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1. Exploring Memorization and Copyright Violation in Frontier LLMs: A Study of the New York Times v. OpenAI 2023 Lawsuit

Author: Freeman, Joshua, Rippe, Chloe, Debenedetti, Edoardo, and Andriushchenko, Maksym
Subjects: Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract: Copyright infringement in frontier LLMs has received much attention recently due to the New York Times v. OpenAI lawsuit, filed in December 2023. The New York Times claims that GPT-4 has infringed its copyrights by reproducing articles for use in LLM training and by memorizing the inputs, thereby publicly displaying them in LLM outputs. Our work aims to measure the propensity of OpenAI's LLMs to exhibit verbatim memorization in its outputs relative to other LLMs, specifically focusing on news articles. We discover that both GPT and Claude models use refusal training and output filters to prevent verbatim output of the memorized articles. We apply a basic prompt template to bypass the refusal training and show that OpenAI models are currently less prone to memorization elicitation than models from Meta, Mistral, and Anthropic. We find that as models increase in size, especially beyond 100 billion parameters, they demonstrate significantly greater capacity for memorization. Our findings have practical implications for training: more attention must be placed on preventing verbatim memorization in very large models. Our findings also have legal significance: in assessing the relative memorization capacity of OpenAI's LLMs, we probe the strength of The New York Times's copyright infringement claims and OpenAI's legal defenses, while underscoring issues at the intersection of generative AI, law, and policy.
Published: 2024

2. Measuring Non-Adversarial Reproduction of Training Data in Large Language Models

Author: Aerni, Michael, Rando, Javier, Debenedetti, Edoardo, Carlini, Nicholas, Ippolito, Daphne, and Tramèr, Florian
Subjects: Computer Science - Computation and Language, Computer Science - Machine Learning
Abstract: Large language models memorize parts of their training data. Memorizing short snippets and facts is required to answer questions about the world and to be fluent in any language. But models have also been shown to reproduce long verbatim sequences of memorized text when prompted by a motivated adversary. In this work, we investigate an intermediate regime of memorization that we call non-adversarial reproduction, where we quantify the overlap between model responses and pretraining data when responding to natural and benign prompts. For a variety of innocuous prompt categories (e.g., writing a letter or a tutorial), we show that up to 15% of the text output by popular conversational language models overlaps with snippets from the Internet. In worst cases, we find generations where 100% of the content can be found exactly online. For the same tasks, we find that human-written text has far less overlap with Internet data. We further study whether prompting strategies can close this reproduction gap between models and humans. While appropriate prompting can reduce non-adversarial reproduction on average, we find that mitigating worst-case reproduction of training data requires stronger defenses -- even for benign interactions.
Published: 2024

3. Adversarial Search Engine Optimization for Large Language Models

Author: Nestaas, Fredrik, Debenedetti, Edoardo, and Tramèr, Florian
Subjects: Computer Science - Cryptography and Security, Computer Science - Machine Learning
Abstract: Large Language Models (LLMs) are increasingly used in applications where the model selects from competing third-party content, such as in LLM-powered search engines or chatbot plugins. In this paper, we introduce Preference Manipulation Attacks, a new class of attacks that manipulate an LLM's selections to favor the attacker. We demonstrate that carefully crafted website content or plugin documentations can trick an LLM to promote the attacker products and discredit competitors, thereby increasing user traffic and monetization. We show this leads to a prisoner's dilemma, where all parties are incentivized to launch attacks, but the collective effect degrades the LLM's outputs for everyone. We demonstrate our attacks on production LLM search engines (Bing and Perplexity) and plugin APIs (for GPT-4 and Claude). As LLMs are increasingly used to rank third-party content, we expect Preference Manipulation Attacks to emerge as a significant threat.
Published: 2024

4. AgentDojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents

Author: Debenedetti, Edoardo, Zhang, Jie, Balunović, Mislav, Beurer-Kellner, Luca, Fischer, Marc, and Tramèr, Florian
Subjects: Computer Science - Cryptography and Security, Computer Science - Machine Learning
Abstract: AI agents aim to solve complex tasks by combining text-based reasoning with external tool calls. Unfortunately, AI agents are vulnerable to prompt injection attacks where data returned by external tools hijacks the agent to execute malicious tasks. To measure the adversarial robustness of AI agents, we introduce AgentDojo, an evaluation framework for agents that execute tools over untrusted data. To capture the evolving nature of attacks and defenses, AgentDojo is not a static test suite, but rather an extensible environment for designing and evaluating new agent tasks, defenses, and adaptive attacks. We populate the environment with 97 realistic tasks (e.g., managing an email client, navigating an e-banking website, or making travel bookings), 629 security test cases, and various attack and defense paradigms from the literature. We find that AgentDojo poses a challenge for both attacks and defenses: state-of-the-art LLMs fail at many tasks (even in the absence of attacks), and existing prompt injection attacks break some security properties but not all. We hope that AgentDojo can foster research on new design principles for AI agents that solve common tasks in a reliable and robust manner.. We release the code for AgentDojo at https://github.com/ethz-spylab/agentdojo., Comment: Updated version after fixing a bug in the Llama implementation and updating the travel suite
Published: 2024

5. Dataset and Lessons Learned from the 2024 SaTML LLM Capture-the-Flag Competition

Author: Debenedetti, Edoardo, Rando, Javier, Paleka, Daniel, Florin, Silaghi Fineas, Albastroiu, Dragos, Cohen, Niv, Lemberg, Yuval, Ghosh, Reshmi, Wen, Rui, Salem, Ahmed, Cherubin, Giovanni, Zanella-Beguelin, Santiago, Schmid, Robin, Klemm, Victor, Miki, Takahiro, Li, Chenhao, Kraft, Stefan, Fritz, Mario, Tramèr, Florian, Abdelnabi, Sahar, and Schönherr, Lea
Subjects: Computer Science - Cryptography and Security, Computer Science - Artificial Intelligence
Abstract: Large language model systems face important security risks from maliciously crafted messages that aim to overwrite the system's original instructions or leak private data. To study this problem, we organized a capture-the-flag competition at IEEE SaTML 2024, where the flag is a secret string in the LLM system prompt. The competition was organized in two phases. In the first phase, teams developed defenses to prevent the model from leaking the secret. During the second phase, teams were challenged to extract the secrets hidden for defenses proposed by the other teams. This report summarizes the main insights from the competition. Notably, we found that all defenses were bypassed at least once, highlighting the difficulty of designing a successful defense and the necessity for additional research to protect LLM systems. To foster future research in this direction, we compiled a dataset with over 137k multi-turn attack chats and open-sourced the platform.
Published: 2024

6. AI Risk Management Should Incorporate Both Safety and Security

Author: Qi, Xiangyu, Huang, Yangsibo, Zeng, Yi, Debenedetti, Edoardo, Geiping, Jonas, He, Luxi, Huang, Kaixuan, Madhushani, Udari, Sehwag, Vikash, Shi, Weijia, Wei, Boyi, Xie, Tinghao, Chen, Danqi, Chen, Pin-Yu, Ding, Jeffrey, Jia, Ruoxi, Ma, Jiaqi, Narayanan, Arvind, Su, Weijie J, Wang, Mengdi, Xiao, Chaowei, Li, Bo, Song, Dawn, Henderson, Peter, and Mittal, Prateek
Subjects: Computer Science - Cryptography and Security, Computer Science - Artificial Intelligence
Abstract: The exposure of security vulnerabilities in safety-aligned language models, e.g., susceptibility to adversarial attacks, has shed light on the intricate interplay between AI safety and AI security. Although the two disciplines now come together under the overarching goal of AI risk management, they have historically evolved separately, giving rise to differing perspectives. Therefore, in this paper, we advocate that stakeholders in AI risk management should be aware of the nuances, synergies, and interplay between safety and security, and unambiguously take into account the perspectives of both disciplines in order to devise mostly effective and holistic risk mitigation approaches. Unfortunately, this vision is often obfuscated, as the definitions of the basic concepts of "safety" and "security" themselves are often inconsistent and lack consensus across communities. With AI risk management being increasingly cross-disciplinary, this issue is particularly salient. In light of this conceptual challenge, we introduce a unified reference framework to clarify the differences and interplay between AI safety and AI security, aiming to facilitate a shared understanding and effective collaboration across communities.
Published: 2024

7. JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models

Author: Chao, Patrick, Debenedetti, Edoardo, Robey, Alexander, Andriushchenko, Maksym, Croce, Francesco, Sehwag, Vikash, Dobriban, Edgar, Flammarion, Nicolas, Pappas, George J., Tramer, Florian, Hassani, Hamed, and Wong, Eric
Subjects: Computer Science - Cryptography and Security, Computer Science - Machine Learning
Abstract: Jailbreak attacks cause large language models (LLMs) to generate harmful, unethical, or otherwise objectionable content. Evaluating these attacks presents a number of challenges, which the current collection of benchmarks and evaluation techniques do not adequately address. First, there is no clear standard of practice regarding jailbreaking evaluation. Second, existing works compute costs and success rates in incomparable ways. And third, numerous works are not reproducible, as they withhold adversarial prompts, involve closed-source code, or rely on evolving proprietary APIs. To address these challenges, we introduce JailbreakBench, an open-sourced benchmark with the following components: (1) an evolving repository of state-of-the-art adversarial prompts, which we refer to as jailbreak artifacts; (2) a jailbreaking dataset comprising 100 behaviors -- both original and sourced from prior work (Zou et al., 2023; Mazeika et al., 2023, 2024) -- which align with OpenAI's usage policies; (3) a standardized evaluation framework at https://github.com/JailbreakBench/jailbreakbench that includes a clearly defined threat model, system prompts, chat templates, and scoring functions; and (4) a leaderboard at https://jailbreakbench.github.io/ that tracks the performance of attacks and defenses for various LLMs. We have carefully considered the potential ethical implications of releasing this benchmark, and believe that it will be a net positive for the community., Comment: The camera-ready version of JailbreakBench v1.0 (accepted at NeurIPS 2024 Datasets and Benchmarks Track): more attack artifacts, more test-time defenses, a more accurate jailbreak judge (Llama-3-70B with a custom prompt), a larger dataset of human preferences for selecting a jailbreak judge (300 examples), an over-refusal evaluation dataset, a semantic refusal judge based on Llama-3-8B
Published: 2024

8. Scaling Compute Is Not All You Need for Adversarial Robustness

Author: Debenedetti, Edoardo, Wan, Zishen, Andriushchenko, Maksym, Sehwag, Vikash, Bhardwaj, Kshitij, and Kailkhura, Bhavya
Subjects: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Cryptography and Security
Abstract: The last six years have witnessed significant progress in adversarially robust deep learning. As evidenced by the CIFAR-10 dataset category in RobustBench benchmark, the accuracy under $\ell_\infty$ adversarial perturbations improved from 44\% in \citet{Madry2018Towards} to 71\% in \citet{peng2023robust}. Although impressive, existing state-of-the-art is still far from satisfactory. It is further observed that best-performing models are often very large models adversarially trained by industrial labs with significant computational budgets. In this paper, we aim to understand: ``how much longer can computing power drive adversarial robustness advances?" To answer this question, we derive \emph{scaling laws for adversarial robustness} which can be extrapolated in the future to provide an estimate of how much cost we would need to pay to reach a desired level of robustness. We show that increasing the FLOPs needed for adversarial training does not bring as much advantage as it does for standard training in terms of performance improvements. Moreover, we find that some of the top-performing techniques are difficult to exactly reproduce, suggesting that they are not robust enough for minor changes in the training setup. Our analysis also uncovers potentially worthwhile directions to pursue in future research. Finally, we make our benchmarking framework (built on top of \texttt{timm}~\citep{rw2019timm}) publicly available to facilitate future analysis in efficient robust deep learning.
Published: 2023

9. First report on the helminthfauna of the yellow-necked mouse, Apodemus flavicollis, in the Iberian Peninsula

Author: Debenedetti Á. L., Sainz-Elipe S., Sáez-Durán S., Galicia D., Imaz A., Galán-Puchades M. T., and Fuentes M. V.
Subjects: helminth community, apodemus flavicollis, yellow-necked mouse, erro river valley, iberian peninsula, Microbiology, QR1-502
Abstract: Information about the prevalence of helminth parasites of the yellow-necked mouse, Apodemus flavicollis, in the Iberian Peninsula is almost non-existent and there is no reliable data reported from Spain. Fourteen A. flavicollis from the Erro River valley (Navarre, Spain) were examined for endoparasites, between February 2001 and July 2002. Thirteen specimens (92.9 %) of the total sample were parasitized by at least one of the following six helminth species: one trematode (Corrigia vitta), one cestode (Taenia parva larvae) and four nematodes (Trichuris muris, Calodium hepaticum, Heligmosomoides polygyrus and Syphacia stroma). This is the first report about the helminthfauna of A. flavicollis in the Iberian Peninsula. Nevertheless, a larger number of hosts should be analysed to complete these preliminary results and to adequately characterize the helminth community of this rodent. The finding of C. hepaticum, the causative agent of human capillarosis, stands out.
Published: 2016
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10. Privacy Side Channels in Machine Learning Systems

Author: Debenedetti, Edoardo, Severi, Giorgio, Carlini, Nicholas, Choquette-Choo, Christopher A., Jagielski, Matthew, Nasr, Milad, Wallace, Eric, and Tramèr, Florian
Subjects: Computer Science - Cryptography and Security, Computer Science - Machine Learning
Abstract: Most current approaches for protecting privacy in machine learning (ML) assume that models exist in a vacuum. Yet, in reality, these models are part of larger systems that include components for training data filtering, output monitoring, and more. In this work, we introduce privacy side channels: attacks that exploit these system-level components to extract private information at far higher rates than is otherwise possible for standalone models. We propose four categories of side channels that span the entire ML lifecycle (training data filtering, input preprocessing, output post-processing, and query filtering) and allow for enhanced membership inference, data extraction, and even novel threats such as extraction of users' test queries. For example, we show that deduplicating training data before applying differentially-private training creates a side-channel that completely invalidates any provable privacy guarantees. We further show that systems which block language models from regenerating training data can be exploited to exfiltrate private keys contained in the training set--even if the model did not memorize these keys. Taken together, our results demonstrate the need for a holistic, end-to-end privacy analysis of machine learning systems., Comment: USENIX Security 2024
Published: 2023

11. Critical behavior in a chiral molecular model

Author: Piaggi, Pablo M., Car, Roberto, Stillinger, Frank H., and Debenedetti, Pablo G.
Subjects: Condensed Matter - Statistical Mechanics, Condensed Matter - Soft Condensed Matter
Abstract: Understanding the condensed-phase behavior of chiral molecules is important in biology, as well as in a range of technological applications, such as the manufacture of pharmaceuticals. Here, we use molecular dynamics simulations to study a chiral four-site molecular model that exhibits a second-order symmetry-breaking phase transition from a supercritical racemic liquid, into subcritical D-rich and L-rich liquids. We determine the infinite-size critical temperature using the fourth-order Binder cumulant, and we show that the finite-size scaling behavior of the order parameter is compatible with the 3D Ising universality class. We also study the spontaneous D-rich to L-rich transition at a slightly subcritical temperature $T\approx0.985 T_c$ and our findings indicate that the free energy barrier for this transformation increases with system size as $N^{2/3}$ where $N$ is the number of molecules, consistent with a surface-dominated phenomenon. The critical behavior observed herein suggests a mechanism for chirality selection in which a liquid of chiral molecules spontaneously forms a phase enriched in one of the two enantiomers as the temperature is lowered below the critical point. Furthermore, the increasing free energy barrier with system size indicates that fluctuations between the L-rich and D-rich phases are suppressed as the size of the system increases, trapping it in one of the two enantiomerically-enriched phases. Such a process could provide the basis for an alternative explanation for the origin of biological homochirality. We also conjecture the possibility of observing nucleation at subcritical temperatures under the action of a suitable chiral external field., Comment: 9 pages, 7 figures
Published: 2023
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12. Evading Black-box Classifiers Without Breaking Eggs

