667,010 results on '"A. Basu"'
Search Results
52. Join BASU for their first ever Uno Tournament!
- Author
-
Jimenez, Rosalia
- Subjects
News, opinion and commentary ,Sports and fitness - Abstract
Byline: Rosalia Jimenez On Wednesday, Nov. 20, GRCC's Black Africana Student Union will be hosting their first ever Uno tournament. The tournament is being held in the Applied Technology Center [...]
- Published
- 2024
53. Armed policing faces crisis of confidence after Chris Kaba case, warns former terror chief; Mistrust is building among the public and within the force itself, says Neil Basu, after Sgt Martyn Blake was acquitted of murder
- Subjects
Law enforcement -- Cases ,Murder -- Cases ,Terrorist organizations -- Cases ,Company legal issue ,General interest ,News, opinion and commentary - Abstract
Byline: Alex Barton, Nick Gutteridge, Chief Political Correspondent There is a crisis of confidence in armed policing after the Chris Kaba case, a former counter-terror chief has said. Sgt Martyn [...]
- Published
- 2024
54. Corporate information: SHOPPERS STOP LTD. - 532638 - Disclosure Under Regulation 30 Of SEBI LODR Update With Respect To Disclosure Ref No. SEC|66|2024-25 Dated July 25, 2024, Intimating The Resignation Of Ms. Shwetal Basu As Customer Care Associate, Chief Marketing And Communication Officer. (Update on 11-09-24)
- Subjects
Shoppers Stop Ltd. -- Customer relations -- Officials and employees -- Laws, regulations and rules ,Securities law ,Department stores -- Officials and employees -- Customer relations ,Disclosure of information -- Laws, regulations and rules ,Customer relations -- Laws, regulations and rules ,Marketing -- Laws, regulations and rules ,Government regulation ,General interest ,News, opinion and commentary - Abstract
Mumbai: SHOPPERS STOP LTD. - 532638 - Disclosure Under Regulation 30 Of SEBI LODR Update With Respect To Disclosure Ref No. SEC/66/2024-25 Dated July 25, 2024, Intimating The Resignation Of [...]
- Published
- 2024
55. Strategies of Resistance in The City Inside by Samit Basu.
- Author
-
Marino, Elisabetta
- Subjects
HOME detention ,COMEDIANS ,FAKE news ,CLIMATE change ,NARRATION ,TELEVISION comedies - Abstract
A filmmaker, a novelist, a short-story author, and a comics writer, Samit Basu has acquired mainstream popularity thanks to House Arrest, a Netflix comedy broadcast in 2019. By focusing on The City Inside (2022), an antidystopic novel, this article sets out to investigate the strategies employed by the writer to tackle and challenge the main issues that affect current-day India (as well as many other countries in the world), namely social and religious inequalities, fundamentalisms, different forms of governmental control, fake news, and climate change. Set in Delhi in 2030, the narrative was written in the wake of the protests against the Citizenship Amendment Act (12 December 2019), which discriminated against the Muslim (and other) minorities. The writer does not seem to aim at providing readers with a mere cautionary tale: the India he portrays is too realistic to be purely fictional. As this article will demonstrate, resistance to power comes hand in hand with awareness and independent thinking, which are exactly what the author wishes to stimulate. [ABSTRACT FROM AUTHOR]
- Published
- 2023
56. Novel UiO-NH2‑like Zr-Based MOF (Basu-DPU) as an Excellent Catalyst for Preparation of New 6H‑Chromeno[4,3‑b]quinolin-6-ones.
- Author
-
Beiranvand, Masoumeh, Habibi, Davood, and Khodakarami, Hosein
- Published
- 2023
- Full Text
- View/download PDF
57. Atrangii App Elevates Nivedita Basu to Senior Vice President Group
- Subjects
Executives ,Advertising, marketing and public relations - Abstract
Byline: Adgully Bureau Atrangii App, much loved Hindi OTT helmed by media baron Vibhu Agarwal, has elevated Nivedita Basu to Senior Vice President Group. Earlier Nivedita was the Vice President [...]
- Published
- 2024
58. Former UK counter-terror lead criticises Priti Patel's 'divisive' comments; Neil Basu says former home secretary's remarks about two-tier policing are laughable and put officers' safety at risk
- Subjects
Law enforcement -- Safety and security measures ,Antiterrorism measures -- Safety and security measures ,News, opinion and commentary - Abstract
Byline: Sammy Gecsoyler The former head of UK counter-terrorism has accused Priti Patel of putting officers at risk after the Tory leadership hopeful made 'divisive' comments about two-tier policing. Since [...]
- Published
- 2024
59. Worst far-right violence should be treated as terrorism, says ex-police chief; Neil Basu, former head of UK counter-terrorism, condemned the weekend's rioters as 'bullies and cowards'UK politics live -- latest updates
- Subjects
Refugees ,Bullying ,Looting ,Terrorism ,Riots ,Hotels and motels -- United Kingdom -- United States ,Holiday Inn Express - Published
- 2024
60. Former counter-terror chief accuses Farage of inciting Southport violence; Neil Basu says Reform UK leader is 'creating conspiracy theories' by questioning whether truth is being 'withheld'
- Subjects
Murder ,Violence ,Antiterrorism measures ,Conspiracy theories ,Terrorist organizations ,News, opinion and commentary - Abstract
Byline: Ben Quinn, Vikram Dodd and Rowena Mason A former counter-terrorism police chief has accused Nigel Farage of helping incite violence that broke out in Southport after the killing of [...]
- Published
- 2024
61. 'Cosmopolitan Sensibility... the Best Way to Describe Me': An Interview with Kunal Basu
- Author
-
Sanchari Mitra and Jati Sankar Mondal
- Subjects
interview ,Kunal Basu ,Language and Literature - Published
- 2019
- Full Text
- View/download PDF
62. Authors' reply to Mondal et al. and Basu et al.
- Author
-
Shreya Shukla, Ujjwal Agarwal, and Abhishek Mahajan
- Subjects
Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Published
- 2023
- Full Text
- View/download PDF
63. Partition as Oedipal Tragedy A Conversation between Bratya Basu and Milinda Banerjee.
- Author
-
Banerjee, Milinda
- Subjects
- *
DRAMATISTS , *GREEK mythology ,PARTITION of India, 1947 - Abstract
The article present an interview with playwright and director & Minister of Education of the Indian state of West Bengal, India, Bratya Basu. It discusses about Basu's play "Hridipash," which adapts Sophocles' play Oedipus Rex to explore the tragedy of the Partition of India in 1947; historical context of Greek tragedy in colonial India; significance of adapting Greek myths to convey contemporary political and social themes; and the interplay between memory, fate and the building of a polity.
- Published
- 2023
- Full Text
- View/download PDF
64. A method to predict vortex shedding response based on Vickery and Basu model: A proposal for the new Brazilian Wind Code
- Author
-
Grala, Pedro, Loredo-Souza, Acir Mércio, and Rocha, Marcelo Maia
- Published
- 2019
- Full Text
- View/download PDF
65. Best of Dhiren Basu.
- Author
-
Basu, Dhiren, performer
- Published
- 1999
66. Digital touchpoint, hyperlocal travel, sustainability driving travel industry:Arindam Basu
- Subjects
Sustainable development ,Travel industry -- Marketing ,Marketing ,Company marketing practices ,Advertising, marketing and public relations - Abstract
Byline: Priya Lalwani Deltin, a leading brand in the hospitality, entertainment, and gaming industry, has announced the 'Tenniversary' of its iconic property - Deltin Royale, located in Goa. To make [...]
- Published
- 2023
67. Presenting a Sustainable Model of Basu Conservatism Using the GMM-sys Method
- Author
-
Farhad Fallahnezhad, Hossien Fakhari, and Shahriar Zaroki
- Subjects
conservatism ,basu model ,share market ,book value ,dynamic method ,Accounting. Bookkeeping ,HF5601-5689 ,Finance ,HG1-9999 - Abstract
To explain the estimation of conservatism as a limiting covenant in accounting, the current paper discussed Basu (1997) conservatism model and Nichols (2010) generalized conservatism model and examined the problems about these models as regards the validity and generalizability of the results of the research on this topic .Accordingly, the discussed problems were explained and the solutions for solving these problems and upgrading the model to estimate conservatism were presented. The data from 2006 to 2016 on 87 corporations were used to carry out the investigations. Also, in addition to the static routine estimator, the dynamic panel estimator (the GMM-sys method) was used to test and estimate the models. The current research results revealed that the new modified conservatism estimation model yielded more appropriate results than the original Basu model and Nichols generalized model. Moreover, it indicated that the dynamic method of model estimation is more suitable than the static one. Finally, the current research showed that the results of the previous research conducted using Basu model to measure conservatism should be considered more cautiously and their application in the capital markets calls for re-examination
- Published
- 2018
- Full Text
- View/download PDF
68. Malika Basu, History of Indigenous Pharmaceutical Companies in Colonial Calcutta (1855-1947)
- Author
-
Marine Bellégo
- Subjects
Social Sciences - Published
- 2022
- Full Text
- View/download PDF
69. Arindam Basu joins Poovayya & Co as a Partner in Corporate Advisory team
- Subjects
Foreign investments ,Law - Abstract
Byline: Bar & Bench Basu has extensive experience in advising on M&A, PE/VC transactions, foreign investments and strategic collaborations. Arindam Basu has joined Poovayya & Co as a Partner in [...]
- Published
- 2023
70. Effects of Ni-Doping in CuMn2O4 Spinel Coatings for Interconnects in Solid Oxide Fuel Cells: Effects of Ni-Doping in CuMn2O4 Spinel Coatings for Interconnects in Solid Oxide Fuel Cells: Zhu, Sun, Gopalan, Pal, Hussain, Dale, Furuya, and Basu
- Author
-
Zhu, Zhikuan, Sun, Zhihao, Gopalan, Srikanth, Pal, Uday B., Hussain, A. Mohammed, Dale, Nilesh, Furuya, Yoshihisa, and Basu, Soumendra N.
