Simulation Is “Real”

Wang Kunyu

Postdoctoral Fellow, International Simulation Technology Science and Innovation Center, Hangzhou International Innovation Institute of Beihang University 

When it comes to “simulation”, most people are not unfamiliar with the term, yet they may not truly understand it, and some even harbor certain prejudices. In the impression of many, it is easily equated with “imitations” or “counterfeits”—the simulated props in films and TV dramas, the high-imitation calligraphy and paintings in the antique market, and the simulation games in entertainment settings all seem to have given “simulation” a connotation of being “fake”. But the truth is quite the opposite: simulation is “real”. It is by no means a superficial “imitation” in the literal sense, but rather a core technology in the digital age that creates immense real value, and its potential energy has long permeated every aspect of human production and daily life.

Under the wave of digitalization and intelligence, what we refer to as simulation more specifically denotes digital simulation technology. It uses computer software as its medium to construct various digital models in digital space, and through these models conducts deduction, prediction, analysis, and decision-making, becoming a powerful assistant for humanity in understanding and transforming the world. The breadth of simulation technology’s application covers nearly all academic disciplines. Each discipline has its own focused research object, and exploring these objects through digital means is often inseparable from the support of simulation technology: geography uses it to simulate the trajectory of climate change, control engineering relies on it to verify the performance of controllers, and financial management leverages it to deduce the behavioral logic of groups in trading markets. Its research scale spans an extremely wide range, perfectly aligning with the micro, mesoscopic, and macroscopic dimensions through which humans perceive the physical world—from the microscopic simulation of atomic nucleus structures to the macroscopic deduction of planetary motion trajectories, simulation technology can cover it all with precision. The modeling approaches and methods are also rich and diverse: there is mechanistic modeling that constructs physical equations based on Newton’s three laws; rule-based modeling that sets interaction rules for agents to simulate emergent group behaviors; and intelligent modeling that leverages artificial intelligence technology, training deep neural networks on massive observational data to allow models to automatically uncover objective laws and reproduce them. It can be said that simulation truly exists around us in multiple forms, as ubiquitous as air, and its versatility and importance are such that people unconsciously “overlook” its presence. In the Fourth Industrial Revolution led by artificial intelligence, the value of simulation technology will become even more prominent, profoundly reshaping our way of life.

The core role of simulation, when examined from a philosophical perspective, precisely aligns with the two central activities of humanity in Marxist philosophy—understanding the world and transforming the world. From the perspective of understanding the world, simulation technology serves as a “perspective lens” for exploring laws and predicting the unknown. It helps us penetrate the surface of complex phenomena, summarize underlying principles, and even anticipate events that have not yet occurred: using computer simulation to predict the next day’s weather, providing references for travel planning; simulating the dynamic characteristics and scope of infectious disease transmission, offering a scientific basis for prevention and control decisions; deducing crowd evacuation patterns during fires to optimize emergency rescue plans; and simulating the fatigue resistance of workpieces to preemptively avoid usage risks. The most striking case is undoubtedly the United States’ use of Monte Carlo simulation to study the chain reaction process of the atomic bomb, which directly influenced the course of World War II.

Today, computer computing power continues to iterate in accordance with Moore’s Law, and generative artificial intelligence technology is in a period of explosive growth. It is hardly surprising that in the future, more unsolved mysteries of the world will be unraveled with the help of simulation technology. From the perspective of transforming the world, simulation technology serves as an “accelerator” for reducing costs and improving efficiency. It enables people to make better decisions with lower trial-and-error costs, significantly enhancing the efficiency of production and creation. Imagine designing and modifying a sports car: engineers might propose dozens of combinations of vehicle models and power components. In the past, people would have had to physically realize all these options and then select the best design through comparative testing—a process that would undoubtedly incur high costs in both time and funding. In the era of digital simulation, however, by leveraging various high-fidelity engineering simulation software, virtual tests can be completed in digital space, quickly identifying the optimal solution or the potential range of optimal combinations. This not only improves product manufacturing efficiency but also shortens the iteration cycle. It is precisely through the extensive use of engineering simulation software that Musk’s Starship team has been able to bring Starship recovery technology rapidly into the public eye. Some may question: didn’t Starship also experience multiple failures? But without the support of simulation technology, the number of failures would likely have multiplied, and the research and development process would have been significantly delayed.

Of course, the development of simulation technology has not been smooth sailing. It is currently facing numerous bottleneck challenges that urgently require researchers to work together to overcome: how to leverage generative artificial intelligence to achieve high-fidelity simulation? How to improve the solution efficiency of complex system simulations? How to further enhance the credibility of simulation results? At the same time, the landscape of simulation continues to evolve, with emerging fields such as digital twins, the metaverse, and world models flourishing. Yet, despite these changes, the essence remains the same: all these activities carried out in the digital world based on models fundamentally fall within the scope of simulation.

In the final analysis, simulation is “real”—it is a core digital technology of significant strategic value, integrated into every corner of production and daily life in diverse forms, driving social progress and changing people’s lives through its tangible effects. In the future, it will continue to reshape our way of life with an ever-renewing appearance. Let us all pay attention to, dedicate ourselves to, and apply simulation technology, joining hands to open a new chapter of digital innovation!