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A remark on the Brown-Susskind conjecture

Building on the Brown-Susskind conjecture, this paper demonstrates that the dimension of the set of nn-qubit unitaries generated by a fixed number of $2$-qubit gates strictly increases when an additional pair of qubits is included, provided the pairs are chosen appropriately at each step.

Original authors: Jean-Luc Brylinski, Ranee Brylinski

Published 2026-09-22
📖 5 min read🧠 Deep dive

Original authors: Jean-Luc Brylinski, Ranee Brylinski

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 growing interest in understanding how complex a system can become when we build it up piece by piece. Imagine a machine made of tiny, interconnected switches, where each switch can be flipped in specific ways to change the state of the whole device. Scientists call these switches qubits, and the operations that flip them are known as gates. When we string these gates together in a sequence, we create a circuit that performs a calculation. A central question in this field is how the complexity of the final result grows as we add more steps to the sequence. For a long time, researchers believed that if you kept adding random steps, the complexity would rise steadily and predictably, eventually reaching a peak that is unimaginably large relative to the size of the system. This idea, known as the Brown-Susskind conjecture, suggests that complexity grows in a straight line until it hits a ceiling determined by the sheer number of possible configurations.

Two recent proofs confirmed that this linear growth does happen on average for random circuits. However, a new paper by Ranee Brylinski and Jean-Luc Brylinski asks a more precise question: does the complexity always increase, or are there moments where adding a step changes nothing? The authors investigate a specific scenario where we have a fixed set of allowed connections between pairs of these switches. They look at the collection of all possible outcomes that can be reached by multiplying a certain number of these allowed operations together. Their goal is to determine if there is always a way to choose the next operation so that the set of reachable outcomes gets strictly larger.

The researchers focused on a mathematical structure that describes these collections of outcomes. They treated the set of all possible operations as a geometric shape, where the size of the shape represents the complexity or "dimension" of the system. If the shape grows, it means we have gained new capabilities; if it stays the same size, we have merely retraced our steps. The paper proves a fundamental property about these shapes: as long as the network of allowed connections between the switches is linked together in a single piece, the total set of operations that can be generated eventually fills the entire space of possibilities. This means that if you keep adding steps, you will eventually be able to reach any possible state of the machine, provided the connections between the switches allow you to travel from any one switch to any other.

The core finding of the paper is that this growth is not just a possibility, but a certainty under the right conditions. The authors demonstrate that if the current set of outcomes has not yet reached its maximum possible size, there is always at least one choice for the next pair of switches to connect that will make the set of outcomes strictly larger. In other words, you can never get stuck in a loop where adding another step fails to expand your reach, as long as you are allowed to pick which pair of switches to use next. This result holds true even though the authors admit they cannot yet provide a simple rule for which specific pair to choose to guarantee this growth. They know such a choice exists, but finding the best one remains an open question.

This work refines our understanding of how quantum systems evolve. While previous studies showed that complexity grows linearly on average, this paper establishes that the growth is strictly monotonic for at least one path forward at every single step. The researchers used advanced tools from algebra and geometry to prove that the shape formed by these operations cannot stay the same size if it is not yet full. They showed that if the shape were to stop growing, it would imply that the entire system is trapped in a smaller, isolated part of the mathematical space, which contradicts the fact that the connections between the switches are linked. Therefore, the system must expand.

The paper also touches on a simpler version of this problem involving two specific, repeating patterns of operations. In this restricted case, the authors suggest that the complexity increases by exactly one unit with each new step, up to a certain limit. This aligns with the intuition that each new operation adds a distinct layer of capability. However, the authors note that this precise behavior relies on the operations being periodic, or repeating in a regular cycle. If the operations do not repeat, the mathematical tools used to prove the result become more difficult to apply, and the exact behavior remains less clear.

Ultimately, this research provides a rigorous guarantee that quantum circuits do not stagnate. It confirms that as long as the underlying network of connections is intact, there is always a way to push the system forward into new territory. The work does not solve the practical problem of how to find the best sequence of operations for a specific task, but it removes the fear that the system might hit a dead end where no further progress is possible. It assures us that the landscape of possibilities is always expanding, waiting for the right choice to reveal the next step.

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