Lemaitre, Joseph C., Lessler, Justin, McAndrew, Thomas, Ye, Wenxuan, Bosse, Nikos, Hlavacek, William S., Lin, Yen Ting, Mallela, Abhishek, Gibson, Graham C., Chen, Ye, Lamm, Shelby M., Lee, Jaechoul, Posner, Richard G., Perofsky, Amanda C., Viboud, Cécile, Clemente, Leonardo, Lu, Fred, Meyer, Austin G., Santillana, Mauricio, Chinazzi, Matteo, Davis, Jessica T., Mu, Kunpeng, Pastore y Piontti, Ana, Vespignani, Alessandro, Xiong, Xinyue, Ben-Nun, Michal, Riley, Pete, Turtle, James, Hulme-Lowe, Chis, Jessa, Shakeel, Nagraj, V. P., Turner, Stephen D., Williams, Desiree, Basu, Avranil, Drake, John M., Fox, Spencer J., Suez, Ehsan, Cojocaru, Monica G., Thommes, Edward W., Cramer, Estee Y., Gerding, Aaron, Stark, Ariane, Ray, Evan L., Reich, Nicholas G., Shandross, Li, Wattanachit, Nutcha, Wang, Yijin, Zorn, Martha W., Aawar, Majd Al, Srivastava, Ajitesh, Meyers, Lauren A., Adiga, Aniruddha, Hurt, Benjamin, Kaur, Gursharn, Lewis, Bryan L., Marathe, Madhav, Venkatramanan, Srinivasan, Butler, Patrick, Farabow, Andrew, Ramakrishnan, Naren, Muralidhar, Nikhil, Reed, Carrie, Biggerstaff, Matthew, and Borchering, Rebecca K.

Published
2024
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28. Defining key concepts for mental state attribution

Author

Quesque, François, Apperly, Ian, Baillargeon, Renée, Baron-Cohen, Simon, Becchio, Cristina, Bekkering, Harold, Bernstein, Daniel, Bertoux, Maxime, Bird, Geoffrey, Bukowski, Henryk, Burgmer, Pascal, Carruthers, Peter, Catmur, Caroline, Dziobek, Isabel, Epley, Nicholas, Erle, Thorsten Michael, Frith, Chris, Frith, Uta, Galang, Carl Michael, Gallese, Vittorio, Grynberg, Delphine, Happé, Francesca, Hirai, Masahiro, Hodges, Sara D., Kanske, Philipp, Kret, Mariska, Lamm, Claus, Nandrino, Jean Louis, Obhi, Sukhvinder, Olderbak, Sally, Perner, Josef, Rossetti, Yves, Schneider, Dana, Schurz, Matthias, Schuwerk, Tobias, Sebanz, Natalie, Shamay-Tsoory, Simone, Silani, Giorgia, Spaulding, Shannon, Todd, Andrew R., Westra, Evan, Zahavi, Dan, and Brass, Marcel

Published
2024
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33. Perceptions of science, science communication, and climate change attitudes in 68 countries – the TISP dataset

