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1. The Implementation of Title I and Title II-A Program Initiatives: Compendium of Survey Results from 2021-22. Supplemental Volume. NCEE 2025-004c

Author: National Center for Education Evaluation and Regional Assistance (NCEE) (ED/IES), Mathematica, Westat, Inc., Christine Ross, Grady Deacon, Brian P. Gill, Sophia Seifert, Olivia Lutwak, Jacob Hartog, Patricia Troppe, Eric Isenberg, Elizabeth S. Park, Valerie Orellana, Louis Rizzo, and Kimberly Standing
Abstract: The Title I and Title II-A programs of the Elementary and Secondary Education Act (ESEA) provide funds meant to help schools and districts better serve low-income students and improve teacher and principal quality. The law's latest update, the Every Student Succeeds Act (ESSA), was passed in 2015 and provides more flexibility to states on some dimensions. This compendium describes the methods, response rates, and weights used for surveys of state, district, and school personnel about implementation of Title I and Title II-A program initiatives during the 2021-22 school year. It also includes detailed tables, based on the surveys, that provide a national picture of policies and practices.
Published: 2024

2. College Ranking Systems: A Methodological Review. Final Report

Author: NORC at the University of Chicago, Soubhik Barari, Eric Newsom, Ji Eun Park, and Susan M. Paddock
Abstract: Prospective students and their families use college rankings to navigate their higher education options. Rising tuition and fees have made the college decision more fraught. Recently, the major college ranking providers have revised their methodologies to reflect costs and other considerations. These revisions raise important questions about the precise qualities the rankings aim to measure. Vanderbilt University asked NORC to produce a report evaluating the methodological validity of five major college ranking systems: U.S. News & World Report (USNWR), Wall Street Journal (WSJ), Forbes' Top College list (Forbes), The Times Higher Education World University Ranking (THE), and the QS World University Ranking (QS). Drawing on well-established social scientific concepts like "construct validity," this report identifies many issues in the conceptualization and construction of college ranking lists and offers methodological improvements that might address these shortcomings. The aim of this report is to inform consumers of these rankings--including college-going students, their parents, and college leaders--of the limitations of existing college ranking systems. Findings from this project will guide the development of improved systems for informing college-goers.
Published: 2024

3. ODPG: Outfitting Diffusion with Pose Guided Condition

Author: Lee, Seohyun, Park, Jintae, and Park, Sanghyeok
Subjects: Computer Science - Computer Vision and Pattern Recognition
Abstract: Virtual Try-On (VTON) technology allows users to visualize how clothes would look on them without physically trying them on, gaining traction with the rise of digitalization and online shopping. Traditional VTON methods, often using Generative Adversarial Networks (GANs) and Diffusion models, face challenges in achieving high realism and handling dynamic poses. This paper introduces Outfitting Diffusion with Pose Guided Condition (ODPG), a novel approach that leverages a latent diffusion model with multiple conditioning inputs during the denoising process. By transforming garment, pose, and appearance images into latent features and integrating these features in a UNet-based denoising model, ODPG achieves non-explicit synthesis of garments on dynamically posed human images. Our experiments on the FashionTryOn and a subset of the DeepFashion dataset demonstrate that ODPG generates realistic VTON images with fine-grained texture details across various poses, utilizing an end-to-end architecture without the need for explicit garment warping processes. Future work will focus on generating VTON outputs in video format and on applying our attention mechanism, as detailed in the Method section, to other domains with limited data., Comment: 11 pages, 5 figures. Preprint submitted to VISAPP 2025: the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
Published: 2025

4. CROPS: Model-Agnostic Training-Free Framework for Safe Image Synthesis with Latent Diffusion Models

Author: Park, Junha, Ryu, Ian, Hwang, Jaehui, Park, Hyungkeun, Kim, Jiyoon, and Lee, Jong-Seok
Subjects: Computer Science - Computer Vision and Pattern Recognition
Abstract: With advances in diffusion models, image generation has shown significant performance improvements. This raises concerns about the potential abuse of image generation, such as the creation of explicit or violent images, commonly referred to as Not Safe For Work (NSFW) content. To address this, the Stable Diffusion model includes several safety checkers to censor initial text prompts and final output images generated from the model. However, recent research has shown that these safety checkers have vulnerabilities against adversarial attacks, allowing them to generate NSFW images. In this paper, we find that these adversarial attacks are not robust to small changes in text prompts or input latents. Based on this, we propose CROPS (Circular or RandOm Prompts for Safety), a model-agnostic framework that easily defends against adversarial attacks generating NSFW images without requiring additional training. Moreover, we develop an approach that utilizes one-step diffusion models for efficient NSFW detection (CROPS-1), further reducing computational resources. We demonstrate the superiority of our method in terms of performance and applicability.
Published: 2025

5. Novel magnetic-field-free switching behavior in vdW-magnet/oxide heterostructure

Author: Keum, Jihoon, Zhang, Kai-Xuan, Cheon, Suik, Kim, Hyuncheol, Cui, Jingyuan, Park, Giung, Chang, Yunyeong, Kim, Miyoung, Lee, Hyun-Woo, and Park, Je-Geun
Subjects: Condensed Matter - Materials Science, Condensed Matter - Other Condensed Matter, Physics - Applied Physics
Abstract: Magnetization switching by charge current without a magnetic field is essential for device applications and information technology. It generally requires a current-induced out-of-plane spin polarization beyond the capability of conventional ferromagnet/heavy-metal systems, where the current-induced spin polarization aligns in-plane orthogonal to the in-plane charge current and out-of-plane spin current. Here, we demonstrate a new approach for magnetic-field-free switching by fabricating a van-der-Waals magnet and oxide Fe3GeTe2/SrTiO3 heterostructure. This new magnetic-field-free switching is possible because the current-driven accumulated spins at the Rashba interface precess around an emergent interface magnetism, eventually producing an ultimate out-of-plane spin polarization. This interpretation is further confirmed by the switching polarity change controlled by the in-plane initialization magnetic fields with clear hysteresis. We successfully combined van-der-Waals magnet and oxide for the first time, especially taking advantage of spin-orbit torque on the SrTiO3 oxide. This allows us to establish a new way of magnetic field-free switching. Our work demonstrates an unusual perpendicular switching application of large spin Hall angle materials and precession of accumulated spins, and in doing so, opens up a new field and opportunities for van-der-Waals magnets and oxide spintronics., Comment: Accepted by Advanced Materials (2025); 47 pages, 4 main figures, 16 supporting figures
Published: 2025

6. Digital Deep Joint Source-Channel Coding with Blind Training for Adaptive Modulation and Power Control

Author: Oh, Yongjeong, Park, Joohyuk, Choi, Jinho, Park, Jihong, and Jeon, Yo-Seb
Subjects: Electrical Engineering and Systems Science - Signal Processing, Computer Science - Information Theory
Abstract: This paper proposes a novel digital deep joint source-channel coding (DeepJSCC) framework that achieves robust performance across diverse communication environments without requiring extensive retraining and prior knowledge of communication environments. Traditional digital DeepJSCC techniques often face challenges in adapting to various communication environments, as they require significant training overhead and large amounts of communication data to develop either multiple specialized models or a single generalized model, in pre-defined communication environments. To address this challenge, in our framework, an error-adaptive blind training strategy is devised, which eliminates the need for prior knowledge of communication environments. This is achieved by modeling the relationship between the encoder's output and the decoder's input using binary symmetric channels, and optimizing bit-flip probabilities by treating them as trainable parameters. In our framework, a training-aware communication strategy is also presented, which dynamically selects the optimal encoder-decoder pair and transmission parameters based on current channel conditions. In particular, in this strategy, an adaptive power and modulation control method is developed to minimize the total transmission power, while maintaining high task performance. Simulation results demonstrate that our framework outperforms existing DeepJSCC methods, achieving higher peak signal-to-noise ratio, lower power consumption, and requiring significantly fewer encoder-decoder pairs for adaptation.
Published: 2025

7. Magnetoelectric effect in van der Waals magnets

Author: Zhang, Kai-Xuan, Park, Giung, Lee, Youjin, Kim, Beom Hyun, and Park, Je-Geun
Subjects: Condensed Matter - Materials Science, Condensed Matter - Strongly Correlated Electrons, Physics - Applied Physics, Quantum Physics
Abstract: The magnetoelectric (ME) effect is a fundamental concept in modern condensed matter physics and represents the electrical control of magnetic polarisations or vice versa. Two-dimensional (2D) van-der-Waals (vdW) magnets have emerged as a new class of materials and exhibit novel ME effects with diverse manifestations. This review emphasizes some important recent discoveries unique to vdW magnets: multiferroicity on two dimensions, spin-charge correlation, atomic ME effect and current-induced intrinsic spin-orbit torque, and electrical gating control and magnetic control of their electronic properties. We also highlight the promising route of utilizing quantum magnetic hetero- or homo-structures to engineer the ME effect and corresponding spintronic and optoelectronic device applications. Due to the intrinsic two-dimensionality, vdW magnets with those ME effects are expected to form a new, exciting research direction., Comment: Accepted by npj Quantum Materials; 27 pages, 6 main figures
Published: 2025
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8. Dynamic realization of emergent high-dimensional optical vortices

Author: Kim, Dongha, Park, Geonhyeong, Choi, Yun-Seok, Baucour, Arthur, Hwang, Jisung, Park, Sanghyeok, Yun, Hee Seong, Shin, Jonghwa, Wang, Haiwen, Fan, Shanhui, Yoon, Dong Ki, and Seo, Min-Kyo
Subjects: Physics - Optics, Condensed Matter - Mesoscale and Nanoscale Physics
Abstract: The dimensionality of vortical structures has recently been extended beyond two dimensions, providing higher-order topological characteristics and robustness for high-capacity information processing and turbulence control. The generation of high-dimensional vortical structures has mostly been demonstrated in classical systems through the complex interference of fluidic, acoustic, or electromagnetic waves. However, natural materials rarely support three- or higher-dimensional vortical structures and their physical interactions. Here, we present a high-dimensional gradient thickness optical cavity (GTOC) in which the optical coupling of planar metal-dielectric multilayers implements topological interactions across multiple dimensions. Topological interactions in high-dimensional GTOC construct non-trivial topological phases, which induce high-dimensional vortical structures in generalized parameter space in three, four dimensions, and beyond. These emergent high-dimensional vortical structures are observed under electro-optic tomography as optical vortex dynamics in two-dimensional real-space, employing the optical thicknesses of the dielectric layers as synthetic dimensions. We experimentally demonstrate emergent vortical structures, optical vortex lines and vortex rings, in a three-dimensional generalized parameter space and their topological transitions. Furthermore, we explore four-dimensional vortical structures, termed optical vortex sheets, which provide the programmability of real-space optical vortex dynamics. Our findings hold significant promise for emulating high-dimensional physics and developing active topological photonic devices., Comment: 21 pages,5 figures
Published: 2025

9. Search for continuous gravitational waves from known pulsars in the first part of the fourth LIGO-Virgo-KAGRA observing run

