In a deuterium–helium-3 (D–^3He) tandem-mirror burner the fusion-born 14.68 MeV proton and 3.67 MeV alpha carry the overwhelming majority of the released power as fast, mirror-trapped ions. Left to thermalise, that energy is shared between electron drag and a broadly heated ion background whose confined, usefully recoverable share is small; the rest exits the loss cone as heat and inflates the recirculating power that sets the burner's engineering gain Q_E. RF alpha-channeling—a resonant wave that extracts perpendicular energy from a fusion product, hands it to the fuel ions, and simultaneously diffuses the spent ash toward the loss boundary—converts this loss into a directed gain. We formalise the mechanism as a bounce-averaged Fokker–Planck problem closed by a quasilinear cyclotron-resonant diffusion operator, derive the Fisch–Rax energy–position coupling E/=/n that makes channeling a bounded lever rather than a closure mechanism, and evaluate it at the frozen M-45 burner operating point (T_i=90 keV, n_e=2.6×10^20 m^-3, x_^3He=0.30, mirror-throat field B_m=17 T, central-cell field B_0c=5.50 T, effective mirror ratio R_mc=4.61). A reduced two-dimensional velocity-space kinetic solve, cross-checked against ray-tracing and particle-in-cell codes on the NVIDIA GPU HPC campaign, raises the recoverable charged fraction from a collisional baseline near 8% to about 80% and recovers up to 195 MW into the confined fuel ions—enough to cover the 40–110 MW plug-localised warm-fill RF cost with margin, while a full-volume warm fill (3.7 GW, 85% of P_ fus) is energetically precluded. We are explicit that this closes only under plug localisation (channeled power confined to 1–3% of the central-cell volume) and that the plant gain remains gated by the plug potential, not by channeling: the design-point Q_E=1.318 is untouched. Every headline quantity is a frozen anchor in the Kronos de-risking register.Key results (frozen anchors): n_e = 2.6 ×10^20; Frec = 8 %; f_n = 5.44 %.Live verification: 11 gate validator(s) with live-recompute cards (9 reproduced, 2 revised). See the Verification section and data/verification.csv.Related: Paper page · De-risking register · 3D model · Learn more about KronosPart of the 2026 Kronos publication series; independently re-run and stamped in the Kronos de-risking register (DOI 10.5281/zenodo.22645689).All numerical values are frozen design-point anchors; see the register.Public research artifact. No proprietary, financial, or supply-chain information is included.Note (REPLACE): This record replaces and supersedes DOI 10.5281/zenodo.22132168; please cite this version.
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.