Skip to content

A Recurrence Converse for Identity Persistence: The Verdict Channel and the Storage–Persistence Capacity Gap

Sep 2026 · PhilPapers (PhilPapers Foundation)

Abstract

Abstract This paper characterizes recurrence and distinguishable-history capacity in finite declared identity regimes. For the class-indexed observable, the central quantity is the logarithm of the spectral radius of the reachable recurrent subgraph. A recurrence converse bounds sound retention codes by this capacity, with matching attainability under the declared conventions, and separates extinction, bare recurrence and branching recurrence. For the continuing verdict-only channel, finite determinization gives an exact computable capacity. Every finite regime lies strictly below one bit per step, while an explicit family approaches that ceiling. A separate stopped-graph construction characterizes the terminating channel: operational words are label-images of walks, at most two words occur at each positive length, and the asymptotic rate is zero or negative infinity according to a reachable-cycle test. For transitions with nonnegative costs and budgets enforced at every prefix, the paper establishes a sublinear-budget characterization, a fixed-tilt spectral converse, and a restricted attainability result for a single recurrent block in the large-buffer limit. Countermodels show why feasible entry, expenditure order and the counted language cannot be omitted. The results are scoped to declared finite models; they do not establish physical resource costs or general autonomous self-improvement. Broader composition and capacity questions remain explicitly open.

Read PDF

Similar papers

#computer vision Open access Jun 2016

Software Development in Startup Companies: The Greenfield Startup Model

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. · 178 citations · ⚡14
#computer vision Open access Oct 2016

Software Startups - A Research Agenda

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. · 157 citations · ⚡17
#machine learning Review Open access Oct 2016

“Failures” to be celebrated: an analysis of major pivots of software startups

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. · 127 citations · ⚡15
#computer vision Review Open access May 2015

A survey study on major technical barriers affecting the decision to adopt cloud services

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. · 111 citations · ⚡8
#computer vision Conference Open access Dec 2013

Affordable and Energy-Efficient Cloud Computing Clusters: The Bolzano Raspberry Pi Cloud Cluster Experiment

The ongoing work building a Raspberry Pi cluster consisting of 300 nodes is presented, with potential use cases 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. · 110 citations · ⚡7
#computer vision Book Open access Mar 2017

On the Unhappiness of Software Developers

The results indicate that software developers are a slightly happy population, but the need for limiting the unhappiness of developers remains, and 219 factors representing causes of unhappiness while developing software are identified.

D. Graziotin, Fabian Fagerholm, Xiaofeng Wang et al. · 84 citations · ⚡6

Related blog posts

Microsoft Research Blog Oct 12, 2026

Simulating student learning for better AI tutoring

StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.