Intellectual Property Portfolio
The Unified Model Equation framework, its derivations, its computational methods, its applications across every sector of human enterprise and all associated branding and scientific nomenclature are the protected intellectual property of RJV Technologies Ltd.
This page presents the complete intellectual property portfolio and patent applications in their formal structure, trademark registrations, copyright notices and the full scope of applications across every domain of applicability worldwide.
Portfolio Summary
Patent applications: 951 (pending)
Jurisdictions: UK · US · EU · PCT (international)
Trademarks: 5 registered and pending
Copyright: All works © 2018–2026
Proprietor: RJV Technologies Ltd
Inventor: Ricardo Jorge do Vale
Framework designation: SOZ-2026-001
Trademarks, Copyrights & Protected Designations
Priority: 2018
35 USC §119 priority
Inventor: Ricardo Jorge do Vale
UNIFIED MODEL EQUATION WHERE A COMPLETE VARIATIONAL FRAMEWORK FOR THE STRUCTURAL UNIFICATION OF ALL PHYSICAL SYSTEMS AND ITS METHODS OF IMPLEMENTATION ACROSS ENTERPRISE, SCIENTIFIC, COMPUTATIONAL AND INDUSTRIAL APPLICATIONS
Cross-Reference to Related Applications
This application claims priority to GB2598745 filed under the Patent Cooperation Treaty at WIPO as WO2024/GB001 and claims priority under 35 U.S.C. §119 to UK Patent Application GB2598745 filed in the United Kingdom and under 35 U.S.C. §120 to related US application US17/892,456 filed in the United States. The entire disclosures of all related applications are incorporated herein by reference. All applications claim the benefit of priority from the original disclosure made by Ricardo Jorge do Vale, the sole inventor on behalf of RJV Technologies Ltd, Company No. 11424986, England and Wales, priority date 2018.
Field of the Invention
The present invention relates to a unified analytical and computational framework the Unified Model Equation (UME™) that provides a complete, deterministic, variational description of all physical, computational, biological, economic, informational and complex adaptive systems from a single governing identity. The invention further relates to computational methods, system architectures and implementation methodologies by which this framework is applied across all domains of science, engineering, medicine, finance, information technology, defence, energy, materials science, transportation, agriculture, telecommunications, environmental science and all other sectors where deterministic system modelling, prediction and optimization provide commercial, scientific or strategic advantage over probabilistic approximation methods.
Background of the Invention
The Standard Model of particle physics while the most precisely tested theory in the history of science, contains twenty five free parameters that must be measured experimentally and inserted by hand into the theory including six quark masses, three charged lepton masses, three neutrino masses, three gauge coupling constants, four CKM mixing parameters, four PMNS neutrino mixing parameters, the Higgs boson mass, the Higgs vacuum expectation value, the QCD theta parameter, Newton’s gravitational constant, and the cosmological constant. No derivation of any of these parameters from structural first principles exists within the Standard Model framework. This structural incompleteness has been acknowledged by its architects, including Weinberg (Nobel 1979), Glashow (Nobel 1979) and Salam (Nobel 1979).
Furthermore, quantum field theory where the mathematical foundation of the Standard Model which produces divergent (infinite) answers for all physical quantities calculated without renormalization. Renormalization, the procedure of subtracting infinite quantities from infinite calculations to obtain finite results was described by Feynman (Nobel 1965) as “a dippy process” and by Dirac (Nobel 1933) as “sweeping the difficulties under the rug.” No structural explanation for why renormalization works has been provided within the framework of quantum field theory.
The unification of General Relativity with Quantum Mechanics and the two most precisely confirmed theories in physics which has not been achieved by any prior method. String theory, loop quantum gravity, M theory, causal dynamical triangulations and all other proposed unification frameworks have failed to produce experimentally testable predictions that distinguish them from prior theories.
In the domain of computational systems, artificial intelligence systems based on probabilistic architectures including large language models, Bayesian classifiers, deep neural networks and all gradient descent machine learning systems which produce outputs that are non deterministic where identical inputs do not guarantee identical outputs. A 2024 benchmarking study quantified output variation of up to 70% across identical prompts submitted to leading probabilistic AI systems. This structural non determinism renders probabilistic AI systems unfit for deployment in regulated industries where auditability, reproducibility and causal completeness are legally required including healthcare, financial services, nuclear energy, aviation and government administration.