- Subjects
SOLID oxide fuel cells ,PROTECTIVE coatings ,DIFFUSION barriers ,ELECTRIC conductivity ,DOPING agents (Chemistry) - Abstract
Chromium (Cr) poisoning from metallic interconnects is a significant issue that impairs the performance of solid oxide fuel cells (SOFCs). Employing doped spinel coatings as a protective layer on interconnects has proven to be a successful mitigation strategy for Cr poisoning. This study examines three different nickel (Ni) doping levels in CuMn
2 O4 spinel to determine the most effective doping content. The compositions explored were CuNi0.2 Mn1.8 O4 , CuNi0.4 Mn1.6 O4 , and CuNi0.6 Mn1.4 O4 . Results indicate that Ni doping enhances the phase stability and electrical conductivity and reduces Cr diffusion in the CuMn2 O4 spinel. Notably, CuNi0.2 Mn1.8 O4 demonstrated best overall performance, exhibiting the highest electrical conductivity of 94–103 S/cm in the 700–800°C range, forming the densest coating layer, and exhibiting the strongest diffusion barrier to Cr migration. Thus, CuNi0.2 Mn1.8 O4 is identified as the optimally Ni-doped Cu-Mn spinel coating. [ABSTRACT FROM AUTHOR]- Published
- 2025
- Full Text
- View/download PDF
71. A density power divergence measure to discriminate between generalized exponential and Weibull distributions: A density power divergence...: S. Basu, H. K. T. Ng.
- Author
-
Basu, Suparna and Ng, Hon Keung Tony
- Abstract
Discriminating two similar candidate statistical models for a given data set based on the conventional ratio of maximized likelihood values has been studied extensively in the literature. The problem of model discrimination becomes more complicated when the candidate models resemble each other closely for a certain region in the parametric space, with only a handful of different characteristics that are difficult to extract or identify from a given data set. The conventional method may fail to provide conclusive discriminatory evidence toward either model for such cases. In this paper, a novel discrimination criterion based on the density power divergence is proposed for model discrimination between the generalized exponential distribution and the Weibull distribution. Along with the discriminating procedure, asymptotic properties of the associated discriminating statistic are discussed. A Monte Carlo simulation study is used to evaluate the performance of the proposed model discrimination method and compare it with the ratio of the maximized likelihood method under different scenarios with and without contamination. A numerical example is presented to illustrate the proposed model discrimination method developed here. [ABSTRACT FROM AUTHOR]
- Published
- 2025
- Full Text
- View/download PDF
72. From Basu-Harvey to Nahm equation via 3-Lie bialgebra
- Author
-
Aali-Javanangrouh, M. and Rezaei-Aghdam, A.
- Subjects
High Energy Physics - Theory - Abstract
Using the concept of 3-Lie bialgebra; we construct the Bagger- Lambert- Gustavson (BLG) model on the Manin triple $\cal D$ of the especial 3-Lie bialgebra $({\cal D},{\cal A}_{\cal G},{\cal A}_{{\cal G}^*}^*)$ which is in correspondence with Manin triple of Lie bialgebra $({\cal D},{\cal G},{\cal G}^*)$. We have shown that the Nahm equation (with Lie bialgebra ${\cal G}$) can be obtained from the Basu-Harvey equation as a boundary condition of BLG model (with 3-Lie bialgebra ${\cal D}$) and vice versa., Comment: 7 pages. Two references are added
- Published
- 2016
73. R2D2: Remembering, Reflecting and Dynamic Decision Making for Web Agents
- Author
-
Huang, Tenghao, Basu, Kinjal, Abdelaziz, Ibrahim, Kapanipathi, Pavan, May, Jonathan, and Chen, Muhao
- Subjects
Computer Science - Artificial Intelligence - Abstract
The proliferation of web agents necessitates advanced navigation and interaction strategies within complex web environments. Current models often struggle with efficient navigation and action execution due to limited visibility and understanding of web structures. Our proposed R2D2 framework addresses these challenges by integrating two paradigms: Remember and Reflect. The Remember paradigm utilizes a replay buffer that aids agents in reconstructing the web environment dynamically, thus enabling the formulation of a detailed ``map'' of previously visited pages. This helps in reducing navigational errors and optimizing the decision-making process during web interactions. Conversely, the Reflect paradigm allows agents to learn from past mistakes by providing a mechanism for error analysis and strategy refinement, enhancing overall task performance. We evaluate R2D2 using the WEBARENA benchmark, demonstrating significant improvements over existing methods, including a 50% reduction in navigation errors and a threefold increase in task completion rates. Our findings suggest that a combination of memory-enhanced navigation and reflective learning promisingly advances the capabilities of web agents, potentially benefiting various applications such as automated customer service and personal digital assistants.
- Published
- 2025
74. Physics-informed deep learning for infectious disease forecasting
- Author
-
Qian, Ying, Marty, Éric, Basu, Avranil, O'Dea, Eamon B., Wang, Xianqiao, Fox, Spencer, Rohani, Pejman, Drake, John M., and Li, He
- Subjects
Computer Science - Machine Learning ,Quantitative Biology - Quantitative Methods - Abstract
Accurate forecasting of contagious illnesses has become increasingly important to public health policymaking, and better prediction could prevent the loss of millions of lives. To better prepare for future pandemics, it is essential to improve forecasting methods and capabilities. In this work, we propose a new infectious disease forecasting model based on physics-informed neural networks (PINNs), an emerging area of scientific machine learning. The proposed PINN model incorporates dynamical systems representations of disease transmission into the loss function, thereby assimilating epidemiological theory and data using neural networks (NNs). Our approach is designed to prevent model overfitting, which often occurs when training deep learning models with observation data alone. In addition, we employ an additional sub-network to account for mobility, vaccination, and other covariates that influence the transmission rate, a key parameter in the compartment model. To demonstrate the capability of the proposed model, we examine the performance of the model using state-level COVID-19 data in California. Our simulation results show that predictions of PINN model on the number of cases, deaths, and hospitalizations are consistent with existing benchmarks. In particular, the PINN model outperforms the basic NN model and naive baseline forecast. We also show that the performance of the PINN model is comparable to a sophisticated Gaussian infection state space with time dependence (GISST) forecasting model that integrates the compartment model with a data observation model and a regression model for inferring parameters in the compartment model. Nonetheless, the PINN model offers a simpler structure and is easier to implement. Our results show that the proposed forecaster could potentially serve as a new computational tool to enhance the current capacity of infectious disease forecasting.
- Published
- 2025
75. Complex Structure around a Circumstellar Disk Caused by Interchange Instability
- Author
-
Machida, Masahiro N. and Basu, Shantanu
- Subjects
Astrophysics - Solar and Stellar Astrophysics ,Astrophysics - Astrophysics of Galaxies - Abstract
We perform a three-dimensional nonideal magnetohydrodynamic simulation of a strongly magnetized cloud core and investigate the complex structure caused by the interchange instability. This is the first simulation that does not use a central sink cell and calculates the long term ($> 10^4$ yr) evolution even as the disk and outflow formation occur. The magnetic field dissipates inside the disk, and magnetic flux accumulates around the edge of the disk, leading to the occurrence of interchange instability. During the main accretion phase, the interchange instability occurs recurrently, disturbing the circumstellar region and forming ring, arc, and cavity structures. These are consistent with recent high-resolution observations of circumstellar regions around young protostars. The structures extend to $>1,000$ au and persist for at least 30,000 yr after protostar formation, demonstrating the dynamic removal process of magnetic flux during star formation. We find that the disk continues to grow even as interchange instability occurs, by accretion through channels between the outgoing cavities. The outflow is initially weak, but becomes strong after $\sim 10^3$ yr., Comment: Accepted for publication in ApJL
- Published
- 2025
76. Search for neutrino doublets and triplets using 11.4 years of IceCube data
- Author
-
