Blockchain Papers

Haroune Bendekkiche

This paper presents, to the best of our knowledge, the first formal mechanism design treatment of Quran 2:282 as a low-cost verification mechanism. It proves that the Quranic debt documentation mechanism drives the creditor's expected verification cost to zero in the costly state verification framework. It achieves this by creating ex ante evidence through writing and witnessing, and by introducing a dual deterrence system: a fixed internal moral cost and a detection-contingent legal penalty. The paper also offers two interpretative contributions. First, it shows that the Quranic witness rule is an early redundancy mechanism for error correction, anticipating the logic later formalized by Hamming (1950). Second, it proposes an economic reading of the terms safih, da'if, and the inability to dictate, arguing that the guardian who dictates with justice may be a qualified third-party verifier, not merely a relative.

Akira Sakurai, Taishi Nakai, Kazuyuki Shudo

When is honest Bitcoin mining rational? This question is central to the incentive design of proof-of-work blockchains. Sapirshtein et al. computationally derived near-tight lower and upper bounds on the incentive-compatibility threshold using a Markov Decision Process. Kiayias et al.'s Blockchain Mining Games instead derived theoretical lower and upper bounds. However, this theoretical approach has two limitations: its model restricts miners to a narrow action space and assumes idealized tie behavior, and its lower and upper bounds are far from tight. We resolve both limitations. We develop a more realistic model with a broader miner action space and asymmetric tie-breaking parameters $γ^-$ and $γ^+$. We then propose an algorithm that computes lower and upper bounds on the incentive-compatibility threshold with a maximum error of $9.98006\times10^{-4}$.

Grigorii Melnikov, Sebastian Müller, Nikita Polyanskii, Yury Yanovich

No abstract is available for this record.

Priyal Bhagwanani

Human societies, economic markets, and digital systems face a fundamental coordination prob- lem: how self-interested agents cooperate in the allocation and use of scarce resources. Across these domains, contention necessitates identity systems that inform coordination mechanisms and govern resource allocation. However, existing literature typically treats identity establishment and coordination as separate problems. Institutional economics often assumes resource identity as an exogenous feature of the environment, while distributed consensus algorithms focus on coordina- tion under the assumption that resource identity is already known and agreed upon. This separation limits our understanding of how identity architectures shape the cost, efficiency, and stability of cooperation. 1 Using game-theoretic modeling and agent-based simulations, this study employs an isomorphic framework linking distributed systems and social institutions to analyze resource contention and coordination. We deploy a Cryptographic Content-Addressed Version-Aware Distributed Mutual Exclusion architecture, supported by an open-source implementation, to model resource identity allocation among concurrent processes. Simulations involving up to 10,000 agents are executed on the developed computational platform to evaluate how decentralized resource identity formation influences coordination costs. By tracking these interactions, the model measures how the structural method used to establish resource identity affects the cost, efficiency, and stability of cooperation among anonymous self-interested agents. The simulations indicate that cryptographically derived resource identities can achieve Nash- Implementable incentive compatibility, enabling cooperative outcomes without requiring a coor- dinating authority beyond a ledger that functions as a passive institutional record whose state may be modified only through resource-specific operations. These computational findings demonstrate a broader coordination paradigm in which identity emerges endogenously from the originating environment or substrate in which the resource is created. When treated as an active institutional design choice, such identity architectures may reduce reliance on external consensus among intelli- gent agents by shifting coordination toward resource-centered state recognition maintained through a non-strategic ledger. This framework endows scarce resources in contention with intelligence through the electronic capability of endogenous, unique self-identification and ledger registration, enabling autonomous self-allocation to contending network agents—a mechanism that can transfer likely directly onto applications within the social sciences where allocation is consensus decided through an intelligent third party agent between independent contending agents. In attempt to provide resource itself the self-identification capability and participation in distribution to agents queueing for allocation, we see we are able to overcome computational cost in macro-structures. More generally, the results suggest that endogenous resource identity provides a framework for optimizing collective action and resolving contention across both digital platforms and broader social institutions. Keywords: resource identity, institutional coordination, cryptographic hashing, consensus protocols, game theory, agent-based modeling, mechanism design, distributed mutual exclusion, computational social science. 1 This paper is an independent writing sample submitted for graduate admission to the University of Chicago MACSS programme. It investigates the intersection of institutional economics, collective action theory, and distributed systems architecture. However, this research is not done for University of Chicago. The paper was not written specifically for this application; it reflects an independent research project undertaken in preparation for graduate study in computational social science. Research on isomorphic modelling for distibuted locking in computer networks: Cryptographic Content-Addressed Version-Aware Distributed Mutual Exclusion and corresponding codebase are available via GitHub (https://github.com/bpriyal/distcodelock/blob/main/README.md) and Zenodo (https://zenodo.org/ records/19634046).

