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1. Daniel Litt's Probability Puzzle

Author

Paterson, Maura B. and Stinson, Douglas R.

Subjects
Mathematics - Combinatorics
Abstract

In this expository note, we discuss a ``balls-and-urns'' probability puzzle posed by Daniel Litt.

Published
2024

2. Gemma 2: Improving Open Language Models at a Practical Size

Author

Gemma Team, Riviere, Morgane, Pathak, Shreya, Sessa, Pier Giuseppe, Hardin, Cassidy, Bhupatiraju, Surya, Hussenot, Léonard, Mesnard, Thomas, Shahriari, Bobak, Ramé, Alexandre, Ferret, Johan, Liu, Peter, Tafti, Pouya, Friesen, Abe, Casbon, Michelle, Ramos, Sabela, Kumar, Ravin, Lan, Charline Le, Jerome, Sammy, Tsitsulin, Anton, Vieillard, Nino, Stanczyk, Piotr, Girgin, Sertan, Momchev, Nikola, Hoffman, Matt, Thakoor, Shantanu, Grill, Jean-Bastien, Neyshabur, Behnam, Bachem, Olivier, Walton, Alanna, Severyn, Aliaksei, Parrish, Alicia, Ahmad, Aliya, Hutchison, Allen, Abdagic, Alvin, Carl, Amanda, Shen, Amy, Brock, Andy, Coenen, Andy, Laforge, Anthony, Paterson, Antonia, Bastian, Ben, Piot, Bilal, Wu, Bo, Royal, Brandon, Chen, Charlie, Kumar, Chintu, Perry, Chris, Welty, Chris, Choquette-Choo, Christopher A., Sinopalnikov, Danila, Weinberger, David, Vijaykumar, Dimple, Rogozińska, Dominika, Herbison, Dustin, Bandy, Elisa, Wang, Emma, Noland, Eric, Moreira, Erica, Senter, Evan, Eltyshev, Evgenii, Visin, Francesco, Rasskin, Gabriel, Wei, Gary, Cameron, Glenn, Martins, Gus, Hashemi, Hadi, Klimczak-Plucińska, Hanna, Batra, Harleen, Dhand, Harsh, Nardini, Ivan, Mein, Jacinda, Zhou, Jack, Svensson, James, Stanway, Jeff, Chan, Jetha, Zhou, Jin Peng, Carrasqueira, Joana, Iljazi, Joana, Becker, Jocelyn, Fernandez, Joe, van Amersfoort, Joost, Gordon, Josh, Lipschultz, Josh, Newlan, Josh, Ji, Ju-yeong, Mohamed, Kareem, Badola, Kartikeya, Black, Kat, Millican, Katie, McDonell, Keelin, Nguyen, Kelvin, Sodhia, Kiranbir, Greene, Kish, Sjoesund, Lars Lowe, Usui, Lauren, Sifre, Laurent, Heuermann, Lena, Lago, Leticia, McNealus, Lilly, Soares, Livio Baldini, Kilpatrick, Logan, Dixon, Lucas, Martins, Luciano, Reid, Machel, Singh, Manvinder, Iverson, Mark, Görner, Martin, Velloso, Mat, Wirth, Mateo, Davidow, Matt, Miller, Matt, Rahtz, Matthew, Watson, Matthew, Risdal, Meg, Kazemi, Mehran, Moynihan, Michael, Zhang, Ming, Kahng, Minsuk, Park, Minwoo, Rahman, Mofi, Khatwani, Mohit, Dao, Natalie, Bardoliwalla, Nenshad, Devanathan, Nesh, Dumai, Neta, Chauhan, Nilay, Wahltinez, Oscar, Botarda, Pankil, Barnes, Parker, Barham, Paul, Michel, Paul, Jin, Pengchong, Georgiev, Petko, Culliton, Phil, Kuppala, Pradeep, Comanescu, Ramona, Merhej, Ramona, Jana, Reena, Rokni, Reza Ardeshir, Agarwal, Rishabh, Mullins, Ryan, Saadat, Samaneh, Carthy, Sara Mc, Cogan, Sarah, Perrin, Sarah, Arnold, Sébastien M. R., Krause, Sebastian, Dai, Shengyang, Garg, Shruti, Sheth, Shruti, Ronstrom, Sue, Chan, Susan, Jordan, Timothy, Yu, Ting, Eccles, Tom, Hennigan, Tom, Kocisky, Tomas, Doshi, Tulsee, Jain, Vihan, Yadav, Vikas, Meshram, Vilobh, Dharmadhikari, Vishal, Barkley, Warren, Wei, Wei, Ye, Wenming, Han, Woohyun, Kwon, Woosuk, Xu, Xiang, Shen, Zhe, Gong, Zhitao, Wei, Zichuan, Cotruta, Victor, Kirk, Phoebe, Rao, Anand, Giang, Minh, Peran, Ludovic, Warkentin, Tris, Collins, Eli, Barral, Joelle, Ghahramani, Zoubin, Hadsell, Raia, Sculley, D., Banks, Jeanine, Dragan, Anca, Petrov, Slav, Vinyals, Oriol, Dean, Jeff, Hassabis, Demis, Kavukcuoglu, Koray, Farabet, Clement, Buchatskaya, Elena, Borgeaud, Sebastian, Fiedel, Noah, Joulin, Armand, Kenealy, Kathleen, Dadashi, Robert, and Andreev, Alek

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

In this work, we introduce Gemma 2, a new addition to the Gemma family of lightweight, state-of-the-art open models, ranging in scale from 2 billion to 27 billion parameters. In this new version, we apply several known technical modifications to the Transformer architecture, such as interleaving local-global attentions (Beltagy et al., 2020a) and group-query attention (Ainslie et al., 2023). We also train the 2B and 9B models with knowledge distillation (Hinton et al., 2015) instead of next token prediction. The resulting models deliver the best performance for their size, and even offer competitive alternatives to models that are 2-3 times bigger. We release all our models to the community.

Published
2024

3. Constraints on Relativistic Jets from the Fast X-ray Transient 210423 using Prompt Radio Follow-Up Observations

Author

Ibrahimzade, Dina, Margutti, R., Bright, J. S., Blanchard, P., Paterson, K., Lin, D., Sears, H., Polzin, A., Andreoni, I., Schroeder, G., Alexander, K. D., Berger, E., Coppejans, D. L., Hajela, A., Irwin, J., Laskar, T., Metzger, B. D., Rastinejad, J. C., and Rhodes, L.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

Fast X-ray Transients (FXTs) are a new observational class of phenomena with no clear physical origin. This is at least partially a consequence of limited multi-wavelength follow up of this class of transients in real time. Here we present deep optical ($g-$ and $i-$ band) photometry with Keck, and prompt radio observations with the VLA of FXT 210423 obtained at ${\delta t \approx 14-36}$ days since the X-ray trigger. We use these multi-band observations, combined with publicly available data sets, to constrain the presence and physical properties of on-axis and off-axis relativistic jets such as those that can be launched by neutron-star mergers and tidal disruption events, which are among the proposed theoretical scenarios of FXTs. Considering a wide range of possible redshifts $z\le3.5$, circumstellar medium (CSM) density $n={10^{-6}-10^{-1}\,\rm{cm^{-3}}}$, isotropic-equivalent jet kinetic energy $E_{k,iso}={10^{48}-10^{55}\,\rm{erg}}$, we find that we can rule out wide jets with opening angle ${\theta_{j}=15^{\circ}}$ viewed within ${10^{\circ}}$ off-axis. For more collimated jets (${\theta_{j}=3^{\circ}}$) we can only rule out on-axis (${\theta_{obs}=0^{\circ}}$) orientations. This study highlights the constraining power of prompt multi-wavelength observations of FXTs discovered in real time by current (e.g., Einstein Probe) and future facilities., Comment: 14 pages, 6 figures

Published
2024

4. Beyond uniform cyclotomy

Author

Huczynska, Sophie, Johnson, Laura, and Paterson, Maura B.

