Fundamental Principle Of Causality Research Articles

All electromagnetic scattering bodies are matrix-valued oscillators

Scattering theory is the basis of all linear optical and photonic devices, whose spectral response underpins wide-ranging applications from sensing to energy conversion. Unlike the Shannon theory for communication channels, or the Fano theory for electric circuits, understanding the limits of spectral wave scattering remains a notoriously challenging open problem. We introduce a mathematical scattering representation that inherently embeds fundamental principles of causality and passivity into its elemental degrees of freedom. We use this representation to reveal strong constraints in the mathematical structure of scattered fields, and to develop a general theory of the maximum radiative heat transfer in the near field, resolving a long-standing open question. Our approach can be seamlessly applied to high-interest applications across nanophotonics, and appears extensible to general classical and quantum scattering theory.

Real and Imaginary Properties of Epsilon-Near-Zero Materials.

From the fundamental principle of causality we show that epsilon-near-zero (ENZ) materials with a very low (asymptotically zero) intrinsic dielectric loss do necessarily possess a very low (asymptotically zero) group velocity of electromagnetic wave propagation. This leads to the loss function being singular and causes high nonradiative damping of the optical resonators and emitters (plasmonic nanoparticles, quantum dots, chromophore molecules) embedded into them or placed at their surfaces. Rough ENZ surfaces do not exhibit hot spots of local fields suggesting that surface modes are overdamped. Reflectors and waveguides also show very large losses both for realistic and idealized ENZ materials.

On the Future of Information: Reunification, Computability, Adaptation, Cybersecurity, Semantics

The vulnerability of software and the Internet and the accumulation of unprocessed information in big data are serious problems in informatics. Both are human-related. The former was traced to flaws caused by human interventions in development. In the latter case, humans also intervene to connect the dots, find meaningful patterns, and make sense of the information. The proposed solutions are based on more human interventions, which tend to aggravate the problems rather than solving them. I propose the complete elimination of human interventions in both cases. This goal is conceptually easy to achieve. The approach, however, is radical and theoretical. It considers the causal set, a mathematical object, as the universal language underlying all information in nature and, hence, also all computation. This assumption is recognized as the fundamental principle of causality, that effects follow their causes. The new theory is based solely on the causal set, its metric, and its vast array of algebraic properties. The consequences are unexpected, fascinating, and totally new. Since translations between causal sets and programming languages are easy, I also propose to confine the use of programming languages to the human interface, and create an inner layer of mathematical code expressed as a causal set. Machines talk only to mathematically verified, bug-free, secure code. Included in this paper are experimental and computational verifications of the theory, proposed applications to Internet vulnerability, science and technology, machine learning, computer intelligence, and details for building a first prototype.

Causal Groupoid Symmetries

Proposed here is a new framework for the analysis of complex systems as a non-explicitly programmed mathematical hierarchy of subsystems using only the fundamental principle of causality, the mathematics of groupoid symmetries, and a basic causal metric needed to support measurement in Physics. The complex system is described as a discrete set S of state variables. Causality is described by an acyclic partial order w on S, and is considered as a constraint on the set of allowed state transitions. Causal set (S, w) is the mathematical model of the system. The dynamics it describes is uncertain. Consequently, we focus on invariants, particularly group-theoretical block systems. The symmetry of S by itself is characterized by its symmetric group, which generates a trivial block system over S. The constraint of causality breaks this symmetry and degrades it to that of a groupoid, which may yield a non-trivial block system on S. In addition, partial order w determines a partial order for the blocks, and the set of blocks becomes a causal set with its own, smaller block system. Recursion yields a multilevel hierarchy of invariant blocks over S with the properties of a scale-free mathematical fractal. This is the invariant being sought. The finding hints at a deep connection between the principle of causality and a class of poorly understood phenomena characterized by the formation of hierarchies of patterns, such as emergence, selforganization, adaptation, intelligence, and semantics. The theory and a thought experiment are discussed and previous evidence is referenced. Several predictions in the human brain are confirmed with wide experimental bases. Applications are anticipated in many disciplines, including Biology, Neuroscience, Computation, Artificial Intelligence, and areas of Engineering such as system autonomy, robotics, systems integration, and image and voice recognition.

