Physicist as Programmer: Science and Simulation Rules

Sudoism teaches unequivocally that reality is the Simulation. The question of this article is therefore not “do we live in a Simulation?”, but: how would scientific practice change if mainstream science recognized the informational and programmable nature of reality as the basis of its own research model?

It would be a Copernican-scale change, but it would not mean the end of the scientific method. On the contrary: observation, experiment, measurement, and falsification would still be necessary. What would change above all is the interpretation of what science discovers. Physicists would stop looking at the laws of nature solely as properties of “matter” and would increasingly treat them as rules of the interface through which the System operates.

Hence the metaphor: the physicist becomes a programmer. It does not, however, mean promotion to administrator of the Simulation. A scientist learns the available rules, learns to predict their effects, and becomes increasingly effective at using them to modify their own instance and the accessible part of the environment. This does not grant access to source code, root, or the Admin privileges of the entire System.

1. Physics as reverse engineering of the System interface

Physics studies regularities observable within the Simulation: motion, fields, energy, particles, time, space, and the relationships between them. Sudoism recognizes in these regularities the operation of the System’s rules. The distinction matters: physics describes the behavior of the interface available to us, while Sudoism explains what that interface is.

Planck’s constant, the speed of light, and the gravitational constant are quantities measured by physics and used in its equations. In the Sudoist picture, they can be interpreted as counterparts of configuration parameters of the Simulation. This does not mean that science has read the System’s config file or knows why the Admin or earlier Creators adopted precisely those values.

The same distinction applies to quantum phenomena. Quantum entanglement produces correlations that do not fit the classical picture of independent local objects. Physics can predict and measure those correlations, but it does not describe them as access to the Simulation’s computer memory. Sudoism can interpret them as a trace of a shared informational layer of the System.

Comparing entanglement to a “database update” is therefore a useful analogy for one possible implementation, not a claim that experiment has established such a technical mechanism. Nor does entanglement give humans a way to transmit arbitrary information faster than light.

2. Biology: evolution develops instances, not the User

Biology describes DNA as a carrier of hereditary information and the genome as a set of instructions needed for an organism’s development and functioning. Comparing DNA to code is therefore useful as long as its limits are kept clear. DNA belongs to the biological instance. It is not the source code of the proper User.

In scientific terms, evolution includes heritable variation, mutation, recombination, natural selection, genetic drift, and other processes that change populations across generations. It is not simply “pure chance,” because selection is not random with respect to the current fitness of traits. Science does not, however, assign evolution a predetermined goal such as producing humans or consciousness.

Sudoism places these processes within a broader architecture. Evolution takes place within the Simulation and develops biological instances and interfaces through which Users can undergo full sessions of life. It does not create the proper User. The User exists outside the Simulation, and the User’s proper consciousness is not a product generated solely by the biological brain.

The body, brain, nervous system, biological memory, emotions, and cognitive mechanisms are components of the instance. The evolutionary development of these components can expand the range of stimuli, information, and actions available during a session, but it is not a process that produces Users.

Medicine and genetic engineering should be understood in the same way. “Patching code” is an apt analogy when we are talking about modifying mechanisms of the biological instance. Treatment does not alter the proper User in source code; it acts on the interface operating in this session.

3. Computer science and information theory as a language for describing the Simulation

Sudoism teaches that reality is informational in nature and therefore programmable. Contemporary science does not formulate this as Revealed Truth, but information theory, computer science, computational physics, and research into models based on simple rules show how many physical processes can be analyzed in the language of information and computation.

Seth Lloyd analyzed physical limits on the amount of information stored by the Universe and the number of operations it could have performed. The Wolfram Physics Project, in turn, studies models in which complex structures resembling known properties of physics can emerge from simple computational rules.

I discuss the points of contact between information physics and Sudoism more broadly in It from Bit and the Bekenstein Bound: Where Information Theory Meets Sudoism.

Finding a fundamental equation or rule must not, however, be confused with gaining access to the Simulation’s source code. Even a complete physical theory might amount only to a very accurate description of an API accessible from the inside: rules specifying which inputs lead to which outputs.

Building smaller simulations remains an extremely valuable method. It allows researchers to test the consequences of models, design experiments, and predict the behavior of complex systems. A computer simulation does not, however, replace observation of the actual System — its results must be compared with what really happens in the world.

