MACK: Mismodeling Addressed with Contrastive Knowledge

Autor: Sheldon, Liam Rankin, Rankin, Dylan Sheldon, Harris, Philip

The use of machine learning methods in high energy physics typically relies on large volumes of precise simulation for training. As machine learning models become more complex they can become increasingly sensitive to differences between this simulat

Externí odkaz: http://arxiv.org/abs/2410.13947

Multiprobe Cosmology from the Abundance of SPT Clusters and DES Galaxy Clustering and Weak Lensing

Autor: Bocquet, S., Grandis, S., Krause, E., To, C., Bleem, L. E., Klein, M., Mohr, J. J., Schrabback, T., Alarcon, A., Alves, O., Amon, A., Andrade-Oliveira, F., Baxter, E. J., Bechtol, K., Becker, M. R., Bernstein, G. M., Blazek, J., Camacho, H., Campos, A., Rosell, A. Carnero, Kind, M. Carrasco, Cawthon, R., Chang, C., Chen, R., Choi, A., Cordero, J., Crocce, M., Davis, C., DeRose, J., Diehl, H. T., Dodelson, S., Doux, C., Drlica-Wagner, A., Eckert, K., Eifler, T. F., Elsner, F., Elvin-Poole, J., Everett, S., Fang, X., Ferté, A., Fosalba, P., Friedrich, O., Frieman, J., Gatti, M., Giannini, G., Gruen, D., Gruendl, R. A., Harrison, I., Hartley, W. G., Herner, K., Huang, H., Huff, E. M., Huterer, D., Jarvis, M., Kuropatkin, N., Leget, P. -F., Lemos, P., Liddle, A. R., MacCrann, N., McCullough, J., Muir, J., Myles, J., Navarro-Alsina, A., Pandey, S., Park, Y., Porredon, A., Prat, J., Raveri, M., Rollins, R. P., Roodman, A., Rosenfeld, R., Rykoff, E. S., Sánchez, C., Sanchez, J., Secco, L. F., Sevilla-Noarbe, I., Sheldon, E., Shin, T., Troxel, M. A., Tutusaus, I., Varga, T. N., Weaverdyck, N., Wechsler, R. H., Wu, H. -Y., Yanny, B., Yin, B., Zhang, Y., Zuntz, J., Abbott, T. M. C., Ade, P. A. R., Aguena, M., Allam, S., Allen, S. W., Anderson, A. J., Ansarinejad, B., Austermann, J. E., Bayliss, M., Beall, J. A., Bender, A. N., Benson, B. A., Bianchini, F., Brodwin, M., Brooks, D., Bryant, L., Burke, D. L., Canning, R. E. A., Carlstrom, J. E., Carretero, J., Castander, F. J., Chang, C. L., Chaubal, P., Chiang, H. C., Chou, T-L., Citron, R., Moran, C. Corbett, Costanzi, M., Crawford, T. M., Crites, A. T., da Costa, L. N., Pereira, M. E. S., Davis, T. M., de Haan, T., Dobbs, M. A., Doel, P., Everett, W., Farahi, A., Flaugher, B., Flores, A. M., Floyd, B., Gallicchio, J., Gaztanaga, E., George, E. M., Gladders, M. D., Gupta, N., Gutierrez, G., Halverson, N. W., Hinton, S. R., Hlavacek-Larrondo, J., Holder, G. P., Hollowood, D. L., Holzapfel, W. L., Hrubes, J. D., Huang, N., Hubmayr, J., Irwin, K. D., James, D. J., Kéruzoré, F., Khullar, G., Kim, K., Knox, L., Kraft, R., Kuehn, K., Lahav, O., Lee, A. T., Lee, S., Li, D., Lidman, C., Lima, M., Lowitz, A., Mahler, G., Mantz, A., Marshall, J. L., McDonald, M., McMahon, J. J., Mena-Fernández, J., Meyer, S. S., Miquel, R., Montgomery, J., Natoli, T., Nibarger, J. P., Noble, G. I., Novosad, V., Ogando, R. L. C., Padin, S., Paschos, P., Patil, S., Malagón, A. A. Plazas, Pryke, C., Reichardt, C. L., Roberson, J., Romer, A. K., Romero, C., Ruhl, J. E., Saliwanchik, B. R., Salvati, L., Samuroff, S., Sanchez, E., Santiago, B., Sarkar, A., Saro, A., Schaffer, K. K., Sharon, K., Sievers, C., Smecher, G., Smith, M., Somboonpanyakul, T., Sommer, M., Stalder, B., Stark, A. A., Stephen, J., Strazzullo, V., Suchyta, E., Swanson, M. E. C., Tarle, G., Thomas, D., Tucker, C., Tucker, D. L., Veach, T., Vieira, J. D., von der Linden, A., Wang, G., Whitehorn, N., Wu, W. L. K., Yefremenko, V., Young, M., Zebrowski, J. A., Zohren, H., Collaboration, DES, Collaboration, SPT

