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MAP-based Problem-Agnostic Diffusion Model for Inverse Problems

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arXiv 2025年

作者： Tao, Pingping Liu, Haixia Su, Jing Yang, Xiaochen Tan, Hongchen Shandong University Library No. 180 West Culture Road Shandong Weihai264209 China School of Mathematics and Statistics Hubei Key Laboratory of Engineering Modeling and Scientific Computing Institute of Interdisciplinary Research for Mathematics and Applied Science Huazhong University of Science and Technology No. 1037 Luoyu road Hubei Wuhan430074 China Dapartment of Basic Sciences Dalian University of Science and Technology No. 999-26 Harbor Road Liaoning Dalian116052 China School of Computer Science and Technology Harbin Institute of Technology No. 2 West Culture Road Shandong Weihai264209 China Institute of Future Technology Dalian University of Technology No. 2 Lingong Road Liaoning Dalian116081 China

Diffusion models have indeed shown great promise in solving inverse problems in image processing. In this paper, we propose a novel, problem-agnostic diffusion model called the maximum a posteriori (MAP)-based guided term estimation method for inverse problems. To leverage unconditionally pretrained diffusion models to address conditional generation tasks, we divide the conditional score function into two terms according to Bayes’ rule: an unconditional score function (approximated by a pretrained score network) and a guided term, which is estimated using a novel MAP-based method that incorporates a Gaussian-type prior of natural images. This innovation allows us to better capture the intrinsic properties of the data, leading to improved performance. Numerical results demonstrate that our method preserves contents more effectively compared to state-of-the-art methods—for example, maintaining the structure of glasses in super-resolution tasks and producing more coherent results in the neighborhood of masked regions during inpainting. Our numerical implementation is available at https://***/liuhaixias1/ MAP-DIFFUSION-IP. Copyright © 2025, The Authors. All rights reserved.

关键词： Inverse problems

GW190521: Tracing imprints of spin-precession on the most massive black hole binary

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arXiv 2023年

作者： Miller, Simona J. Isi, Maximiliano Chatziioannou, Katerina Varma, Vijay Mandel, Ilya Department of Physics California Institute of Technology PasadenaCA91125 United States LIGO Laboratory California Institute of Technology PasadenaCA91125 United States Center for Computational Astrophysics Flatiron Institute New YorkNY10010 United States Department of Mathematics Center for Scientific Computing and Data Science Research University of Massachusetts DartmouthMA02747 United States Max Planck Institute for Gravitational Physics Albert Einstein Institute PotsdamD-14476 Germany School of Physics Astronomy Monash University ClaytonVIC3800 Australia OzGrav: The ARC Centre of Excellence for Gravitational Wave Discovery ClaytonVIC3800 Australia

GW190521 is a remarkable gravitational-wave signal on multiple fronts: its source is the most massive black hole binary identified to date and could have spins misaligned with its orbit, leading to spin-induced precession;an astrophysically consequential property linked to the binary's origin. However, due to its large mass, GW190521 was only observed during its final 3-4 cycles, making precession constraints puzzling and giving rise to alternative interpretations, such as eccentricity. Motivated by these complications, we trace the observational imprints of precession on GW190521 by dissecting the data with a novel time domain technique, allowing us to explore the morphology and interplay of the few observed cycles. We find that precession inference hinges on a quiet portion of the pre-merger data that is suppressed relative to the merger-ringdown. Neither pre-merger nor post-merger data alone are the sole driver of inference, but rather their combination;in the quasi-circular scenario, precession emerges as a mechanism to accommodate the lack of a stronger pre-merger signal in light of the observed post-merger. In terms of source dynamics, the pre-merger suppression arises from a tilting of the binary with respect to the observer. Establishing such a consistent picture between the source dynamics and the observed data is crucial for characterizing the growing number of massive binary observations and bolstering the robustness of ensuing astrophysical claims. © 2023, CC BY.

关键词： Stars

Automation Intervention for Monitoring Agriculture Farming Scale: A Review

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Automation Intervention for Monitoring Agriculture Farming S...