Subjects
Mathematics - Number Theory, Mathematics - Combinatorics, 11T22, 05B10
Abstract

Cyclotomy, the study of cyclotomic classes and cyclotomic numbers, is an area of number theory first studied by Gauss. It has natural applications in discrete mathematics and information theory. Despite this long history, there are significant limitations to what is known explicitly about cyclotomic numbers, which limits the use of cyclotomy in applications. The main explicit tool available is that of uniform cyclotomy, introduced by Baumert, Mills and Ward in 1982. In this paper, we present an extension of uniform cyclotomy which gives a direct method for evaluating all cyclotomic numbers over $GF(q^n)$ of order dividing $(q^n-1)/(q-1)$, for any prime power $q$ and $n \geq 2$, which does not use character theory nor direct calculation in the field. This allows the straightforward evaluation of many cyclotomic numbers for which other methods are unknown or impractical. Our methods exploit connections between cyclotomy, Singer difference sets and finite geometry.

Published
2024

5. Learning Run-time Safety Monitors for Machine Learning Components

Author

Vardal, Ozan, Hawkins, Richard, Paterson, Colin, Picardi, Chiara, Omeiza, Daniel, Kunze, Lars, and Habli, Ibrahim

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

For machine learning components used as part of autonomous systems (AS) in carrying out critical tasks it is crucial that assurance of the models can be maintained in the face of post-deployment changes (such as changes in the operating environment of the system). A critical part of this is to be able to monitor when the performance of the model at runtime (as a result of changes) poses a safety risk to the system. This is a particularly difficult challenge when ground truth is unavailable at runtime. In this paper we introduce a process for creating safety monitors for ML components through the use of degraded datasets and machine learning. The safety monitor that is created is deployed to the AS in parallel to the ML component to provide a prediction of the safety risk associated with the model output. We demonstrate the viability of our approach through some initial experiments using publicly available speed sign datasets.

Published
2024

6. Strong External Difference Families and Classification of $\alpha$-valuations

Author

Kreher, Donald L., Paterson, Maura B., and Stinson, Douglas R.

Subjects
Mathematics - Combinatorics, 05B10, 05C78
Abstract

One method of constructing $(a^2+1, 2,a, 1)$-SEDFs (i.e., strong external difference families) in $\mathbb{Z}_{a^2+1}$ makes use of $\alpha$-valuations of complete bipartite graphs $K_{a,a}$. We explore this approach and we provide a classification theorem which shows that all such $\alpha$-valuations can be constructed recursively via a sequence of ``blow-up'' operations. We also enumerate all $(a^2+1, 2,a, 1)$-SEDFs in $\mathbb{Z}_{a^2+1}$ for $a \leq 14$ and we show that all these SEDFs are equivalent to $\alpha$-valuations via affine transformations. Whether this holds for all $a > 14$ as well is an interesting open problem. We also study SEDFs in dihedral groups, where we show that two known constructions are equivalent.

Published
2024

7. Community-Guided, Autism-Adapted Group Cognitive Behavioral Therapy for Depression in Autistic Youth (CBT-DAY): Preliminary Feasibility, Acceptability, and Efficacy

Author

Jessica M. Schwartzman, Marissa C. Roth, Ann V. Paterson, Alexandra X. Jacobs, and Zachary J. Williams

Abstract

This study examined the preliminary feasibility, acceptability, and efficacy of an autism-adapted cognitive behavioral therapy for depression in autistic youth, CBT-DAY. Twenty-four autistic youth (11-17 years old) participated in the pilot non-randomized trial including 5 cisgender females, 14 cisgender males, and 5 non-binary youth. Youth participated in 12 weeks of, CBT-DAY and youth depressive symptoms (i.e., primary clinical outcome) and emotional reactivity and self-esteem (i.e., intervention mechanisms) were assessed through self-report and caregiver report at four timepoints: baseline (week 0), midpoint (week 6), post-treatment (week 12), and follow-up (week 24). Results suggested that CBT-DAY may be feasible (16.67% attrition) in an outpatient setting and acceptable to adolescents and their caregivers. Bayesian linear mixed-effects models showed that CBT-DAY may be efficacious in targeting emotional reactivity [[beta][subscript T1-T3] = -2.53, CrI[subscript 95%] (-4.62, -0.58), P[subscript d] = 0.995, d = -0.35] and self-esteem [[beta][subscript T1-T3] = -3.57, CrI[subscript 95%] (-5.17, -2.00), P[subscript d] > 0.999, d = -0.47], as well as youth depressive symptom severity [[beta] = -2.72, CrI[subscript 95%] (-3.85, -1.63), P[subscript d] > 0.999]. Treatment gains were maintained at follow-up. A cognitive behavioral group therapy designed for and with autistic people demonstrates promise in targeting emotional reactivity and self-esteem to improve depressive symptom severity in youth. Findings can be leveraged to implement larger, more controlled trials of CBT-DAY. The trial was registered at Clinicaltrials.gov (Identifier: NCT05430022; https://beta.clinicaltrials.gov/study/NCT05430022).

Published
2024
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8. Euclid. III. The NISP Instrument

