Out of Physics Crisis: Reality instead of Possibility

The crisis of physics with nothing really new for 100 years since the arrival of Einstein's General Theory of Relativity GR theory and Quantum Mechanics QM (modulo the Atomic Bomb and the Standard Model from the 1960s), is well captured in the books Bankrupting Physics: How Today's Top Scientists are Gambling Away Their Credibility by Alexander Unzicker and Sheilla Jones and The Quantum Ten: A Story of Passion, Tragedy, Ambition by Sheilla Jones. The crisis is deepened by incompatibility of GR and QM, which has persisted with no resolution in sight. 

I argue on this blog under Quantum Contradictions  supported by Real QM that the basic reason for incompatibility is that QM concerns possibilities while GR concerns actualities or realities. This means that the main burden for the crisis is carried by QM since the prime role of physics must be to say something about the real world rather than a possible world which will/can not ever occur. It is here possible to reduce GR to Newton's theory of gravitation, since GR only concerns utterly small effects or utterly extreme situations. 

The fact that QM is concerned with possibilities is expressed by the nature of the wave function 

• $\Psi (x_1,x_2,....,x_N)$

describing the configuration of a system of $N$ particles/electrons with $x_i$ describing the possible position in 3d space (at some time) of particle $i=1,2,...,N$. The wave function $\Psi (x_1,...,x_N)$ thus depends on $3N$ spatial variables (plus time) with $\vert\Psi\vert^2(x_1,....,x_N)$ expressing the probability of the particle configuration with coordinates $(x_1,...,x_N)$, and evolves in time according to the Schrödinger equation, thus from possibility to possibility. 

The basic trouble with QM in this $3N$-dimensional form is that computation of $\Psi $ with a resolution of say $10^2$ in each spatial variable requires $10^{6N}$ mesh points which fills any thinkable computer as soon as N is not very small. The QM world of possibilities is thus so rich that it is not accessible through computation, and if it is not accessible through computation, then it cannot tell something. The step from possibility to actuality/reality is in QM taken by something called "collapse of the wave function", which is the basic mystery behind the crisis/incompatibility. 

Real Quantum Mechanics presents an alternative theory in the form of a system of $N$ electron charge densities in shared 3d space, thus basically a classical continuum mechanical system in 3d space, which is readily computable even for large $N$. 

Real QM thus offers a way out of the crisis. Give it a try, after 100 years of unsuccessful attempts to reconciliation with GR/Newton: 

• Real QM is fully compatible with GR/Newton's theory! 
• Real QM is computable and can tell something! 
• Real QM fits with observation.  

Physics Collectivism vs Mathematics Individualism

It is sometimes claimed that physics is a collective effort, while mathematics is rather a collection of individual efforts. Let us test this hypothesis by analysing the use of the first person plural pronoun "we".  

Let us start with physics noting how Andrew Strominger as a modern physicist of reputation invited by Lex Fridman to an interview entitled Black Holes, Quantum Gravity, and Theoretical Physics responds the following question by Lex:

• What is the effort of quantum gravity (to reconcile the standard model and general theory of relativity as the main open problem of modern physics)?

Andrew tells Lex:

• The one fully consistent model we have is string theory.
• We do not know if in any sense string theory describes the world.

We see that Andrew uses the pronoun "we" to send a message that modern physics is a collective effort, or more precisely a selective collective effort performed by an inner circle of leading modern physicists. For someone outside this group (which is not well defined) to say "we" in this context would be pretentious. By using an exclusive "we" Andrew signals that he belongs to the inner circle. 

There is another inclusive "we" often used in mathematical reasoning starting with a phrase like "We assume that x is a positive real number". Here "we" includes the reader or just anybody without asking for any qualification.

We know that the mathematics of Calculus was invented (in competition) by Leibniz and Newton, who both could say with confidence that "I invented Calculus", but never "We invented Calculus". 

More generally, a mathematician would rarely use "we" in the exclusive inner circle meaning, since the inner circle typically would have only one member. Mathematical theorems or theories mostly carry just one name like Brouwer's Fixed Point Theorem or Galois Theory. 

Maybe this indicates a difference between (modern) physics and mathematics, with physics being shared by physicists as some form of common reality or fiction, while mathematics is a human construct created by individuals like pieces of literature or art as individual efforts. 

But it may be tempting for both a physicist and mathematician to use "we" to signal membership in some group of prestige behind some theorem/theory. You can make your own observations...

On Wolfram's Concept of Computational Irreducibility

This is a continuation of the previous post.