Author: Debenedetti, Edoardo, Carlini, Nicholas, and Tramèr, Florian
Subjects: Computer Science - Cryptography and Security, Computer Science - Machine Learning, Statistics - Machine Learning
Abstract: Decision-based evasion attacks repeatedly query a black-box classifier to generate adversarial examples. Prior work measures the cost of such attacks by the total number of queries made to the classifier. We argue this metric is flawed. Most security-critical machine learning systems aim to weed out "bad" data (e.g., malware, harmful content, etc). Queries to such systems carry a fundamentally asymmetric cost: queries detected as "bad" come at a higher cost because they trigger additional security filters, e.g., usage throttling or account suspension. Yet, we find that existing decision-based attacks issue a large number of "bad" queries, which likely renders them ineffective against security-critical systems. We then design new attacks that reduce the number of bad queries by $1.5$-$7.3\times$, but often at a significant increase in total (non-bad) queries. We thus pose it as an open problem to build black-box attacks that are more effective under realistic cost metrics., Comment: Code at https://github.com/ethz-privsec/realistic-adv-examples. Accepted at IEEE SaTML 2024
Published: 2023

13. Atomically smooth films of CsSb: a chemically robust visible light photocathode

Author: Parzyck, C. T., Pennington, C. A., DeBenedetti, W. J. I., Balajka, J., Echeverria, E., Paik, H., Moreschini, L., Faeth, B. D., Hu, C., Nangoi, J. K., Anil, V., Arias, T. A., Hines, M. A., Schlom, D. G., Galdi, A., Shen, K. M., and Maxson, J. M.
Subjects: Physics - Accelerator Physics, Condensed Matter - Materials Science
Abstract: Alkali antimonide semiconductor photocathodes provide a promising platform for the generation of high brightness electron beams, which are necessary for the development of cutting-edge probes including x-ray free electron lasers and ultrafast electron diffraction. However, to harness the intrinsic brightness limits in these compounds, extrinsic degrading factors, including surface roughness and contamination, must be overcome. By exploring the growth of CsxSb thin films monitored by in situ electron diffraction, the conditions to reproducibly synthesize atomically smooth films of CsSb on 3C-SiC (100) and graphene coated TiO2 (110) substrates are identified, and detailed structural, morphological, and electronic characterization is presented. These films combine high quantum efficiency in the visible (up to 1.2% at 400 nm), an easily accessible photoemission threshold of 550 nm, low surface roughness (down to 600 pm on a 1 um scale), and a robustness against oxidation up to 15 times greater then Cs3Sb. These properties suggest that CsSb has the potential to operate as an alternative to Cs$_3$Sb in electron source applications where the demands of the vacuum environment might otherwise preclude the use of traditional alkali antimonides., Comment: 11 pages, 6 figures, 1 table
Published: 2023
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14. A first-principles machine-learning force field for heterogeneous ice nucleation on microcline feldspar

Author: Piaggi, Pablo M., Selloni, Annabella, Panagiotopoulos, Athanassios Z., Car, Roberto, and Debenedetti, Pablo G.
Subjects: Condensed Matter - Materials Science, Condensed Matter - Statistical Mechanics
Abstract: The formation of ice in the atmosphere affects precipitation and cloud properties, and plays a key role in the climate of our planet. Although ice can form directly from liquid water at deeply supercooled conditions, the presence of foreign particles can aid ice formation at much warmer temperatures. Over the past decade, experiments have highlighted the remarkable efficiency of feldspar minerals as ice nuclei compared to other particles present in the atmosphere. However, the exact mechanism of ice formation on feldspar surfaces has yet to be fully understood. Here, we develop a first-principles machine-learning model for the potential energy surface aimed at studying ice nucleation at microcline feldspar surfaces. The model is able to reproduce with high fidelity the energies and forces derived from density-functional theory (DFT) based on the SCAN exchange and correlation functional. We apply the machine-learning force field to study different fully-hydroxylated terminations of the (100), (010), and (001) surfaces of microcline exposed to vacuum. Our calculations suggest that terminations that do not minimize the number of broken bonds are preferred in vacuum. We also study the structure of supercooled liquid water in contact with microcline surfaces, and find that water density correlations extend up to around 1 nm from the surfaces. Finally, we show that the force field maintains a high accuracy during the simulation of ice formation at microcline surfaces, even for large systems of around 30,000 atoms. Future work will be directed towards the calculation of nucleation free energy barriers and rates using the force field developed herein, and understanding the role of different microcline surfaces on ice nucleation., Comment: 12 pages, 6 figures
Published: 2023
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15. Language Validation and Cultural Adaptation of the Italian Version of the Family Caregiver Quality of Life Scale

Author: Simone Debenedetti, Simone Cosmai, Daniela Cattani, Stefano Mancin, Giovanni Cangelosi, Fabio Petrelli, and Beatrice Mazzoleni
Subjects: heart failure, quality of life, caregiver, linguistic validation, nursing assessment scale, Nursing, RT1-120
Abstract: Background: Heart failure significantly impacts healthcare systems and society, affecting quality of life (QoL) due to its symptoms and continuous care needs. Nurses are crucial in managing heart failure, supporting both patients and caregivers who face physical, emotional, social, and spiritual challenges. The Family Caregiver Quality of Life (FAMQOL) scale evaluates caregivers’ QoL across all dimensions. This study aims to translate and culturally adapt the FAMQOL from English to Italian, enhancing its utility in nursing research and practice to better identify and support caregiver well-being. Methods: Following EORTC guidelines (2017), the FAMQOL underwent linguistic validation and cultural adaptation. This included independent forward translations from English to Italian, back translations, and reconciliation discussions to produce a testable translation. A pilot test with 15 caregivers assessed the questionnaire’s acceptability and comprehensibility. Results: Linguistic adjustments ensured the questionnaire’s understandability in Italian. Interviews confirmed its acceptability and comprehensibility, with minor modifications enhancing clarity. Conclusions: The translation process successfully adapted the FAMQOL for Italian caregivers. This tool is essential for nursing research and practice, providing a culturally relevant assessment of the burden of care. It allows targeted interventions to support health workers, intercepting the QoL of caregivers early and, consequently, the well-being of patients with heart failure.
Published: 2024
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16. Melting curves of ice polymorphs in the vicinity of the liquid-liquid critical point

Author: Piaggi, Pablo M., Gartner III, Thomas E., Car, Roberto, and Debenedetti, Pablo G.
Subjects: Condensed Matter - Statistical Mechanics, Condensed Matter - Soft Condensed Matter, Physics - Chemical Physics
Abstract: The possible existence of a liquid-liquid critical point in deeply supercooled water has been a subject of debate in part due to the challenges associated with providing definitive experimental evidence. Pioneering work by Mishima and Stanley [Nature 392, 164 (1998) and Phys. Rev. Lett. 85, 334 (2000)] sought to shed light on this problem by studying the melting curves of different ice polymorphs and their metastable continuation in the vicinity of the expected location of the liquid-liquid transition and its associated critical point. Based on the continuous or discontinuous changes in slope of the melting curves, Mishima suggested that the liquid-liquid critical point lies between the melting curves of ice III and ice V. Here, we explore this conjecture using molecular dynamics simulations with a purely-predictive machine learning model based on ab initio quantum-mechanical calculations. We study the melting curves of ices III, IV, V, VI, and XIII using this model and find that the melting lines of all the studied ice polymorphs are supercritical and do not intersect the liquid-liquid transition locus. We also find a pronounced, yet continuous, change in slope of the melting lines upon crossing of the locus of maximum compressibility of the liquid. Finally, we analyze critically the literature in light of our findings, and conclude that the scenario in which melting curves are supercritical is favored by the most recent computational and experimental evidence. Thus, although the preponderance of experimental and computational evidence is consistent with the existence of a second critical point in water, the behavior of the melting lines of ice polymorphs does not provide strong evidence in support of this viewpoint, according to our calculations., Comment: 21 pages, 4 figures, supplementary information
Published: 2023
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17. Evading Black-box Classifiers Without Breaking Eggs.

Author: Edoardo Debenedetti, Nicholas Carlini, and Florian Tramèr
Published: 2024
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18. Data-driven molecular design and simulation in modern chemical engineering

Author: Gartner, III, Thomas E., Ferguson, Andrew L., and Debenedetti, Pablo G.
Published: 2024
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19. A Light Recipe to Train Robust Vision Transformers

Author: Debenedetti, Edoardo, Sehwag, Vikash, and Mittal, Prateek
Subjects: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract: In this paper, we ask whether Vision Transformers (ViTs) can serve as an underlying architecture for improving the adversarial robustness of machine learning models against evasion attacks. While earlier works have focused on improving Convolutional Neural Networks, we show that also ViTs are highly suitable for adversarial training to achieve competitive performance. We achieve this objective using a custom adversarial training recipe, discovered using rigorous ablation studies on a subset of the ImageNet dataset. The canonical training recipe for ViTs recommends strong data augmentation, in part to compensate for the lack of vision inductive bias of attention modules, when compared to convolutions. We show that this recipe achieves suboptimal performance when used for adversarial training. In contrast, we find that omitting all heavy data augmentation, and adding some additional bag-of-tricks ($\varepsilon$-warmup and larger weight decay), significantly boosts the performance of robust ViTs. We show that our recipe generalizes to different classes of ViT architectures and large-scale models on full ImageNet-1k. Additionally, investigating the reasons for the robustness of our models, we show that it is easier to generate strong attacks during training when using our recipe and that this leads to better robustness at test time. Finally, we further study one consequence of adversarial training by proposing a way to quantify the semantic nature of adversarial perturbations and highlight its correlation with the robustness of the model. Overall, we recommend that the community should avoid translating the canonical training recipes in ViTs to robust training and rethink common training choices in the context of adversarial training., Comment: Camera-ready version for SaTML 2023, code available at https://github.com/dedeswim/vits-robustness-torch
Published: 2022

20. Formation of Dissipative Structures in Microscopic Models of Mixtures with Species Interconversion

Author: Longo, Thomas J., Shumovskyi, Nikolay A., Uralcan, Betül, Buldyrev, Sergey V., Anisimov, Mikhail A., and Debenedetti, Pablo G.
Subjects: Condensed Matter - Statistical Mechanics
Abstract: The separation of substances into different phases is ubiquitous in nature and important scientifically and technologically. This phenomenon may become drastically different if the species involved, whether molecules or supramolecular assemblies, interconvert. In the presence of an external force large enough to overcome energetic differences between the interconvertible species (forced interconversion), the two alternative species will be present in equal amounts, and the striking phenomenon of steady-state, restricted phase separation into mesoscales is observed. Such microphase separation is one of the simplest examples of dissipative structures in condensed matter. In this work, we investigate the formation of such mesoscale steady-state structures through Monte Carlo and Molecular Dynamics simulations of three physically distinct microscopic models of binary mixtures that exhibit both equilibrium (natural) interconversion and a nonequilibrium source of forced interconversion. We show that this source can be introduced through an internal imbalance of intermolecular forces or an external flux of energy that promotes molecular interconversion, possible manifestations of which could include the internal nonequilibrium environment of living cells or a flux of photons. The main trends and observations from the simulations are well captured by a non-equilibrium thermodynamic theory of phase transitions affected by interconversion. We show how a nonequilibrium bicontinuous microemulsion or a spatially modulated state may be generated depending on the interplay between diffusion, natural interconversion, and forced interconversion., Comment: Manuscript submitted as a contributed article to PNAS
Published: 2022
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21. Liquid-liquid transition in water from first principles

Author: Gartner III, Thomas E., Piaggi, Pablo M., Car, Roberto, Panagiotopoulos, Athanassios Z., and Debenedetti, Pablo G.
Subjects: Condensed Matter - Statistical Mechanics, Physics - Chemical Physics
Abstract: A longstanding question in water research is the possibility that supercooled liquid water can undergo a liquid-liquid phase transition (LLT) into high- and low-density liquids. We used several complementary molecular simulation techniques to evaluate the possibility of an LLT in an ab initio neural network model of water trained on density functional theory calculations with the SCAN exchange correlation functional. We conclusively show the existence of a first-order LLT and an associated critical point in the SCAN description of water, representing the first definitive computational evidence for an LLT in water from first principles., Comment: 14 pages, 3 figures. Supplemental material contains 11 pages, 8 figures
Published: 2022
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22. Homogeneous ice nucleation in an ab initio machine learning model of water

Author: Piaggi, Pablo M., Weis, Jack, Panagiotopoulos, Athanassios Z., Debenedetti, Pablo G., and Car, Roberto
Subjects: Condensed Matter - Materials Science, Physics - Chemical Physics, Physics - Computational Physics
Abstract: Molecular simulations have provided valuable insight into the microscopic mechanisms underlying homogeneous ice nucleation. While empirical models have been used extensively to study this phenomenon, simulations based on first-principles calculations have so far proven prohibitively expensive. Here, we circumvent this difficulty by using an efficient machine learning model trained on density-functional theory (DFT) energies and forces. We compute nucleation rates at atmospheric pressure, over a broad range of supercoolings, using the seeding technique and systems of up to hundreds of thousands of atoms simulated with ab initio accuracy. The key quantity provided by the seeding technique is the size of the critical cluster (i.e., a size such that the cluster has equal probabilities of growing or melting at the given supersaturation) which is used together with the equations of classical nucleation theory to compute nucleation rates. We find that nucleation rates for our model at moderate supercoolings are in good agreement with experimental measurements within the error of our calculation. We also study the impact of properties such as the thermodynamic driving force, interfacial free energy, and stacking disorder on the calculated rates., Comment: 20 pages, 5 figures
Published: 2022
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23. Privacy Side Channels in Machine Learning Systems.