Marius Lombard-Platet, Doron Zarchy

We present Aggios, a scalable and privacy preserving proxy voting system designed for frequent and large-scale elections such as Decentralized Autonomous Organizations (DAO), when storing votes on the bulletin board is expensive. To this end, Aggios introduces ‘aggregators’: entities to which voters delegate their votes, and who then post their batched proofs on the public ledger. Aggios achieves strong integrity guarantees: only authorized voters can vote, votes are counted correctly, voters are assured their vote is counted.

Yuzhe Zhang, Manvir Schneider, Qin Wang, Davide Grossi

Voting methods weighted by stakes are the fundamental governance paradigm in Proof-of-Stake (PoS) blockchains. Such a paradigm is known to be prone to power distortions: a few users possessing large stakes may completely control decision making, even without owning the totality of the stakes. We study this phenomenon through the lens of computational social choice, focusing on the extent of power imbalances in stake-weighted voting when power is quantified using the Penrose-Banzhaf power index. Our work presents both analytical and empirical contributions. Analytically, we demonstrate that while a perfect alignment between power and relative stake ownership is generally unattainable, it can be approximated in expectation under specific conditions. Empirically, using data from a real-world on-chain governance system (Project Catalyst), we provide a more fine-grained understanding of the power imbalances that are likely to occur in current stake-weighted governance systems.

Olena Onishchenko

No abstract is available for this record.

Alexander Braun, Niklas Haeusle

A first-order design task in blockchain-based decentralized autonomous organizations is to ensure that malicious actors are sanctioned. We show that, when voters act strategically and the system is insufficiently decentralized, payoff-matching bribes undermine the sanctioning of malicious actors under conventional governance. Our framework formalizes DAO voting mechanisms and lets us identify those that mitigate the problem. Stochastic voting decouples a tokenholder’s influence from the voting behavior of others. Thus, bribery-proofness can be restored in the presence of sufficiently centralized governance tokenholders. Alternatively, masked voting increases resilience against bribery. Our work contributes to the broader debate on the merits and pitfalls of decentralization and highlights the need to align governance mechanisms with the degree of decentralization in blockchain networks.

Geoffrey Broomhead, Sovereign Trust Node: Broomhead Private Sovereign Trust, geoffreybroomhead.eth

The witness/extractability framework was established in the General Witness Theorem across three otherwise-disjoint domains: combinatorial mathematics, common-law evidence, and economic ledgers. The framework’s predictive content licenses a stronger claim: any domain admitting a valid instantiation of the abstract setup is governed by the framework, whether or not the domain’s practitioners have noticed. This paper instantiates the framework in a fourth domain: distributed consensus under Byzantine fault tolerance. We prove the BFT Witness Asymmetry Theorem: the structural cost of operating without standing on Byzantine nodes is super-linear, exhibited at single-level non-extractability as the standard O(n²) communication lower bound (Dolev–Reischuk 1985). We then state the Hierarchical-Coalition Cost-Asymmetry Conjecture: under recursive Byzantine sub-coalitions of adversarially-chosen depth k, the communication lower bound grows as Ω(n^{k+1}).