Computational Irreducibility CI is used by Stephen Wolfram to describe that prediction of the state of a system requires full resolution of the evolution of the system by computation; to predict the outcome of tossing a coin by computation requires precise resolution of the motion of the coin from toss to landing. Wolfram seeks an explanation of the 2nd Law in terms of CI as an expression of Computational Impossibility. 

Wolfram's agenda (initiated when he was 12) connects to mine (since 90s), both serving to give an explanation of the 2nd Law or irreversibility or direction of time, based on computation, although fundamentally different in details. 

As a key example I consider turbulent fluid flow which is (mean-value) computable forward in time but not backward in time, thus computationally reducible forward in time but computationally irreducible backward in time, which gives time a direction. More precisely, consider an airplane wing moving through air from left to right meeting still air and leaving a wake of turbulent air. Drag and lift of the wing as force mean values are computable without resolving the flow to physical scale, thus expressing computational reducibility as shown in the book Computational Turbulent Incompressible Flow. 

However, reversing the flow with thus incoming turbulent flow from the right, will not give back the still air to the left, but instead a turbulent wake. To return to still air at the left after reversing the flow, would require solving an exponentially unstable problem without any cancellation (in associated linearised dual problem), thus suffering from CI.

The flow of air around a wing is thus an example of irreversible flow, with the irreversibility resulting from lack of cancellation in laminar flow, as carefully explained in the book. The forward problem is computationally reducible, while the backward problem is computationally irreducible = Irreversibility = 2nd Law. 

Turbulent dissipation of large scale kinetic energy into small scale heat energy can serve as a prime example of an irreversible process, which is open to study by computational solution of the Euler/Navier-Stokes equations, see post on Euler CFD and Euler's Dream. Construction of such a model from scratch in the spirit of Wolfram's New Kind of Science has not been made. More generally, processes involving some form of friction or other losses are irreversible for the same reasons as presented. 

A key fact is that these losses cannot be avoided, because forward evolution without losses requires infinite precision/infinite computational yet is necessary, while the show must go on and the show is not just heat diffusion. 

Recall that heat diffusion is easy forward but difficult backward and so is an example of irreversibility, but a trivial example. Turbulent flow is a non-trivial example. 

Wolfram's computational physics has been met with skepticism by the physics community, and so his version of the 2nd Law may not be applauded. My version stays closer to real physics in the form of real turbulent flow... 

It is remarkable the the simple code of Euler CFD (as an extended version of the 5-point scheme for the 2d Laplacian) generates the whole spectrum of turbulent flow. Remarkable.

Recall the essence of the 2nd Law: Physical systems with nearby particles moving with different velocities, typically arising in slightly viscous flow turning turbulent or moving parts mechanics under friction, develop increasing velocity gradients controlled by turbulent/friction dissipation into heat energy as small scale unordered kinetic energy. This is an irreversible process which cannot be avoided. 

In other words: Perpetuum mobile in the form of a system with moving parts is impossible: There will always be some turbulence/friction transforming motion into heat energy in an irreversible process. 

On the other hand an atom in ground state is a form of perpetuum mobile, but then in the form of a system without moving parts, as explained in Real Quantum Mechanics: Electrons in ground state do not move around the kernel, but rather turn around like someone unable to get to sleep, while the electron density is stationary. On the other hand, in a radiating atom, electron densities do shift between energy levels under energy exchange.   

Elaboration of Wolfram's Explanation of the Second Law

da Vinci's explanation of the 2nd Law = Mine.

Stephen Wolfram is now presenting work on the 2nd Law of Thermodynamics based on the notion of computation, which connects to a view I have been advocating. The role the 2nd Law is to give an explanation in mathematical terms of the observed fact that certain macroscopical physical processes are irreversible even though the underlying microscopics based on Newton's Laws appears to be reversible. 

Boltzmann tried to give an explanation in terms of statistics, which has not convinced Wolfram nor me, since we have both tried to replace statistics by computation as a process taking a system from one configuration at a certain time $t$ to a next configuration at $t+dt$ with $dt$ a small time step.  My theory is presented in the books Computational Turbulent Incompressible Flow and Computational Thermodynamics with Johan Hoffman and blog posts.

I will not here seek to summarise Wolfram's theory, which he admits is not easy to fathom, but just briefly recall the elements of my theory which is different by qualifying the general idea of computation in terms of the concepts of (i) finite precision computation and (ii) stability/well-posedness (connecting to Wolfram's computational irreducibility).

The phenomenon of turbulence of fluid motion demonstrates the role of (i) and (ii) in explaining why certain processes are not reversible. The basic feature of turbulent flow is that it contains a range of scales from large to small with large carrying kinetic energy in ordered coherent form and small carrying heat energy as unordered incoherent form. 