Author

Niels G. Mede, Viktoria Cologna, Sebastian Berger, John Besley, Cameron Brick, Marina Joubert, Edward W. Maibach, Sabina Mihelj, Naomi Oreskes, Mike S. Schäfer, Sander van der Linden, Nor Izzatina Abdul Aziz, Suleiman Abdulsalam, Nurulaini Abu Shamsi, Balazs Aczel, Indro Adinugroho, Eleonora Alabrese, Alaa Aldoh, Mark Alfano, Innocent Mbulli Ali, Mohammed Alsobay, Marlene Altenmüller, R. Michael Alvarez, Richard Amoako, Tabitha Amollo, Patrick Ansah, Denisa Apriliawati, Flavio Azevedo, Ani Bajrami, Ronita Bardhan, Keagile Bati, Eri Bertsou, Cornelia Betsch, Apurav Yash Bhatiya, Rahul Bhui, Olga Białobrzeska, Michał Bilewicz, Ayoub Bouguettaya, Katherine Breeden, Amélie Bret, Ondrej Buchel, Pablo Cabrera-Álvarez, Federica Cagnoli, André Calero Valdez, Timothy Callaghan, Rizza Kaye Cases, Sami Çoksan, Gabriela Czarnek, Steven De Peuter, Ramit Debnath, Sylvain Delouvée, Lucia Di Stefano, Celia Díaz-Catalán, Kimberly C. Doell, Simone Dohle, Karen M. Douglas, Charlotte Dries, Dmitrii Dubrov, Małgorzata Dzimińska, Ullrich K. H. Ecker, Christian T. Elbaek, Mahmoud Elsherif, Benjamin Enke, Tom W. Etienne, Matthew Facciani, Antoinette Fage-Butler, Md. Zaki Faisal, Xiaoli Fan, Christina Farhart, Christoph Feldhaus, Marinus Ferreira, Stefan Feuerriegel, Helen Fischer, Jana Freundt, Malte Friese, Simon Fuglsang, Albina Gallyamova, Patricia Garrido-Vásquez, Mauricio E. Garrido Vásquez, Winfred Gatua, Oliver Genschow, Omid Ghasemi, Theofilos Gkinopoulos, Jamie L. Gloor, Ellen Goddard, Mario Gollwitzer, Claudia González-Brambila, Hazel Gordon, Dmitry Grigoryev, Gina M. Grimshaw, Lars Guenther, Håvard Haarstad, Dana Harari, Lelia N. Hawkins, Przemysław Hensel, Alma Cristal Hernández-Mondragón, Atar Herziger, Guanxiong Huang, Markus Huff, Mairéad Hurley, Nygmet Ibadildin, Maho Ishibashi, Mohammad Tarikul Islam, Younes Jeddi, Tao Jin, Charlotte A. Jones, Sebastian Jungkunz, Dominika Jurgiel, Zhangir Kabdulkair, Jo-Ju Kao, Sarah Kavassalis, John R. Kerr, Mariana Kitsa, Tereza Klabíková Rábová, Olivier Klein, Hoyoun Koh, Aki Koivula, Lilian Kojan, Elizaveta Komyaginskaya, Laura König, Lina Koppel, Kochav Koren Nobre Cavalcante, Alexandra Kosachenko, John Kotcher, Laura S. Kranz, Pradeep Krishnan, Silje Kristiansen, André Krouwel, Toon Kuppens, Eleni A. Kyza, Claus Lamm, Anthony Lantian, Aleksandra Lazić, Oscar Lecuona, Jean-Baptiste Légal, Zoe Leviston, Neil Levy, Amanda M. Lindkvist, Grégoire Lits, Andreas Löschel, Alberto López-Ortega, Carlos Lopez-Villavicencio, Nigel Mantou Lou, Chloe H. Lucas, Kristin Lunz-Trujillo, Mathew D. Marques, Sabrina J. Mayer, Ryan McKay, Hugo Mercier, Julia Metag, Taciano L. Milfont, Joanne M. Miller, Panagiotis Mitkidis, Fredy Monge-Rodríguez, Matt Motta, Iryna Mudra, Zarja Muršič, Jennifer Namutebi, Eryn J. Newman, Jonas P. Nitschke, Ntui-Njock Vincent Ntui, Daniel Nwogwugwu, Thomas Ostermann, Tobias Otterbring, Jaime Palmer-Hague, Myrto Pantazi, Philip Pärnamets, Paolo Parra Saiani, Mariola Paruzel-Czachura, Michal Parzuchowski, Yuri G. Pavlov, Adam R. Pearson, Myron A. Penner, Charlotte R. Pennington, Katerina Petkanopoulou, Marija M. Petrović, Jan Pfänder, Dinara Pisareva, Adam Ploszaj, Karolína Poliaková, Ekaterina Pronizius, Katarzyna Pypno-Blajda, Diwa Malaya A. Quiñones, Pekka Räsänen, Adrian Rauchfleisch, Felix G. Rebitschek, Cintia Refojo Seronero, Gabriel Rêgo, James P. Reynolds, Joseph Roche, Simone Rödder, Jan Philipp Röer, Robert M. Ross, Isabelle Ruin, Osvaldo Santos, Ricardo R. Santos, Philipp Schmid, Stefan Schulreich, Bermond Scoggins, Amena Sharaf, Justin Sheria Nfundiko, Emily Shuckburgh, Johan Six, Nevin Solak, Leonhard Späth, Bram Spruyt, Olivier Standaert, Samantha K. Stanley, Gert Storms, Noel Strahm, Stylianos Syropoulos, Barnabas Szaszi, Ewa Szumowska, Mikihito Tanaka, Claudia Teran-Escobar, Boryana Todorova, Abdoul Kafid Toko, Renata Tokrri, Daniel Toribio-Florez, Manos Tsakiris, Michael Tyrala, Özden Melis Uluğ, Ijeoma Chinwe Uzoma, Jochem van Noord, Christiana Varda, Steven Verheyen, Iris Vilares, Madalina Vlasceanu, Andreas von Bubnoff, Iain Walker, Izabela Warwas, Marcel Weber, Tim Weninger, Mareike Westfal, Florian Wintterlin, Adrian Dominik Wojcik, Ziqian Xia, Jinliang Xie, Ewa Zegler-Poleska, Amber Zenklusen, and Rolf A. Zwaan

