DOE Funds Brain-Inspired Self-Tuning Quantum Sensor Research

What if there was a light detector so sensitive it could register a single photon? Now, what if it could autonomously determine its own optimal sensitivity? No engineer manually adjusting calibration. This is the premise of a new Department of Energy (DOE) project, and the key proponent is a brain scientist.

Keith Hengen, an associate professor of biology at Washington University in St. Louis, is a co-principal investigator on a $750,000 project with Argonne National Laboratory physicist Whitney Armstrong. Hengen’s contribution stems from neuroscience: a concept called criticality, which may enable superconducting sensors to self-regulate to their ideal operating point.

It’s important to clarify the project’s current status. This is a funded initiative, awarded in late July through the DOE’s Genesis Mission, and as of now, no hardware has been produced. The grant supports an attempt, not a guaranteed outcome.

Criticality: The edge between order and chaos

According to a report by Washington University, criticality describes a system operating at the boundary between rigid order and total chaos. If a system is too ordered, it can’t adapt to new information. If it’s too chaotic, it lacks the stability to process information effectively. At the critical point, small inputs can generate significant, useful responses, while the system remains stable enough for processing.

Hengen’s lab proposes that the brain intentionally operates near this critical edge. He explained to Washington University’s Ampersand: 

“We’ve shown that the brain constantly adjusts itself to stay close to criticality, and that the closer a brain is to criticality, the faster it can learn. We think that quantum sensors will also work best if they’re tuned very close to a critical point. Instead of manually adjusting each chip within the sensor, the chips could self-tune, just like brain circuits do.”

This concept of self-tuning chips is the project’s core proposition. Your brain continuously performs this self-tuning without you noticing, which is precisely the mark of a well-functioning brain.

The hardware: Single-photon detection

The target device is a superconducting nanowire single-photon detector (SNSPD). These are genuine quantum sensing devices, known for their exquisite sensitivity. They consist of an extremely thin superconducting wire, cooled to a point where electrical resistance virtually disappears. When a single photon strikes the wire, it momentarily disrupts its superconducting state, generating a measurable electrical signal.

Detecting individual photons is crucial because photons carry quantum information in optical networks, facilitate measurements, and act as carriers in some quantum computing schemes.

Armstrong is developing detectors to sense photons emitted from helium nuclei. The engineering challenge isn’t merely detecting a single photon; it’s maintaining the accuracy and efficiency of an entire network of detectors as the system expands, without requiring constant human oversight for each component. This calibration problem intensifies with scale, a recurring issue in quantum sensing hardware.

The initial phase: Entirely theoretical

Now for the candid assessment, where excitement must be tempered with realism. The connection between brain networks and superconducting electronics is currently a hypothesis. It has not yet been demonstrated that criticality, a concept studied in neural circuits, directly applies to a chip cooled to near absolute zero. The underlying mathematics might transfer, or it might not. Hengen acknowledged this: 

“In the early phase of the project, most of my lab’s work is going to be purely theoretical and computational. We want to show that these quantum sensors will be maximally effective when they’re tuned to criticality. That work should take about nine months. If it goes well, we’ll consult on the actual construction of the chips, which will be made at MIT.”

It’s crucial to understand this sequence: nine months of simulation and mathematical modeling first. Only if these models prove viable will physical hardware be considered. Even then, the chips will be built at MIT, then tested, and subsequently analyzed. This is a theory-first, hardware-later approach, with the entire first phase dedicated to determining if the analogy is robust enough to justify investment in silicon.

The project’s foundation is a preprint authored by Hengen, postdoc Leandro Fosque, engineering professor ShiNung Ching, and University of Arkansas physicist Woodrow Shew, which posits criticality as a general information-processing principle. A preprint indicates it has not yet undergone peer review. The framework is a proposal, not an established law of computing, regardless of how grand the phrase “fundamental law of computing” may sound.

Practical implications

Stripping away the neuroscience-inspired romance, the practical hope is this: complex sensor systems typically require extensive external control to maintain optimal operation. This control can be costly and energy-intensive. If detectors could autonomously maintain operation near criticality, it could significantly reduce manual calibration and lower energy consumption. This project is part of the DOE’s Genesis Mission.

The collaboration merits recognition. Adopting a design principle from biology, rather than solely relying on conventional electrical engineering, is a genuinely innovative approach. Armstrong deserves credit for recognizing the potential of a biology preprint for detector design. Such cross-field pollination is rare and often yields valuable insights.

However, no hardware demonstrations exist yet. There’s no measured improvement in detector accuracy, no efficiency gains, no self-tuning chip in a cryostat. What exists is a promising idea, a modest grant, and a nine-month timeline.

The funding and the plan are genuine. The self-tuning sensor remains an aspiration. Revisit this discussion in a year.