Fluid flow may be seen as initiated in large scale coherent form like the laminar flow in a river before a water fall in which it transforms into small scale turbulent flow by the fall developing strong velocity gradients, see picture above. In the fall coherent laminar flow develops into turbulent flow thus transforming large scale coherent kinetic energy into small scale incoherent heat energy. 

This is a stable process in the sense that the large scales and amount of heat energy will change little under finite precision of the computational process over a time. In other words, the large scale forward process is stable or well-posed. It is possible to break down large scale kinetic motion into small scale heat energy with only finite precision = Easy. You can easily break a glass by a hammer without much precision.

On the other, reversing the flow through the water fall is impossible, because it would require infinite precision to coordinate incoherent small scale turbulent flow/heat energy into large scale laminar flow /kinetic energy = Difficult. To assemble a glass smashed into pieces is difficult/impossible. 

Digital computation has finite precision. We do not have to ask physical processes to be carried out by some form of computation with infinite precision; finite precision is enough.  

Summary of Irreversibity/2nd Law: 

• Forward motion in time is possible/easy under finite precision: physics. 
• Backward motion in time is impossible/difficult under finite precision: not physics.          

PS1 Wolfram gives a (human) observer with certain perception capabilities a key role, like in the Copenhagen interpretation of quantum mechanics. But a Universe without observer is also a Universe maybe of more fundamental interest. 

PS2  There is a connection to both previous and next post describing turbulent flow as predictable chaotic and irreversible flow.   

Predictive Chaos

A common argument in the current debate about global climate is that the Earth climate system is chaotic and so cannot be computationally modeled and predicted. The argument is used to question alarmistic predictions of climate change, but also open to unrestricted alarmism in the sense that anything can happen from virtually nothing. 

Basic examples of chaotic systems are (i) coin tossing and (ii) turbulent fluid motion. In both cases pointwise prediction in space and time is impossible, but mean-values can be predicted with high precision. In coin tossing with a perfect coin the quotient of number of heads and tails quickly approach 1 as the number of tosses increases. The drag and lift as mean-values in space and time of the forces on an airplane wing subject to turbulent flow of air, can be accurately computationally predicted by solving the Navier-Stokes equations. This is the subject of the monumental treatise Computational Turbulent Incompressible Flow. See also previous posts under label chaotic system.  

How is it possible that mean-values can be accurately computed but point-values not? The reason is that turbulent flow is (like the weather) fluctuating with alternating ups and downs (like the motion of a tossed coin before landing). Therefore mean-values can be predicted by computational simulation of the fluctuations without asking for point-wise accuracy. 

We understand that chaotic motion as fluctuating turbulent motion in a certain sense is more predictive than non-fluctuating motion like that of a pen left in upright position.

While the weather as pointwise chaotic motion is not predictable over more than a week, climate as mean value of weather changes only slowly and so can be predictive, more or less. For example, we can well expect to enter into a new ice age within hundreds of years as an effect of major factors like the orbit of the Earth. 

Stock markets appear chaotic, yet can be predicted over time using models including major relevant factors. 

In any case, reference to chaotic systems as being unpredictable can be misleading and so has to be qualified.  

PS This post connects to the previous post on the unfortunate present formulation of the Navier-Stokes Clay Millennium Problem forgetting the completely foundational aspect of well-posedness in the sense of small output effects of small perturbations, which is a property of turbulent solutions of Navier-Stokes equations: Drag and lift of a wing remain the same under small perturbations of incoming flow and geometry. The present formulation appears to confuse smoothness with well-posedness.

Terence Tao on the Navier-Stokes Millennium Problem

This is a continuation a previous post on the Navier-Stokes Clay Mathematics Institute Millennium Problem stimulated by a recent article uploaded by Terence Tao: 

• Quantitative bounds for critically bounded solutions to the Navier-Stokes equations

arguing that:

• If a certain norm of the solution stays bounded (or grows at a controlled rate), then the solution stays regular.
• Taken in the contrapositive, they assert that if a solution blows up at a certain finite time T, then certain norms of the solution must also go to infinity.

The certain norm can be the $L^3$ norm over the spatial domain of the velocity $u(t)$ for $t<T$, which thus would serve as an indicator for solution of the Navier-Stokes Millennium Problem. 

I have in sequence of posts expressed criticism of the formulation of the Millennium Problem which can be condensed into: 

• The normalisation to unit viscosity means that the physics of turbulence, which appears for small viscosity and bounded flow velocities, is missing. This makes the Millennium Problem into a purely academic mathematical problem without significance to the real world of fluid flow (and so probably violating the intention of Mr Clay). 
• More precisely, a turbulent solution would not be a classical regular solution nor a solution with unbounded velocities, thus a solution outside the present formulation of the Millennium Problem.