Abbasi, R., Ackermann, M., Adams, J., Agarwalla, S. K., Aguilar, J. A., Ahlers, M., Alameddine, J. M., Amin, N. M., Andeen, K., Argüelles, C., Ashida, Y., Athanasiadou, S., Axani, S. N., Babu, R., Bai, X., V., A. Balagopal, Baricevic, M., Barwick, S. W., Bash, S., Basu, V., Bay, R., Beatty, J. J., Tjus, J. Becker, Beise, J., Bellenghi, C., BenZvi, S., Berley, D., Bernardini, E., Besson, D. Z., Blaufuss, E., Bloom, L., Blot, S., Bontempo, F., Motzkin, J. Y. Book, Meneguolo, C. Boscolo, Böser, S., Botner, O., Böttcher, J., Braun, J., Brinson, B., Brisson-Tsavoussis, Z., Brostean-Kaiser, J., Brusa, L., Burley, R. T., Butterfield, D., Campana, M. A., Caracas, I., Carloni, K., Carpio, J., Chattopadhyay, S., Chau, N., Chen, Z., Chirkin, D., Choi, S., Clark, B. A., Coleman, A., Coleman, P., Collin, G. H., Connolly, A., Conrad, J. M., Corley, R., Cowen, D. F., De Clercq, C., DeLaunay, J. J., Delgado, D., Deng, S., Desai, A., Desiati, P., de Vries, K. D., de Wasseige, G., DeYoung, T., Diaz, A., Díaz-Vélez, J. C., Dierichs, P., Dittmer, M., Domi, A., Draper, L., Dujmovic, H., Durnford, D., Dutta, K., DuVernois, M. A., Ehrhardt, T., Eidenschink, L., Eimer, A., Eller, P., Ellinger, E., Mentawi, S. El, Elsässer, D., Engel, R., Erpenbeck, H., Esmail, W., Evans, J., Evenson, P. A., Fan, K. L., Fang, K., Farrag, K., Fazely, A. R., Fedynitch, A., Feigl, N., Fiedlschuster, S., Finley, C., Fischer, L., Fox, D., Franckowiak, A., Fukami, S., Fürst, P., Gallagher, J., Ganster, E., Garcia, A., Garcia, M., Garg, G., Genton, E., Gerhardt, L., Ghadimi, A., Girard-Carillo, C., Glaser, C., Glüsenkamp, T., Gonzalez, J. G., Goswami, S., Granados, A., Grant, D., Gray, S. J., Griffin, S., Griswold, S., Groth, K. M., Guevel, D., Günther, C., Gutjahr, P., Ha, C., Haack, C., Hallgren, A., Halve, L., Halzen, F., Hamacher, L., Hamdaoui, H., Minh, M. Ha, Handt, M., Hanson, K., Hardin, J., Harnisch, A. A., Hatch, P., Haungs, A., Häußler, J., Helbing, K., Hellrung, J., Hermannsgabner, J., Heuermann, L., Heyer, N., Hickford, S., Hidvegi, A., Hill, C., Hill, G. C., Hmaid, R., Hoffman, K. D., Hori, S., Hoshina, K., Hostert, M., Hou, W., Huber, T., Hultqvist, K., Hünnefeld, M., Hussain, R., Hymon, K., Ishihara, A., Iwakiri, W., Jacquart, M., Jain, S., Janik, O., Jansson, M., Jeong, M., Jin, M., Jones, B. J. P., Kamp, N., Kang, D., Kang, W., Kang, X., Kappes, A., Kappesser, D., Kardum, L., Karg, T., Karl, M., Karle, A., Katil, A., Katz, U., Kauer, M., Kelley, J. L., Khanal, M., Zathul, A. Khatee, Kheirandish, A., Kiryluk, J., Klein, S. R., Kobayashi, Y., Kochocki, A., Koirala, R., Kolanoski, H., Kontrimas, T., Köpke, L., Kopper, C., Koskinen, D. J., Koundal, P., Kowalski, M., Kozynets, T., Krieger, N., Krishnamoorthi, J., Krishnan, T., Kruiswijk, K., Krupczak, E., Kumar, A., Kun, E., Kurahashi, N., Lad, N., Gualda, C. Lagunas, Lamoureux, M., Larson, M. J., Lauber, F., Lazar, J. P., DeHolton, K. Leonard, Leszczyńska, A., Liao, J., Lincetto, M., Liu, Y. T., Liubarska, M., Love, C., Lu, L., Lucarelli, F., Luszczak, W., Lyu, Y., Madsen, J., Magnus, E., Mahn, K. B. M., Makino, Y., Manao, E., Mancina, S., Mand, A., Sainte, W. Marie, Mariş, I. C., Marka, S., Marka, Z., Marsee, M., Martinez-Soler, I., Maruyama, R., Mayhew, F., McNally, F., Mead, J. V., Meagher, K., Mechbal, S., Medina, A., Meier, M., Merckx, Y., Merten, L., Mitchell, J., Montaruli, T., Moore, R. W., Morii, Y., Morse, R., Moulai, M., Mukherjee, T., Naab, R., Nakos, M., Naumann, U., Necker, J., Negi, A., Neste, L., Neumann, M., Niederhausen, H., Nisa, M. U., Noda, K., Noell, A., Novikov, A., Pollmann, A. Obertacke, O'Dell, V., Olivas, A., Orsoe, R., Osborn, J., O'Sullivan, E., Palusova, V., Pandya, H., Park, N., Parker, G. K., Parrish, V., Paudel, E. N., Paul, L., Heros, C. Pérez de los, Pernice, T., Peterson, J., Pizzuto, A., Plum, M., Pontén, A., Popovych, Y., Rodriguez, M. Prado, Pries, B., Procter-Murphy, R., Przybylski, G. T., Pyras, L., Raab, C., Rack-Helleis, J., Rad, N., Ravn, M., Rawlins, K., Rechav, Z., Rehman, A., Resconi, E., Reusch, S., Rhode, W., Riedel, B., Rifaie, A., Roberts, E. J., Robertson, S., Rodan, S., Rongen, M., Rosted, A., Rott, C., Ruhe, T., Ruohan, L., Ryckbosch, D., Safa, I., Saffer, J., Salazar-Gallegos, D., Sampathkumar, P., Sandrock, A., Santander, M., Sarkar, S., Savelberg, J., Savina, P., Schaile, P., Schaufel, M., Schieler, H., Schindler, S., Schlickmann, L., Schlüter, B., Schlüter, F., Schmeisser, N., Schmidt, T., Schneider, J., Schröder, F. G., Schumacher, L., Schwirn, S., Sclafani, S., Seckel, D., Seen, L., Seikh, M., Seo, M., Seunarine, S., Myhr, P. Sevle, Shah, R., Shefali, S., Shimizu, N., Silva, M., Skrzypek, B., Smithers, B., Snihur, R., Soedingrekso, J., Søgaard, A., Soldin, D., Soldin, P., Sommani, G., Spannfellner, C., Spiczak, G. M., Spiering, C., Stachurska, J., Stamatikos, M., Stanev, T., Stezelberger, T., Stürwald, T., Stuttard, T., Sullivan, G. W., Taboada, I., Ter-Antonyan, S., Terliuk, A., Thiesmeyer, M., Thompson, W. G., Thwaites, J., Tilav, S., Tollefson, K., Tönnis, C., Toscano, S., Tosi, D., Trettin, A., Elorrieta, M. A. Unland, Upadhyay, A. K., Upshaw, K., Vaidyanathan, A., Valtonen-Mattila, N., Vandenbroucke, J., van Eijndhoven, N., Vannerom, D., van Santen, J., Vara, J., Varsi, F., Veitch-Michaelis, J., Venugopal, M., Vereecken, M., Carrasco, S. Vergara, Verpoest, S., Veske, D., Vijai, A., Walck, C., Wang, A., Weaver, C., Weigel, P., Weindl, A., Weldert, J., Wen, A. Y., Wendt, C., Werthebach, J., Weyrauch, M., Whitehorn, N., Wiebusch, C. H., Williams, D. R., Witthaus, L., Wolf, M., Wrede, G., Xu, X. W., Yanez, J. P., Yildizci, E., Yoshida, S., Young, R., Yu, F., Yu, S., Yuan, T., Zegarelli, A., Zhang, S., Zhang, Z., Zhelnin, P., Zilberman, P., and Zimmerman, M.
- Subjects
Astrophysics - High Energy Astrophysical Phenomena - Abstract
We report a search for high-energy astrophysical neutrino multiplets, detections of multiple neutrino clusters in the same direction within 30 days, based on an analysis of 11.4 years of IceCube data. A new search method optimized for transient neutrino emission with a monthly time scale is employed, providing a higher sensitivity to neutrino fluxes. This result is sensitive to neutrino transient emission, reaching per-flavor flux of approximately $10^{-10}\ {\rm erg}\ {\rm cm}^{-2}\ {\rm sec}^{-1}$ from the Northern sky in the energy range $E\gtrsim 50$~TeV. The number of doublets and triplets identified in this search is compatible with the atmospheric background hypothesis, which leads us to set limits on the nature of neutrino transient sources with emission timescales of one month.
- Published
- 2025
77. Formally Verified Neural Lyapunov Function for Incremental Input-to-State Stability of Unknown Systems
- Author
-
Basu, Ahan, Dey, Bhabani Shankar, and Jagtap, Pushpak
- Subjects
Electrical Engineering and Systems Science - Systems and Control - Abstract
This work presents an approach to synthesize a Lyapunov-like function to ensure incrementally input-to-state stability ($\delta$-ISS) property for an unknown discrete-time system. To deal with challenges posed by unknown system dynamics, we parameterize the Lyapunov-like function as a neural network, which we train using the data samples collected from the unknown system along with appropriately designed loss functions. We propose a validity condition to test the obtained function and incorporate it into the training framework to ensure provable correctness at the end of the training. Finally, the usefulness of the proposed technique is proved using two case studies: a scalar non-linear dynamical system and a permanent magnet DC motor.
- Published
- 2025
78. Controlled probing of Anderson localization and non-Hermitian skin effect via topolectrical circuits
- Author
-
Halder, Dipendu and Basu, Saurabh
- Subjects
Condensed Matter - Disordered Systems and Neural Networks ,Condensed Matter - Mesoscale and Nanoscale Physics ,Physics - Applied Physics ,Quantum Physics - Abstract
The Anderson localization (AL) and the non-Hermitian skin effect (NHSE) are two distinct wavefunction-localization phenomena arising out of disorder and non-reciprocity, respectively. An integration of both in a single framework will provide a platform to study the interplay between the two. In this connection, we consider the one-dimensional Aubry-Andr\'e (AA) model, which has garnered significant attention among the disordered models due to its self-dual properties. Hence, we investigate a non-reciprocal AA model with complex phase modulation and implement it in suitably designed topolectrical circuits featuring an interface, segregating two non-equivalent circuit networks. In the circuit, the voltage profile localizes at the interface due to the NHSE, while the AL limits localization phenomena within the vicinity of the excitation node. This competing phenomenon leads to a controllable, node-dependent localization or even partial delocalization of the output voltage. Our results not only provide a practical platform for experimentally studying and controlling the wave localization phenomenon but also highlight the potential of circuit architectures in designing highly sensitive sensors and information transfer in communication devices., Comment: 11 pages, (5+2) figures
- Published
- 2025
79. First result from tetrafluoroethane (C$_2$H$_2$F$_4$) superheated emulsion detector for dark matter search at JUSL
- Author
-
Kumar, V., Ali, S., Das, M., Biswas, N., Das, S., Sahoo, S., Chaddha, N., Basu, J., and Jha, V. N.
- Subjects
Physics - Instrumentation and Detectors ,Astrophysics - Astrophysics of Galaxies - Abstract
The superheated emulsion detector consisting of the droplets of tetra-fluoroethane (C2HC$_2$H$_2$F$_4$2F4) has been fabricated at the laboratory and installed at the 555m deep underground laboratory, JUSL during July to Dec 2022. The 500ml detector ran for an effective period of 48.6 days at a threshold of 5.87 keV with an exposure of 2.47 kg-days. The acoustic signals produced due to the bubble nucleation were collected by the acoustic sensor and FPGAbased data acquisition system. The data shows a minimum sensitivity of SI-nucleon for carbon at WIMP mass of 22.81 GeV/c$^2$ and SD (p) for fluorine at 30.67 GeV/c$^2$. The threshold of WIMP mass is 5.16 GeV/c$^2$ for F and 4.44 GeV/c$^2$ for C at the operating threshold of 5.87 keV. The first result of the dark matter direct search experiment named InDEx with tetra-fluoro-ethane active liquid from JUSL underground laboratory is reported in this article.