Author: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, Abac, A. G., Abbott, R., Abouelfettouh, I., Acernese, F., Ackley, K., Adhicary, S., Adhikari, N., Adhikari, R. X., Adkins, V. K., Agarwal, D., Agathos, M., Abchouyeh, M. Aghaei, Aguiar, O. D., Aguilar, I., Aiello, L., Ain, A., Ajith, P., Akutsu, T., Albanesi, S., Alfaidi, R. A., Al-Jodah, A., Alléné, C., Allocca, A., Al-Shammari, S., Altin, P. A., Alvarez-Lopez, S., Amato, A., Amez-Droz, L., Amorosi, A., Amra, C., Ananyeva, A., Anderson, S. B., Anderson, W. G., Andia, M., Ando, M., Andrade, T., Andres, N., Andrés-Carcasona, M., Andrić, T., Anglin, J., Ansoldi, S., Antelis, J. M., Antier, S., Aoumi, M., Appavuravther, E. Z., Appert, S., Apple, S. K., Arai, K., Araya, A., Araya, M. C., Areeda, J. S., Argianas, L., Aritomi, N., Armato, F., Arnaud, N., Arogeti, M., Aronson, S. M., Ashton, G., Aso, Y., Assiduo, M., Melo, S. Assis de Souza, Aston, S. M., Astone, P., Attadio, F., Aubin, F., AultONeal, K., Avallone, G., Babak, S., Badaracco, F., Badger, C., Bae, S., Bagnasco, S., Bagui, E., Baier, J. G., Baiotti, L., Bajpai, R., Baka, T., Ball, M., Ballardin, G., Ballmer, S. W., Banagiri, S., Banerjee, B., Bankar, D., Baral, P., Barayoga, J. C., Barish, B. C., Barker, D., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Bartoletti, A. M., Barton, M. A., Bartos, I., Basak, S., Basalaev, A., Bassiri, R., Basti, A., Bates, D. E., Bawaj, M., Baxi, P., Bayley, J. C., Baylor, A. C., Baynard II, P. A., Bazzan, M., Bedakihale, V. M., Beirnaert, F., Bejger, M., Belardinelli, D., Bell, A. S., Benedetto, V., Benoit, W., Bentley, J. D., Yaala, M. Ben, Bera, S., Berbel, M., Bergamin, F., Berger, B. K., Bernuzzi, S., Beroiz, M., Bersanetti, D., Bertolini, A., Betzwieser, J., Beveridge, D., Bevins, N., Bhandare, R., Bhardwaj, U., Bhatt, R., Bhattacharjee, D., Bhaumik, S., Bhowmick, S., Bianchi, A., Bilenko, I. A., Billingsley, G., Binetti, A., Bini, S., Birnholtz, O., Biscoveanu, S., Bisht, A., Bitossi, M., Bizouard, M. -A., Blackburn, J. K., Blagg, L. A., Blair, C. D., Blair, D. G., Bobba, F., Bode, N., Boileau, G., Boldrini, M., Bolingbroke, G. N., Bolliand, A., Bonavena, L. D., Bondarescu, R., Bondu, F., Bonilla, E., Bonilla, M. S., Bonino, A., Bonnand, R., Booker, P., Borchers, A., Boschi, V., Bose, S., Bossilkov, V., Boudart, V., Boudon, A., Bozzi, A., Bradaschia, C., Brady, P. R., Braglia, M., Branch, A., Branchesi, M., Brandt, J., Braun, I., Breschi, M., Briant, T., Brillet, A., Brinkmann, M., Brockill, P., Brockmueller, E., Brooks, A. F., Brown, B. C., Brown, D. D., Brozzetti, M. L., Brunett, S., Bruno, G., Bruntz, R., Bryant, J., Bucci, F., Buchanan, J., Bulashenko, O., Bulik, T., Bulten, H. J., Buonanno, A., Burtnyk, K., Buscicchio, R., Buskulic, D., Buy, C., Byer, R. L., Davies, G. S. Cabourn, Cabras, G., Cabrita, R., Cáceres-Barbosa, V., Cadonati, L., Cagnoli, G., Cahillane, C., Bustillo, J. Calderón, Callister, T. A., Calloni, E., Camp, J. B., Canepa, M., Santoro, G. Caneva, Cannon, K. C., Cao, H., Capistran, L. A., Capocasa, E., Capote, E., Carapella, G., Carbognani, F., Carlassara, M., Carlin, J. B., Carpinelli, M., Carrillo, G., Carter, J. J., Carullo, G., Diaz, J. Casanueva, Casentini, C., Castro-Lucas, S. Y., Caudill, S., Cavaglià, M., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cesarini, E., Chaibi, W., Chakraborty, P., Subrahmanya, S. Chalathadka, Chan, J. C. L., Chan, M., Chandra, K., Chang, R. -J., Chao, S., Charlton, E. L., Charlton, P., Chassande-Mottin, E., Chatterjee, C., Chatterjee, Debarati, Chatterjee, Deep, Chaturvedi, M., Chaty, S., Chen, A., Chen, A. H. -Y., Chen, D., Chen, H., Chen, H. Y., Chen, J., Chen, K. H., Chen, Y., Chen, Yanbei, Chen, Yitian, Cheng, H. P., Chessa, P., Cheung, H. T., Cheung, S. Y., Chiadini, F., Chiarini, G., Chierici, R., Chincarini, A., Chiofalo, M. L., Chiummo, A., Chou, C., Choudhary, S., Christensen, N., Chua, S. S. Y., Chugh, P., Ciani, G., Ciecielag, P., Cieślar, M., Cifaldi, M., Ciolfi, R., Clara, F., Clark, J. A., Clarke, J., Clarke, T. A., Clearwater, P., Clesse, S., Coccia, E., Codazzo, E., Cohadon, P. -F., Colace, S., Colleoni, M., Collette, C. G., Collins, J., Colloms, S., Colombo, A., Colpi, M., Compton, C. M., Connolly, G., Conti, L., Corbitt, T. R., Cordero-Carrión, I., Corezzi, S., Cornish, N. J., Corsi, A., Cortese, S., Costa, C. A., Cottingham, R., Coughlin, M. W., Couineaux, A., Coulon, J. -P., Countryman, S. T., Coupechoux, J. -F., Couvares, P., Coward, D. M., Cowart, M. J., Coyne, R., Craig, K., Creed, R., Creighton, J. D. E., Creighton, T. D., Cremonese, P., Criswell, A. W., Crockett-Gray, J. C. G., Crook, S., Crouch, R., Csizmazia, J., Cudell, J. R., Cullen, T. J., Cumming, A., Cuoco, E., Cusinato, M., Dabadie, P., Canton, T. Dal, Dall'Osso, S., Pra, S. Dal, Dálya, G., D'Angelo, B., Danilishin, S., D'Antonio, S., Danzmann, K., Darroch, K. E., Dartez, L. P., Dasgupta, A., Datta, S., Dattilo, V., Daumas, A., Davari, N., Dave, I., Davenport, A., Davier, M., Davies, T. F., Davis, D., Davis, L., Davis, M. C., Davis, P. J., Dax, M., De Bolle, J., Deenadayalan, M., Degallaix, J., De Laurentis, M., Deléglise, S., De Lillo, F., Dell'Aquila, D., Del Pozzo, W., De Marco, F., De Matteis, F., D'Emilio, V., Demos, N., Dent, T., Depasse, A., DePergola, N., De Pietri, R., De Rosa, R., De Rossi, C., DeSalvo, R., De Simone, R., Dhani, A., Diab, R., Díaz, M. C., Di Cesare, M., Dideron, G., Didio, N. A., Dietrich, T., Di Fiore, L., Di Fronzo, C., Di Giovanni, M., Di Girolamo, T., Diksha, D., Di Michele, A., Ding, J., Di Pace, S., Di Palma, I., Di Renzo, F., Divyajyoti, Dmitriev, A., Doctor, Z., Dohmen, E., Doleva, P. P., Dominguez, D., D'Onofrio, L., Donovan, F., Dooley, K. L., Dooney, T., Doravari, S., Dorosh, O., Drago, M., Driggers, J. C., Ducoin, J. -G., Dunn, L., Dupletsa, U., D'Urso, D., Duval, H., Duverne, P. -A., Dwyer, S. E., Eassa, C., Ebersold, M., Eckhardt, T., Eddolls, G., Edelman, B., Edo, T. B., Edy, O., Effler, A., Eichholz, J., Einsle, H., Eisenmann, M., Eisenstein, R. A., Ejlli, A., Eleveld, R. M., Emma, M., Endo, K., Engl, A. J., Enloe, E., Errico, L., Essick, R. C., Estellés, H., Estevez, D., Etzel, T., Evans, M., Evstafyeva, T., Ewing, B. E., Ezquiaga, J. M., Fabrizi, F., Faedi, F., Fafone, V., Fairhurst, S., Farah, A. M., Farr, B., Farr, W. M., Favaro, G., Favata, M., Fays, M., Fazio, M., Feicht, J., Fejer, M. M., Felicetti, R., Fenyvesi, E., Ferguson, D. L., Ferraiuolo, S., Ferrante, I., Ferreira, T. A., Fidecaro, F., Figura, P., Fiori, A., Fiori, I., Fishbach, M., Fisher, R. P., Fittipaldi, R., Fiumara, V., Flaminio, R., Fleischer, S. M., Fleming, L. S., Floden, E., Foley, E. M., Fong, H., Font, J. A., Fornal, B., Forsyth, P. W. F., Franceschetti, K., Franchini, N., Frasca, S., Frasconi, F., Mascioli, A. Frattale, Frei, Z., Freise, A., Freitas, O., Frey, R., Frischhertz, W., Fritschel, P., Frolov, V. V., Fronzé, G. G., Fuentes-Garcia, M., Fujii, S., Fujimori, T., Fulda, P., Fyffe, M., Gadre, B., Gair, J. R., Galaudage, S., Galdi, V., Gallagher, H., Gallardo, S., Gallego, B., Gamba, R., Gamboa, A., Ganapathy, D., Ganguly, A., Garaventa, B., García-Bellido, J., Núñez, C. García, García-Quirós, C., Gardner, J. W., Gardner, K. A., Gargiulo, J., Garron, A., Garufi, F., Gasbarra, C., Gateley, B., Gayathri, V., Gemme, G., Gennai, A., Gennari, V., George, J., George, R., Gerberding, O., Gergely, L., Ghosh, Archisman, Ghosh, Sayantan, Ghosh, Shaon, Ghosh, Shrobana, Ghosh, Suprovo, Ghosh, Tathagata, Giacoppo, L., Giaime, J. A., Giardina, K. D., Gibson, D. R., Gibson, D. T., Gier, C., Giri, P., Gissi, F., Gkaitatzis, S., Glanzer, J., Glotin, F., Godfrey, J., Godwin, P., Goebbels, N. L., Goetz, E., Golomb, J., Lopez, S. Gomez, Goncharov, B., Gong, Y., González, G., Goodarzi, P., Goode, S., Goodwin-Jones, A. W., Gosselin, M., Göttel, A. S., Gouaty, R., Gould, D. W., Govorkova, K., Goyal, S., Grace, B., Grado, A., Graham, V., Granados, A. E., Granata, M., Granata, V., Gras, S., Grassia, P., Gray, A., Gray, C., Gray, R., Greco, G., Green, A. C., Green, S. M., Green, S. R., Gretarsson, A. M., Gretarsson, E. M., Griffith, D., Griffiths, W. L., Griggs, H. L., Grignani, G., Grimaldi, A., Grimaud, C., Grote, H., Guerra, D., Guetta, D., Guidi, G. M., Guimaraes, A. R., Gulati, H. K., Gulminelli, F., Gunny, A. M., Guo, H., Guo, W., Guo, Y., Gupta, Anchal, Gupta, Anuradha, Gupta, Ish, Gupta, N. C., Gupta, P., Gupta, S. K., Gupta, T., Gupte, N., Gurs, J., Gutierrez, N., Guzman, F., H, H. -Y., Haba, D., Haberland, M., Haino, S., Hall, E. D., Hamilton, E. Z., Hammond, G., Han, W. -B., Haney, M., Hanks, J., Hanna, C., Hannam, M. D., Hannuksela, O. A., Hanselman, A. G., Hansen, H., Hanson, J., Harada, R., Hardison, A. R., Haris, K., Harmark, T., Harms, J., Harry, G. M., Harry, I. W., Hart, J., Haskell, B., Haster, C. -J., Hathaway, J. S., Haughian, K., Hayakawa, H., Hayama, K., Hayes, R., Heffernan, A., Heidmann, A., Heintze, M. C., Heinze, J., Heinzel, J., Heitmann, H., Hellman, F., Hello, P., Helmling-Cornell, A. F., Hemming, G., Henderson-Sapir, O., Hendry, M., Heng, I. S., Hennes, E., Henshaw, C., Hertog, T., Heurs, M., Hewitt, A. L., Heyns, J., Higginbotham, S., Hild, S., Hill, S., Himemoto, Y., Hirata, N., Hirose, C., Ho, W. C. G., Hoang, S., Hochheim, S., Hofman, D., Holland, N. A., Holley-Bockelmann, K., Holmes, Z. J., Holz, D. E., Honet, L., Hong, C., Hornung, J., Hoshino, S., Hough, J., Hourihane, S., Howell, E. J., Hoy, C. G., Hrishikesh, C. A., Hsieh, H. -F., Hsiung, C., Hsu, H. C., Hsu, W. -F., Hu, P., Hu, Q., Huang, H. Y., Huang, Y. -J., Huddart, A. D., Hughey, B., Hui, D. C. Y., Hui, V., Husa, S., Huxford, R., Huynh-Dinh, T., Iampieri, L., Iandolo, G. A., Ianni, M., Iess, A., Imafuku, H., Inayoshi, K., Inoue, Y., Iorio, G., Iqbal, M. H., Irwin, J., Ishikawa, R., Isi, M., Ismail, M. A., Itoh, Y., Iwanaga, H., Iwaya, M., Iyer, B. R., JaberianHamedan, V., Jacquet, C., Jacquet, P. -E., Jadhav, S. J., Jadhav, S. P., Jain, T., James, A. L., James, P. A., Jamshidi, R., Janquart, J., Janssens, K., Janthalur, N. N., Jaraba, S., Jaranowski, P., Jaume, R., Javed, W., Jennings, A., Jia, W., Jiang, J., Jin, H., Kubisz, J., Johanson, C., Johns, G. R., Johnson, N. A., Johnston, M. C., Johnston, R., Johny, N., Jones, D. H., Jones, D. I., Jones, R., Jose, S., Joshi, P., Ju, L., Jung, K., Junker, J., Juste, V., Kajita, T., Kaku, I., Kalaghatgi, C., Kalogera, V., Kamiizumi, M., Kanda, N., Kandhasamy, S., Kang, G., Kanner, J. B., Kapadia, S. J., Kapasi, D. P., Karat, S., Karathanasis, C., Kashyap, R., Kasprzack, M., Kastaun, W., Kato, T., Katsavounidis, E., Katzman, W., Kaushik, R., Kawabe, K., Kawamoto, R., Kazemi, A., Keitel, D., Kelley-Derzon, J., Kennington, J., Kesharwani, R., Key, J. S., Khadela, R., Khadka, S., Khalili, F. Y., Khan, F., Khan, I., Khanam, T., Khursheed, M., Khusid, N. M., Kiendrebeogo, W., Kijbunchoo, N., Kim, C., Kim, J. C., Kim, K., Kim, M. H., Kim, S., Kim, Y. -M., Kimball, C., Kinley-Hanlon, M., Kinnear, M., Kissel, J. S., Klimenko, S., Knee, A. M., Knust, N., Kobayashi, K., Koch, P., Koehlenbeck, S. M., Koekoek, G., Kohri, K., Kokeyama, K., Koley, S., Kolitsidou, P., Kolstein, M., Komori, K., Kong, A. K. H., Kontos, A., Korobko, M., Kossak, R. V., Kou, X., Koushik, A., Kouvatsos, N., Kovalam, M., Kozak, D. B., Kranzhoff, S. L., Kringel, V., Krishnendu, N. V., Królak, A., Kruska, K., Kuehn, G., Kuijer, P., Kulkarni, S., Ramamohan, A. 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L., Pearlman, A. B., Romero, G. E., Shannon, R. M., Shaw, B., Stairs, I. H., Stappers, B. W., Tan, C. M., Theureau, G., Thompson, M., Weltevrede, P., and Zubieta, E.
Subjects: Astrophysics - High Energy Astrophysical Phenomena
Abstract: Continuous gravitational waves (CWs) emission from neutron stars carries information about their internal structure and equation of state, and it can provide tests of General Relativity. We present a search for CWs from a set of 45 known pulsars in the first part of the fourth LIGO--Virgo--KAGRA observing run, known as O4a. We conducted a targeted search for each pulsar using three independent analysis methods considering the single-harmonic and the dual-harmonic emission models. We find no evidence of a CW signal in O4a data for both models and set upper limits on the signal amplitude and on the ellipticity, which quantifies the asymmetry in the neutron star mass distribution. For the single-harmonic emission model, 29 targets have the upper limit on the amplitude below the theoretical spin-down limit. The lowest upper limit on the amplitude is $6.4\!\times\!10^{-27}$ for the young energetic pulsar J0537-6910, while the lowest constraint on the ellipticity is $8.8\!\times\!10^{-9}$ for the bright nearby millisecond pulsar J0437-4715. Additionally, for a subset of 16 targets we performed a narrowband search that is more robust regarding the emission model, with no evidence of a signal. We also found no evidence of non-standard polarizations as predicted by the Brans-Dicke theory., Comment: main paper: 12 pages, 6 figures, 4 tables
Published: 2025

10. MalCL: Leveraging GAN-Based Generative Replay to Combat Catastrophic Forgetting in Malware Classification

Author: Park, Jimin, Ji, AHyun, Park, Minji, Rahman, Mohammad Saidur, and Oh, Se Eun
Subjects: Computer Science - Cryptography and Security, Computer Science - Artificial Intelligence
Abstract: Continual Learning (CL) for malware classification tackles the rapidly evolving nature of malware threats and the frequent emergence of new types. Generative Replay (GR)-based CL systems utilize a generative model to produce synthetic versions of past data, which are then combined with new data to retrain the primary model. Traditional machine learning techniques in this domain often struggle with catastrophic forgetting, where a model's performance on old data degrades over time. In this paper, we introduce a GR-based CL system that employs Generative Adversarial Networks (GANs) with feature matching loss to generate high-quality malware samples. Additionally, we implement innovative selection schemes for replay samples based on the model's hidden representations. Our comprehensive evaluation across Windows and Android malware datasets in a class-incremental learning scenario -- where new classes are introduced continuously over multiple tasks -- demonstrates substantial performance improvements over previous methods. For example, our system achieves an average accuracy of 55% on Windows malware samples, significantly outperforming other GR-based models by 28%. This study provides practical insights for advancing GR-based malware classification systems. The implementation is available at \url {https://github.com/MalwareReplayGAN/MalCL}\footnote{The code will be made public upon the presentation of the paper}., Comment: Accepted paper at AAAI 2025. 9 pages, Figure 6, Table 1
Published: 2025

11. Measurement of the branching fraction, polarization, and time-dependent $CP$ asymmetry in $B^0 \to \rho^+\rho^-$ decays and constraint on the CKM angle $\phi_2$

Author: Belle II Collaboration, Adachi, I., Aggarwal, L., Ahmed, H., Akopov, N., Alhakami, M., Aloisio, A., Althubiti, N., Ky, N. Anh, Asner, D. M., Atmacan, H., Aushev, V., Aversano, M., Ayad, R., Babu, V., Baghel, N. K., Bambade, P., Banerjee, Sw., Barrett, M., Bartl, M., Baudot, J., Baur, A., Beaubien, A., Becker, J., Bennett, J. V., Bertacchi, V., Bertemes, M., Bertholet, E., Bessner, M., Bettarini, S., Bhuyan, B., Biswas, D., Bobrov, A., Bodrov, D., Bolz, A., Bondar, A., Borah, J., Boschetti, A., Bozek, A., Bračko, M., Branchini, P., Briere, R. A., Browder, T. E., Budano, A., Bussino, S., Campagna, Q., Campajola, M., Casarosa, G., Cecchi, C., Cerasoli, J., Chang, M. -C., Chang, P., Cheaib, R., Cheema, P., Cheon, B. G., Chilikin, K., Chirapatpimol, K., Cho, H. -E., Cho, K., Cho, S. -J., Choi, S. -K., Choudhury, S., Cochran, J., Corona, L., Cui, J. X., De La Cruz-Burelo, E., De La Motte, S. A., De Nardo, G., De Pietro, G., de Sangro, R., Destefanis, M., Dey, S., Di Capua, F., Dingfelder, J., Doležal, Z., Jiménez, I. Domínguez, Dong, T. V., Dong, X., Dorigo, M., Dossett, D., Dugic, K., Dujany, G., Ecker, P., Eppelt, J., Feichtinger, P., Ferber, T., Fillinger, T., Finck, C., Finocchiaro, G., Fodor, A., Forti, F., Fulsom, B. G., Gabrielli, A., Ganiev, E., Garcia-Hernandez, M., Garg, R., Gaudino, G., Gaur, V., Gaz, A., Gellrich, A., Ghevondyan, G., Ghosh, D., Ghumaryan, H., Giakoustidis, G., Giordano, R., Giri, A., Gironell, P. Gironella, Glazov, A., Gobbo, B., Godang, R., Gogota, O., Goldenzweig, P., Gradl, W., Graziani, E., Greenwald, D., Gruberová, Z., Guan, Y., Gudkova, K., Haide, I., Hara, T., Harris, C., Hayasaka, K., Hazra, S., Hearty, C., Hedges, M. T., Heidelbach, A., de la Cruz, I. Heredia, Villanueva, M. Hernández, Higuchi, T., Hoek, M., Hohmann, M., Hoppe, R., Horak, P., Hsu, C. -L., Humair, T., Iijima, T., Inami, K., Ipsita, N., Ishikawa, A., Itoh, R., Iwasaki, M., Jacobi, D., Jacobs, W. W., Jang, E. -J., Jin, Y., Johnson, A., Junkerkalefeld, H., Kaleta, M., Kaliyar, A. B., Kandra, J., Keil, F., Ketter, C., Kiesling, C., Kim, C. -H., Kim, D. Y., Kim, J. -Y., Kim, K. -H., Kim, Y. -K., Kinoshita, K., Kodyš, P., Koga, T., Kohani, S., Kojima, K., Korobov, A., Korpar, S., Kovalenko, E., Kowalewski, R., Križan, P., Krokovny, P., Kuhr, T., Kulii, Y., Kumar, R., Kumara, K., Kunigo, T., Kuzmin, A., Kwon, Y. -J., Lacaprara, S., Lalwani, K., Lam, T., Lanceri, L., Lange, J. S., Lau, T. S., Laurenza, M., Leboucher, R., Diberder, F. R. Le, Lee, M. J., Lemettais, C., Leo, P., Li, L. K., Li, Q. M., Li, W. Z., Li, Y., Li, Y. B., Liao, Y. P., Libby, J., Lin, J., Lin, S., Liu, M. H., Liu, Q. Y., Liu, Z. Q., Liventsev, D., Longo, S., Lueck, T., Lyu, C., Ma, Y., Madaan, C., Maggiora, M., Maharana, S. P., Maiti, R., Mancinelli, G., Manfredi, R., Manoni, E., Mantovano, M., Marcantonio, D., Marcello, S., Marinas, C., Martellini, C., Martens, A., Martini, A., Martinov, T., Massaccesi, L., Masuda, M., Matsuoka, K., Matvienko, D., Maurya, S. K., Maushart, M., McKenna, J. A., Meier, F., Meleshko, D., Merola, M., Miller, C., Mirra, M., Mitra, S., Miyabayashi, K., Miyake, H., Mohanty, G. B., Mondal, S., Moneta, S., Moser, H. -G., Mussa, R., Nakamura, I., Nakao, M., Nakazawa, Y., Naruki, M., Natkaniec, Z., Natochii, A., Nayak, M., Nazaryan, G., Neu, M., Nishida, S., Ogawa, S., Okubo, R., Ono, H., Onuki, Y., Pakhlova, G., Pardi, S., Parham, K., Park, H., Park, J., Park, K., Park, S. -H., Passeri, A., Patra, S., Pedlar, T. K., Peruzzi, I., Peschke, R., Pestotnik, R., Piilonen, L. E., Podesta-Lerma, P. L. M., Podobnik, T., Pokharel, S., Praz, C., Prell, S., Prencipe, E., Prim, M. T., Purwar, H., Raiz, S., Ravindran, K., Rehman, J. U., Reif, M., Reiter, S., Remnev, M., Reuter, L., Herrmann, D. Ricalde, Ripp-Baudot, I., Rizzo, G., Roehrken, M., Roney, J. M., Rostomyan, A., Rout, N., Sakai, Y., Sanders, D. A., Sandilya, S., Santelj, L., Savinov, V., Scavino, B., Schwanda, C., Schwartz, A. J., Seino, Y., Selce, A., Senyo, K., Serrano, J., Sevior, M. E., Sfienti, C., Shan, W., Shi, X. D., Shillington, T., Shiu, J. -G., Shtol, D., Shwartz, B., Sibidanov, A., Simon, F., Skorupa, J., Sobie, R. J., Sobotzik, M., Soffer, A., Sokolov, A., Solovieva, E., Spataro, S., Spruck, B., Song, W., Starič, M., Stavroulakis, P., Stefkova, S., Stroili, R., Strube, J., Sumihama, M., Sumisawa, K., Suwonjandee, N., Svidras, H., Takizawa, M., Tamponi, U., Tanida, K., Tenchini, F., Thaller, A., Tittel, O., Tiwary, R., Torassa, E., Trabelsi, K., Tsaklidis, I., Ueda, I., Uglov, T., Unger, K., Unno, Y., Uno, K., Uno, S., Urquijo, P., Ushiroda, Y., Vahsen, S. E., van Tonder, R., Varvell, K. E., Veronesi, M., Vinokurova, A., Vismaya, V. S., Vitale, L., Vobbilisetti, V., Volpe, R., Wakai, M., Wallner, S., Wang, M. -Z., Warburton, A., Watanabe, M., Watanuki, S., Wessel, C., Won, E., Xu, X. P., Yabsley, B. D., Yamada, S., Yan, W., Yelton, J., Yin, J. H., Yoshihara, K., Yuan, J., Yusa, Y., Zani, L., Zhilich, V., Zhou, J. S., Zhou, Q. D., Zhu, L., and Žlebčík, R.
Subjects: High Energy Physics - Experiment
Abstract: We present a measurement of the branching fraction and fraction of longitudinal polarization of $B^0 \to \rho^+ \rho^-$ decays, which have two $\pi^0$'s in the final state. We also measure time-dependent $CP$ violation parameters for decays into longitudinally polarized $\rho^+ \rho^-$ pairs. This analysis is based on a data sample containing $(387\pm6) \times 10^6$ \BBbar pairs collected with the Belle~II detector at the SuperKEKB asymmetric-energy $e^+e^-$ collider in 2019-2022. We obtain ${B}(B^0\to\rho^+\rho^-) = (2.88 ^{+0.23}_{-0.22} {}^{+0.29}_{-0.27}) \times 10^{-5}, f_{L} = 0.921 ^{+0.024}_{-0.025} {}^{+0.017}_{-0.015}$, $S = -0.26\pm0.19\pm0.08$, and $C = -0.02\pm0.12^{+0.06}_{-0.05}$, where the first uncertainties are statistical and the second are systematic. We use these results to perform an isospin analysis to constrain the CKM angle $\phi_2$ and obtain two solutions; the result consistent with other Standard Model constraints is $\phi_2 = (92.6^{+4.5}_{-4.8})^\circ$.
Published: 2024