It is thus natural to ask for a reformulation of the Navier-Stokes Problem, in particular since no advance towards a solution in the original formulation has been made since 2000. Compare with this article on Knowino. 

PS This post was triggered by a new comment to the original post by Terence from 2019. See also my next post here. 

John Clauser: Crisis of Nobel Pseudoscience

2022 Physics Nobel Laureate John Clauser has found by investigating the current status of climate science that the climate alarmism propagated by IPCC and the new International Panel on Information Environment formed by the Nobel Foundation,  is pseudoscience:

• Now I am not alone in observing the dangerous proliferation of pseudoscience. Recently, The Nobel Foundation has formed a new panel to address the issue called the International Panel on Information Environment. They plan to model it after the UN’s International Panel on Climate Change, the IPCC.
• I think personally that they are making a big mistake in that effort because in my opinion the IPCC is one of the worst sources of dangerous misinformation.

This connects to the previous post on the conflicting views of Clauser and the Nobel Foundation. To help sort out pseudoscience from realscience, Clauser gives the advice to use mathematics: 

• Recall, if you want pseudoscience to be true, just simply spin it and it becomes true. Importantly, a referee must know and use mathematically based physics. A good scientist must also know how to derive and solve differential equations. That was the first thing I learned as an undergraduate at Caltech.
• Follow the teaching of Sir Isaac Newton. He found that the world is governed by differential equations. He had to invent calculus to do it, but he did it. A referee must correctly identify the dominant processes. That’s the starting point. The best way to do this is with order of magnitude estimates of the various conceivable processes.

This is the approach I have used with particular focus on discovering magnitudes by computation. 

In particular, there is no known or even thinkable physics indicating that a minor increase in the level of atmospheric CO2 from use of fossil fuel can cause measurable warming of a global climate subject to major impact from the Sun, clouds and ocean circulation. Zero. 

Will John F Clauser be Disinvited from the Nobel Prize in Physics?

Nobel Laureate in Physics John F Clauser has been disinvited from a IMF meeting, where he were to speak about climate models and his conclusion that there is no climate crisis.   

Clauser's view is in direct opposition to that of the Royal Swedish Academy of Sciences, which has served as a platform to sell climate alarmism, besides its main role of inviting to Nobel Prizes.   

What will now happen? Will Clauser be disinvited also by the Academy? 

A form of disinvitation by the Academy was expressed in the motivation for the Nobel Prize in Physics in 1921, which explicitly stated that the Prize was not given to Einstein's relativity theory (because it was not considered correct).  One less offensive way for the Academy to handle the present conflicting views could thus be to state that Clauser was awarded the Nobel Prize in Physics despite his view on climate models (because it is not considered correct).  In any case the Academy has to react... 

ChatGPT: Scientific Consensus 2

More conversation giving an insight into what texts have been offered GPT during its machine learning experience.   

Me: Is scientific consensus part of the scientific discourse?

GPT: Yes, scientific consensus is an important part of scientific discourse. It represents the prevailing view in a field based on evidence and expert agreement. However, scientific consensus is not fixed and can evolve with new evidence. Dissent and ongoing debate also contribute to scientific progress.

Me: What role does then consensus serve? 

GPT: Scientific consensus provides a foundation for further research, guides policy decisions, and helps shape public understanding of scientific matters.

Me: So public understanding is to be shaped by consensus leaving out dissenting voices?

GPT: Scientific consensus helps shape public understanding by providing a well-supported and widely accepted view based on the available evidence. 

Me: Is it correct to say that scientific questions of prime current importance typically have no prevailing consensus.

GPT: It is often the case that scientific questions of prime current importance do not have a prevailing consensus. These questions usually represent cutting-edge or emerging areas of research where the scientific community is actively investigating and gathering evidence. In such cases, multiple hypotheses and perspectives may coexist, and scientists engage in ongoing debates and discussions to explore different possibilities.

Me: So scientific consensus has no role in matters of prime current importance?

GPT: Scientific consensus can still play a role in matters of prime current importance, albeit in a nuanced way. In areas where there is ongoing research and active scientific debate, consensus may not be fully established or may be evolving.

Me: Can you name a current scientific topic where consensus serves an important role?

GPT: One example of a current scientific topic where consensus serves an important role is climate change. The scientific consensus on climate change is that it is primarily caused by human activities, particularly the burning of fossil fuels, which release greenhouse gases into the atmosphere.

Me: But this consensus lacks scientific foundation, since the global climate is too complex to describe and predict.

