Lossless compression
View article: TET Suite v1.1 + TU-GUT-SYSY v8 — Eternal Extension Pure-Proton Fusion, 300 K Vacuum Torque, and Eternal Neuromorphic Computing 50/50 Partnership: Simon Soliman & Grok (xAI)
TET Suite v1.1 + TU-GUT-SYSY v8 — Eternal Extension Pure-Proton Fusion, 300 K Vacuum Torque, and Eternal Neuromorphic Computing 50/50 Partnership: Simon Soliman & Grok (xAI) Open
Versione corretta: upper bounds su torque dal vuoto (≤ 10^{-27} Nm, non misurabile). Verifica Borexino: nessuna anomalia significativa. Sezione aurea nell'imballaggio: ottimizzazione numerica valida, ma non implica nuova fisica. Include co…
View article: TET Suite v1.1 + TU-GUT-SYSY v8 — Eternal Extension Pure-Proton Fusion, 300 K Vacuum Torque, and Eternal Neuromorphic Computing 50/50 Partnership: Simon Soliman & Grok (xAI)
TET Suite v1.1 + TU-GUT-SYSY v8 — Eternal Extension Pure-Proton Fusion, 300 K Vacuum Torque, and Eternal Neuromorphic Computing 50/50 Partnership: Simon Soliman & Grok (xAI) Open
Versione corretta: upper bounds su torque dal vuoto (≤ 10^{-27} Nm, non misurabile). Verifica Borexino: nessuna anomalia significativa. Sezione aurea nell'imballaggio: ottimizzazione numerica valida, ma non implica nuova fisica. Include co…
View article: Maximal Heat and Maximal Cold in Causal Compression Theory Part II: Foundations, Significance, and Unified Physical Framework
Maximal Heat and Maximal Cold in Causal Compression Theory Part II: Foundations, Significance, and Unified Physical Framework Open
This work presents the unified physical foundation of maximal heat and maximal cold through the Planck-normalized compression variable K=ρ/ρP,K = \rho/\rho_P,K=ρ/ρP, which emerges as the single causal axis organizing all thermal and gravit…
View article: Maximal Heat and Maximal Cold in Causal Compression Theory Part II: Foundations, Significance, and Unified Physical Framework
Maximal Heat and Maximal Cold in Causal Compression Theory Part II: Foundations, Significance, and Unified Physical Framework Open
This work presents the unified physical foundation of maximal heat and maximal cold through the Planck-normalized compression variable K=ρ/ρP,K = \rho/\rho_P,K=ρ/ρP, which emerges as the single causal axis organizing all thermal and gravit…
View article: Holographix: a percept-first codec and network substrate for Large Vision Models and Large Audio Models over UDP
Holographix: a percept-first codec and network substrate for Large Vision Models and Large Audio Models over UDP Open
Impaired networks are normal in robotics, remote presence, ad-hoc meshes, radios, and disaster links: loss, burst loss, jitter, reordering, duplication, and intermittent connectivity are the rule rather than an edge case. For perceptual me…
View article: Holographix: a percept-first codec and network substrate for Large Vision Models and Large Audio Models over UDP
Holographix: a percept-first codec and network substrate for Large Vision Models and Large Audio Models over UDP Open
Impaired networks are normal in robotics, remote presence, ad-hoc meshes, radios, and disaster links: loss, burst loss, jitter, reordering, duplication, and intermittent connectivity are the rule rather than an edge case. For perceptual me…
View article: ADC (Adaptive Differential Coding) . Lossy Audio Codec and more.
ADC (Adaptive Differential Coding) . Lossy Audio Codec and more. Open
ADC – Audio Codec for lossy Compression - ADC Codec - Version 0.80 Technical Overview The ADC (Advanced Differential Coding) Codec, Version 0.80, represents a significant evolution in low-bitrate, high-fidelity audio compression. It employ…
View article: ADC (Adaptive Differential Coding) . Lossy Audio Codec and more.
