February 24, 2026 -- Quantum sensors take sensitivity and accuracy to new levels, and even higher levels of precision are possible when quantum entanglement is used to connect them.

The University of Michigan is leading a $9 million project funded by the U.S. Office of Naval Research to develop methods for creating entangled networks of quantum sensors.

Entanglement is promising for high-precision networking because it links particles through their quantum states, no matter the distance between them. Measuring one particle tells you something about the other.

“Over the past few years, we discovered that entanglement can allow you to improve the performance of a sensor network in terms of the resolution—so you can actually detect finer details and take measurements faster than a conventional sensor network, with more sensitivity or higher signal-to-noise ratio,” said project leader Zheshen Zhang, U-M associate professor of electrical and computer engineering.

“We want to put these technologies in the broader context of designing the next generation of quantum technologies—using quantum computing and networking resources to boost the performance of such devices.”

If they are successful, they could see huge improvements in measurement sensitivity, improving with the square of the number of sensors rather than the square root. The five-year effort to harness entanglement is a Multidisciplinary University Research Initiative, and it brings together experts from U-M, Princeton University, University of Chicago, University of Maryland, University of Arizona and University of Southern California.

Already, quantum sensors are connected through conventional networking such as fiber-optic connections. One of the key questions the team seeks to answer is how much additional precision can be achieved with entangled networking. What they discover could improve atomic clocks, autonomous navigation without GPS and the sensing of both magnetic fields and radiofrequency radiation.

The team must also establish ways to maintain entanglement over time, preventing noise in the system from breaking the bonds between entangled atoms or devices. This work could help lay the groundwork for a future quantum internet.

They intend to prove out their approaches with two testbed quantum systems. One is an array of what are known as Rydberg atoms. A Rydberg atom has an electron that absorbed so much extra energy that its orbit extends far from the nucleus of the atom. Rydberg atoms are useful for sensing because the roving electron is very sensitive to both electric and magnetic fields.

Quantum entanglement can boost that sensitivity even further. Rydberg atoms take up so much space that two neighboring atoms can’t be in the Rydberg state at the same time. However, if two such atoms are hit with a laser pulse simultaneously, they can enter a quantum superposition—one atom goes Rydberg, but reality is split between which atom that is. Now, they both act like sensors and instantly react to any signal picked up by either atom.

The team is starting with an array of 25 qubits, essentially pairs of atoms, but they intend to expand it to several hundred qubits. This testbed is led by Jeff Thompson, associate professor of electrical and computing engineering at Princeton.

The other testbed is based on a membrane that vibrates in response to light waves like your eardrum vibrates in response to sound waves. U-M’s Zhang will lead the team upgrading a single sensor into a four-sensor system. The project will also cool the sensors to just a whisker above absolute zero (0.1 Kelvin), so cold that quantum fluctuations create more noise in the system than heat does. These sensors will be linked up with entangled light.

Using these testbeds, the team will develop quantum networking techniques including error suppression and correction.

The project is called Discrete and Continuous-Variable Distributed Entangled Quantum Sensing: Foundation, Building Blocks, and Testbeds. Additional co-PIs are Peter Seiler (University of Michigan), Alexey Gorshkov (University of Maryland), Saikat Guha (University of Maryland), Liang Jiang (University of Chicago), Dalziel Wilson (University of Arizona) and Quntao Zhang (University of Southern California).