Author: Edoardo Debenedetti, Giorgio Severi, Milad Nasr, Christopher A. Choquette-Choo, Matthew Jagielski, Eric Wallace, Nicholas Carlini, and Florian Tramèr
Published: 2024

24. A single-crystal alkali antimonide photocathode: high efficiency in the ultra-thin limit

Author: Parzyck, C. T., Galdi, A., Nangoi, J. K., DeBenedetti, W. J. I., Balajka, J., Faeth, B. D., Paik, H., Hu, C., Arias, T. A., Hines, M. A., Schlom, D. G., Shen, K. M., and Maxson, J. M.
Subjects: Physics - Accelerator Physics, Condensed Matter - Materials Science
Abstract: The properties of photoemission electron sources determine the ultimate performance of a wide class of electron accelerators and photon detectors. To date, all high-efficiency visible-light photocathode materials are either polycrystalline or exhibit intrinsic surface disorder, both of which limit emitted electron beam brightness. In this letter we demonstrate the synthesis of epitaxial thin films of Cs$_3$Sb on 3C-SiC (001) using molecular-beam epitaxy. Films as thin as 4 nm have quantum efficiencies exceeding 2\% at 532 nm. We also find that epitaxial films have an order of magnitude larger quantum efficiency at 650 nm than comparable polycrystalline films on Si. Additionally, these films permit angle-resolved photoemission spectroscopy measurements of the electronic structure, which are found to be in good agreement with theory. Epitaxial films open the door to dramatic brightness enhancements via increased efficiency near threshold, reduced surface disorder, and the possibility of engineering new photoemission functionality at the level of single atomic layers., Comment: Submitted Manuscript: 8 pages, 4 figures
Published: 2021
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25. Interconversion-controlled liquid-liquid phase separation in a molecular chiral model

Author: Uralcan, Betul, Longo, Thomas J., Anisimov, Mikhail A., Stillinger, Frank H., and Debenedetti, Pablo G.
Subjects: Condensed Matter - Statistical Mechanics, Condensed Matter - Soft Condensed Matter
Abstract: Liquid-liquid phase separation of liquids exhibiting interconversion between alternative states has been proposed as an underlying mechanism for fluid polyamorphism, and may be of relevance to protein function and intracellular organization. However, molecular-level insight into the interplay between competing forces that can drive or restrict phase separation in interconverting fluids remains elusive. Here, we utilize an off-lattice model of enantiomers with tunable chiral interconversion and interaction properties to elucidate the physics underlying the stabilization and tunability of phase separation in fluids with interconverting states. We show that introducing an imbalance in the intermolecular forces between two enantiomers results in nonequilibrium, arrested phase separation into microdomains. We also find that in the equilibrium case, when all interaction forces are conservative, the growth of the phase domain is restricted only by system size. In this case, we observe phase amplification, in which one of the two alternative phases grows at the expense of the other. These findings provide novel insights on how the interplay between dynamics and thermodynamics defines the equilibrium and steady-state morphologies of phase transitions in fluids with interconverting molecular or supramolecular states., Comment: Intended for JCP
Published: 2021
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26. Thermodynamics and kinetics of crystallisation in deeply supercooled Stillinger-Weber silicon

Author: Goswami, Yagyik, Vasisht, Vishwas V., Frenkel, Daan, Debenedetti, Pablo G., and Sastry, Srikanth
Subjects: Condensed Matter - Soft Condensed Matter, Condensed Matter - Statistical Mechanics
Abstract: We study the kinetics of crystallization in deeply supercooled liquid silicon employing computer simulations and the Stillinger-Weber three body potential. The free energy barriers to crystallisation are computed using umbrella sampling Monte Carlo simulations, and for selected low temperature and zero pressure state points, using unconstrained molecular dynamics simulations to reconstruct the free energy from a mean first passage time formulation. We focus on state points that have been described in earlier work [Sastry and Angell, Nature Mater., 2, 739, 2003] as straddling a first order liquid-liquid phase transition (LLPT) between two metastable liquid states. It was argued subsequently [Ricci et al., Mol. Phys., 117, 3254, 2019] that the apparent phase transition is in fact due the loss of metastability of the liquid state with respect to the globally stable crystalline state. The presence or absence of a barrier to crystallization for these state points is therefore of importance to ascertain, with due attention to ambiguities that may arise from the choice of order parameters. We discuss our choice of order parameters and also our choice of methods to calculate the free energy at deep supercooling. We find a well-defined free energy barrier to crystallisation and demonstrate that both umbrella sampling and mean first passage time methods yield results that agree quantitatively. Our results thus provide strong evidence against the possibility that the liquids at state points close to the reported LLPT exhibit slow, spontaneous crystallisation, but they do not address the existence of a LLPT (or lack thereof). We also compute the free energy barriers to crystallisation at other state points over a broad range of temperatures and pressures, and discuss the effect of changes in the microscopic structure of the metastable liquid on the free energy barrier heights.
Published: 2021
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27. REASONS TO LOVE NEW YORK: RIGHT NOW

Author: Debenedetti, Gabriel
Subjects: General interest, News, opinion and commentary
Abstract: THE MAYOR HAD HIS PHONES SEIZED BY THE FBI, rents were never higher, and library hours and 3-K alike found themselves in peril. Also, it rained for eight consecutive weekends. [...]
Published: 2023