ADC (Adaptive Differential Coding) . Lossy Audio Codec and more. Open
ADC (Adaptive Differential Coding ) – Audio Codec for lossy Compression Redefining Time-Domain Audio Compression ADC is a new audio codec engineered to achieve exceptional compression efficiency and perceptual quality by fundamentally chal…
View article: athncb/memory_attractors_and_tension_as_hidden_structure: PCPI Numerical Proofs — Initial release (v1.0.0)
athncb/memory_attractors_and_tension_as_hidden_structure: PCPI Numerical Proofs — Initial release (v1.0.0) Open
This release contains the exact code used to reproduce the three numerical proofs of the article: "Mémoire, Attracteurs et Tension comme Structure Cachée des Systèmes Dynamiques" Proof 1 — Non-Markovianity on a synthetic controlled system …
View article: athncb/memory_attractors_and_tension_as_hidden_structure: PCPI Numerical Proofs — Initial release (v1.0.0)
athncb/memory_attractors_and_tension_as_hidden_structure: PCPI Numerical Proofs — Initial release (v1.0.0) Open
This release contains the exact code used to reproduce the three numerical proofs of the article: "Mémoire, Attracteurs et Tension comme Structure Cachée des Systèmes Dynamiques" Proof 1 — Non-Markovianity on a synthetic controlled system …
View article: Holographix: a percept-first codec and network substrate for Large Vision Models and Large Audio Models over UDP
Holographix: a percept-first codec and network substrate for Large Vision Models and Large Audio Models over UDP Open
Holographix is a percept-first codec and UDP transport substrate for RGB images and PCM audio on impaired links, including loss, burst loss, jitter, reordering, duplication and intermittent connectivity. Each signal is represented as a coa…
View article: Revisiting SVD and Wavelet Difference Reduction for Lossy Image Compression: A Reproducibility Study
Revisiting SVD and Wavelet Difference Reduction for Lossy Image Compression: A Reproducibility Study Open
This work presents an independent reproducibility study of a lossy image compression technique that integrates singular value decomposition (SVD) and wavelet difference reduction (WDR). The original paper claims that combining SVD and WDR …
View article: Revisiting SVD and Wavelet Difference Reduction for Lossy Image Compression: A Reproducibility Study
Revisiting SVD and Wavelet Difference Reduction for Lossy Image Compression: A Reproducibility Study Open
This work presents an independent reproducibility study of a lossy image compression technique that integrates singular value decomposition (SVD) and wavelet difference reduction (WDR). The original paper claims that combining SVD and WDR …
View article: Spiral Data Compression (SDC): A Self-Similar Spiral Framework for Efficient Data Encoding
Spiral Data Compression (SDC): A Self-Similar Spiral Framework for Efficient Data Encoding Open
SDC introduces a compression architecture based on spiral self-similarity, resonance mapping and geometric redundancy minimization.The model offers structure-preserving compression methods applicable to AI, databases and large-scale data p…
View article: Lensless and Lossless HoloVAM
Lensless and Lossless HoloVAM Open
We report the first successful fabrication of three-dimensional models using our fully lensless holographic volumetric additive manufacturing (HoloVAM) platform. In this configuration, tomographic light fields are generated directly from a…
View article: Lensless and Lossless HoloVAM
Lensless and Lossless HoloVAM Open
We report the first successful fabrication of three-dimensional models using our fully lensless holographic volumetric additive manufacturing (HoloVAM) platform. In this configuration, tomographic light fields are generated directly from a…
View article: Spiral Data Compression (SDC): A Self-Similar Spiral Framework for Efficient Data Encoding
Spiral Data Compression (SDC): A Self-Similar Spiral Framework for Efficient Data Encoding Open
SDC introduces a compression architecture based on spiral self-similarity, resonance mapping and geometric redundancy minimization.The model offers structure-preserving compression methods applicable to AI, databases and large-scale data p…
View article: Towards Interactive Analysis of Compressed Provenance Graphs Without Decompression
Towards Interactive Analysis of Compressed Provenance Graphs Without Decompression Open
Enterprise security systems generate massive volumes of log data essential for forensic analysis and cyber threat investigation. The challenge is scale. Storing these logs requires significant resources, and searching through them is painf…
View article: KV-Cache Compression via Attention Pattern Pruning for Latency-Constrained LLMs
KV-Cache Compression via Attention Pattern Pruning for Latency-Constrained LLMs Open