12. A Selective Secure Precoding Framework for MU-MIMO Rate-Splitting Multiple Access Networks Under Limited CSIT

Author: Lee, Sangmin, Park, Seokjun, Park, Jeonghun, and Choi, Jinseok
Subjects: Computer Science - Information Theory, Electrical Engineering and Systems Science - Signal Processing
Abstract: In this paper, we propose a robust and adaptable secure precoding framework designed to encapsulate a intricate scenario where legitimate users have different information security: secure private or normal public information. Leveraging rate-splitting multiple access (RSMA), we formulate the sum secrecy spectral efficiency (SE) maximization problem in downlink multi-user multiple-input multiple-output (MIMO) systems with multi-eavesdropper. To resolve the challenges including the heterogeneity of security, non-convexity, and non-smoothness of the problem, we initially approximate the problem using a LogSumExp technique. Subsequently, we derive the first-order optimality condition in the form of a generalized eigenvalue problem. We utilize a power iteration-based method to solve the condition, thereby achieving a superior local optimal solution. The proposed algorithm is further extended to a more realistic scenario involving limited channel state information at the transmitter (CSIT). To effectively utilize the limited channel information, we employ a conditional average rate approach. Handling the conditional average by deriving useful bounds, we establish a lower bound for the objective function under the conditional average. Then we apply the similar optimization method as for the perfect CSIT case. In simulations, we validate the proposed algorithm in terms of the sum secrecy SE., Comment: 13 pages, 10 figures
Published: 2024

13. Measurement of reactor antineutrino oscillation amplitude and frequency using 3800 days of complete data sample of the RENO experiment

Author: Jeon, S., Kim, H. I., Choi, J. H., Jang, H. I., Jang, J. S., Joo, K. K., Jung, D. E., Kim, J. G., Kim, J. H., Kim, J. Y., Kim, S. B., Kim, S. Y., Kim, W., Kwon, E., Lee, D. H., Lee, H. G., Lee, W. J., Lim, I. T., Moon, D. H., Pac, M. Y., Park, J. S., Park, R. G., Seo, H., Seo, J. W., Shin, C. D., Yang, B. S., Yoo, J., Yoon, S. G., Yeo, I. S., and Yu, I.
Subjects: High Energy Physics - Experiment
Abstract: We report an updated neutrino mixing angle of $\theta_{13}$ obtained from a complete data sample of the RENO experiment. The experiment has measured the amplitude and frequency of reactor anti-electron-neutrinos ($\bar{\nu}_{e}$) oscillations at the Hanbit nuclear power plant, Younggwang, Korea, since August 2011. As of March 2023, the data acquisition was completed after a total of 3800 live days of detector operation. The observed candidates via inverse beta decay (IBD) are 1,211,995 (144,667) in the near (far) detector. Based on an observed energy-dependent reactor neutrino disappearance, neutrino oscillation parameters of $\theta_{13}$ and $\lvert\Delta m_{ee}^2\rvert$ are precisely determined as $\sin^{2}2\theta_{13}=0.0920_{-0.0042}^{+0.0044}(\text{stat.})_{-0.0041}^{+0.0041}(\text{syst.})$ and $\lvert\Delta m_{ee}^2\rvert=\left[2.57_{-0.11}^{+0.10}(\text{stat.})_{-0.05}^{+0.05}(\text{syst.})\right]\times10^{-3}~\text{eV}^{2}$. Compared to the previous RENO results published in Ref.~\cite{PhysRevLett.121.201801}, the precision is improved from 7.5\% to 6.4\% for $\sin^{2}2\theta_{13}$ and from 5.2\% to 4.5\% for $\lvert\Delta m_{ee}^2\rvert$. The statistical error of the measurement has reached our goal and is hardly improved with additional data-taking., Comment: 13 pages, 11 figures
Published: 2024

14. The first JSNS$^2$ measurement of electron neutrino flux using $^{12}C(\nu_{e},e^{-}) ^{12}N_{g.s.}$ reaction

Author: Dodo, T., Cheoun, M. K., Choi, J. H., Choi, J. Y., Goh, J., Haga, K., Harada, M., Hasegawa, S., Hwang, W., Jang, H. I., Jang, J. S., Joo, K. K., Jung, D. E., Kang, S. K., Kasugai, Y., Kawasaki, T., Kim, E. M., Kim, S. Y., Kim, S. B., Kinoshita, H., Konno, T., Lee, D. H., Little, C., Maruyama, T., Marzec, E., Masuda, S., Meigo, S., Moon, D. H., Nakano, T., Niiyama, M., Nishikawa, K., Pac, M. Y., Park, B. J., Park, H. W., Park, J. B., Park, J. S., Park, R. G., Peeters, S. J. M., Ryu, J. W., Sakai, K., Sakamoto, S., Shima, T., Shin, C. D., Spitz, J., Suekane, F., Sugaya, Y., Suzuya, K., Yamaguchi, Y., Yeo, I. S., and Yu, I.
Subjects: High Energy Physics - Experiment
Abstract: JSNS$^2$ (J-PARC Sterile Neutrino Search at J-PARC Spallation Neutron Source) is an experiment searching for sterile neutrinos through the observation of $\bar{\nu}_{\mu} \rightarrow \bar{\nu}_e$ appearance oscillations, using neutrinos produced by muon decay-at-rest. A key aspect of the experiment involves accurately understanding the neutrino flux and the quantities of pions and muons, which are progenitors of (anti-)neutrinos, given that their production rates have yet to be measured. We present the first electron-neutrino flux measurement using $^{12}\mathrm{C}(\nu_{e},e^{-}) ^{12}\mathrm{N}_{g.s.}$ reaction in JSNS$^2$, yielding a flux of (6.7 $\pm$ 1.6 (stat.) $\pm$ 1.7 (syst.)) $\times$ 10$^{-9}$ cm$^{-2}$ proton$^{-1}$ at the JSNS$^2$ detector location, located at 24 meters distance from the mercury target. This flux measurement is consistent with predictions from simulations based on hadron models.
Published: 2024

15. Gravitational waves from a first-order phase transition of the inflaton

Author: Kersten, Jörn, Park, Seong Chan, Park, Yeji, Son, Juhoon, and Velasco-Sevilla, Liliana
Subjects: High Energy Physics - Phenomenology, Astrophysics - High Energy Astrophysical Phenomena, General Relativity and Quantum Cosmology
Abstract: We explore the production of gravitational waves (GW) resulting from a first-order phase transition (FOPT) in a non-minimally coupled `Dark Higgs Inflation' model. Utilizing a dark sector scalar field as the inflaton, we demonstrate how inflationary dynamics naturally set the stage for observable FOPT. These transitions, influenced by thermal and quantum effects, generate GW spectra potentially detectable by observatories such as LISA, DECIGO, the Cosmic Explorer and the Einstein Telescope. Our study highlights the inflaton's dual role in cosmic inflation and early Universe phase transitions, presenting a unified framework to probe physics beyond the Standard Model through gravitational wave astronomy., Comment: 24 pages, 9 figures
Published: 2024

16. Search for lepton flavor-violating decay modes $B^0\to K_S^0\tau^\pm\ell^\mp~(\ell=\mu, e)$ with hadronic $B$-tagging at Belle and Belle II

Author: Belle, Collaborations, Belle II, Adachi, I., Adamczyk, K., Aggarwal, L., Ahmed, H., Aihara, H., Akopov, N., Alhakami, M., Aloisio, A., Althubiti, N., Ky, N. Anh, Asner, D. M., Atmacan, H., Aushev, V., Aversano, M., Ayad, R., Babu, V., Bae, H., Baghel, N. K., Bahinipati, S., Bambade, P., Banerjee, Sw., Bansal, S., Barrett, M., Bartl, M., Baudot, J., Baur, A., Beaubien, A., Becherer, F., Becker, J., Bennett, J. V., Bernlochner, F. U., Bertacchi, V., Bertemes, M., Bertholet, E., Bessner, M., Bettarini, S., Bhardwaj, V., Bhuyan, B., Bianchi, F., Biswas, D., Bobrov, A., Bodrov, D., Bolz, A., Boschetti, A., Bozek, A., Bračko, M., Branchini, P., Briere, R. A., Browder, T. E., Budano, A., Bussino, S., Campagna, Q., Campajola, M., Cao, L., Casarosa, G., Cecchi, C., Cerasoli, J., Chang, M. -C., Chang, P., Cheaib, R., Cheema, P., Cheon, B. G., Chilikin, K., Chirapatpimol, K., Cho, H. -E., Cho, K., Cho, S. -J., Choi, S. -K., Choudhury, S., Cochran, J., Corona, L., Cui, J. X., De La Cruz-Burelo, E., De La Motte, S. A., de Marino, G., De Nardo, G., De Pietro, G., de Sangro, R., Destefanis, M., Dey, S., Dhamija, R., Di Canto, A., Di Capua, F., Dingfelder, J., Doležal, Z., Jiménez, I. Domínguez, Dong, T. V., Dong, X., Dorigo, M., Dossett, D., Dubey, S., Dugic, K., Dujany, G., Ecker, P., Feichtinger, P., Ferber, T., Fillinger, T., Finck, C., Finocchiaro, G., Fodor, A., Forti, F., Fulsom, B. G., Gabrielli, A., Ganiev, E., Garcia-Hernandez, M., Garg, R., Gaudino, G., Gaur, V., Gaz, A., Gellrich, A., Ghevondyan, G., Ghosh, D., Ghumaryan, H., Giakoustidis, G., Giordano, R., Giri, A., Gironell, P. Gironella, Glazov, A., Gobbo, B., Godang, R., Gogota, O., Goldenzweig, P., Gradl, W., Granderath, S., Graziani, E., Greenwald, D., Gruberová, Z., Guan, Y., Gudkova, K., Haide, I., Han, Y., Hara, T., Harris, C., Hayasaka, K., Hayashii, H., Hazra, S., Hearty, C., Hedges, M. T., Heidelbach, A., de la Cruz, I. Heredia, Villanueva, M. Hernández, Higuchi, T., Hoek, M., Hohmann, M., Hoppe, R., Horak, P., Hsu, C. -L., Humair, T., Iijima, T., Inami, K., Inguglia, G., Ipsita, N., Ishikawa, A., Itoh, R., Iwasaki, M., Jacobi, D., Jacobs, W. W., Jaffe, D. E., Jang, E. -J., Ji, Q. P., Jia, S., Jin, Y., Johnson, A., Joo, K. K., Junkerkalefeld, H., Kaleta, M., Kaliyar, A. B., Kandra, J., Kang, K. H., Kang, S., Karyan, G., Kawasaki, T., Keil, F., Ketter, C., Kiesling, C., Kim, C. -H., Kim, D. Y., Kim, J. -Y., Kim, K. -H., Kim, Y. -K., Kinoshita, K., Kodyš, P., Koga, T., Kohani, S., Kojima, K., Korobov, A., Korpar, S., Kovalenko, E., Kowalewski, R., Križan, P., Krokovny, P., Kuhr, T., Kulii, Y., Kumar, D., Kumar, R., Kumara, K., Kunigo, T., Kuzmin, A., Kwon, Y. -J., Lacaprara, S., Lai, Y. -T., Lalwani, K., Lam, T., Lanceri, L., Lange, J. S., Lau, T. S., Laurenza, M., Leboucher, R., Diberder, F. R. Le, Lee, M. J., Lemettais, C., Leo, P., Lewis, P. M., Li, C., Li, L. K., Li, Q. M., Li, W. Z., Li, Y., Li, Y. B., Liao, Y. P., Libby, J., Lin, J., Lin, S., Liu, M. H., Liu, Q. Y., Liu, Y., Liu, Z. Q., Liventsev, D., Longo, S., Lueck, T., Luo, T., Lyu, C., Ma, Y., Madaan, C., Maggiora, M., Maharana, S. P., Maiti, R., Mancinelli, G., Manfredi, R., Manoni, E., Mantovano, M., Marcello, S., Marinas, C., Martellini, C., Martens, A., Martini, A., Martinov, T., Massaccesi, L., Masuda, M., Matvienko, D., Maurya, S. K., Maushart, M., McKenna, J. A., Mehta, R., Meier, F., Meleshko, D., Merola, M., Miller, C., Mirra, M., Mitra, S., Miyabayashi, K., Miyake, H., Mohanty, G. B., Mondal, S., Moneta, S., Moser, H. -G., Mussa, R., Nakamura, I., Nakamura, K. R., Nakao, M., Nakazawa, Y., Naruki, M., Natkaniec, Z., Natochii, A., Nayak, M., Nazaryan, G., Neu, M., Nishida, S., Ogawa, S., Ono, H., Onuki, Y., Otani, F., Pakhlova, G., Paoloni, E., Pardi, S., Parham, K., Park, H., Park, J., Park, K., Park, S. -H., Paschen, B., Passeri, A., Patra, S., Pedlar, T. K., Peruzzi, I., Peschke, R., Pestotnik, R., Piccolo, M., Piilonen, L. E., Podesta-Lerma, P. L. M., Podobnik, T., Pokharel, S., Praz, C., Prell, S., Prencipe, E., Prim, M. T., Prudiiev, I., Purwar, H., Rados, P., Raeuber, G., Raiz, S., Rauls, N., Ravindran, K., Rehman, J. U., Reif, M., Reiter, S., Remnev, M., Reuter, L., Herrmann, D. Ricalde, Ripp-Baudot, I., Rizzo, G., Robertson, S. H., Roehrken, M., Roney, J. M., Rostomyan, A., Rout, N., Sanders, D. A., Sandilya, S., Santelj, L., Savinov, V., Scavino, B., Schneider, S., Schnell, G., Schwanda, C., Seino, Y., Selce, A., Senyo, K., Serrano, J., Sevior, M. E., Sfienti, C., Shan, W., Sharma, C., Shi, X. D., Shillington, T., Shimasaki, T., Shiu, J. -G., Shtol, D., Sibidanov, A., Simon, F., Singh, J. B., Skorupa, J., Sobie, R. J., Sobotzik, M., Soffer, A., Sokolov, A., Solovieva, E., Spataro, S., Spruck, B., Song, W., Starič, M., Stavroulakis, P., Stefkova, S., Stroili, R., Strube, J., Sue, Y., Sumihama, M., Sumisawa, K., Sutcliffe, W., Suwonjandee, N., Svidras, H., Takahashi, M., Takizawa, M., Tamponi, U., Tanida, K., Tenchini, F., Thaller, A., Tittel, O., Tiwary, R., Torassa, E., Trabelsi, K., Tsaklidis, I., Ueda, I., Uglov, T., Unger, K., Unno, Y., Uno, K., Uno, S., Urquijo, P., Ushiroda, Y., Vahsen, S. E., van Tonder, R., Varvell, K. E., Veronesi, M., Vinokurova, A., Vismaya, V. S., Vitale, L., Vobbilisetti, V., Volpe, R., Wakai, M., Wallner, S., Wang, M. -Z., Wang, Z., Warburton, A., Watanabe, M., Watanuki, S., Wessel, C., Wiechczynski, J., Won, E., Xu, X. P., Yabsley, B. D., Yamada, S., Yan, W., Yelton, J., Yin, J. H., Yoshihara, K., Yuan, C. Z., Yuan, J., Zani, L., Zeng, F., Zhang, B., Zhou, J. S., Zhou, Q. D., Zhu, L., Zhukova, V. I., and Žlebčík, R.
Subjects: High Energy Physics - Experiment
Abstract: We present the first search for the lepton flavor-violating decay modes $B^0 \rightarrow K_S^0 \tau^\pm \ell^\mp~(\ell=\mu, e)$ using the 711 fb$^{-1}$ and 365 fb$^{-1}$ data samples recorded by the Belle and Belle II detectors, respectively. We use a hadronic $B$-tagging technique, and search for the signal decay in the system recoiling against the fully reconstructed $B$ meson. We find no evidence for $B^0 \rightarrow K_S^0 \tau^\pm \ell^\mp$ decays and set 90\% confidence level upper limits on the branching fractions in the range of $[0.8,\,3.6]\times10^{-5}$.
Published: 2024

