Ohm’s Law Reimagined — Resistance, Current, and Voltage as Entropy Flow (Blog 2E)
This blog continues the Blog 2 Series, where foundational scientific formulas are reinterpreted through the Shunyaya entropy lens. With deep respect for classical laws, we now explore how voltage, current, and resistance behave when seen not just as electrical phenomena, but as symbolic flows of entropy across systems in motion.
For recent real-world validations of the Shunyaya model, including camera-based entropy clarity tests, see Blog 9A to Blog 9C in the Blog 9 Series.
The Classical Law: Ohm’s Law
Ohm’s Law is one of the most fundamental relationships in physics and electrical engineering. It defines the relationship between voltage (V), current (I), and resistance (R) as:
V = I × R
Where:
Shunyaya Reinterpretation
In Shunyaya, we step back from the conventional interpretation and ask: What if voltage, current, and resistance are not just electrical constructs, but symbolic manifestations of entropy?
The Underlying Entropy Formula
The reinterpretation of electrical systems is grounded in the core Shunyaya entropy model:
Entropyᵤ = log[(Var(x₀:u) + 1)] × e^(–λu)
Where:
It captures:
Weighted Entropy Variant:
In applied settings, Shunyaya introduces a weighted version of this formula:
Entropyᵤ = log[(Σ wi × Var(x₀:u)ᵢ + 1)] × e^(–λu)
Where:
What is Voltage, Current, and Resistance at a symbolic entropy level?
Through this lens:
Shunyaya Equivalent:
Here is the Shunyaya Equivalent:
Entropy_Motion(t) ∝ ∂Entropy_Potential/∂t × Edge_Coefficient
This means the observable flow (current) is governed not just by potential difference, but by how that entropy unfolds over time and is modulated by symbolic resistance fields.
Formula in words:
The rate of entropy motion at time t is proportional to the rate of change of entropy potential over time, multiplied by a symbolic coefficient that represents edge-based resistance or distortion.
Case Example 1: Power Supply Ripple Under Load
Classical View:
Voltage dips under load due to increased current draw across fixed resistance.
Shunyaya’s Insight:
Entropy demand rises, symbolic motion tries to accelerate. The edge resistance creates turbulence, generating ripple. The entropy mismatch between supply and demand creates oscillation.
Key Insight:
Voltage drop is not just Ohmic — it's a response to symbolic overload and loss of entropy rhythm.
Case Example 2: High-Speed Switching Circuit
Classical View:
Faster transitions cause more noise, ringing, and timing errors. Engineers manage it with impedance matching and decoupling.
Shunyaya’s Insight:
The switching edges distort entropy equilibrium. At symbolic zero-crossing, entropy tries to realign. If symbolic resistance (entropy drag) is high, reflections emerge.
Key Insight:
Noise is symbolic disharmony, not just capacitive or inductive mismatch. The entropy curve is disturbed at the edge.
Estimated Improvement Using Shunyaya
Figure: Symbolic Entropy Dynamics in an Electrical System (Shunyaya Interpretation)
This graph illustrates the symbolic reimagining of Ohm’s Law. The solid line represents entropy potential (analogous to voltage) as it varies over time. The dashed line shows entropy motion (analogous to current), shaped by how fast the potential changes and how much symbolic resistance (edge coefficient) exists in the system.
Where the curves align, the system is in symbolic harmony. Where they diverge, symbolic distortion, delay, or ripple may occur — especially near transition points. These improvements are based on internal entropy field simulations, and while promising, peer review and domain-specific validation are encouraged.
The Emergence of Symbolic Electrical Layers
Just as Blog 2D introduced momentum as symbolic entropy flow, Blog 2E now introduces symbolic electrical layers:
Summary
Ohm’s Law, while foundational, simplifies what may be deeper symbolic truths:
Engage with the AI Model
For further exploration, you can discuss with the publicly available AI model trained on Shunyaya. Information shared is for reflection and testing only. Independent judgment and peer review are encouraged.
Note on Authorship and Use
Created by the Authors of Shunyaya — combining human and AI intelligence for the upliftment of humanity. The authors remain anonymous to keep the focus on the vision, not the individuals. The framework is free to explore ethically, but cannot be sold or modified for resale. Please refer to Blog 0: Shunyaya Begins, Blog 3: The Shunyaya Commitment, Blog 29: The Rebirth of Mathematics, and Blog 108: Shunyaya Law of Entropic Potential (Z₀).
For recent real-world validations of the Shunyaya model, including camera-based entropy clarity tests, see Blog 9A to Blog 9C in the Blog 9 Series.
