By harnessing the unique properties of quantum mechanics, scientists and engineers worldwide seek to enable systems with extraordinary capabilities. Many of them are working on the highly anticipated development of quantum computers capable of completing complex calculations at unprecedented speeds. These computers could meet the growing computational demands of both scientific research and data-intensive industries like finance, cybersecurity, and medicine.  

Necessary for quantum system development is an environment in which the fragile nature of quantum bits (qubits) is stabilized and the thermal noise (fluctuations in current/voltage) inherent in superconducting electronics is dampened. That environment requires cryogenic temperatures, those ranging from 5 to 10 millikelvins, colder than the extreme temperatures encountered in space. Dilution refrigerators create this needed cryogenic condition.

Dilution refrigerators used for quantum R&D need a wiring system that can operate in cryogenic temperatures, maintain a power-efficient direct current, and support high-speed data transmission. Researchers at MIT Lincoln Laboratory prototyped flexible, ribbon-like, low-frequency (LF) cables that not only meet these demands, but also are compatible with commercial circuit-board manufacturing processes. Maybell Quantum, a Colorado-based company supplying hardware for developing quantum systems, licensed the design for these cables and is adapting them for use in their dilution refrigerators.

"We’re planning to integrate Maybell LF CryoTrace, the ribbon wiring system transferred from MIT Lincoln Laboratory, across all thermal stages of our dilution refrigerators. Initially, the cables will be used for LF services, such as thermometry, heaters, and sensors, with feasibility studies planned for additional functions," says Lasse Nielsen, strategy and operations lead at Maybell Quantum. "After qualification testing, LF CryoTrace is planned for the next iteration of our internal wiring across the Maybell product family."

Motivation for invention

To support government initiatives in quantum computing, the Lincoln Laboratory research team investigated alternatives to conventional coaxial cables for use in hardware like dilution refrigerators. Coaxial cables can generate heavy heat loads for cryogenic hardware to address. And, as the number of qubits in quantum computers will increase, so will the number of coaxial cables in the infrastructure, making it difficult to fit stiff, bulky cable arrays into hardware supporting superconducting qubits.    

The team chose a stripline cable configuration with conductive layers positioned between flexible polymer layers that shield against electromagnetic interference (also known as crosstalk). Striplines offer consistency across different frequencies and minimal signal loss. The new cables were designed to accommodate large numbers of simultaneous signal transmissions; support direct-current operation without warming the cryogenic environment; and, importantly, provide easier integration into hardware than achievable with brittle coaxial cables.

"The main innovation is that the laboratory's cables can be fabricated by a traditional printed-circuit-board manufacturer. They're cheaper to fabricate and easier to install than traditional coaxial cables," says John Cummings, a principal investigator in the flexible cables project of the Lincoln Laboratory Quantum-Enabled Computation Group.

Citing ease of installation and durability as two factors making these cables attractive, Maybell Quantum says the ribbon format is mechanically robust, reducing handling-related breakages common with thin coaxials and improving repeatability in production. The supple flex cables allow assembly tasks that took days to complete to be done in a few hours.

"Over time, we think ribbonized, quantum-specific internal wiring can reshape manufacturing norms: faster and more consistent builds, easier field service, and more modular upgrades," Nielsen says.

Future outlook

Maybell Quantum is looking toward supporting quantum computing's transition from a laboratory-based capability to an industrial, commercially viable one. The huge gap between the current highly specialized quantum-laboratory environment and the robust infrastructure required for future industrial quantum computing lies in the hardware promoting the development of functional chips.

Maybell's mission is to develop reliable tools that commercial developers of quantum computers can use with ease and without the high costs and expert training associated with the equipment in today's quantum labs. The flex cables and Maybell's continued R&D into their capabilities and integration into various tools will foster a future infrastructure that could enable industry to scale manufacture of quantum computers to a level at which these powerful machines could cost-effectively find use in myriad enterprises.

"If you want to scale to hundreds of chips, you need interconnects that can handle more signals more reliably. That’s why the Lincoln Laboratory cables are so exciting for us — they enable true scalability," says Kyle Thompson, founder and chief technology officer of Maybell Quantum. "We believe this technology will materially improve our systems and strengthen the broader U.S. quantum ecosystem by moving federally funded innovation into American manufacturing."

From the icy expanse of the South Pole, John Della Costa, a researcher on the Background Imaging of Cosmic Extragalactic Polarization (BICEP) project, watches STS.042/8.225 (Einstein, Oppenheimer, Feynman: Physics in the 20th Century), a free online class from MIT Open Learning’s OpenCourseWare, as part of a weekly “Fysics Fridays” series he started with his team.

MIT Professor David Kaiser, who teaches the course, often receives thoughtful notes from remote learners, but says an email from Della Costa stood out.

“Hearing that John and his team are spending a part of their time with this course was just the best message to receive,” says Kaiser.

The BICEP collaboration uses a series of radio telescopes at the South Pole to study the cosmic microwave background — the oldest light, emitted about 380,000 years after the start of the universe. The team is looking for signs of primordial gravitational waves, which would help to support MIT Professor Alan Guth’s theory of cosmic inflation that explains the rapid early expansion of the universe.