Author

Euclid Collaboration, Jahnke, K., Gillard, W., Schirmer, M., Ealet, A., Maciaszek, T., Prieto, E., Barbier, R., Bonoli, C., Corcione, L., Dusini, S., Grupp, F., Hormuth, F., Ligori, S., Martin, L., Morgante, G., Padilla, C., Toledo-Moreo, R., Trifoglio, M., Valenziano, L., Bender, R., Castander, F. J., Garilli, B., Lilje, P. B., Rix, H. -W., Auricchio, N., Balestra, A., Barriere, J. -C., Battaglia, P., Berthe, M., Bodendorf, C., Boenke, T., Bon, W., Bonnefoi, A., Caillat, A., Capobianco, V., Carle, M., Casas, R., Cho, H., Costille, A., Ducret, F., Ferriol, S., Franceschi, E., Gimenez, J. -L., Holmes, W., Hornstrup, A., Jhabvala, M., Kohley, R., Kubik, B., Laureijs, R., Mignant, D. Le, Lloro, I., Medinaceli, E., Mellier, Y., Polenta, G., Racca, G. D., Renzi, A., Salvignol, J. -C., Secroun, A., Seidel, G., Seiffert, M., Sirignano, C., Sirri, G., Strada, P., Smadja, G., Stanco, L., Wachter, S., Anselmi, S., Borsato, E., Caillat, L., Cogato, F., Colodro-Conde, C., Crouzet, P. -E., Conforti, V., D'Alessandro, M., Copin, Y., Cuillandre, J. -C., Davies, J. E., Davini, S., Derosa, A., Diaz, J. J., Di Domizio, S., Di Ferdinando, D., Farinelli, R., Ferrari, A. G., Fornari, F., Gabarra, L., Gutierrez, C. M., Giacomini, F., Lagier, P., Gianotti, F., Krause, O., Madrid, F., Laudisio, F., Macias-Perez, J., Naletto, G., Niclas, M., Marpaud, J., Mauri, N., da Silva, R., Passalacqua, F., Paterson, K., Patrizii, L., Risso, I., Solheim, B. G. B., Scodeggio, M., Stassi, P., Steinwagner, J., Tenti, M., Testera, G., Travaglini, R., Tosi, S., Troja, A., Tubio, O., Valieri, C., Vescovi, C., Ventura, S., Aghanim, N., Altieri, B., Amara, A., Amiaux, J., Andreon, S., Aussel, H., Baldi, M., Bardelli, S., Basset, A., Bonchi, A., Bonino, D., Branchini, E., Brescia, M., Brinchmann, J., Camera, S., Carbone, C., Cardone, V. F., Carretero, J., Casas, S., Castellano, M., Cavuoti, S., Chabaud, P. -Y., Cimatti, A., Congedo, G., Conselice, C. J., Conversi, L., Courbin, F., Courtois, H. M., Cropper, M., Cuby, J. -G., Da Silva, A., Degaudenzi, H., Di Giorgio, A. M., Dinis, J., Douspis, M., Dubath, F., Duncan, C. A. J., Dupac, X., Fabricius, M., Farina, M., Farrens, S., Faustini, F., Fosalba, P., Fotopoulou, S., Fourmanoit, N., Frailis, M., Franzetti, P., Galeotta, S., Gillis, B., Giocoli, C., Gómez-Alvarez, P., Granett, B. R., Grazian, A., Guzzo, L., Hailey, M., Haugan, S. V. H., Hoar, J., Hoekstra, H., Hook, I., Hudelot, P., Joachimi, B., Keihänen, E., Kermiche, S., Kiessling, A., Kilbinger, M., Kitching, T., Kümmel, M., Kunz, M., Kurki-Suonio, H., Lahav, O., Lindholm, V., Alvarez, J. Lorenzo, Maino, D., Maiorano, E., Mansutti, O., Marggraf, O., Markovic, K., Martignac, J., Martinet, N., Marulli, F., Massey, R., Masters, D. C., Maurogordato, S., McCracken, H. J., Mei, S., Melchior, M., Meneghetti, M., Merlin, E., Meylan, G., Mohr, J. J., Moresco, M., Moscardini, L., Nakajima, R., Nichol, R. C., Niemi, S. -M., Nutma, T., Paech, K., Paltani, S., Pasian, F., Peacock, J. A., Pedersen, K., Percival, W. J., Pettorino, V., Pires, S., Poncet, M., Popa, L. A., Pozzetti, L., Raison, F., Rebolo, R., Refregier, A., Rhodes, J., Riccio, G., Romelli, E., Roncarelli, M., Rosset, C., Rossetti, E., Rottgering, H. J. A., Saglia, R., Sapone, D., Sauvage, M., Scaramella, R., Schneider, P., Schrabback, T., Serrano, S., Tallada-Crespí, P., Tavagnacco, D., Taylor, A. N., Teplitz, H. I., Tereno, I., Torradeflot, F., Tutusaus, I., Vassallo, T., Kleijn, G. Verdoes, Veropalumbo, A., Vibert, D., Wang, Y., Weller, J., Zacchei, A., Zamorani, G., Zerbi, F. M., Zoubian, J., Zucca, E., Appleton, P. N., Baccigalupi, C., Biviano, A., Bolzonella, M., Boucaud, A., Bozzo, E., Burigana, C., Calabrese, M., Casenove, P., Crocce, M., De Lucia, G., Vigo, J. A. Escartin, Fabbian, G., Finelli, F., George, K., Gracia-Carpio, J., Ilić, S., Liebing, P., Liu, C., Mainetti, G., Marcin, S., Martinelli, M., Morris, P. W., Neissner, C., Pezzotta, A., Pöntinen, M., Porciani, C., Sakr, Z., Scottez, V., Sefusatti, E., Viel, M., Wiesmann, M., Akrami, Y., Allevato, V., Aubourg, E., Ballardini, M., Bertacca, D., Bethermin, M., Blanchard, A., Blot, L., Borgani, S., Borlaff, A. S., Bruton, S., Cabanac, R., Calabro, A., Calderone, G., Canas-Herrera, G., Cappi, A., Carvalho, C. S., Castignani, G., Castro, T., Chambers, K. C., Charles, Y., Chary, R., Colbert, J., Contarini, S., Contini, T., Cooray, A. R., Costanzi, M., Cucciati, O., De Caro, B., de la Torre, S., Desprez, G., Díaz-Sánchez, A., Dole, H., Escoffier, S., Ferreira, P. G., Ferrero, I., Finoguenov, A., Fontana, A., Ganga, K., García-Bellido, J., Gautard, V., Gaztanaga, E., Gozaliasl, G., Gregorio, A., Hall, A., Hartley, W. G., Hemmati, S., Hildebrandt, H., Hjorth, J., Hosseini, S., Huertas-Company, M., Ilbert, O., Jacobson, J., Joudaki, S., Kajava, J. J. E., Kansal, V., Karagiannis, D., Kirkpatrick, C. C., Lacasa, F., Brun, V. Le, Graet, J. Le, Legrand, L., Libet, G., Liu, S. J., Loureiro, A., Magliocchetti, M., Mancini, C., Mannucci, F., Maoli, R., Martins, C. J. A. P., Matthew, S., Maurin, L., McPartland, C. J. R., Metcalf, R. B., Migliaccio, M., Miluzio, M., Monaco, P., Moretti, C., Nadathur, S., Nicastro, L., Walton, Nicholas A., Odier, J., Oguri, M., Popa, V., Potter, D., Pourtsidou, A., Rocci, P. -F., Rollins, R. P., Rusholme, B., Sahlén, M., Sánchez, A. G., Scarlata, C., Schaye, J., Schewtschenko, J. A., Schneider, A., Schultheis, M., Sereno, M., Shankar, F., Shulevski, A., Sikkema, G., Silvestri, A., Simon, P., Mancini, A. Spurio, Stadel, J., Stanford, S. A., Tanidis, K., Tao, C., Tessore, N., Teyssier, R., Toft, S., Tucci, M., Valiviita, J., Vergani, D., Vernizzi, F., Verza, G., Vielzeuf, P., Weaver, J. R., Zalesky, L., Zinchenko, I. A., Archidiacono, M., Atrio-Barandela, F., Bennett, C. L., Bouvard, T., Caro, F., Conseil, S., Dimauro, P., Duc, P. -A., Fang, Y., Ferguson, A. M. N., Gasparetto, T., Kova{č}ić, I., Kruk, S., Brun, A. M. C. Le, Liaudat, T. I., Montoro, A., Mora, A., Murray, C., Pagano, L., Paoletti, D., Radovich, M., Sarpa, E., Tommasi, E., Viitanen, A., Lesgourgues, J., Levi, M. E., and Martín-Fleitas, J.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract

The Near-Infrared Spectrometer and Photometer (NISP) on board the Euclid satellite provides multiband photometry and R>=450 slitless grism spectroscopy in the 950-2020nm wavelength range. In this reference article we illuminate the background of NISP's functional and calibration requirements, describe the instrument's integral components, and provide all its key properties. We also sketch the processes needed to understand how NISP operates and is calibrated, and its technical potentials and limitations. Links to articles providing more details and technical background are included. NISP's 16 HAWAII-2RG (H2RG) detectors with a plate scale of 0.3" pix^-1 deliver a field-of-view of 0.57deg^2. In photo mode, NISP reaches a limiting magnitude of ~24.5AB mag in three photometric exposures of about 100s exposure time, for point sources and with a signal-to-noise ratio (SNR) of 5. For spectroscopy, NISP's point-source sensitivity is a SNR = 3.5 detection of an emission line with flux ~2x10^-16erg/s/cm^2 integrated over two resolution elements of 13.4A, in 3x560s grism exposures at 1.6 mu (redshifted Ha). Our calibration includes on-ground and in-flight characterisation and monitoring of detector baseline, dark current, non-linearity, and sensitivity, to guarantee a relative photometric accuracy of better than 1.5%, and relative spectrophotometry to better than 0.7%. The wavelength calibration must be better than 5A. NISP is the state-of-the-art instrument in the NIR for all science beyond small areas available from HST and JWST - and an enormous advance due to its combination of field size and high throughput of telescope and instrument. During Euclid's 6-year survey covering 14000 deg^2 of extragalactic sky, NISP will be the backbone for determining distances of more than a billion galaxies. Its NIR data will become a rich reference imaging and spectroscopy data set for the coming decades., Comment: Paper submitted as part of the A&A special issue 'Euclid on Sky', which contains Euclid key reference papers and first results from the Euclid Early Release Observations