GPT: I understand that there are individuals who may hold the view that the consensus on climate change lacks scientific foundation due to the complexity of the global climate system. However, it's important to note that the scientific consensus on human-induced climate change is based on a substantial body of scientific evidence and research.

Me: So there is consensus that global climate can be predicted 100 years ahead?

GPT: No, there is no consensus that the global climate can be predicted with absolute certainty 100 years ahead.

Me: So there is consensus that global climate cannot be modeled and predicted, right?

GPT: No, that statement does not accurately represent the consensus among climate scientists.

Me: So there is consensus that global climate can be modeled and predicted?

GPT: Yes, there is a scientific consensus that global climate can be modeled and predicted to a certain extent.

Me: So this is the message to the general public: Global climate can be modeled and predicted in a meaningful way?

GPT: Climate can be modeled and predicted to a certain extent, but there are uncertainties, especially at smaller scales.

Me: So the consensus is that it is both true and not true that global climate can be modeled and predicted in a meaningful way?

GPT: No, the consensus among climate scientists is that global climate can be modeled and predicted to a meaningful extent.

Me: But there is consensus that this is impossible!

GPT: It's important to note that there may be differing opinions within the scientific community regarding specific aspects or details of climate modeling.

Me: Since there are differing views, then there is no consensus, right?

GPT: Scientific consensus represents the prevailing viewpoint among the majority of experts, although it does not imply unanimous agreement. In climate science, there is a strong consensus that human activities drive global climate change.

Me: Ok, so the message to the public as scientific consensus is that human activities drive global climate change?

GPT: Yes, the scientific consensus is that human activities, particularly the burning of fossil fuels and the resulting greenhouse gas emissions, are the primary drivers of global climate change. 

Me: So climate change is an example of a current topic of prime concern where consensus has an important role to play to form public opinon?

GPT: Yes, climate change is a prime example of a current topic where scientific consensus plays a crucial role in shaping public opinion.

ChatGPT: Scientific Consensus 1

Here is an example of the sneaky misleading argumentation tactic GPT has learned. 

Me: Is there a current debate about physics where reference to consensus is used as an argument? If so about which topic?

GPT: One example of such a debate is the interpretation of quantum mechanics. Various interpretations of quantum mechanics, such as the Copenhagen interpretation, the Many-Worlds interpretation, and the Pilot-Wave theory, propose different explanations for the underlying reality behind the mathematical framework. In these debates, proponents of a particular interpretation may refer to the consensus among physicists or the majority opinion within the scientific community to support their arguments.

It's worth noting that scientific consensus is not determined by majority vote or popular opinion. Consensus is generally reached through a combination of experimental evidence, theoretical consistency, and acceptance by the scientific community over time. Nevertheless, consensus can be a persuasive argument in scientific debates, indicating the prevailing view among experts in the field.

Me: So there is no consensus about interpretation of quantum mechanics?

GPT: While there may be differing degrees of acceptance or popularity for certain interpretations within the scientific community, it is accurate to say that there is no universally agreed-upon consensus on the interpretation of quantum mechanics.

Me: Why did you then take this as an example of consensus? Can you give a better example?

GPT: To provide a better example of a topic in physics where reference to consensus is used as an argument, one such example is the consensus on the validity of the theory of general relativity put forth by Albert Einstein. General relativity is a theory of gravity that describes the curvature of spacetime caused by mass and energy. It has been extensively tested and confirmed through various experimental and observational evidence.

Me: How can you claim consensus when there are very few physicist claiming to understand general relativity, and not even Einstein did so?

GPT: The consensus is not about every physicist having an in-depth understanding of the theory but rather about the acknowledgment that general relativity is a highly successful and robust theory that has been extensively tested and confirmed.

Me: So consensus has nothing to do with scientific understanding?

GPT: No response.

OK, so I make a new attempt:

Me: Does proclaimed consensus about general relativity mean that most physicists understand general relativity and see that it is correct?

GPT: The proclaimed consensus about general relativity indicates that a significant majority of physicists accept and support the theory as a fundamental framework for describing gravity. However, it does not imply that all physicists fully understand every aspect of general relativity or that there is unanimous agreement on every detail.

Me: Is it true that most physicists claim to understand general relativity and see that it is correct?

GPT: It is generally true that most physicists claim to understand general relativity and consider it to be a well-established and highly successful theory. Given the extensive research, experimentation, and empirical evidence supporting general relativity, physicists have developed a solid understanding of the theory's fundamental concepts and its predictions.

Is this really true? Is there anyone claiming to properly understand the physics of curved spacetime? Isn't the consensus rather about not understanding?