“Inflation is really important in making sense of our observations of our universe,” says Della Costa. “We have yet to discover the evidence for inflation that definitively proves that it did happen, and BICEP’s main role here at the South Pole is to discover gravitational waves from the very early universe.”

Kaiser co-directs a research group on early-universe cosmology with Guth. He says he has colleagues who have worked as Antarctica winter-overs, and can appreciate the immense challenge of this work.

“It’s very exciting to see this important research flourishing,” says Kaiser. “It takes enormous effort and dedication.” 

Bringing Open Learning to the South Pole

Della Costa first discovered MIT OpenCourseWare, part of MIT Open Learning, as a graduate student at San Diego State University. At the time, the Covid-19 pandemic had altered his schedule and created more downtime to pursue additional independent learning. He was taking a nuclear physics course as part of his graduate program in astrophysics, and wanted to learn much more about the topic. A little bit of online research led to his discovery of class 22.01 (Introduction to Nuclear Engineering and Ionizing Radiation), taught by Professor Michael Short.

“I found the course so interesting, and I’ve been exploring OpenCourseWare ever since then,” says Della Costa.

Preparing to spend an entire year at the South Pole (from November 2025 to December 2026), he realized he would need a productive way to occupy his downtime and stay entertained while isolated from much of the world.

“The station is completely isolated. After a certain point, no planes can fly in because it’s too cold,” says Della Costa. “The station closed on February 14, and it will reopen at the end of October or early November, depending on the weather.”

Because internet access is so limited at the South Pole, he downloaded several courses ahead of time, including: STS.042/8.225, 8.02 (Physics II: Electricity and Magnetism), 8.03 (Physics III: Vibrations and Waves), and Guth’s course, 8.286 (The Early Universe).

Like Della Costa’s discovery of OpenCourseWare, STS.042/8.225 was rooted in the disruptive days of the Covid-19 pandemic. Kaiser had taught the course in its traditional, in-person format many times, until fall 2020, when the courses needed to be taught entirely remotely. He made slides and taught the course via Zoom — for synchronous and asynchronous learning — to approximately 100 students located throughout the world. The materials were initially posted on the course site. The online version was later refined and expanded, launching on OpenCourseWare in August 2022. Unlike many physics offerings, this course includes background readings by physicists, as well as historians, philosophers, and sociologists.

“In this course, we get to talk about some really amazing ideas from modern physics,” says Kaiser. “We start in the middle of the 19th century, still in an era of what we would now call classical physics, and we rapidly go through things like relativity, quantum theory, nuclear physics, and particle physics. We end up with some of my favorite material about cosmology and the Big Bang — the kinds of things that John and his team are actively working on right now from their perch at the South Pole.”

Building community and learning together

Beyond finding ways to stay occupied during downtime from his research, Della Costa realized the importance of engaging the 45-person community at the South Pole. He describes it as a tight-knit group that needs to work together and look out for one another, especially given the extreme isolation, cold, and darkness, which can take a serious toll on mental health during the winter months.

“It’s very important to have community activities here,” says Della Costa, who thought of the idea to launch the “Fysics Fridays” series a couple of months ago. 

The group gathers to watch lectures and documentaries about physics every Friday. The series kicked off with a documentary about atomic bombs, drawing strong interest from the very beginning. 

Della Costa realized that STS.042/8.225 would be an ideal offering for Fysics Fridays.

“I thought this would be a perfect lecture series for us to watch, because it’s fairly introductory,” says Della Costa. “Not everyone here is a physicist, actually. It’s widely accessible, but still meaty, and worth people’s time to watch.”

Team members have been very interested in watching the course, and they’ve also started doing experiments before watching the lectures. Della Costa says that they’ve done the double-slit experiment and plan to also make a cloud chamber to see cosmic rays going through it.

Now that Della Costa and Kaiser are in contact, Kaiser has made plans to provide a special Zoom colloquium for the community at the South Pole.

“This use of the course is especially inspiring,” says Kaiser. “It really speaks to the excellence and far reach of OpenCourseWare and Open Learning.”

An auto factory worker can remember the storage bin where she left a partly assembled component the night before, and quickly return to that spot to pick it up. But robots that may work side-by-side with her would struggle to develop and access this same type of “spatiotemporal” memory.

Now, MIT researchers have developed a long-term memory framework that allows robots to rapidly form and recall a detailed mental model of complicated, large-scale environments.

In the future, this advance could allow the factory worker to send a robotic assistant to fetch the item, simply by asking it to “go and grab the component we started assembling last night.”

This new method combines advanced map representations with rich descriptions of the environment that the robot gathers as it travels over a long period of time. The robot can quickly access this memory to answer complex queries about its environment in plain language.

This memory framework, which answers questions more accurately than state-of-the-art methods, runs fast enough for a mobile robot to use in real-time.

In addition to its potential uses in robotics, this method could have applications in augmented reality systems that aid maintenance workers in anomaly detection or assist commuters in wayfinding.