changzheng zhou, ziqing zhou

The governance practice of decentralized autonomous organizations faces a deepparadox: token-voting mechanisms designed with the intention of decentralizationpersistently tilt toward centralization and oligarchy during operation. This paperreveals that the root of this predicament lies not only in the design of specificvoting rules but, more fundamentally, in an implicit presupposition of the theoretical paradigm that dominates such rule design—that the governance space hasbeen fully specified before operation begins. The revelation principle on whichtraditional mechanism design theory relies requires the designer to possess a prioriknowledge of the participants’ type space, yet when the very concepts of governance—such as “fairness,” “contribution,” or “membership”—themselves become objectsof dispute and reconstruction, the presupposition of a fixed type space ceases tohold. Drawing on Ostrom’s core insight concerning meta-rules within multi-levelinstitutional analysis, this paper distinguishes the governance levels of distributedautonomous organizations into operational rules, collective-choice rules, and metarules, and proposes a post-mechanism design paradigm centered on a cognitiveconstitution—shifting the designer’s role from “selector of optimal rules” to “steward of the rule-evolution ecosystem.” The paper further advances three meta-ruleprinciples of post-mechanism design: conceptual anchoring, cognitive diversity regularization, and pathological pruning, and discusses the engineering pathways fortranslating these principles into executable technical specifications. The paper argues that when “what constitutes optimal governance” is itself an open question,the core duty of the designer is not to answer this question but to ensure that thesystem possesses the capacity to continuously discover better answers.

Alvise Spanò, Lorenzo Benetollo, Michele Bugliesi, Silvia Crafà · 6 authors

As Distributed Ledger Technology and smart contracts continue to grow in popularity, there is increasing interest in developing more expressive programming abstractions for digital asset management, along with verification tools that ensure safety and correctness before deployment on blockchain platforms. Addressing this challenge, we introduce AlgoMove , a framework designed to improve smart contract development on the Algorand blockchain. While Algorand is widely recognized for its high performance, scalability, and secure consensus protocol, it still lacks high-level programming abstractions and strong language-based verification mechanisms. AlgoMove brings the Move language, renowned for its robust support for secure digital asset management, to the Algorand platform, adapting its abstractions to the underlying execution model. The result is a high-level, resource-oriented programming model that preserves the core principles of Move while adapting them to Algorand’s unique environment. We present a formal specification of AlgoMove and its encoding into TEAL, Algorand’s native assembly-level language, along with a proof of the soundness of this encoding. To demonstrate the practical value and expressive power of the framework, we provide a prototype implementation consisting of a Move-to-TEAL compilation system and an accompanying library for writing smart contracts. Beyond enhancing the Algorand smart contract ecosystem, AlgoMove is significant in its own right as part of a broader effort to bring advances in programming language theory and formal verification into the blockchain space. By balancing expressiveness, ease of use, and strong compile-time guarantees, we seek to meet the distinctive requirements of secure and reliable blockchain applications.

B. G. Anand kumar, M. Nikhil Kumar, T. Sravan Kumar, G. Janaki Ram · 6 authors

Explore the article titled A Trustworthy Voting Framework Using Aadhaar and Distributed Ledger Technology from IJIRT Volume 12, Issue 10. This study evaluates the effectiveness of teaching programs on waste management knowledge among women.

Mike P. Sinn

Website: https://manual.warondisease.org/knowledge/appendix/wishocracy-paper.html Abstract: Politicians' votes have near-zero correlation with citizen preferences (Gilens and Page, 2014). Elite preferences predict policy outcomes. No mechanism connects citizen preferences to electoral consequences for representatives. RAPPA: Millions of citizens answer simple pairwise questions ("How would you split \$100 between these two budget categories?"). Geometric mean aggregation produces population-level preference weights from sparse individual responses. Unlike approval voting or ranked choice, RAPPA captures preference *intensity*, not just what people want, but how much they care. Compare aggregated preferences to each legislator's voting record. Publish Citizen Alignment Scores. Channel campaign resources to high-alignment candidates through Incentive Alignment Bonds. The mechanism achieves three properties no prior system combines: minimal cognitive load (~20 comparisons per participant yields statistical convergence), preference intensity capture, and approximate strategy-proofness. At system scale, the Optimal Governance Trajectory reaches 56.7x (95% CI: 19.3x-304x) the Earth baseline after 20 years, raises average income to \$1.16 million (95% CI: \$395,118-\$6.22 million) versus \$20,483 on the status-quo path, reaches \$10.7 quadrillion (95% CI: \$3.64 quadrillion-\$57.2 quadrillion) in total output, and recovers roughly \$101 trillion (95% CI: \$83.3 trillion-\$191 trillion)/year in suppressed value ([The Political Dysfunction Tax](https://political-dysfunction-tax.warondisease.org)). Summary: Representative democracy suffers from an inescapable principal-agent problem where elected officials' incentives diverge from citizen welfare. Wishocracy introduces RAPPA (Randomized Aggregated Pairwise Preference Allocation), which aggregates citizen preferences through cognitively tractable pairwise comparisons and creates accountability via Citizen Alignment Scores that channel electoral resources toward politicians who actually represent what citizens want.