- Published
- 2025
80. 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. Kulur, Kumar, A., Kumar, Praveen, Kumar, Prayush, Kumar, Rahul, Kumar, Rakesh, Kume, J., Kuns, K., Kuntimaddi, N., Kuroyanagi, S., Kurth, N. J., Kuwahara, S., Kwak, K., Kwan, K., Kwok, J., Lacaille, G., Lagabbe, P., Laghi, D., Lai, S., Laity, A. H., Lakkis, M. H., Lalande, E., Lalleman, M., Lalremruati, P. C., Landry, M., Lane, B. B., Lang, R. N., Lange, J., Lantz, B., La Rana, A., La Rosa, I., Lartaux-Vollard, A., Lasky, P. D., Lawrence, J., Lawrence, M. N., Laxen, M., Lazzarini, A., Lazzaro, C., Leaci, P., Lecoeuche, Y. K., Lee, H. M., Lee, H. W., Lee, K., Lee, R. -K., Lee, R., Lee, S., Lee, Y., Legred, I. N., Lehmann, J., Lehner, L., Jean, M. Le, Lemaître, A., Lenti, M., Leonardi, M., Lequime, M., Leroy, N., Lesovsky, M., Letendre, N., Lethuillier, M., Levin, S. E., Levin, Y., Leyde, K., Li, A. K. Y., Li, K. L., Li, T. G. F., Li, X., Li, Z., Lihos, A., Lin, C-Y., Lin, C. -Y., Lin, E. T., Lin, F., Lin, H., Lin, L. C. -C., Lin, Y. -C., Linde, F., Linker, S. D., Littenberg, T. B., Liu, A., Liu, G. C., Liu, Jian, Villarreal, F. Llamas, Llobera-Querol, J., Lo, R. K. L., Locquet, J. -P., London, L. T., Longo, A., Lopez, D., Portilla, M. Lopez, Lorenzini, M., Lorenzo-Medina, A., Loriette, V., Lormand, M., Losurdo, G., Lott IV, T. P., Lough, J. D., Loughlin, H. A., Lousto, C. O., Lowry, M. J., Lu, N., Lück, H., Lumaca, D., Lundgren, A. P., Lussier, A. W., Ma, L. -T., Ma, S., Ma'arif, M., Macas, R., Macedo, A., MacInnis, M., Maciy, R. R., Macleod, D. M., MacMillan, I. A. O., Macquet, A., Macri, D., Maeda, K., Maenaut, S., Hernandez, I. Magaña, Magare, S. S., Magazzù, C., Magee, R. M., Maggio, E., Maggiore, R., Magnozzi, M., Mahesh, M., Mahesh, S., Maini, M., Majhi, S., Majorana, E., Makarem, C. N., Makelele, E., Malaquias-Reis, J. A., Mali, U., Maliakal, S., Malik, A., Man, N., Mandic, V., Mangano, V., Mannix, B., Mansell, G. L., Mansingh, G., Manske, M., Mantovani, M., Mapelli, M., Marchesoni, F., Pina, D. Marín, Marion, F., Márka, S., Márka, Z., Markosyan, A. S., Markowitz, A., Maros, E., Marsat, S., Martelli, F., Martin, I. W., Martin, R. M., Martinez, B. B., Martinez, M., Martinez, V., Martini, A., Martinovic, K., Martins, J. C., Martynov, D. V., Marx, E. J., Massaro, L., Masserot, A., Masso-Reid, M., Mastrodicasa, M., Mastrogiovanni, S., Matcovich, T., Matiushechkina, M., Matsuyama, M., Mavalvala, N., Maxwell, N., McCarrol, G., McCarthy, R., McClelland, D. E., McCormick, S., McCuller, L., McEachin, S., McElhenny, C., McGhee, G. I., McGinn, J., McGowan, K. B. M., McIver, J., McLeod, A., McRae, T., Meacher, D., Meijer, Q., Melatos, A., Mellaerts, S., Menendez-Vazquez, A., Menoni, C. S., Mera, F., Mercer, R. A., Mereni, L., Merfeld, K., Merilh, E. L., Mérou, J. R., Merritt, J. D., Merzougui, M., Messenger, C., Messick, C., Metzler, Z., Meyer-Conde, M., Meylahn, F., Mhaske, A., Miani, A., Miao, H., Michaloliakos, I., Michel, C., Michimura, Y., Middleton, H., Miller, A. L., Miller, S., Millhouse, M., Milotti, E., Milotti, V., Minenkov, Y., Mio, N., Mir, Ll. M., Mirasola, L., Miravet-Tenés, M., Miritescu, C. -A., Mishra, A. K., Mishra, A., Mishra, C., Mishra, T., Mitchell, A. L., Mitchell, J. G., Mitra, S., Mitrofanov, V. P., Mittleman, R., Miyakawa, O., Miyamoto, S., Miyoki, S., Mo, G., Mobilia, L., Mohapatra, S. R. P., Mohite, S. R., Molina-Ruiz, M., Mondal, C., Mondin, M., Montani, M., Moore, C. J., Moraru, D., More, A., More, S., Moreno, G., Morgan, C., Morisaki, S., Moriwaki, Y., Morras, G., Moscatello, A., Mourier, P., Mours, B., Mow-Lowry, C. M., Muciaccia, F., Mukherjee, Arunava, Mukherjee, D., Mukherjee, Samanwaya, Mukherjee, Soma, Mukherjee, Subroto, Mukherjee, Suvodip, Mukund, N., Mullavey, A., Munch, J., Mundi, J., Mungioli, C. L., Oberg, W. R. Munn, Murakami, Y., Murakoshi, M., Murray, P. G., Muusse, S., Nabari, D., Nadji, S. L., Nagar, A., Nagarajan, N., Nagler, K. N., Nakagaki, K., Nakamura, K., Nakano, H., Nakano, M., Nandi, D., Napolano, V., Narayan, P., Nardecchia, I., Narikawa, T., Narola, H., Naticchioni, L., Nayak, R. K., Neilson, J., Nelson, A., Nelson, T. J. N., Nery, M., Neunzert, A., Ng, S., Quynh, L. Nguyen, Nichols, S. A., Nielsen, A. B., Nieradka, G., Niko, A., Nishino, Y., Nishizawa, A., Nissanke, S., Nitoglia, E., Niu, W., Nocera, F., Norman, M., North, C., Novak, J., Siles, J. F. Nuño, Nuttall, L. K., Obayashi, K., Oberling, J., O'Dell, J., Oertel, M., Offermans, A., Oganesyan, G., Oh, J. J., Oh, K., O'Hanlon, T., Ohashi, M., Ohkawa, M., Ohme, F., Oliveira, A. S., Oliveri, R., O'Neal, B., Oohara, K., O'Reilly, B., Ormsby, N. D., Orselli, M., O'Shaughnessy, R., O'Shea, S., Oshima, Y., Oshino, S., Ossokine, S., Osthelder, C., Ota, I., Ottaway, D. J., Ouzriat, A., Overmier, H., Owen, B. J., Pace, A. E., Pagano, R., Page, M. A., Pai, A., Pal, A., Pal, S., Palaia, M. A., Pálfi, M., Palma, P. P., Palomba, C., Palud, P., Pan, H., Pan, J., Pan, K. C., Panai, R., Panda, P. K., Pandey, S., Panebianco, L., Pang, P. T. H., Pannarale, F., Pannone, K. A., Pant, B. C., Panther, F. H., Paoletti, F., Paolone, A., Papalexakis, E. E., Papalini, L., Papigkiotis, G., Paquis, A., Parisi, A., Park, B. -J., Park, J., Parker, W., Pascale, G., Pascucci, D., Pasqualetti, A., Passaquieti, R., Passenger, L., Passuello, D., Patane, O., Pathak, D., Pathak, M., Patra, A., Patricelli, B., Patron, A. S., Paul, K., Paul, S., Payne, E., Pearce, T., Pedraza, M., Pegna, R., Pele, A., Arellano, F. E. Peña, Penn, S., Penuliar, M. D., Perego, A., Pereira, Z., Perez, J. J., Périgois, C., Perna, G., Perreca, A., Perret, J., Perriès, S., Perry, J. W., Pesios, D., Petracca, S., Petrillo, C., Pfeiffer, H. P., Pham, H., Pham, K. A., Phukon, K. S., Phurailatpam, H., Piarulli, M., Piccari, L., Piccinni, O. J., Pichot, M., Piendibene, M., Piergiovanni, F., Pierini, L., Pierra, G., Pierro, V., Pietrzak, M., Pillas, M., Pilo, F., Pinard, L., Pinto, I. M., Pinto, M., Piotrzkowski, B. J., Pirello, M., Pitkin, M. D., Placidi, A., Placidi, E., Planas, M. L., Plastino, W., Poggiani, R., Polini, E., Pompili, L., Poon, J., Porcelli, E., Porter, E. K., Posnansky, C., Poulton, R., Powell, J., Pracchia, M., Pradhan, B. K., Pradier, T., Prajapati, A. K., Prasai, K., Prasanna, R., Prasia, P., Pratten, G., Principe, G., Principe, M., Prodi, G. A., Prokhorov, L., Prosposito, P., Puecher, A., Pullin, J., Punturo, M., Puppo, P., Pürrer, M., Qi, H., Qin, J., Quéméner, G., Quetschke, V., Quigley, C., Quinonez, P. J., Raab, F. J., Raabith, S. S., Raaijmakers, G., Raja, S., Rajan, C., Rajbhandari, B., Ramirez, K. E., Vidal, F. A. Ramis, Ramos-Buades, A., Rana, D., Ranjan, S., Ransom, K., Rapagnani, P., Ratto, B., Rawat, S., Ray, A., Raymond, V., Razzano, M., Read, J., Payo, M. Recaman, Regimbau, T., Rei, L., Reid, S., Reitze, D. H., Relton, P., Renzini, A. I., Rettegno, P., Revenu, B., Reyes, R., Rezaei, A. S., Ricci, F., Ricci, M., Ricciardone, A., Richardson, J. W., Richardson, M., Rijal, A., Riles, K., Riley, H. K., Rinaldi, S., Rittmeyer, J., Robertson, C., Robinet, F., Robinson, M., Rocchi, A., Rolland, L., Rollins, J. G., Romano, A. E., Romano, R., Romero, A., Romero-Shaw, I. M., Romie, J. H., Ronchini, S., Roocke, T. J., Rosa, L., Rosauer, T. J., Rose, C. A., Rosińska, D., Ross, M. P., Rossello, M., Rowan, S., Roy, S. K., Roy, S., Rozza, D., Ruggi, P., Ruhama, N., Morales, E. Ruiz, Ruiz-Rocha, K., Sachdev, S., Sadecki, T., Sadiq, J., Saffarieh, P., Sah, M. R., Saha, S. S., Saha, S., Sainrat, T., Menon, S. Sajith, Sakai, K., Sakellariadou, M., Sakon, S., Salafia, O. S., Salces-Carcoba, F., Salconi, L., Saleem, M., Salemi, F., Sallé, M., Salvador, S., Sanchez, A., Sanchez, E. J., Sanchez, J. H., Sanchez, L. E., Sanchis-Gual, N., Sanders, J. R., Sänger, E. M., Santoliquido, F., Saravanan