“If we want robots to work side-by-side with humans and interact better with humans, they must speak the same language. The robot must be able to reason about time and space the same way humans do. That is essentially what our method is doing. It is turning a traditional map into a language-based map that is easier for the robot to think about and access using language,” says Luca Carlone, an associate professor in MIT’s Department of Aeronautics and Astronautics (AeroAstro), principal investigator in the Laboratory for Information and Decision Systems (LIDS), and director of the MIT SPARK Laboratory.

He is joined on the paper by lead author Nicolas Gorlo, an MIT graduate student; and Lukas Schmid, a former research scientist at MIT and now professor at the University of Technology Nuremberg in Germany. The research was recently presented at the Conference on Computer Vision and Pattern Recognition (CVPR).

Spatiotemporal memory

Memory allows an artificial intelligence system, like a chatbot, to answer complex questions and reason about previous interactions with its user.

“We want to design a new type of memory, a spatiotemporal memory, that enables an AI-powered robot to remember real interactions and sensor observations. Like ChatGPT, but grounded in the real world and capable of answering any question about the environment, like ‘Where did I leave my wallet?’” Carlone says.

To develop such a memory framework, the MIT researchers bridged two lines of work: computer vision and robotic mapping.

Multimodal computer vision models can understand and richly describe the objects in a scene, but they often only process a single annotation at a time. On the other hand, robotic mapping frameworks create 3D maps of an environment, like an entire apartment or university campus, but usually lack detailed descriptions of objects or are computationally expensive.

The method the MIT researchers created, called Describe Anything, Anywhere, Anytime, at Any Moment (DAAAM), takes the best of both approaches.

Using DAAAM, as a robot traverses its environment, it attaches rich descriptions to objects it sees. For instance, the robot may note that a particular building on the MIT campus is called the Stata Center and is designed with a certain type of architecture, or that a bike rack holds five bicycles and the red one has a flat tire. 

It stores this detailed information in a 3D map-based representation that is arranged spatially, so objects will be grouped into separate regions. In this way, the robot can remember that the red bicycle with the flat tire is in the bike rack outside the Stata Center.

But existing techniques that capture such rich descriptions typically take a few seconds to annotate a few objects. This is too slow for real-time performance, since a robot might see hundreds of objects during a few minutes of exploration.

“The faster the robot can form this spatial memory, the more efficient it will be performing actions in the environment,” Carlone adds.

Streamlining the process

To speed things up, DAAAM aggregates nearby objects as it travels and uses an optimization method to select key frames to annotate. These are images with the clearest view of multiple objects, allowing the system to thoroughly describe several items in parallel, speeding up computation tenfold.

As the robot explores the space, it attaches each batch of annotations to multiple objects in a particular location on the 3D map.

“We annotate every object only once, so our framework can run in very large-scale environments in real time. And by clustering objects into regions, it can answer a wide range of queries about objects and locations in the environment,” Gorlo explains.

Once the system builds this spatial memory, it must retrieve information from an enormous database of objects and descriptions in an efficient manner. 

To enable this, the researchers used an LLM that calls on various tools, which can quickly retrieve specific information in a way that reduces hallucinations. This allows DAAAM to answer a user query accurately in only a few seconds. 

For instance, if one asks a robot about a certain sculpture it saw near an MIT campus building, DAAAM can use a semantic search tool to retrieve information based on the word “sculpture” or a different tool to retrieve information based on the location of the building.

When tested and compared with other methods, DAAAM was between 21 percent and 53 percent more accurate, depending on the question type. 

In the future, the researchers want to expand DAAAM so the system can capture significant events that happened in the environment. They are also working to incorporate confidence levels into the system’s responses.

“Ultimately, we want to have robots that can help with any sort of tasks. With this framework, we are trying to create the foundations to enable a generalist agent that can do anything you ask,” Gorlo says.

This research was funded, in part, by the U.S. Army Research Laboratory and the Office of Naval Research. Carlone is currently on sabbatical as an Amazon Scholar; this article describes work performed at MIT and is not associated with Amazon.

In May, the Initiative for New Manufacturing (INM) marked its first anniversary with MIT Manufacturing Week, four days of events that attracted more than 800 registrants including students, faculty, industry leaders, investors, entrepreneurs, and government officials to explore topics ranging from how companies are using AI on factory floors to the role of startups in introducing innovation to new workforce solutions to address the worker shortage.

“INM launched a year ago with the premise that strengthening the industrial base needed a coordinated response, and MIT has a responsibility to lead it,” says Paula T. Hammond, dean of MIT’s School of Engineering and co-chair of INM’s Steering Committee. “The response and participation level has been huge. MIT Manufacturing Week proved that the appetite for change — from students to chief executives — is real and urgent.”

The week opened with a cybersecurity workshop co-led by INM and Google Cloud for the initiative’s industry members. It continued with the MIT MIMO (Machine Intelligence for Manufacturing Operations) symposium focused on deploying artificial intelligence on factory floors, alongside discussions on workforce development, emerging technologies, startups, and industrial transformation. The week closed with a regional research showcase and competition that drew more than 140 graduate students and postdocs from across New England.

