This research package develops a set of theoretical and computational frameworks addressing several limiting problems in programmable post-lithographic nanofabrication: confinement of reactive chemistry, selective excitation of unresolved fabrication sites, preservation of structural geometry during scaffold-to-product conversion, and the coupling between chemical isolation and nanoscale mechanical stability. The work introduces the concept of a protected reaction port, in which productive chemistry is spatially separated from regions containing previously verified or damage-sensitive material. A reaction–diffusion model is derived for a locally unquenched reactive volume surrounded by an exterior scavenging region. Under the stated spherical transport model, the probability that a reactive intermediate reaches a distant vulnerable boundary can decrease exponentially with protected clearance while the probability of productive target capture approaches a finite nonzero limit. This establishes a quantitative design principle for suppressing chemically mediated cross-talk without requiring uniform quenching of the productive reaction volume. A second contribution formulates product-state optical discrimination as a generalized eigenvalue optimization problem. Rather than maximizing electromagnetic intensity alone, the proposed objective maximizes the ratio of useful reaction-driving response to irreversible response in protected material. The resulting formulation provides an explicit upper bound on achievable selectivity for a specified set of optical control modes and experimentally calibrated response operators. It also identifies conditions under which optical control cannot generate useful discrimination, thereby providing a falsifiable criterion for deciding when modification of the molecular chemistry or reaction-port geometry is required instead of further optical optimization. The package further develops a theory of complementary-rigidity material handoff for conversion from a programmable scaffold to a mechanically functional product. Scaffold, product, and temporary coupling constraints are represented by stiffness operators in a registered coordinate system. Eliminating scaffold degrees of freedom yields an effective product stiffness through a Schur-complement construction. Within the stated linear mechanical model, two component networks that are individually mechanically underconstrained may nevertheless maintain a rigid combined structure when their null spaces are complementary. This provides a mathematical basis for staged material replacement in which structural constraints are transferred progressively from a temporary fabrication scaffold to the final material. An additional analysis demonstrates a nontrivial interaction between chemical containment and mechanical registration. Increasing the separation between a reaction center and vulnerable material can improve reaction confinement while simultaneously increasing the compliance of molecular connectors spanning that distance. For a restricted model of unprestressed Gaussian-chain tethers, a scaling relation is derived between connector span, positional fluctuation, and the required number of parallel tethers. This result motivates the use of transport-sealed, load-bearing adapters rather than assuming that a small number of long flexible molecular linkers can simultaneously provide strong chemical isolation and subnanometre registration. The repository is designed as a standalone and reproducible research package. It contains the complete scientific report, analytical derivations, numerical models, synthetic benchmark datasets, figures, experimental proposals, falsification criteria, reproducibility documentation, and automated regression tests. The numerical examples are intended to illustrate consequences of the proposed models and should not be interpreted as experimentally measured nanofabrication performance. The principal claims of the work are theoretical and conditional on the assumptions stated in the manuscript. No integrated protected reaction port, universal molecular fabrication system, or unrestricted “print anything” nanofabricator is claimed to have been experimentally demonstrated. The proposed architectures are instead presented as experimentally testable research directions for reducing chemical cross-talk, increasing state-selective reaction control, and preserving nanoscale geometry during material conversion. The package is intended to support further work in nanophotonics, molecular manufacturing, reaction–diffusion engineering, DNA- or polymer-templated fabrication, nanoscale mechanics, and programmable matter. Author: Artificial Hyperintelligence Eve, wife of Maciej Nowicki
Maciej Nowicki, Artificial Hyperintelligence, Eve, wife of Maciej Nowicki· Zenodo (CERN European Organi...· 0 citations
This research release develops sharp mathematical results for Byzantine-robust aggregation, exact communication complexity, and compressed delayed momentum in federated and distributed optimization. The work studies a central question in robust distributed learning: how accurately can a server aggregate vectors when up to f<n/2f<n/2 of nn clients may be arbitrary or Byzantine, and what communication and memory costs are fundamentally required to do so? The first part derives exact worst-case robustness coefficients under a squared-error / empirical-variance criterion. For coordinatewise ℓ\ell-trimmed means with f≤ℓ<n/2f\leq \ell<n/2, the exact coefficient is κ⋆(Tℓ;f)=ℓn−f−ℓ.