From brain scans to spacecraft navigation, measuring physical quantities like time, energy, or electric and magnetic fields with extreme precision is central to modern science and technology. In hospitals, for instance, magnetic field detection powers MRI machines. In mining or space exploration, accurate sensing of accelerations helps us navigate and understand unfamiliar environments.
Victor Montenegro
Khalifa University’s Victor Montenegro holds a doctorate in physics. Outside of his academic work, he is an amateur guitar player who enjoys photography and reading widely across genres.
Now, a new wave of ultra-sensitive tools – quantum sensors – is pushing these capabilities even further. Thanks to the bizarre but powerful properties of quantum physics, these sensors can detect tiny changes in their environment with unprecedented accuracy. As a result, they’ve become a hot topic in scientific research.
The simplest starting point for quantum sensors is measuring just one unknown quantity — like a magnetic field or time — while assuming everything else is already known and under control. This clean setup is not only elegant but also lets quantum devices push precision to its ultimate limit. But the real world is far from this ideal scenario. In many practical situations, several things are unknown at once. This more complex challenge, called multiparameter quantum sensing, makes everything trickier – from designing the quantum sensor itself to figuring out how well it can perform.
To tackle the challenges of sensing multiple unknowns at once, scientists use a powerful mathematical tool called the Fisher information matrix. Think of it as a way to measure how much useful information a quantum sensor picks up. Loosely speaking, the larger the Fisher information, the higher the accuracy for estimating the parameter in question. But there’s a catch: sometimes, this matrix can become singular, meaning it can’t be used to estimate the parameters at all. It makes the sensing impossible. This breakdown can happen for a few reasons, for instance, maybe the measurements just aren’t chosen appropriately, or maybe the parameters we thought were independent are actually tangled together in the quantum system.
This new approach lets you ask, in principle, different questions in sequence, learning more from how the system responds over time.
My team at the College of Computing and Mathematical Sciences at Khalifa University, along with collaborators from the University of Electronic Science and Technology in China, has tackled this long-standing problem in quantum sensing: what to do when the information matrix breaks down. Our solution? A surprisingly simple but powerful idea – measure the system multiple times in a row – rather than just once.
This method, known as a sequential measurement strategy, only requires keeping track of how the outcomes change step by step. It works even if you’re looking only at a small part of the system. Unlike conventional sensing – which is like asking the same question again and again – this new approach lets you ask, in principle, different questions in sequence, learning more from how the system responds over time.
Because each measurement builds on the last, hidden connections between outcomes start to emerge. These correlations help untangle the unknowns and fix the problem of singular information matrices – all without adding much extra complexity. It’s a novel and unconventional strategy that opens the door to smarter, more efficient quantum sensing.
To show just how practical this strategy is, the team tested it on two very different quantum systems. The results were clear: This sequential sensing approach works across a wide range of setups, keeps the experimental demands low, and still delivers highly accurate estimates.
Read the paper here.