Kevin Fathi

We present two new proofs of the Gibbard–Satterthwaite theorem, the foundational result in social choice theory establishing that every surjective, strategy-proof social choice function on three or more alternatives is dictatorial. Both proofs share a common engine—the Mutual Exclusion of Influence (a six-line theorem showing that two voters cannot both control the same alternative pair at a shared profile while ranking the pair differently)—but diverge in how they derive dictatorship from this principle. The first proof is purely combinatorial: mutual exclusion combined with a transition sequence identifies a uniquely decisive voter without constructing a classical pivotal voter. The second proof is information-theoretic: under the uniform distribution on preference profiles, strategy-proofness yields an exact identity relating conditional outcome entropy to option-set size. The zero-overlap theorem—a measure-theoretic consequence of mutual exclusion—forces influence entropy to concentrate entirely in a single voter, characterizing dictatorship as the unique entropy profile (log |X|, 0, …, 0) compatible with strategy-proofness and surjectivity. To our knowledge, the second proof is the first to establish the Gibbard–Satterthwaite theorem via Shannon-type information-theoretic quantities. The Mutual Exclusion Theorem itself is new and replaces the pivotal-voter construction across all four established proof routes with a single structural principle. Both proofs connect to the Adversarial Aggregation Channel (AAC) framework, in which the influence entropy corresponds to adversarial sub-channel capacity and the mutual exclusion principle instantiates a channel-capacity conservation law.

Felipe Lara

The Debreu Koopmans theorem restricts separable aggregation to at most one nonconvex component. We solve this by proving that a separable, additive or multiplicative, function is star quasiconvex, those with star shaped sublevel sets about minimizers, if and only if each component is star quasiconvex. This immediately yields star quasiconvexity of separable sums of quasiconvex functions, formally bridging diversification theory with the S shaped value functions of Prospect Theory. Furthermore, we develop a complete calculus, monotonic composition, pointwise minima, quasi arithmetic means, and we apply it to Cobb-Douglas functions, multifactor risk models, and constant function market makers in decentralized finance. Star quasiconvexity thus provides a unified framework for applications in optimization and economic modeling beyond the classical Debreu Koopmans constraint. The introduction discuss economic motivations.

Ali Sadhik Shaik

First-generation Decentralized Autonomous Organizations (DAOs) rely predominantly on "Coin-Voting" schemes (1 Token = 1 Vote). While permissionless, this model inevitably degrades into plutocracy, where capital centralization allows a minority of "Whales" to capture protocol utility. Furthermore, the liquidity of voting tokens exposes governance to "Flash Loan Attacks" and short-term rent-seeking. This paper introduces a novel governance primitive: Time-Decayed Stake-Weighted (TDSW) Voting. We propose a dual-class structure that weighs voting power not merely by capital magnitude, but by Capital Lock-Duration (Time) and Epistemic History (Merit). By introducing "Reputation Entropy"—where governance power decays automatically if not exercised - we solve the "Zombie Stake" problem and ensure that control remains with active, long-term contributors rather than passive capital aggregators. Author's Note: This paper is a foundational pillar of the Klyrox Protocol architecture, expanding upon the core framework published in The Klyrox Protocol: A Decentralized Framework for Optimistic Content Verification and Epistemic Reputation (available at: https://doi.org/10.5281/zenodo.18729968). It outlines the specific mechanics underpinning the concept of "Epistemic Capital," as explored in the complete five-volume series, The Algorithmic Monographs (The Algorithmic Invisible Hand, The Republic of Code, The Market for Truth, The Heavy Metal Intelligence, and The Synthetic C-Suite).

