On the Relation between Gravitational Field Line Deflection and Matter Spatial Configuration – A Modified Gravitational Theory Based on Geometric Principles
Sep 2026· Zenodo (CERN European Organization for Nuclear Research)
Cosmology and Gravitation Theories
Abstract
Newton’s law of universal gravitation has achieved extremely high verificationaccuracy within the solar system scale, and the geometric essence of its inverse-square law is the uniform diffusion of field lines on a spherical surface. However, ongalactic scales, there is a systematic deviation between the observed gravitationaleffects and the gravity expected solely from visible baryonic matter. Starting fromthe geometric principle of field line deflection, this paper proposes that this devi-ation originates from the modulation effect of matter spatial configuration on thespatial distribution of gravitational field lines. By establishing a three-point model(gravitational source A, deflection source B, observation point C), this paper de-rives the general expression for the gravitational correction factor Y , proving thatthe gravitational anomaly arises from the deflection of field lines in non-sphericallysymmetric matter distributions, which leads to changes in field line density at theobservation point. This paper further explores the geometric interpretation of ”massas area,” pointing out that in non-spherically symmetric cases, mass alone cannotuniquely determine the gravitational effect, and configuration information is an in-dependent physical degree of freedom. The theory presented in this paper does notrely on dark matter or modified gravity assumptions, extending Newtonian grav-ity from the ”spherically symmetric special case” to the general case of ”arbitraryconfigurations.”
The results are packaged in the Greenfield Startup Model (GSM), which explains the priority of startups to release the product as quickly as possible, and the need to shorten time-to-market, by speeding up the development through low-precision engineering activities.
Carmine Giardino, Nicolò Paternoster, M. Unterkalmsteiner et al.· IEEE Transactions on Softwar...· 178 citations· ⚡14
Software startup companies develop innovative, software-intensive products within limited timeframes and with few resources, searching for sustainable and scalable business models.
M. Unterkalmsteiner, P. Abrahamsson, Xiaofeng Wang et al.· e-Informatica Software Engin...· 157 citations· ⚡17
This study conducts a case survey study based on the secondary data of the major pivots happened in 49 software startups, and demonstrates that customer need pivot is the most common among all pivot types.
Sohaib Shahid Bajwa, Xiaofeng Wang, Anh Nguyen-Duc et al.· Empirical Software Engineeri...· 127 citations· ⚡15
The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.
Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al.· Journal of Systems and Softw...· 111 citations· ⚡8
This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.
Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al.· Journal of Systems and Softw...· 78 citations· ⚡6
The application of agile software methods and more recently the integration of Lean practices contribute to the trend of continuous improvement in the software industry. One such area warranting proper empirical evidence is a project’s operational efficiency when using the Kanban method. This short paper takes a new angle and explores waste in the Kanban-driven software development project context. A preliminary research model is presented for helping the consequent replication of the study. The results from the empirical analysis suggest Kanban can be an effective method in visualizing and organizing the current work, but does not prevent waste from creeping in, although the overall project outcome may be successful.
Marko Ikonen, Petri Kettunen, Nilay V. Oza et al.· EUROMICRO Conference on Soft...· 67 citations· ⚡9
Related blog posts
MIT News · Artificial Intelligence· news.mit.eduSep 14, 2026
The “HardFlow” algorithm could help generative AI models produce high-quality outputs that obey strict requirements when “pretty close” doesn’t cut it.
AI may appear weightless, but every model depends on physical infrastructure. To understand responsible AI, we need to look beyond algorithms and consider the entire lifecycle of the hardware behind them. The post Responsible AI Must Consider Its Afterlife appeared first on GPT-Lab.