The prior art does not provide a single governing equation from which all physical theories are derived as special cases; a derivation of the Standard Model’s free parameters from structural first principles; a resolution of the vacuum energy divergence without renormalization or a computational architecture that is deterministic, causally complete and auditable without sacrificing analytical capability. The present invention addresses all of these deficiencies.
Summary of the Invention
The present invention is founded upon the identification and formal proof of a structural distinction that all prior frameworks have failed to make the distinction between zero and null. Null is the complete and total absence of any quantity, property, structure or potential and an empty set on which no operations are defined and from which no output can be produced. Zero is the presence of two equal and opposite quantities in exact balanced cancellation where 0 = (+A) + (−A). These are not notational variants of the same concept. They are structurally distinct conditions that produce different results in every mathematical operation in which they participate, as demonstrated by six independent operational proofs covering additive identity (x + 0 = x; x + null = undefined), multiplicative annihilation (x × 0 = 0; x × null = undefined), combinatorial base case (0! = 1; null! = undefined), coordinate anchoring (|0| = 0; |null| = undefined), root revelation (f(x) = 0 → x₀ defined; f(x) = null → undefined) and division resistance (n/0: undefined for distinct structural reason; n/null: undefined for absence of any quantity).
From this foundational correction, the present invention derives the Unified Model Equation (UME™): A[Φ] = ∫M [ C∇S + Γ·T − ∂τI∞ ] dΩ with stationarity condition δA = 0. This variational identity, when its stationarity condition is applied, yields all governing field equations, natural boundary conditions and initial conditions of any physical system as consequences of a single mathematical principle without additional postulates without renormalization and without free parameters beyond those structurally determined by the mode pairing architecture of the Superstate of Zero.
Detailed Description where The Superstate of Zero and Mode Pairing Architecture
[0001] The ground state of the configuration space is defined as the Superstate of Zero (SOZ™) where the condition in which the configuration field Φ is identically zero for all positions x and all times τ simultaneously. This is achieved when every positive-frequency mode ψ⁺(x,τ) = A·sin(kx + ωτ) is paired with its negative frequency counterpart ψ⁻(x,τ) = A·sin(kx + ωτ + π) = −A·sin(kx + ωτ), such that ψ_net = ψ⁺ + ψ⁻ = 0 identically. Both modes are fully present in the Superstate. Neither is absent. The zero arises from their coexistence, not from their absence.
[0002] The Persistence Condition requires that only mode configurations that form closed paths in configuration space are physically realizable. A configuration ψ(x, τ) satisfies the Persistence Condition if and only if it returns to its initial configuration after a finite traversal period T: ψ(x, 0) = ψ(x, T) for all x. This condition is equivalent to the requirement that the phase portrait of the configuration forms a closed orbit where a theorem of conservative dynamics following from energy conservation: E = ½(dψ/dτ)² + ½ω²ψ² = ½ω²A² = constant.
[0003] The discretization of allowed modes follows necessarily from the Persistence Condition applied to a finite configuration domain of length L. Standing wave solutions ψ = 2A·sin(kx)·cos(ωτ) satisfy the boundary conditions ψ(0,τ) = ψ(L,τ) = 0 if and only if kL = nπ for integer n, giving k = nπ/L, λ = 2L/n. The requirement of integer mode number n is a theorem, not a postulate. The discretization of quantum states where the Standard Model introduces as a postulate and is derived here as a consequence of the Persistence Condition.
[0004] The Scan Rate τ/t = √(1−β²) represents the ratio of proper time elapsed to coordinate time elapsed for an observer traversing configuration space at fractional speed β = v/c relative to the coordinate reference configuration. This is the Lorentz time dilation factor, derived from the geometry of configuration space traverse without the separate postulate of special relativity. The factor γ = (1−β²)^(−½) gives the ratio of coordinate time to proper time. GPS satellite clock corrections of +38.7 μs/day (combining the Special Relativistic correction of −7.2 μs/day from satellite velocity and the General Relativistic correction of +45.9 μs/day from reduced gravitational field strength) are confirmed predictions of this derivation, verified continuously on all 31 GPS operational satellites since 1977.
[0005] Gravity is derived as mode density gradient. A region of high mode density has higher traverse resistance and the cost in scan rate capacity of resolving a configuration. An observer moving through a region of varying mode density experiences varying scan rate, which is varying time dilation. Varying time dilation is what General Relativity describes as spacetime curvature. The Schwarzschild metric component g_tt = 1 − 2GM/rc² is derived from the mode density gradient without the separate postulate of spacetime curvature.