Subjects
Science
Abstract

Abstract Science is integral to society because it can inform individual, government, corporate, and civil society decision-making on issues such as public health, new technologies or climate change. Yet, public distrust and populist sentiment challenge the relationship between science and society. To help researchers analyse the science-society nexus across different geographical and cultural contexts, we undertook a cross-sectional population survey resulting in a dataset of 71,922 participants in 68 countries. The data were collected between November 2022 and August 2023 as part of the global Many Labs study “Trust in Science and Science-Related Populism” (TISP). The questionnaire contained comprehensive measures for individuals’ trust in scientists, science-related populist attitudes, perceptions of the role of science in society, science media use and communication behaviour, attitudes to climate change and support for environmental policies, personality traits, political and religious views and demographic characteristics. Here, we describe the dataset, survey materials and psychometric properties of key variables. We encourage researchers to use this unique dataset for global comparative analyses on public perceptions of science and its role in society and policy-making.

Published
2025
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34. The global RNA-binding protein RbpB is a regulator of polysaccharide utilization in Bacteroides thetaiotaomicron

Author

Ann-Sophie Rüttiger, Daniel Ryan, Luisella Spiga, Vanessa Lamm-Schmidt, Gianluca Prezza, Sarah Reichardt, Madison Langford, Lars Barquist, Franziska Faber, Wenhan Zhu, and Alexander J. Westermann

Subjects
Science
Abstract

Abstract Paramount to human health, symbiotic bacteria in the gastrointestinal tract rely on the breakdown of complex polysaccharides to thrive in this sugar-deprived environment. Gut Bacteroides are metabolic generalists and deploy dozens of polysaccharide utilization loci (PULs) to forage diverse dietary and host-derived glycans. The expression of the multi-protein PUL complexes is tightly regulated at the transcriptional level. However, how PULs are orchestrated at translational level in response to the fluctuating levels of their cognate substrates is unknown. Here, we identify the RNA-binding protein RbpB and a family of noncoding RNAs as key players in post-transcriptional PUL regulation. We demonstrate that RbpB interacts with numerous cellular transcripts, including a paralogous noncoding RNA family comprised of 14 members, the FopS (family of paralogous sRNAs). Through a series of in-vitro and in-vivo assays, we reveal that FopS sRNAs repress the translation of SusC-like glycan transporters when substrates are limited—an effect antagonized by RbpB. Ablation of RbpB in Bacteroides thetaiotaomicron compromises colonization in the mouse gut in a diet-dependent manner. Together, this study adds to our understanding of RNA-coordinated metabolic control as an important factor contributing to the in-vivo fitness of predominant microbiota species in dynamic nutrient landscapes.