Causal Mathematical Logic as a guiding framework for the prediction of “Intelligence Signals” in brain simulations

Abstract A recent theory of physical information based on the fundamental principles of causality and thermodynamics has proposed that a large number of observable life and intelligence signals can be described in terms of the Causal Mathematical Logic (CML), which is proposed to encode the natural principles of intelligence across any physical domain and substrate. We attempt to expound the current definition of CML, the “Action functional” as a theory in terms of its ability to possess a superior explanatory power for the current neuroscientific data we use to measure the mammalian brains “intelligence” processes at its most general biophysical level. Brain simulation projects define their success partly in terms of the emergence of “non-explicitly programmed” complex biophysical signals such as self-oscillation and spreading cortical waves. Here we propose to extend the causal theory to predict and guide the understanding of these more complex emergent “intelligence Signals”. To achieve this we review whether causal logic is consistent with, can explain and predict the function of complete perceptual processes associated with intelligence. Primarily those are defined as the range of Event Related Potentials (ERP) which include their primary subcomponents; Event Related Desynchronization (ERD) and Event Related Synchronization (ERS). This approach is aiming for a universal and predictive logic for neurosimulation and AGi. The result of this investigation has produced a general “Information Engine” model from translation of the ERD and ERS. The CML algorithm run in terms of action cost predicts ERP signal contents and is consistent with the fundamental laws of thermodynamics. A working substrate independent natural information logic would be a major asset. An information theory consistent with fundamental physics can be an AGi. It can also operate within genetic information space and provides a roadmap to understand the live biophysical operation of the phenotype

Apparent entropy, residual entropy, causality, metastability, constraints, and the glass transition

Abstract A thermodynamic framework for the investigation of ‘residual entropy’ and related phenomena is developed, expanding and clarifying the work of Kivelson and Reiss and the important work of several other investigators. The main difficulties encountered in the development of such a framework are the need to deal with constrained equilibrium as well as to include irreversible processes in the overall study. These challenges are met by using the device of auxiliary constraints and the equivalent equilibrated states that they produce. The importance of a thermodynamic framework is tied to the fact that evolving molecular theories of residual entropy, which also impact the glass transition, no matter how sophisticated, invariably contain approximations whose effects are hard to assess. Thus a thermodynamic framework provides a vehicle within which the internal consistency of a theory can be tested. Phenomena that are treated in such a framework, along with others, are those mentioned in the title of this paper. The concept of residual entropy , its reality or unreality, is often considered to be an unimportant issue. The findings of this paper, besides emphasizing the unreality of residual entropy, show that the question of its existence is a significant one. Among other things, the fundamental principle of causality is involved and we should not be so cavalier as to dispense with it. Among other rigorous analysis we present an argument involving an ideal binary solution whose behavior as the limiting behavior of a real solution provides access, in principle, to experiment. The argument does make the generally accepted assumption that, at equilibrium at 0 K, pure crystals of the binary system’s components have zero entropy. It strongly suggests that residual entropy, in general, is an impression that stems from the inclusion of an irreversible step in an experimental thermodynamic cycle.

Comment on “Criterion for Negative Refraction with Low Optical Losses from a Fundamental Principle of Causality”

Comment on “Criterion for Negative Refraction with Low Optical Losses from a Fundamental Principle of Causality”

Criterion for Negative Refraction with Low Optical Losses from a Fundamental Principle of Causality

From the fundamental requirement of causality, we derive a rigorous criterion of negative refraction (left handedness). This criterion imposes the lower limits on the electric and magnetic losses in the region of the negative refraction. If these losses are eliminated or significantly reduced by any means, including the compensation by active (gain) media, then the negative refraction will disappear. This theory can be particularly useful in designing new left-handed materials: testing the expected polarizabilities of a medium against this criterion would check the compliance with the causality and verify the design feasibility.

The real effects of pseudo forces

A clear comprehension of the Newtonian notion of force remains elusive to many students due to lack of experience with observations in a noninertial frame of reference. In this article is described a software that can be easily run on a desktop computer and which acquaints the student user with the Newtonian notion of force. Fundamental principles of causality and determinism in Newtonian mechanics are elucidated.

Early Differentiation of Causal Mechanisms Appropriate to Biological and Nonbiological Kinds

Although Piaget characterized young children as precausal until about 7-8 years of age, recent work indicates that preschoolers do honor fundamental principles of causality. This literature has mainly focused on general principles invoked in reasoning about mechanical events. By contrast, the present study examined whether children differentiate between the causal mechanisms appropriate for different conceptual domains. The results of 3 preliminary investigations and 1 main experiment suggested that preschoolers prefer natural mechanisms for color inheritance in biological kinds, particularly when causal substrates resemble their consequences. By contrast, the same children recognized the importance of human intentions in producing the color of an artifact, and also judged that mechanical mechanisms serve to mediate between intentions and outcomes. The results are relevant to recent studies on the development of biological thought, and overall suggest that early causal reasoning reflects both domain-specific and domain-general principles.