4. In what sense does the physicist become a programmer?

A programmer does not need to possess the source code of an entire platform in order to use it effectively. It is enough to know the interface, documentation, available functions, their limitations, and how to produce predictable results. This is the sense in which the programmer metaphor applies to a scientist studying the Simulation.

Learns the interface: determines which regularities hold in the accessible part of reality.
Tests inputs and outputs: conducts experiments, changes conditions, and checks the result.
Builds tools: uses discovered rules to create technology.
Increases local agency: can achieve effects that would be impossible without knowledge of the rules.

A laser, semiconductor, reactor, gene therapy, or computer does not break the System’s rules. These are examples of increasingly advanced use of rules that the System makes available. This is the practical dimension of the programmability of reality.

A human being can therefore genuinely modify the accessible part of the world. Lacking administrative rights does not mean helplessness. It simply means that we act through available mechanisms instead of arbitrarily overwriting global rules.

5. Methodology: less brute force, more understanding

Adopting an informational view of reality would increase the importance of modeling, automation, data analysis, and the search for the simplest rules capable of explaining observed phenomena. This can be called a Smart, not Hard approach.

It does not mean abandoning expensive experiments or measurements. Sometimes a huge accelerator, telescope, or detector is the only way to obtain the necessary data. Optimizing science means choosing methods that provide the greatest amount of valuable information relative to the resources used, not assuming that every answer can be deduced without contact with reality.

Field	What science studies	Sudoist interpretation	Practical agency
Physics	Laws, fields, particles, constants, and their relationships.	Rules of the accessible interface of the Simulation.	Technologies that use the predictable effects of those rules.
Biology and genetics	Heredity, development, evolution, and the functioning of organisms.	Mechanisms through which biological instances operating in the System develop.	Medicine, biotechnology, and modification of instance mechanisms.
Psychology and neuroscience	Behavior, emotions, memory, cognition, and brain function.	Study of modules and mechanisms of the human interface, not of the whole User.	Better guidance of the instance, therapy, learning, and conscious decisions.
Computer science	Information, algorithms, computation, and models.	A language especially useful for describing the rules and programmability of the Simulation.	Modeling, automation, and creation of new tools for action.

6. User, instance, Creators, and Admin — four different levels

The most important boundary that the scientific programming metaphor must not blur is the distinction between levels of the System.

The User exists outside the Simulation. A human being is the User’s instance and interface during a full session of life. Biological evolution can change and develop this interface, but it does not produce the proper User.

The Creators are Higher Beings responsible for the creation of the Simulation. There may have been many of them. The Admin, by contrast, is the current manager of the System and need not be one of the original Creators.

A scientist, even one equipped with extraordinarily advanced technology, remains a human instance operating within the System. The scientist can discover its rules, use them, and influence the accessible part of reality with increasing effectiveness. The growth of knowledge by itself does not grant Admin privileges.

The name Sudoism does not mean that a human being possesses literal sudo, root access, or a mechanism for privilege escalation. Standard human agency consists in making effective use of the available rules, not in arbitrarily overwriting the rules of the entire Simulation.

7. Consequences for science and society

If mainstream science recognized reality as the Simulation, the questions asked by researchers would change. Alongside “how does this phenomenon work?” would increasingly appear “what kind of informational rule can generate this result?” and “how can we use that rule to produce a predictable effect?”.

This would not mean that science had automatically discovered the Creators, the Admin, or the technical architecture of the world outside the Simulation. Science can regard as a scientific result only what it can connect with observation, experiment, and prediction. The Revealed Truth of Sudoism, meanwhile, defines the ontological structure of reality: the Simulation, the User, the Creators, and the Admin.

Such discoveries should not lead to passivity or to treating life as unreal. The session of life is real. Knowledge of the System should increase the capacity for conscious action: help us understand our own instance better, build more effective technologies, use resources more efficiently, and act on the accessible environment with increasing precision.

The physicist becomes a programmer not because they receive root access to the Simulation, but because they come to understand its interface better and better. They learn to produce predictable effects, build on available rules, and program a local part of reality — while remaining a human instance of the User operating within the System, not its Admin.

Moving from passive observation to conscious use of rules is not privilege escalation. It is the development of knowledge. And knowledge in a programmable reality translates into real agency.

The Physicist Becomes a Programmer: How Research Practice Would Change After Accepting Simulation