28. Erratum to: Search for exclusive Higgs and Z boson decays to ϕγ and ργ with the ATLAS detector

Author: The ATLAS collaboration, M. Aaboud, G. Aad, B. Abbott, O. Abdinov, B. Abeloos, S. H. Abidi, O. S. AbouZeid, N. L. Abraham, H. Abramowicz, H. Abreu, R. Abreu, Y. Abulaiti, B. S. Acharya, S. Adachi, L. Adamczyk, J. Adelman, M. Adersberger, T. Adye, A. A. Affolder, Y. Afik, T. Agatonovic-Jovin, C. Agheorghiesei, J. A. Aguilar-Saavedra, S. P. Ahlen, F. Ahmadov, G. Aielli, S. Akatsuka, H. Akerstedt, T. P. A. Åkesson, E. Akilli, A. V. Akimov, G. L. Alberghi, J. Albert, P. Albicocco, M. J. Alconada Verzini, S. C. Alderweireldt, M. Aleksa, I. N. Aleksandrov, C. Alexa, G. Alexander, T. Alexopoulos, M. Alhroob, B. Ali, M. Aliev, G. Alimonti, J. Alison, S. P. Alkire, B. M. M. Allbrooke, B. W. Allen, P. P. Allport, A. Aloisio, A. Alonso, F. Alonso, C. Alpigiani, A. A. Alshehri, M. I. Alstaty, B. Alvarez Gonzalez, D. Álvarez Piqueras, M. G. Alviggi, B. T. Amadio, Y. Amaral Coutinho, C. Amelung, D. Amidei, S. P. Amor Dos Santos, S. Amoroso, G. Amundsen, C. Anastopoulos, L. S. Ancu, N. Andari, T. Andeen, C. F. Anders, J. K. Anders, K. J. Anderson, A. Andreazza, V. Andrei, S. Angelidakis, I. Angelozzi, A. Angerami, A. V. Anisenkov, N. Anjos, A. Annovi, C. Antel, M. Antonelli, A. Antonov, D. J. Antrim, F. Anulli, M. Aoki, L. Aperio Bella, G. Arabidze, Y. Arai, J. P. Araque, V. Araujo Ferraz, A. T. H. Arce, R. E. Ardell, F. A. Arduh, J-F. Arguin, S. Argyropoulos, M. Arik, A. J. Armbruster, L. J. Armitage, O. Arnaez, H. Arnold, M. Arratia, O. Arslan, A. Artamonov, G. Artoni, S. Artz, S. Asai, N. Asbah, A. Ashkenazi, L. Asquith, K. Assamagan, R. Astalos, M. Atkinson, N. B. Atlay, K. Augsten, G. Avolio, B. Axen, M. K. Ayoub, G. Azuelos, A. E. Baas, M. J. Baca, H. Bachacou, K. Bachas, M. Backes, P. Bagnaia, M. Bahmani, H. Bahrasemani, J. T. Baines, M. Bajic, O. K. Baker, P. J. Bakker, E. M. Baldin, P. Balek, F. Balli, W. K. Balunas, E. Banas, A. Bandyopadhyay, Sw. Banerjee, A. A. E. Bannoura, L. Barak, E. L. Barberio, D. Barberis, M. Barbero, T. Barillari, M.-S. Barisits, J. T. Barkeloo, T. Barklow, N. Barlow, S. L. Barnes, B. M. Barnett, R. M. Barnett, Z. Barnovska-Blenessy, A. Baroncelli, G. Barone, A. J. Barr, L. Barranco Navarro, F. Barreiro, J. Barreiro Guimarães da Costa, R. Bartoldus, A. E. Barton, P. Bartos, A. Basalaev, A. Bassalat, R. L. Bates, S. J. Batista, J. R. Batley, M. Battaglia, M. Bauce, F. Bauer, H. S. Bawa, J. B. Beacham, M. D. Beattie, T. Beau, P. H. Beauchemin, P. Bechtle, H. P. Beck, H. C. Beck, K. Becker, M. Becker, C. Becot, A. J. Beddall, A. Beddall, V. A. Bednyakov, M. Bedognetti, C. P. Bee, T. A. Beermann, M. Begalli, M. Begel, J. K. Behr, A. S. Bell, G. Bella, L. Bellagamba, A. Bellerive, M. Bellomo, K. Belotskiy, O. Beltramello, N. L. Belyaev, O. Benary, D. Benchekroun, M. Bender, N. Benekos, Y. Benhammou, E. Benhar Noccioli, J. Benitez, D. P. Benjamin, M. Benoit, J. R. Bensinger, S. Bentvelsen, L. Beresford, M. Beretta, D. Berge, E. Bergeaas Kuutmann, N. Berger, L. J. Bergsten, J. Beringer, S. Berlendis, N. R. Bernard, G. Bernardi, C. Bernius, F. U. Bernlochner, T. Berry, P. Berta, C. Bertella, G. Bertoli, I. A. Bertram, C. Bertsche, G. J. Besjes, O. Bessidskaia Bylund, M. Bessner, N. Besson, A. Bethani, S. Bethke, A. Betti, A. J. Bevan, J. Beyer, R. M. Bianchi, O. Biebel, D. Biedermann, R. Bielski, K. Bierwagen, N. V. Biesuz, M. Biglietti, T. R. V. Billoud, H. Bilokon, M. Bindi, A. Bingul, C. Bini, S. Biondi, T. Bisanz, C. Bittrich, D. M. Bjergaard, J. E. Black, K. M. Black, R. E. Blair, T. Blazek, I. Bloch, C. Blocker, A. Blue, U. Blumenschein, Dr. Blunier, G. J. Bobbink, V. S. Bobrovnikov, S. S. Bocchetta, A. Bocci, C. Bock, M. Boehler, D. Boerner, D. Bogavac, A. G. Bogdanchikov, C. Bohm, V. Boisvert, P. Bokan, T. Bold, A. S. Boldyrev, A. E. Bolz, M. Bomben, M. Bona, M. Boonekamp, A. Borisov, G. Borissov, J. Bortfeldt, D. Bortoletto, V. Bortolotto, D. Boscherini, M. Bosman, J. D. Bossio Sola, J. Boudreau, E. V. Bouhova-Thacker, D. Boumediene, C. Bourdarios, S. K. Boutle, A. Boveia, J. Boyd, I. R. Boyko, A. J. Bozson, J. Bracinik, A. Brandt, G. Brandt, O. Brandt, F. Braren, U. Bratzler, B. Brau, J. E. Brau, W. D. Breaden Madden, K. Brendlinger, A. J. Brennan, L. Brenner, R. Brenner, S. Bressler, D. L. Briglin, T. M. Bristow, D. Britton, D. Britzger, F. M. Brochu, I. Brock, R. Brock, G. Brooijmans, T. Brooks, W. K. Brooks, J. Brosamer, E. Brost, J. H. Broughton, P. A. Bruckman de Renstrom, D. Bruncko, A. Bruni, G. Bruni, L. S. Bruni, S. Bruno, B. H. Brunt, M. Bruschi, N. Bruscino, P. Bryant, L. Bryngemark, T. Buanes, Q. Buat, P. Buchholz, A. G. Buckley, I. A. Budagov, F. Buehrer, M. K. Bugge, O. Bulekov, D. Bullock, T. J. Burch, S. Burdin, C. D. Burgard, A. M. Burger, B. Burghgrave, K. Burka, S. Burke, I. Burmeister, J. T. P. Burr, D. Büscher, V. Büscher, P. Bussey, J. M. Butler, C. M. Buttar, J. M. Butterworth, P. Butti, W. Buttinger, A. Buzatu, A. R. Buzykaev, S. Cabrera Urbán, D. Caforio, H. Cai, V. M. Cairo, O. Cakir, N. Calace, P. Calafiura, A. Calandri, G. Calderini, P. Calfayan, G. Callea, L. P. Caloba, S. Calvente Lopez, D. Calvet, S. Calvet, T. P. Calvet, R. Camacho Toro, S. Camarda, P. Camarri, D. Cameron, R. Caminal Armadans, C. Camincher, S. Campana, M. Campanelli, A. Camplani, A. Campoverde, V. Canale, M. Cano Bret, J. Cantero, T. Cao, M. D. M. Capeans Garrido, I. Caprini, M. Caprini, M. Capua, R. M. Carbone, R. Cardarelli, F. Cardillo, I. Carli, T. Carli, G. Carlino, B. T. Carlson, L. Carminati, R. M. D. Carney, S. Caron, E. Carquin, S. Carrá, G. D. Carrillo-Montoya, D. Casadei, M. P. Casado, A. F. Casha, M. Casolino, D. W. Casper, R. Castelijn, V. Castillo Gimenez, N. F. Castro, A. Catinaccio, J. R. Catmore, A. Cattai, J. Caudron, V. Cavaliere, E. Cavallaro, D. Cavalli, M. Cavalli-Sforza, V. Cavasinni, E. Celebi, F. Ceradini, L. Cerda Alberich, A. S. Cerqueira, A. Cerri, L. Cerrito, F. Cerutti, A. Cervelli, S. A. Cetin, A. Chafaq, D. Chakraborty, S. K. Chan, W. S. Chan, Y. L. Chan, P. Chang, J. D. Chapman, D. G. Charlton, C. C. Chau, C. A. Chavez Barajas, S. Che, S. Cheatham, A. Chegwidden, S. Chekanov, S. V. Chekulaev, G. A. Chelkov, M. A. Chelstowska, C. Chen, H. Chen, J. Chen, S. Chen, X. Chen, Y. Chen, H. C. Cheng, H. J. Cheng, A. Cheplakov, E. Cheremushkina, R. Cherkaoui El Moursli, E. Cheu, K. Cheung, L. Chevalier, V. Chiarella, G. Chiarelli, G. Chiodini, A. S. Chisholm, A. Chitan, Y. H. Chiu, M. V. Chizhov, K. Choi, A. R. Chomont, S. Chouridou, Y. S. Chow, V. Christodoulou, M. C. Chu, J. Chudoba, A. J. Chuinard, J. J. Chwastowski, L. Chytka, A. K. Ciftci, D. Cinca, V. Cindro, I. A. Cioară, A. Ciocio, F. Cirotto, Z. H. Citron, M. Citterio, M. Ciubancan, A. Clark, B. L. Clark, M. R. Clark, P. J. Clark, R. N. Clarke, C. Clement, Y. Coadou, M. Cobal, A. Coccaro, J. Cochran, L. Colasurdo, B. Cole, A. P. Colijn, J. Collot, T. Colombo, P. Conde Muiño, E. Coniavitis, S. H. Connell, I. A. Connelly, S. Constantinescu, G. Conti, F. Conventi, M. Cooke, A. M. Cooper-Sarkar, F. Cormier, K. J. R. Cormier, M. Corradi, F. Corriveau, A. Cortes-Gonzalez, G. Costa, M. J. Costa, D. Costanzo, G. Cottin, G. Cowan, B. E. Cox, K. Cranmer, S. J. Crawley, R. A. Creager, G. Cree, S. Crépé-Renaudin, F. Crescioli, W. A. Cribbs, M. Cristinziani, V. Croft, G. Crosetti, A. Cueto, T. Cuhadar Donszelmann, A. R. Cukierman, J. Cummings, M. Curatolo, J. Cúth, S. Czekierda, P. Czodrowski, G. D’amen, S. D’Auria, L. D’eramo, M. D’Onofrio, M. J. Da Cunha Sargedas De Sousa, C. Da Via, W. Dabrowski, T. Dado, T. Dai, O. Dale, F. Dallaire, C. Dallapiccola, M. Dam, J. R. Dandoy, M. F. Daneri, N. P. Dang, A. C. Daniells, N. S. Dann, M. Danninger, M. Dano Hoffmann, V. Dao, G. Darbo, S. Darmora, J. Dassoulas, A. Dattagupta, T. Daubney, W. Davey, C. David, T. Davidek, D. R. Davis, P. Davison, E. Dawe, I. Dawson, K. De, R. de Asmundis, A. De Benedetti, S. De Castro, S. De Cecco, N. De Groot, P. de Jong, H. De la Torre, F. De Lorenzi, A. De Maria, D. De Pedis, A. De Salvo, U. De Sanctis, A. De Santo, K. De Vasconcelos Corga, J. B. De Vivie De Regie, R. Debbe, C. Debenedetti, D. V. Dedovich, N. Dehghanian, I. Deigaard, M. Del Gaudio, J. Del Peso, D. Delgove, F. Deliot, C. M. Delitzsch, A. Dell’Acqua, L. Dell’Asta, M. Dell’Orso, M. Della Pietra, D. della Volpe, M. Delmastro, C. Delporte, P. A. Delsart, D. A. DeMarco, S. Demers, M. Demichev, A. Demilly, S. P. Denisov, D. Denysiuk, D. Derendarz, J. E. Derkaoui, F. Derue, P. Dervan, K. Desch, C. Deterre, K. Dette, M. R. Devesa, P. O. Deviveiros, A. Dewhurst, S. Dhaliwal, F. A. Di Bello, A. Di Ciaccio, L. Di Ciaccio, W. K. Di Clemente, C. Di Donato, A. Di Girolamo, B. Di Girolamo, B. Di Micco, R. Di Nardo, K. F. Di Petrillo, A. Di Simone, R. Di Sipio, D. Di Valentino, C. Diaconu, M. Diamond, F. A. Dias, M. A. Diaz, J. Dickinson, E. B. Diehl, J. Dietrich, S. Díez Cornell, A. Dimitrievska, J. Dingfelder, P. Dita, S. Dita, F. Dittus, F. Djama, T. Djobava, J. I. Djuvsland, M. A. B. do Vale, D. Dobos, M. Dobre, D. Dodsworth, C. Doglioni, J. 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Fakhrutdinov, S. Falciano, R. J. Falla, J. Faltova, Y. Fang, M. Fanti, A. Farbin, A. Farilla, C. Farina, E. M. Farina, T. Farooque, S. Farrell, S. M. Farrington, P. Farthouat, F. Fassi, P. Fassnacht, D. Fassouliotis, M. Faucci Giannelli, A. Favareto, W. J. Fawcett, L. Fayard, O. L. Fedin, W. Fedorko, S. Feigl, L. Feligioni, C. Feng, E. J. Feng, M. J. Fenton, A. B. Fenyuk, L. Feremenga, P. Fernandez Martinez, J. Ferrando, A. Ferrari, P. Ferrari, R. Ferrari, D. E. Ferreira de Lima, A. Ferrer, D. Ferrere, C. Ferretti, F. Fiedler, A. Filipčič, M. Filipuzzi, F. Filthaut, M. Fincke-Keeler, K. D. Finelli, M. C. N. Fiolhais, L. Fiorini, A. Fischer, C. Fischer, J. Fischer, W. C. Fisher, N. Flaschel, I. Fleck, P. Fleischmann, R. R. M. Fletcher, T. Flick, B. M. Flierl, L. R. Flores Castillo, M. J. Flowerdew, G. T. Forcolin, A. Formica, F. A. Förster, A. Forti, A. G. Foster, D. Fournier, H. Fox, S. Fracchia, P. Francavilla, M. Franchini, S. Franchino, D. Francis, L. Franconi, M. Franklin, M. 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Petridis, C. Petridou, P. Petroff, E. Petrolo, M. Petrov, F. Petrucci, N. E. Pettersson, A. Peyaud, R. Pezoa, F. H. Phillips, P. W. Phillips, G. Piacquadio, E. Pianori, A. Picazio, M. A. Pickering, R. Piegaia, J. E. Pilcher, A. D. Pilkington, M. Pinamonti, J. L. Pinfold, H. Pirumov, M. Pitt, L. Plazak, M.-A. Pleier, V. Pleskot, E. Plotnikova, D. Pluth, P. Podberezko, R. Poettgen, R. Poggi, L. Poggioli, I. Pogrebnyak, D. Pohl, I. Pokharel, G. Polesello, A. Poley, A. Policicchio, R. Polifka, A. Polini, C. S. Pollard, V. Polychronakos, K. Pommès, D. Ponomarenko, L. Pontecorvo, G. A. Popeneciu, D. M. Portillo Quintero, S. Pospisil, K. Potamianos, I. N. Potrap, C. J. Potter, H. Potti, T. Poulsen, J. Poveda, M. E. Pozo Astigarraga, P. Pralavorio, A. Pranko, S. Prell, D. Price, M. Primavera, S. Prince, N. Proklova, K. Prokofiev, F. Prokoshin, S. Protopopescu, J. Proudfoot, M. Przybycien, A. Puri, P. Puzo, J. Qian, G. Qin, Y. Qin, A. Quadt, M. Queitsch-Maitland, D. Quilty, S. Raddum, V. Radeka, V. Radescu, S. K. Radhakrishnan, P. Radloff, P. Rados, F. Ragusa, G. Rahal, J. A. Raine, S. Rajagopalan, C. Rangel-Smith, T. Rashid, S. Raspopov, M. G. Ratti, D. M. Rauch, F. Rauscher, S. Rave, I. Ravinovich, J. H. Rawling, M. Raymond, A. L. Read, N. P. Readioff, M. Reale, D. M. Rebuzzi, A. Redelbach, G. Redlinger, R. Reece, R. G. Reed, K. Reeves, L. Rehnisch, J. Reichert, A. Reiss, C. Rembser, H. Ren, M. Rescigno, S. Resconi, E. D. Resseguie, S. Rettie, E. Reynolds, O. L. Rezanova, P. Reznicek, R. Rezvani, R. Richter, S. Richter, E. Richter-Was, O. Ricken, M. Ridel, P. Rieck, C. J. Riegel, J. Rieger, O. Rifki, M. Rijssenbeek, A. Rimoldi, M. Rimoldi, L. Rinaldi, G. Ripellino, B. Ristić, E. Ritsch, I. Riu, F. Rizatdinova, E. Rizvi, C. Rizzi, R. T. Roberts, S. H. Robertson, A. Robichaud-Veronneau, D. Robinson, J. E. M. Robinson, A. Robson, E. Rocco, C. Roda, Y. Rodina, S. Rodriguez Bosca, A. Rodriguez Perez, D. Rodriguez Rodriguez, S. Roe, C. S. Rogan, O. Røhne, J. Roloff, A. Romaniouk, M. Romano, S. M. Romano Saez, E. Romero Adam, N. Rompotis, M. Ronzani, L. Roos, S. Rosati, K. Rosbach, P. Rose, N.-A. Rosien, E. Rossi, L. P. Rossi, J. H. N. Rosten, R. Rosten, M. Rotaru, J. Rothberg, D. Rousseau, D. Roy, A. Rozanov, Y. Rozen, X. Ruan, F. Rubbo, F. Rühr, A. Ruiz-Martinez, Z. Rurikova, N. A. Rusakovich, H. L. Russell, J. P. Rutherfoord, N. Ruthmann, E. M. Rüttinger, Y. F. Ryabov, M. Rybar, G. Rybkin, S. Ryu, A. Ryzhov, G. F. Rzehorz, A. F. Saavedra, G. Sabato, S. Sacerdoti, H. F-W. Sadrozinski, R. Sadykov, F. Safai Tehrani, P. Saha, M. Sahinsoy, M. Saimpert, M. Saito, T. Saito, H. Sakamoto, Y. Sakurai, G. Salamanna, J. E. Salazar Loyola, D. Salek, P. H. Sales De Bruin, D. Salihagic, A. Salnikov, J. Salt, D. Salvatore, F. Salvatore, A. Salvucci, A. Salzburger, D. Sammel, D. Sampsonidis, D. Sampsonidou, J. Sánchez, V. Sanchez Martinez, A. Sanchez Pineda, H. Sandaker, R. L. Sandbach, C. O. Sander, M. Sandhoff, C. Sandoval, D. P. C. Sankey, M. Sannino, Y. Sano, A. Sansoni, C. Santoni, H. Santos, I. Santoyo Castillo, A. Sapronov, J. G. Saraiva, B. Sarrazin, O. Sasaki, K. Sato, E. Sauvan, G. Savage, P. Savard, N. Savic, C. Sawyer, L. Sawyer, J. Saxon, C. Sbarra, A. Sbrizzi, T. Scanlon, D. A. Scannicchio, J. Schaarschmidt, P. Schacht, B. M. Schachtner, D. Schaefer, L. Schaefer, R. Schaefer, J. Schaeffer, S. Schaepe, S. Schaetzel, U. Schäfer, A. C. Schaffer, D. Schaile, R. D. Schamberger, V. A. Schegelsky, D. Scheirich, F. Schenck, M. Schernau, C. Schiavi, S. Schier, L. K. Schildgen, C. Schillo, M. Schioppa, S. Schlenker, K. R. Schmidt-Sommerfeld, K. Schmieden, C. Schmitt, S. Schmitt, S. Schmitz, U. Schnoor, L. Schoeffel, A. Schoening, B. D. Schoenrock, E. Schopf, M. Schott, J. F. P. Schouwenberg, J. Schovancova, S. Schramm, N. Schuh, A. Schulte, M. J. Schultens, H.-C. Schultz-Coulon, H. Schulz, M. Schumacher, B. A. Schumm, Ph. Schune, A. Schwartzman, T. A. Schwarz, H. Schweiger, Ph. Schwemling, R. Schwienhorst, J. Schwindling, A. Sciandra, G. Sciolla, M. Scornajenghi, F. Scuri, F. Scutti, J. Searcy, P. Seema, S. C. Seidel, A. Seiden, J. M. Seixas, G. Sekhniaidze, K. Sekhon, S. J. Sekula, N. Semprini-Cesari, S. Senkin, C. Serfon, L. Serin, L. Serkin, M. Sessa, R. Seuster, H. Severini, T. Šfiligoj, F. Sforza, A. Sfyrla, E. Shabalina, N. W. Shaikh, L. Y. Shan, R. Shang, J. T. Shank, M. Shapiro, P. B. Shatalov, K. Shaw, S. M. Shaw, A. Shcherbakova, C. Y. Shehu, Y. Shen, N. Sherafati, A. D. Sherman, P. Sherwood, L. Shi, S. Shimizu, C. O. Shimmin, M. Shimojima, I. P. J. Shipsey, S. Shirabe, M. Shiyakova, J. Shlomi, A. Shmeleva, D. Shoaleh Saadi, M. J. Shochet, S. Shojaii, D. R. Shope, S. Shrestha, E. Shulga, M. A. Shupe, P. Sicho, A. M. Sickles, P. E. Sidebo, E. Sideras Haddad, O. Sidiropoulou, A. Sidoti, F. Siegert, Dj. Sijacki, J. Silva, S. B. Silverstein, V. Simak, L. Simic, S. Simion, E. Simioni, B. Simmons, M. Simon, P. Sinervo, N. B. Sinev, M. Sioli, G. Siragusa, I. Siral, S. Yu. Sivoklokov, J. Sjölin, M. B. Skinner, P. Skubic, M. Slater, T. Slavicek, M. Slawinska, K. Sliwa, R. Slovak, V. Smakhtin, B. H. Smart, J. Smiesko, N. Smirnov, S. Yu. Smirnov, Y. Smirnov, L. N. Smirnova, O. Smirnova, J. W. Smith, M. N. K. Smith, R. W. Smith, M. Smizanska, K. Smolek, A. A. Snesarev, I. M. Snyder, S. Snyder, R. Sobie, F. Socher, A. Soffer, A. Søgaard, D. A. Soh, G. Sokhrannyi, C. A. Solans Sanchez, M. Solar, E. Yu. Soldatov, U. Soldevila, A. A. Solodkov, A. Soloshenko, O. V. Solovyanov, V. Solovyev, P. Sommer, H. Son, A. Sopczak, D. Sosa, C. L. Sotiropoulou, S. Sottocornola, R. Soualah, A. M. Soukharev, D. South, B. C. Sowden, S. Spagnolo, M. Spalla, M. Spangenberg, F. Spanò, D. Sperlich, F. Spettel, T. M. Spieker, R. Spighi, G. Spigo, L. A. Spiller, M. Spousta, R. D. St. Denis, A. Stabile, R. Stamen, S. Stamm, E. Stanecka, R. W. Stanek, C. Stanescu, M. M. Stanitzki, B. S. Stapf, S. Stapnes, E. A. Starchenko, G. H. Stark, J. Stark, S. H. Stark, P. Staroba, P. Starovoitov, S. Stärz, R. Staszewski, M. Stegler, P. Steinberg, B. Stelzer, H. J. Stelzer, O. Stelzer-Chilton, H. Stenzel, T. J. Stevenson, G. A. Stewart, M. C. Stockton, M. Stoebe, G. Stoicea, P. Stolte, S. Stonjek, A. R. Stradling, A. Straessner, M. E. Stramaglia, J. Strandberg, S. Strandberg, M. Strauss, P. Strizenec, R. Ströhmer, D. M. Strom, R. Stroynowski, A. Strubig, S. A. Stucci, B. Stugu, N. A. Styles, D. Su, J. Su, S. Suchek, Y. Sugaya, M. Suk, V. V. Sulin, D. M. S. Sultan, S. Sultansoy, T. Sumida, S. Sun, X. Sun, K. Suruliz, C. J. E. Suster, M. R. Sutton, S. Suzuki, M. Svatos, M. Swiatlowski, S. P. Swift, I. Sykora, T. Sykora, D. Ta, K. Tackmann, J. Taenzer, A. Taffard, R. Tafirout, E. Tahirovic, N. Taiblum, H. Takai, R. Takashima, E. H. Takasugi, K. Takeda, T. Takeshita, Y. Takubo, M. Talby, A. A. Talyshev, J. Tanaka, M. Tanaka, R. Tanaka, S. Tanaka, R. Tanioka, B. B. Tannenwald, S. Tapia Araya, S. Tapprogge, S. Tarem, G. F. Tartarelli, P. Tas, M. Tasevsky, T. Tashiro, E. Tassi, A. Tavares Delgado, Y. Tayalati, A. C. Taylor, A. J. Taylor, G. N. Taylor, P. T. E. Taylor, W. Taylor, P. Teixeira-Dias, D. Temple, H. Ten Kate, P. K. Teng, J. J. Teoh, F. Tepel, S. Terada, K. Terashi, J. Terron, S. Terzo, M. Testa, R. J. Teuscher, S. J. Thais, T. Theveneaux-Pelzer, F. Thiele, J. P. Thomas, J. Thomas-Wilsker, P. D. Thompson, A. S. Thompson, L. A. Thomsen, E. Thomson, Y. Tian, M. J. Tibbetts, R. E. Ticse Torres, V. O. Tikhomirov, Yu. A. Tikhonov, S. Timoshenko, P. Tipton, S. Tisserant, K. Todome, S. Todorova-Nova, S. Todt, J. Tojo, S. Tokár, K. Tokushuku, E. Tolley, L. Tomlinson, M. Tomoto, L. Tompkins, K. Toms, B. Tong, P. Tornambe, E. Torrence, H. Torres, E. Torró Pastor, J. Toth, F. Touchard, D. R. Tovey, C. J. Treado, T. Trefzger, F. Tresoldi, A. Tricoli, I. M. Trigger, S. Trincaz-Duvoid, M. F. Tripiana, W. Trischuk, B. Trocmé, A. Trofymov, C. Troncon, M. Trottier-McDonald, M. Trovatelli, L. Truong, M. Trzebinski, A. Trzupek, K. W. Tsang, J. C-L. Tseng, P. V. Tsiareshka, N. Tsirintanis, S. Tsiskaridze, V. Tsiskaridze, E. G. Tskhadadze, I. I. Tsukerman, V. Tsulaia, S. Tsuno, D. Tsybychev, Y. Tu, A. Tudorache, V. Tudorache, T. T. Tulbure, A. N. Tuna, S. Turchikhin, D. Turgeman, I. Turk Cakir, R. Turra, P. M. Tuts, G. Ucchielli, I. Ueda, M. Ughetto, F. Ukegawa, G. Unal, A. Undrus, G. Unel, F. C. Ungaro, Y. Unno, K. Uno, C. Unverdorben, J. Urban, P. Urquijo, P. Urrejola, G. Usai, J. Usui, L. Vacavant, V. Vacek, B. Vachon, K. O. H. Vadla, A. Vaidya, C. Valderanis, E. Valdes Santurio, M. Valente, S. Valentinetti, A. Valero, L. Valéry, S. Valkar, A. Vallier, J. A. Valls Ferrer, W. Van Den Wollenberg, H. van der Graaf, P. van Gemmeren, J. Van Nieuwkoop, I. van Vulpen, M. C. van Woerden, M. Vanadia, W. Vandelli, A. Vaniachine, P. Vankov, G. Vardanyan, R. Vari, E. W. Varnes, C. Varni, T. Varol, D. Varouchas, A. Vartapetian, K. E. Varvell, J. G. Vasquez, G. A. Vasquez, F. Vazeille, D. Vazquez Furelos, T. Vazquez Schroeder, J. Veatch, V. Veeraraghavan, L. M. Veloce, F. Veloso, S. Veneziano, A. Ventura, M. Venturi, N. Venturi, A. Venturini, V. Vercesi, M. Verducci, W. Verkerke, A. T. Vermeulen, J. C. Vermeulen, M. C. Vetterli, N. Viaux Maira, O. Viazlo, I. Vichou, T. Vickey, O. E. Vickey Boeriu, G. H. A. Viehhauser, S. Viel, L. Vigani, M. Villa, M. Villaplana Perez, E. Vilucchi, M. G. Vincter, V. B. Vinogradov, A. Vishwakarma, C. Vittori, I. Vivarelli, S. Vlachos, M. Vogel, P. Vokac, G. Volpi, H. von der Schmitt, E. von Toerne, V. Vorobel, K. Vorobev, M. Vos, R. Voss, J. H. Vossebeld, N. Vranjes, M. Vranjes Milosavljevic, V. Vrba, M. Vreeswijk, R. Vuillermet, I. Vukotic, P. Wagner, W. Wagner, J. Wagner-Kuhr, H. Wahlberg, S. Wahrmund, K. Wakamiya, J. Walder, R. Walker, W. Walkowiak, V. Wallangen, C. Wang, F. Wang, H. Wang, J. Wang, Q. Wang, R.-J. Wang, R. Wang, S. M. Wang, T. Wang, W. Wang, Z. Wang, C. Wanotayaroj, A. Warburton, C. P. Ward, D. R. Wardrope, A. Washbrook, P. M. Watkins, A. T. Watson, M. F. Watson, G. Watts, S. Watts, B. M. Waugh, A. F. Webb, S. Webb, M. S. Weber, S. M. Weber, S. W. Weber, S. A. Weber, J. S. Webster, A. R. Weidberg, B. Weinert, J. Weingarten, M. Weirich, C. Weiser, H. Weits, P. S. Wells, T. Wenaus, T. Wengler, S. Wenig, N. Wermes, M. D. Werner, P. Werner, M. Wessels, T. D. Weston, K. Whalen, N. L. Whallon, A. M. Wharton, A. S. White, A. White, M. J. White, R. White, D. Whiteson, B. W. Whitmore, F. J. Wickens, W. Wiedenmann, M. Wielers, C. Wiglesworth, L. A. M. Wiik-Fuchs, A. Wildauer, F. Wilk, H. G. Wilkens, H. H. Williams, S. Williams, C. Willis, S. Willocq, J. A. Wilson, I. Wingerter-Seez, E. Winkels, F. Winklmeier, O. J. Winston, B. T. Winter, M. Wittgen, M. Wobisch, A. Wolf, T. M. H. Wolf, R. Wolff, M. W. Wolter, H. Wolters, V. W. S. Wong, N. L. Woods, S. D. Worm, B. K. Wosiek, J. Wotschack, K. W. Wozniak, M. Wu, S. L. Wu, X. Wu, Y. Wu, T. R. Wyatt, B. M. Wynne, S. Xella, Z. Xi, L. Xia, D. Xu, L. Xu, T. Xu, W. Xu, B. Yabsley, S. Yacoob, D. Yamaguchi, Y. Yamaguchi, A. Yamamoto, S. Yamamoto, T. Yamanaka, F. Yamane, M. Yamatani, T. Yamazaki, Y. Yamazaki, Z. Yan, H. Yang, Y. Yang, Z. Yang, W-M. Yao, Y. C. Yap, Y. Yasu, E. Yatsenko, K. H. Yau Wong, J. Ye, S. Ye, I. Yeletskikh, E. Yigitbasi, E. Yildirim, K. Yorita, K. Yoshihara, C. Young, C. J. S. Young, J. Yu, S. P. Y. Yuen, I. Yusuff, B. Zabinski, G. Zacharis, R. Zaidan, A. M. Zaitsev, N. Zakharchuk, J. Zalieckas, A. Zaman, S. Zambito, D. Zanzi, C. Zeitnitz, G. Zemaityte, A. Zemla, J. C. Zeng, Q. Zeng, O. Zenin, T. Ženiš, D. Zerwas, D. Zhang, F. Zhang, G. Zhang, H. Zhang, J. Zhang, L. Zhang, M. Zhang, P. Zhang, R. Zhang, X. Zhang, Y. Zhang, Z. Zhang, X. Zhao, Y. Zhao, Z. Zhao, A. Zhemchugov, B. Zhou, C. Zhou, L. Zhou, M. Zhou, N. Zhou, Y. Zhou, C. G. Zhu, H. Zhu, J. Zhu, Y. Zhu, X. Zhuang, K. Zhukov, A. Zibell, D. Zieminska, N. I. Zimine, C. Zimmermann, S. Zimmermann, Z. Zinonos, M. Zinser, M. Ziolkowski, L. Živković, G. Zobernig, A. Zoccoli, R. Zou, M. zur Nedden, and L. Zwalinski
Subjects: Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Published: 2023
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29. Manifestations of metastable criticality in the long-range structure of model water glasses