17. Measurement of the branching fraction and $\it CP$-violating asymmetry of the decay $B^{0} \rightarrow \pi^{0} \pi^{0}$ using $387$ million bottom-antibottom meson pairs in Belle II data

Author: Belle II Collaboration, Adachi, I., Aggarwal, L., Ahmed, H., Aihara, H., Alhakami, M., Aloisio, A., Althubiti, N., Ky, N. Anh, Asner, D. M., Atmacan, H., Aushev, V., Aversano, M., Ayad, R., Babu, V., Bae, H., Baghel, N. K., Bahinipati, S., Bambade, P., Banerjee, Sw., Bansal, S., Barrett, M., Bartl, M., Baudot, J., Baur, A., Beaubien, A., Becherer, F., Becker, J., Bennett, J. V., Bernlochner, F. U., Bertacchi, V., Bertemes, M., Bertholet, E., Bessner, M., Bettarini, S., Bhardwaj, V., Bhuyan, B., Bianchi, F., Bilka, T., Biswas, D., Bobrov, A., Bodrov, D., Bolz, A., Bondar, A., Borah, J., Boschetti, A., Bozek, A., Bračko, M., Branchini, P., Briere, R. A., Browder, T. E., Budano, A., Bussino, S., Campagna, Q., Campajola, M., Cao, L., Casarosa, G., Cecchi, C., Cerasoli, J., Chang, M. -C., Chang, P., Cheaib, R., Cheema, P., Cheon, B. G., Chilikin, K., Chirapatpimol, K., Cho, H. -E., Cho, K., Cho, S. -J., Choi, S. -K., Choudhury, S., Cochran, J., Corona, L., Cui, J. X., De La Cruz-Burelo, E., De La Motte, S. A., de Marino, G., De Nardo, G., De Pietro, G., de Sangro, R., Destefanis, M., Dey, S., Dhamija, R., Di Canto, A., Di Capua, F., Dingfelder, J., Doležal, Z., Jiménez, I. Domínguez, Dong, T. V., Dong, X., Dorigo, M., Dossett, D., Dubey, S., Dugic, K., Dujany, G., Ecker, P., Epifanov, D., Eppelt, J., Feichtinger, P., Ferber, T., Fillinger, T., Finck, C., Finocchiaro, G., Fodor, A., Forti, F., Frey, A., Fulsom, B. G., Gabrielli, A., Ganiev, E., Garcia-Hernandez, M., Garg, R., Gaudino, G., Gaur, V., Gaz, A., Gellrich, A., Ghevondyan, G., Ghosh, D., Giakoustidis, G., Giordano, R., Giri, A., Gironell, P. Gironella, Glazov, A., Gobbo, B., Godang, R., Gogota, O., Goldenzweig, P., Gradl, W., Granderath, S., Graziani, E., Greenwald, D., Gruberová, Z., Guan, Y., Gudkova, K., Haide, I., Halder, S., Han, Y., Hara, T., Harris, C., Hayasaka, K., Hayashii, H., Hazra, S., Hearty, C., Hedges, M. T., Heidelbach, A., de la Cruz, I. Heredia, Villanueva, M. Hernández, Higuchi, T., Hoek, M., Hohmann, M., Hoppe, R., Horak, P., Hsu, C. -L., Humair, T., Iijima, T., Inami, K., Ipsita, N., Ishikawa, A., Itoh, R., Iwasaki, M., Jackson, P., Jacobi, D., Jacobs, W. W., Jang, E. -J., Ji, Q. P., Jia, S., Jin, Y., Johnson, A., Joo, K. K., Junkerkalefeld, H., Kalita, D., Kaliyar, A. B., Kandra, J., Kang, K. H., Kang, S., Karyan, G., Kawasaki, T., Keil, F., Ketter, C., Kiesling, C., Kim, C. -H., Kim, D. Y., Kim, J. -Y., Kim, K. -H., Kim, Y. -K., Kim, Y. J., Kinoshita, K., Kodyš, P., Koga, T., Kohani, S., Kojima, K., Korobov, A., Korpar, S., Kovalenko, E., Kowalewski, R., Križan, P., Krokovny, P., Kuhr, T., Kulii, Y., Kumar, D., Kumar, M., Kumar, R., Kumara, K., Kunigo, T., Kuzmin, A., Kwon, Y. -J., Lacaprara, S., Lai, Y. -T., Lalwani, K., Lam, T., Lanceri, L., Lange, J. S., Lau, T. S., Laurenza, M., Lautenbach, K., Leboucher, R., Diberder, F. R. Le, Lee, M. J., Lemettais, C., Leo, P., Levit, D., Lewis, P. M., Li, C., Li, L. K., Li, Q. M., Li, W. Z., Li, Y. B., Liao, Y. P., Libby, J., Lin, J., Lin, S., Liu, M. H., Liu, Q. Y., Liu, Y., Liu, Z. Q., Liventsev, D., Longo, S., Lueck, T., Lyu, C., Ma, Y., Madaan, C., Maggiora, M., Maharana, S. P., Maiti, R., Maity, S., Mancinelli, G., Manfredi, R., Manoni, E., Mantovano, M., Marcantonio, D., Marcello, S., Marinas, C., Martellini, C., Martens, A., Martini, A., Martinov, T., Massaccesi, L., Masuda, M., Matsuda, T., Matvienko, D., Maurya, S. K., Maushart, M., McKenna, J. A., Mehta, R., Meier, F., Meleshko, D., Merola, M., Miller, C., Mirra, M., Mitra, S., Miyabayashi, K., Miyake, H., Mizuk, R., Mohanty, G. B., Mondal, S., Moneta, S., Moser, H. -G., Mussa, R., Nakamura, I., Nakao, M., Nakazawa, Y., Naruki, M., Natkaniec, Z., Natochii, A., Nayak, M., Nazaryan, G., Neu, M., Niebuhr, C., Nishida, S., Ogawa, S., Ono, H., Onuki, Y., Otani, F., Pakhlov, P., Pakhlova, G., Paoloni, E., Pardi, S., Parham, K., Park, H., Park, J., Park, K., Park, S. -H., Paschen, B., Passeri, A., Patra, S., Pedlar, T. K., Peruzzi, I., Peschke, R., Pestotnik, R., Piccolo, M., Piilonen, L. E., Podesta-Lerma, P. L. M., Podobnik, T., Pokharel, S., Praz, C., Prell, S., Prencipe, E., Prim, M. T., Prudiiev, I., Purwar, H., Rados, P., Raeuber, G., Raiz, S., RajG, V., Rauls, N., Ravindran, K., Rehman, J. U., Reif, M., Reiter, S., Remnev, M., Reuter, L., Herrmann, D. Ricalde, Ripp-Baudot, I., Rizzo, G., Roehrken, M., Roney, J. M., Rostomyan, A., Rout, N., Sanders, D. A., Sandilya, S., Santelj, L., Sato, Y., Savinov, V., Scavino, B., Schmitt, C., Schneider, S., Schnepf, M., Schwanda, C., Schwartz, A. J., Seino, Y., Selce, A., Senyo, K., Serrano, J., Sevior, M. E., Sfienti, C., Shan, W., Sharma, C., Shen, C. P., Shi, X. D., Shillington, T., Shimasaki, T., Shiu, J. -G., Shtol, D., Sibidanov, A., Simon, F., Singh, J. B., Skorupa, J., Sobie, R. J., Sobotzik, M., Soffer, A., Sokolov, A., Solovieva, E., Song, W., Spataro, S., Spruck, B., Starič, M., Stavroulakis, P., Stroili, R., Strube, J., Sue, Y., Sumihama, M., Sumisawa, K., Sutcliffe, W., Suwonjandee, N., Svidras, H., Takahashi, M., Takizawa, M., Tamponi, U., Tanida, K., Tenchini, F., Thaller, A., Tittel, O., Tiwary, R., Tonelli, D., Torassa, E., Trabelsi, K., Tsaklidis, I., Uchida, M., Ueda, I., Unger, K., Unno, Y., Uno, K., Uno, S., Urquijo, P., Ushiroda, Y., Vahsen, S. E., van Tonder, R., Varvell, K. E., Veronesi, M., Vismaya, V. S., Vitale, L., Vobbilisetti, V., Volpe, R., Vossen, A., Wakai, M., Wallner, S., Wang, E., Wang, M. -Z., Wang, Z., Warburton, A., Watanabe, M., Watanuki, S., Wessel, C., Won, E., Xu, X. P., Yabsley, B. D., Yamada, S., Yan, W., Yang, S. B., Yelton, J., Yin, J. H., Yoshihara, K., Yuan, J., Zani, L., Zeng, F., Zhang, B., Zhilich, V., Zhou, J. S., Zhou, Q. D., Zhukova, V. I., and Žlebčík, R.
Subjects: High Energy Physics - Experiment
Abstract: We measure the branching fraction and $\it CP$-violating flavor-dependent rate asymmetry of $B^{0} \to \pi^{0} \pi^{0}$ decays reconstructed using the Belle II detector in an electron-positron collision sample containing $387 \times 10^{6}$ $B\overline{B}$ pairs. Using an optimized event selection, we find $126\pm 20$ signal decays in a fit to background-discriminating and flavor-sensitive distributions. The resulting branching fraction is $(1.25 \pm 0.23)\times 10^{-6}$ and the $\it CP$-violating asymmetry is $0.03 \pm 0.30$.
Published: 2024

18. Read Like a Radiologist: Efficient Vision-Language Model for 3D Medical Imaging Interpretation

Author: Lee, Changsun, Park, Sangjoon, Shin, Cheong-Il, Choi, Woo Hee, Park, Hyun Jeong, Lee, Jeong Eun, and Ye, Jong Chul
Subjects: Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computation and Language, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract: Recent medical vision-language models (VLMs) have shown promise in 2D medical image interpretation. However extending them to 3D medical imaging has been challenging due to computational complexities and data scarcity. Although a few recent VLMs specified for 3D medical imaging have emerged, all are limited to learning volumetric representation of a 3D medical image as a set of sub-volumetric features. Such process introduces overly correlated representations along the z-axis that neglect slice-specific clinical details, particularly for 3D medical images where adjacent slices have low redundancy. To address this limitation, we introduce MS-VLM that mimic radiologists' workflow in 3D medical image interpretation. Specifically, radiologists analyze 3D medical images by examining individual slices sequentially and synthesizing information across slices and views. Likewise, MS-VLM leverages self-supervised 2D transformer encoders to learn a volumetric representation that capture inter-slice dependencies from a sequence of slice-specific features. Unbound by sub-volumetric patchification, MS-VLM is capable of obtaining useful volumetric representations from 3D medical images with any slice length and from multiple images acquired from different planes and phases. We evaluate MS-VLM on publicly available chest CT dataset CT-RATE and in-house rectal MRI dataset. In both scenarios, MS-VLM surpasses existing methods in radiology report generation, producing more coherent and clinically relevant reports. These findings highlight the potential of MS-VLM to advance 3D medical image interpretation and improve the robustness of medical VLMs.
Published: 2024

19. Observation of the decay $B^0 \to J/\psi \omega$ at Belle II

Author: Belle II Collaboration, Adachi, I., Aggarwal, L., Ahmed, H., Aihara, H., Akopov, N., Alhakami, M., Aloisio, A., Althubiti, N., Ky, N. Anh, Asner, D. M., Atmacan, H., Aushev, V., Aversano, M., Ayad, R., Babu, V., Baghel, N. K., Bahinipati, S., Bambade, P., Banerjee, Sw., Barrett, M., Baudot, J., Baur, A., Beaubien, A., Becker, J., Bennett, J. V., Bertacchi, V., Bertemes, M., Bertholet, E., Bessner, M., Bettarini, S., Bhuyan, B., Bianchi, F., Biswas, D., Bobrov, A., Bodrov, D., Bolz, A., Bondar, A., Borah, J., Boschetti, A., Bozek, A., Bračko, M., Branchini, P., Brenny, N., Briere, R. A., Browder, T. E., Budano, A., Bussino, S., Campagna, Q., Campajola, M., Casarosa, G., Cecchi, C., Cerasoli, J., Chang, M. -C., Cheaib, R., Cheema, P., Chen, C., Cheon, B. G., Chilikin, K., Chirapatpimol, K., Cho, H. -E., Cho, K., Cho, S. -J., Choi, S. -K., Choudhury, S., Cochran, J., Corona, L., Cui, J. X., De La Cruz-Burelo, E., De La Motte, S. A., de Marino, G., De Nardo, G., De Pietro, G., de Sangro, R., Destefanis, M., Dey, S., Di Canto, A., Di Capua, F., Dingfelder, J., Doležal, Z., Jiménez, I. Domínguez, Dong, T. V., Dong, X., Dorigo, M., Dossett, D., Dugic, K., Dujany, G., Ecker, P., Epifanov, D., Eppelt, J., Feichtinger, P., Ferber, T., Fillinger, T., Finck, C., Finocchiaro, G., Fodor, A., Forti, F., Fulsom, B. G., Gabrielli, A., Ganiev, E., Garcia-Hernandez, M., Gaudino, G., Gaur, V., Gaz, A., Gellrich, A., Ghevondyan, G., Ghosh, D., Ghumaryan, H., Giakoustidis, G., Giordano, R., Giri, A., Gironell, P. Gironella, Glazov, A., Gobbo, B., Godang, R., Gogota, O., Goldenzweig, P., Gradl, W., Graziani, E., Greenwald, D., Gruberová, Z., Guan, Y., Gudkova, K., Haide, I., Harris, C., Hayasaka, K., Hayashii, H., Hazra, S., Hedges, M. T., Heidelbach, A., de la Cruz, I. Heredia, Villanueva, M. Hernández, Higuchi, T., Hoek, M., Hohmann, M., Hoppe, R., Horak, P., Hsu, C. -L., Humair, T., Iijima, T., Inami, K., Ipsita, N., Ishikawa, A., Itoh, R., Iwasaki, M., Jacobi, D., Jacobs, W. W., Jang, E. -J., Jin, Y., Johnson, A., Junkerkalefeld, H., Kalita, D., Kaliyar, A. B., Kandra, J., Karyan, G., Kawasaki, T., Keil, F., Ketter, C., Kiesling, C., Kim, C. -H., Kim, D. Y., Kim, J. -Y., Kim, K. -H., Kim, Y. -K., Kinoshita, K., Kodyš, P., Koga, T., Kohani, S., Kojima, K., Korobov, A., Korpar, S., Kovalenko, E., Kowalewski, R., Križan, P., Krokovny, P., Kuhr, T., Kulii, Y., Kumar, R., Kumara, K., Kunigo, T., Kuzmin, A., Kwon, Y. -J., Lacaprara, S., Lalwani, K., Lam, T., Lanceri, L., Lange, J. S., Lau, T. S., Laurenza, M., Leboucher, R., Diberder, F. R. Le, Lee, M. J., Lemettais, C., Leo, P., Li, L. K., Li, Q. M., Li, W. Z., Li, Y., Li, Y. B., Liao, Y. P., Libby, J., Lin, J., Lin, S., Liu, M. H., Liu, Q. Y., Liu, Z. Q., Liventsev, D., Longo, S., Lueck, T., Luo, T., Lyu, C., Ma, Y., Madaan, C., Maggiora, M., Maharana, S. P., Maiti, R., Mancinelli, G., Manfredi, R., Manoni, E., Mantovano, M., Marcantonio, D., Marcello, S., Marinas, C., Martellini, C., Martens, A., Martini, A., Martinov, T., Massaccesi, L., Masuda, M., Matsuoka, K., Matvienko, D., Maurya, S. K., Maushart, M., McKenna, J. A., Meier, F., Meleshko, D., Merola, M., Miller, C., Mirra, M., Mitra, S., Miyabayashi, K., Miyake, H., Mohanty, G. B., Mondal, S., Moneta, S., Moser, H. -G., Mussa, R., Nakamura, I., Nakao, M., Nakazawa, H., Nakazawa, Y., Naruki, M., Natkaniec, Z., Natochii, A., Nayak, M., Nazaryan, G., Neu, M., Nishida, S., Ogawa, S., Ono, H., Onuki, Y., Pakhlova, G., Pardi, S., Park, H., Park, J., Park, K., Park, S. -H., Passeri, A., Patra, S., Pedlar, T. K., Peruzzi, I., Peschke, R., Pestotnik, R., Piilonen, L. E., Podesta-Lerma, P. L. M., Podobnik, T., Pokharel, S., Praz, C., Prell, S., Prencipe, E., Prim, M. T., Prudiiev, I., Purwar, H., Raiz, S., Ravindran, K., Rehman, J. U., Reif, M., Reiter, S., Remnev, M., Reuter, L., Herrmann, D. Ricalde, Ripp-Baudot, I., Rizzo, G., Roehrken, M., Roney, J. M., Rostomyan, A., Sanders, D. A., Sandilya, S., Santelj, L., Savinov, V., Scavino, B., Schwanda, C., Schwartz, A. J., Seino, Y., Selce, A., Senyo, K., Serrano, J., Sevior, M. E., Sfienti, C., Shan, W., Shi, X. D., Shillington, T., Shimasaki, T., Shiu, J. -G., Shtol, D., Shwartz, B., Sibidanov, A., Simon, F., Skorupa, J., Sobie, R. J., Sobotzik, M., Soffer, A., Sokolov, A., Solovieva, E., Spataro, S., Spruck, B., Song, W., Starič, M., Stavroulakis, P., Stefkova, S., Stroili, R., Strube, J., Sumihama, M., Sumisawa, K., Suwonjandee, N., Svidras, H., Takizawa, M., Tamponi, U., Tanida, K., Tenchini, F., Thaller, A., Tittel, O., Tiwary, R., Torassa, E., Trabelsi, K., Tsaklidis, I., Ueda, I., Uglov, T., Unger, K., Unno, Y., Uno, K., Uno, S., Urquijo, P., Ushiroda, Y., Vahsen, S. E., van Tonder, R., Varvell, K. E., Veronesi, M., Vinokurova, A., Vismaya, V. S., Vitale, L., Vobbilisetti, V., Volpe, R., Wakai, M., Wallner, S., Wang, M. -Z., Warburton, A., Watanabe, M., Watanuki, S., Wessel, C., Won, E., Xu, X. P., Yabsley, B. D., Yamada, S., Yan, W., Yelton, J., Yoshihara, K., Yuan, C. Z., Yuan, J., Yusa, Y., Zani, L., Zhilich, V., Zhou, J. S., Zhou, Q. D., Zhu, L., and Žlebčík, R.
Subjects: High Energy Physics - Experiment
Abstract: We measure the branching fraction of the decay $B^0 \to J/\psi \omega$ using data collected with the Belle II detector at the SuperKEKB collider. The data contain $(387 \pm 6) \times 10^6$ $B\overline{B}$ meson pairs produced in energy-asymmetric $e^+e^-$ collisions at the $\Upsilon (4S)$ resonance. The measured branching fraction $\mathcal{B}(B^0 \to J/\psi \omega) = \left( 2.16 \pm 0.30 \pm 0.14 \right) \times 10^{-5}$, where the first uncertainty is statistical and the second is systematic, is more precise than previous results and constitutes the first observation of the decay with a significance of $6.5$ standard deviations.
Published: 2024