Published
2025
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35. Strongly positive amphicheiral knots with doubly symmetric diagrams

Author

Lamm, Christoph

Subjects
Mathematics - Geometric Topology, 57K10
Abstract

We determine the prime strongly positive amphicheiral knots up to 16 crossings and show that a large fraction of them admit knot diagrams with a double symmetry (rotational symmetry for strongly positive amphicheirality and an additional mirror symmetry for the ribbon property). The remaining knots are presented as `almost doubly symmetric' diagrams, defined as diagrams with double symmetry where exactly one symmetric pair of crossings is switched. We also find that the rosette knot 14a19470, which has period 7, is the first prime strongly positive amphicheiral knot in the knot tables which is not slice., Comment: 22 pages, version 2 with additions/corrections in Table 4/appendix and additional illustration in the introduction

Published
2023

36. Retail-786k: a Large-Scale Dataset for Visual Entity Matching

Author

Lamm, Bianca and Keuper, Janis

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Entity Matching (EM) defines the task of learning to group objects by transferring semantic concepts from example groups (=entities) to unseen data. Despite the general availability of image data in the context of many EM-problems, most currently available EM-algorithms solely rely on (textual) meta data. In this paper, we introduce the first publicly available large-scale dataset for "visual entity matching", based on a production level use case in the retail domain. Using scanned advertisement leaflets, collected over several years from different European retailers, we provide a total of ~786k manually annotated, high resolution product images containing ~18k different individual retail products which are grouped into ~3k entities. The annotation of these product entities is based on a price comparison task, where each entity forms an equivalence class of comparable products. Following on a first baseline evaluation, we show that the proposed "visual entity matching" constitutes a novel learning problem which can not sufficiently be solved using standard image based classification and retrieval algorithms. Instead, novel approaches which allow to transfer example based visual equivalent classes to new data are needed to address the proposed problem. The aim of this paper is to provide a benchmark for such algorithms. Information about the dataset, evaluation code and download instructions are provided under https://www.retail-786k.org/.

Published
2023

37. Reconstructing Thermal Quantum Quench Dynamics from Pure States

Author

Saroni, Jason, Lamm, Henry, Orth, Peter P., and Iadecola, Thomas

Subjects
Quantum Physics, Condensed Matter - Strongly Correlated Electrons, High Energy Physics - Lattice
Abstract

Simulating the nonequilibrium dynamics of thermal states is a fundamental problem across scales from high energy to condensed matter physics. Quantum computers may provide a way to solve this problem efficiently. Preparing a thermal state on a quantum computer is challenging, but there exist methods to circumvent this by computing a weighted sum of time-dependent matrix elements in a convenient basis. While the number of basis states can be large, in this work we show that it can be reduced by simulating only the largest density matrix elements by weight, capturing the density matrix to a specified precision. Leveraging Hamiltonian symmetries enables further reductions. This approach paves the way to more accurate thermal-state dynamics simulations on near-term quantum hardware., Comment: 8+4 pages, 6+3 figures

Published
2023
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38. Mechanical modeling of the maturation process for tissue-engineered implants: application to biohybrid heart valves

Author

Sesa, Mahmoud, Holthusen, Hagen, Lamm, Lukas, Böhm, Christian, Brepols, Tim, Jockenhövel, Stefan, and Reese, Stefanie

Subjects
Computer Science - Computational Engineering, Finance, and Science
Abstract

The development of tissue-engineered cardiovascular implants can improve the lives of large segments of our society who suffer from cardiovascular diseases. Regenerative tissues are fabricated using a process called tissue maturation. Furthermore, it is highly challenging to produce cardiovascular regenerative implants with sufficient mechanical strength to withstand the loading conditions within the human body. Therefore, biohybrid implants for which the regenerative tissue is reinforced by standard reinforcement material (e.g. textile or 3d printed scaffold) can be an interesting solution. In silico models can significantly contribute to characterizing, designing, and optimizing biohybrid implants. The first step towards this goal is to develop a computational model for the maturation process of tissue-engineered implants. This paper focuses on the mechanical modeling of textile-reinforced tissue-engineered cardiovascular implants. First, we propose an energy-based approach to compute the collagen evolution during the maturation process. Then, we apply the concept of structural tensors to model the anisotropic behavior of the extracellular matrix and the textile scaffold. Next, the newly developed material model is embedded into a special solid-shell finite element formulation with reduced integration. Finally, we use our framework to compute two structural problems: a pressurized shell construct and a tubular-shaped heart valve. The results show the ability of the model to predict collagen growth in response to the boundary conditions applied during the maturation process. Consequently, we can predict the implant's mechanical response, such as the deformation and stresses of the implant., Comment: Preprint submitted to Elsevier