Over the past year, INM has also continued its distinguished speaker series featuring manufacturing leaders including Keith Flynn, senior vice president of manufacturing at Anduril; Roland Busch, president and CEO of Siemens; and Venky Alagirisamy, COO of Nike.

Inspiring a new generation of manufacturing startups

A central goal of INM is to help more students see manufacturing as a frontier for scientific discovery, technological innovation, entrepreneurship, and societal impact.

To support that effort, INM is launching and leading programs to help move early-stage ideas and new technologies from the lab to real-world development, and to catalyze new manufacturing companies. 

This year, INM partnered with NSF I-Corps New England, which helps researchers turn their startup ideas into companies, to host its first manufacturing research showcase. More than 140 teams from 17 universities across New England applied to participate. Forty finalist teams received mentorship on their ideas and advanced to the final competition, where eight teams shared $50,000 in prize funding.

The top prize in the category “most transformative innovation” went to MIT PhD student Jake Read for “The End of G Code,” a project focused on modular machine control architectures designed to accelerate the development of new manufacturing equipment and processes. Vatsal Patel from MIT and Joshua Grace from Yale University won the top prize in the research excellence category, for “VisFT,” scalable six-axis force-torque sensors.

Project themes presented by participating teams included AI tools for manufacturing, semiconductor manufacturing and process control, robotics and autonomous assembly, digital twins and simulation, new materials, additive manufacturing, next-generation shipbuilding, and biomanufacturing. 

“Entrepreneurship is a transformative pathway to take research to market, and to drive faster innovation and scale-up,” says John Hart, INM faculty co-director and head of MIT’s Department of Mechanical Engineering. “At INM’s inaugural research showcase, we had tremendous interest from universities across New England, along with enthusiastic participation from industry, investors, and experienced founders across the ecosystem. We are excited to build on this success and work toward a nationwide program and platform for entrepreneurship and translation in manufacturing.” 

The Cheng Wu Foundation supported the showcase. 

Growing industry membership

During MIT Manufacturing Week, First Solar became INM’s eighth industry member, joining Amgen, Autodesk, GE Vernova, Flex, PTC, Sanofi and Siemens. 

The growth of INM’s consortium reflects a broader recognition that the challenges facing modern manufacturing — from supply chain resilience to workforce development and industrial competitiveness — are too complex for any single sector or company to address alone. 

This reflects renewed interest in manufacturing at a moment when advances in artificial intelligence, robotics, energy systems, and advanced materials are transforming industrial production. INM provides a platform to convene and provide solutions.

INM’s industry consortium model brings industry, researchers, and educators together around shared manufacturing challenges, with a focus on emerging technologies, workforce transformation, and commercialization pathways. Members participate in workshops and working groups on topics including cybersecurity and digital twins, implementing automated systems, AI agents in regulatory environments, and AI and continuous innovation. INM helps them connect with students, meet with startups, and learn from one another.

“Our members see MIT as a partner that can help them both address today’s challenges and think far into the future,” says Rick Locke, dean of the MIT Sloan School of Management and co-chair of INM’s steering committee. “This kind of multi-industry engagement is unusual and powerful.”

A year of rapid progress

When MIT launched INM a year ago, the goal was to create stronger connections between research, industry, workforce development, and entrepreneurship — helping accelerate how new manufacturing technologies move from the laboratory into real-world development.

Since then, the initiative has expanded quickly across research, industry, workforce training, and student engagement. INM issued a call for proposals focused on artificial intelligence and automation, receiving an incredible response from faculty and researchers, and funding eight seed research projects. In June, the initiative plans to publish eight white papers as part of a broader study examining the future of manufacturing. 

During MIT’s Independent Activities Period (IAP) in January 2026, INM collaborated with NSF I-Corps to guide 13 early-stage teams through customer discovery as part of the I-Corps Spark program.

Workforce development has also been a major focus. This fall, MIT launched the Technologist Advanced Manufacturing Program (TechAMP), led by Principal Research Scientist John Liu, to create a new generation of shop floor leaders and drivers of productivity — becoming“‘technologists” — at six sites across New England, including three community colleges. 

“INM has the potential to transform the national manufacturing workforce,” says Liu. “It will require deep engagement between how people learn and lead, and how firms adopt new technologies and transform. We’re just getting started.” 

INM is now exploring a national rollout of TechAMP, along with expansion into areas including biomanufacturing and semiconductor manufacturing.

On campus, INM supported student engagements including an AI and automation lunch series that Professor Faez Ahmed and colleagues organized, and visited factories through its Factory Observatory program that Ben Armstrong and the MIT Industrial Performance Center led. This spring, students also founded MIT’s first manufacturing club, holding its launch event during MIT Manufacturing Week. “We’re thrilled students are taking the lead,” says Sloan associate professor and INM faculty co-director Karen Zheng. “It was really exciting to see a full room of 80-plus students across campus coming together for the kickoff event during the busiest final period of a semester. This speaks to the students’ enthusiasm.” 