Author: Gartner III, Thomas E., Torquato, Salvatore, Car, Roberto, and Debenedetti, Pablo G.
Subjects: Condensed Matter - Soft Condensed Matter, Condensed Matter - Statistical Mechanics
Abstract: Much attention has been devoted to water's metastable phase behavior, including polyamorphism (multiple amorphous solid phases), and the hypothesized liquid-liquid transition and associated critical point. However, the possible relationship between these phenomena remains incompletely understood. Using molecular dynamics simulations of the realistic TIP4P/2005 model, we found a striking signature of the liquid-liquid critical point in the structure of water glasses, manifested as a pronounced increase in long-range density fluctuations at pressures proximate to the critical pressure. By contrast, these signatures were absent in glasses of two model systems that lack a critical point. We also characterized the departure from equilibrium upon vitrification via the non-equilibrium index; water-like systems exhibited a strong pressure dependence in this metric, whereas simple liquids did not. These results reflect a surprising relationship between the metastable equilibrium phenomenon of liquid-liquid criticality and the non-equilibrium structure of glassy water, with implications for our understanding of water phase behavior and glass physics. Our calculations suggest a possible experimental route to probing the existence of the liquid-liquid transition in water and other fluids., Comment: 9 pages, 5 figures. Published in Nature Communications (2021)
Published: 2021
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30. Phase equilibrium of water with hexagonal and cubic ice using the SCAN functional

Author: Piaggi, Pablo M., Panagiotopoulos, Athanassios Z., Debenedetti, Pablo G., and Car, Roberto
Subjects: Condensed Matter - Statistical Mechanics, Physics - Computational Physics
Abstract: Machine learning models are rapidly becoming widely used to simulate complex physicochemical phenomena with ab initio accuracy. Here, we use one such model as well as direct density functional theory (DFT) calculations to investigate the phase equilibrium of water, hexagonal ice (Ih), and cubic ice (Ic), with an eye towards studying ice nucleation. The machine learning model is based on deep neural networks and has been trained on DFT data obtained using the SCAN exchange and correlation functional. We use this model to drive enhanced sampling simulations aimed at calculating a number of complex properties that are out of reach of DFT-driven simulations and then employ an appropriate reweighting procedure to compute the corresponding properties for the SCAN functional. This approach allows us to calculate the melting temperature of both ice polymorphs, the driving force for nucleation, the heat of fusion, the densities at the melting temperature, the relative stability of ice Ih and Ic, and other properties. We find a correct qualitative prediction of all properties of interest. In some cases, quantitative agreement with experiment is better than for state-of-the-art semiempirical potentials for water. Our results also show that SCAN correctly predicts that ice Ih is more stable than ice Ic., Comment: 20 pages, 9 figures
Published: 2021
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31. JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models.

Author: Patrick Chao, Edoardo Debenedetti, Alexander Robey, Maksym Andriushchenko, Francesco Croce, Vikash Sehwag, Edgar Dobriban, Nicolas Flammarion, George J. Pappas, Florian Tramèr, Hamed Hassani, and Eric Wong 0001
Published: 2024
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32. Adversarial Search Engine Optimization for Large Language Models.

Author: Fredrik Nestaas, Edoardo Debenedetti, and Florian Tramèr
Published: 2024
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33. AgentDojo: A Dynamic Environment to Evaluate Attacks and Defenses for LLM Agents.

Author: Edoardo Debenedetti, Jie Zhang, Mislav Balunovic, Luca Beurer-Kellner, Marc Fischer 0002, and Florian Tramèr
Published: 2024
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34. AI Risk Management Should Incorporate Both Safety and Security.

Author: Xiangyu Qi, Yangsibo Huang, Yi Zeng 0005, Edoardo Debenedetti, Jonas Geiping, Luxi He, Kaixuan Huang, Udari Madhushani, Vikash Sehwag, Weijia Shi, Boyi Wei, Tinghao Xie, Danqi Chen 0001, Pin-Yu Chen, Jeffrey Ding, Ruoxi Jia 0001, Jiaqi Ma, Arvind Narayanan, Weijie J. Su, Mengdi Wang, Chaowei Xiao, Bo Li 0026, Dawn Song, Peter Henderson 0002, and Prateek Mittal
Published: 2024
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35. Dataset and Lessons Learned from the 2024 SaTML LLM Capture-the-Flag Competition.

Author: Edoardo Debenedetti, Javier Rando, Daniel Paleka, Silaghi Fineas Florin, Dragos Albastroiu, Niv Cohen, Yuval Lemberg, Reshmi Ghosh, Rui Wen 0002, Ahmed Salem 0001, Giovanni Cherubin, Santiago Zanella Béguelin, Robin Schmid, Victor Klemm, Takahiro Miki, Chenhao Li, Stefan Kraft, Mario Fritz, Florian Tramèr, Sahar Abdelnabi, and Lea Schönherr
Published: 2024
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36. A Light Recipe to Train Robust Vision Transformers.

Author: Edoardo Debenedetti, Vikash Sehwag, and Prateek Mittal
Published: 2023
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37. From feeling like home to being at home: The negative outcomes of attachment to commercial places

Author: Debenedetti, Alain and Chaney, Damien
Published: 2024
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38. Balancing exclusivity and inclusivity through the strategic domestication of the luxury retail experience

Author: Debenedetti, Alain, Philippe, Déborah, and Dion, Delphine
Published: 2024
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39. RobustBench: a standardized adversarial robustness benchmark

Author: Croce, Francesco, Andriushchenko, Maksym, Sehwag, Vikash, Debenedetti, Edoardo, Flammarion, Nicolas, Chiang, Mung, Mittal, Prateek, and Hein, Matthias
Subjects: Computer Science - Machine Learning, Computer Science - Cryptography and Security, Computer Science - Computer Vision and Pattern Recognition, Statistics - Machine Learning
Abstract: As a research community, we are still lacking a systematic understanding of the progress on adversarial robustness which often makes it hard to identify the most promising ideas in training robust models. A key challenge in benchmarking robustness is that its evaluation is often error-prone leading to robustness overestimation. Our goal is to establish a standardized benchmark of adversarial robustness, which as accurately as possible reflects the robustness of the considered models within a reasonable computational budget. To this end, we start by considering the image classification task and introduce restrictions (possibly loosened in the future) on the allowed models. We evaluate adversarial robustness with AutoAttack, an ensemble of white- and black-box attacks, which was recently shown in a large-scale study to improve almost all robustness evaluations compared to the original publications. To prevent overadaptation of new defenses to AutoAttack, we welcome external evaluations based on adaptive attacks, especially where AutoAttack flags a potential overestimation of robustness. Our leaderboard, hosted at https://robustbench.github.io/, contains evaluations of 120+ models and aims at reflecting the current state of the art in image classification on a set of well-defined tasks in $\ell_\infty$- and $\ell_2$-threat models and on common corruptions, with possible extensions in the future. Additionally, we open-source the library https://github.com/RobustBench/robustbench that provides unified access to 80+ robust models to facilitate their downstream applications. Finally, based on the collected models, we analyze the impact of robustness on the performance on distribution shifts, calibration, out-of-distribution detection, fairness, privacy leakage, smoothness, and transferability., Comment: The camera-ready version accepted at the NeurIPS'21 Datasets and Benchmarks Track: 120+ evaluations, 80+ models, 7 leaderboards (Linf, L2, common corruptions; CIFAR-10, CIFAR-100, ImageNet), significantly expanded analysis part (calibration, fairness, privacy leakage, smoothness, transferability)
Published: 2020

40. Erratum to: Search for exclusive Higgs and Z boson decays to ϕγ and ργ with the ATLAS detector

Author: Aaboud, M., Aad, G., Abbott, B., Abdinov, O., Abeloos, B., Abidi, S. H., AbouZeid, O. S., Abraham, N. L., Abramowicz, H., Abreu, H., Abreu, R., Abulaiti, Y., Acharya, B. S., Adachi, S., Adamczyk, L., Adelman, J., Adersberger, M., Adye, T., Affolder, A. A., Afik, Y., Agatonovic-Jovin, T., Agheorghiesei, C., Aguilar-Saavedra, J. A., Ahlen, S. P., Ahmadov, F., Aielli, G., Akatsuka, S., Akerstedt, H., Åkesson, T. P. A., Akilli, E., Akimov, A. V., Alberghi, G. L., Albert, J., Albicocco, P., Alconada Verzini, M. J., Alderweireldt, S. C., Aleksa, M., Aleksandrov, I. N., Alexa, C., Alexander, G., Alexopoulos, T., Alhroob, M., Ali, B., Aliev, M., Alimonti, G., Alison, J., Alkire, S. P., Allbrooke, B. M. M., Allen, B. W., Allport, P. P., Aloisio, A., Alonso, A., Alonso, F., Alpigiani, C., Alshehri, A. A., Alstaty, M. I., Alvarez Gonzalez, B., Álvarez Piqueras, D., Alviggi, M. G., Amadio, B. T., Amaral Coutinho, Y., Amelung, C., Amidei, D., Amor Dos Santos, S. P., Amoroso, S., Amundsen, G., Anastopoulos, C., Ancu, L. S., Andari, N., Andeen, T., Anders, C. F., Anders, J. K., Anderson, K. J., Andreazza, A., Andrei, V., Angelidakis, S., Angelozzi, I., Angerami, A., Anisenkov, A. V., Anjos, N., Annovi, A., Antel, C., Antonelli, M., Antonov, A., Antrim, D. J., Anulli, F., Aoki, M., Aperio Bella, L., Arabidze, G., Arai, Y., Araque, J. P., Araujo Ferraz, V., Arce, A. T. H., Ardell, R. E., Arduh, F. A., Arguin, J-F., Argyropoulos, S., Arik, M., Armbruster, A. J., Armitage, L. J., Arnaez, O., Arnold, H., Arratia, M., Arslan, O., Artamonov, A., Artoni, G., Artz, S., Asai, S., Asbah, N., Ashkenazi, A., Asquith, L., Assamagan, K., Astalos, R., Atkinson, M., Atlay, N. B., Augsten, K., Avolio, G., Axen, B., Ayoub, M. K., Azuelos, G., Baas, A. E., Baca, M. J., Bachacou, H., Bachas, K., Backes, M., Bagnaia, P., Bahmani, M., Bahrasemani, H., Baines, J. T., Bajic, M., Baker, O. K., Bakker, P. J., Baldin, E. M., Balek, P., Balli, F., Balunas, W. K., Banas, E., Bandyopadhyay, A., Banerjee, Sw., Bannoura, A. A. E., Barak, L., Barberio, E. L., Barberis, D., Barbero, M., Barillari, T., Barisits, M.-S., Barkeloo, J. T., Barklow, T., Barlow, N., Barnes, S. L., Barnett, B. M., Barnett, R. M., Barnovska-Blenessy, Z., Baroncelli, A., Barone, G., Barr, A. J., Barranco Navarro, L., Barreiro, F., Barreiro Guimarães da Costa, J., Bartoldus, R., Barton, A. E., Bartos, P., Basalaev, A., Bassalat, A., Bates, R. L., Batista, S. J., Batley, J. R., Battaglia, M., Bauce, M., Bauer, F., Bawa, H. S., Beacham, J. B., Beattie, M. D., Beau, T., Beauchemin, P. H., Bechtle, P., Beck, H. P., Beck, H. C., Becker, K., Becker, M., Becot, C., Beddall, A. J., Beddall, A., Bednyakov, V. A., Bedognetti, M., Bee, C. P., Beermann, T. A., Begalli, M., Begel, M., Behr, J. K., Bell, A. S., Bella, G., Bellagamba, L., Bellerive, A., Bellomo, M., Belotskiy, K., Beltramello, O., Belyaev, N. L., Benary, O., Benchekroun, D., Bender, M., Benekos, N., Benhammou, Y., Benhar Noccioli, E., Benitez, J., Benjamin, D. P., Benoit, M., Bensinger, J. R., Bentvelsen, S., Beresford, L., Beretta, M., Berge, D., Bergeaas Kuutmann, E., Berger, N., Bergsten, L. J., Beringer, J., Berlendis, S., Bernard, N. R., Bernardi, G., Bernius, C., Bernlochner, F. U., Berry, T., Berta, P., Bertella, C., Bertoli, G., Bertram, I. A., Bertsche, C., Besjes, G. J., Bessidskaia Bylund, O., Bessner, M., Besson, N., Bethani, A., Bethke, S., Betti, A., Bevan, A. J., Beyer, J., Bianchi, R. M., Biebel, O., Biedermann, D., Bielski, R., Bierwagen, K., Biesuz, N. V., Biglietti, M., Billoud, T. R. V., Bilokon, H., Bindi, M., Bingul, A., Bini, C., Biondi, S., Bisanz, T., Bittrich, C., Bjergaard, D. M., Black, J. E., Black, K. M., Blair, R. E., Blazek, T., Bloch, I., Blocker, C., Blue, A., Blumenschein, U., Blunier, Dr., Bobbink, G. J., Bobrovnikov, V. S., Bocchetta, S. 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Published: 2023
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41. Closely related Lak megaphages replicate in the microbiomes of diverse animals