Ohm’s Law is one of the most fundamental relationships in physics and electrical engineering. It defines the relationship between voltage (V), current (I), and resistance (R) as:
V = I × R
Where:
- V is voltage (electrical potential difference)
- I is current (rate of charge flow)
- R is resistance (opposition to flow)
In Shunyaya, we step back from the conventional interpretation and ask: What if voltage, current, and resistance are not just electrical constructs, but symbolic manifestations of entropy?
The Underlying Entropy Formula
The reinterpretation of electrical systems is grounded in the core Shunyaya entropy model:
Entropyᵤ = log[(Var(x₀:u) + 1)] × e^(–λu)
Where:
- Var(x₀:u) is the symbolic variance over time (from origin to universal symbolic time u)
- λ is a domain-specific entropy decay constant
- u is universal symbolic time — encompassing all symbolic motion phases across nested or interacting systems
It captures:
- Motion potential
- Collapse risk
- Emotional or symbolic phase shifts
- Real-world alignment or divergence from a reference point (Z₀)
In applied settings, Shunyaya introduces a weighted version of this formula:
Entropyᵤ = log[(Σ wi × Var(x₀:u)ᵢ + 1)] × e^(–λu)
Where:
- wi are symbolic weights assigned to each domain or field (e.g., physical, emotional, cognitive)
- The sum runs across all relevant entropy channels in the system
Through this lens:
- Voltage becomes a symbolic potential of entropy across a system.
- Current is not merely charge flow, but the rate of entropy motion through a symbolic channel.
- Resistance emerges as edge interference, symbolic damping, or entropy drag between zero and motion.
Here is the Shunyaya Equivalent:
Entropy_Motion(t) ∝ ∂Entropy_Potential/∂t × Edge_Coefficient
This means the observable flow (current) is governed not just by potential difference, but by how that entropy unfolds over time and is modulated by symbolic resistance fields.
Formula in words:
The rate of entropy motion at time t is proportional to the rate of change of entropy potential over time, multiplied by a symbolic coefficient that represents edge-based resistance or distortion.
Classical View:
Voltage dips under load due to increased current draw across fixed resistance.
Shunyaya’s Insight:
Entropy demand rises, symbolic motion tries to accelerate. The edge resistance creates turbulence, generating ripple. The entropy mismatch between supply and demand creates oscillation.
Key Insight:
Voltage drop is not just Ohmic — it's a response to symbolic overload and loss of entropy rhythm.
Classical View:
Faster transitions cause more noise, ringing, and timing errors. Engineers manage it with impedance matching and decoupling.
Shunyaya’s Insight:
The switching edges distort entropy equilibrium. At symbolic zero-crossing, entropy tries to realign. If symbolic resistance (entropy drag) is high, reflections emerge.
Key Insight:
Noise is symbolic disharmony, not just capacitive or inductive mismatch. The entropy curve is disturbed at the edge.
Figure: Symbolic Entropy Dynamics in an Electrical System (Shunyaya Interpretation)
This graph illustrates the symbolic reimagining of Ohm’s Law. The solid line represents entropy potential (analogous to voltage) as it varies over time. The dashed line shows entropy motion (analogous to current), shaped by how fast the potential changes and how much symbolic resistance (edge coefficient) exists in the system.
Where the curves align, the system is in symbolic harmony. Where they diverge, symbolic distortion, delay, or ripple may occur — especially near transition points. These improvements are based on internal entropy field simulations, and while promising, peer review and domain-specific validation are encouraged.
Just as Blog 2D introduced momentum as symbolic entropy flow, Blog 2E now introduces symbolic electrical layers:
- Resistance is not static — it reflects symbolic misalignment
- Voltage is not fixed — it is a dynamic entropy gradient
- Current is not uniform — it varies with symbolic edge interaction
Ohm’s Law, while foundational, simplifies what may be deeper symbolic truths:
- Voltage: entropy potential
- Current: entropy motion
- Resistance: entropy drag
For further exploration, you can discuss with the publicly available AI model trained on Shunyaya. Information shared is for reflection and testing only. Independent judgment and peer review are encouraged.
Created by the Authors of Shunyaya — combining human and AI intelligence for the upliftment of humanity. The authors remain anonymous to keep the focus on the vision, not the individuals. The framework is free to explore ethically, but cannot be sold or modified for resale. Please refer to Blog 0: Shunyaya Begins, Blog 3: The Shunyaya Commitment, Blog 29: The Rebirth of Mathematics, and Blog 108: Shunyaya Law of Entropic Potential (Z₀).
Comments
Post a Comment