An eye toward the long term

While maintaining a deep focus on strengthening domestic manufacturing, INM aims to have a global reach. For example, the initiative is collaborating with NAMTECH, a new education institute in Ahmedabad, India, where students are now taking an adaptation of MIT’s well-known “yo-yo course,” or 2.008 (Design and Manufacturing II), focused on the fundamentals of manufacturing processes.

Next year, INM plans to bring more manufacturing leaders to campus, offer additional programming for emerging entrepreneurs, graduate the first cohort of TechAMP students, bring TechAMP to new states, grow the consortium to include new industries, and deepen research into manufacturing productivity. 

“INM aims to be a catalyst for transforming manufacturing across the nation to drive innovation, economic growth, and new types of jobs,” says Chris Love, faculty co-director of INM. “MIT’s work on the PIE (Production in the Innovation Economy) study in 2013 highlighted the value of proximity between production and innovation. INM seeks to rekindle this relationship in manufacturing across the country.”

In 2026, MIT granted tenure to 10 faculty members across the School of Engineering. This year’s tenured engineers hold appointments in the departments of Aeronautics and Astronautics, Civil and Environmental Engineering, Electrical Engineering and Computer Science (EECS) — which reports jointly to the School of Engineering and MIT Schwarzman College of Computing — and Mechanical Engineering, as well as within the Institute for Medical Engineering and Sciences (IMES).

“I’m delighted to congratulate the 10 newest tenured faculty members in the School of Engineering. This major career milestone reflects not only their impact and excellence in research, but their deep commitment to education and mentoring the next generation of engineers. I am so excited to see what new developments, innovations, and technologies will come next from this incredibly accomplished group,” says Paula T. Hammond ’84, PhD ’93, dean of engineering, Institute Professor, and professor of chemical engineering.

This year’s newly tenured engineering faculty include the following:

Jacob Andreas is an associate professor in EECS and is affiliated with the Computer Science and Artificial Intelligence Laboratory (CSAIL). His work is in natural language processing, and more broadly in AI. He aims to understand the computational foundations of language learning, and to build intelligent systems that can learn from human guidance.

Zachary Cordero is the Esther and Harold E. Edgerton Associate Professor in the Department of Aeronautics and Astronautics and the associate director of the MIT Gas Turbine Laboratory. His research seeks to enable frontier aviation and space platforms through advanced materials, manufacturing, and structures, with a particular focus on high-temperature systems.

Christina Delimitrou is the KDD Career Development Professor in Communications and Technology and an associate professor in EECS. She is also affiliated with CSAIL. Her research sits at the intersection of computer architecture and computer systems; specifically, she is one of the first systems researchers to apply machine learning techniques to design and management problems in the cloud.

Sili Deng is the Doherty Career Development Professor in Ocean Utilization and an associate professor in the Department of Mechanical Engineering. Her group develops scientific machine learning and experimental approaches to understand, predict, and engineer chemically reacting systems for sustainable energy, advanced materials manufacturing, and climate-resilient technologies.

David Des Marais is the Amgen Career Development Professor in the Department of Civil and Environmental Engineering. He leads the Des Marais Lab, whose primary focus of research is to understand the mechanisms of plant-environment interaction, using tools from molecular, quantitative, and population genetics to identify the physiological basis of plant response to environmental cues.

Carmen Guerra-Garcia is the Esther and Harold E. Edgerton Associate Professor in the Department of Aeronautics and Astronautics and the director of the Aerospace Plasma Group. Her work lies at the intersection of aerospace engineering, low-temperature plasma technologies, and gas discharge physics. It addresses two aviation challenges — reducing emissions, and ensuring safety of next-generation aircraft — through three interconnected thrusts: advancing the fundamental science of electrical discharges in flowing gases and nonuniform media, applying that science to plasma-assisted combustion and chemical conversion, and developing physics-based approaches to lightning protection.

Laura Lewis is the Athinoula A. Martinos Associate Professor in EECS and IMES. Her research aims to develop methods to analyze and interpret multi-modal neuroimaging data in order to enable measurement of previously undetectable aspects of brain function. She has a particular interest in fast fMRI, EEG, and PET, and is applying those methods to study sleep.

Tami Lieberman is the Hermann L. F. von Helmholtz Career Development Professor in the Department of Civil and Environmental Engineering and IMES. She leads the Lieberman Lab, which seeks to understand how ecology and evolution shape the personalized communities of the human microbiome, and the role of this personalization on human health.

Kevin O’Brien is an associate professor in EECS and a member of the Research Laboratory of Electronics.  He leads the Quantum Coherent Electronics Group. His research efforts focus on developing tools, techniques, and devices to enhance the measurement of quantum systems, most notably superconducting quantum computers.

Wim van Rees is an associate professor in the Department of Mechanical Engineering and the Leonardo Career Development Professor in Engineering. His research advances high-order, high-fidelity numerical methods for efficiently simulating interactions between fluid flows and moving or deforming bodies, with methodologies spanning applications from wake vortex dynamics to bio-inspired propulsion and morphing structures. 