International Conference on computing and Networking Technology (ICCNT)

作者： Kapil Joshi Santosh Kumar Shruti Bhatla Vishal Kaushik Harishchander Anandaram Anil Kumar Department of CSE Uttaranchal Institute of Technology Uttaranchal University Dehradun India Department of Mathematics Sharda School of Basic Sciences and Research Sharda University Greater Noida UP India Department of Computer Science and Engineering Graphic Era Hill University Dehradun Uttarakhand India School of Computer Science UPES Dehradun India Centre for Computational Engineering and Networking Amrita Vishwa Vidyapeetham Coimbatore Tamil Nadu India School of Computing DIT University Dehradun India

Agricultural data is only valuable when it has been managed successfully. As data has evolved into the fundamental ingredient in contemporary agriculture to assist farmers with vital decision, latest developments in managing data are causing Smart Agriculture to rise dramatically. With factual information obtained by sensors, significant advantages emerge with the goal of enhancing production and ecology. This type of data-driven farm management is built on information that can boost efficiency by preventing resource waste and contamination of the ecosystem. Data-driven farming, with the assistance of automated solutions using artificial intelligence techniques, lays the groundwork for potential sustainable *** article analyses the current state of sophisticated agricultural systems by rehashing each critical step, from data processing in field crops to variable interest rate implementations, so that farmers can make optimised decision making to save funds while safeguarding the natural environment and converting how meal would be generated to meet the upcoming population explosion.

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Comparing the Life Cycle Carbon Impact of Conventional and Biogenic Building Materials Across Major Residential Typologies in Ghana and Senegal

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SSRN

SSRN 2023年

作者： Lokko, Mae-Ling Manu, Frederick Wireko Mboup, Nzinga Aly Etman, Mohamed A. Raugei, Marco Niang, Ibrahim Ametepe, Kingdom Sarfo-Mensah, Rosemary Yale University United States Building and Road Research Institute Council for Scientific and Industrial Research Ghana Worofila Senegal Senegal School of Engineering Computing and Mathematics Oxford Brookes University Wheatley OxfordOX33 1HX United Kingdom Center for Life Cycle Assessment Columbia University New YorkNY10027 United States AARMBN Senegal Senegal Zambia

Across West African cities, patterns of high greenhouse gas emissions are driven by the widespread importation and adoption of high embodied carbon building materials by a largely self-built industry and recurring operational carbon costs driven by increased access to fossil-fuel based energy services. Life cycle assessments of major residential typologies in Ghana and Senegal investigates the comparative greenhouse gas emissions of imported building materials with local alternative materials within conventional housing typologies. Results indicate that low-rise detached housing typologies have the highest greenhouse emissions and four-storey apartment typologies, the lowest. Given the equatorial location of both contexts, the integration of insulation materials within low-rise conventional roofing assemblies had the largest potential to reduce energy related GHG emissions during the operational phase by a factor of 4 to 5, thereby far outweighing up-front "embodied" emissions. While vertical expansion of housing represents an important driver in reducing greenhouse gas emissions per capita, 10-12% increases in greenhouse gas emissions associated with higher reinforced concrete mass ratios were observed with each additional storey. Tradeoffs in higher embodied carbon associated with optimizing geogenic material for passive climatic performance in local climate, demonstrate recurring low operational carbon emissions over the lifetime of the building. © 2023, The Authors. All rights reserved.

关键词： Life cycle

Incorporating AI and IoT for Smart Poultry Monitoring and Health Detection

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Incorporating AI and IoT for Smart Poultry Monitoring and He...