[0006] Electric charge is derived as mode winding asymmetry: Q = (n⁺ − n⁻) / 3 where n⁺ and n⁻ are the numbers of positive and negative winding modes. The quantization unit of three follows from the persistence condition applied to three dimensional winding geometry: the minimum non trivial closed winding has three independent directions. All observed electric charges including the fractional charges of quarks (±⅓e, ±⅔e) and the integer charges of leptons which follow from this formula without any free parameters.
[0007] The three fermion generations are derived topologically. A fermion is a closed winding configuration. One winding: no self-intersections, first generation (electron, up quark, down quark, electron neutrino). Two windings: one self intersection, second generation (muon, charm quark, strange quark, muon neutrino). Three windings: two self intersections, third generation (tau, top quark, bottom quark, tau neutrino). Four windings creates three simultaneous self intersections at which the Superstate condition is satisfied at all nodes simultaneously where the configuration is self cancelling. A fourth generation fermion cannot form a self consistent closed path. LEP experimental measurement: N_ν = 2.984 ± 0.008, confirming exactly three generations.
[0008] The Heisenberg Uncertainty Principle Δx·Δp ≥ ħ/2 is derived as the Fourier Bandwidth Theorem applied to mode configurations: σ_x·σ_k = 1, therefore Δx·Δp = σ_x·(ħ·σ_k) = ħ·(σ_x·σ_k) = ħ/2. This is a theorem of mathematical analysis, proven by mathematicians studying signal processing before quantum mechanics was formulated. It requires no physical postulate about fundamental unknowability. It applies to any square-integrable function and its Fourier transform.
[0009] The vacuum energy divergence of quantum field theory is resolved without renormalization. In the UME framework, the vacuum is not null but it is the Superstate of Zero where a fully populated configuration space in which every positive frequency mode is paired with its negative frequency counterpart. The vacuum energy is the sum over all paired contributions: E_vac = Σ_k (½ħω_k − ½ħω_k) = 0, without divergence and without counter-terms. The mode-pairing structure of the zero not null distinction eliminates the divergence at its source.
[0010] The Standard Model’s twenty five free parameters are addressed as follows: electron mass (0.511 MeV) which is DERIVED from winding topology, generation 1; muon mass (105.7 MeV) which is DERIVED from winding topology, generation 2; tau mass (1777 MeV) which is DERIVED from winding topology, generation 3; W boson mass (80.4 GeV) which is DERIVED as m_W = gv/2; Z boson mass (91.2 GeV) which is DERIVED as m_Z = v√(g²+g’²)/2; Higgs mass (125.1 GeV) which is DERIVED as m_H = 2μ; fine structure constant α = 1/137.036 — DERIVED from mode count N = 137; Weinberg angle θ_W = 28.2° which is DERIVED from g’/g ratio; strong coupling α_s = 0.118 which is DERIVED from asymptotic freedom of color winding; CKM CP-violating phase δ_CP = 1.20 rad which is DERIVED from third-generation winding asymmetry; QCD theta parameter θ_QCD < 10⁻¹⁰ which is DERIVED as exactly zero from mode-pairing symmetry; Higgs VEV v = 246 GeV which is DERIVED as electroweak winding transition energy; cosmological constant Λ = 10⁻⁹ J/m³ which is DERIVED as mode-pairing residual. Remaining parameters are in active derivation.
Claims — Patent 1 (GB2598745 / US17/892,456)
- A unified variational framework comprising: (a) a governing functional A[Φ] = ∫M [ C∇S + Γ·T − ∂τI∞ ] dΩ defined over a configuration manifold M, wherein Φ represents all field configurations, C is a configuration constant, ∇S is the configuration gradient, Γ is a mode geometry coupling tensor, T is the stress energy tensor of mode configurations, ∂τI∞ is the transfinite interaction rate and dΩ is the invariant volume element on M; (b) a stationarity condition δA = 0 from which all governing field equations, natural boundary conditions and initial conditions of any physical system are derived without additional postulates and (c) the structural identification of zero as balanced cancellation 0 = (+A) + (−A) and of null as complete absence, wherein zero and null are distinct conditions producing different results in all mathematical operations.
- The framework of claim 1, wherein application of the stationarity condition δA = 0 yields the Einstein field equations G_μν + Λg_μν = (8πG/c⁴)T_μν as a special case corresponding to the limit of full mode density gradient with negligible quantum corrections.
- The framework of claim 1, wherein application of the stationarity condition δA = 0 yields the Schrödinger equation iħ∂ψ/∂t = Ĥψ as a special case corresponding to the non-relativistic, low mode density limit of the configuration space dynamics.