Researchers around the world are racing to develop new quantum-based systems for sensing, communication, computing, and control that have the promise of outperforming traditional systems. Creating stable, measurable, distinguishable quantum states, which would be the heart of any such system, is a daunting task.

Quantum states possess unique properties that can be exploited for developing novel information processing systems. Two key properties, stability and distinguishability, are hard to achieve, however. Extracting information from a quantum system depends on the distinguishability of quantum states, an intrinsic property associated with a property known as orthogonality. Nevertheless, no two Gaussian states (a widely studied class of quantum states) are orthogonal, and this yields an unavoidable error when attempting to distinguish them. 

In addition, present quantum devices tend to remain stable only for a fraction of a second, and require complex protocols to distinguish states. Now, researchers at MIT and the University of Ferrara have found a new approach for creating easily distinguishable states that could help to enable the development of these new quantum-based devices.

The new approach is described in a paper published today in the journal Physical Review A, by Moe Z. Win and Peter L. Falb at MIT with Andrea Giani and Andrea Conti at the University of Ferrara. The team found a way of translating between quantum states of light and algebraic varieties (a mathematical structure from abstract algebra), making the analysis more manageable by reducing it to solvable mathematical equations.

“Quantum systems can provide performance that is significantly better than classical counterparts,” Win says, “but this doesn’t come for free.” To develop practical devices for producing and detecting different states, “one needs to carefully engineer the quantum states in which they encode information.” 

Traditional computers typically use different voltages in a solid-state device to encode ones and zeros, while optical systems may use the presence or absence of a pulse of light. In quantum devices, the states might have to do with the spin state of a single atom, or the excitation level of a group of electrons.

Win adds that “we have been studying how to design distinguishable quantum states, which translates directly into improved performance for sensing and communication.” In the jargon of the field, they are improving the orthogonality — that is, the distinguishability — of different states.

The particular kinds of states studied in this theoretical analysis had to do with energy levels of photons, or particles of light. Giani explains that they used an operation called photon variation. This can take two forms: photon addition, in which photons are excited to a higher energy state, or photon subtraction, in which photons are annihilated (i.e., removed from the system). These operations change the quantum state from Gaussian to non-Gaussian states; it’s the non-Gaussian states that seem most useful, the team concluded. 

“The domain of non-Gaussian states is quite big,” Giani says, “but among them, we are looking into non-Gaussian states that are easier to implement with current technologies, because if we want to make the transition to the quantum world, we need to take into account realistic experimental challenges.”

Unlike some kinds of cutting-edge technologies being studied for possible quantum applications, Giani explains, “these kinds of photon-varied states have already been produced in the laboratory, and there is much interest in this kind of operation.”

These types of states are relatively new, Conti says, and so “there was a need for a theoretical characterization for these states,” The theoretical characterization this team derived, based on underlying mathematical properties, makes it possible to design states with higher levels of distinguishability. 

With this work, Win says, “we have a theory that gives us a blueprint to go design these non-Gaussian states, rather than just, ‘try this and that, and let’s hope they’re somewhat distinguishable.’ Our theory tells us exactly how to go about designing orthogonal non-Gaussian states.”

The findings result from the connection between the algebraic equations and the underlying physics, Win says, “That was the important connection between different disciplines — bringing algebraic geometry to the table.” 

“The equations to be solved for determining the orthogonality” of the quantum states “happened to be polynomial equations,” Falb says. “It just happened that there was the appropriate mathematics to solve them.”

Now that the principles have been established through this work, implementation should be relatively straightforward, the researchers say. There already are some optical setups that can be used to implement these kinds of states. 

“In principle,” Giani notes, “you can just put the parameters that you find by solving these equations directly into your physical apparatuses and produce these kinds of states. I don’t think this requires some more-advanced technology.” 

Conti adds that “as soon as this paper is published, we hope that experimentalists can try these methods.”

But that’s just the beginning, Win emphasizes. “We are getting momentum, and it’s very exciting,” he says. “The approach that we are taking here is to ask more general questions than just, ‘here’s a particular setup, how do you tune it to get a performance gain?’ Rather, we’re looking at a class of signal design problems, and then finding keys that really unlock these, so that hopefully the answer will not just be applied to only one particular setup, but something significantly broader.”

An international team of researchers has developed a novel fluorescent nanosensor powered by carbon nanotubes that is capable of rapidly detecting an emerging biomarker linked to gut health and disease. 

This important development could eventually lead to faster and more accessible gut-health testing. 

Indole-3-propionic acid (IPA) is a metabolite produced by gut bacteria during the breakdown of dietary tryptophan, an amino acid essential for protein synthesis. It plays an important role in regulating inflammation and oxidative stress, and has been associated with conditions such as inflammatory bowel disease (IBD), Type 2 diabetes, and liver disease. However, current detection methods rely on traditional mass spectrometry-based analytical techniques, which are costly and time-consuming, making it impractical for routine screening or point-of-care use.

