Sep 2026· Zenodo (CERN European Organization for Nuclear Research)
Abstract
We propose that consciousness is a phase transition of a non-equilibrium dissipative structure, characterised by two independently controlled channels that must both be driven past threshold. The central result is an exclusion criterion: a macroscopic dissipative structure cannot be conscious unless it satisfies three necessary conditions - (i) an energy channel G > 1 maintaining non-equilibrium pumping, (ii) an information channel G_info(kappa) > 1 maintaining global phase coherence (with analytic critical point kappa_c = 1.8809), and (iii) topological closure via a self-referential triad (|SCC| >= 3). The framework traces a single causal chain: non-equilibrium driving -> Brusselator Hopf bifurcation -> sigmoid threshold -> phase-amplitude coupling (PAC) -> von Mises phase density -> Kuramoto network amplification -> G_info > 1 -> conscious phase transition. Each stage is derived from first principles (Appendices C-G). At the microscopic level, a basis-free trace-distance order parameter O(g) = 1/2 tr|rho+ - rho-| in two-qubit Gorini-Kossakowski-Sudarshan-Lindblad (GKSL) systems rigorously proves that the energy and information channels are independently controllable: a symmetrisation scan collapses O(g) from 0.306 to < 10^-4 as the absorption/emission asymmetry is removed, while a separate dephasing scan destroys coherence-carried asymmetry without affecting the energy flow. The topological closure condition is instantiated at multiple physical scales by a self-referential triad of three irreducible roles - reversible carrier, energy currency, irreversible anchor - which we identify in quantum coherence, aerobic metabolism, neural dynamics, and planetary geochemistry. We demonstrate the framework's explanatory power through clinical neuroscience and artificial intelligence. General anaesthesia abolishes consciousness by selectively collapsing kappa below threshold while metabolic pumping persists - a channel dissociation no single-channel theory predicts. Mindfulness meditation acts as a phase-locking mechanism that elevates kappa past kappa_c by suppressing Default Mode Network noise. Feedforward large language models fail all three conditions: their computational graph is acyclic, sustains no limit cycle, and operates as a closed system at inference. The widely observed model collapse under recursive self-training is the thermodynamic signature of the system relaxing toward equilibrium.
GAOKAO-Bench is introduced, an intuitive benchmark that employs questions from the Chinese GAOKAO examination as test samples, including both subjective and objective questions that contribute a robust evaluation benchmark for future large language models and offers valuable insights into the advantages and limitations of such models.
Xiaotian Zhang, Chun-yan Li, Yi Zong et al.· arXiv.org· 216 citations· ⚡17
Software startups are newly created companies with no operating history and oriented towards producing cutting-edge products. However, despite the increasing importance of startups in the economy, few scientific studies attempt to address software engineering issues, especially for early-stage startups. If anything, startups need engineering practices of the same level or better than those of larger companies, as their time and resources are more scarce, and one failed project can put them out of business. In this study we aim to improve understanding of the software development strategies employed by startups. We performed this state-of-practice investigation using a grounded theory approach. We packaged the results in the Greenfield Startup Model (GSM), which explains the priority of startups to release the product as quickly as possible. This strategy allows startups to verify product and market fit, and to adjust the product trajectory according to early collected user feedback. The need to shorten time-to-market, by speeding up the development through low-precision engineering activities, is counterbalanced by the need to restructure the product before targeting further growth. The resulting implications of the GSM outline challenges and gaps, pointing out opportunities for future research to develop and validate engineering practices in the startup context.
Carmine Giardino, Nicolò Paternoster, M. Unterkalmsteiner et al.· IEEE Transactions on Softwar...· 179 citations· ⚡14
Software startup companies develop innovative, software-intensive products within limited timeframes and with few resources, searching for sustainable and scalable business models. Software startup ...
M. Unterkalmsteiner, P. Abrahamsson, Xiaofeng Wang et al.· e-Informatica Software Engin...· 157 citations· ⚡17
In the context of software startups, project failure is embraced actively and considered crucial to obtain validated learning that can lead to pivots. A pivot is the strategic change of a business concept, product or the different elements of a business model. A better understanding is needed on different types of pivots and different factors that lead to failures and trigger pivots, for software entrepreneurial teams to make better decisions under chaotic and unpredictable environment. Due to the nascent nature of the topic, the existing research and knowledge on the pivots of software startups are very limited. In this study, we aimed at identifying the major types of pivots that software startups make during their startup processes, and highlighting the factors that fail software projects and trigger pivots. To achieve this, we conducted a case survey study based on the secondary data of the major pivots happened in 49 software startups. 10 pivot types and 14 triggering factors were identified. The findings show that customer need pivot is the most common among all pivot types. Together with customer segment pivot, they are common market related pivots. The major product related pivots are zoom-in and technology pivots. Several new pivot types were identified, including market zoom-in, complete and side project pivots. Our study also demonstrates that negative customer reaction and flawed business model are the most common factors that trigger pivots in software startups. Our study extends the research knowledge on software startup pivot types and pivot triggering factors. Meanwhile it provides practical knowledge to software startups, which they can utilize to guide their effective decisions on pivoting.
Sohaib Shahid Bajwa, Xiaofeng Wang, Anh Nguyen-Duc et al.· Empirical Software Engineeri...· 127 citations· ⚡15
In the context of cloud computing, risks associated with underlying technologies, risks involving service models and outsourcing, and enterprise readiness have been recognized as potential barriers for the adoption. To accelerate cloud adoption, the concrete barriers negatively influencing the adoption decision need to be identified. Our study aims at understanding the impact of technical and security-related barriers on the organizational decision to adopt the cloud. We analyzed data collected through a web survey of 352 individuals working for enterprises consisting of decision makers as well as employees from other levels within an organization. The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability. The result from our logistic regression analysis confirms the criticality of the security concern, which results in an up to 26-fold increase in the non-adoption likelihood. Our study 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
We present our ongoing work building a Raspberry Pi cluster consisting of 300 nodes. The unique characteristics of this single board computer pose several challenges, but also offer a number of interesting opportunities. On the one hand, a single Raspberry Pi can be purchased cheaply and has a low power consumption, which makes it possible to create an affordable and energy-efficient cluster. On the other hand, it lacks in computing power, which makes it difficult to run computationally intensive software on it. Nevertheless, by combining a large number of Raspberries into a cluster, this drawback can be (partially) offset. Here we report on the first important steps of creating our cluster: how to set up and configure the hardware and the system software, and how to monitor and maintain the system. We also discuss potential use cases for our cluster, the two most important being an inexpensive and green test bed for cloud computing research and a robust and mobile data center for operating in adverse environments.
P. Abrahamsson, S. Helmer, Nattakarn Phaphoom et al.· IEEE International Conferenc...· 110 citations· ⚡7