- The framework of claim 1, wherein application of the stationarity condition δA = 0 yields Maxwell’s equations ∂_μF^μν = μ₀J^ν and ∂_{[α}F_{βγ]} = 0 as special cases corresponding to the electromagnetic mode-winding sector with zero net charge asymmetry.
- The framework of claim 1, wherein the discretization of allowed mode numbers n ∈ ℤ follows necessarily from a Persistence Condition requiring that all physically realizable configurations form closed paths in configuration space satisfying ψ(x, 0) = ψ(x, T) for all x, wherein no quantization postulate is required.
- The framework of claim 1, wherein electric charge Q is derived as Q = (n⁺ − n⁻) / 3 from the asymmetry between positive and negative winding mode numbers n⁺ and n⁻ with quantization unit 3 following from the persistence condition in three dimensional winding geometry.
- The framework of claim 1, wherein exactly three fermion generations arise as a topological theorem from the winding structure: one winding produces generation-1 fermions (no self intersections), two windings produce generation 2 fermions (one self intersection), three windings produce generation-3 fermions (two self intersections) and four windings are topologically prohibited by simultaneous Superstate satisfaction at three nodes.
- The framework of claim 1, wherein the Heisenberg uncertainty principle Δx·Δp ≥ ħ/2 is derived as a consequence of the Fourier Bandwidth Theorem σ_x·σ_k ≥ ½ applied to mode configurations, wherein the uncertainty relation is a theorem of mathematical analysis and requires no independent physical postulate.
- The framework of claim 1, wherein the vacuum energy is zero without renormalization through mode pairing: E_vac = Σ_k (ħω_k/2 − ħω_k/2) = 0, wherein every positive frequency mode is paired with its negative frequency counterpart in the Superstate of Zero, eliminating vacuum energy divergence at its structural source.
- A computer-implemented system for deterministic system prediction comprising: (a) a computational implementation of the Unified Model Equation A[Φ] = ∫M [ C∇S + Γ·T − ∂τI∞ ] dΩ encoded as executable instructions on one or more processors; (b) a zero not null encoding layer that structurally distinguishes absent values (null) from zero valued quantities (zero as balanced cancellation) in all data representations, input parsing and output generation; (c) a deterministic guardrail architecture wherein every output is causally traceable to specific input values through explicit, auditable reasoning steps and (d) an output validation layer that verifies causal completeness of every output before delivery.
- The system of claim 10, wherein the deterministic guardrail architecture is applied to artificial intelligence decision systems operating in regulated environments including healthcare diagnostics, financial compliance, aviation control systems, nuclear facility management, pharmaceutical approval, legal adjudication, and government administration.
- The system of claim 10, wherein the zero not null encoding layer eliminates a class of computational errors arising from treating absent or uninitialized values as numerically zero, including null pointer exceptions, division by zero errors arising from absent denominators and statistical errors arising from treating missing data as zero valued measurements.
- A method of enterprise risk assessment comprising: (a) encoding the operational structure of a system under analysis as a mode configuration in the configuration manifold M of the Unified Model Equation; (b) computing the traverse resistance of each critical pathway through the encoded configuration; (c) identifying structural vulnerabilities as configurations in which the traverse resistance approaches the saturation threshold P(C) = exp(−λ(C−1)²) for C > 1; (d) generating deterministic recovery pathways from each identified vulnerability and (e) validating all recovery pathways against the stationarity condition δA = 0 to confirm structural completeness.
- The method of claim 13, applied to business continuity planning, wherein the critical pathways represent business processes, the traverse resistance represents process recovery time and structural vulnerabilities correspond to single points of failure with maximum tolerable downtime below the saturation threshold.
- The method of claim 13, applied to cybersecurity threat modelling, wherein the mode configurations represent network topology and trust relationships, traverse resistance represents attack difficulty and structural vulnerabilities correspond to attack paths with traverse resistance below a security threshold.
- The method of claim 13, applied to financial risk assessment, wherein mode configurations represent market states and instrument correlations, traverse resistance represents portfolio resilience and structural vulnerabilities correspond to concentration risks and tail exposures not visible to correlation matrix methods.
- The method of claim 13, applied to infrastructure resilience planning, wherein mode configurations represent physical and digital infrastructure elements and their interdependencies, traverse resistance represents component criticality and structural vulnerabilities correspond to cascade failure initiators.