Published
2024

9. Euclid. I. Overview of the Euclid mission

Author

Euclid Collaboration, Mellier, Y., Abdurro'uf, Barroso, J. A. Acevedo, Achúcarro, A., Adamek, J., Adam, R., Addison, G. E., Aghanim, N., Aguena, M., Ajani, V., Akrami, Y., Al-Bahlawan, A., Alavi, A., Albuquerque, I. S., Alestas, G., Alguero, G., Allaoui, A., Allen, S. W., Allevato, V., Alonso-Tetilla, A. V., Altieri, B., Alvarez-Candal, A., Alvi, S., Amara, A., Amendola, L., Amiaux, J., Andika, I. T., Andreon, S., Andrews, A., Angora, G., Angulo, R. E., Annibali, F., Anselmi, A., Anselmi, S., Arcari, S., Archidiacono, M., Aricò, G., Arnaud, M., Arnouts, S., Asgari, M., Asorey, J., Atayde, L., Atek, H., Atrio-Barandela, F., Aubert, M., Aubourg, E., Auphan, T., Auricchio, N., Aussel, B., Aussel, H., Avelino, P. P., Avgoustidis, A., Avila, S., Awan, S., Azzollini, R., Baccigalupi, C., Bachelet, E., Bacon, D., Baes, M., Bagley, M. B., Bahr-Kalus, B., Balaguera-Antolinez, A., Balbinot, E., Balcells, M., Baldi, M., Baldry, I., Balestra, A., Ballardini, M., Ballester, O., Balogh, M., Bañados, E., Barbier, R., Bardelli, S., Baron, M., Barreiro, T., Barrena, R., Barriere, J. -C., Barros, B. J., Barthelemy, A., Bartolo, N., Basset, A., Battaglia, P., Battisti, A. J., Baugh, C. M., Baumont, L., Bazzanini, L., Beaulieu, J. -P., Beckmann, V., Belikov, A. N., Bel, J., Bellagamba, F., Bella, M., Bellini, E., Benabed, K., Bender, R., Benevento, G., Bennett, C. L., Benson, K., Bergamini, P., Bermejo-Climent, J. R., Bernardeau, F., Bertacca, D., Berthe, M., Berthier, J., Bethermin, M., Beutler, F., Bevillon, C., Bhargava, S., Bhatawdekar, R., Bianchi, D., Bisigello, L., Biviano, A., Blake, R. P., Blanchard, A., Blazek, J., Blot, L., Bosco, A., Bodendorf, C., Boenke, T., Böhringer, H., Boldrini, P., Bolzonella, M., Bonchi, A., Bonici, M., Bonino, D., Bonino, L., Bonvin, C., Bon, W., Booth, J. T., Borgani, S., Borlaff, A. S., Borsato, E., Bose, B., Botticella, M. T., Boucaud, A., Bouche, F., Boucher, J. S., Boutigny, D., Bouvard, T., Bouwens, R., Bouy, H., Bowler, R. A. A., Bozza, V., Bozzo, E., Branchini, E., Brando, G., Brau-Nogue, S., Brekke, P., Bremer, M. N., Brescia, M., Breton, M. -A., Brinchmann, J., Brinckmann, T., Brockley-Blatt, C., Brodwin, M., Brouard, L., Brown, M. L., Bruton, S., Bucko, J., Buddelmeijer, H., Buenadicha, G., Buitrago, F., Burger, P., Burigana, C., Busillo, V., Busonero, D., Cabanac, R., Cabayol-Garcia, L., Cagliari, M. S., Caillat, A., Caillat, L., Calabrese, M., Calabro, A., Calderone, G., Calura, F., Quevedo, B. Camacho, Camera, S., Campos, L., Canas-Herrera, G., Candini, G. P., Cantiello, M., Capobianco, V., Cappellaro, E., Cappelluti, N., Cappi, A., Caputi, K. I., Cara, C., Carbone, C., Cardone, V. F., Carella, E., Carlberg, R. G., Carle, M., Carminati, L., Caro, F., Carrasco, J. M., Carretero, J., Carrilho, P., Duque, J. Carron, Carry, B., Carvalho, A., Carvalho, C. 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Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

The current standard model of cosmology successfully describes a variety of measurements, but the nature of its main ingredients, dark matter and dark energy, remains unknown. Euclid is a medium-class mission in the Cosmic Vision 2015-2025 programme of the European Space Agency (ESA) that will provide high-resolution optical imaging, as well as near-infrared imaging and spectroscopy, over about 14,000 deg^2 of extragalactic sky. In addition to accurate weak lensing and clustering measurements that probe structure formation over half of the age of the Universe, its primary probes for cosmology, these exquisite data will enable a wide range of science. This paper provides a high-level overview of the mission, summarising the survey characteristics, the various data-processing steps, and data products. We also highlight the main science objectives and expected performance., Comment: Accepted for publication in the A&A special issue`Euclid on Sky'

Published
2024

10. Comprehensive view on a $z\sim6.5$ radio-loud QSO: from the radio to the optical/NIR to the X-ray band

Author

Ighina, Luca, Caccianiga, Alessandro, Moretti, Alberto, Broderick, Jess W., Leung, James K., Paterson, Sean, Rigamonti, Fabio, Seymour, Nick, Belladitta, Silvia, Drouart, Guillaume, Galvin, Tim J., and Hurley-Walker, Natasha

Subjects
Astrophysics - Astrophysics of Galaxies, Astrophysics - High Energy Astrophysical Phenomena
Abstract

We present a multi-wavelength analysis, from the radio to the X-ray band, of the redshift $z=6.44$ VIK J2318$-$31 radio-loud (RL) quasi stellar object (QSO), one of the most distant currently known in this class. The work is based on newly obtained (uGMRT, ATCA, Chandra) as well as archival (GNIRS and X-Shooter) dedicated observations that have not been published yet. Based on the observed X-ray and radio emission, its relativistic jets are likely young and misaligned from our line of sight. Moreover, we can confirm, with simultaneous observations, the presence of a turnover in the radio spectrum at $\nu_{\rm peak} \sim 650$ MHz which is unlikely to be associated with self-synchrotron absorption. From the NIR spectrum we derived the mass of the central black hole, M$_{\rm BH}=8.1^{+6.8}_{-5.6} \times 10^8 {\rm M_{\odot}}$, and the Eddington ratio, $\lambda_{\rm EDD} = 0.8^{+0.8}_{-0.6}$, using broad emission lines as well as an accretion disc model fit to the continuum emission. Given the high accretion rate, the presence of a $\sim$8$\times$10$^8$ M$_\odot$ black hole at $z=6.44$ can be explained by a seed black hole ($\sim$10$^{4}$ M$_\odot$) that formed at $z\sim25$, assuming a radiative efficiency $\eta_{\rm d}\sim0.1$. However, by assuming $\eta_{\rm d}\sim0.3$, as expected for jetted systems, the mass observed would challenge current theoretical models of black hole formation., Comment: Accepted for publication on A&A the 22nd April 2024

Published
2024
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11. Thermal conductivity reduction due to phonon geometrical scattering in nano-engineered epitaxial germanium

Author

Paterson, Jessy, Mitra, Sunanda, Liu, Yanqing, Boukhari, Mustapha, Singhal, Dhruv, Lacroix, David, Hadji, Emmanuel, Barski, André, Tainoff, Dimitri, and Bourgeois, Olivier

Subjects
Condensed Matter - Mesoscale and Nanoscale Physics
Abstract

Nano-engineering crystalline materials can be used to tailor their thermal properties. By adding new nanoscale phonon scattering centers and controlling their size, one can effectively decrease the phonon mean free path and hence the thermal conductivity of a fully crystalline material. In this letter, we use the 3$\omega$ method in the temperature range of 100-300 K to experimentally report on the more than threefold reduction of the thermal conductivity of an epitaxially-grown crystalline germanium thin film with embedded polydispersed crystalline \ch{Ge3Mn5} nano-inclusions with diameters ranging from 5 to 25~nm. A detailed analysis of the structure of the thin film coupled with Monte Carlo simulations of phonon transport highlight the role of the nano-inclusions volume fraction in the reduction of the phononic contribution to the thermal conductivity, in particular its temperature dependence, leading to a phonon mean free path that is set by geometrical constraints., Comment: Applied Physics Letters, In press

Published
2024

12. RecurrentGemma: Moving Past Transformers for Efficient Open Language Models

Author

Botev, Aleksandar, De, Soham, Smith, Samuel L, Fernando, Anushan, Muraru, George-Cristian, Haroun, Ruba, Berrada, Leonard, Pascanu, Razvan, Sessa, Pier Giuseppe, Dadashi, Robert, Hussenot, Léonard, Ferret, Johan, Girgin, Sertan, Bachem, Olivier, Andreev, Alek, Kenealy, Kathleen, Mesnard, Thomas, Hardin, Cassidy, Bhupatiraju, Surya, Pathak, Shreya, Sifre, Laurent, Rivière, Morgane, Kale, Mihir Sanjay, Love, Juliette, Tafti, Pouya, Joulin, Armand, Fiedel, Noah, Senter, Evan, Chen, Yutian, Srinivasan, Srivatsan, Desjardins, Guillaume, Budden, David, Doucet, Arnaud, Vikram, Sharad, Paszke, Adam, Gale, Trevor, Borgeaud, Sebastian, Chen, Charlie, Brock, Andy, Paterson, Antonia, Brennan, Jenny, Risdal, Meg, Gundluru, Raj, Devanathan, Nesh, Mooney, Paul, Chauhan, Nilay, Culliton, Phil, Martins, Luiz Gustavo, Bandy, Elisa, Huntsperger, David, Cameron, Glenn, Zucker, Arthur, Warkentin, Tris, Peran, Ludovic, Giang, Minh, Ghahramani, Zoubin, Farabet, Clément, Kavukcuoglu, Koray, Hassabis, Demis, Hadsell, Raia, Teh, Yee Whye, and de Frietas, Nando

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

We introduce RecurrentGemma, a family of open language models which uses Google's novel Griffin architecture. Griffin combines linear recurrences with local attention to achieve excellent performance on language. It has a fixed-sized state, which reduces memory use and enables efficient inference on long sequences. We provide two sizes of models, containing 2B and 9B parameters, and provide pre-trained and instruction tuned variants for both. Our models achieve comparable performance to similarly-sized Gemma baselines despite being trained on fewer tokens.

