BSMScanner: a lightweight framework for beyond-the-Standard-Model global fits
The paper introduces BSMScanner, a lightweight framework that enables users to define beyond-the-Standard-Model global fits via declarative YAML specifications which are compiled into efficient C++ kernels and executed by various scanning engines to analyze benchmark models.
Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer
In the vast landscape of modern physics, there is a persistent gap between the rules we know work and the universe we actually observe. Scientists have a highly successful rulebook called the Standard Model, which explains how particles like electrons and quarks interact. Yet, this book is incomplete. It cannot explain why gravity is so weak compared to other forces, why the universe is made of matter rather than antimatter, or what dark matter is. To find the missing pieces, physicists propose "Beyond the Standard Model" theories. These are new rulebooks that add extra particles or forces to the existing ones. However, a new theory is just a guess until it is tested against reality. To do this, researchers must take a theory, plug in every possible combination of its new numbers, and see which combinations survive the harsh constraints of real-world experiments. This process is like trying to find a single specific needle in a haystack that is constantly changing shape, and doing it requires checking billions of possibilities.
For decades, the tools used to perform this search have been clumsy and difficult to reuse. Every time a physicist wanted to test a new theory, they had to write a custom computer program from scratch. They would manually code how to calculate the mass of a new particle, how to mix different types of particles together, and how to compare the results to experimental data. This meant that if a scientist wanted to change the search strategy or test a slightly different version of the theory, they often had to rewrite large parts of their code. It was slow, prone to errors, and made it very hard for other scientists to check the work or repeat the experiment. The machinery of discovery was being rebuilt for every single new question, rather than being reused.
Mohamed Belfkir and his team at the University of Doha for Science and Technology have introduced a new approach that changes how this search is conducted. They created a framework called BSMScanner, which treats a physics model not as a complex computer program, but as a simple, readable document. Instead of writing code to define a theory, a researcher writes a text file that lists the theory's ingredients: the names of the new particles, their possible mass ranges, and the rules that govern how they interact. This file acts as a blueprint. The software then reads this blueprint, checks it for consistency, and automatically translates it into a highly efficient, pre-compiled engine that can run millions of calculations per second.
The power of this system lies in its separation of the "what" from the "how." The researcher defines what they want to study in a clear, structured format, while the software handles the heavy lifting of the mathematics. This includes complex tasks like calculating how particles mix together or determining if a proposed set of numbers leads to a physically impossible universe. Because the software compiles this information once into a fast, unchangeable core, it can test points in the search space incredibly quickly. In tests, the system evaluated complex models with twenty-six different variables in less than a minute on a single computer processor. This speed allows researchers to explore vast areas of possibilities that were previously too slow to check.
The framework also solves the problem of reproducibility. In the old way of working, the details of a search were hidden inside lines of code that only the original author could easily read. With BSMScanner, the entire setup is visible in the text file. If another scientist wants to verify the results, they can simply read the file to see exactly which parameters were tested, what rules were applied, and what search method was used. The system produces a clear record of every step taken, ensuring that the results can be audited and trusted.
To prove the system works, the team applied it to six different theoretical models, ranging from simple additions of new particles to complex scenarios involving dark matter and new forces. They tested models that required finding a specific best fit, as well as models where the goal was simply to find any region that was allowed by the laws of physics. In one case, they studied a model where the valid solutions were so rare that a standard search would have failed to find them; the new system successfully located the tiny, hidden regions where the theory could work. In another test, they examined a model with many variables and found that the system could navigate the complex landscape to find the best possible match with experimental data, confirming that the software could handle the intricate math required for modern particle physics.
The researchers also demonstrated how easily the system can adapt to new challenges. Because the model is defined in a document, changing the search strategy is as simple as editing a few lines of text. If a researcher wants to switch from a random search to a more sophisticated method that looks for clusters of good solutions, they do not need to rewrite the physics. They simply change the instruction in the file, and the software runs the new strategy on the same compiled model. This flexibility means that scientists can spend their time thinking about the physics rather than debugging their code.
The results show that this approach is not just a theoretical improvement but a practical one. The system successfully identified the best possible matches for the models tested and mapped out the regions where the theories remain valid. It confirmed that the new framework can handle the complexity of modern particle physics while making the process faster, more reliable, and easier to share. By turning the search for new physics into a declarative process, BSMScanner allows scientists to focus on the questions that matter, leaving the tedious work of calculation to a tool that is built to be reused, understood, and trusted.
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