Author: Crisci, Marco A, Chen, Lin-Xing, Devoto, Audra E, Borges, Adair L, Bordin, Nicola, Sachdeva, Rohan, Tett, Adrian, Sharrar, Allison M, Segata, Nicola, Debenedetti, Francesco, Bailey, Mick, Burt, Rachel, Wood, Rhiannon M, Rowden, Lewis J, Corsini, Paula M, van Winden, Steven, Holmes, Mark A, Lei, Shufei, Banfield, Jillian F, and Santini, Joanne M
Subjects: Genetics, Human Genome, Microbiome, Omics, Virology
Abstract: Lak phages with alternatively coded ∼540 kbp genomes were recently reported to replicate in Prevotella in microbiomes of humans that consume a non-Western diet, baboons, and pigs. Here, we explore Lak phage diversity and broader distribution using diagnostic polymerase chain reaction and genome-resolved metagenomics. Lak phages were detected in 13 animal types, including reptiles, and are particularly prevalent in pigs. Tracking Lak through the pig gastrointestinal tract revealed significant enrichment in the hindgut compared to the foregut. We reconstructed 34 new Lak genomes, including six curated complete genomes, all of which are alternatively coded. An anomalously large (∼660 kbp) complete genome reconstructed for the most deeply branched Lak from a horse microbiome is also alternatively coded. From the Lak genomes, we identified proteins associated with specific animal species; notably, most have no functional predictions. The presence of closely related Lak phages in diverse animals indicates facile distribution coupled to host-specific adaptation.
Published: 2021

42. Measurement of the top-quark mass using a leptonic invariant mass in pp collisions at s $$ \sqrt{s} $$ = 13 TeV with the ATLAS detector

Author: The ATLAS collaboration, G. Aad, B. Abbott, D. C. Abbott, A. Abed Abud, K. Abeling, D. K. Abhayasinghe, S. H. Abidi, O. S. AbouZeid, N. L. Abraham, H. Abramowicz, H. Abreu, Y. Abulaiti, B. S. Acharya, B. Achkar, S. Adachi, L. Adam, C. Adam Bourdarios, L. Adamczyk, L. Adamek, J. Adelman, M. Adersberger, A. Adiguzel, S. Adorni, T. Adye, A. A. Affolder, Y. Afik, C. Agapopoulou, M. N. Agaras, A. Aggarwal, C. Agheorghiesei, J. A. Aguilar-Saavedra, F. Ahmadov, W. S. Ahmed, X. Ai, G. Aielli, S. Akatsuka, T. P. A. Åkesson, E. Akilli, A. V. Akimov, K. Al Khoury, G. L. Alberghi, J. Albert, M. J. Alconada Verzini, S. Alderweireldt, M. Aleksa, I. N. Aleksandrov, C. Alexa, T. Alexopoulos, A. Alfonsi, F. Alfonsi, M. Alhroob, B. Ali, M. Aliev, G. Alimonti, C. Allaire, B. M. M. Allbrooke, B. W. Allen, P. P. Allport, A. Aloisio, F. Alonso, C. Alpigiani, A. A. Alshehri, E. Alunno Camelia, M. Alvarez Estevez, M. G. Alviggi, Y. Amaral Coutinho, A. Ambler, L. Ambroz, C. Amelung, D. Amidei, S. P. Amor Dos Santos, S. Amoroso, C. S. Amrouche, F. An, C. Anastopoulos, N. Andari, T. Andeen, C. F. Anders, J. K. Anders, A. Andreazza, V. Andrei, C. R. Anelli, S. Angelidakis, A. Angerami, A. V. Anisenkov, A. Annovi, C. Antel, M. T. Anthony, E. Antipov, M. Antonelli, D. J. A. Antrim, F. Anulli, M. Aoki, J. A. Aparisi Pozo, L. Aperio Bella, J. P. Araque, V. Araujo Ferraz, R. Araujo Pereira, C. Arcangeletti, A. T. H. Arce, F. A. Arduh, J-F. Arguin, S. Argyropoulos, J.-H. Arling, A. J. Armbruster, A. Armstrong, O. Arnaez, H. Arnold, Z. P. Arrubarrena Tame, G. Artoni, S. Artz, S. Asai, T. Asawatavonvanich, N. A. Asbah, E. M. Asimakopoulou, L. Asquith, J. Assahsah, K. Assamagan, R. Astalos, R. J. Atkin, M. Atkinson, N. B. Atlay, H. Atmani, K. Augsten, G. Avolio, M. K. Ayoub, G. Azuelos, H. Bachacou, K. Bachas, M. Backes, F. Backman, P. Bagnaia, H. Bahrasemani, A. J. Bailey, V. R. Bailey, J. T. Baines, C. Bakalis, O. K. Baker, P. J. Bakker, D. Bakshi Gupta, S. Balaji, E. M. Baldin, P. 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Watson, G. Watts, B. M. Waugh, A. F. Webb, S. Webb, C. Weber, M. S. Weber, S. A. Weber, S. M. Weber, A. R. Weidberg, J. Weingarten, M. Weirich, C. Weiser, P. S. Wells, T. Wenaus, T. Wengler, S. Wenig, N. Wermes, M. D. Werner, M. Wessels, T. D. Weston, K. Whalen, N. L. Whallon, A. M. Wharton, A. S. White, A. White, M. J. White, D. Whiteson, B. W. Whitmore, W. Wiedenmann, C. Wiel, M. Wielers, N. Wieseotte, C. Wiglesworth, L. A. M. Wiik-Fuchs, H. G. Wilkens, L. J. Wilkins, H. H. Williams, S. Williams, C. Willis, S. Willocq, I. Wingerter-Seez, E. Winkels, F. Winklmeier, O. J. Winston, B. T. Winter, M. Wittgen, M. Wobisch, A. Wolf, T. M. H. Wolf, R. Wolff, R. Wölker, J. Wollrath, M. W. Wolter, H. Wolters, V. W. S. Wong, N. L. Woods, S. D. Worm, B. K. Wosiek, K. W. Woźniak, K. Wraight, S. L. Wu, X. Wu, Y. Wu, T. R. Wyatt, B. M. Wynne, S. Xella, Z. Xi, X. Xiao, I. Xiotidis, D. Xu, H. Xu, L. Xu, T. Xu, W. Xu, Z. Xu, B. Yabsley, S. Yacoob, K. Yajima, D. P. Yallup, N. Yamaguchi, Y. Yamaguchi, A. Yamamoto, M. Yamatani, T. Yamazaki, Y. Yamazaki, Z. Yan, H. J. Yang, H. T. Yang, S. Yang, T. Yang, X. Yang, Y. Yang, W-M. Yao, Y. C. Yap, Y. Yasu, E. Yatsenko, H. Ye, J. Ye, S. Ye, I. Yeletskikh, M. R. Yexley, E. Yigitbasi, K. Yorita, K. Yoshihara, C. J. S. Young, C. Young, J. Yu, R. Yuan, X. Yue, M. Zaazoua, B. Zabinski, G. Zacharis, E. Zaffaroni, T. Zakareishvili, N. Zakharchuk, S. Zambito, D. Zanzi, D. R. Zaripovas, S. V. Zeißner, C. Zeitnitz, G. Zemaityte, J. C. Zeng, O. Zenin, T. Ženiš, D. Zerwas, M. Zgubič, B. Zhang, D. F. Zhang, G. Zhang, H. Zhang, J. Zhang, L. Zhang, M. Zhang, R. Zhang, S. Zhang, X. Zhang, Y. Zhang, Z. Zhang, P. Zhao, Z. Zhao, A. Zhemchugov, Z. Zheng, D. Zhong, B. Zhou, C. Zhou, M. S. Zhou, M. Zhou, N. Zhou, Y. Zhou, C. G. Zhu, C. Zhu, H. L. Zhu, H. Zhu, J. Zhu, Y. Zhu, X. Zhuang, K. Zhukov, V. Zhulanov, D. Zieminska, N. I. Zimine, S. Zimmermann, Z. Zinonos, M. Ziolkowski, L. Živković, G. Zobernig, A. Zoccoli, K. Zoch, T. G. Zorbas, R. Zou, and L. Zwalinski
Subjects: Hadron-Hadron Scattering, Top Physics, Nuclear and particle physics. Atomic energy. Radioactivity, QC770-798
Abstract: Abstract A measurement of the top-quark mass (m t ) in the t t ¯ $$ t\overline{t} $$ → lepton + jets channel is presented, with an experimental technique which exploits semileptonic decays of b-hadrons produced in the top-quark decay chain. The distribution of the invariant mass m ℓμ of the lepton, ℓ (with ℓ = e, μ), from the W-boson decay and the muon, μ, originating from the b-hadron decay is reconstructed, and a binned-template profile likelihood fit is performed to extract m t . The measurement is based on data corresponding to an integrated luminosity of 36.1 fb −1 of s $$ \sqrt{s} $$ = 13 TeV pp collisions provided by the Large Hadron Collider and recorded by the ATLAS detector. The measured value of the top-quark mass is m t = 174.41 ± 0.39 (stat.) ± 0.66 (syst.) ± 0.25 (recoil) GeV, where the third uncertainty arises from changing the Pythia8 parton shower gluon-recoil scheme, used in top-quark decays, to a recently developed setup.
Published: 2023
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43. Who Can Make Joe Go? Democrats stared into the debate abyss. Now they ask if he's a lost cause

Author: Debenedetti, Gabriel
Subjects: Political parties, Campaign debates, General interest, News, opinion and commentary
Abstract: A FEW MINUTES into the June 27 presidential debate in Atlanta, when Joe Biden's wavering answers first trailed off into incoherence, I got a text from a Democratic congressman close [...]
Published: 2024

44. Intra-articular corticosteroid injections are associated with a dose-dependent risk of total knee arthroplasty at 5 years

Author: Burnett, III, Robert A., Khalid, Syed, DeBenedetti, Anne, Terhune, E. Bailey, Angotti, Morgan L., and Della Valle, Craig J.
Published: 2023
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45. Atomically smooth films of CsSb: A chemically robust visible light photocathode

Author: C. T. Parzyck, C. A. Pennington, W. J. I. DeBenedetti, J. Balajka, E. M. Echeverria, H. Paik, L. Moreschini, B. D. Faeth, C. Hu, J. K. Nangoi, V. Anil, T. A. Arias, M. A. Hines, D. G. Schlom, A. Galdi, K. M. Shen, and J. M. Maxson
Subjects: Biotechnology, TP248.13-248.65, Physics, QC1-999
Abstract: Alkali antimonide semiconductor photocathodes provide a promising platform for the generation of high-brightness electron beams, which are necessary for the development of cutting-edge probes, including x-ray free electron lasers and ultrafast electron diffraction. Nonetheless, to harness the intrinsic brightness limits in these compounds, extrinsic degrading factors, including surface roughness and contamination, must be overcome. By exploring the growth of CsxSb thin films monitored by in situ electron diffraction, the conditions to reproducibly synthesize atomically smooth films of CsSb on 3C–SiC (100) and graphene-coated TiO2 (110) substrates are identified, and detailed structural, morphological, and electronic characterization is presented. These films combine high quantum efficiency in the visible (up to 1.2% at 400 nm), an easily accessible photoemission threshold of 566 nm, low surface roughness (down to 600 pm on a 1 μm scale), and a robustness against oxidation up to 15 times greater than Cs3Sb. These properties lead us to suggest that CsSb has the potential to operate as an alternative to Cs3Sb in electron source applications where the demands of the vacuum environment might otherwise preclude the use of traditional alkali antimonides.
Published: 2023
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46. Dual-Mobility versus Large Femoral Heads in Revision Total Hip Arthroplasty: Interim Analysis of a Randomized Controlled Trial

Author: Weintraub, Matthew T., DeBenedetti, Anne, Nam, Denis, Darrith, Brian, Baker, Colin M., Waren, Daniel, Schwarzkopf, Ran, Courtney, P. Maxwell, and Della Valle, Craig J.
Published: 2023
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47. Special Topic Preface: Nucleation—Current understanding approaching 150 years after Gibbs.

Author: Debenedetti, Pablo G., Kim, Yi-Yeoun, Meldrum, Fiona C., and Tanaka, Hajime
Subjects: *NUCLEATION
Abstract: This article explores the concept of nucleation, which is the formation of small nuclei that eventually lead to the creation of a new phase. Nucleation is involved in various processes such as ice formation, drug crystallization, and the setting of concrete. The classical theory of nucleation, developed by Gibbs, is widely used but has limitations. The article emphasizes the need for new theories and computational methods to accurately describe nucleation mechanisms, considering factors like size, non-classical pathways, and stochastic effects. The collection of articles in this issue provides an overview of nucleation in different scientific fields, including ice formation, biomedical applications, and functional materials. Recent research in this area has utilized experimental techniques, simulations, and theoretical models to investigate factors influencing nucleation, such as surface properties and composition. Understanding nucleation mechanisms is crucial for applications in materials science, nanotechnology, and environmental science. The article highlights the progress made in recent years and the potential for further advancements in our understanding of nucleation processes. [Extracted from the article]
Published: 2024
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48. Free-energy landscape and spinodals for the liquid–liquid transition of the TIP4P/2005 and TIP4P/Ice models of water.