, T. R., Sarin, N., Sasaoka, S., Sasli, A., Sassi, P., Sassolas, B., Satari, H., Sato, R., Sato, Y., Sauter, O., Savage, R. L., Sawada, T., Sawant, H. L., Sayah, S., Scacco, V., Schaetzl, D., Scheel, M., Schiebelbein, A., Schiworski, M. G., Schmidt, P., Schmidt, S., Schnabel, R., Schneewind, M., Schofield, R. M. S., Schouteden, K., Schulte, B. W., Schutz, B. F., Schwartz, E., Scialpi, M., Scott, J., Scott, S. M., Seetharamu, T. C., Seglar-Arroyo, M., Sekiguchi, Y., Sellers, D., Sengupta, A. S., Sentenac, D., Seo, E. G., Seo, J. W., Sequino, V., Serra, M., Servignat, G., Sevrin, A., Shaffer, T., Shah, U. S., Shaikh, M. A., Shao, L., Sharma, A. K., Sharma, P., Sharma-Chaudhary, S., Shaw, M. R., Shawhan, P., Shcheblanov, N. S., Sheridan, E., Shikano, Y., Shikauchi, M., Shimode, K., Shinkai, H., Shiota, J., Shoemaker, D. H., Shoemaker, D. M., Short, R. W., ShyamSundar, S., Sider, A., Siegel, H., Sieniawska, M., Sigg, D., Silenzi, L., Simmonds, M., Singer, L. P., Singh, A., Singh, D., Singh, M. K., Singh, S., Singha, A., Sintes, A. M., Sipala, V., Skliris, V., Slagmolen, B. J. J., Slaven-Blair, T. J., Smetana, J., Smith, J. R., Smith, L., Smith, R. J. E., Smith, W. J., Soldateschi, J., Somiya, K., Song, I., Soni, K., Soni, S., Sordini, V., Sorrentino, F., Sorrentino, N., Sotani, H., Soulard, R., Southgate, A., Spagnuolo, V., Spencer, A. P., Spera, M., Spinicelli, P., Spoon, J. B., Sprague, C. A., Srivastava, A. K., Stachurski, F., Steer, D. A., Steinlechner, J., Steinlechner, S., Stergioulas, N., Stevens, P., StPierre, M., Stratta, G., Strong, M. D., Strunk, A., Sturani, R., Stuver, A. L., Suchenek, M., Sudhagar, S., Sueltmann, N., Suleiman, L., Sullivan, K. D., Sun, L., Sunil, S., Suresh, J., Sutton, P. J., Suzuki, T., Suzuki, Y., Swinkels, B. L., Syx, A., Szczepańczyk, M. J., Szewczyk, P., Tacca, M., Tagoshi, H., Tait, S. C., Takahashi, H., Takahashi, R., Takamori, A., Takase, T., Takatani, K., Takeda, H., Takeshita, K., Talbot, C., Tamaki, M., Tamanini, N., Tanabe, D., Tanaka, K., Tanaka, S. J., Tanaka, T., Tang, D., Tanioka, S., Tanner, D. B., Tao, L., Tapia, R. D., Martín, E. N. Tapia San, Tarafder, R., Taranto, C., Taruya, A., Tasson, J. D., Teloi, M., Tenorio, R., Themann, H., Theodoropoulos, A., Thirugnanasambandam, M. P., Thomas, L. M., Thomas, M., Thomas, P., Thompson, J. E., Thondapu, S. R., Thorne, K. A., Thrane, E., Tissino, J., Tiwari, A., Tiwari, P., Tiwari, S., Tiwari, V., Todd, M. R., Toivonen, A. M., Toland, K., Tolley, A. E., Tomaru, T., Tomita, K., Tomura, T., Tong-Yu, C., Toriyama, A., Toropov, N., Torres-Forné, A., Torrie, C. I., Toscani, M., Melo, I. Tosta e, Tournefier, E., Trapananti, A., Travasso, F., Traylor, G., Trevor, M., Tringali, M. C., Tripathee, A., Troian, G., Troiano, L., Trovato, A., Trozzo, L., Trudeau, R. J., Tsang, T. T. L., Tso, R., Tsuchida, S., Tsukada, L., Tsutsui, T., Turbang, K., Turconi, M., Turski, C., Ubach, H., Uchiyama, T., Udall, R. P., Uehara, T., Uematsu, M., Ueno, K., Ueno, S., Undheim, V., Ushiba, T., Vacatello, M., Vahlbruch, H., Vaidya, N., Vajente, G., Vajpeyi, A., Valdes, G., Valencia, J., Valentini, M., Vallejo-Peña, S. A., Vallero, S., Valsan, V., van Bakel, N., van Beuzekom, M., van Dael, M., Brand, J. F. J. van den, Broeck, C. Van Den, Vander-Hyde, D. C., van der Sluys, M., Van de Walle, A., van Dongen, J., Vandra, K., van Haevermaet, H., van Heijningen, J. V., Van Hove, P., VanKeuren, M., Vanosky, J., van Putten, M. H. P. M., van Ranst, Z., van Remortel, N., Vardaro, M., Vargas, A. F., Varghese, J. J., Varma, V., Vasúth, M., Vecchio, A., Vedovato, G., Veitch, J., Veitch, P. J., Venikoudis, S., Venneberg, J., Verdier, P., Verkindt, D., Verma, B., Verma, P., Verma, Y., Vermeulen, S. M., Vetrano, F., Veutro, A., Vibhute, A. M., Viceré, A., Vidyant, S., Viets, A. D., Vijaykumar, A., Vilkha, A., Villa-Ortega, V., Vincent, E. T., Vinet, J. -Y., Viret, S., Virtuoso, A., Vitale, S., Vives, A., Vocca, H., Voigt, D., von Reis, E. R. G., von Wrangel, J. S. A., Vyatchanin, S. P., Wade, L. E., Wade, M., Wagner, K. J., Wajid, A., Walker, M., Wallace, G. S., Wallace, L., Wang, H., Wang, J. Z., Wang, W. H., Wang, Z., Waratkar, G., Warner, J., Was, M., Washimi, T., Washington, N. Y., Watarai, D., Wayt, K. E., Weaver, B. R., Weaver, B., Weaving, C. R., Webster, S. A., Weinert, M., Weinstein, A. J., Weiss, R., Wellmann, F., Wen, L., Weßels, P., Wette, K., Whelan, J. T., Whiting, B. F., Whittle, C., Wildberger, J. B., Wilk, O. S., Wilken, D., Wilkin, A. T., Willadsen, D. J., Willetts, K., Williams, D., Williams, M. J., Williams, N. S., Willis, J. L., Willke, B., Wils, M., Winterflood, J., Wipf, C. C., Woan, G., Woehler, J., Wofford, J. K., Wolfe, N. E., Wong, H. T., Wong, H. W. Y., Wong, I. C. F., Wright, J. L., Wright, M., Wu, C., Wu, D. S., Wu, H., Wuchner, E., Wysocki, D. M., Xu, V. A., Xu, Y., Yadav, N., Yamamoto, H., Yamamoto, K., Yamamoto, T. S., Yamamoto, T., Yamamura, S., Yamazaki, R., Yan, S., Yan, T., Yang, F. W., Yang, F., Yang, K. Z., Yang, Y., Yarbrough, Z., Yasui, H., Yeh, S. -W., Yelikar, A. B., Yin, X., Yokoyama, J., Yokozawa, T., Yoo, J., Yu, H., Yuan, S., Yuzurihara, H., Zadrożny, A., Zanolin, M., Zeeshan, M., Zelenova, T., Zendri, J. -P., Zeoli, M., Zerrad, M., Zevin, M., Zhang, A. C., Zhang, L., Zhang, R., Zhang, T., Zhang, Y., Zhao, C., Zhao, Yue, Zhao, Yuhang, Zheng, Y., Zhong, H., Zhou, R., Zhu, X. -J., Zhu, Z. -H., Zimmerman, A. B., Zucker, M. E., Zweizig, J., Furlan, S. B. Araujo, Arzoumanian, Z., Basu, A., Cassity, A., Cognard, I., Crowter, K., del Palacio, S., Espinoza, C. M., Fonseca, E., Flynn, C. M. L., Gancio, G., Garcia, F., Gendreau, K. C., Good, D. C., Guillemot, L., Guillot, S., Keith, M. J., Kuiper, L., Lower, M. E., Lyne, A. G., McKee, J. W., Meyers, B. W., Palfreyman, J. 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
81. Anandita Basu | Mandatory Dematerialisation For Pvt Co.S (Video)
- Subjects
Corporation law -- Interpretation and construction ,Business, international ,India. Depositories Act 1996 ,India. Companies Act 1956 - Abstract
self Watch the latest edition of JSA Live, where our Principal Associate, Anindita Basu, discusses the mandatory requirement for private companies to issue securities exclusively in dematerialized form. The objective [...]
- Published
- 2024
82. Isoperimetry is All We Need: Langevin Posterior Sampling for RL with Sublinear Regret
- Author
-
Jorge, Emilio, Dimitrakakis, Christos, and Basu, Debabrota
- Subjects
Computer Science - Machine Learning ,Statistics - Machine Learning - Abstract
In Reinforcement Learning (RL) theory, we impose restrictive assumptions to design an algorithm with provably sublinear regret. Common assumptions, like linear or RKHS models, and Gaussian or log-concave posteriors over the models, do not explain practical success of RL across a wider range of distributions and models. Thus, we study how to design RL algorithms with sublinear regret for isoperimetric distributions, specifically the ones satisfying the Log-Sobolev Inequality (LSI). LSI distributions include the standard setups of RL and others, such as many non-log-concave and perturbed distributions. First, we show that the Posterior Sampling-based RL (PSRL) yields sublinear regret if the data distributions satisfy LSI under some mild additional assumptions. Also, when we cannot compute or sample from an exact posterior, we propose a Langevin sampling-based algorithm design: LaPSRL. We show that LaPSRL achieves order optimal regret and subquadratic complexity per episode. Finally, we deploy LaPSRL with a Langevin sampler -- SARAH-LD, and test it for different bandit and MDP environments. Experimental results validate the generality of LaPSRL across environments and its competitive performance with respect to the baselines.