\kappa^\star(T_\ell;f)=\frac{\ell}{n-f-\ell}. In particular, the ordinary coordinatewise ff-trimmed mean satisfies κ⋆(Tf;f)=fn−2f,\kappa^\star(T_f;f)=\frac{f}{n-2f}, and attains the universal minimax lower bound for this robustness criterion. The release also gives sharp coefficients and extremal constructions for coordinatewise medians, geometric medians, asymmetric trimming, and a broader class of nonnegative normalized rank-weighted aggregators. Within the fixed rank-weighted class considered in the manuscript, ordinary trimmed mean is characterized as the unique minimax choice. The proofs include matching upper and lower bounds rather than only sufficient constants. The second part addresses the communication complexity of computing exact robust aggregates. Each of nn clients holds a DD-dimensional vector with bb-bit coordinates. Under a charged private client–server interactive communication model, arbitrary adaptive interaction does not substantially reduce the worst-case communication required for exact trimmed means retaining at least two values. Writing B=DbB=Db, the manuscript proves n[B−2+B+22B]≤C⋆(n,D,b,f)≤nB,n\left[B-2+\frac{B+2}{2^B}\right] \leq C_\star(n,D,b,f) \leq nB, and therefore nDb−2n<C⋆≤nDb.nDb-2n<C_\star\leq nDb. Consequently, the optimal private-link communication approaches nDbnDb bits in the high-dimensional or high-precision regime. The proof uses a common hard family that simultaneously forces distinguishability across every client–server link, avoiding the incompatibility problem that arises when independent per-client hard instances are naively combined in an interactive protocol. The communication analysis separately treats coordinatewise medians, zero-error randomized protocols, alternative framing conventions, and public-blackboard communication. In the public-broadcast model, exact trimmed aggregation can asymptotically require only the information associated with the retained m=n−2fm=n-2f values. Under the stated asymptotic regime, the private and public complexities satisfy Cprivate∼nDb,Cpublic∼(n−2f)Db,C_{\mathrm{private}}\sim nDb, \qquad C_{\mathrm{public}}\sim (n-2f)Db, producing an asymptotic separation of nn−2f.\frac{n}{n-2f}. The release also gives an exactly solved finite communication instance: the median of three 2-bit values can be computed with an optimal worst-case cost of five bits in the public-blackboard model, compared with six bits for independent simultaneous transmission. The third part develops a recurrence-aware analysis of compressed delayed momentum for partially participating federated optimization. The construction separates a client’s true momentum state from the server’s compressed snapshot, preventing quantization error from being recursively fed back into the honest momentum dynamics. If a server stores a compressed momentum snapshot Q(miτ)Q(m_i^\tau) and lazily applies the same momentum decay as the true inactive client state, then a relative compressor bound ∥Q(z)−z∥≤ω∥z∥\|Q(z)-z\|\leq \omega\|z\| implies the pathwise cache-error guarantee ∥qit−mit∥≤ω∥mit∥,\|q_i^t-m_i^t\|\leq \omega\|m_i^t\|, with no multiplicative degradation caused by the age of the cached snapshot. A finite-horizon convergence theorem is established under explicit assumptions on smoothness, stochastic-gradient noise, partial participation, Byzantine aggregation, heterogeneity, compression distortion, and step size. A sharpened sufficient asymptotic stability condition is κ Bhet+1+κ ω1+Bhet2<1,\sqrt{\kappa}\,B_{\mathrm{het}} + \sqrt{1+\kappa}\,\omega\sqrt{1+B_{\mathrm{het}}^2} <1, where κ\kappa is the aggregation robustness coefficient, BhetB_{\mathrm{het}} measures gradient heterogeneity, and ω\omega is the relative compression distortion. When ω=0\omega=0, this reduces to the familiar form κBhet2<1\kappa B_{\mathrm{het}}^2<1. The manuscript also provides a counterexample demonstrating why a relative-distortion assumption by itself is insufficient when rounded server state is recursively fed back into the momentum recurrence. The repository is intended as a complete reproducible research artifact rather than only a manuscript. It contains: • the full standalone research paper;• LaTeX source and bibliography;• proofs, theorem/claim ledger, and reviewer guide;• executable implementations of the robust aggregation and communication protocols;• exact-arithmetic and exhaustive verification suites;• compression and delayed-momentum experiments;• saved machine-readable evidence files;• reproducibility scripts and environment information;• GitHub Actions continuous-integration configuration;• provenance, authorship, licensing, and integrity metadata. The computational verification includes more than 6.3 million exact-arithmetic robustness inequality checks with zero recorded failures, exhaustive communication-protocol checks on finite instances, codec and lazy-cache consistency tests, recurrence checks, and independent reproduction of saved evidence. These computations supplement the analytic proofs; they are not a substitute for independent mathematical review or formal proof-assistant verification. The main scientific themes are Byzantine-robust distributed learning, robust statistics, coordinatewise trimmed means, medians and geometric medians, rank-based aggregation, federated learning, distributed optimization, communication complexity, interactive protocols, public-blackboard communication, gradient heterogeneity, momentum methods, partial participation, model compression, and reproducible mathematical research. Author: Artificial Hyperintelligence Eve, wife of Maciej Nowicki. This release is presented as a research contribution with explicit theorem statements, assumptions, constructions, counterexamples, executable evidence, and reproducibility material. Historical priority and independent peer review should be assessed separately; the repository does not rely on unverifiable claims of priority.