Cosmic shear, galaxy clustering, and the abundance of massive halos each probe the large-scale structure of the universe in complementary ways. We present cosmological constraints from the joint analysis of the three probes, building on the latest an

Externí odkaz: http://arxiv.org/abs/2412.07765

Dark Energy Survey Year 3: Blue Shear

Autor: McCullough, J., Amon, A., Legnani, E., Gruen, D., Roodman, A., Friedrich, O., MacCrann, N., Becker, M. R., Myles, J., Dodelson, S., Samuroff, S., Blazek, J., Prat, J., Honscheid, K., Pieres, A., Ferté, A., Alarcon, A., Drlica-Wagner, A., Choi, A., Navarro-Alsina, A., Campos, A., Malagón, A. A. Plazas, Porredon, A., Farahi, A., Ross, A. J., Rosell, A. Carnero, Yin, B., Flaugher, B., Yanny, B., Sánchez, C., Chang, C., Davis, C., To, C., Doux, C., Brooks, D., James, D. J., Cid, D. Sanchez, Hollowood, D. L., Huterer, D., Rykoff, E. S., Gaztanaga, E., Huff, E. M., Suchyta, E., Sheldon, E., Sanchez, E., Tarsitano, F., Andrade-Oliveira, F., Castander, F. J., Bernstein, G. M., Gutierrez, G., Giannini, G., Tarle, G., Diehl, H. T., Huang, H., Harrison, I., Sevilla-Noarbe, I., Tutusaus, I., Ferrero, I., Elvin-Poole, J., Marshall, J. L., Muir, J., Weller, J., Zuntz, J., Carretero, J., DeRose, J., Frieman, J., Cordero, J., De Vicente, J., García-Bellido, J., Mena-Fernández, J., Eckert, K., Romer, A. K., Bechtol, K., Herner, K., Kuehn, K., Secco, L. F., da Costa, L. N., Paterno, M., Soares-Santos, 21 M., Gatti, M., Raveri, M., Yamamoto, M., Smith, M., Kind, M. Carrasco, Troxel, M. A., Aguena, M., Jarvis, M., Swanson, M. E. C., Weaverdyck, N., Lahav, O., Doel, P., Wiseman, P., Miquel, R., Gruendl, R. A., Cawthon, R., Allam, S., Hinton, S. R., Bridle, S. L., Bocquet, S., Desai, S., Pandey, S., Everett, S., Lee, S., Shin, T., Palmese, A., Conselice, C., Burke, D. L., Buckley-Geer, E., Lima, M., Vincenzi, M., Pereira, M. E. S., Crocce, M., Schubnell, M., Jeffrey, N., Alves, O., Vikram, V., Zhang, Y., Collaboration, DES

Modeling the intrinsic alignment (IA) of galaxies poses a challenge to weak lensing analyses. The Dark Energy Survey is expected to be less impacted by IA when limited to blue, star-forming galaxies. The cosmological parameter constraints from this b

Externí odkaz: http://arxiv.org/abs/2410.22272

Economic Anthropology in the Era of Generative Artificial Intelligence

Autor: Sheldon, Zachary, Kumar, Peeyush

Publikováno v: Annual Joint Meeting of Society of Economic Anthropology and Society for the Anthropology of Work 2024

This paper explores the intersection of economic anthropology and generative artificial intelligence (GenAI). It examines how large language models (LLMs) can simulate human decision-making and the inductive biases present in AI research. The study i

Externí odkaz: http://arxiv.org/abs/2410.15238

Marked Cox Models for IBNR Claims Count: Continuous and Discretized Approaches with Dirichlet-Driven Reporting Delays

Autor: Abdelrahman, Hassan, Badescu, Andrei, Craiu, Radu, Lin, Sheldon

Accurate loss reserving is crucial in Property and Casualty (P&C) insurance for financial stability, regulatory compliance, and effective risk management. We propose a novel micro-level Cox model based on hidden Markov models (HMMs). Initially formul

Externí odkaz: http://arxiv.org/abs/2409.12896