Augmented Intelligence and Sustainable Systems (ICAISS), International Conference on

作者： Kapil Joshi Arun Kumar Harishchander Anandaram Anil Kumar Ambika Aggarwal Gunjan Chhabra Department of CSE Uttaranchal Institute of Technology Uttaranchal University Dehradun India Department of Mathematics Sharda School of Basic Sciences and Research Sharda University Greater Noida India Centre for Computational Engineering and Networking Amrita School of Artificial Intelligence Coimbatore India School of Computing DIT University Dehradun India Department of CSE UPES Dehradun India Department of CSE Graphic Era Hill University Dehradun India

One vital sector of animal husbandry, poultry farming, is moving towards scale, intelligence, and automated operations. The emergence of digital technology has significantly improved a number of fields. An extensive analysis of the literature is presented in this paper, with a focus on AI-enabled IoT applications for managing poultry health and well-being. This study primarily centred on chicken welfare, considering modern poultry husbandry is challenged with problems pertaining to standardised criteria for welfare evaluation and reliable monitoring methods, notably for broiler wellness and disease outbreak prevention. There is a compelling rationale for using contemporary technology to continually monitor big farms with millions of birds and increase overall production. This is because there are now increasingly affordable processing resources, IoT sensors, and standard algorithms available. The most important sources of protein in the diet are eggs and poultry, thus poultry farm oversight should prioritize the use of cutting-edge technology solutions. As a result, this study presents a systematic review of the most cutting-edge IoT systems with AI capabilities as well as their most recent developments in the creation of smart systems in this field. The study also explores the benefits and problems that AI and IoT present for chicken farming.

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EXPLICIT RUNGE–KUTTA METHODS THAT ALLEVIATE ORDER REDUCTION

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arXiv 2023年

作者： Biswas, Abhijit Ketcheson, David I. Roberts, Steven Seibold, Benjamin Shirokoff, David Computer Electrical and Mathematical Sciences & Engineering Division King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia Center for Applied Scientific Computing Lawrence Livermore National Laboratory LivermoreCA94550 United States Department of Mathematics Temple University PhiladelphiaPA19122 United States Department of Mathematical Sciences New Jersey Institute of Technology NewarkNJ07102 United States

Explicit Runge–Kutta (RK) methods are susceptible to a reduction in the observed order of convergence when applied to initial-boundary value problem with time-dependent boundary conditions. We study conditions on explicit RK methods that guarantee high-order convergence for linear problems;we refer to these conditions as weak stage order conditions. We prove a general relationship between the method’s order, weak stage order, and number of stages. We derive explicit RK methods with high weak stage order and demonstrate, through numerical tests, that they avoid the order reduction phenomenon up to any order for linear problems and up to order three for nonlinear *** Codes 65L04, 65L20, 65M12 Copyright © 2023, The Authors. All rights reserved.

关键词： Runge Kutta methods

Gravitational wave surrogate model for spinning, intermediate mass ratio binaries based on perturbation theory and numerical relativity

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arXiv 2024年

作者： Rink, Katie Bachhar, Ritesh Islam, Tousif Rifat, Nur E.M. González-Quesada, Kevin Field, Scott E. Khanna, Gaurav Hughes, Scott A. Varma, Vijay Department of Physics Center for Scientific Computing & Visualization Research University of Massachusetts DartmouthMA02747 United States Department of Physics Center for Gravitational Physics University of Texas AustinTX78712 United States Department of Physics Center for Computational Research University of Rhode Island East Hall KingstonRI02881 United States Kavli Institute for Theoretical Physics University of California Santa Barbara Kohn Hall Lagoon Rd Santa BarbaraCA93106 United States Kavli Institute for Theoretical Physics University of California Santa BarbaraCA93106 United States Department of Physics University of Virginia 1827 University Avenue CharlottesvilleVA22903 United States Case Western Reserve University ClevelandOH44106 United States Department of Mathematics Center for Scientific Computing & Visualization Research University of Massachusetts DartmouthMA02747 United States Department of Physics Massachusetts Institute of Technology CambridgeMA02139 United States