- Published
- 2024
83. Flat Bands and Compact Localised States: A Carrollian roadmap
- Author
-
Ara, Nisa, Banerjee, Aritra, Basu, Rudranil, and Krishnan, Bhagya
- Subjects
High Energy Physics - Theory ,Condensed Matter - Strongly Correlated Electrons ,Quantum Physics - Abstract
We show how Carrollian symmetries become important in the construction of one-dimensional fermionic systems with all flat-band spectra from first principles. The key ingredient of this construction is the identification of Compact Localised States (CLSs), which appear naturally by demanding $\textit{supertranslation}$ invariance of the system. We use CLS basis states, with inherent $\textit{ultra-local}$ correlations, to write down an interacting theory which shows a non-trivial phase structure and an emergent Carroll conformal symmetry at the gapless points. We analyze this theory in detail for both zero and finite chemical potential.
- Published
- 2024
84. On Robust Cross Domain Alignment
- Author
-
Chakrabarty, Anish, Basu, Arkaprabha, and Das, Swagatam
- Subjects
Statistics - Machine Learning ,Computer Science - Machine Learning - Abstract
The Gromov-Wasserstein (GW) distance is an effective measure of alignment between distributions supported on distinct ambient spaces. Calculating essentially the mutual departure from isometry, it has found vast usage in domain translation and network analysis. It has long been shown to be vulnerable to contamination in the underlying measures. All efforts to introduce robustness in GW have been inspired by similar techniques in optimal transport (OT), which predominantly advocate partial mass transport or unbalancing. In contrast, the cross-domain alignment problem being fundamentally different from OT, demands specific solutions to tackle diverse applications and contamination regimes. Deriving from robust statistics, we discuss three contextually novel techniques to robustify GW and its variants. For each method, we explore metric properties and robustness guarantees along with their co-dependencies and individual relations with the GW distance. For a comprehensive view, we empirically validate their superior resilience to contamination under real machine learning tasks against state-of-the-art methods.
- Published
- 2024
85. Emergent short-range repulsion for attractively coupled active particles
- Author
-
Sarkar, Ritwick and Basu, Urna
- Subjects
Condensed Matter - Statistical Mechanics - Abstract
We show that heterogeneity in self-propulsion speed leads to the emergence of effective short-range repulsion among active particles coupled via strong attractive potentials. Taking the example of two harmonically coupled active Brownian particles, we analytically compute the stationary distribution of the distance between them in the strong coupling regime, i.e., where the coupling strength is much larger than the rotational diffusivity of the particles. The effective repulsion in this regime is manifest in the emergence of a minimum distance between the particles, proportional to the difference in their self-propulsion speeds. Physically, this distance of the closest approach is associated to the orientations of the particles being parallel to each other. We show that the physical scenario remains qualitatively similar for any long-range coupling potential, which is attractive everywhere. Moreover, we show that, for a collection of $N$ particles interacting via pairwise attractive potentials, a short-range repulsion emerges for each pair of particles with different self-propulsion speeds. Finally, we show that our results are robust and hold irrespective of the specific active dynamics of the particles.
- Published
- 2024
86. Crosstalk-induced Side Channel Threats in Multi-Tenant NISQ Computers
- Author
-
Choudhury, Navnil, Mude, Chaithanya Naik, Das, Sanjay, Tikkireddi, Preetham Chandra, Tannu, Swamit, and Basu, Kanad
- Subjects
Computer Science - Emerging Technologies - Abstract
As quantum computing rapidly advances, its near-term applications are becoming increasingly evident. However, the high cost and under-utilization of quantum resources are prompting a shift from single-user to multi-user access models. In a multi-tenant environment, where multiple users share one quantum computer, protecting user confidentiality becomes crucial. The varied uses of quantum computers increase the risk that sensitive data encoded by one user could be compromised by others, rendering the protection of data integrity and confidentiality essential. In the evolving quantum computing landscape, it is imperative to study these security challenges within the scope of realistic threat model assumptions, wherein an adversarial user can mount practical attacks without relying on any heightened privileges afforded by physical access to a quantum computer or rogue cloud services. In this paper, we demonstrate the potential of crosstalk as an attack vector for the first time on a Noisy Intermediate Scale Quantum (NISQ) machine, that an adversarial user can exploit within a multi-tenant quantum computing model. The proposed side-channel attack is conducted with minimal and realistic adversarial privileges, with the overarching aim of uncovering the quantum algorithm being executed by a victim. Crosstalk signatures are used to estimate the presence of CNOT gates in the victim circuit, and subsequently, this information is encoded and classified by a graph-based learning model to identify the victim quantum algorithm. When evaluated on up to 336 benchmark circuits, our attack framework is found to be able to unveil the victim's quantum algorithm with up to 85.7\% accuracy.
- Published
- 2024
87. Atomic Learning Objectives Labeling: A High-Resolution Approach for Physics Education
- Author
-
Liu, Naiming, Sonkar, Shashank, Mallick, Debshila Basu, Baraniuk, Richard, and Chen, Zhongzhou
- Subjects
Computer Science - Computers and Society - Abstract
This paper introduces a novel approach to create a high-resolution "map" for physics learning: an "atomic" learning objectives (LOs) system designed to capture detailed cognitive processes and concepts required for problem solving in a college-level introductory physics course. Our method leverages Large Language Models (LLMs) for automated labeling of physics questions and introduces a comprehensive set of metrics to evaluate the quality of the labeling outcomes. The atomic LO system, covering nine chapters of an introductory physics course, uses a "subject-verb-object'' structure to represent specific cognitive processes. We apply this system to 131 questions from expert-curated question banks and the OpenStax University Physics textbook. Each question is labeled with 1-8 atomic LOs across three chapters. Through extensive experiments using various prompting strategies and LLMs, we compare automated LOs labeling results against human expert labeling. Our analysis reveals both the strengths and limitations of LLMs, providing insight into LLMs reasoning processes for labeling LOs and identifying areas for improvement in LOs system design. Our work contributes to the field of learning analytics by proposing a more granular approach to mapping learning objectives with questions. Our findings have significant implications for the development of intelligent tutoring systems and personalized learning pathways in STEM education, paving the way for more effective "learning GPS'' systems., Comment: The paper is accepted to LAK'2025
- Published
- 2024
88. Addressing Positivity Violations in Extending Inference to a Target Population
- Author
-
Lu, Jun and Basu, Sanjib
- Subjects
Statistics - Methodology - Abstract
Enhancing the external validity of trial results is essential for their applicability to real-world populations. However, violations of the positivity assumption can limit both the generalizability and transportability of findings. To address positivity violations in estimating the average treatment effect for a target population, we propose a framework that integrates characterizing the underrepresented group and performing sensitivity analysis for inference in the original target population. Our approach helps identify limitations in trial sampling and improves the robustness of trial findings for real-world populations. We apply this approach to extend findings from phase IV trials of treatments for opioid use disorder to a real-world population based on the 2021 Treatment Episode Data Set.
- Published
- 2024
89. PBR-NeRF: Inverse Rendering with Physics-Based Neural Fields
- Author
-
Wu, Sean, Basu, Shamik, Broedermann, Tim, Van Gool, Luc, and Sakaridis, Christos
- Subjects
Computer Science - Computer Vision and Pattern Recognition - Abstract
We tackle the ill-posed inverse rendering problem in 3D reconstruction with a Neural Radiance Field (NeRF) approach informed by Physics-Based Rendering (PBR) theory, named PBR-NeRF. Our method addresses a key limitation in most NeRF and 3D Gaussian Splatting approaches: they estimate view-dependent appearance without modeling scene materials and illumination. To address this limitation, we present an inverse rendering (IR) model capable of jointly estimating scene geometry, materials, and illumination. Our model builds upon recent NeRF-based IR approaches, but crucially introduces two novel physics-based priors that better constrain the IR estimation. Our priors are rigorously formulated as intuitive loss terms and achieve state-of-the-art material estimation without compromising novel view synthesis quality. Our method is easily adaptable to other inverse rendering and 3D reconstruction frameworks that require material estimation. We demonstrate the importance of extending current neural rendering approaches to fully model scene properties beyond geometry and view-dependent appearance. Code is publicly available at https://github.com/s3anwu/pbrnerf, Comment: 16 pages, 7 figures. Code is publicly available at https://github.com/s3anwu/pbrnerf
- Published
- 2024
90. A new and flexible design method for Symmetric Quadrature Hybrid Couplers using Markov Chain Monte Carlo
- Author
-
Ghosh, Arjun and Thakur, Ritoban Basu
- Subjects
Astrophysics - Instrumentation and Methods for Astrophysics - Abstract
Quadrature Hybrid Couplers (QHDC) are critical components in RF, mm-wave, and sub-mm wave astronomical instrumentation, where wideband performance with minimal passband ripple is essential. Traditional designs have been limited to 5-sections at most due to computational limitations. In this work, we introduce a new analytical technique to design couplers with larger sections and improved performance. We do this by employing a Markov Chain Monte Carlo (MCMC) based solver. By defining a likelihood function based on S-parameter equations and incorporating physical priors, we derive optimized impedance values that enhance bandwidth beyond what is reported in the literature. Our flexible pipeline allows efficient tuning of the coupler design. The results demonstrate fractional bandwidths that reach 1.0 for a 9-section coupler, substantially outperforming previous designs. Statistical analysis and convergence tests confirm the robustness of our approach., Comment: 9 pages, 13 figures
- Published
- 2024
91. Insights into Transient Dynamics of Bacteria Laden Liquid Bridges
- Author
-
Dewangan, Kush Kumar, S, Srinivas Rao, Roy, Durbar, Chowdhury, Atish Roy, Chakravortty, Dipshikha, and Basu, Saptarshi
- Subjects
Condensed Matter - Soft Condensed Matter ,Physics - Fluid Dynamics - Abstract
We study evaporation and precipitate formation mechanics of bacteria-laden liquid bridge using experimental and theoretical analysis. Aqueous suspension of motile and non-motile Salmonella Typhimurium and Pseudomonas aeruginosa typically found in contaminated food and water were used in liquid bridge configuration between hydrophilic substrates. Using inverse logarithmic evaporation flux model, we study volume regression for cylindrical/catenoid volume models with confinement distance as a parameter. For all confinement distances, the regression is linear on normalizing both volume and time as in the case of pure sessile drop. However, in normalized volume and dimensional time space, we observe non-linearities as the evaporation time scales non linearly with the confinement distance. The non-linearities were captured using the catenoid model. The catenoid model conforms to the experimental volume regression data at all confinement distances, and the transient liquid bridge interface evolution profile at high confinement distance. We also study the precipitate pattern and bacterial distribution using micro/nano characterization techniques. We show the average precipitate pattern for both sessile and higher confinement distance resembles coffee ring type deposits although the underlying bacterial distribution differs. For lower confinement, we observe pattern resulting from a combination of coffee ring effect, stick-slick motion, and thin film instability. The reduction in confinement distance causes an altered bacterial agglomeration, resulting in a multi-pattern network instead of a single circumferential edge deposition. We show the aerial size of motile bacteria increases with decreasing confinement, whereas the size for non-motile bacteria remains constant in the precipitate.