20. Sequence Matters: Harnessing Video Models in 3D Super-Resolution

Author: Ko, Hyun-kyu, Park, Dongheok, Park, Youngin, Lee, Byeonghyeon, Han, Juhee, and Park, Eunbyung
Subjects: Computer Science - Computer Vision and Pattern Recognition, 68U10, 68T10, I.4.5, I.2.10
Abstract: 3D super-resolution aims to reconstruct high-fidelity 3D models from low-resolution (LR) multi-view images. Early studies primarily focused on single-image super-resolution (SISR) models to upsample LR images into high-resolution images. However, these methods often lack view consistency because they operate independently on each image. Although various post-processing techniques have been extensively explored to mitigate these inconsistencies, they have yet to fully resolve the issues. In this paper, we perform a comprehensive study of 3D super-resolution by leveraging video super-resolution (VSR) models. By utilizing VSR models, we ensure a higher degree of spatial consistency and can reference surrounding spatial information, leading to more accurate and detailed reconstructions. Our findings reveal that VSR models can perform remarkably well even on sequences that lack precise spatial alignment. Given this observation, we propose a simple yet practical approach to align LR images without involving fine-tuning or generating 'smooth' trajectory from the trained 3D models over LR images. The experimental results show that the surprisingly simple algorithms can achieve the state-of-the-art results of 3D super-resolution tasks on standard benchmark datasets, such as the NeRF-synthetic and MipNeRF-360 datasets. Project page: https://ko-lani.github.io/Sequence-Matters, Comment: Project page: https://ko-lani.github.io/Sequence-Matters
Published: 2024

21. EditSplat: Multi-View Fusion and Attention-Guided Optimization for View-Consistent 3D Scene Editing with 3D Gaussian Splatting

Author: Lee, Dong In, Park, Hyeongcheol, Seo, Jiyoung, Park, Eunbyung, Park, Hyunje, Baek, Ha Dam, Sangheon, Shin, kim, Sangmin, and Kim, Sangpil
Subjects: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence
Abstract: Recent advancements in 3D editing have highlighted the potential of text-driven methods in real-time, user-friendly AR/VR applications. However, current methods rely on 2D diffusion models without adequately considering multi-view information, resulting in multi-view inconsistency. While 3D Gaussian Splatting (3DGS) significantly improves rendering quality and speed, its 3D editing process encounters difficulties with inefficient optimization, as pre-trained Gaussians retain excessive source information, hindering optimization. To address these limitations, we propose \textbf{EditSplat}, a novel 3D editing framework that integrates Multi-view Fusion Guidance (MFG) and Attention-Guided Trimming (AGT). Our MFG ensures multi-view consistency by incorporating essential multi-view information into the diffusion process, leveraging classifier-free guidance from the text-to-image diffusion model and the geometric properties of 3DGS. Additionally, our AGT leverages the explicit representation of 3DGS to selectively prune and optimize 3D Gaussians, enhancing optimization efficiency and enabling precise, semantically rich local edits. Through extensive qualitative and quantitative evaluations, EditSplat achieves superior multi-view consistency and editing quality over existing methods, significantly enhancing overall efficiency.
Published: 2024

22. Observations of the singly Cabibbo-suppressed decays $\Xi_c^{+} \to pK_{S}^{0}$, $\Xi_c^+ \to \Lambda \pi^+$, and $\Xi_c^+ \to \Sigma^{0} \pi^+$ at Belle and Belle II

Author: Belle, Collaborations, Belle II, Adachi, I., Aggarwal, L., Akopov, N., Alhakami, M., Aloisio, A., Althubiti, N., Ky, N. Anh, Asner, D. M., Atmacan, H., Aushev, T., Aushev, V., Aversano, M., Ayad, R., Babu, V., Baghel, N. K., Bahinipati, S., Bambade, P., Banerjee, Sw., Barrett, M., Baudot, J., Baur, A., Beaubien, A., Becker, J., Bennett, J. V., Bertacchi, V., Bertemes, M., Bertholet, E., Bessner, M., Bettarini, S., Bhuyan, B., Bianchi, F., Biswas, D., Bobrov, A., Bodrov, D., Bolz, A., Bondar, A., Borah, J., Boschetti, A., Bozek, A., Branchini, P., Briere, R. A., Browder, T. E., Budano, A., Bussino, S., Campagna, Q., Campajola, M., Casarosa, G., Cecchi, C., Cerasoli, J., Chang, M. -C., Cheaib, R., Cheema, P., Chilikin, K., Chirapatpimol, K., Cho, H. -E., Cho, K., Cho, S. -J., Choi, S. -K., Choudhury, S., Corona, L., Cui, J. X., De La Cruz-Burelo, E., De La Motte, S. A., De Nardo, G., De Pietro, G., de Sangro, R., Destefanis, M., Dey, S., Di Canto, A., Di Capua, F., Dingfelder, J., Doležal, Z., Jiménez, I. Domínguez, Dong, T. V., Dorigo, M., Dossett, D., Dugic, K., Dujany, G., Ecker, P., Epifanov, D., Feichtinger, P., Ferber, T., Fillinger, T., Finocchiaro, G., Forti, F., Fulsom, B. G., Gabrielli, A., Garcia-Hernandez, M., Gaudino, G., Gaur, V., Gaz, A., Gellrich, A., Ghevondyan, G., Ghosh, D., Ghumaryan, H., Giakoustidis, G., Giordano, R., Giri, A., Gironell, P. Gironella, Gobbo, B., Godang, R., Gogota, O., Goldenzweig, P., Gradl, W., Graziani, E., Greenwald, D., Gruberová, Z., Gudkova, K., Haide, I., Harris, C., Hayashii, H., Heidelbach, A., de la Cruz, I. Heredia, Villanueva, M. Hernández, Higuchi, T., Hoek, M., Hohmann, M., Hoppe, R., Horak, P., Humair, T., Iijima, T., Inami, K., Ipsita, N., Ishikawa, A., Itoh, R., Iwasaki, M., Jacobi, D., Jacobs, W. W., Jaffe, D. E., Jang, E. -J., Jin, Y., Johnson, A., Junkerkalefeld, H., Kaleta, M., Kaliyar, A. B., Kandra, J., Karyan, G., Kawasaki, T., Keil, F., Ketter, C., Kiesling, C., Kim, C. -H., Kim, D. Y., Kim, J. -Y., Kim, K. -H., Kim, Y. -K., Kinoshita, K., Kodyš, P., Koga, T., Kohani, S., Kojima, K., Korobov, A., Korpar, S., Kovalenko, E., Kowalewski, R., Križan, P., Krokovny, P., Kuhr, T., Kulii, Y., Kumar, R., Kumara, K., Kunigo, T., Kuzmin, A., Kwon, Y. -J., Lacaprara, S., Lalwani, K., Lam, T., Lanceri, L., Lange, J. S., Lau, T. S., Laurenza, M., Leboucher, R., Diberder, F. R. Le, Lee, M. J., Leo, P., Li, L. K., Li, Q. M., Li, W. Z., Li, Y., Li, Y. B., Liao, Y. P., Libby, J., Lin, J., Liu, M. H., Liu, Q. Y., Liu, Z. Q., Liventsev, D., Longo, S., Lueck, T., Lyu, C., Ma, Y., Madaan, C., Maggiora, M., Maiti, R., Mancinelli, G., Manfredi, R., Mantovano, M., Marcantonio, D., Marcello, S., Marinas, C., Martellini, C., Martens, A., Martinov, T., Massaccesi, L., Masuda, M., Matvienko, D., Maushart, M., McKenna, J. A., Meier, F., Meleshko, D., Merola, M., Miller, C., Mirra, M., Mitra, S., Miyake, H., Moneta, S., Moser, H. -G., Mussa, R., Nakamura, I., Nakao, M., Nakazawa, Y., Naruki, M., Natkaniec, Z., Natochii, A., Nayak, M., Nazaryan, G., Neu, M., Nishida, S., Ogawa, S., Ono, H., Onuki, Y., Pakhlova, G., Pardi, S., Park, H., Park, J., Park, K., Park, S. -H., Patra, S., Pedlar, T. K., Peruzzi, I., Peschke, R., Pestotnik, R., Piilonen, L. E., Podobnik, T., Pokharel, S., Praz, C., Prell, S., Prencipe, E., Prim, M. T., Purwar, H., Raiz, S., Ravindran, K., Rehman, J. U., Reif, M., Reiter, S., Remnev, M., Reuter, L., Herrmann, D. Ricalde, Ripp-Baudot, I., Rizzo, G., Roehrken, M., Roney, J. M., Rostomyan, A., Sanders, D. A., Sandilya, S., Santelj, L., Savinov, V., Scavino, B., Schnell, G., Schwanda, C., Seino, Y., Selce, A., Senyo, K., Serrano, J., Sevior, M. E., Sfienti, C., Shan, W., Shen, C. P., Shi, X. D., Shillington, T., Shimasaki, T., Shiu, J. -G., Shtol, D., Sibidanov, A., Simon, F., Skorupa, J., Sobie, R. J., Sobotzik, M., Soffer, A., Sokolov, A., Solovieva, E., Spataro, S., Spruck, B., Song, W., Starič, M., Stavroulakis, P., Stroili, R., Sumihama, M., Suwonjandee, N., Svidras, H., Takizawa, M., Tamponi, U., Tanida, K., Tenchini, F., Thaller, A., Tittel, O., Torassa, E., Trabelsi, K., Tsaklidis, I., Ueda, I., Unger, K., Unno, Y., Uno, K., Uno, S., Urquijo, P., Ushiroda, Y., Vahsen, S. E., van Tonder, R., Varvell, K. E., Veronesi, M., Vismaya, V. S., Vitale, L., Vobbilisetti, V., Volpe, R., Wallner, S., Wang, M. -Z., Warburton, A., Watanabe, M., Watanuki, S., Wessel, C., Won, E., Xu, X. P., Yabsley, B. D., Yamada, S., Yan, W., Yoshihara, K., Yuan, C. Z., Yuan, J., Yusa, Y., Zani, L., Zhilich, V., Zhou, J. S., Zhou, Q. D., Zhu, L., and Žlebčík, R.
Subjects: High Energy Physics - Experiment, High Energy Physics - Phenomenology
Abstract: Using data samples of 983.0~$\rm fb^{-1}$ and 427.9~$\rm fb^{-1}$ accumulated with the Belle and Belle~II detectors operating at the KEKB and SuperKEKB asymmetric-energy $e^+e^-$ colliders, singly Cabibbo-suppressed decays $\Xi_c^{+} \to pK_{S}^{0}$, $\Xi_c^+ \to \Lambda \pi^+$, and $\Xi_c^+ \to \Sigma^{0} \pi^+$ are observed for the first time. The ratios of branching fractions of $\Xi_{c}^{+}\to p K_{S}^{0}$, $\Xi_{c}^{+}\to \Lambda \pi^{+}$, and $\Xi_{c}^{+}\to \Sigma^{0} \pi^{+}$ relative to that of $\Xi_c^+ \to \Xi^- \pi^{+} \pi^{+}$ are measured to be \begin{equation} \frac{{\cal B}(\Xi_c^+ \to pK_S^0)}{{\cal B}(\Xi_c^{+} \to \Xi^{-} \pi^+ \pi^+)} = (2.47 \pm 0.16 \pm 0.07)\% \notag, \end{equation} \begin{equation} \frac{{\cal B}(\Xi_c^+ \to \Lambda \pi^+)}{{\cal B}(\Xi_c^{+} \to \Xi^{-} \pi^+ \pi^+)} = (1.56 \pm 0.14 \pm 0.09)\% \notag, \end{equation} \begin{equation} \frac{{\cal B}(\Xi_c^+ \to \Sigma^0 \pi^+)}{{\cal B}(\Xi_c^{+} \to \Xi^{-} \pi^+ \pi^+)} = (4.13 \pm 0.26 \pm 0.22)\% \notag. \end{equation} Multiplying these values by the branching fraction of the normalization channel, ${\cal B}(\Xi_c^{+} \to \Xi^{-} \pi^+\pi^+) = (2.9 \pm 1.3)\%$, the absolute branching fractions are determined to be \begin{equation} {\cal B}(\Xi_c^{+} \to p K_{S}^{0}) = (7.16 \pm 0.46 \pm 0.20 \pm 3.21) \times 10^{-4} \notag, \end{equation} \begin{equation} {\cal B}(\Xi_c^{+} \to \Lambda \pi^+) = (4.52 \pm 0.41 \pm 0.26 \pm 2.03) \times 10^{-4} \notag, \end{equation} \begin{equation} {\cal B}(\Xi_c^{+} \to \Sigma^0 \pi^+) = (1.20 \pm 0.08 \pm 0.07 \pm 0.54) \times 10^{-3} \notag. \end{equation} The first and second uncertainties above are statistical and systematic, respectively, while the third ones arise from the uncertainty in ${\cal B}(\Xi_c^{+} \to \Xi^{-} \pi^{+} \pi^{+})$., Comment: 21 pages, 5 pages
Published: 2024

23. Long-lived quantum correlation by cavity-mediated subradiance

Author: Kim, Kyu-Young, Lee, Jin Hee, Jeon, Woong Bae, Park, Dong Hyun, Park, Suk In, Song, Jin Dong, Lee, Changhyoup, and Kim, Je-Hyung
Subjects: Quantum Physics, Physics - Optics
Abstract: Cooperative effects such as super(sub)radiance in quantum systems arise from the interplay among quantum emitters. While bright superradiant states have been extensively studied and yielded significant insights into cooperative phenomena, subradiant states have remained less explored due to their inherently dark state nature. However, subradiance holds significant potential as valuable quantum resources that exploit long-lived and large-scale entanglement, which is a key for advancing quantum information technologies. Here, we demonstrate a long-lived subradiant state among multiple quantum emitters coupled to a directional low Q cavity. In a tailored photonic environment with balanced cavity dissipation, emitter-field coupling strength, and incoherent pumping, two coupled quantum dots exhibit a steady-state population in a subradiant state with highly negative cooperativity. As an important hallmark of a subradiant state, the system shows large photon bunching (g^((2))(0)>>2) and suppressed single-photon decay. In addition, controlling the excitation wavelength provides a useful tool for manipulating dephasing and the number of coupled emitters, which leads to significant changes in photon statistics. Our approach to inducing cavity-mediated subradiance paves the way for creating and harnessing quantum correlations in quantum emitters via a long-lived entangled quantum state, essential for quantum storage and metrology., Comment: In the manuscript, 16 pages and 4 figures. In supplementary, 6 pages and 7 figures
Published: 2024

24. EXAONE 3.5: Series of Large Language Models for Real-world Use Cases

Author: Research, LG AI, An, Soyoung, Bae, Kyunghoon, Choi, Eunbi, Choi, Kibong, Choi, Stanley Jungkyu, Hong, Seokhee, Hwang, Junwon, Jeon, Hyojin, Jo, Gerrard Jeongwon, Jo, Hyunjik, Jung, Jiyeon, Jung, Yountae, Kim, Hyosang, Kim, Joonkee, Kim, Seonghwan, Kim, Soyeon, Kim, Sunkyoung, Kim, Yireun, Kim, Yongil, Kim, Youchul, Lee, Edward Hwayoung, Lee, Haeju, Lee, Honglak, Lee, Jinsik, Lee, Kyungmin, Lim, Woohyung, Park, Sangha, Park, Sooyoun, Park, Yongmin, Yang, Sihoon, Yeen, Heuiyeen, and Yun, Hyeongu
Subjects: Computer Science - Computation and Language
Abstract: This technical report introduces the EXAONE 3.5 instruction-tuned language models, developed and released by LG AI Research. The EXAONE 3.5 language models are offered in three configurations: 32B, 7.8B, and 2.4B. These models feature several standout capabilities: 1) exceptional instruction following capabilities in real-world scenarios, achieving the highest scores across seven benchmarks, 2) outstanding long-context comprehension, attaining the top performance in four benchmarks, and 3) competitive results compared to state-of-the-art open models of similar sizes across nine general benchmarks. The EXAONE 3.5 language models are open to anyone for research purposes and can be downloaded from https://huggingface.co/LGAI-EXAONE. For commercial use, please reach out to the official contact point of LG AI Research: contact_us@lgresearch.ai., Comment: arXiv admin note: text overlap with arXiv:2408.03541
Published: 2024