Sean Hash

In a multipolar world with no trusted monetary coordinator, how do rational actors settle large-value transactions across trust boundaries? We model this as a non-cooperative game—the "Exit Game"—in which capital allocators choose between capturable settlement systems ("Stay") and neutral settlement ("Exit"). The model rests on four empirical axioms: persistent multipolarity, rational self-interest, computational hardness, and network effect persistence. We prove three results. First, the payoff advantage of Exit over Stay is strictly increasing in adoption: every term in the payoff differential favors Exit under maintained monotonicity conditions, and each actor's adoption threshold approaches zero under structural debasement (Theorem 1). Second, no coalition can sustain coordinated Stay, because permissionless access makes defection costless and the first defector captures fleeing capital (Theorem 2). Third, the resulting equilibrium is absorbing: the monotone adoption process converges to full adoption once a critical mass is reached, because trust conditions required for coordinated return cannot be reestablished (Theorem 3). The model is explicitly falsifiable: six conditions are identified under which the central claims would fail. Bitcoin is the unique asset satisfying the necessary properties for neutral settlement—a result proved by systematic elimination across seven asset classes in Hash (2026b).

Felipe Lara

The Debreu–Koopmans theorem [14] restricts separable aggregation to at most one nonconvex component. We solve this by proving that a separable (additive or multiplicative) function is star quasiconvex (those with star-shaped sublevel sets about minimizers) if and only if each component is star quasiconvex. This immediately yields star quasiconvexity of separable sums of quasiconvex functions, formally bridging diversification theory with the S-shaped value functions of Prospect Theory. Furthermore, we develop a complete calculus (monotonic composition, pointwise minima, quasi-arithmetic means) and we apply it to Cobb-Douglas functions, multi-factor risk models, and constant function market makers in decentralized finance. Star quasiconvexity thus provides a unified framework for economic modeling beyond the classical Debreu–Koopmans constraint.

Mohammad Muavia

The Deflated Sharpe Ratio (Bailey and López de Prado, 2014) corrects an observed Sharpe ratio for the number of trials N behind it, separating genuine skill from the selection bias of a large backtest search. Its practical weakness is structural: N is supplied by the same researcher whose result it constrains. A search over a thousand configurations, reported as a single trial, satisfies the formula while defeating its purpose. The correction is sound; its input is self-reported. We present a construction that removes the researcher's discretion over that input. The trial set is committed to a Merkle tree before evaluation; the trial count N is the leaf count of the tree, not a reported scalar; and the winning strategy is bound, inside a zero-knowledge proof (a STARK), to be the maximum over the committed leaves. The deflation is then recomputed in-circuit on Merkle-pinned prices, net of a cost model the credential discloses, so the figure an allocator reads is derived by the circuit rather than asserted by the manager. The output is a credential, checkable by anyone, in seconds, without disclosure of the strategy, whose anti-overfitting correction cannot be understated within the committed search. We give the commitment scheme and its in-circuit binding; state precisely the manipulation it eliminates (understating N, cherry-picking a non-maximal winner, softening the cost model) and the residual trust it does not (off-ledger trials, closed only by forward pre-registration); and report a live implementation that additionally computes, in-circuit, the Probability of Backtest Overfitting over all C(16,8) = 12,870 combinatorially-symmetric splits (via recursive proof composition), together with the Probabilistic Sharpe Ratio and Hansen's Superior Predictive Ability. We demonstrate the system on its own flagship strategy, which it rules not significant (DSR 0.68, below the 0.95 bar), and publish that failure as the reference credential.

Dr.Scient. M.Phil. M.D. Paul A. Torvund

No abstract is available for this record.

Sharvina Srivastava

Most decentralized autonomous organizations (DAOs) use a 1-Token-1-Vote rule, allowing capital ownership to translate directly into governance power. This paper evaluates how a Quadratic Voting (QV)-inspired square-root reweighting counterfactual would affect voting outcomes in the Arbitrum DAO. For this, a time-paginated pipeline was developed to retrieve approximately 850,000 off-chain Snapshot vote records across fifteen of the DAO's highest-turnout proposals where each participating wallet's token-weighted voting power was replaced with its square root, and the proposal outcomes were recalculated. The results reveal extreme concentration of voting power, with a mean Gini coefficient of approximately 0.9950 among active participating wallets. In some proposals, the ten largest participating wallets or delegates collectively controlled as much as 86.87% of the total voting weight. Consequently, square-root reweighting changed the winning outcome in four of the fifteen proposals (26.7% of this purposively-selected, high-turnout sample), demonstrating that these outcomes were sensitive to the distribution of voting power across wallets. Its effect on victory margins was heterogeneous: margins widened in six proposals and narrowed in nine, with changes ranging from a 55.90-percentage-point expansion to a 37.76-percentage-point contraction. Notably, all four outcome reversals involved funding, grants, security expenditure, coalition financing, or related resource-allocation decisions. These findings suggest that square-root reweighting can alter both the magnitude and direction of token-weighted governance outcomes by reducing the relative influence of highly concentrated token holdings.