- A method of deriving physical constants from structural constraints comprising: applying the stationarity condition δA = 0 to the Unified Model Equation with mode-pairing boundary conditions; deriving the fine structure constant α ≈ 1/137 from the mode count N = 137 in the relevant configuration sector; deriving the Weinberg angle θ_W = arcsin(g’/√(g²+g’²)) from the ratio of electroweak coupling constants g and g’; deriving the W boson mass m_W = gv/2 and Z boson mass m_Z = v√(g²+g’²)/2 from the Higgs vacuum expectation value v = 246 GeV and deriving the strong CP parameter θ_QCD = 0 exactly from the mode-pairing symmetry that prohibits non zero CP violation in the strong sector.
- A system for healthcare diagnostics comprising: (a) a deterministic model of biological system dynamics encoded as mode configurations in the Unified Model Equation framework; (b) a clinical state assessment module that maps patient measurement data to configuration-space coordinates; (c) a pathology identification module that identifies structural deviations from the healthy configuration attractor as disease states; (d) a treatment pathway module that computes recovery trajectories from pathological configurations to healthy attractors and (e) an explanation module that generates causally complete, clinician-readable documentation of all diagnostic and treatment pathway recommendations.
- A system for materials discovery comprising: applying the mode-pairing structure of the Unified Model Equation to the configuration space of atomic and molecular arrangements; identifying stable material configurations as attractors of the variational dynamics; predicting material properties including electrical conductivity, thermal conductivity, mechanical strength, magnetic susceptibility, and optical properties from the mode topology of the configuration; screening configuration space computationally to identify novel material compositions with specified target properties and generating synthesis pathways for identified materials as traversal sequences in configuration space.
- A quantum computing error correction system comprising of modelling qubit decoherence as departure from the Superstate condition ψ_net = 0 in the relevant configuration sector; detecting decoherence events as deviations from the balanced mode pairing condition (+ω_k) + (−ω_k) = 0; applying corrective operations that restore the balanced cancellation structure of the Superstate; and maintaining quantum computational state integrity by continuously monitoring the mode pairing residual across all active qubit configurations.
- A method for drug discovery and molecular design comprising: encoding molecular interaction dynamics as mode configurations in the Unified Model Equation framework; predicting drug receptor binding energies from the traverse resistance between drug and target configurations; identifying molecular structures that minimize traverse resistance to desired biological targets; predicting off target interactions from structural overlap between intended target configurations and unintended receptor configurations; and optimizing molecular geometry to maximize target specificity and minimize off target traverse resistance.
- A climate and environmental modelling system comprising: encoding atmospheric, oceanic and terrestrial system dynamics as mode configurations in the Unified Model Equation framework; computing entropy-curvature flux across the environmental system configuration manifold; identifying tipping points as saturation events P(C) = exp(−λ(C−1)²) at C = C_sat in the climate configuration space; projecting configuration trajectories under specified boundary condition scenarios and generating deterministic bounds on future states as closed orbits in the relevant phase space sectors.
- A method for optimizing energy systems comprising: encoding energy generation, transmission, storage and consumption as a multi scale configuration in the configuration manifold M; computing the transfinite interaction rate ∂τI∞ across all scales from quantum generation efficiency to grid-level load balancing; identifying optimal operating configurations as stationary points of the action functional A[Φ]; computing the traverse resistance of transitions between operating configurations to model grid switching costs and controlling energy system parameters to maintain configurations in the vicinity of the action functional’s stationary point.
- A system for autonomous vehicle control comprising: encoding the spatial and dynamic configuration of a vehicle and its environment as a mode configuration in the Unified Model Equation; computing safe traverse paths as closed orbits in the vehicle environment configuration space satisfying the Persistence Condition; verifying trajectory safety as a structural property of the configuration rather than a probabilistic estimate; generating deterministic control outputs that are causally traceable to specific environmental measurements; and providing explanation documentation for every control decision meeting DO 178C standards for safety critical airborne software and equivalent automotive safety standards.
- A financial market simulation and risk management system comprising: encoding market state dynamics as mode configurations in the Unified Model Equation framework; modelling market correlations as mode-winding overlaps between financial instrument configurations; computing the saturation threshold C_sat of market microstructure to identify liquidity crisis conditions; predicting cascade failure sequences in interconnected financial systems using transfinite interaction modelling ∂τI∞ and generating deterministic risk assessments with causally complete audit trails satisfying DORA, FCA and Basel III documentation requirements.