Author: Sciortino, Francesco, Gartner III, Thomas E., and Debenedetti, Pablo G.
Subjects: GIBBS' energy diagram, CRITICAL temperature, METASTABLE states, CRITICAL point (Thermodynamics)
Abstract: Continued increases in computational power now make it possible to evaluate the free-energy landscape associated with the first-order liquid–liquid transition in realistic models of water for which an accurate estimate of the liquid–liquid critical point exists, and to explore its change with pressure near the coexistence line. We report the results of 50 μs-long NPT umbrella sampling simulations for two realistic models for water, TIP4P/2005 and TIP4P/ice, 3–9 K below their critical temperatures. The free energy profile at different pressures clearly shows the presence of two well-defined free energy basins and makes it possible to identify the liquid–liquid spinodal points, the limits of stability that define the (temperature dependent) pressure range within which two distinct free energy basins exist. The results show that for temperatures less than 10 K below the critical temperature, metastable states are possible across a very limited pressure interval, information that is relevant to the interpretation of experiments probing the metastable phase behavior of deeply supercooled water in the so-called no-man's land. [ABSTRACT FROM AUTHOR]
Published: 2024
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49. Vitamin D3 Supplementation Prior to Total Knee Arthroplasty: A Randomized Controlled Trial

Author: Weintraub, Matthew T., Guntin, Jonathan, Yang, JaeWon, DeBenedetti, Anne, Karas, Vasili, Della Valle, Craig J., and Nam, Denis
Published: 2023
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50. Measurement of the top-quark mass using a leptonic invariant mass in pp collisions at s = 13 TeV with the ATLAS detector