Published
2024

13. Gemma: Open Models Based on Gemini Research and Technology

Author

Gemma Team, Mesnard, Thomas, Hardin, Cassidy, Dadashi, Robert, Bhupatiraju, Surya, Pathak, Shreya, Sifre, Laurent, Rivière, Morgane, Kale, Mihir Sanjay, Love, Juliette, Tafti, Pouya, Hussenot, Léonard, Sessa, Pier Giuseppe, Chowdhery, Aakanksha, Roberts, Adam, Barua, Aditya, Botev, Alex, Castro-Ros, Alex, Slone, Ambrose, Héliou, Amélie, Tacchetti, Andrea, Bulanova, Anna, Paterson, Antonia, Tsai, Beth, Shahriari, Bobak, Lan, Charline Le, Choquette-Choo, Christopher A., Crepy, Clément, Cer, Daniel, Ippolito, Daphne, Reid, David, Buchatskaya, Elena, Ni, Eric, Noland, Eric, Yan, Geng, Tucker, George, Muraru, George-Christian, Rozhdestvenskiy, Grigory, Michalewski, Henryk, Tenney, Ian, Grishchenko, Ivan, Austin, Jacob, Keeling, James, Labanowski, Jane, Lespiau, Jean-Baptiste, Stanway, Jeff, Brennan, Jenny, Chen, Jeremy, Ferret, Johan, Chiu, Justin, Mao-Jones, Justin, Lee, Katherine, Yu, Kathy, Millican, Katie, Sjoesund, Lars Lowe, Lee, Lisa, Dixon, Lucas, Reid, Machel, Mikuła, Maciej, Wirth, Mateo, Sharman, Michael, Chinaev, Nikolai, Thain, Nithum, Bachem, Olivier, Chang, Oscar, Wahltinez, Oscar, Bailey, Paige, Michel, Paul, Yotov, Petko, Chaabouni, Rahma, Comanescu, Ramona, Jana, Reena, Anil, Rohan, McIlroy, Ross, Liu, Ruibo, Mullins, Ryan, Smith, Samuel L, Borgeaud, Sebastian, Girgin, Sertan, Douglas, Sholto, Pandya, Shree, Shakeri, Siamak, De, Soham, Klimenko, Ted, Hennigan, Tom, Feinberg, Vlad, Stokowiec, Wojciech, Chen, Yu-hui, Ahmed, Zafarali, Gong, Zhitao, Warkentin, Tris, Peran, Ludovic, Giang, Minh, Farabet, Clément, Vinyals, Oriol, Dean, Jeff, Kavukcuoglu, Koray, Hassabis, Demis, Ghahramani, Zoubin, Eck, Douglas, Barral, Joelle, Pereira, Fernando, Collins, Eli, Joulin, Armand, Fiedel, Noah, Senter, Evan, Andreev, Alek, and Kenealy, Kathleen

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

This work introduces Gemma, a family of lightweight, state-of-the art open models built from the research and technology used to create Gemini models. Gemma models demonstrate strong performance across academic benchmarks for language understanding, reasoning, and safety. We release two sizes of models (2 billion and 7 billion parameters), and provide both pretrained and fine-tuned checkpoints. Gemma outperforms similarly sized open models on 11 out of 18 text-based tasks, and we present comprehensive evaluations of safety and responsibility aspects of the models, alongside a detailed description of model development. We believe the responsible release of LLMs is critical for improving the safety of frontier models, and for enabling the next wave of LLM innovations.

Published
2024

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

Author

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

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

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

Published
2024

15. Experimental set-up for thermal measurements at the nanoscale using an SThM probe with niobium nitride thermometer

Author

Swami, R., Julie, G., Le-Denmat, S., Pernot, G., Singhal, D., Paterson, J., Maire, J., Motte, J. F., Paillet, N., Guillou, H., Gomes, S., and Bourgeois, O.

Subjects
Condensed Matter - Mesoscale and Nanoscale Physics, Physics - Applied Physics
Abstract

Scanning Thermal Microscopy (SThM) has become an important measurement tool for characterizing the thermal properties of materials at the nanometer scale. This technique requires a SThM probe that combines an Atomic Force Microscopy (AFM) probe and a very sensitive resistive thermometry; the thermometer being located at the apex of the probe tip allows the mapping of temperature or thermal properties of nanostructured materials with very high spatial resolution. The high interest of the SThM technique in the field of thermal nanoscience currently suffers from a low temperature sensitivity despite its high spatial resolution. To address this challenge, we developed a high vacuum-based AFM system hosting a highly sensitive niobium nitride (NbN) SThM probe to demonstrate its unique performance. As a proof of concept, we utilized this custom-built system to carry out thermal measurements using the 3$\omega$ method. By measuring the $V_{3\omega}$ voltage on the NbN resistive thermometer in vacuum conditions we were able to determine the SThM probe's thermal conductance and thermal time constant. The performance of the probe is demonstrated by doing thermal measurements in-contact with a sapphire sample., Comment: 17 pages, 13 figures

Published
2024

17. Effects of atmospheric pressure change during flight on insulin pump delivery and glycaemic control of pilots with insulin-treated diabetes: an in vitro simulation and a retrospective observational real-world study

Author

Garden, Gillian L., Fan, Ka Siu, Paterson, Megan, Shojaee-Moradie, Fariba, Borg Inguanez, Monique, Manoli, Antonios, Edwards, Victoria, Lee, Vivienne, Frier, Brian M., Hutchison, Ewan J., Maher, Declan, Mathieu, Chantal, Mitchell, Stuart J., Heller, Simon R., Roberts, Graham A., Shaw, Kenneth M., Koehler, Gerd, Mader, Julia K., King, Bruce R., and Russell-Jones, David L.

Published
2024
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18. Combination Versus Monotherapy for Carbapenem-Resistant Acinetobacter Species Serious Infections: A Prospective IPTW Adjusted Cohort Study

Author

Manesh, Abi, George, Mithun Mohan, Palanikumar, Prasannakumar, Nagaraj, V., Bhanuprasad, Kundakarla, Krishnan, Ramya, Nivetha, G., Lal, Binesh, Triveni, K. Rajitha, Gautam, Priyanka, George, Biju, Kulkarni, Uday, Mathews, Vikram, Subramani, K., Rao, Shoma, Chacko, Binila, Zachariah, Anand, Sathyendra, Sowmya, Hansdak, Samuel George, Abraham, Ooriapadickal Cherian, Iyadurai, Ramya, Karthik, Rajiv, Peter, John Victor, Mo, Yin, Veeraraghavan, Balaji, Varghese, George M., and Paterson, David Leslie

Published
2024
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25. Using a multistate Mapping Approach to Surface Hopping to predict the Ultrafast Electron Diffraction signal of gas-phase cyclobutanone

Author

Hutton, Lewis, Carrascosa, Andres Moreno, Prentice, Andrew W., Simmermacher, Mats, Runeson, Johan E., Paterson, Martin J., and Kirrander, Adam

Subjects
Physics - Chemical Physics
Abstract

Using the recently developed multistate mapping approach to surface hopping (multistate MASH) method combined with SA(3)-CASSCF(12,12)/aug-cc-pVDZ electronic structure calculations, the gas-phase isotropic ultrafast electron diffraction (UED) of cyclobutanone is predicted and analyzed. After excitation into the n-3s Rydberg state (S$_2$), cyclobutanone can relax through two S$_2$/S$_1$ conical intersections, one characterized by compression of the \ce{CO} bond, the other by dissociation of the $\mathrm{\alpha}$-CC bond. Subsequent transfer into the ground state (S$_0$) is then achieved via two additional S$_1$/S$_0$ conical intersections that lead to three reaction pathways: $\mathrm{\alpha}$ ring-opening, ethene/ketene production, and \ce{CO} liberation. The isotropic gas-phase UED signal is predicted from the multistate MASH simulations, allowing for a direct comparison to experimental data. This work, which is a contribution to the cyclobutanone prediction challenge, facilitates the identification of the main photoproducts in the UED signal and thereby emphasizes the importance of dynamics simulations for the interpretation of ultrafast experiments., Comment: Cyclobutanone prediction challenge in Journal of Chemical Physics