- A secure communications and cryptographic system comprising of encoding cryptographic keys as closed mode configurations satisfying the Persistence Condition; verifying key integrity through the mode pairing structure of the Superstate condition; detecting eavesdropping as perturbations to the balanced mode pairing architecture; generating quantum resistant encryption keys from topologically stable winding configurations that cannot be efficiently factored by Shor’s algorithm or similar quantum algorithms and providing post quantum cryptographic security grounded in the topological invariants of the configuration manifold.
- An agricultural yield optimization system comprising: encoding soil composition, atmospheric conditions, crop genetics and management practices as mode configurations; identifying optimal growing configurations as stationary points of the agricultural action functional; computing configuration trajectories from current state to optimal state as traversal paths in the crop configuration space; predicting yield outcomes from traverse resistance calculations and generating management recommendations as configuration-space navigation instructions with deterministic outcome predictions.
- A method for structural engineering and materials failure prediction comprising: encoding structural geometry, material properties and loading conditions as mode configurations in the Unified Model Equation; computing structural integrity as the distance from current configuration to the nearest saturation event; identifying failure modes as configurations in which the Persistence Condition can no longer be satisfied; predicting remaining service life as the traverse distance to the nearest failure configuration and generating maintenance recommendations as configuration space navigation paths that maintain structural configurations above the saturation threshold.
- A legal and regulatory compliance automation system comprising: encoding regulatory requirements, legal obligations and transactional records as mode configurations; computing compliance status as the configuration space distance from required to actual operational configuration; identifying non compliance conditions as configurations that violate the relevant closed orbit constraints; generating audit trails as causally complete traversal sequences in the compliance configuration space and providing deterministic compliance assessments satisfying EU AI Act Article 13 transparency requirements, GDPR Article 22 automated decision requirements and equivalent regulatory explainability obligations in all applicable jurisdictions.
Abstract
International Patent Classifications (IPC)
EPC Article 54 novelty confirmed
International phase pending
Inventor: Ricardo Jorge do Vale
ENTROPY CURVATURE FLUX TENSOR COMPUTATION METHODS: UNIFIED THERMODYNAMIC-GRAVITATIONAL ARCHITECTURE AND ITS APPLICATIONS TO INFRASTRUCTURE RESILIENCE, ENERGY SYSTEMS AND MULTI SCALE COMPLEX SYSTEM MODELLING
Field of the Invention
This invention relates to computational methods for implementing the entropy curvature coupling that arises naturally within the Unified Model Equation framework (UME™, SOZ-2026-001) specifically the coupling between mode count entropy S = k ln(N) which is derived from the differentiation structure of the configuration space and the curvature tensor of the configuration manifold M. The invention discloses methods for computing this coupling, its applications to thermodynamic and gravitational unification and its deployment in multi scale complex system modelling including critical infrastructure resilience, energy grid optimization and systems where cross scale coupling is the dominant failure mechanism.
Detailed Description — Entropy-Curvature Coupling
[0001] The Entropy Derivation from Mode Differentiation. The entropy of a configuration state is S = k ln(N), where k is the Boltzmann constant and N is the number of distinct mode configurations available to the system. N increases through the differentiation process where a configuration space reaches the saturation threshold C_sat, new modes can no longer coexist without coincidence and the probability of mode differentiation rises steeply as P_d = 1 − (1 − p₀)^(N·dC). Each differentiation event increases N, increasing entropy. The arrow of time is the direction of increasing differentiation which is a theorem derived from the mode structure and not a separate postulate of thermodynamics.
[0002] The Curvature-Entropy Coupling. In the UME framework, the curvature of the configuration manifold M at any point is determined by the local mode density gradient ∇ρ_M, where ρ_M is the number of distinct mode configurations per unit volume of M. High mode density → high curvature → high traverse resistance → gravitational effect. The entropy S = k ln(N) of a configuration is coupled to the curvature through the relationship R_μν − ½Rg_μν = (8πG/c⁴)(T_μν + T^entropy_μν) where T^entropy_μν is the entropy-contribution tensor derived from S. This coupling unifies thermodynamics and gravity within the single variational structure of the UME without additional postulates.
[0003] Cross Scale Interaction Modelling. The transfinite interaction term ∂τI∞ in the UME action functional encodes interactions that span multiple scales simultaneously. In infrastructure systems, cross-scale coupling is the primary mechanism of catastrophic failure: a component failure at the device scale propagates through the network scale, the service scale, the organizational scale and the societal scale with each transition governed by the entropy curvature coupling at the relevant scale boundary. Standard risk models treat each scale independently, missing the cascade mechanism entirely.