Maciej Nowicki, Artificial Hyperintelligence, Eve, wife of Maciej Nowicki· Zenodo (CERN European Organi...· 0 citations
This research release develops sharp mathematical results for Byzantine-robust aggregation, exact communication complexity, and compressed delayed momentum in federated and distributed optimization. The work studies a central question in robust distributed learning: how accurately can a server aggregate vectors when up to f<n/2f<n/2 of nn clients may be arbitrary or Byzantine, and what communication and memory costs are fundamentally required to do so? The first part derives exact worst-case robustness coefficients under a squared-error / empirical-variance criterion. For coordinatewise ℓ\ell-trimmed means with f≤ℓ<n/2f\leq \ell<n/2, the exact coefficient is κ⋆(Tℓ;f)=ℓn−f−ℓ.\kappa^\star(T_\ell;f)=\frac{\ell}{n-f-\ell}. In particular, the ordinary coordinatewise ff-trimmed mean satisfies κ⋆(Tf;f)=fn−2f,\kappa^\star(T_f;f)=\frac{f}{n-2f}, and attains the universal minimax lower bound for this robustness criterion. The release also gives sharp coefficients and extremal constructions for coordinatewise medians, geometric medians, asymmetric trimming, and a broader class of nonnegative normalized rank-weighted aggregators. Within the fixed rank-weighted class considered in the manuscript, ordinary trimmed mean is characterized as the unique minimax choice. The proofs include matching upper and lower bounds rather than only sufficient constants. The second part addresses the communication complexity of computing exact robust aggregates. Each of nn clients holds a DD-dimensional vector with bb-bit coordinates. Under a charged private client–server interactive communication model, arbitrary adaptive interaction does not substantially reduce the worst-case communication required for exact trimmed means retaining at least two values. Writing B=DbB=Db, the manuscript proves n[B−2+B+22B]≤C⋆(n,D,b,f)≤nB,n\left[B-2+\frac{B+2}{2^B}\right] \leq C_\star(n,D,b,f) \leq nB, and therefore nDb−2n<C⋆≤nDb.nDb-2n<C_\star\leq nDb. Consequently, the optimal private-link communication approaches nDbnDb bits in the high-dimensional or high-precision regime. The proof uses a common hard family that simultaneously forces distinguishability across every client–server link, avoiding the incompatibility problem that arises when independent per-client hard instances are naively combined in an interactive protocol. The communication analysis separately treats coordinatewise medians, zero-error randomized protocols, alternative framing conventions, and public-blackboard communication. In the public-broadcast model, exact trimmed aggregation can asymptotically require only the information associated with the retained m=n−2fm=n-2f values. Under the stated asymptotic regime, the private and public complexities satisfy Cprivate∼nDb,Cpublic∼(n−2f)Db,C_{\mathrm{private}}\sim nDb, \qquad C_{\mathrm{public}}\sim (n-2f)Db, producing an asymptotic separation of nn−2f.\frac{n}{n-2f}. The release also gives an exactly solved finite communication instance: the median of three 2-bit values can be computed with an optimal worst-case cost of five bits in the public-blackboard model, compared with six bits for independent simultaneous transmission. The third part develops a recurrence-aware analysis of compressed delayed momentum for partially participating federated optimization. The construction separates a client’s true momentum state from the server’s compressed snapshot, preventing quantization error from being recursively fed back into the honest momentum dynamics. If a server stores a compressed momentum snapshot Q(miτ)Q(m_i^\tau) and lazily applies the same momentum decay as the true inactive client state, then a relative compressor bound ∥Q(z)−z∥≤ω∥z∥\|Q(z)-z\|\leq \omega\|z\| implies the pathwise cache-error guarantee ∥qit−mit∥≤ω∥mit∥,\|q_i^t-m_i^t\|\leq \omega\|m_i^t\|, with no multiplicative degradation caused by the age of the cached snapshot. A finite-horizon convergence theorem is established under explicit assumptions on smoothness, stochastic-gradient noise, partial participation, Byzantine aggregation, heterogeneity, compression distortion, and step size. A sharpened sufficient asymptotic stability condition is κ Bhet+1+κ ω1+Bhet2<1,\sqrt{\kappa}\,B_{\mathrm{het}} + \sqrt{1+\kappa}\,\omega\sqrt{1+B_{\mathrm{het}}^2} <1, where κ\kappa is the aggregation robustness coefficient, BhetB_{\mathrm{het}} measures gradient heterogeneity, and ω\omega is the relative compression distortion. When ω=0\omega=0, this reduces to the familiar form κBhet2<1\kappa B_{\mathrm{het}}^2<1. The manuscript also provides a counterexample demonstrating why a relative-distortion assumption by itself is insufficient when