Published
2023

39. Fine-Grained Product Classification on Leaflet Advertisements

Author

Ladwig, Daniel, Lamm, Bianca, and Keuper, Janis

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

In this paper, we describe a first publicly available fine-grained product recognition dataset based on leaflet images. Using advertisement leaflets, collected over several years from different European retailers, we provide a total of 41.6k manually annotated product images in 832 classes. Further, we investigate three different approaches for this fine-grained product classification task, Classification by Image, by Text, as well as by Image and Text. The approach "Classification by Text" uses the text extracted directly from the leaflet product images. We show, that the combination of image and text as input improves the classification of visual difficult to distinguish products. The final model leads to an accuracy of 96.4% with a Top-3 score of 99.2%. We release our code at https://github.com/ladwigd/Leaflet-Product-Classification.

Published
2023

40. Simulating $\mathbb{Z}_2$ lattice gauge theory on a quantum computer

Author

Charles, Clement, Gustafson, Erik J., Hardt, Elizabeth, Herren, Florian, Hogan, Norman, Lamm, Henry, Starecheski, Sara, Van de Water, Ruth S., and Wagman, Michael L.

Subjects
High Energy Physics - Lattice, Quantum Physics
Abstract

The utility of quantum computers for simulating lattice gauge theories is currently limited by the noisiness of the physical hardware. Various quantum error mitigation strategies exist to reduce the statistical and systematic uncertainties in quantum simulations via improved algorithms and analysis strategies. We perform quantum simulations of $1+1d$ $\mathbb{Z}_2$ gauge theory with matter to study the efficacy and interplay of different error mitigation methods: readout error mitigation, randomized compiling, rescaling, and dynamical decoupling. We compute Minkowski correlation functions in this confining gauge theory and extract the mass of the lightest spin-1 state from fits to their time dependence. Quantum error mitigation extends the range of times over which our correlation function calculations are accurate by a factor of six and is therefore essential for obtaining reliable masses., Comment: 20 Pages, 18 Figures

Published
2023

41. COVID‐19 Vaccination Before Initiating Rituximab Treatment Induces Strong Serological Response in Autoimmune Rheumatic Disease, Reducing Post‐Pandemic Concerns About the Impact of Rituximab

Author

Christian Ammitzbøll, Marianne Kragh Thomsen, Lars Erik Bartels, Cecilie Bo Hansen, Marie‐Louise From Hermansen, Mathias Hänel, Rasmus Klose‐Jensen, Mads Lamm Larsen, Morgan Oliver Lauritsen, Clara Elbæk Mistegaard, Susan Mikkelsen, Janne Bille Mønster Olesen, Esben Uggerby Næser, Morten Aagaard Nielsen, Christian Erikstrup, Peter Garred, Ellen‐Margrethe Hauge, and Anne Troldborg