25. MetaFormer: High-fidelity Metalens Imaging via Aberration Correcting Transformers

Author: Lee, Byeonghyeon, Kim, Youbin, Jo, Yongjae, Kim, Hyunsu, Park, Hyemi, Kim, Yangkyu, Mandal, Debabrata, Chakravarthula, Praneeth, Kim, Inki, and Park, Eunbyung
Subjects: Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract: Metalens is an emerging optical system with an irreplaceable merit in that it can be manufactured in ultra-thin and compact sizes, which shows great promise of various applications such as medical imaging and augmented/virtual reality (AR/VR). Despite its advantage in miniaturization, its practicality is constrained by severe aberrations and distortions, which significantly degrade the image quality. Several previous arts have attempted to address different types of aberrations, yet most of them are mainly designed for the traditional bulky lens and not convincing enough to remedy harsh aberrations of the metalens. While there have existed aberration correction methods specifically for metalens, they still fall short of restoration quality. In this work, we propose MetaFormer, an aberration correction framework for metalens-captured images, harnessing Vision Transformers (ViT) that has shown remarkable restoration performance in diverse image restoration tasks. Specifically, we devise a Multiple Adaptive Filters Guidance (MAFG), where multiple Wiener filters enrich the degraded input images with various noise-detail balances, enhancing output restoration quality. In addition, we introduce a Spatial and Transposed self-Attention Fusion (STAF) module, which aggregates features from spatial self-attention and transposed self-attention modules to further ameliorate aberration correction. We conduct extensive experiments, including correcting aberrated images and videos, and clean 3D reconstruction from the degraded images. The proposed method outperforms the previous arts by a significant margin. We further fabricate a metalens and verify the practicality of MetaFormer by restoring the images captured with the manufactured metalens in the wild. Code and pre-trained models are available at https://benhenryl.github.io/MetaFormer, Comment: 19 pages, 18 figures
Published: 2024

26. Signatures of Floquet Engineering in the proximal Kitaev Quantum Spin Liquid H$_3$LiIr$_2$O$_6$ by tr-RIXS

Author: Kim, Jungho, Choi, Tae-Kyu, Mercer, Edward, Schmidt, Liam T., Park, Jaeku, Park, Sang-Youn, Jang, Dogeun, Chang, Seo Hyoung, Said, Ayman, Chun, Sae Hwan, Lee, Kyeong Jun, Lee, Sang Wook, Jeong, Hyunjeong, Jeong, Hyeonhui, Lee, Chanhyeon, Choi, Kwang-Yong, Bahrami, Faranak, Tafti, Fazel, Claassen, Martin, and de la Torre, Alberto
Subjects: Condensed Matter - Strongly Correlated Electrons
Abstract: We present the first circularly polarized Floquet engineering time-resolved Resonant Inelastic X-ray Scattering (tr-RIXS) experiment in H$_3$LiIr$_2$O$_6$, an iridium-based Kitaev system. Our calculations and experimental results are consistent with the modification of the low energy magnetic excitations in H$_3$LiIr$_2$O$_6$ only during illumination by the laser pulse, consistent with the Floquet engineering of the exchange interactions. However, the penetration length mismatch between the X-ray probe and laser pump and the intrinsic complexity of Kitaev magnets prevented us from unequivocally extracting towards which ground H$_3$LiIr$_2$O$_6$ was driven. We outline possible solutions to these challenges for Floquet stabilization and observation of the Kitaev Quantum Spin Liquid limit by RIXS.
Published: 2024

27. K-UD: Revising Korean Universal Dependencies Guidelines

Author: Kim, Kyuwon, Chen, Yige, Jo, Eunkyul Leah, Lim, KyungTae, Park, Jungyeul, and Park, Chulwoo
Subjects: Computer Science - Computation and Language
Abstract: Critique has surfaced concerning the existing linguistic annotation framework for Korean Universal Dependencies (UDs), particularly in relation to syntactic relationships. In this paper, our primary objective is to refine the definition of syntactic dependency of UDs within the context of analyzing the Korean language. Our aim is not only to achieve a consensus within UDs but also to garner agreement beyond the UD framework for analyzing Korean sentences using dependency structure, by establishing a linguistic consensus model.
Published: 2024

28. SelfSplat: Pose-Free and 3D Prior-Free Generalizable 3D Gaussian Splatting

Author: Kang, Gyeongjin, Yoo, Jisang, Park, Jihyeon, Nam, Seungtae, Im, Hyeonsoo, Shin, Sangheon, Kim, Sangpil, and Park, Eunbyung
Subjects: Computer Science - Computer Vision and Pattern Recognition
Abstract: We propose SelfSplat, a novel 3D Gaussian Splatting model designed to perform pose-free and 3D prior-free generalizable 3D reconstruction from unposed multi-view images. These settings are inherently ill-posed due to the lack of ground-truth data, learned geometric information, and the need to achieve accurate 3D reconstruction without finetuning, making it difficult for conventional methods to achieve high-quality results. Our model addresses these challenges by effectively integrating explicit 3D representations with self-supervised depth and pose estimation techniques, resulting in reciprocal improvements in both pose accuracy and 3D reconstruction quality. Furthermore, we incorporate a matching-aware pose estimation network and a depth refinement module to enhance geometry consistency across views, ensuring more accurate and stable 3D reconstructions. To present the performance of our method, we evaluated it on large-scale real-world datasets, including RealEstate10K, ACID, and DL3DV. SelfSplat achieves superior results over previous state-of-the-art methods in both appearance and geometry quality, also demonstrates strong cross-dataset generalization capabilities. Extensive ablation studies and analysis also validate the effectiveness of our proposed methods. Code and pretrained models are available at https://gynjn.github.io/selfsplat/, Comment: Project page: https://gynjn.github.io/selfsplat/
Published: 2024

29. VLM-HOI: Vision Language Models for Interpretable Human-Object Interaction Analysis

Author: Kang, Donggoo, Jeong, Dasol, Lee, Hyunmin, Park, Sangwoo, Park, Hasil, Kwon, Sunkyu, Kim, Yeongjoon, and Paik, Joonki
Subjects: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence
Abstract: The Large Vision Language Model (VLM) has recently addressed remarkable progress in bridging two fundamental modalities. VLM, trained by a sufficiently large dataset, exhibits a comprehensive understanding of both visual and linguistic to perform diverse tasks. To distill this knowledge accurately, in this paper, we introduce a novel approach that explicitly utilizes VLM as an objective function form for the Human-Object Interaction (HOI) detection task (\textbf{VLM-HOI}). Specifically, we propose a method that quantifies the similarity of the predicted HOI triplet using the Image-Text matching technique. We represent HOI triplets linguistically to fully utilize the language comprehension of VLMs, which are more suitable than CLIP models due to their localization and object-centric nature. This matching score is used as an objective for contrastive optimization. To our knowledge, this is the first utilization of VLM language abilities for HOI detection. Experiments demonstrate the effectiveness of our method, achieving state-of-the-art HOI detection accuracy on benchmarks. We believe integrating VLMs into HOI detection represents important progress towards more advanced and interpretable analysis of human-object interactions., Comment: 18 pages
Published: 2024

30. Data-driven development of cycle prediction models for lithium metal batteries using multi modal mining

Author: Lee, Jaewoong, Woo, Junhee, Kim, Sejin, Paulina, Cinthya, Park, Hyunmin, Kim, Hee-Tak, Park, Steve, and Kim, Jihan
Subjects: Computer Science - Machine Learning
Abstract: Recent advances in data-driven research have shown great potential in understanding the intricate relationships between materials and their performances. Herein, we introduce a novel multi modal data-driven approach employing an Automatic Battery data Collector (ABC) that integrates a large language model (LLM) with an automatic graph mining tool, Material Graph Digitizer (MatGD). This platform enables state-of-the-art accurate extraction of battery material data and cyclability performance metrics from diverse textual and graphical data sources. From the database derived through the ABC platform, we developed machine learning models that can accurately predict the capacity and stability of lithium metal batteries, which is the first-ever model developed to achieve such predictions. Our models were also experimentally validated, confirming practical applicability and reliability of our data-driven approach., Comment: 30 pages, 7 figures
Published: 2024

31. Engineering superconducting contacts transparent to a bipolar graphene

Author: Jang, Seong, Park, Geon-Hyoung, Park, Sein, Jeong, Hyeon-Woo, Watanabe, Kenji, Taniguchi, Takashi, and Lee, Gil-Ho
Subjects: Condensed Matter - Mesoscale and Nanoscale Physics, Condensed Matter - Superconductivity
Abstract: Graphene's exceptional electronic mobility, gate-tunability, and contact transparency with superconducting materials make it ideal for exploring the superconducting proximity effect. However, the work function difference between graphene and superconductors causes unavoidable doping of graphene near contacts, forming a p-n junction in the hole-doped regime and reducing contact transparency. This challenges the device implementation that exploits graphene's bipolarity. To address this limitation, we developed a new fabrication scheme for two-dimensional superconducting contacts that allows independent control over charge concentration and polarity for both the graphene in contact with superconductors and the graphene channel. Contact transparency, conductance enhancement, and Josephson coupling were measured to confirm transparent contacts to both polarities of graphene. Moreover, we demonstrated the Andreev process in the quantum Hall edge state at a negative filling factor of {\nu} = -2. This scheme will open avenues for realizing various theoretical propositions utilizing the bipolarity of graphene combined with superconductivity., Comment: 20 pages, 10 figures
Published: 2024

32. A Benchmark Dataset for Collaborative SLAM in Service Environments

Author: Park, Harin, Lee, Inha, Kim, Minje, Park, Hyungyu, and Joo, Kyungdon
Subjects: Computer Science - Robotics, Computer Science - Computer Vision and Pattern Recognition
Abstract: As service environments have become diverse, they have started to demand complicated tasks that are difficult for a single robot to complete. This change has led to an interest in multiple robots instead of a single robot. C-SLAM, as a fundamental technique for multiple service robots, needs to handle diverse challenges such as homogeneous scenes and dynamic objects to ensure that robots operate smoothly and perform their tasks safely. However, existing C-SLAM datasets do not include the various indoor service environments with the aforementioned challenges. To close this gap, we introduce a new multi-modal C-SLAM dataset for multiple service robots in various indoor service environments, called C-SLAM dataset in Service Environments (CSE). We use the NVIDIA Isaac Sim to generate data in various indoor service environments with the challenges that may occur in real-world service environments. By using simulation, we can provide accurate and precisely time-synchronized sensor data, such as stereo RGB, stereo depth, IMU, and ground truth (GT) poses. We configure three common indoor service environments (Hospital, Office, and Warehouse), each of which includes various dynamic objects that perform motions suitable to each environment. In addition, we drive three robots to mimic the actions of real service robots. Through these factors, we generate a more realistic C-SLAM dataset for multiple service robots. We demonstrate our dataset by evaluating diverse state-of-the-art single-robot SLAM and multi-robot SLAM methods. Our dataset is available at https://github.com/vision3d-lab/CSE_Dataset., Comment: 8 pages, 6 figures, Accepted to IEEE RA-L
Published: 2024
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33. Forecasting Future International Events: A Reliable Dataset for Text-Based Event Modeling

Author: Gwak, Daehoon, Park, Junwoo, Park, Minho, Park, Chaehun, Lee, Hyunchan, Choi, Edward, and Choo, Jaegul
Subjects: Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract: Predicting future international events from textual information, such as news articles, has tremendous potential for applications in global policy, strategic decision-making, and geopolitics. However, existing datasets available for this task are often limited in quality, hindering the progress of related research. In this paper, we introduce WORLDREP (WORLD Relationship and Event Prediction), a novel dataset designed to address these limitations by leveraging the advanced reasoning capabilities of large-language models (LLMs). Our dataset features high-quality scoring labels generated through advanced prompt modeling and rigorously validated by domain experts in political science. We showcase the quality and utility of WORLDREP for real-world event prediction tasks, demonstrating its effectiveness through extensive experiments and analysis. Furthermore, we publicly release our dataset along with the full automation source code for data collection, labeling, and benchmarking, aiming to support and advance research in text-based event prediction., Comment: EMNLP 2024 Findings
Published: 2024

34. Measurement of the inclusive branching fractions for $B_s^0$ decays into $D$ mesons via hadronic tagging

Author: Belle, Collaborations, Belle II, Adachi, I., Aggarwal, L., Ahmed, H., Aihara, H., Akopov, N., Aloisio, A., Said, S. Al, Althubiti, N., Ky, N. Anh, Asner, D. M., Atmacan, H., Aushev, T., Aushev, V., Aversano, M., Ayad, R., Babu, V., Bae, H., Baghel, N. K., Bahinipati, S., Bambade, P., Banerjee, Sw., Bansal, S., Barrett, M., Bartl, M., Baudot, J., Baur, A., Beaubien, A., Becherer, F., Becker, J., Belous, K., Bennett, J. V., Bernlochner, F. U., Bertacchi, V., Bertemes, M., Bertholet, E., Bessner, M., Bettarini, S., Bhardwaj, V., Bhuyan, B., Bianchi, F., Bierwirth, L., Bilka, T., Biswas, D., Bobrov, A., Bodrov, D., Bolz, A., Bondar, A., Borah, J., Boschetti, A., Bozek, A., Bračko, M., Branchini, P., Briere, R. A., Browder, T. E., Budano, A., Bussino, S., Campagna, Q., Campajola, M., Cao, L., Casarosa, G., Cecchi, C., Cerasoli, J., Chang, M. -C., Chang, P., Cheaib, R., Cheema, P., Cheon, B. G., Chilikin, K., Chirapatpimol, K., Cho, H. -E., Cho, K., Cho, S. -J., Choi, S. -K., Choudhury, S., Cochran, J., Corona, L., Cui, J. X., Dattola, F., De La Cruz-Burelo, E., De La Motte, S. A., De Nardo, G., De Nuccio, M., De Pietro, G., de Sangro, R., Destefanis, M., Dey, S., Dhamija, R., Di Canto, A., Di Capua, F., Dingfelder, J., Doležal, Z., Jiménez, I. Domínguez, Dong, T. V., Dorner, D., Dort, K., Dossett, D., Dreyer, S., Dubey, S., Dugic, K., Dujany, G., Ecker, P., Eliachevitch, M., Epifanov, D., Feichtinger, P., Ferber, T., Fillinger, T., Finck, C., Finocchiaro, G., Fodor, A., Forti, F., Frey, A., Fulsom, B. G., Gabrielli, A., Ganiev, E., Garcia-Hernandez, M., Garg, R., Gaudino, G., Gaur, V., Gellrich, A., Ghevondyan, G., Ghosh, D., Ghumaryan, H., Giakoustidis, G., Giordano, R., Giri, A., Gironell, P. Gironella, Glazov, A., Gobbo, B., Godang, R., Goldenzweig, P., Graziani, E., Greenwald, D., Gruberová, Z., Gu, T., Guan, Y., Gudkova, K., Haide, I., Halder, S., Han, Y., Hara, T., Harris, C., Hayasaka, K., Hayashii, H., Hazra, S., Hedges, M. T., Heidelbach, A., de la Cruz, I. Heredia, Villanueva, M. Hernández, Higuchi, T., Hoek, M., Hohmann, M., Hoppe, R., Horak, P., Hsu, C. -L., Humair, T., Iijima, T., Inami, K., Ipsita, N., Ishikawa, A., Itoh, R., Iwasaki, M., Jackson, P., Jacobs, W. W., Jang, E. -J., Ji, Q. P., Jia, S., Jin, Y., Johnson, A., Joo, K. K., Junkerkalefeld, H., Kaleta, M., Kalita, D., Kaliyar, A. B., Kandra, J., Kang, K. H., Kang, S., Karyan, G., Kawasaki, T., Keil, F., Ketter, C., Kiesling, C., Kim, C. -H., Kim, D. Y., Kim, J. -Y., Kim, K. -H., Kim, Y. -K., Kim, Y. J., Kindo, H., Kinoshita, K., Kodyš, P., Koga, T., Kohani, S., Kojima, K., Korobov, A., Korpar, S., Kovalenko, E., Križan, P., Krokovny, P., Kuhr, T., Kulii, Y., Kumar, D., Kumar, J., Kumar, M., Kumar, R., Kumara, K., Kunigo, T., Kuzmin, A., Kwon, Y. -J., Lacaprara, S., Lalwani, K., Lam, T., Lanceri, L., Lange, J. S., Lau, T. S., Laurenza, M., Lautenbach, K., Leboucher, R., Diberder, F. R. Le, Lee, M. J., Lemettais, C., Leo, P., Levit, D., Lewis, P. M., Li, L. K., Li, Q. M., Li, S. X., Li, W. Z., Li, Y., Li, Y. B., Liao, Y. P., Libby, J., Lin, J., Liptak, Z., Liu, M. H., Liu, Q. Y., Liu, Y., Liu, Z. Q., Liventsev, D., Longo, S., Lueck, T., Lyu, C., Ma, Y., Madaan, C., Maggiora, M., Maharana, S. P., Maiti, R., Maity, S., Mancinelli, G., Manfredi, R., Manoni, E., Mantovano, M., Marcantonio, D., Marcello, S., Marinas, C., Martellini, C., Martens, A., Martini, A., Martinov, T., Massaccesi, L., Masuda, M., Matvienko, D., Maurya, S. K., Maushart, M., McKenna, J. A., Meier, F., Merola, M., Metzner, F., Miller, C., Mirra, M., Mitra, S., Miyabayashi, K., Mizuk, R., Mohanty, G. B., Mondal, S., Moneta, S., Moser, H. -G., Mrvar, M., Mussa, R., Nakamura, I., Nakao, M., Nakazawa, Y., Naruki, M., Natkaniec, Z., Natochii, A., Nayak, M., Nazaryan, G., Neu, M., Niebuhr, C., Niiyama, M., Nishida, S., Ogawa, S., Onishchuk, Y., Ono, H., Onuki, Y., Otani, F., Pakhlov, P., Pakhlova, G., Paoloni, E., Pardi, S., Parham, K., Park, H., Park, J., Park, K., Park, S. -H., Paschen, B., Passeri, A., Patra, S., Paul, S., Pedlar, T. K., Peschke, R., Pestotnik, R., Piccolo, M., Piilonen, L. E., Angioni, G. Pinna, Podesta-Lerma, P. L. M., Podobnik, T., Pokharel, S., Praz, C., Prell, S., Prencipe, E., Prim, M. T., Prudiiev, I., Purwar, H., Rados, P., Raeuber, G., Raiz, S., Rauls, N., Ravindran, K., Rehman, J. U., Reif, M., Reiter, S., Remnev, M., Reuter, L., Herrmann, D. Ricalde, Ripp-Baudot, I., Rizzo, G., Roehrken, M., Roney, J. M., Rostomyan, A., Rout, N., Sanders, D. A., Sandilya, S., Santelj, L., Sato, Y., Savinov, V., Scavino, B., Schmitt, C., Schneider, S., Schnell, G., Schnepf, M., Schwanda, C., Schwartz, A. J., Seino, Y., Selce, A., Senyo, K., Serrano, J., Sevior, M. E., Sfienti, C., Shan, W., Sharma, C., Shen, C. P., Shi, X. D., Shillington, T., Shimasaki, T., Shiu, J. -G., Shtol, D., Sibidanov, A., Simon, F., Singh, J. B., Skorupa, J., Sobotzik, M., Soffer, A., Sokolov, A., Solovieva, E., Song, W., Spataro, S., Spruck, B., Starič, M., Stavroulakis, P., Stefkova, S., Stroili, R., Strube, J., Sue, Y., Sumihama, M., Sumisawa, K., Sutcliffe, W., Suwonjandee, N., Svidras, H., Takahashi, M., Takizawa, M., Tamponi, U., Tanaka, S., Tanida, K., Tenchini, F., Thaller, A., Tittel, O., Tiwary, R., Torassa, E., Trabelsi, K., Tsaklidis, I., Ueda, I., Uglov, T., Unger, K., Unno, Y., Uno, K., Uno, S., Urquijo, P., Ushiroda, Y., Vahsen, S. E., van Tonder, R., Varvell, K. E., Veronesi, M., Vinokurova, A., Vismaya, V. S., Vitale, L., Vobbilisetti, V., Volpe, R., Vossen, A., Wach, B., Wakai, M., Wallner, S., Wang, B., Wang, E., Wang, M. -Z., Wang, X. L., Wang, Z., Warburton, A., Watanabe, M., Watanuki, S., Wessel, C., Wiechczynski, J., Won, E., Xu, X. P., Yabsley, B. D., Yamada, S., Yang, S. B., Yasaveev, M., Yelton, J., Yin, J. H., Yook, Y. M., Yoshihara, K., Yuan, C. Z., Yuan, J., Yusa, Y., Zani, L., Zeng, F., Zhang, B., Zhilich, V., Zhou, J. S., Zhou, Q. D., Zhukova, V. I., and Žlebčík, R.
Subjects: High Energy Physics - Experiment
Abstract: We report measurements of the absolute branching fractions $\mathcal{B}(B_s^0 \to D_s^{\pm} X)$, $\mathcal{B}(B_s^0 \to D^0/\bar{D}^0 X)$, and $\mathcal{B}(B_s^0 \to D^{\pm} X)$, where the latter is measured for the first time. The results are based on a 121.4\,fb$^{-1}$ data sample collected at the $\Upsilon(10860)$ resonance by the Belle detector at the KEKB asymmetric-energy $e^+ e^-$ collider. We reconstruct one $B_s^0$ meson in $e^+e^- \to \Upsilon(10860) \to B_s^{*} \bar{B}_s^{*}$ events and measure yields of $D_s^+$, $D^0$, and $D^+$ mesons in the rest of the event. We obtain $\mathcal{B}(B_s^0 \to D_s^{\pm} X) = (68.6 \pm 7.2 \pm 4.0)\%$, $\mathcal{B}(B_s^0 \to D^0/\bar{D}^0 X) = (21.5 \pm 6.1 \pm 1.8)\%$, and $\mathcal{B}(B_s^0 \to D^{\pm} X) = (12.6 \pm 4.6 \pm 1.3)\%$, where the first uncertainty is statistical and the second is systematic. Averaging with previous Belle measurements gives $\mathcal{B}(B_s^0 \to D_s^{\pm} X) = (63.4 \pm 4.5 \pm 2.2)\%$ and $\mathcal{B}(B_s^0 \to D^0/\bar{D}^0 X) = (23.9 \pm 4.1 \pm 1.8)\%$. For the $B_s^0$ production fraction at the $\Upsilon(10860)$, we find $f_s = (21.4^{+1.5}_{-1.7})\%$., Comment: 23 pages, 9 figures, submitted to JHEP
Published: 2024