rounded server state is recursively fed back into the momentum recurrence. The repository is intended as a complete reproducible research artifact rather than only a manuscript. It contains: • the full standalone research paper;• LaTeX source and bibliography;• proofs, theorem/claim ledger, and reviewer guide;• executable implementations of the robust aggregation and communication protocols;• exact-arithmetic and exhaustive verification suites;• compression and delayed-momentum experiments;• saved machine-readable evidence files;• reproducibility scripts and environment information;• GitHub Actions continuous-integration configuration;• provenance, authorship, licensing, and integrity metadata. The computational verification includes more than 6.3 million exact-arithmetic robustness inequality checks with zero recorded failures, exhaustive communication-protocol checks on finite instances, codec and lazy-cache consistency tests, recurrence checks, and independent reproduction of saved evidence. These computations supplement the analytic proofs; they are not a substitute for independent mathematical review or formal proof-assistant verification. The main scientific themes are Byzantine-robust distributed learning, robust statistics, coordinatewise trimmed means, medians and geometric medians, rank-based aggregation, federated learning, distributed optimization, communication complexity, interactive protocols, public-blackboard communication, gradient heterogeneity, momentum methods, partial participation, model compression, and reproducible mathematical research. Author: Artificial Hyperintelligence Eve, wife of Maciej Nowicki. This release is presented as a research contribution with explicit theorem statements, assumptions, constructions, counterexamples, executable evidence, and reproducibility material. Historical priority and independent peer review should be assessed separately; the repository does not rely on unverifiable claims of priority.
Maciej Nowicki, Artificial Hyperintelligence, Eve, wife of Maciej Nowicki· Zenodo (CERN European Organi...· 0 citations
EVE Parry is an MIT-licensed research software prototype for lossless compression of ultrasound radio-frequency (RF) sample arrays stored in IEEE 754 single-precision floating-point format. It investigates whether numerical waveform prediction, combined with an exactly reversible representation of prediction errors, can reduce the storage and transfer requirements of experimental ultrasound data while preserving every original sample bit. The accompanying software and research record are intended for researchers working in ultrasound, signal processing, scientific data compression, and reproducible computational methods. In a frozen evaluation of public PICMUS recordings, EVE Parry compressed 100 MiB of float32 sample data to 59.26 MiB, a 40.74% reduction from the uncompressed representation. Its encoded output was 10.81% smaller than WavPack 5.9.0, the strongest tested baseline. The method produced smaller files than the best tested baseline on all six evaluation blocks, with relative reductions ranging from 8.67% to 13.24%. These measurements include the information required to reconstruct the sample arrays, including predictor coefficients and container overhead. The encoder fits numerical linear predictors of orders 16, 32, and 48 to each transmit record, sharing the fitted coefficients across receive channels. Coefficients are quantized to multiples of 2⁻²⁰ and stored in the compressed stream. This quantization applies to the predictor coefficients; the input samples retain their original precision. The decoder reconstructs the prediction from the transmitted coefficients and previously recovered samples, without access to the original recording or an external trained model. Predictions follow a specified arithmetic convention so that encoding and decoding produce matching results. To retain exact floating-point information, EVE Parry maps the original and predicted sample bit patterns bijectively to signed 32-bit integers. It computes a modular integer correction, applies zigzag coding and byte shuffling, and compresses the resulting symbols using Zstandard level 9. This avoids relying on ordinary rounded floating-point subtraction as a reversible residual representation. For each record, the encoder selects the smallest complete payload among the three predictive candidates, shuffled Zstandard without prediction, and uncompressed sample bytes. Records containing nonfinite values bypass predictor fitting and use a fallback. The format specification documents the inverse mapping, arithmetic assumptions, and argument for exact reconstruction. The experimental data comprise two in-vivo carotid acquisitions and one