- Published
- 2024
92. MISFEAT: Feature Selection for Subgroups with Systematic Missing Data
- Author
-
Genossar, Bar, On, Thinh, Islam, Md. Mouinul, Eliav, Ben, Roy, Senjuti Basu, and Gal, Avigdor
- Subjects
Computer Science - Machine Learning ,Computer Science - Databases ,Statistics - Machine Learning - Abstract
We investigate the problem of selecting features for datasets that can be naturally partitioned into subgroups (e.g., according to socio-demographic groups and age), each with its own dominant set of features. Within this subgroup-oriented framework, we address the challenge of systematic missing data, a scenario in which some feature values are missing for all tuples of a subgroup, due to flawed data integration, regulatory constraints, or privacy concerns. Feature selection is governed by finding mutual Information, a popular quantification of correlation, between features and a target variable. Our goal is to identify top-K feature subsets of some fixed size with the highest joint mutual information with a target variable. In the presence of systematic missing data, the closed form of mutual information could not simply be applied. We argue that in such a setting, leveraging relationships between available feature mutual information within a subgroup or across subgroups can assist inferring missing mutual information values. We propose a generalizable model based on heterogeneous graph neural network to identify interdependencies between feature-subgroup-target variable connections by modeling it as a multiplex graph, and employing information propagation between its nodes. We address two distinct scalability challenges related to training and propose principled solutions to tackle them. Through an extensive empirical evaluation, we demonstrate the efficacy of the proposed solutions both qualitatively and running time wise.
- Published
- 2024
93. Application of Random Matrix Theory in High-Dimensional Statistics
- Author
-
Bhattacharyya, Swapnaneel, Chattopadhyay, Srijan, and Basu, Sevantee
- Subjects
Statistics - Methodology ,Mathematics - Statistics Theory - Abstract
This review article provides an overview of random matrix theory (RMT) with a focus on its growing impact on the formulation and inference of statistical models and methodologies. Emphasizing applications within high-dimensional statistics, we explore key theoretical results from RMT and their role in addressing challenges associated with high-dimensional data. The discussion highlights how advances in RMT have significantly influenced the development of statistical methods, particularly in areas such as covariance matrix inference, principal component analysis (PCA), signal processing, and changepoint detection, demonstrating the close interplay between theory and practice in modern high-dimensional statistical inference., Comment: 56 pages, 7 figures
- Published
- 2024
94. Asteroseismic Structure Inversions of Main-Sequence Solar-like Oscillators with Convective Cores
- Author
-
Buchele, Lynn, Bellinger, Earl P., Hekker, Saskia, and Basu, Sarbani
- Subjects
Astrophysics - Solar and Stellar Astrophysics - Abstract
Asteroseismic inferences of main-sequence solar-like oscillators often rely on best-fit models. However, these models cannot fully reproduce the observed mode frequencies, suggesting that the internal structure of the model does not fully match that of the star. Asteroseismic structure inversions provide a way to test the interior of our stellar models. Recently, structure inversion techniques were used to study 12 stars with radiative cores. In this work, we extend that analysis to 43 main-sequence stars with convective cores observed by Kepler to look for differences in the sound speed profiles in the inner 30% of the star by radius. For around half of our stars, the structure inversions show that our models reproduce the internal structure of the star, where the inversions are sensitive, within the observational uncertainties. For the stars where our inversions reveal significant differences, we find cases where our model sound speed is too high and cases where our model sound speed is too low. We use the star with the most significant differences to explore several changes to the physics of our model in an attempt to resolve the inferred differences. These changes include using a different overshoot prescription and including the effects of diffusion, gravitational settling, and radiative levitation. We find that the resulting changes to the model structure are too small to resolve the differences shown in our inversions., Comment: 18 pages, 8 figures, Resubmitted to ApJ after favorable referee report
- Published
- 2024
95. Observation of Cosmic-Ray Anisotropy in the Southern Hemisphere with Twelve Years of Data Collected by the IceCube Neutrino Observatory
- Author
-
Abbasi, R., Ackermann, M., Adams, J., Agarwalla, S. K., Aguado, T., Aguilar, J. A., Ahlers, M., Alameddine, J. M., Amin, N. M., Andeen, K., Argüelles, C., Ashida, Y., Athanasiadou, S., Axani, S. N., Babu, R., Bai, X., V., A. Balagopal, Baricevic, M., Barwick, S. W., Bash, S., Basu, V., Bay, R., Beatty, J. J., Tjus, J. Becker, Beise, J., Bellenghi, C., BenZvi, S., Berley, D., Bernardini, E., Besson, D. Z., Blaufuss, E., Bloom, L., Blot, S., Bontempo, F., Motzkin, J. Y. Book, Meneguolo, C. Boscolo, Böser, S., Botner, O., Böttcher, J., Braun, J., Brinson, B., Brisson-Tsavoussis, Z., Brostean-Kaiser, J., Brusa, L., Burley, R. T., Butterfield, D., Campana, M. A., Caracas, I., Carloni, K., Carpio, J., Chattopadhyay, S., Chau, N., Chen, Z., Chirkin, D., Choi, S., Clark, B. A., Cochling, C., Coleman, A., Coleman, P., Collin, G. H., Connolly, A., Conrad, J. M., Corley, R., Cowen, D. F., De Clercq, C., DeLaunay, J. J., Delgado, D., Deng, S., Desai, A., Desiati, P., de Vries, K. D., de Wasseige, G., DeYoung, T., Diaz, A., Díaz-Vélez, J. C., Dierichs, P., Dittmer, M., Domi, A., Draper, L., Dujmovic, H., Durnford, D., Dutta, K., DuVernois, M. A., Ehrhardt, T., Eidenschink, L., Eimer, A., Eller, P., Ellinger, E., Mentawi, S. El, Elsässer, D., Engel, R., Erpenbeck, H., Esmail, W., Evans, J., Evenson, P. A., Fan, K. L., Fang, K., Farrag, K., Fazely, A. R., Fedynitch, A., Feigl, N., Fiedlschuster, S., Finley, C., Fischer, L., Fox, D., Franckowiak, A., Fukami, S., Fürst, P., Gallagher, J., Ganster, E., Garcia, A., Garcia, M., Garg, G., Genton, E., Gerhardt, L., Ghadimi, A., Girard-Carillo, C., Glaser, C., Glüsenkamp, T., Gonzalez, J. G., Goswami, S., Granados, A., Grant, D., Gray, S. J., Griffin, S., Griswold, S., Groth, K. M., Guevel, D., Günther, C., Gutjahr, P., Gruchot, K., Ha, C., Haack, C., Hallgren, A., Halve, L., Halzen, F., Hamacher, L., Hamdaoui, H., Minh, M. Ha, Handt, M., Hanson, K., Hardin, J., Harnisch, A. A., Hatch, P., Haungs, A., Häußler, J., Hardy, A., Hayes, W., Helbing, K., Hellrung, J., Hermannsgabner, J., Heuermann, L., Heyer, N., Hickford, S., Hidvegi, A., Hill, C., Hill, G. C., Hmaid, R., Hoffman, K. D., Hori, S., Hoshina, K., Hostert, M., Hou, W., Huber, T., Hultqvist, K., Hünnefeld, M., Hussain, R., Hymon, K., Ishihara, A., Iwakiri, W., Jacquart, M., Jain, S., Janik, O., Jansson, M., Jeong, M., Jin, M., Jones, B. J. P., Kamp, N., Kang, D., Kang, W., Kang, X., Kappes, A., Kappesser, D., Kardum, L., Karg, T., Karl, M., Karle, A., Katil, A., Katz, U., Kauer, M., Kelley, J. L., Khanal, M., Zathul, A. Khatee, Kheirandish, A., Kiryluk, J., Klein, S. R., Kobayashi, Y., Kochocki, A., Koirala, R., Kolanoski, H., Kontrimas, T., Köpke, L., Kopper, C., Koskinen, D. J., Koundal, P., Kowalski, M., Kozynets, T., Krieger, N., Krishnamoorthi, J., Kruiswijk, K., Krupczak, E., Kumar, A., Kun, E., Kurahashi, N., Lad, N., Gualda, C. Lagunas, Lamoureux, M., Larson, M. J., Lauber, F., Lazar, J. P., Lee, J. W., DeHolton, K. Leonard, Leszczyńska, A., Liao, J., Lincetto, M., Liu, Y. T., Liubarska, M., Love, C., Lu, L., Lucarelli, F., Luszczak, W., Lyu, Y., Madsen, J., Magnus, E., Mahn, K. B. M., Makino, Y., Manao, E., Mancina, S., Mand, A., Sainte, W. Marie, Mariş, I. C., Marka, S., Marka, Z., Marsee, M., Martinez-Soler, I., Maruyama, R., Mayhew, F., McNally, F., Mead, J. V., Meagher, K., Mechbal, S., Medina, A., Meier, M., Merckx, Y., Merten, L., Mitchell, J., Montaruli, T., Moore, R. W., Morii, Y., Morse, R., Moulai, M., Moy, A., Mukherjee, T., Naab, R., Nakos, M., Naumann, U., Necker, J., Negi, A., Neste, L., Neumann, M., Niederhausen, H., Nisa, M. U., Noda, K., Noell, A., Novikov, A., Pollmann, A. Obertacke, O'Dell, V., Olivas, A., Orsoe, R., Osborn, J., O'Sullivan, E., Palusova, V., Pandya, H., Park, N., Parker, G. K., Parrish, V., Paudel, E. N., Paul, L., Heros, C. Pérez de