Large Language Models (LLMs) have achieved remarkable success across diverse natural language processing tasks. However, their autoregressive inference, particularly with long input sequences, is significantly bottlenecked by the Key-Value…
View article: KV-Cache Compression via Attention Pattern Pruning for Latency-Constrained LLMs
KV-Cache Compression via Attention Pattern Pruning for Latency-Constrained LLMs Open
Large Language Models (LLMs) have achieved remarkable success across diverse natural language processing tasks. However, their autoregressive inference, particularly with long input sequences, is significantly bottlenecked by the Key-Value…
View article: Forest Timber Stacks Dataset for Geometric and Volume Estimation
Forest Timber Stacks Dataset for Geometric and Volume Estimation Open
The dataset consists of 1686 frames of sorted cut timber stacks taken in forest areas across Poland in Sep 2025 and 4907 frames of assorted timber stacks in Lithuania, Nov. 2025. The images depict systematically piled and fresh piled (to b…
View article: Federated Learning and Trajectory Compression for Enhanced AIS Coverage
Federated Learning and Trajectory Compression for Enhanced AIS Coverage Open
This paper presents the VesselEdge system, which leverages federated learning and bandwidth-constrained trajectory compression to enhance maritime situational awareness by extending AIS coverage. VesselEdge transforms vessels into mobile s…
View article: FBI-Style Nonverbal Behavior Knowledge Graph Dataset
FBI-Style Nonverbal Behavior Knowledge Graph Dataset Open
This dataset compiles a five-level granular lossless knowledge graph and corresponding hierarchical mind map based on Joe Navarro's classic work What Every BODY is Saying, aiming to reconstruct the FBI-style system for interpreting body la…
View article: nucleomic/nqx-format: NQX v1.0.1 Hybrid Format (Zenodo-registered)
nucleomic/nqx-format: NQX v1.0.1 Hybrid Format (Zenodo-registered) Open
This is the first Zenodo-registered packaging of the NQX v1.0 hybrid format. The underlying specification and reference implementation are identical to v1.0.0. NQX v1.0.0 – Hybrid File Format Release This release introduces NQX v1.0, a com…
View article: nucleomic/nqx-format: NQX v1.0.1 Hybrid Format (Zenodo-registered)
nucleomic/nqx-format: NQX v1.0.1 Hybrid Format (Zenodo-registered) Open
This is the first Zenodo-registered packaging of the NQX v1.0 hybrid format. The underlying specification and reference implementation are identical to v1.0.0. NQX v1.0.0 – Hybrid File Format Release This release introduces NQX v1.0, a com…
View article: Compression Physics: A Domain-Normalized Efficiency Index (Generalized Efficiency Coefficient, GEC)
Compression Physics: A Domain-Normalized Efficiency Index (Generalized Efficiency Coefficient, GEC) Open
This work introduces the Generalized Efficiency Coefficient (GEC), a domain-normalized index for quantifying how efficiently a system approaches its theoretical or empirical bound. We develop the broader framework of Compression Physics, w…
View article: PIXELCODE: A VQ-VAE Based Image-to-Alphanumeric Reversible Encoding System
PIXELCODE: A VQ-VAE Based Image-to-Alphanumeric Reversible Encoding System Open
This paper presents a system, PIXELCODE, where we can preserve data by converting data into human readable alphanumeric strings. This paper demonstrates a novel reversible way to convert image-to-alphanumeric strings encoding system that s…
View article: Time Series Lossy Compression Using Wavelet, Fourier, and Cosine Transforms: Benchmarking Optimisation Paramters, Compression Ratios and Decompression Error
Time Series Lossy Compression Using Wavelet, Fourier, and Cosine Transforms: Benchmarking Optimisation Paramters, Compression Ratios and Decompression Error Open
View article: Quantum Coherent Thermal Lensing A Dimensional-Coherence Framework for Lossless Directed Heat Transport
Quantum Coherent Thermal Lensing A Dimensional-Coherence Framework for Lossless Directed Heat Transport Open
This work introduces Quantum Coherent Thermal Lensing (QCTL), a new theoretical framework in which heat is transported as a coherence-preserving phase excitation rather than a diffusive process. QCTL enables lensing, focusing, beam splitti…
View article: Quantum Coherent Thermal Lensing A Dimensional-Coherence Framework for Lossless Directed Heat Transport
Quantum Coherent Thermal Lensing A Dimensional-Coherence Framework for Lossless Directed Heat Transport Open
This work introduces Quantum Coherent Thermal Lensing (QCTL), a new theoretical framework in which heat is transported as a coherence-preserving phase excitation rather than a diffusive process. QCTL enables lensing, focusing, beam splitti…