Published
2024
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26. Multi-scale, open-system magmatic and sub-solidus processes contribute to the chemical and isotopic characteristics of the Jurassic Guadalupe Igneous Complex, Sierra Nevada, California, USA

Author

Ratschbacher, Barbara C, Ardill, Katie, Keller, C Brenhin, Schoene, Blair, Paterson, Scott R, Putirka, Keith D, Lackey, Jade Star, and Paige, Matthew L

Subjects
Earth Sciences, Geochemistry, Geology, Geophysics, Geochemistry & Geophysics
Abstract

The chemical and isotopic characteristics of a solidified pluton represent the integration of magmatic and sub-solidus processes operating across a range of spatial and temporal scales during pluton construction, crystallization, and cooling. Disentangling these processes and understanding where chemical and isotopic signatures were acquired requires the combination of multiple tools tracing processes at different time and length scales. We combine whole-rock oxygen and Sr-Nd isotopes, zircon oxygen isotopes and trace elements, and mineral compositions with published high-precision U-Pb zircon geochronology to evaluate differentiation within the bimodal Guadalupe Igneous Complex, Sierra Nevada, California (USA). The complex was constructed in ~300 k.y. between 149 and 150 Ma. Felsic magmas crystallized as centimeter- to meter-sized segregations in gabbros in the lower part of the complex and as granites and granophyres structurally above the gabbros. A central mingling zone separates the mafic and felsic units. Pluton-wide δ18O(whole-rock), δ18O(zircon), and Sr-Nd isotopic ranges are too large to be explained by in situ, closed-system differentiation, instead requiring open-system behavior at all scales. Low δ18O(whole-rock) and δ18O(zircon) values indicate assimilation of hydrothermally altered marine host rocks during ascent and/or emplacement. In situ differentiation processes operated on a smaller scale (meters to tens of meters) for at least ~200 k.y. via (1) percolation and segregation of chemically and isotopically diverse silicic interstitial melt from a heterogeneous gabbro mush; (2) crystal accumulation; and (3) sub-solidus, high-temperature, hydrothermal alteration at the shallow roof of the complex to modify the chemical and isotopic characteristics. Whole-rock and mineral chemistry in combination with geochronology allows deciphering open-system differentiation processes at the outcrop to pluton scale from magmatic to sub-solidus temperatures over time scales of hundreds of thousands to millions of years.

Published
2024

27. Amyloid pathology and vascular risk are associated with distinct patterns of cerebral white matter hyperintensities: A multicenter study in 3132 memory clinic patients

Author

Biesbroek, J Matthijs, Coenen, Mirthe, DeCarli, Charles, Fletcher, Evan M, Maillard, Pauline M, Initiative, Alzheimer's Disease Neuroimaging, Barkhof, Frederik, Barnes, Josephine, Benke, Thomas, Chen, Christopher PLH, Dal‐Bianco, Peter, Dewenter, Anna, Duering, Marco, Enzinger, Christian, Ewers, Michael, Exalto, Lieza G, Franzmeier, Nicolai, Hilal, Saima, Hofer, Edith, Koek, Huiberdina L, Maier, Andrea B, McCreary, Cheryl R, Papma, Janne M, Paterson, Ross W, Pijnenburg, Yolande AL, Rubinski, Anna, Schmidt, Reinhold, Schott, Jonathan M, Slattery, Catherine F, Smith, Eric E, Sudre, Carole H, Steketee, Rebecca ME, Teunissen, Charlotte E, van den Berg, Esther, van der Flier, Wiesje M, Venketasubramanian, Narayanaswamy, Venkatraghavan, Vikram, Vernooij, Meike W, Wolters, Frank J, Xin, Xu, Kuijf, Hugo J, and Biessels, Geert Jan

Subjects
Biomedical and Clinical Sciences, Neurosciences, Clinical Sciences, Vascular Cognitive Impairment/Dementia, Brain Disorders, Clinical Research, Acquired Cognitive Impairment, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Alzheimer's Disease Related Dementias (ADRD), Aging, Dementia, Cerebrovascular, Alzheimer's Disease, Neurodegenerative, Neurological, Humans, Female, Middle Aged, Aged, Aged, 80 and over, Male, White Matter, Arteriolosclerosis, Amyloid beta-Peptides, Magnetic Resonance Imaging, amyloid pathology, arteriolosclerosis, dementia, lesion pattern, white matter hyperintensities, Alzheimer's Disease Neuroimaging Initiative, Geriatrics, Clinical sciences, Biological psychology
Abstract

IntroductionWhite matter hyperintensities (WMH) are associated with key dementia etiologies, in particular arteriolosclerosis and amyloid pathology. We aimed to identify WMH locations associated with vascular risk or cerebral amyloid-β1-42 (Aβ42)-positive status.MethodsIndividual patient data (n = 3,132; mean age 71.5 ± 9 years; 49.3% female) from 11 memory clinic cohorts were harmonized. WMH volumes in 28 regions were related to a vascular risk compound score (VRCS) and Aß42 status (based on cerebrospinal fluid or amyloid positron emission tomography), correcting for age, sex, study site, and total WMH volume.ResultsVRCS was associated with WMH in anterior/superior corona radiata (B = 0.034/0.038, p

Published
2024

28. Predictive Analytics in Education: Considerations in Predicting versus Explaining College Student Retention

Author

Paterson, Kevin and Guerrero, Adam

Abstract

Data from a moderately-selective state university in the Midwest is used to cross-examine the most appropriate data analytical techniques for predicting versus explaining college student persistence decisions. The current research provides an overview of the relative benefits of models specializing in prediction versus explanation with particular emphasis on estimation methodologies, model specification by estimation technique, and model diagnostics, including classification tables and measurements of the goodness of fit. The predictive validity of a model of college student retention estimated using logistic regression is compared with that of discriminant analysis estimated using cognitive and non-cognitive predictors of retention. Key contributions to the literature include a unique analysis sample, a unique set of independent variables, and statistical estimation methodologies that build upon traditional frameworks, including machine learning techniques. The currents study ends with a discussion that will allow leaders in higher education and policymakers to make better data-informed decisions surrounding prediction and explanation so that they can proactively intervene with the most appropriate attrition-minimization policies.

Published
2023

40. SAGUARO: Time-domain Infrastructure for the Fourth Gravitational-wave Observing Run and Beyond

Author

Hosseinzadeh, Griffin, Paterson, Kerry, Rastinejad, Jillian C., Shrestha, Manisha, Daly, Philip N., Lundquist, Michael J., Sand, David J., Fong, Wen-fai, Bostroem, K. Azalee, Hall, Saarah, Wyatt, Samuel D., Gibbs, Alex R., Christensen, Eric, Lindstrom, William, Nation, Jonathan, Chatelain, Joseph, and McCully, Curtis

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - High Energy Astrophysical Phenomena
Abstract

We present upgraded infrastructure for Searches after Gravitational Waves Using ARizona Observatories (SAGUARO) during LIGO, Virgo, and KAGRA's fourth gravitational-wave (GW) observing run (O4). These upgrades implement many of the lessons we learned after a comprehensive analysis of potential electromagnetic counterparts to the GWs discovered during the previous observing run. We have developed a new web-based target and observation manager (TOM) that allows us to coordinate sky surveys, vet potential counterparts, and trigger follow-up observations from one centralized portal. The TOM includes software that aggregates all publicly available information on the light curves and possible host galaxies of targets, allowing us to rule out potential contaminants like active galactic nuclei, variable stars, solar-system objects, and preexisting supernovae, as well as to assess the viability of any plausible counterparts. We have also upgraded our image-subtraction pipeline by assembling deeper reference images and training a new neural network-based real-bogus classifier. These infrastructure upgrades will aid coordination by enabling the prompt reporting of observations, discoveries, and analysis to the GW follow-up community, and put SAGUARO in an advantageous position to discover kilonovae in the remainder of O4 and beyond. Many elements of our open-source software stack have broad utility beyond multimessenger astronomy, and will be particularly relevant in the "big data" era of transient discoveries by the Vera C. Rubin Observatory., Comment: updated to match accepted version

Published
2023
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41. Circular external difference families, graceful labellings and cyclotomy

Author

Paterson, Maura B. and Stinson, Douglas R.