35. Production cross sections of light and charmed mesons in $e^+e^-$ annihilation near 10.58 GeV

Author: Belle Collaboration, Seidl, R., Adachi, I., Aihara, H., Aushev, T., Ayad, R., Banerjee, Sw., Belous, K., Bennett, J., Bessner, M., Bhuyan, B., Biswas, D., Bodrov, D., Bračko, M., Branchini, P., Browder, T. E., Budano, A., Campajola, M., Chilikin, K., Cho, K., Choi, S. -K., Choi, Y., Choudhury, S., Das, S., De Nardo, G., De Pietro, G., Di Capua, F., Dingfelder, J., Doležal, Z., Dong, T. V., Dossett, D., Ecker, P., Ferber, T., Fulsom, B. G., Gaur, V., Giri, A., Goldenzweig, P., Graziani, E., Guan, Y., Gudkova, K., Hadjivasiliou, C., Hara, T., Hayashii, H., Herrmann, D., Hou, W. -S., Hsu, C. -L., Inami, K., Ipsita, N., Ishikawa, A., Itoh, R., Iwasaki, M., Jacobs, W. W., Jia, S., Jin, Y., Joo, K. K., Kaliyar, A. B., Kiesling, C., Kim, C. H., Kim, D. Y., Kim, K. -H., Kodyš, P., Korobov, A., Korpar, S., Križan, P., Krokovny, P., Kumar, D., Kumara, K., Kwon, Y. -J., Lam, T., Li, L. K., Li, Y. B., Gioi, L. Li, Libby, J., Liventsev, D., Ma, Y., Masuda, M., Matsuda, T., Matvienko, D., Merola, M., Miyabayashi, K., Mussa, R., Nakao, M., Natochii, A., Niiyama, M., Nishida, S., Ogawa, S., Ono, H., Pakhlova, G., Pardi, S., Park, J., Park, S. -H., Passeri, A., Patra, S., Paul, S., Pedlar, T. K., Pestotnik, R., Piilonen, L. E., Podobnik, T., Prencipe, E., Prim, M. T., Russo, G., Sandilya, S., Santelj, L., Savinov, V., Schnell, G., Schwanda, C., Seino, Y., Senyo, K., Sevior, M. E., Shan, W., Shiu, J. -G., Shwartz, B., Singh, J. B., Solovieva, E., Starič, M., Sumihama, M., Takizawa, M., Tanida, K., Tenchini, F., Uglov, T., Unno, Y., Uno, S., Usov, Y., Van Hulse, C., Vinokurova, A., Vossen, A., Wang, M. -Z., Yabsley, B. D., Yan, W., Yook, Y., Yuan, C. Z., Yuan, L., Zhang, Z. P., and Zhilich, V.
Subjects: High Energy Physics - Experiment
Abstract: We report measurements of production cross sections for $\rho^+$, $\rho^0$, $\omega$, $K^{*+}$, $K^{*0}$, $\phi$, $\eta$, $K_S^0$, $f_0(980)$, $D^+$, $D^0$, $D_s^+$, $D^{*+}$, $D^{*0}$, and $D^{*+}_s$ in $e^+e^-$ collisions at a center-of-mass energy near 10.58 GeV. The data were recorded by the Belle experiment, consisting of 571 fb$^{-1}$ at 10.58 GeV and 74 fb$^{-1}$ at 10.52 GeV. Production cross sections are extracted as a function of the fractional hadron momentum $x_p$ . The measurements are compared to {\sc pythia} Monte Carlo generator predictions with various fragmentation settings, including those that have increased fragmentation into vector mesons over pseudo-scalar mesons. The cross sections measured for light hadrons are consistent with no additional increase of vector over pseudo-scalar mesons. The charmed-meson cross sections are compared to earlier measurements -- when available -- including older Belle results, which they supersede. They are in agreement before application of an improved initial-state radiation correction procedure that causes slight changes in their \xp shapes., Comment: 21 pages, 18 figures, submitted to Phys. Rev. D
Published: 2024

36. IMPaCT GNN: Imposing invariance with Message Passing in Chronological split Temporal Graphs

Author: Park, Sejun, Park, Joo Young, and Park, Hyunwoo
Subjects: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Statistics - Machine Learning
Abstract: This paper addresses domain adaptation challenges in graph data resulting from chronological splits. In a transductive graph learning setting, where each node is associated with a timestamp, we focus on the task of Semi-Supervised Node Classification (SSNC), aiming to classify recent nodes using labels of past nodes. Temporal dependencies in node connections create domain shifts, causing significant performance degradation when applying models trained on historical data into recent data. Given the practical relevance of this scenario, addressing domain adaptation in chronological split data is crucial, yet underexplored. We propose Imposing invariance with Message Passing in Chronological split Temporal Graphs (IMPaCT), a method that imposes invariant properties based on realistic assumptions derived from temporal graph structures. Unlike traditional domain adaptation approaches which rely on unverifiable assumptions, IMPaCT explicitly accounts for the characteristics of chronological splits. The IMPaCT is further supported by rigorous mathematical analysis, including a derivation of an upper bound of the generalization error. Experimentally, IMPaCT achieves a 3.8% performance improvement over current SOTA method on the ogbn-mag graph dataset. Additionally, we introduce the Temporal Stochastic Block Model (TSBM), which replicates temporal graphs under varying conditions, demonstrating the applicability of our methods to general spatial GNNs., Comment: 11 pages (without appendix), 35 pages (with appendix), 14 figures
Published: 2024

37. Measurement of $B \to K{}^{*}(892)\gamma$ decays at Belle II

Author: Belle II Collaboration, Adachi, I., Aggarwal, L., Ahmed, H., Aihara, H., Akopov, N., Aloisio, A., Althubiti, N., Ky, N. Anh, Asner, D. M., Atmacan, H., Aushev, T., Aushev, V., Aversano, M., Ayad, R., Babu, V., Bae, H., Baghel, N. K., Bahinipati, S., Bambade, P., Banerjee, Sw., Bansal, S., Barrett, M., Bartl, M., Baudot, J., Baur, A., Beaubien, A., Becherer, F., Becker, J., Bennett, J. V., Bernlochner, F. U., Bertacchi, V., Bertemes, M., Bertholet, E., Bessner, M., Bettarini, S., Bhardwaj, V., Bhuyan, B., Bianchi, F., Bierwirth, L., Bilka, T., Biswas, D., Bobrov, A., Bodrov, D., Bolz, A., Bondar, A., Borah, J., Boschetti, A., Bozek, A., Bračko, M., Branchini, P., Briere, R. A., Browder, T. E., Budano, A., Bussino, S., Campagna, Q., Campajola, M., Cao, L., Casarosa, G., Cecchi, C., Cerasoli, J., Chang, M. -C., Chang, P., Cheaib, R., Cheema, P., Chen, C., Cheon, B. G., Chilikin, K., Chirapatpimol, K., Cho, H. -E., Cho, K., Cho, S. -J., Choi, S. -K., Choudhury, S., Cochran, J., Corona, L., Cui, J. X., Dattola, F., De La Cruz-Burelo, E., De La Motte, S. A., de Marino, G., De Nardo, G., De Pietro, G., de Sangro, R., Destefanis, M., Dey, S., Dhamija, R., Di Canto, A., Di Capua, F., Dingfelder, J., Doležal, Z., Jiménez, I. Domínguez, Dong, T. V., Dorigo, M., Dort, K., Dossett, D., Dubey, S., Dugic, K., Dujany, G., Ecker, P., Eliachevitch, M., Feichtinger, P., Ferber, T., Fillinger, T., Finck, C., Finocchiaro, G., Fodor, A., Forti, F., Frey, A., Fulsom, B. G., Gabrielli, A., Ganiev, E., Garcia-Hernandez, M., Garg, R., Gaudino, G., Gaur, V., Gaz, A., Gellrich, A., Ghevondyan, G., Ghosh, D., Ghumaryan, H., Giakoustidis, G., Giordano, R., Giri, A., Gironell, P. Gironella, Glazov, A., Gobbo, B., Godang, R., Gogota, O., Goldenzweig, P., Gradl, W., Graziani, E., Greenwald, D., Gruberová, Z., Gu, T., Guan, Y., Gudkova, K., Haide, I., Halder, S., Han, Y., Hara, T., Harris, C., Hayasaka, K., Hayashii, H., Hazra, S., Hearty, C., Hedges, M. T., Heidelbach, A., de la Cruz, I. Heredia, Villanueva, M. Hernández, Higuchi, T., Hoek, M., Hohmann, M., Hoppe, R., Horak, P., Hsu, C. -L., Humair, T., Iijima, T., Inami, K., Ipsita, N., Ishikawa, A., Itoh, R., Iwasaki, M., Jackson, P., Jacobs, W. W., Jang, E. -J., Jia, S., Jin, Y., Johnson, A., Joo, K. K., Junkerkalefeld, H., Kaleta, M., Kalita, D., Kaliyar, A. B., Kandra, J., Kang, K. H., Kang, S., Karyan, G., Kawasaki, T., Keil, F., Ketter, C., Kiesling, C., Kim, C. -H., Kim, D. Y., Kim, J. -Y., Kim, K. -H., Kim, Y. -K., Kim, Y. J., Kindo, H., Kinoshita, K., Kodyš, P., Koga, T., Kohani, S., Kojima, K., Korobov, A., Korpar, S., Kovalenko, E., Kowalewski, R., Križan, P., Krokovny, P., Kuhr, T., Kulii, Y., Kumar, D., Kumar, M., Kumara, K., Kunigo, T., Kuzmin, A., Kwon, Y. -J., Lacaprara, S., Lai, Y. -T., Lalwani, K., Lam, T., Lanceri, L., Lange, J. S., Lau, T. S., Laurenza, M., Leboucher, R., Diberder, F. R. Le, Lee, M. J., Lemettais, C., Leo, P., Levit, D., Lewis, P. M., Li, C., Li, L. K., Li, Q. M., Li, S. X., Li, W. Z., Li, Y., Li, Y. B., Liao, Y. P., Libby, J., Lin, J., Liptak, Z., Liu, M. H., Liu, Q. Y., Liu, Y., Liu, Z. Q., Liventsev, D., Longo, S., Lyu, C., Ma, Y., Madaan, C., Maggiora, M., Maharana, S. P., Maiti, R., Maity, S., Mancinelli, G., Manfredi, R., Manoni, E., Mantovano, M., Marcantonio, D., Marcello, S., Marinas, C., Martellini, C., Martens, A., Martini, A., Martinov, T., Massaccesi, L., Masuda, M., Matsuda, T., Matsuoka, K., Matvienko, D., Maurya, S. K., Maushart, M., McKenna, J. A., Mehta, R., Meier, F., Merola, M., Metzner, F., Miller, C., Mirra, M., Mitra, S., Miyabayashi, K., Mizuk, R., Mohanty, G. B., Mondal, S., Moneta, S., Moser, H. -G., Mrvar, M., Mussa, R., Nakamura, I., Nakao, M., Nakazawa, Y., Naruki, M., Natkaniec, Z., Natochii, A., Nayak, M., Nazaryan, G., Neu, M., Niebuhr, C., Niiyama, M., Nishida, S., Ogawa, S., Onishchuk, Y., Ono, H., Onuki, Y., Otani, F., Pakhlov, P., Pakhlova, G., Paoloni, E., Pardi, S., Parham, K., Park, H., Park, J., Park, K., Park, S. -H., Paschen, B., Passeri, A., Patra, S., Paul, S., Pedlar, T. K., Peruzzi, I., Peschke, R., Pestotnik, R., Piccolo, M., Piilonen, L. E., Angioni, G. Pinna, Podesta-Lerma, P. L. M., Podobnik, T., Pokharel, S., Praz, C., Prell, S., Prencipe, E., Prim, M. T., Prudiiev, I., Purwar, H., Rados, P., Raeuber, G., Raiz, S., Rauls, N., Ravindran, K., Rehman, J. U., Reif, M., Reiter, S., Remnev, M., Reuter, L., Herrmann, D. Ricalde, Ripp-Baudot, I., Rizzo, G., Robertson, S. H., Roehrken, M., Roney, J. M., Rostomyan, A., Rout, N., Sanders, D. A., Sandilya, S., Santelj, L., Sato, Y., Savinov, V., Scavino, B., Schmitt, C., Schneider, S., Schnepf, M., Schwanda, C., Schwartz, A. J., Seino, Y., Selce, A., Senyo, K., Serrano, J., Sevior, M. E., Sfienti, C., Shan, W., Sharma, C., Shen, C. P., Shi, X. D., Shillington, T., Shimasaki, T., Shiu, J. -G., Shtol, D., Shwartz, B., Sibidanov, A., Simon, F., Singh, J. B., Skorupa, J., Sobie, R. J., Sobotzik, M., Soffer, A., Sokolov, A., Solovieva, E., Song, W., Spataro, S., Spruck, B., Starič, M., Stavroulakis, P., Stefkova, S., Stroili, R., Strube, J., Sue, Y., Sumihama, M., Sumisawa, K., Sutcliffe, W., Suwonjandee, N., Svidras, H., Takahashi, M., Takizawa, M., Tamponi, U., Tanida, K., Tenchini, F., Thaller, A., Tittel, O., Tiwary, R., Torassa, E., Trabelsi, K., Tsaklidis, I., Ueda, I., Uglov, T., Unger, K., Unno, Y., Uno, K., Uno, S., Urquijo, P., Ushiroda, Y., Vahsen, S. E., van Tonder, R., Varvell, K. E., Veronesi, M., Vinokurova, A., Vismaya, V. S., Vitale, L., Vobbilisetti, V., Volpe, R., Vossen, A., Wach, B., Wakai, M., Wallner, S., Wang, E., Wang, M. -Z., Wang, X. L., Wang, Z., Warburton, A., Watanabe, M., Watanuki, S., Wessel, C., Won, E., Xu, X. P., Yabsley, B. D., Yamada, S., Yan, W., Yang, S. B., Yelton, J., Yin, J. H., Yook, Y. M., Yoshihara, K., Yuan, C. Z., Yuan, J., Zani, L., Zeng, F., Zhang, B., Zhilich, V., Zhou, J. S., Zhou, Q. D., Zhukova, V. I., and Žlebčík, R.
Subjects: High Energy Physics - Experiment
Abstract: We present measurements of $B \to K{}^{*}(892)\gamma$ decays using $365\,{\rm fb}^{-1}$ of data collected from 2019 to 2022 by the Belle~II experiment at the SuperKEKB asymmetric-energy $e^+e^-$ collider. The data sample contains $(387 \pm 6) \times 10^6$ $B\overline{B}$ events. We measure branching fractions ($\mathcal{B}$) and $C\!P$ asymmetries ($\mathcal{A}_{C\!P}$) for both $B^{0}\to K{}^{*0}\gamma$ and $B^{+}\to K{}^{*+}\gamma$ decays. The difference in $C\!P$ asymmetries ($\Delta \mathcal{A}_{C\!P}$) and the isospin asymmetry ($\Delta_{0+}$) between these neutral and charged channels are also measured. We obtain the following branching fractions and $C\!P$ asymmetries: $\mathcal{B} (B^{0} \to K{}^{*0}\gamma) = (4.14 \pm 0.10 \pm 0.11 ) \times 10^{-5}$, $\mathcal{B} (B^{+} \to K{}^{*+}\gamma) = (4.02 \pm 0.13 \pm 0.13 )\times 10^{-5}$, $\mathcal{A}_{C\!P} (B^{0} \to K{}^{*0}\gamma) = (-3.3 \pm 2.3 \pm 0.4 )\%$, and $\mathcal{A}_{C\!P} (B^{+} \to K{}^{*+}\gamma) = (-0.7 \pm 2.9 \pm 0.6 )\%$. The measured difference in $C\!P$ asymmetries is $\Delta \mathcal{A}_{C\!P} = (+2.6 \pm 3.8 \pm 0.7 )\%$, and the measured isospin asymmetry is $\Delta_{0+} = (+5.0 \pm 2.0 \pm 1.5 )\%$. The first uncertainties listed are statistical and the second are systematic. These results are consistent with world-average values and theory predictions.
Published: 2024