The new platform addresses a longstanding gap in gut metabolite sensing. Using a fluorescence-based approach, the sensor produces a rapid optical readout within minutes, offering a significantly faster and more accessible alternative to conventional analytical techniques. It demonstrates high selectivity, distinguishing IPA from closely related metabolites commonly found in the gut, which enables accurate detection even in complex biological environments such as blood serum.

“This is the first time we are able to directly and rapidly measure IPA levels in biological samples using an optical nanosensor,” says co-first author Mervin Ang, assistant professor at the National Institute of Education (NIE) within Nanyang Technological University in Singapore, who was also associate scientific director at the Disruptive and Sustainable Technologies for Agricultural Precision (DiSTAP) interdisciplinary research group within the Singapore-MIT Alliance for Research and Technology (SMART) when the research was initiated. “This novel approach, which moves away from traditional mass spectrometry, can pave the way towards faster and more accessible ways of monitoring gut health in real-world settings.”

This latest breakthrough is described in the research team’s open-access paper, “Fluorescent Nanosensor for Indole-3-Propionic Acid Detection in Gut Health Monitoring,” in the journal Advanced Healthcare Materials. The work was led by researchers at NIE, MIT, and SMART, in collaboration with clinicians from the National University Hospital (NUH) and Yong Loo Lin School of Medicine within the National University of Singapore (NUS Medicine). 

From monitoring plants to sensing human health

The new nanosensor builds on SMART DiSTAP’s research into nano and optical sensor technologies. Originally developed to monitor plant health — including plant growth signals and stress responses —  the technology has now been adapted for human health applications by redesigning the nano- and optical-sensing platform to detect IPA.

“This work builds on technology at SMART DiSTAP on molecular recognition. We have used techniques like this to measure hormones and metabolites in living plants for agriculture, and have now applied it to the human gastrointestinal system. We were able to apply it to this long-standing challenge in gut health,” says Michael Strano, SMART DiSTAP lead principal investigator, the Carbon P. Dubbs Professor of Chemical Engineering at MIT, and corresponding author. 

“By focusing our molecular recognition on this important gut health biomarker, we’ve demonstrated a powerful new tool that could one day enable proactive, personalized health care. The tool promises near-instant insights into gut wellness, or the status of chronic diseases like IBD.”

A dual-mode platform for rapid testing and future monitoring

A key innovation of the technology is its dual-mode sensing capability. 

The nanosensor operates in both a visible fluorescence mode, enabling rapid, low-cost, high-throughput screening of biological samples; and a near-infrared mode, with wavelengths that can penetrate deeper into tissues. The near-infrared capability, enabled by carbon nanotubes, allows the technology to be adapted for in vivo applications and integration into wearable devices that could be used for home-based testing or continuous monitoring. This could, for example, help patients with chronic conditions like IBD detect flare-ups earlier and manage their health with greater autonomy. 

This flexibility allows the platform to be utilized in various environments, from laboratory tests to hospital bedside use, and wearable devices for real-time health monitoring. 

Validated in patient samples

To evaluate its clinical relevance, the research team collaborated with NUH clinicians to test the nanosensor on 125 human plasma samples across multiple patient groups, including healthy individuals and those with gastrointestinal diseases.

The study revealed significant differences in IPA levels between healthy individuals and patients with inflammatory bowel diseases, including Crohn’s disease and ulcerative colitis. Patients with active gut inflammation showed lower IPA levels — consistent with established clinical findings.

“From a clinical perspective, having a rapid and minimally complex way to assess metabolite levels like IPA could be very valuable,” says Jonathan Lee, senior consultant in the Division of Gastroenterology and Hepatology within the Department of Medicine at NUH; adjunct associate professor at NUS Medicine; and co-first author of the work. “It has the potential to complement existing diagnostic tools and provide additional insights into patients with inflammatory bowel diseases.”

Faster, more accessible gut health testing

Beyond the laboratory, this research could pave the way for faster and more accessible gut health testing. Instead of relying on complex and time-intensive laboratory methods, the new nanosensor could enable rapid screening in clinics, or even portable or home-based testing, helping to detect gut diseases earlier and monitor treatment progress more easily.

Unlike conventional microbiome tests that focus on identifying which bacteria are present, this nanosensor measures what those microbes are actively producing, offering a more direct and functional snapshot of gut health. Directly measuring metabolite output, rather than bacterial composition alone, could provide more meaningful insights into overall health and support more personalized approaches to health care. 

Beyond clinical diagnostics, the technology can be used to track the immediate efficacy of dietary interventions. Users can see rapidly if specific foods or probiotics are successfully fueling their gut bacteria to produce anti-inflammatory molecules like IPA. The sensor also demonstrated reliable performance in complex biological fluids such as serum and plasma, an important step toward real-world clinical deployment and further translational applications. 

For pharmaceutical and therapeutic research, the nanosensor could be used to conduct rapid functional tests to determine the efficacy of new therapeutics or probiotics. By providing an instant readout of IPA levels, the platform could enable them to demonstrate in real time that their therapeutics are biologically active and effective, significantly accelerating drug screening and dosage optimization processes.