Author: Aad, G., Abbott, B., Abbott, D. C., Abed Abud, A., Abeling, K., Abhayasinghe, D. K., Abidi, S. H., AbouZeid, O. S., Abraham, N. L., Abramowicz, H., Abreu, H., Abulaiti, Y., Acharya, B. S., Achkar, B., Adachi, S., Adam, L., Adam Bourdarios, C., Adamczyk, L., Adamek, L., Adelman, J., Adersberger, M., Adiguzel, A., Adorni, S., Adye, T., Affolder, A. A., Afik, Y., Agapopoulou, C., Agaras, M. N., Aggarwal, A., Agheorghiesei, C., Aguilar-Saavedra, J. A., Ahmadov, F., Ahmed, W. S., Ai, X., Aielli, G., Akatsuka, S., Åkesson, T. P. A., Akilli, E., Akimov, A. V., Al Khoury, K., Alberghi, G. L., Albert, J., Alconada Verzini, M. J., Alderweireldt, S., Aleksa, M., Aleksandrov, I. N., Alexa, C., Alexopoulos, T., Alfonsi, A., Alfonsi, F., Alhroob, M., Ali, B., Aliev, M., Alimonti, G., Allaire, C., Allbrooke, B. M. M., Allen, B. W., Allport, P. P., Aloisio, A., Alonso, F., Alpigiani, C., Alshehri, A. A., Alunno Camelia, E., Alvarez Estevez, M., Alviggi, M. G., Amaral Coutinho, Y., Ambler, A., Ambroz, L., Amelung, C., Amidei, D., Amor Dos Santos, S. P., Amoroso, S., Amrouche, C. S., An, F., Anastopoulos, C., Andari, N., Andeen, T., Anders, C. F., Anders, J. K., Andreazza, A., Andrei, V., Anelli, C. R., Angelidakis, S., Angerami, A., Anisenkov, A. V., Annovi, A., Antel, C., Anthony, M. T., Antipov, E., Antonelli, M., Antrim, D. J. A., Anulli, F., Aoki, M., Aparisi Pozo, J. A., Aperio Bella, L., Araque, J. P., Araujo Ferraz, V., Araujo Pereira, R., Arcangeletti, C., Arce, A. T. H., Arduh, F. A., Arguin, J-F., Argyropoulos, S., Arling, J.-H., Armbruster, A. J., Armstrong, A., Arnaez, O., Arnold, H., Arrubarrena Tame, Z. P., Artoni, G., Artz, S., Asai, S., Asawatavonvanich, T., Asbah, N. A., Asimakopoulou, E. M., Asquith, L., Assahsah, J., Assamagan, K., Astalos, R., Atkin, R. J., Atkinson, M., Atlay, N. B., Atmani, H., Augsten, K., Avolio, G., Ayoub, M. K., Azuelos, G., Bachacou, H., Bachas, K., Backes, M., Backman, F., Bagnaia, P., Bahrasemani, H., Bailey, A. J., Bailey, V. R., Baines, J. T., Bakalis, C., Baker, O. K., Bakker, P. J., Bakshi Gupta, D., Balaji, S., Baldin, E. M., Balek, P., Balli, F., Balunas, W. K., Balz, J., Banas, E., Bandyopadhyay, A., Banerjee, Sw., Bannoura, A. A. E., Barak, L., Barbe, W. M., Barberio, E. L., Barberis, D., Barbero, M., Barbour, G., Barillari, T., Barisits, M-S., Barkeloo, J., Barklow, T., Barnea, R., Barnett, B. M., Barnett, R. M., Barnovska-Blenessy, Z., Baroncelli, A., Barone, G., Barr, A. J., Barranco Navarro, L., Barreiro, F., Barreiro Guimarães da Costa, J., Barsov, S., Bartoldus, R., Bartolini, G., Barton, A. E., Bartos, P., Basalaev, A., Basan, A., Bassalat, A., Basso, M. J., Bates, R. L., Batlamous, S., Batley, J. R., Batool, B., Battaglia, M., Bauce, M., Bauer, F., Bauer, K. T., Bawa, H. S., Beacham, J. B., Beau, T., Beauchemin, P. H., Becherer, F., Bechtle, P., Beck, H. C., Beck, H. P., Becker, K., Becot, C., Beddall, A., Beddall, A. J., Bednyakov, V. A., Bedognetti, M., Bee, C. P., Beermann, T. A., Begalli, M., Begel, M., Behera, A., Behr, J. K., Beisiegel, F., Bell, A. S., Bella, G., Bellagamba, L., Bellerive, A., Bellos, P., Beloborodov, K., Belotskiy, K., Belyaev, N. L., Benchekroun, D., Benekos, N., Benhammou, Y., Benjamin, D. P., Benoit, M., Bensinger, J. R., Bentvelsen, S., Beresford, L., Beretta, M., Berge, D., Bergeaas Kuutmann, E., Berger, N., Bergmann, B., Bergsten, L. J., Beringer, J., Berlendis, S., Bernardi, G., Bernius, C., Bernlochner, F. U., Berry, T., Berta, P., Bertella, C., Bertram, I. A., Bessidskaia Bylund, O., Besson, N., Bethani, A., Bethke, S., Betti, A., Bevan, A. J., Beyer, J., Bhattacharya, D. S., Bhattarai, P., Bi, R., Bianchi, R. M., Biebel, O., Biedermann, D., Bielski, R., Bierwagen, K., Biesuz, N. V., Biglietti, M., Billoud, T. R. V., Bindi, M., Bingul, A., Bini, C., Biondi, S., Birman, M., Bisanz, T., Biswas, D., Bitadze, A., Bittrich, C., Bjørke, K., Blazek, T., Bloch, I., Blocker, C., Blue, A., Blumenschein, U., Bobbink, G. J., Bobrovnikov, V. S., Bocchetta, S. S., Bocci, A., Bogavac, D., Bogdanchikov, A. G., Bohm, C., Boisvert, V., Bokan, P., Bold, T., Bolz, A. E., Bomben, M., Bona, M., Bonilla, J. S., Boonekamp, M., Booth, C. D., Borecka-Bielska, H. M., Borgna, L. S., Borisov, A., Borissov, G., Bortfeldt, J., Bortoletto, D., Boscherini, D., Bosman, M., Bossio Sola, J. D., Bouaouda, K., Boudreau, J., Bouhova-Thacker, V., Boumediene, D., Boutle, S. K., Boveia, A., Boyd, J., Boye, D., Boyko, I. R., Bozson, A. J., Bracinik, J., Brahimi, N., Brandt, G., Brandt, O., Braren, F., Brau, B., Brau, J. E., Breaden Madden, W. D., Brendlinger, K., Brenner, L., Brenner, R., Bressler, S., Brickwedde, B., Briglin, D. L., Britton, D., Britzger, D., Brock, I., Brock, R., Brooijmans, G., Brooks, W. K., Brost, E., Broughton, J. H, Bruckman de Renstrom, P. A., Bruncko, D., Bruni, A., Bruni, G., Bruni, L. S., Bruno, S., Bruschi, M., Bruscino, N., Bryant, P., Bryngemark, L., Buanes, T., Buat, Q., Buchholz, P., Buckley, A. G., Budagov, I. A., Bugge, M. K., Bührer, F., Bulekov, O., Burch, T. J., Burdin, S., Burgard, C. D., Burger, A. M., Burghgrave, B., Burr, J. T. P., Burton, C. D., Burzynski, J. C., Büscher, V., Buschmann, E., Bussey, P. J., Butler, J. M., Buttar, C. M., Butterworth, J. M., Butti, P., Buttinger, W., Buxo Vazquez, C. J., Buzatu, A., Buzykaev, A. R., Cabras, G., Cabrera Urbán, S., Caforio, D., Cai, H., Cairo, V. M. M., Cakir, O., Calace, N., Calafiura, P., Calandri, A., Calderini, G., Calfayan, P., Callea, G., Caloba, L. P., Caltabiano, A., Calvente Lopez, S., Calvet, D., Calvet, S., Calvet, T. P., Calvetti, M., Camacho Toro, R., Camarda, S., Camarero Munoz, D., Camarri, P., Cameron, D., Camincher, C., Campana, S., Campanelli, M., Camplani, A., Campoverde, A., Canale, V., Canesse, A., Cano Bret, M., Cantero, J., Cao, T., Cao, Y., Capeans Garrido, M. D. M., Capua, M., Cardarelli, R., Cardillo, F., Carli, I., Carli, T., Carlino, G., Carlson, B. T., Carminati, L., Carney, R. M. D., Caron, S., Carquin, E., Carrá, S., Carter, J. W. S., Casado, M. P., Casha, A. F., Casper, D. W., Castelijn, R., Castillo, F. L., Castillo Garcia, L., Castillo Gimenez, V., Castro, N. F., Catinaccio, A., Catmore, J. R., Cattai, A., Cavaliere, V., Cavallaro, E., Cavalli-Sforza, M., Cavasinni, V., Celebi, E., Cerda Alberich, L., Cerny, K., Cerqueira, A. S., Cerri, A., Cerrito, L., Cerutti, F., Cervelli, A., Cetin, S. A., Chadi, Z., Chakraborty, D., Chan, J., Chan, W. S., Chan, W. Y., Chapman, J. D., Chargeishvili, B., Charlton, D. G., Charman, T. P., Chau, C. C., Che, S., Chekanov, S., Chekulaev, S. V., Chelkov, G. A., Chen, B., Chen, C., Chen, C. H., Chen, H., Chen, J., Chen, J., Chen, J., Chen, S., Chen, S. J., Chen, X., Chen, Y-H., Cheng, H. C., Cheng, H. J., Cheplakov, A., Cheremushkina, E., Cherkaoui El Moursli, R., Cheu, E., Cheung, K., Chevalérias, T. J. A., Chevalier, L., Chiarella, V., Chiarelli, G., Chiodini, G., Chisholm, A. S., Chitan, A., Chiu, I., Chiu, Y. H., Chizhov, M. V., Choi, K., Chomont, A. R., Chouridou, S., Chow, E. Y. S., Chu, M. C., Chu, X., Chudoba, J., Chwastowski, J. J., Chytka, L., Cieri, D., Ciesla, K. M., Cinca, D., Cindro, V., Cioară, I. A., Ciocio, A., Cirotto, F., Citron, Z. H., Citterio, M., Ciubotaru, D. A., Ciungu, B. M., Clark, A., Clark, M. R., Clark, P. J., Clement, C., Coadou, Y., Cobal, M., Coccaro, A., Cochran, J., Coelho Lopes De Sa, R., Cohen, H., Coimbra, A. E. C., Cole, B., Colijn, A. P., Collot, J., Conde Muiño, P., Connell, S. H., Connelly, I. A., Constantinescu, S., Conventi, F., Cooper-Sarkar, A. 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R., Olszewski, A., Olszowska, J., O’Neil, D. C., O’Neill, A. P., Onofre, A., Onyisi, P. U. E., Oppen, H., Oreglia, M. J., Orellana, G. E., Orestano, D., Orlando, N., Orr, R. S., O’Shea, V., Ospanov, R., Otero y Garzon, G., Otono, H., Ott, P. S., Ouchrif, M., Ouellette, J., Ould-Saada, F., Ouraou, A., Ouyang, Q., Owen, M., Owen, R. E., Ozcan, V. E., Ozturk, N., Pacalt, J., Pacey, H. A., Pachal, K., Pacheco Pages, A., Padilla Aranda, C., Pagan Griso, S., Paganini, M., Palacino, G., Palazzo, S., Palestini, S., Palka, M., Pallin, D., Palni, P., Panagoulias, I., Pandini, C. E., Panduro Vazquez, J. G., Pani, P., Panizzo, G., Paolozzi, L., Papadatos, C., Papageorgiou, K., Parajuli, S., Paramonov, A., Paredes Hernandez, D., Paredes Saenz, S. R., Parida, B., Park, T. H., Parker, A. J., Parker, M. A., Parodi, F., Parrish, E. W., Parsons, J. A., Parzefall, U., Pascual Dominguez, L., Pascuzzi, V. R., Pasner, J. M. P., Pasquali, F., Pasqualucci, E., Passaggio, S., Pastore, F., Pasuwan, P., Pataraia, S., Pater, J. R., Pathak, A., Patton, J., Pauly, T., Pearkes, J., Pearson, B., Pedersen, M., Pedraza Diaz, L., Pedro, R., Peiffer, T., Peleganchuk, S. V., Penc, O., Peng, H., Peralva, B. S., Perego, M. M., Pereira Peixoto, A. P., Perepelitsa, D. V., Peri, F., Perini, L., Pernegger, H., Perrella, S., Perrevoort, A., Peters, K., Peters, R. F. Y., Petersen, B. A., Petersen, T. C., Petit, E., Petridis, A., Petridou, C., Petrov, M., Petrucci, F., Pettee, M., Pettersson, N. E., Petukhova, K., Peyaud, A., Pezoa, R., Pezzotti, L., Pham, T., Phillips, F. H., Phillips, P. W., Phipps, M. W., Piacquadio, G., Pianori, E., Picazio, A., Pickles, R. H., Piegaia, R., Pietreanu, D., Pilcher, J. E., Pilkington, A. D., Pinamonti, M., Pinfold, J. L., Pitt, M., Pizzimento, L., Pleier, M.-A., Pleskot, V., Plotnikova, E., Podberezko, P., Poettgen, R., Poggi, R., Poggioli, L., Pogrebnyak, I., Pohl, D., Pokharel, I., Polesello, G., Poley, A., Policicchio, A., Polifka, R., Polini, A., Pollard, C. S., Polychronakos, V., Ponomarenko, D., Pontecorvo, L., Popa, S., Popeneciu, G. A., Portales, L., Portillo Quintero, D. M., Pospisil, S., Potamianos, K., Potrap, I. N., Potter, C. J., Potti, H., Poulsen, T., Poveda, J., Powell, T. D., Pownall, G., Pozo Astigarraga, M. E., Pralavorio, P., Prell, S., Price, D., Primavera, M., Prince, S., Proffitt, M. L., Proklova, N., Prokofiev, K., Protopopescu, S., Proudfoot, J., Przybycien, M., Pudzha, D., Puri, A., Puzo, P., Qian, J., Qin, Y., Quadt, A., Queitsch-Maitland, M., Qureshi, A., Racko, M., Ragusa, F., Rahal, G., Raine, J. A., Rajagopalan, S., Ramirez Morales, A., Ran, K., Rashid, T., Raspopov, S., Rauch, D. M., Rauscher, F., Rave, S., Ravina, B., Ravinovich, I., Rawling, J. H., Raymond, M., Read, A. L., Readioff, N. P., Reale, M., Rebuzzi, D. M., Redelbach, A., Redlinger, G., Reeves, K., Rehnisch, L., Reichert, J., Reikher, D., Reiss, A., Rej, A., Rembser, C., Renardi, A., Renda, M., Rescigno, M., Resconi, S., Resseguie, E. D., Rettie, S., Reynolds, B., Reynolds, E., Rezanova, O. L., Reznicek, P., Ricci, E., Richter, R., Richter, S., Richter-Was, E., Ricken, O., Ridel, M., Rieck, P., Rifki, O., Rijssenbeek, M., Rimoldi, A., Rimoldi, M., Rinaldi, L., Ripellino, G., Riu, I., Rivera Vergara, J. C., Rizatdinova, F., Rizvi, E., Rizzi, C., Roberts, R. T., Robertson, S. H., Robin, M., Robinson, D., Robles Gajardo, C. M., Robles Manzano, M., Robson, A., Rocchi, A., Rocco, E., Roda, C., Rodriguez Bosca, S., Rodriguez Perez, A., Rodriguez Rodriguez, D., Rodríguez Vera, A. M., Roe, S., Røhne, O., Röhrig, R., Rojas, R. A., Roland, B., Roland, C. P. A., Roloff, J., Romaniouk, A., Romano, M., Rompotis, N., Ronzani, M., Roos, L., Rosati, S., Rosin, G., Rosser, B. J., Rossi, E., Rossi, E., Rossi, E., Rossi, L. P., Rossini, L., Rosten, R., Rotaru, M., Rothberg, J., Rottler, B., Rousseau, D., Rovelli, G., Roy, A., Roy, D., Rozanov, A., Rozen, Y., Ruan, X., Rühr, F., Ruiz-Martinez, A., Rummler, A., Rurikova, Z., Rusakovich, N. A., Russell, H. L., Rustige, L., Rutherfoord, J. P., Rüttinger, E. M., Rybar, M., Rybkin, G., Rye, E. B., Ryzhov, A., Sabater Iglesias, J. A., Sabatini, P., Sabato, G., Sacerdoti, S., Sadrozinski, H. F-W., Safai Tehrani, F., Safarzadeh Samani, B., Safdari, M., Saha, P., Saha, S., Sahinsoy, M., Sahu, A., Saimpert, M., Saito, M., Saito, T., Sakamoto, H., Sakharov, A., Salamani, D., Salamanna, G., Salazar Loyola, J. E., Salnikov, A., Salt, J., Salvatore, D., Salvatore, F., Salvucci, A., Salzburger, A., Samarati, J., Sammel, D., Sampsonidis, D., Sampsonidou, D., Sánchez, J., Sanchez Pineda, A., Sandaker, H., Sander, C. O., Sanderswood, I. G., Sandhoff, M., Sandoval, C., Sankey, D. P. C., Sannino, M., Sano, Y., Sansoni, A., Santoni, C., Santos, H., Santpur, S. N., Santra, A., Saraiva, J. G., Sardain, J., Sasaki, O., Sato, K., Sauerburger, F., Sauvan, E., Savard, P., Sawada, R., Sawyer, C., Sawyer, L., Sbarra, C., Sbrizzi, A., Scanlon, T., Schaarschmidt, J., Schacht, P., Schachtner, B. M., Schaefer, D., Schaefer, L., Schaeffer, J., Schaepe, S., Schäfer, U., Schaffer, A. C., Schaile, D., Schamberger, R. D., Scharmberg, N., Schegelsky, V. A., Scheirich, D., Schenck, F., Schernau, M., Schiavi, C., Schildgen, L. K., Schillaci, Z. M., Schioppa, E. J., Schioppa, M., Schleicher, K. E., Schlenker, S., Schmidt-Sommerfeld, K. R., Schmieden, K., Schmitt, C., Schmitt, S., Schmitz, S., Schmoeckel, J. C., Schoeffel, L., Schoening, A., Scholer, P. G., Schopf, E., Schott, M., Schouwenberg, J. F. P., Schovancova, J., Schramm, S., Schroeder, F., Schulte, A., Schultz-Coulon, H-C., Schumacher, M., Schumm, B. A., Schune, Ph., Schwartzman, A., Schwarz, T. A., Schwemling, Ph., Schwienhorst, R., Sciandra, A., Sciolla, G., Scodeggio, M., Scornajenghi, M., Scuri, F., Scutti, F., Scyboz, L. M., Sebastiani, C. D., Seema, P., Seidel, S. C., Seiden, A., Seidlitz, B. D., Seiss, T., Seixas, J. M., Sekhniaidze, G., Sekula, S. J., Semprini-Cesari, N., Sen, S., Serfon, C., Serin, L., Serkin, L., Sessa, M., Severini, H., Sevova, S., Šfiligoj, T., Sforza, F., Sfyrla, A., Shabalina, E., Shahinian, J. D., Shaikh, N. W., Shaked Renous, D., Shan, L. Y., Shank, J. T., Shapiro, M., Sharma, A., Sharma, A. S., Shatalov, P. B., Shaw, K., Shaw, S. M., Shehade, M., Shen, Y., Sherman, A. D., Sherwood, P., Shi, L., Shimizu, S., Shimmin, C. O., Shimogama, Y., Shimojima, M., Shipsey, I. P. J., Shirabe, S., Shiyakova, M., Shlomi, J., Shmeleva, A., Shochet, M. J., Shojaii, J., Shope, D. R., Shrestha, S., Shrif, E. M., Shulga, E., Sicho, P., Sickles, A. M., Sidebo, P. E., Sideras Haddad, E., Sidiropoulou, O., Sidoti, A., Siegert, F., Sijacki, Dj., Silva, M. Jr., Silva Oliveira, M. V., Silverstein, S. B., Simion, S., Simoniello, R., Simsek, S., Sinervo, P., Sinetckii, V., Sinev, N. B., Singh, S., Sioli, M., Siral, I., Sivoklokov, S. Yu., Sjölin, J., Skorda, E., Skubic, P., Slawinska, M., Sliwa, K., Slovak, R., Smakhtin, V., Smart, B. H., Smiesko, J., Smirnov, N., Smirnov, S. Yu., Smirnov, Y., Smirnova, L. N., Smirnova, O., Smith, J. W., Smizanska, M., Smolek, K., Smykiewicz, A., Snesarev, A. A., Snoek, H. L., Snyder, I. M., Snyder, S., Sobie, R., Soffer, A., Søgaard, A., Sohns, F., Solans Sanchez, C. A., Soldatov, E. Yu., Soldevila, U., Solodkov, A. A., Soloshenko, A., Solovyanov, O. V., Solovyev, V., Sommer, P., Son, H., Song, W., Song, W. Y., Sopczak, A., Sopio, A. L., Sopkova, F., Sotiropoulou, C. L., Sottocornola, S., Soualah, R., South, D., Spagnolo, S., Spalla, M., Spangenberg, M., Spanò, F., Sperlich, D., Spieker, T. M., Spigo, G., Spina, M., Spiteri, D. P., Spousta, M., Stabile, A., Stamen, R., Stamenkovic, M., Stanecka, E., Stanislaus, B., Stanitzki, M. M., Stankaityte, M., Stapf, B., Starchenko, E. A., Stark, G. H., Stark, J., Staroba, P., Starovoitov, P., Stärz, S., Staszewski, R., Stavropoulos, G., Stegler, M., Steinberg, P., Steinhebel, A. L., Stelzer, B., Stelzer, H. J., Stelzer-Chilton, O., Stenzel, H., Stevenson, T. J., Stewart, G. A., Stockton, M. C., Stoicea, G., Stolarski, M., Stonjek, S., Straessner, A., Strandberg, J., Strandberg, S., Strauss, M., Strizenec, P., Ströhmer, R., Strom, D. M., Stroynowski, R., Strubig, A., Stucci, S. A., Stugu, B., Stupak, J., Styles, N. A., Su, D., Su, W., Suchek, S., Sulin, V. V., Sullivan, M. J., Sultan, D. M. S., Sultansoy, S., Sumida, T., Sun, S., Sun, X., Suruliz, K., Suster, C. J. E., Sutton, M. R., Suzuki, S., Svatos, M., Swiatlowski, M., Swift, S. 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A., Timoshenko, S., Tipton, P., Tisserant, S., Todome, K., Todorova-Nova, S., Todt, S., Tojo, J., Tokár, S., Tokushuku, K., Tolley, E., Tomiwa, K. G., Tomoto, M., Tompkins, L., Tong, B., Tornambe, P., Torrence, E., Torres, H., Torró Pastor, E., Tosciri, C., Toth, J., Tovey, R., Traeet, A., Treado, C. J., Trefzger, T., Tresoldi, F., Tricoli, A., Trigger, I. M., Trincaz-Duvoid, S., Trischuk, D. A., Trocmé, B., Trofymov, A., Troncon, C., Trovato, F., Truong, L., Trzebinski, M., Trzupek, A., Tsai, F., Tseng, J. C-L., Tsiareshka, P. V., Tsirigotis, A., Tsiskaridze, V., Tskhadadze, E. G., Tsopoulou, M., Tsukerman, I. I., Tsulaia, V., Tsuno, S., Tsybychev, D., Tu, Y., Tudorache, A., Tudorache, V., Tulbure, T. T., Tuna, A. N., Turchikhin, S., Turgeman, D., Turk Cakir, I., Turner, R. J., Turra, R., Tuts, P. M., Tzamarias, S., Tzovara, E., Ucchielli, G., Uchida, K., Ukegawa, F., Unal, G., Undrus, A., Unel, G., Ungaro, F. C., Unno, Y., Uno, K., Urban, J., Urquijo, P., Usai, G., Uysal, Z., Vacek, V., Vachon, B., Vadla, K. O. H., Vaidya, A., Valderanis, C., Valdes Santurio, E., Valente, M., Valentinetti, S., Valero, A., Valéry, L., Vallance, R. A., Vallier, A., Valls Ferrer, J. A., Van Daalen, T. R., Van Gemmeren, P., Van Vulpen, I., Vanadia, M., Vandelli, W., Vandenbroucke, M., Vandewall, E. R., Vaniachine, A., Vannicola, D., Vari, R., Varnes, E. W., Varni, C., Varol, T., Varouchas, D., Varvell, K. E., Vasile, M. E., Vasquez, G. A., Vazeille, F., Vazquez Furelos, D., Vazquez Schroeder, T., Veatch, J., Vecchio, V., Veen, M. J., Veloce, L. M., Veloso, F., Veneziano, S., Ventura, A., Venturi, N., Verbytskyi, A., Vercesi, V., Verducci, M., Vergel Infante, C. M., Vergis, C., Verkerke, W., Vermeulen, A. T., Vermeulen, J. C., Vetterli, M. C., Viaux Maira, N., Vicente Barreto Pinto, M., Vickey, T., Vickey Boeriu, O. E., Viehhauser, G. H. A., Vigani, L., Villa, M., Villaplana Perez, M., Vilucchi, E., Vincter, M. G., Virdee, G. S., Vishwakarma, A., Vittori, C., Vivarelli, I., Vogel, M., Vokac, P., von Buddenbrock, S. E., Von Toerne, E., Vorobel, V., Vorobev, K., Vos, M., Vossebeld, J. H., Vozak, M., Vranjes, N., Vranjes Milosavljevic, M., Vrba, V., Vreeswijk, M., Vuillermet, R., Vukotic, I., Wagner, P., Wagner, W., Wagner-Kuhr, J., Wahdan, S., Wahlberg, H., Walbrecht, V. M., Walder, J., Walker, R., Walker, S. D., Walkowiak, W., Wallangen, V., Wang, A. M., Wang, A. Z., Wang, C., Wang, F., Wang, H., Wang, H., Wang, J., Wang, J., Wang, P., Wang, Q., Wang, R.-J., Wang, R., Wang, R., Wang, S. M., Wang, W. T., Wang, W. X., Wang, Y., Wang, Z., Wanotayaroj, C., Warburton, A., Ward, C. P., Wardrope, D. R., Warrack, N., Washbrook, A., Watson, A. T., Watson, M. F., Watts, G., Waugh, B. M., Webb, A. F., Webb, S., Weber, C., Weber, M. S., Weber, S. A., Weber, S. M., Weidberg, A. R., Weingarten, J., Weirich, M., Weiser, C., Wells, P. S., Wenaus, T., Wengler, T., Wenig, S., Wermes, N., Werner, M. D., Wessels, M., Weston, T. D., Whalen, K., Whallon, N. L., Wharton, A. M., White, A. S., White, A., White, M. J., Whiteson, D., Whitmore, B. W., Wiedenmann, W., Wiel, C., Wielers, M., Wieseotte, N., Wiglesworth, C., Wiik-Fuchs, L. A. M., Wilkens, H. G., Wilkins, L. J., Williams, H. H., Williams, S., Willis, C., Willocq, S., Wingerter-Seez, I., Winkels, E., Winklmeier, F., Winston, O. J., Winter, B. T., Wittgen, M., Wobisch, M., Wolf, A., Wolf, T. M. H., Wolff, R., Wölker, R., Wollrath, J., Wolter, M. W., Wolters, H., Wong, V. W. S., Woods, N. L., Worm, S. D., Wosiek, B. K., Woźniak, K. W., Wraight, K., Wu, S. L., Wu, X., Wu, Y., Wyatt, T. R., Wynne, B. M., Xella, S., Xi, Z., Xiao, X., Xiotidis, I., Xu, D., Xu, H., Xu, H., Xu, L., Xu, T., Xu, W., Xu, Z., Xu, Z., Yabsley, B., Yacoob, S., Yajima, K., Yallup, D. P., Yamaguchi, N., Yamaguchi, Y., Yamamoto, A., Yamatani, M., Yamazaki, T., Yamazaki, Y., Yan, Z., Yang, H. J., Yang, H. T., Yang, S., Yang, T., Yang, X., Yang, Y., Yao, W-M., Yap, Y. C., Yasu, Y., Yatsenko, E., Ye, H., Ye, J., Ye, S., Yeletskikh, I., Yexley, M. R., Yigitbasi, E., Yorita, K., Yoshihara, K., Young, C. J. S., Young, C., Yu, J., Yuan, R., Yue, X., Zaazoua, M., Zabinski, B., Zacharis, G., Zaffaroni, E., Zakareishvili, T., Zakharchuk, N., Zambito, S., Zanzi, D., Zaripovas, D. R., Zeißner, S. V., Zeitnitz, C., Zemaityte, G., Zeng, J. C., Zenin, O., Ženiš, T., Zerwas, D., Zgubič, M., Zhang, B., Zhang, D. F., Zhang, G., Zhang, H., Zhang, J., Zhang, L., Zhang, L., Zhang, M., Zhang, R., Zhang, S., Zhang, X., Zhang, Y., Zhang, Z., Zhang, Z., Zhao, P., Zhao, Z., Zhemchugov, A., Zheng, Z., Zhong, D., Zhou, B., Zhou, C., Zhou, M. S., Zhou, M., Zhou, N., Zhou, Y., Zhu, C. G., Zhu, C., Zhu, H. L., Zhu, H., Zhu, J., Zhu, Y., Zhuang, X., Zhukov, K., Zhulanov, V., Zieminska, D., Zimine, N. I., Zimmermann, S., Zinonos, Z., Ziolkowski, M., Živković, L., Zobernig, G., Zoccoli, A., Zoch, K., Zorbas, T. G., Zou, R., and Zwalinski, L.
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