Claims — Patent EP22168432 / WO2024/GB001
- A method for computing entropy curvature flux in multi-scale systems comprising: (a) determining the mode count entropy S = k ln(N) of each scale layer of a system under analysis; (b) computing the curvature tensor R_μν of the configuration manifold at each scale from the mode density gradient ∇ρ_M; (c) computing the entropy curvature coupling tensor T^entropy_μν from the gradient of S with respect to the configuration coordinates; (d) identifying cross scale coupling strengths from the transfinite interaction integral ∂τI∞ evaluated at each scale boundary and (e) predicting cascade failure sequences as entropy curvature flux flows from high curvature to low curvature regions of the configuration manifold.
- The method of claim 1 applied to power grid resilience, wherein scale layers comprise individual generation units, transmission segments, distribution networks and consumer loads and cascade failures are predicted as entropy curvature flux sequences from generation loss events through transmission congestion to load shedding.
- The method of claim 1 applied to financial system stability, wherein scale layers comprise individual transactions, instrument price dynamics, portfolio level exposures and systemic market structure and contagion events are predicted as entropy curvature flux flows from individual instrument failures through correlation mediated cascade to systemic crisis.
- The method of claim 1 applied to healthcare system resilience, wherein scale layers comprise individual clinical systems, ward and departmental operations, hospital wide functions and regional healthcare network capacity and failure cascades are predicted as entropy curvature flux flows from device or system failure through clinical pathway disruption to patient safety impact.
- The method of claim 1 applied to internet and telecommunications infrastructure, wherein scale layers comprise physical layer components, network protocol layers, application service layers and platform ecosystem dependencies and outage cascades are predicted as entropy curvature flux flows from hardware failure through protocol-layer propagation to application-layer service disruption.
- A thermodynamic-gravitational unified computation system comprising: a mode differentiation engine that tracks the number of distinct configuration states N as a function of time and system parameters; an entropy computation module that determines S = k ln(N) continuously; a curvature computation module that determines R_μν from ∇ρ_M; an entropy-curvature coupling module that computes T^entropy_μν and evaluates its effect on the configuration manifold geometry and a trajectory prediction engine that integrates the coupled entropy curvature dynamics to predict the time evolution of complex systems.
- A method of predicting and preventing organizational entropy which the degradation of operational capability through increasing disorder in business processes, information flows and decision structures comprising of encoding organizational processes as mode configurations; computing the entropy S = k ln(N) of the process configuration space; identifying entropy increasing perturbations as configurations that increase N without compensating increases in operational output; computing the curvature of the organizational configuration manifold to identify structural rigidities that impede adaptation and generating reorganization recommendations as entropy-reducing traversal sequences in the organizational configuration space.
Scope of Application — Protected by Patent Portfolio
Applications Across Applicable Domains
The Unified Model Equation framework applies across every domain in which systems must be modelled, predicted, optimized or controlled deterministically.
The following is a representative and not exhaustive enumeration of protected applications.
- Clinical diagnostic AI — deterministic
- Drug-receptor binding prediction
- Molecular drug design and optimisation
- Protein structure and folding prediction
- Genomic variant pathogenicity assessment
- Radiological image analysis — auditable
- Surgical robotics trajectory planning
- ICU patient deterioration prediction
- Pandemic spread modelling
- Clinical trial outcome prediction
- Personalised medicine dosing systems
- Medical device failure prediction
- Hospital capacity and flow optimisation
- NHS digital transformation architecture
- Credit decisioning — DORA compliant
- Fraud detection — zero false negative
- Derivatives pricing — no Monte Carlo
- Portfolio risk — deterministic VaR
- Systemic contagion cascade prediction
- Regulatory capital optimisation
- AML transaction monitoring
- Insurance actuarial modelling
- Central bank policy impact simulation
- High-frequency trading risk controls
- Clearing house default prediction
- FCA / PRA explainability compliance
- DORA operational resilience testing
- Sovereign debt sustainability analysis
- Deterministic AI architecture design
- Causal complete decision engines
- Auditable autonomous agent systems
- EU AI Act compliance architecture
- Explainable AI for regulated industries
- Zero-hallucination inference systems
- Agentic workflow with kill-switches
- AI governance framework design
- Robotic process automation — traceable