Subjects
Mathematics - Combinatorics, Computer Science - Cryptography and Security, 05B10, 94A60, 05C78, 11T22
Abstract

(Strong) circular external difference families (which we denote as CEDFs and SCEDFs) can be used to construct nonmalleable threshold schemes. They are a variation of (strong) external difference families, which have been extensively studied in recent years. We provide a variety of constructions for CEDFs based on graceful labellings ($\alpha$-valuations) of lexicographic products $C_n \boldsymbol{\cdot} K_{\ell}^c$, where $C_n$ denotes a cycle of length $n$. SCEDFs having more than two subsets do not exist. However, we can construct close approximations (more specifically, certain types of circular algebraic manipulation detection (AMD) codes) using the theory of cyclotomic numbers in finite fields.

Published
2023

42. A New Mechanism for Generation of Langmuir Circulations

Author

Basovich, Andre, Wall, Dylan, and Paterson, Eric

Subjects
Physics - Fluid Dynamics, Physics - Atmospheric and Oceanic Physics
Abstract

A new mechanism has been identified that explains the generation of Langmuir circulations. A wind-driven current in the presence of surface waves gives rise to an instability where the emerging circulations redistribute the turbulence in the cross-wind direction. The non-uniform eddy-viscosity locally changes the rate of momentum transfer from the wind to the shear current, producing a non-uniform velocity field. The interaction of this non-uniform velocity field with the surface waves, due to the Craik-Leibovich vortex force, amplifies the circulations and creates a feedback mechanism. The currently accepted CL2 model of instability assumes a constant eddy-viscosity. This paper presents a model which explains the generation of Langmuir circulations and its predictions of both spatial and time scales are in good agreement with experimental results. The modeling approach combines a perturbation method with a RANS turbulence model. Through parametric variation of the perturbation, the growth rate and spatial scales of the circulations are extracted from the simulations.

Published
2023

43. Conductors of twisted Weil--Deligne representations

Author

Bisatt, Matthew and Paterson, Ross

Subjects
Mathematics - Number Theory, 11S40 (11G40 11G10 14G10)
Abstract

We study the behaviour of conductors of L-functions associated to certain Weil--Deligne representations under twisting. For each global field K we prove a sharp upper bound for the conductor of the Rankin--Selberg L-function associated to a pair of abelian varieties., Comment: Major restructuring: strengthened main result on Rankin--Selberg L-functions and removed results on character twists. Comments welcome!

Published
2023

44. Clinical Outcomes and Bacterial Characteristics of Carbapenem-resistant Acinetobacter baumannii Among Patients From Different Global Regions.

Author

Wang, Minggui, Ge, Lizhao, Chen, Liang, Komarow, Lauren, Hanson, Blake, Reyes, Jinnethe, Cober, Eric, Alenazi, Thamer, Zong, Zhiyong, Xie, Qing, Liu, Zhengyin, Li, Lanjuan, Yu, Yunsong, Gao, Hainv, Kanj, Souha, Figueroa, Jairo, Herc, Erica, Cordova, Ezequiel, Weston, Gregory, Ananth Tambyah, Paul, Garcia-Diaz, Julia, Kaye, Keith, Dhar, Sorabh, Munita, Jose, Salata, Robert, Vilchez, Samuel, Stryjewski, Martin, Villegas Botero, Maria, Iovleva, Alina, Evans, Scott, Baum, Keri, Hill, Carol, Kreiswirth, Barry, Patel, Robin, Paterson, David, Arias, Cesar, Bonomo, Robert, Chambers, Henry, Fowler, Vance, Satlin, Michael, van Duin, David, and Doi, Yohei

Subjects
carbapenem-resistant Acinetobacter baumannii, clinical impact, international epidemiology, Humans, Acinetobacter baumannii, Carbapenems, Prospective Studies, Microbial Sensitivity Tests, Acinetobacter Infections, beta-Lactamases, Bacterial Proteins, Anti-Bacterial Agents
Abstract

BACKGROUND: Carbapenem-resistant Acinetobacter baumannii (CRAb) is 1 of the most problematic antimicrobial-resistant bacteria. We sought to elucidate the international epidemiology and clinical impact of CRAb. METHODS: In a prospective observational cohort study, 842 hospitalized patients with a clinical CRAb culture were enrolled at 46 hospitals in five global regions between 2017 and 2019. The primary outcome was all-cause mortality at 30 days from the index culture. The strains underwent whole-genome analysis. RESULTS: Of 842 cases, 536 (64%) represented infection. By 30 days, 128 (24%) of the infected patients died, ranging from 1 (6%) of 18 in Australia-Singapore to 54 (25%) of 216 in the United States and 24 (49%) of 49 in South-Central America, whereas 42 (14%) of non-infected patients died. Bacteremia was associated with a higher risk of death compared with other types of infection (40 [42%] of 96 vs 88 [20%] of 440). In a multivariable logistic regression analysis, bloodstream infection and higher age-adjusted Charlson comorbidity index were independently associated with 30-day mortality. Clonal group 2 (CG2) strains predominated except in South-Central America, ranging from 216 (59%) of 369 in the United States to 282 (97%) of 291 in China. Acquired carbapenemase genes were carried by 769 (91%) of the 842 isolates. CG2 strains were significantly associated with higher levels of meropenem resistance, yet non-CG2 cases were over-represented among the deaths compared with CG2 cases. CONCLUSIONS: CRAb infection types and clinical outcomes differed significantly across regions. Although CG2 strains remained predominant, non-CG2 strains were associated with higher mortality. Clinical Trials Registration. NCT03646227.

Published
2024

45. Re-evaluating our focus in addiction: emotional dysregulation is a critical driver of relapse to drug use

Author

Lexi J. Hand, Louise M. Paterson, and Anne R. Lingford-Hughes

Subjects
Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Abstract Most addiction research has focused on reward- and impulsivity-related neurocircuitry. However, the impact of the withdrawal/negative affect stage in the addiction cycle has been somewhat overlooked, despite it being commonly evident in the clinic. This stage crucially drives negative reinforcement of repeated drug use and relapse, yet less is known about its neural underpinnings. How negative emotional processing is dysregulated in substance dependence is incompletely understood and may manifest differentially across the types of substances. In turn, the regions involved in negative emotional processing may show different patterns of dysregulation. Understanding how neurocircuitry involved in negative states differs across various substances may help inform new targets for treatments. Following a comprehensive literature search of studies examining negative emotional processing in substance dependence, a quantitative approach was deemed inappropriate. Instead, we employed a narrative approach to exploring neural responses to tasks involving emotional processing in alcohol, cocaine, opioid and cannabis dependence. Regions that were found to be dysregulated included the amygdala, insula, anterior cingulate, and medial prefrontal cortex. However, patterns of reactivity differed across alcohol, cocaine, opioid and cannabis dependence. Brain activation in alcohol dependence broadly appeared blunted in response to negative affective stimuli and emotional faces, whilst conversely appeared heightened in cocaine dependence. In opioid dependence, the amygdala was consistently implicated, whilst the insula, anterior cingulate, and medial prefrontal cortex were implicated in cannabis dependence. However, there was wide variability amongst the studies, with very few studies investigating opioid and cannabis dependence. These findings suggest emotional dysregulation varies according to the type of substance dependence. However, the variability in findings and lack of studies highlights the need for more research in this area. Further characterisation of emotional dysregulation in substance dependence will enable identification of treatment targets. More targeted treatments that modulate negative emotional processing could substantially improve outcomes by aiding relapse prevention.

Published
2024
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46. Higher dissociation and lower verbal ability predict news-related information sharing on social media

Author

Misia Temler, Helen M. Paterson, and Carolyn MacCann

Subjects
Social cognition, Cognitive styles, Individual differences, Distributed cognition, Social media, Psychology, BF1-990
Abstract

Abstract High levels of online activity have been linked with lower critical engagement and cognitive ability as well as lapses in attention and memory. This study examines whether individual differences in cognitive styles and abilities relating to the theoretical framework of distributed cognition predict social media behaviour. In this online study, 784 MTurk participants (55% male) completed measures of social media use, online friendships, need for cognition, dissociative tendencies, and vocabulary. They also answered questions about online news-related information sharing (with and without reading the article). Multiple regression and relative weights analysis show that higher dissociative tendencies and lower verbal ability predict social media use, online friendships and information sharing behaviour. Dissociation was the most important predictor, particularly for sharing news-related information without first reading it, with moderate to large effects. Perceptions of information accuracy and source trustworthiness were identified as key factors in driving information sharing behaviour. Our research has important implications for today’s technological society.