Subjects
Diseases of the musculoskeletal system, RC925-935
Abstract

Objective Rituximab (RTX)‐treated patients exhibit suboptimal responses to COVID‐19 vaccines. However, existing research primarily involves patients already receiving RTX when vaccines were introduced, failing to account for the current landscape where patients are vaccinated before initiating RTX. Our objective was to compare the serological response to COVID‐19 vaccines in patients vaccinated before or after RTX initiation. Methods We included 254 RTX‐treated patients with autoimmune inflammatory rheumatic diseases (AIIRDs) and 113 blood donors (BDs) in a retrospective, observational cohort study. Patients were categorized based on the timing of RTX treatment relative to primary COVID‐19 vaccination. Serological vaccine responses were assessed using three immunoassays, and logistic regression analysis was used to identify predictors of serological response. Results Patients vaccinated before initiating RTX treatment had significantly higher seroconversion rates of SARS‐CoV‐2 immunoglobulin G (87%) and neutralizing antibodies (91%) compared with those receiving RTX before and after vaccination (n = 132) (61% and 65%, respectively). In the logistic regression analysis, a positive serological response was associated with the number of vaccines administered >9 months after the last RTX treatment. Patients receiving the highest number of vaccines with >9 months after RTX showed a response comparable to that of the BDs. Conclusion Vaccinating before RTX initiation yields a robust serological response in patients with AIIRDs. Furthermore, we highlight the reversibility of antibody impairment after RTX treatment cessation, provided that adequate vaccinations occur within a minimum of 9 months after RTX. Our findings offer essential insights for clinical decision‐making regarding COVID‐19 vaccination and RTX treatment, alleviating concerns about future RTX use.

Published
2024
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42. Quantum mean estimation for lattice field theory

Author

Gustafson, Erik J., Lamm, Henry, and Unmuth-Yockey, Judah

Subjects
High Energy Physics - Lattice, Quantum Physics
Abstract

We demonstrate the quantum mean estimation algorithm on Euclidean lattice field theories. This shows a quadratic advantage over Monte Carlo methods which persists even in presence of a sign problem, and is insensitive to critical slowing down. The algorithm is used to compute $\pi$ with and without a sign problem, a toy U(1) gauge theory model, and the Ising model. The effect of $R_{Z}$-gate synthesis errors on a future fault-tolerant quantum computer is investigated., Comment: 14 pages, 18 figures

Published
2023
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43. Stylistic features of the translation of the poem by A. Chobat 'Vaclav Ivanovsky' into Russian

Author

Lamm Maria Andreevna

Subjects
polish-belarusian borderland, kresy, vaclav ivanovsky, rock poetry, literary translation, History of scholarship and learning. The humanities, AZ20-999
Abstract

The paper studies the features of the literary translation of the Belarusian poem and song “Vaclav Ivanovsky” into the Russian language. The translation considered the linguistic features of the poem translation between closely related languages and the genre originality of rock poetry. The translation was recorded as a song. A survey was conducted among the bearers of Russian culture in order to identify the features of the associative perception of the song text dedicated to a certain historical figure in a particular period.

Published
2024

44. The conserved noncoding RNA ModT coordinates growth and virulence in Clostridioides difficile.

Author

Tina Lenče, Johannes Sulzer, Kilian Andress, Anne-Sophie Gribling-Burrer, Vanessa Lamm-Schmidt, Lars Barquist, Redmond P Smyth, and Franziska Faber

Subjects
Biology (General), QH301-705.5
Abstract

Bacterial noncoding RNAs fulfill a variety of cellular functions as catalysts, as scaffolds in protein complexes or as regulators of gene expression. They often exhibit complex tertiary structures that are a key determinant of their biochemical function. Here, we characterize the structured "raiA motif" RNA from Clostridioides difficile, which is conserved in more than 2,500 bacterial species from the phyla Bacillota and Actinomycetota. We show that its transcript abundance and stability in exponentially growing bacteria rivals that of ribosomal RNAs. Deletion of the "raiA motif" RNA is associated with delayed transition into stationary phase, and changes in stationary phase pathways such as spore formation, hence we rename it ModT (modulator of transition phase). Mechanistically, we show that ModT-mediated changes in cellular cyclic di-GMP levels are linked to the pronounced sporulation defect in the modT mutant. Importantly, we show that expression profiles and isoform patterns of ModT are conserved in Clostridium perfringens and Paeniclostridium sordellii, and that these orthologs can functionally complement ModT in C. difficile. Chemical structure probing of ModT in vivo reveals dynamic refolding and provides initial evidence for a potential association of ModT with proteins. In summary, our findings indicate that ModT fulfills a conserved role in regulating growth transitions in bacteria and provide a crucial step towards delineating its molecular mechanism.