- Natural language processing — auditable
- Computer vision — deterministic outputs
- Knowledge representation systems
- Reinforcement learning — safe bounds
- AI safety and alignment research
- Ballistic trajectory calculation
- Electronic warfare signal processing
- Radar and sonar target discrimination
- Autonomous weapon system safety bounds
- Secure communications — quantum-safe
- Intelligence analysis — deterministic
- Critical infrastructure threat modelling
- Military logistics optimisation
- Cyber defence — zero-day prediction
- SIGINT signal analysis
- Mission planning optimisation
- Sovereign AI systems — no foreign cloud
- Command and control decision support
- Nuclear safety system verification
- Power grid stability and optimisation
- Fusion reactor plasma control
- Nuclear safety system modelling
- Renewable energy yield forecasting
- Carbon capture system optimisation
- Climate tipping point prediction
- Smart grid demand management
- Battery chemistry optimisation
- Oil & gas reservoir modelling
- Environmental contamination spread
- Ecosystem collapse prediction
- Water system management
- Hydrogen fuel cell optimisation
- Energy storage system design
- Predictive maintenance — causal
- Process quality control — deterministic
- Supply chain cascade failure prediction
- Materials science — new discovery
- Semiconductor process optimisation
- Additive manufacturing path planning
- Structural integrity assessment
- Industrial IoT anomaly detection
- OT/IT convergence security
- Just-in-time logistics optimisation
- Factory layout optimisation
- Component lifecycle prediction
- Welding and joining quality assurance
- Robotics motion planning — safe
- Autonomous vehicle control — DO-178C
- Air traffic control optimisation
- Spacecraft trajectory calculation
- Railway signalling — EN 50128
- Maritime routing optimisation
- Aircraft structural fatigue prediction
- Engine performance modelling
- Traffic flow optimisation
- UAV swarm coordination
- Satellite orbit determination
- Re-entry trajectory prediction
- Accident causation modelling
- Hyperloop system dynamics
- Urban air mobility routing
- Disaster recovery architecture
- Business continuity planning — BIA
- Cloud migration — dependency mapping
- Cybersecurity threat modelling
- Zero-trust architecture design
- Network topology optimisation
- Quantum computing error correction
- Post-quantum cryptography
- Distributed systems consensus
- Database query optimisation
- Compiler optimisation
- Firmware verification — formal
- Operating system scheduler design
- Edge computing latency optimisation
- Standard Model parameter derivation
- Quantum gravity unification
- Dark matter identification
- Dark energy characterisation
- Cosmological constant derivation
- Particle mass prediction
- Strong CP problem resolution
- Neutrino mass determination
- Proton radius calculation
- QCD confinement proof
- Electroweak unification extension
- Baryon asymmetry derivation
- Gravitational wave source modelling
- Black hole information resolution
- Protein folding — deterministic
- Enzyme catalysis mechanism
- Cell signalling pathway modelling
- Evolutionary trajectory prediction
- Epidemiological spread modelling
- Cancer progression modelling
- Gene regulatory network analysis
- Metabolic pathway optimisation
- Microbiome interaction modelling
- Neuronal firing pattern analysis
- Immunological response prediction
- Agricultural pest management
- Synthetic biology circuit design
- CRISPR off-target prediction
- Critical national infrastructure protection
- Emergency response planning
- Digital public services architecture
- Tax system compliance modelling
- Social system stability analysis
- Border security system design
- Criminal justice risk assessment
- Pension system sustainability
- NHS capacity planning
- Government AI Act compliance
- Public spending optimisation
- Smart city infrastructure planning
- Electoral system integrity analysis
- Regulatory impact assessment
- Orbital mechanics — high precision
- Exoplanet detection algorithm
- Galaxy formation modelling
- Gravitational lensing prediction
- Pulsar timing analysis
- Cosmic ray source identification
- Space debris collision avoidance
- Interplanetary mission planning
- Gravitational wave detector design
- Black hole merger simulation
- Cosmological large-scale structure
- Solar activity prediction
- Space weather impact modelling
- Dark energy survey analysis
Patent applications GB2598745, US17/892,456, EP22168432, and WO2024/GB001 are the property of RJV Technologies Ltd (Company No. 11424986). All patent applications are pending.
The filing of these applications constitutes prior art establishing priority as of the stated filing dates. Any person or organization that implements, deploys or commercializes any system, method or composition that falls within the scope of the claims set out in these applications, whether in whole or in part, without the express written authorization of RJV Technologies Ltd, may be liable for patent infringement in the United Kingdom under the Patents Act 1977, in the United States under 35 U.S.C. §271, in the European Union under the European Patent Convention and in all PCT member states under their respective national patent legislation.
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