Published
2024
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47. Decentralised finance, regulation, and systems theory

Author

John Paterson

Subjects
cryptocurrency, central bank digital currencies, internal differentiation, dedifferentiation, criptomoneda, monedas digitales de bancos centrales, diferenciación interna, desdiferenciación, Social legislation, K7585-7595
Abstract

Cryptocurrency has sparked expressions of concern from regulators – though sometimes coupled with expressions of interest in state-backed alternatives. This paradoxical situation neatly encapsulates the conundrum confronting regulators as they seek to come to terms with the new world opened up by blockchain and leading ultimately perhaps to decentralised finance. How do we best understand this confusing situation? This paper looks for answers by attempting to conceptualise the phenomenon of decentralised finance in autopoietic systems terms. Insofar as a plausible argument can be made for the proposition that finance represents an example of the internal differentiation of the economy, does decentralised finance in some sense constitute an intensified internal differentiation? Alternatively, and paradoxically, insofar as what we are concerned with is decentralised finance, does it instead in some sense represent an example of dedifferentiation? Answers to these questions will have relevance for efforts to regulate this emerging phenomenon. They will also help to shed light on whether state and central bank experiments in this space will produce positive effects or bring their own challenges. La criptomoneda ha suscitado la preocupación de los reguladores, aunque a veces ha ido acompañada del interés expresado sobre algunas alternativas respaldadas por el Estado. Esta paradójica situación resume a la perfección el enigma al que se enfrentan los reguladores cuando tratan de aceptar el nuevo mundo abierto por la cadena de bloques y que, en última instancia, quizá conduzca a unas finanzas descentralizadas. ¿Cuál es la mejor manera de entender esta confusa situación? Este artículo busca respuestas intentando conceptualizar el fenómeno de las finanzas descentralizadas en términos de sistemas autopoiéticos. En la medida en que se puede argumentar de forma plausible que las finanzas representan un ejemplo de la diferenciación interna de la economía, ¿constituyen las finanzas descentralizadas, en cierto sentido, una diferenciación interna intensificada? Por otra parte, y paradójicamente, en la medida en que tratamos sobre finanzas descentralizadas, ¿representan en cierto sentido un ejemplo de desdiferenciación? Las respuestas a estas preguntas serán relevantes para los esfuerzos por regular este fenómeno emergente. También ayudarán a arrojar luz sobre si los experimentos del Estado y los bancos centrales en este espacio producirán efectos positivos o nuevos desafíos.

Published
2024
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48. Combination Versus Monotherapy for Carbapenem-Resistant Acinetobacter Species Serious Infections: A Prospective IPTW Adjusted Cohort Study

Author

Abi Manesh, Mithun Mohan George, Prasannakumar Palanikumar, V. Nagaraj, Kundakarla Bhanuprasad, Ramya Krishnan, G. Nivetha, Binesh Lal, K. Rajitha Triveni, Priyanka Gautam, Biju George, Uday Kulkarni, Vikram Mathews, K. Subramani, Shoma Rao, Binila Chacko, Anand Zachariah, Sowmya Sathyendra, Samuel George Hansdak, Ooriapadickal Cherian Abraham, Ramya Iyadurai, Rajiv Karthik, John Victor Peter, Yin Mo, Balaji Veeraraghavan, George M. Varghese, and David Leslie Paterson

Subjects
Acinetobacter, Combination therapy, CRAB infections, Polymyxins, Infectious and parasitic diseases, RC109-216
Abstract

Abstract Introduction International guidelines recommend definitive combination antibiotic therapy for the management of serious infections involving carbapenem-resistant Acinetobacter (CRAB) species. The commonly available combination options include high-dose sulbactam, polymyxins, tetracyclines, and cefiderocol. Scanty prospective data exist to support this approach. Methods Patients with CRAB bacteraemia, ventilator-associated pneumonia (VAP), or both were categorized based on whether they received combination therapy or monotherapy. The 30-day mortality was compared between the two groups. Inverse probability treatment weighting (IPTW) was done using propensity score (PS) for a balanced comparison between groups. Results Between January 2021 and May 2023, of the 161 patients with CRAB bacteraemia (n = 55, 34.2%), VAP (n = 46, 28.6%), or both (n = 60, 37.3%) who received appropriate intravenous antibiotic therapy, 70% (112/161) received monotherapy, and the rest received combination therapy. The overall 30-day mortality was 62% (99/161) and not different (p = 0.76) between the combination therapy (31/49, 63.3%) and monotherapy (68/112, 60.7%) groups. The propensity score matching using IPTW did not show a statistical difference (p = 0.47) in 30-day mortality for receiving combination therapy with an adjusted odds ratio (OR) P of 1.29 (0.64, 2.58). Conclusion Combination therapy for CRAB infections needs further study in a randomised controlled trial, as this observational study showed no difference in 30-day mortality between monotherapy and combination therapy.

Published
2024
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49. Head and neck cancer incidence is rising but the sociodemographic profile is unchanging: a population epidemiological study (2001–2020)

Author

Craig D. L. Smith, Alex D. McMahon, Mitana Purkayastha, Grant Creaney, Kelten Clements, Gareth J. Inman, Lesley A. Bhatti, Catriona M. Douglas, Claire Paterson, and David I. Conway

Subjects
Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background Increasing incidence of head and neck cancers (HNCs), driven by rising rates of oropharynx cancer (OPC), has been recorded around the world. This study examined trends in HNC and subsites (oral cavity, oropharynx, and larynx cancers) in Scotland focusing on assessing whether the sociodemographic profile has changed over the past 20 years. Methods Scottish Cancer Registry data (2001–2020) including European Age Standardised Rates of HNC and subsites were analysed in multivariate Poisson regression by age, sex, area-based socioeconomic status, and year of diagnosis (with interaction tests). Results Overall HNC and oral cavity cancer (OCC) incidence remained relatively stable. OPC incidence rates increased by 78%, while larynx cancer incidence declined by 27%. Over time, there were marginal shifts to a slightly older age profile for HNC (p = 0.001) and OCC (p = 0.001), but no changes in OPC (p = 0.86) and larynx cancer (p = 0.29). No shift in the sex profile of HNC was observed except for minor increases in female OCC rates (p = 0.001), and the socioeconomic distribution remained unchanged across all HNC subsites. Conclusions There have been no significant changes in the sociodemographic profile of HNC in Scotland over the last 20 years, despite the changing trends in HNCs with dramatically increasing incidence rates in OPC and reducing larynx cancer. This information can be used to target or stratify HNC prevention and control.

Published
2024
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50. GRABSEEDS: extraction of plant organ traits through image analysis

Author

Haibao Tang, Wenqian Kong, Pheonah Nabukalu, Johnathan S. Lomas, Michel Moser, Jisen Zhang, Mengwei Jiang, Xingtan Zhang, Andrew H. Paterson, and Won Cheol Yim

Subjects
Image analysis, Phenotype, Seed traits, High throughput, QTL mapping, Plant culture, SB1-1110, Biology (General), QH301-705.5
Abstract

Abstract Background Phenotyping of plant traits presents a significant bottleneck in Quantitative Trait Loci (QTL) mapping and genome-wide association studies (GWAS). Computerized phenotyping using digital images promises rapid, robust, and reproducible measurements of dimension, shape, and color traits of plant organs, including grain, leaf, and floral traits. Results We introduce GRABSEEDS, which is specifically tailored to extract a comprehensive set of features from plant images based on state-of-the-art computer vision and deep learning methods. This command-line enabled tool, which is adept at managing varying light conditions, background disturbances, and overlapping objects, uses digital images to measure plant organ characteristics accurately and efficiently. GRABSEED has advanced features including label recognition and color correction in a batch setting. Conclusion GRABSEEDS streamlines the plant phenotyping process and is effective in a variety of seed, floral and leaf trait studies for association with agronomic traits and stress conditions. Source code and documentations for GRABSEEDS are available at: https://github.com/tanghaibao/jcvi/wiki/GRABSEEDS .

Published
2024
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