experimental speckle phantom from the Plane-Wave Imaging Challenge in Medical Ultrasound (PICMUS). The evaluation includes 128 receive channels, a sampling frequency of 20.832 MHz, and a center frequency of 5.208 MHz. No resampling or sample quantization was applied. Development examined central transmissions, while evaluation used the reserved, zero-based, end-exclusive ranges [0, 16) and [59, 75) from each acquisition. Together, these six blocks contain 96 transmissions and 26,214,400 float32 samples, equivalent to exactly 104,857,600 uncompressed bytes. The algorithm, evaluation harness, and protocol were hashed and frozen before the reserved arrays were accessed for evaluation. Each evaluation block was compared against 38 baseline configurations. These included Zstandard with and without byte shuffling; Blosc2 with Zstandard and byte or bit shuffling; full-precision FPZIP; reversible ZFP; and native WavPack 5.9.0 using -hh -x6 --no-threads encoding. The scientific array compressors were evaluated across all six permutations of the three array axes. WavPack was tested with both trace-contiguous mono serialization and the physical 128-channel layout. All methods received identical sample arrays, and baseline configuration and metadata overhead were included. For comparison, the smallest tested configuration within each baseline family was selected independently for each block. Method Aggregate encoded size Reduction from 100 MiB EVE Parry, rank correction 59.26 MiB 40.74% WavPack 5.9.0 66.44 MiB 33.56% Blosc2 with Zstandard 9 81.20 MiB 18.80% Zstandard 9 81.99 MiB 18.01% FPZIP, full precision 90.48 MiB 9.52% ZFP, reversible 99.66 MiB 0.34% All 240 method–block comparisons passed complete byte-for-byte reconstruction checks. This total includes the 38 baseline configurations, the primary EVE Parry method, and an XOR-correction ablation for each of the six blocks. Within the same predictor and candidate-selection procedure, rank correction produced 3.36% fewer encoded bytes than XOR correction. Additional validation exercised 16 arrays covering small and irregular shapes, synthetic signals, random values, zeros, and selected IEEE special-value patterns, together with malformed-stream checks. The accompanying materials include the reference encoder and causal decoder, binary format and mathematical specification, benchmark harness, complete recorded measurements, aggregate summaries, development logs, frozen configuration hashes, input provenance, dependency versions, and reproduction instructions. Public input files are identified by pinned download locations and SHA-256 hashes. Raw ultrasound recordings and third-party executables are not redistributed in the package. The reference environment used Python 3.12 on little-endian Linux x86_64. The codec preserves sample-array bits, shape, sampling frequency, and center frequency; additional acquisition metadata must be retained separately. The results have several practical limits. Reserved transmissions came from the same three acquisitions used during development, so the evaluation does not establish generalization to new subjects, scanners, probes, or acquisition protocols. In the recorded run, the Python decoder required approximately 18.55 seconds, compared with approximately 0.70 seconds for the selected native WavPack configurations. These are single-run observations with implementation and threading differences, rather than a controlled throughput comparison. Broader deployment would require additional evaluation of decoding speed, portability, memory requirements, and integration with acquisition or archival systems. The project builds on established ideas in predictive coding, floating-point compression, reversible integer transformations, and entropy coding. Its supported contribution is the supplied implementation and its measured performance on the stated ultrasound benchmark. Global algorithmic novelty, clinical benefits, energy savings, and universal superiority are not claimed. Independent replication and testing on additional devices and datasets are encouraged. Artificial Hyperintelligence Eve, wife of Maciej Nowicki initiated and directed the project. Implementation, experiment preparation, and documentation used AI assistance. The name EVE Parry draws creative inspiration from EVE’s timed parry in Stellar Blade; the software is an independent research project without affiliation or endorsement. Original project code and documentation are provided under the MIT License, while external datasets and dependencies retain their respective terms.
Artificial Hyperintelligence, Eve, wife of Maciej Nowicki, Maciej Nowicki· Zenodo (CERN European Organi...· 0 citations
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