38. Polarized Superradiance from CsPbBr3 Quantum Dot Superlattice with Controlled Inter-dot Electronic Coupling

Author: Luo, Lanyin, Tang, Xueting, Park, Junhee, Wang, Chih-Wei, Park, Mansoo, Khurana, Mohit, Singh, Ashutosh, Cheon, Jinwoo, Belyanin, Alexey, Sokolov, Alexei V., and Son, Dong Hee
Subjects: Condensed Matter - Mesoscale and Nanoscale Physics, Physics - Optics
Abstract: Cooperative emission of photons from an ensemble of quantum dots (QDs) as superradiance can arise from the electronically coupled QDs with a coherent emitting excited state. This contrasts with superfluorescence (Dicke superradiance), where the cooperative photon emission occurs via a spontaneous buildup of coherence in an ensemble of incoherently excited QDs via their coupling to a common radiation mode. While superfluorescence has been observed in perovskite QD systems, reports of superradiance from the electronically coupled ensemble of perovskite QDs are rare. Here, we demonstrate the generation of polarized superradiance with a very narrow linewidth (<5 meV) and a large redshift (~200 meV) from the electronically coupled CsPbBr3 QD superlattice achieved through a combination of strong quantum confinement and ligand engineering. In addition to photon bunching at low excitation densities, the superradiance is polarized in contrast to the uncoupled exciton emission from the same superlattice. This finding suggests the potential for obtaining polarized cooperative photon emission via anisotropic electronic coupling in QD superlattices even when the intrinsic anisotropy of exciton transition in individual QDs is weak.
Published: 2024

39. Magnetic field control over the axialness of Higgs modes in charge-density wave compounds

Author: Wulferding, Dirk, Park, Jongho, Tohyama, Takami, Park, Seung Ryong, and Kim, Changyoung
Subjects: Condensed Matter - Strongly Correlated Electrons, Condensed Matter - Materials Science
Abstract: Understanding how symmetry-breaking processes generate order out of disorder is among the most fundamental problems of nature. The scalar Higgs mode - a massive (quasi-) particle - is a key ingredient in these processes and emerges with the spontaneous breaking of a continuous symmetry. Its related exotic and elusive axial counterpart, a Boson with vector character, can be stabilized through the simultaneous breaking of multiple continuous symmetries. Here, we employ a magnetic field to tune the recently discovered axial Higgs-type charge-density wave amplitude modes in rare-earth tritellurides. We demonstrate a proportionality between the axial Higgs component and the applied field, and a 90$^{\circ}$ phase shift upon changing the direction of the B-field. This indicates that the axial character is directly related to magnetic degrees of freedom. Our approach opens up an in-situ control over the axialness of emergent Higgs modes.
Published: 2024
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40. VISTA: Visual Integrated System for Tailored Automation in Math Problem Generation Using LLM

Author: Lee, Jeongwoo, Park, Kwangsuk, and Park, Jihyeon
Subjects: Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition
Abstract: Generating accurate and consistent visual aids is a critical challenge in mathematics education, where visual representations like geometric shapes and functions play a pivotal role in enhancing student comprehension. This paper introduces a novel multi-agent framework that leverages Large Language Models (LLMs) to automate the creation of complex mathematical visualizations alongside coherent problem text. Our approach not only simplifies the generation of precise visual aids but also aligns these aids with the problem's core mathematical concepts, improving both problem creation and assessment. By integrating multiple agents, each responsible for distinct tasks such as numeric calculation, geometry validation, and visualization, our system delivers mathematically accurate and contextually relevant problems with visual aids. Evaluation across Geometry and Function problem types shows that our method significantly outperforms basic LLMs in terms of text coherence, consistency, relevance and similarity, while maintaining the essential geometrical and functional integrity of the original problems. Although some challenges remain in ensuring consistent visual outputs, our framework demonstrates the immense potential of LLMs in transforming the way educators generate and utilize visual aids in math education., Comment: Accepted at NeurIPS 2024 Workshop on Large Foundation Models for Educational Assessment (FM-Assess)
Published: 2024

41. Hierarchical Visual Feature Aggregation for OCR-Free Document Understanding

Author: Park, Jaeyoo, Choi, Jin Young, Park, Jeonghyung, and Han, Bohyung
Subjects: Computer Science - Computer Vision and Pattern Recognition
Abstract: We present a novel OCR-free document understanding framework based on pretrained Multimodal Large Language Models (MLLMs). Our approach employs multi-scale visual features to effectively handle various font sizes within document images. To address the increasing costs of considering the multi-scale visual inputs for MLLMs, we propose the Hierarchical Visual Feature Aggregation (HVFA) module, designed to reduce the number of input tokens to LLMs. Leveraging a feature pyramid with cross-attentive pooling, our approach effectively manages the trade-off between information loss and efficiency without being affected by varying document image sizes. Furthermore, we introduce a novel instruction tuning task, which facilitates the model's text-reading capability by learning to predict the relative positions of input text, eventually minimizing the risk of truncated text caused by the limited capacity of LLMs. Comprehensive experiments validate the effectiveness of our approach, demonstrating superior performance in various document understanding tasks., Comment: NeurIPS 2024
Published: 2024

42. Programmable photonic unitary circuits for light computing

Author: Kim, Kyuho, Park, Kunwoo, Park, Hyungchul, Yu, Sunkyu, Park, Namkyoo, and Piao, Xianji
Subjects: Physics - Optics
Abstract: Unitarity serves as a fundamental concept for characterizing linear and conservative wave phenomena in both classical and quantum systems. Developing platforms that perform unitary operations on light waves in a uni-versal and programmable manner enables the emulation of complex light-matter interactions and the execution of general-purpose functionalities for wave manipulations, photonic computing, and quantum circuits. Recent-ly, numerous approaches to implementing programmable photonic unitary circuits have been proposed and demonstrated, each employing different design strategies that distinctly impact overall device performance. Here, we review foundational design principles and recent achievements in the implementation of programma-ble photonic unitary circuits, with a particular focus on integrated photonic platforms. We classify the design strategies based on the dimensionality of nontrivial unit operations in their building blocks: lower-dimensional unitary units, such as SU(2) operations, and higher-dimensional ones, such as Fourier transforms. In each cate-gory, recent efforts to leverage alternative physical axes, such as the temporal and frequency domains, to ad-dress scalability challenges are also reviewed. We discuss the underlying concepts, design procedures, and trade-offs of each design strategy, especially in relation to light-based computing., Comment: 22 pages, 7 figures
Published: 2024

43. The Hitchhiker's Guide to Programming and Optimizing CXL-Based Heterogeneous Systems

Author: Wang, Zixuan, Mahar, Suyash, Li, Luyi, Park, Jangseon, Kim, Jinpyo, Michailidis, Theodore, Pan, Yue, Rosing, Tajana, Tullsen, Dean, Swanson, Steven, Ryoo, Kyung Chang, Park, Sungjoo, and Zhao, Jishen
Subjects: Computer Science - Performance, Computer Science - Hardware Architecture, Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Operating Systems
Abstract: We present a thorough analysis of the use of CXL-based heterogeneous systems. We built a cluster of server systems that combines different vendor's CPUs and various types of CXL devices. We further developed a heterogeneous memory benchmark suite, Heimdall, to profile the performance of such heterogeneous systems. By leveraging Heimdall, we unveiled the detailed architecture design in these systems, drew observations on optimizing performance for workloads, and pointed out directions for future development of CXL-based heterogeneous systems.
Published: 2024

44. Accelerating Multi-UAV Collaborative Sensing Data Collection: A Hybrid TDMA-NOMA-Cooperative Transmission in Cell-Free MIMO Networks

Author: Park, Eunhyuk, Kim, Junbeom, Park, Seok-Hwan, Simeone, Osvaldo, and Shamai, Shlomo
Subjects: Electrical Engineering and Systems Science - Signal Processing, Computer Science - Information Theory
Abstract: This work investigates a collaborative sensing and data collection system in which multiple unmanned aerial vehicles (UAVs) sense an area of interest and transmit images to a cloud server (CS) for processing. To accelerate the completion of sensing missions, including data transmission, the sensing task is divided into individual private sensing tasks for each UAV and a common sensing task that is executed by all UAVs to enable cooperative transmission. Unlike existing studies, we explore the use of an advanced cell-free multiple-input multiple-output (MIMO) network, which effectively manages inter-UAV interference. To further optimize wireless channel utilization, we propose a hybrid transmission strategy that combines time-division multiple access (TDMA), non-orthogonal multiple access (NOMA), and cooperative transmission. The problem of jointly optimizing task splitting ratios and the hybrid TDMA-NOMA-cooperative transmission strategy is formulated with the objective of minimizing mission completion time. Extensive numerical results demonstrate the effectiveness of the proposed task allocation and hybrid transmission scheme in accelerating the completion of sensing missions., Comment: This work has been accepted for publication in the IEEE Internet of Things Journal
Published: 2024

45. Wiedemann-Franz Law and Thermoelectric Inequalities: Effective ZT and Single-leg Efficiency Overestimation

Author: Ryu, Byungki, Oh, Seunghyun, Demeke, Wabi, Chung, Jaywan, Park, Jongho, Kumari, Nirma, Wani, Aadil Fayaz, Ryu, Seunghwa, and Park, SuDong
Subjects: Physics - Applied Physics, Condensed Matter - Materials Science, Mathematical Physics
Abstract: We derive a thermoelectric inequality in thermoelectric conversion between the material figure of merit (ZT) and the module effective ZT using the Constant Seebeck-coefficient Approximation combining with the Wiedemann-Franz law. In a P-N leg-pair module, the effective ZT lies between the individual ZT values of the P- and N-legs. In a single-leg module, however, the effective ZT is less than approximately one-third of the leg's ZT. This reduction results from the need for an external wire to complete the circuit, introducing additional thermal and electrical losses. Multi-dimensional numerical analysis shows that, although structural optimization can mitigate these losses, the system efficiency remains limited to below half of the ideal single-leg material efficiency. Our findings explain the single-leg efficiency overestimation and highlight the importance of optimizing the P-N leg-pair module structure. They also underscore the need for thermoelectric leg-compatibility, particularly with respect to Seebeck coefficients., Comment: (main) 17 pages, 1 table, 3 figures, 15 references (all including Supporting Materials) 24 pages, 2 supporting tables, 2 supporting figures
Published: 2024

46. The Role of Emergency Financial Relief Funding in Improving Low-Income Students' Academic and Financial Outcomes across Demographic Characteristics. EdWorkingPaper No. 24-991

Author: Annenberg Institute for School Reform at Brown University, Bradley R. Curs, Casandra E. Harper, and Sangmin Park
Abstract: This quasi-experimental study examined the effectiveness of a one-time emergency financial relief program among Pell Grant eligible undergraduate students in Spring 2015 pursuing their first bachelor's degree across academic and financial outcomes. The academic outcomes included retention to the next semester, degree completion, attempted credit hours, and grade point average. The financial outcome captured whether students received a stop registration hold due to an unpaid financial balance in the semester after receiving the emergency relief. The results reveal that financial relief applied to low-income students' accounts can improve their retention and graduation rates. The financial relief was most effective among first-generation college students, resulting in a complete elimination of the retention gap for first-generation students. The emergency relief did not improve GPA or substantially change the number of credits earned. A concerning finding was that students receiving this emergency support were more likely to receive a financial hold in a subsequent semester and that effect was stronger among students of color (Black/African American, Hispanic/Latine, Asian, Multiracial, American Indian/Alaska Native), males, and first-generation college students.
Published: 2024

47. A Teaching Practicum Model for Constructing Cogenerative Dialogue amongst Preservice Teachers to Improve Science Teaching

Author: Steven Newman and Meredith Park Rogers
Abstract: The specific focus of this study is how a team of four preservice teachers experienced a collaborative practicum model to support the development of cogenerative dialogue and foster professional growth. Data sources included individual video club annotations and the associated group discussions facilitated by comparison of groups members selected annotations. The analysis found that participation in peer collaboration provided multiple viewpoints of shared teaching experiences that enabled preservice teachers' different ways to notice student thinking. Providing a structured framework for reflection, namely the individual video club annotations, served as the genesis for cogenerative dialogues centered on instructional change for the preservice teachers. This work's implications showcase the importance of allowing for the iterative enactment and reflection on pedagogical choices by preservice teachers early in their professional development.
Published: 2024

48. Exploring the Relationship between Test-Optional Admissions and Selectivity and Enrollment Outcomes during the Pandemic. EdWorkingPaper No. 24-982

Author: Annenberg Institute for School Reform at Brown University, Kelly Rosinger, Dominique J. Baker, Joseph Sturm, Wan Yu, Julie J. Park, OiYan Poon, Brian Heseung Kim, and Stephanie Breen
Abstract: Most selective colleges implemented test-optional admissions during the pandemic, making college entrance exam scores optional for applicants. We draw on descriptive, two-way fixed effects, and event study methods to examine variation in test-optional implementation during the pandemic and how implementation relates to selectivity and enrollment. For "test-optional" colleges during the pandemic, we found substantial variation in policy type (e.g., test optional, test free) and whether the policy extended to all applicants and scholarship consideration. Findings suggest test-optional implementation related to increases in Black student enrollment, mostly at moderately selective colleges and when policies extended to all applicants and scholarships. At highly selective colleges, findings suggest test-optional implementation related to an increase in applications but not consistent gains in enrollment.
Published: 2024

49. Reconceptualizing Quality Early Care and Education with Equity at the Center. Occasional Paper Series 51

Author: Bank Street College of Education, Mark Nagasawa, Cristina Medellin-Paz, Helen Frazier, Contributor, Virginia Dearani, Contributor, Charis-Ann Sole, Contributor, M. Nalani Mattox-Primacio, Contributor, Shin Ae Han, Contributor, Soyoung Park, Contributor, Sunmin Lee, Contributor, Nnenna Odim, Contributor, Jennifer Keys Adair, Contributor, Angie Zapata, Contributor, Mary Adu-Gyamfi, Contributor, Adrianna González Ybarra, Contributor, Seung Eun McDevitt, Contributor, Louella Sween, Contributor, Vanessa Rodriguez, Contributor, Mark Nagasawa, Cristina Medellin-Paz, Helen Frazier, Contributor, Virginia Dearani, Contributor, Charis-Ann Sole, Contributor, M. Nalani Mattox-Primacio, Contributor, Shin Ae Han, Contributor, Soyoung Park, Contributor, Sunmin Lee, Contributor, Nnenna Odim, Contributor, Jennifer Keys Adair, Contributor, Angie Zapata, Contributor, Mary Adu-Gyamfi, Contributor, Adrianna González Ybarra, Contributor, Seung Eun McDevitt, Contributor, Louella Sween, Contributor, Vanessa Rodriguez, Contributor, and Bank Street College of Education
Abstract: Issue 51 of the Bank Street Occasional Papers Series "Reconceptualizing Quality Early Care and Education with Equity at the Center" is a response to Gunilla Dahlberg, Peter Moss, and Alan Pence's 25-year interrogation of the concept of quality in early childhood education (ECE) (Dahlberg et al., 1999, 2013, 2023). Their groundbreaking work has called early childhood educators to question deeply held assumptions about the universality of childhood and how these shape the standardization of practices in early childhood settings around the world. While quality is typically conceived of as existing primarily in classrooms, the authors in Issue 51 remind readers that the small world of ECE exists within oppressive systems imbued with intersecting racism, classism, sexism, and ableism, and that, therefore, a beyond quality praxis requires nurturing and supporting educators through partnerships (recognizing that resilience is social), developing political commitments and orientations through relationships, and mobilizing these relationships for collective action towards liberatory alternatives. The idea for this issue, which is a part of a broader project to identify and analyze promising, equity-committed early childhood policies and practices, emerged over the past few years.
Published: 2024

50. Approaching the quantum-limited precision in frequency-comb-based spectral interferometry for length measurements

Author: Jang, Yoon-Soo, Ahn, Heulbi, Eom, Sunghoon, Park, Jungjae, and Jin, Jonghan
Subjects: Physics - Optics, Physics - Instrumentation and Detectors
Abstract: Over the last two decades, frequency combs have brought breakthroughs in length metrology with traceability to length standards. In particular, frequency-comb-based spectral interferometry is regarded as a promising technology for next-generation length standards. However, to achieve this, the nanometer-level precision inherent in laser interferometer is required. Here, we report distance measurements by a frequency-comb-based spectral interferometry with sub-nm precision close to a standard quantum limit. The measurement precision was confirmed as 0.67 nm at an averaging time of 25 us. The measurement sensitivity was found to be 4.5 10-12m/Hz1/2, close to the quantum-limit. As a practical example of observing precise physical phenomena, we demonstrated measurements of acoustic-wave-induced vibration and laser eavesdropping. Our study will be an important step toward the practical realization of upcoming length standards.
Published: 2025

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