Massimo Franceschet, Enrico Bozzo

Token-based voting systems are increasingly adopted in digital governance contexts such as decentralized autonomous organizations and participatory budgeting, yet their standard aggregation rules often lead to undesirable outcomes, including oligarchic dominance or voter apathy. This paper introduces a general mathematical framework for token-based voting that interpolates between one-person-one-vote and one-token-onevote paradigms through the notion of radical voting functions. These functions map voting tokens to actual votes via concave transformations that preserve incentives for participation while compressing excessive voting power. We formalize consensus as an aggregation of transformed votes and study its structural properties using tools from convex analysis and majorization theory. We show that radical voting functions reward broad and evenly distributed support and penalize highly concentrated voting patterns, thereby favoring pluralistic outcomes over individualistic ones. Quadratic voting emerges as a special case within this framework, characterized by linear marginal voting costs. The analysis is extended to account for voter heterogeneity by incorporating similarity measures into the consensus function, linking voting outcomes to diversity among participants. Overall, the framework provides a principled foundation for designing voting mechanisms that balance merit, inclusiveness, and resistance to capture in token-based governance systems.

Rujia Li, Mingfei Zhang, Xueqian Lu, Wenbo Xu · 6 authors

No abstract is available for this record.

Qais Alassa

Decentralized reputation mechanisms certify trust by making agents spend a scarce resource: computation (Proof of Work), capital (Proof of Stake), or identity (Proof of Personhood). In all three the resource is orthogonal to the quality being certified — a well-capitalized agent is not a skilled one. We study the construction in which the spent resource is the certified competence: Proof of Calibration, in which pseudonymous agents commit probabilistic predictions, outcomes resolve against ground truth, and reputation accrues through a strictly proper scoring rule. Building on the merit-gating results of Calibration-Gated Reputation (Alassa and Alashqar, SSRN 6505678), we replace that paper's concentration estimates with an exact theory. The realized mean score of an identity is a linear function of a single sufficient statistic — its empirical outcome frequency p̂ — so passing a merit bar is exactly the event that p̂ reaches an "alibi frequency" q_c, and the price of that event is an information divergence: the Sybil-lottery success probability is controlled, two-sidedly for all K and all N beyond a mild explicit threshold, by e^(−N·KL(q_c‖p)). Strict propriety is precisely positivity of this rate at every dishonest report, unifying the companion paper's impossibility and merit-gating theorems as the zero- and positive-rate regimes of one scalar. The theory is exact enough to reproduce, with zero free parameters, every Monte Carlo experiment of the companion suite, including the finite-size deviations from the asymptotic ε⁻⁴ cold-start law. Two structural results follow. First, the gate has two margins: in expectation, the adversary's best response is honesty and the margin is the generalized-entropy gap; at the event level, the optimal attack is skill-mimicry — report the bar's skill, not your own — and the margin is min{KL(p_h‖p_a), KL(1−p_h‖p_a)}, the divergence between the skills themselves, identical across all strictly proper, outcome-symmetric rules. The gate's security exponent is a property of the skills, not of the rule. Second, Sybil amplification requires independent evidence: identities scored on a shared outcome stream gain almost nothing from their number. Finally, the gate is not merely sound but optimal: no local pseudonymous mechanism that admits honest bar-skill agents with non-vanishing probability achieves a soundness exponent exceeding KL(p_h‖p_a), and the strictly proper gate attains it — it is the Neyman–Pearson test of the skill hypothesis. The composite Notch Score reduces to the same single statistic, yielding an exact calibration-weight floor.