los, Pernice, T., Peterson, J., Pizzuto, A., Plum, M., Pontén, A., Popovych, Y., Rodriguez, M. Prado, Pries, B., Procter-Murphy, R., Przybylski, G. T., Pyras, L., Raab, C., Rack-Helleis, J., Rad, N., Ravn, M., Rawlins, K., Rechav, Z., Rehman, A., Resconi, E., Reusch, S., Rhode, W., Riedel, B., Rifaie, A., Roberts, E. J., Robertson, S., Rodan, S., Roellinghoff, G., Rongen, M., Rosted, A., Rott, C., Ruhe, T., Ruohan, L., Ryckbosch, D., Safa, I., Saffer, J., Salazar-Gallegos, D., Sampathkumar, P., Sandrock, A., Santander, M., Sarkar, S., Savelberg, J., Savina, P., Schaile, P., Schaufel, M., Schieler, H., Schindler, S., Schlickmann, L., Schlüter, B., Schlüter, F., Schmeisser, N., Schmidt, E., Schmidt, T., Schneider, J., Schröder, F. G., Schumacher, L., Schwirn, S., Sclafani, S., Seckel, D., Seen, L., Seikh, M., Seo, M., Seunarine, S., Myhr, P. Sevle, Shah, R., Shefali, S., Shimizu, N., Silva, M., Simmons, A., Skrzypek, B., Smithers, B., Snihur, R., Soedingrekso, J., Søgaard, A., Soldin, D., Soldin, P., Sommani, G., Spannfellner, C., Spiczak, G. M., Spiering, C., Stachurska, J., Stamatikos, M., Stanev, T., Stezelberger, T., Stürwald, T., Stuttard, T., Sullivan, G. W., Taboada, I., Ter-Antonyan, S., Terliuk, A., Thiesmeyer, M., Thompson, W. G., Thorpe, A., Thwaites, J., Tilav, S., Tollefson, K., Tönnis, C., Toscano, S., Tosi, D., Trettin, A., Turcotte, R., Elorrieta, M. A. Unland, Upadhyay, A. K., Upshaw, K., Vaidyanathan, A., Valtonen-Mattila, N., Vandenbroucke, J., van Eijndhoven, N., Vannerom, D., van Santen, J., Vara, J., Varsi, F., Veitch-Michaelis, J., Venugopal, M., Vereecken, M., Carrasco, S. Vergara, Verpoest, S., Veske, D., Vijai, A., Walck, C., Wang, A., Weaver, C., Weigel, P., Weindl, A., Weldert, J., Wen, A. Y., Wendt, C., Werthebach, J., Weyrauch, M., Whitehorn, N., Wiebusch, C. H., Williams, D. R., Witthaus, L., Wolf, M., Woodward, H., Wrede, G., Xu, X. W., Yanez, J. P., Yildizci, E., Yoshida, S., Young, R., Yu, S., Yuan, T., Zegarelli, A., Zhang, S., Zhang, Z., Zhelnin, P., Zilberman, P., and Zimmerman, M.
- Subjects
Astrophysics - High Energy Astrophysical Phenomena - Abstract
We analyzed the 7.92$\times 10^{11}$ cosmic-ray-induced muon events collected by the IceCube Neutrino Observatory from May 13, 2011, when the fully constructed experiment started to take data, to May 12, 2023. This dataset provides an up-to-date cosmic-ray arrival direction distribution in the Southern Hemisphere with unprecedented statistical accuracy covering more than a full period length of a solar cycle. Improvements in Monte Carlo event simulation and better handling of year-to-year differences in data processing significantly reduce systematic uncertainties below the level of statistical fluctuations compared to the previously published results. We confirm the observation of a change in the angular structure of the cosmic-ray anisotropy between 10 TeV and 1 PeV, more specifically in the 100-300 TeV energy range.
- Published
- 2024
96. Geodesic Trees and Exceptional Directions in FPP on Hyperbolic Groups
- Author
-
Basu, Riddhipratim and Mj, Mahan
- Subjects
Mathematics - Probability ,Mathematics - Group Theory ,Mathematics - Geometric Topology ,60K35, 82B43, 20F67 (20F65, 51F99, 60J50) - Abstract
We continue the study of the geometry of infinite geodesics in first passage percolation (FPP) on Gromov-hyperbolic groups G, initiated by Benjamini-Tessera and developed further by the authors. It was shown earlier by the authors that, given any fixed direction $\xi\in \partial G$, and under mild conditions on the passage time distribution, there exists almost surely a unique semi-infinite FPP geodesic from each $v\in G$ to $\xi$. Also, these geodesics coalesce to form a tree. Our main topic of study is the set of (random) exceptional directions for which uniqueness or coalescence fails. We study these directions in the context of two random geodesics trees: one formed by the union of all geodesics starting at a given base point, and the other formed by the union of all semi-infinite geodesics in a given direction $\xi\in \partial G$. We show that, under mild conditions, the set of exceptional directions almost surely has a strictly smaller Hausdorff dimension than the boundary, and hence has measure zero with respect to the Patterson-Sullivan measure. We also establish an upper bound on the maximum number of disjoint geodesics in the same direction. For groups that are not virtually free, we show that almost surely exceptional directions exist and are dense in $\partial G$. When the topological dimension of $\partial G$ is greater than one, we establish the existence of uncountably many exceptional directions. When the topological dimension of $\partial G$ is $n$, we prove the existence of directions $\xi$ with at least $(n+1)$ disjoint geodesics. Our results hinge on deep facts about hyperbolic groups. En route, we also establish facts about the structure of random bigeodesics that substantially strengthen prior results., Comment: v2: 43 pages, 2 figures. References added. Section 5.2 added
- Published
- 2024
97. History and Habitability of the LP 890-9 Planetary System
- Author
-
Barnes, Rory, Amaral, Laura N. R. do, Birky, Jessica, Carone, Ludmila, Driscoll, Peter, Livesey, Joseph R., Graham, David, Becker, Juliette, Cui, Kaiming, Schlecker, Martin, Garcia, Rodolfo, Gialluca, Megan, Adams, Arthur, Ahmed, MD Redyan, Bonney, Paul, Broussard, Wynter, Chawla, Chetan, Damasso, Mario, Danchi, William C., Deitrick, Russell, Ducrot, Elsa, Fromont, Emeline F., Gaches, Brandt A. L., Gupta, Sakshi, Hill, Michelle L., Jackman, James A. G., Janin, Estelle M., Karawacki, Mikolaj, Koren, Matheus Daniel, La Greca, Roberto, Leung, Michaela, Miranda-Rosete, Arturo, Olohoy, Michael Kent A., Ngo, Cecelia, Paul, Daria, Sahu, Chandan Kumar, Sarkar, Debajyoti Basu, Shadab, Mohammad Afzal, Schwieterman, Edward W., Sedler, Melissa, Texeira, Katie, Vazan, Allona, Vega, Karen N. Delgado, Vijayakumar, Rohit, and Wojack, Jonathan T.
- Subjects
Astrophysics - Earth and Planetary Astrophysics - Abstract
We present numerous aspects of the evolution of the LP 890-9 (SPECULOOS-2/TOI-4306) planetary system, focusing on the likelihood that planet c can support life. We find that the host star reaches the main sequence in 1 Gyr and that planet c lies close to the inner boundary of the habitable zone. We find the magma ocean stage can last up to 50 Myr, remove 8 Earth-oceans of water, and leave up to 2000 bars of oxygen in the atmosphere. However, if the planet forms with a hydrogen envelope as small as 0.1 Earth-masses, no water will be lost during the star's pre-main sequence phase from thermal escape processes. We find that the planets are unlikely to be in a 3:1 mean motion resonance and that both planets tidally circularize within 0.5 Gyr when tidal dissipation is held constant. However, if tidal dissipation is a function of mantle temperature and rheology, then we find that planet c's orbit may require more than 7 Gyr to circularize, during which time tidal heating may reach hundreds of terawatts. We thus conclude that the habitability of planet c depends most strongly on the initial volatile content and internal properties, but no data yet preclude the viability of an active biosphere on the planet., Comment: 16 pages, 9 figures, accepted to PSJ
- Published
- 2024
98. Preference-based Pure Exploration
- Author
-
Shukla, Apurv and Basu, Debabrota
- Subjects
Statistics - Machine Learning ,Computer Science - Machine Learning - Abstract
We study the preference-based pure exploration problem for bandits with vector-valued rewards. The rewards are ordered using a (given) preference cone $\mathcal{C}$ and our goal is to identify the set of Pareto optimal arms. First, to quantify the impact of preferences, we derive a novel lower bound on sample complexity for identifying the most preferred policy with a confidence level $1-\delta$. Our lower bound elicits the role played by the geometry of the preference cone and punctuates the difference in hardness compared to existing best-arm identification variants of the problem. We further explicate this geometry when the rewards follow Gaussian distributions. We then provide a convex relaxation of the lower bound and leverage it to design the Preference-based Track and Stop (PreTS) algorithm that identifies the most preferred policy. Finally, we show that the sample complexity of PreTS is asymptotically tight by deriving a new concentration inequality for vector-valued rewards.
- Published
- 2024
99. MAKING SPACE FOR ‘SCIENCE’ IN A COLONIAL CITY : A STUDY OF BASU VIGYAN MANDIR
- Author
-
Mitra, Sandipan
- Published
- 2017
100. 1) H_o Shipra Nandi 2) H_o Arun Ghosh 3) H_o Basu Sarkar 4)basu Sarkar 5) Sabujpally More 6) H_o Sadhan Mukherjee 7) H_o Abinash Halder 8) H_o Hiru Das 9)h_o Mithun Pahari 10) H_o Mintu Das 11)h_o Babla Bank 12) H_o Fulia
- Subjects
Banks (Finance) ,Business, international - Abstract
Tenders are invited for 1) H_o Shipra Nandi 2) H_o Arun Ghosh 3) H_o Basu Sarkar 4)Basu Sarkar 5) Sabujpally More 6) H_o Sadhan Mukherjee 7) H_o Abinash Halder 8) [...]
- Published
- 2024
Catalog
Discovery Service for Jio Institute Digital Library
For full access to our library's resources, please sign in.