We present BHPTNRSur2dq1e3, a reduced order surrogate model of gravitational waves emitted from binary black hole (BBH) systems in the comparable to large mass ratio regime with aligned spin (χ1) on the heavier mass (m1). We trained this model on waveform data generated from point particle black hole perturbation theory (ppBHPT) with mass ratios varying from 3 ≤ q ≤ 1000 and spins from −0.8 ≤ χ1 ≤ 0.8. The waveforms are 13,500 m1 long and include all ≤ 4 spin-weighted spherical harmonic modes except the (4, 1) and m = 0 modes. We find that for binaries with χ1 −0.5, retrograde quasi-normal modes are significantly excited, thereby complicating the modeling process. To overcome this issue, we introduce a domain decomposition approach to model the inspiral and merger-ringdown portion of the signal separately. The resulting model can faithfully reproduce ppBHPT waveforms with a median time-domain mismatch error of 8 × 10−5. We then calibrate our model with numerical relativity (NR) data in the comparable mass regime (3 ≤ q ≤ 10). By comparing with spin-aligned BBH NR simulations at q = 15, we find that the dominant quadrupolar (subdominant) modes agree to better than ≈ 10−3 (≈ 10−2) when using a time-domain mismatch error, where the largest source of calibration error comes from the transition-to-plunge and ringdown approximations of perturbation theory. Mismatch errors are below ≈ 10−2 for systems with mass ratios between 6 ≤ q ≤ 15 and typically get smaller at larger mass ratio. Our two models – both the ppBHPT waveform model and the NR-calibrated ppBHPT model – will be publicly available through gwsurrogate and the Black Hole Perturbation Toolkit packages. © 2024, CC BY.

关键词： Perturbation techniques

LOWEST-DEGREE POLYNOMIAL DE RHAM COMPLEX ON GENERAL QUADRILATERAL GRIDS

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arXiv 2020年

作者： Qimengquan Ji, Xia Zhang, Shuo University of Chinese Academy of Sciences Beijing100190 China LSEC Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and System Sciences Chinese Academy of Sciences Beijing100190 China

This paper devotes to the construction of finite elements on grids that consist of general quadrilaterals not limited in parallelograms. Two finite elements are established for the H1 and H(rot) elliptic problems, respectively. The two finite element spaces on general quadrilateral grids, together with the space of piecewise constant functions, formulate a discretised de Rham complex. First order convergence rate can be proved for both of them under the asymptotic-parallelogram assumption on the grids. The local shape functions of the two spaces are piecewise polynomials, and the global finite element functions are nonconforming. A rigorous analysis is given in this paper that it is impossible to construct a practically useful finite element defined as Ciarlet’s triple whose shape functions are always piecewise polynomials and which can form conforming subspaces on a grid that consists of arbitrary quadrilaterals. Copyright © 2020, The Authors. All rights reserved.

关键词： Polynomials

Gravitational waves from black hole emission

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arXiv 2024年

作者： Islam, Tousif Khanna, Gaurav Liebling, Steven L. Kavli Institute of Theoretical Physics University of California Santa Barbara Santa BarbaraCA93106 United States Theoretical Astrophysics Walter Burke Institute for Theoretical Physics California Institute of Technology PasadenaCA91125 United States Department of Physics University of Massachusetts DartmouthMA02747 United States Department of Mathematics University of Massachusetts DartmouthMA02747 United States Center for Scientific Computing and Data Science Research University of Massachusetts DartmouthMA02747 United States Department of Physics Center for Computational Research University of Rhode Island KingstonRI02881 United States Long Island University BrookvilleNY11548 United States

Using adiabatic point-particle black hole perturbation theory, we simulate plausible gravitational wave (GW) signatures in two exotic scenarios (i) where a small black hole is emitted by a larger one (‘black hole emission’) and (ii) where a small black hole is emitted by a larger one and subsequently absorbed back (‘black hole absorption’). While such scenarios are forbidden in general relativity!(GR), alternative theories (such as certain quantum gravity scenarios obeying the weak gravity conjecture, white holes, and Hawking radiation) may allow them. By leveraging the phenomenology of black hole emission and absorption signals, we introduce straightforward modifications to existing gravitational waveform models to mimic gravitational radiation associated with these exotic events. We anticipate that these (incomplete but) initial simulations, coupled with the adjusted waveform models, will aid in the development of null tests for GR using GWs. Copyright © 2024, The Authors. All rights reserved.

关键词： Black holes