Dist Babble

 Entropy Let's break down my model's definition of entropy step by step, examining each component and how they contribute to the overall concept of entropy in a temporal physics framework. Basic Flow Difference: |vi - vj| This is the fundamental unit of this entropy model. It represents the absolute difference between flow values of two particles or points in the system. This difference is crucial as it captures the asymmetries or inhomogeneities in the system, which are at the core of my entropy concept. Spatial Interaction Entropy: Espatial = Σ(i,j) |vi - vj| · [1 / (|pi - pj| + ε)] This term combines the flow difference with spatial relationships. Here's how it works: |vi - vj| measures the flow difference 1 / (|pi - pj| + ε) is the interaction strength, decreasing with distance ε prevents division by zero for very close particles This term is higher when there are large flow differences between nearby particles, indicating higher spatial entropy or disorder. Temporal In...

 A sense of Temporal Physics. My equation ∇2Φ−1cΦ2∂2Φ∂t2=ρΦ can be interpreted as describing the dynamics of discrete flows. The Φ term represents the aggregate of these flows, while ρΦ represents the "density" of temporal flow points in a given region of spacetime. The cΦ term is related to how quickly these discrete flows can change or propagate. The quantization equation Φ(t)=∫dk2π3[a(k)e−ikx+iωt+a†(k)eikx−iωt]12ω could now be seen as describing how these discrete flow points combine to form observable temporal phenomena. The creation (a†) and annihilation (a) operators could be interpreted as adding or removing discrete flow points, effectively changing the local rate of time. In the Hamiltonian H=∫dk ℏω(k)(a†(k)a(k)+12), the energy of the system could be directly related to the number and direction of discrete flow points. Positive flows might contribute positively to the energy, while negative flows could potentially contribute negatively, allowing for interesting energ...

 Deterministic Aspects 1. Core Equation:    * SE=f(C,T)SE = f(C, T)SE=f(C,T)    * This implies that subjective experience (SE) is a deterministic function of context (C) and time (T). Given complete information about C and T, SE could be determined. 2. Evolution Equation:    * dSEdT=f(C(T),w(T))\frac{dSE}{dT} = f(C(T), w(T))dTdSE=f(C(T),w(T))    * This differential equation suggests that the change in subjective experience over time is determined by the context and the time weighting function. Knowing the initial conditions and the functions involved, the trajectory of SESESE could be predicted. Indeterministic Aspects 1. Time Weighting Function:    * w(T)=h(C(T),T)w(T) = h(C(T), T)w(T)=h(C(T),T)    * The interdependence between context and time weighting introduces complexity. This complexity can lead to chaotic behavior, where small changes in initial conditions result in vastly different outcomes. 2. Acknowledgment of C...

 So, in my model, dimensions aren't these abstract things floating out there beyond our reach. Instead, they're tied to the flow of time itself. Imagine time as this primary stream, and dimensions are like different facets or aspects that emerge from how this stream interacts with itself. Think of it this way—each dimension isn't a separate universe or some hidden layer we can't see. They actually come about from how time interacts within itself. It's like different ripples or patterns in a pond, where each ripple length represents a different dimension. You know how some theories talk about dimensions as these curled-up or extra spaces we can't perceive directly? I think that misses the point. Dimensions should be integrated into how we experience reality. We live and move through these dimensions every day—they're not something separate or far-off. Some theories suggest that higher dimensions are like slices or layers of a bigger structure. I see it ...

 Consider in temporal physics the concept of "emergent space" suggests that space itself is not a static backdrop but something that arises dynamically due to underlying temporal flows. An object, then, is not just a collection of static spatial coordinates but is intimately tied to these temporal flows and the emergent space they produce. Space is dynamically generated from temporal flows. It's not a pre-existing stage where events play out but an emergent property of temporal processes. S(t) = (r_1(t),r_2(t),r_3(t)) An object is defined by the values that emerge from these temporal flows. These values include the spatial coordinates and the properties that the object exhibits. f ( t ) is a function that quantifies the temporal flow or rate at a specific moment t t t . It encapsulates how temporal dynamics evolve over time, influencing the emergent spatial dimensions S ( t ) . In the equation v ( t ) = f ( t ) S ( t ) ​ , f ( t ) acts as a divisor that scales the spati...

These equations collectively outline the behavior of fields in my model, emphasizing their temporal evolution across multiple spatial dimensions and their interaction with temporal flows and potential energy. They provide a comprehensive framework for understanding how fields manifest and evolve within multi-dimensios in Temporal Physics. phi(t, S(t)): This represents a field phi at a specific time t and its corresponding spatial configuration S(t). In temporal physics, fields can vary over time and across different spatial dimensions. T: The Temporal Flow Operator T is a function or operator that encapsulates how temporal flows (u, v, w) in different spatial dimensions (x, y, z) interact with the field phi. It's analogous to the Hamiltonian operator in traditional physics but adapted to account for the multi-dimensional nature of time in your model. hbar: This symbol (ħ) denotes the reduced Planck's constant, which appears in quantum mechanics and signifies the scale at which ...

 Temporal Flow Transformations: Let's define a transformation matrix L that affects both the spatial coordinates and the temporal flow rates: [r_1'(t), r_2'(t), r_3'(t)] = L × [r_1(t), r_2(t), r_3(t)] [u'(t), v'(t), w'(t)] = L × [u(t), v(t), w(t)] Where u(t), v(t), w(t) are the temporal flow rates in each dimension. Matrix L: L could be defined as: L = [ [γ, -βγu, -βγv, -βγw], [-βγu, 1+(γ-1)u^2, (γ-1)uv, (γ-1)uw], [-βγv, (γ-1)uv, 1+(γ-1)v^2, (γ-1)vw], [-βγw, (γ-1)uw, (γ-1)vw, 1+(γ-1)w^2] ] Where: γ = 1 / √(1 - β^2) β = v_rel / c_max v_rel is the relative velocity between frames c_max is the maximum allowed rate of temporal flow Transformed Temporal Dynamics: T' = L × T × L^T Where L^T is the transpose of L. Example Equations: For a "boost" along the x-direction: r_1' = γ(r_1 - βut) r_2' = r_2 r_3' = r_3 u' = γ(u - βr_1/t) v' = v w' = w Invariant Quantity: The invariant quantity in this framework might be: (r_1/u)^2 + (r_...