Published
2024
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45. Exploring Social Media Information Seeking During the COVID-19 Pandemic to Inform Science and Health Communication During a Crisis

Author

Fallys Masambuka-Kanchewa, Alexa J. Lamm, and Millicent Akinyi Oyugi

Subjects
History of scholarship and learning. The humanities, AZ20-999, Social Sciences
Abstract

The COVID-19 pandemic and the resulting lockdowns increased access to specific social media usage, underscoring the importance of health science communicators sharing accurate information on popular platforms. This study aimed to investigate social media information-seeking behaviors during the COVID-19 outbreak when states were under lockdown orders. The study described respondents’ perceptions of COVID-19 information on social media, types of social media platforms used, people respondents connected with, and the relationship between social media use and the groups respondents connected with. An online survey was administered to 1,048 respondents in the United States via Qualtrics using non-probability opt-in sampling to capture information-seeking behaviors using researcher-adapted scales. The information could help determine the potential of leveraging online social networks to communicate credible health science messages. The results showed that over 70% of the respondents felt overwhelmed while searching for COVID-19 information, had difficulty accessing or interpreting additional information, and sometimes avoided news about COVID-19. Also, Facebook, Instagram, and Twitter were the most popular social media platforms for COVID-19 information. Notably, Facebook was the most widely used platform during lockdowns. Meanwhile, respondents primarily used Facebook to connect with friends and family during the pandemic, and those with more social networks accessed social media platforms more frequently. The findings emphasize the crucial role of Facebook in sharing trustworthy information during the COVID-19 pandemic. They also underscore the need for strategies to help individuals navigate the overwhelming volume of information, including misinformation on social media platforms, especially in times of crisis.

Published
2024
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46. Sleep quality, sleep quantity, and sleep timing: contrasts in Austrian and U.S. college students

Author

June J. Pilcher, Elizabeth G. Rummel, and Claus Lamm

Subjects
sleep habits, timing of sleep, sleep duration, cross-national, cross-culture, environment, Medicine
Abstract

ObjectiveThe current study compared self-reported sleep in undergraduate students in Austria and the United States.MethodsThe Pittsburgh Sleep Quality Index responses from 292 Austrian university students (237 females) and 313 U.S. university students (189 females) were analyzed. In addition to the standard scoring procedure for the scale and the individual components of the scale, the data were also evaluated as separate sleep quality and sleep quantity factors using ANOVAs. Sleep timing (bedtime, wake-time, and midpoint) was also examined using independent t-tests.ResultsAustrian students reported better sleep quality and quantity than the U.S. students. In addition, Austrian students had more sleep disturbances and took longer to fall asleep but slept longer and used less sleep medication than U.S. students. Austrian students also went to bed earlier and woke up later than U.S. students.ConclusionsThe current results indicate that sleep in undergraduate students varies across countries. A major difference between the two groups of students was the university setting with the Austrian students living in a large urban area and the U.S. students living in a rural college town, suggesting that the environment could impact student sleep and sleep choices. Finally, the current data indicate that examining sleep quality as a separate factor from sleep quantity provides additional information about sleep in college students. Better documenting sleep and sleep habits in college students across different countries can address important differences that universities and societies can use to help improve sleep and wellbeing in their students.

Published
2024
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47. Robustness of Gauge Digitization to Quantum Noise

Author

Gustafson, Erik J. and Lamm, Henry

Subjects
High Energy Physics - Lattice, Quantum Physics
Abstract

Quantum noise limits the use of quantum memory in high energy physics simulations. In particular, it breaks the gauge symmetry of stored quantum states. We examine this effect for abelian and nonabelian theories and demonstrate that optimizing the digitization of gauge theories to quantum memory to account for noise channels can extend the lifetime before complete loss of gauge symmetry by $2-10\times$ over some other digitizations. These constructions also allow for quantum error correction to integrate the symmetries of quantum fields and prioritize the largest gauge violations., Comment: 5 pages, 3 figures, 4 tables

Published
2023

48. Diffusive stability and self-similar decay for the harmonic map heat flow

Author

Lamm, Tobias and Schneider, Guido

Subjects
Mathematics - Differential Geometry, Mathematics - Analysis of PDEs
Abstract

In this paper we study the harmonic map heat flow on the euclidean space $\mathbb{R}^d$ and we show an unconditional uniqueness result for maps with small initial data in the homogeneous Besov space $\dot{B}^{\frac{d}{p}}_{p,\infty}(\mathbb{R}^d)$ where $d

Published
2023

49. The Future of California Consumer Energy Finance

Author

Campbell, Andrew, Lamm, Ted, and Hoff, Katherine

Subjects
consumer energy finance, building decarbonization, equity
Abstract

Based on program analysis, literature review, expert interviews, and an October 2022 expert roundtable, this report identifies a set of conclusions and recommendations for California policymakers. We offer recommendations in distinct but overlapping areas:• Expanding consumer energy financing programs• Addressing the needs of lower- and moderate-income residents• Accelerating building decarbonization toward California’s 2045 goal• Ensuring equity in program revenue sources• Improving program design through learningThese recommendations all reflect a core insight developed from the research and outreach process: that the enormous size of California’s building decarbonization need calls for significant infusions of private capital, and financing programs can be a mechanism to attract some of this capital. However, consumer energy finance programs are not yet operating on a scale that matches the challenge. Even at their most robust and effective these programs will likely only fund a portion of the needed retrofits and are not always appropriate for lowerincome residents, who will require access to alternative measures involving minimal or zero repayment obligations. And effectively taking advantage of newly available federal Inflation Reduction incentives will rely on state programs that facilitate layering of funds from an array of sources.A central recommendation across this report’s sections is that state legislators and financing program administrators consider alternatives to utility ratepayer funds as the core revenue source for credit enhancement. Shifting from ratepayer funds to alternative sources including taxpayer funds, federal funds, and philanthropic sources could potentially help scale up the GoGreen Financing programs’ reach and flexibility across utility service territories, fuel sources, and eligible measures; facilitate more seamless integration with other state programs; reduce procedural barriers to rapid adaptation to market and technology developments; and advance equity by relying on a more progressive revenue source

Published
2023

50. Quantum Simulation for High-Energy Physics

Author

Bauer, Christian W, Davoudi, Zohreh, Balantekin, A Baha, Bhattacharya, Tanmoy, Carena, Marcela, de Jong, Wibe A, Draper, Patrick, El-Khadra, Aida, Gemelke, Nate, Hanada, Masanori, Kharzeev, Dmitri, Lamm, Henry, Li, Ying-Ying, Liu, Junyu, Lukin, Mikhail, Meurice, Yannick, Monroe, Christopher, Nachman, Benjamin, Pagano, Guido, Preskill, John, Rinaldi, Enrico, Roggero, Alessandro, Santiago, David I, Savage, Martin J, Siddiqi, Irfan, Siopsis, George, Van Zanten, David, Wiebe, Nathan, Yamauchi, Yukari, Yeter-Aydeniz, Kübra, and Zorzetti, Silvia

Subjects
Quantum Physics, Physical Sciences, Affordable and Clean Energy
Abstract

It is for the first time that quantum simulation for high-energy physics (HEP) is studied in the U.S. decadal particle-physics community planning, and in fact until recently, this was not considered a mainstream topic in the community. This fact speaks of a remarkable rate of growth of this subfield over the past few years, stimulated by the impressive advancements in quantum information sciences (QIS) and associated technologies over the past decade, and the significant investment in this area by the government and private sectors in the U.S. and other countries. High-energy physicists have quickly identified problems of importance to our understanding of nature at the most fundamental level, from tiniest distances to cosmological extents, that are intractable with classical computers but may benefit from quantum advantage. They have initiated, and continue to carry out, a vigorous program in theory, algorithm, and hardware co-design for simulations of relevance to the HEP mission. This Roadmap is an attempt to bring this exciting and yet challenging area of research to the spotlight, and to elaborate on what the promises, requirements, challenges, and potential solutions are over the next decade and beyond.

Published
2023

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