Toward point-of-care diagnostics, and beyond

“The transition from laboratory discovery to a point-of-care clinical tool is already underway,” says Ang. “With further development, the platform has the potential to be translated into clinical applications, and in the long term, adapted into portable platforms for routine health monitoring.”

Looking ahead, the research team has been awarded an Innovation to Startup Innovation Grant to incubate a Singapore proto-startup to advance validation and development. The focus would be to translate the sensor into a point-of-care clinical diagnostic tool, and aim to expand the platform to detect multiple gut metabolites simultaneously and AI-driven signal deconvolution, enabling more accurate, comprehensive and personalized gut health monitoring. 

Future developments may also explore integration into wearable devices, microneedle systems, or microfluidic platforms for continuous, real-time sensing.

The research was supported by the Intra-CREATE Seed Collaboration Grant, and research conducted at SMART was supported by the National Research Foundation Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) program.

In a hospital or at home, temperatures are usually taken using an oral or forehead thermometer, but these do not always accurately reflect the core body temperature. Measuring core temperature from within the body could make it easier to determine whether someone is sick, and whether they’re at risk of spiking a dangerous fever.

To make it more feasible to obtain core body temperature measurements, MIT engineers have developed an ingestible sensor that can send continuous temperature updates from the GI tract. 

The sensor is shaped like a tiny blueberry, 6 millimeters in diameter and 4 millimeters in height. That makes it much smaller than existing ingestible temperature sensors, which are more difficult to swallow and pose a potential risk of obstructing the GI tract.

“A sensor like this gives us the ability to monitor infections and identify them early,” says Giovanni Traverso, an associate professor of mechanical engineering at MIT, a gastroenterologist at Brigham and Women’s Hospital, and an associate member of the Broad Institute of MIT and Harvard. “That’s very relevant, particularly for at-risk populations like people who are immunosuppressed from chemotherapy treatments or immunosuppressive drugs.”

Ingestible sensors could also enable more accurate temperature measurements for fertility tracking, and for monitoring people during anesthesia.

Traverso and Anantha Chandrakasan, MIT’s provost and the Vannevar Bush Professor of Electrical Engineering and Computer Science, are the senior authors of the new study. MIT postdoc Saransh Sharma is the lead author of the paper, which appears today in Nature Electronics.

Ingestible electronics

A handful of ingestible temperature sensors have become commercially available in recent years, but most are the size of a multivitamin or slightly larger, making them more challenging to swallow. Their size can also increase the risk of obstructing the GI tract.

Those capsules tend to be large due to the complex circuits they include, which require a great deal of power. That power is provided by relatively large, on-board batteries that make up much of the bulk of the capsule.

The MIT team wanted to design sensors that could measure temperature accurately, but at a much smaller size.

“The reason for them to be small is safety,” Traverso says. “We want something that is so small that the risk of any blockage or obstruction is highly mitigated, and also so that it can be easily ingested.”

To create a smaller device, the researchers set out to reduce the size of all of the main components — the temperature-sensing circuit, the antenna that relays temperature data, and the battery.

For the circuit, they created their own customized circuit that can fit onto a 1-square-millimeter silicon chip. To reduce the chip’s power consumption, the researchers designed an oscillator based on leakage current — the small current that flows through a circuit when it’s off. The frequency of this current varies depending on the temperature of the chip’s surroundings.

This circuit, which can detect temperature with an accuracy of 0.01 degrees Celsius, requires very little power — about 10 nanowatts. This means that it can be powered with a 1.55-volt coin cell battery, which is 4.8 millimeters in diameter and about 1.6 millimeter thick.

The new design further cuts energy consumption by using a communication strategy known as backscattering. This approach allows most of the power requirements to be outsourced to an external antenna that is located outside the body, within a foot or two of the sensor. The external antenna emits an ultra-high-frequency radio wave, which is then modulated by a tiny antenna within the sensor and sent back to the external antenna. By interpreting the changes in the radio wave, the external antenna can calculate the temperature value.

“We combined all of these different pieces together — the silicon chip, the battery, and the antenna — and we made it into an ingestible capsule, which is the smallest ingestible capsule that we have seen for temperature-sensing paradigms,” Sharma says. 

The internal antenna sends out a temperature reading once every second, allowing for continuous monitoring of temperature.

Tiny thermometers

The researchers envision that this kind of sensor could be useful in several scenarios, including monitoring infection and observing patients during and after anesthesia. Anesthesia often disrupts the body’s normal temperature regulation mechanisms, which can put patients at risk of hypothermia.

This type of device could also be used at home, for monitoring fevers in children, or measuring core body temperature as a marker of ovulation, for fertility purposes. It could also be useful for monitoring athletes, soldiers, or anyone else who might be exposed to extreme temperatures. 

To explore these possible uses, the researchers tested the sensors in animals while they were under anesthesia, and found that they could accurately detect and transmit temperature information. They also obtained accurate readings from animals that were awake and actively moving.

The researchers are now working on combining the temperature sensor with other sensors that could measure vital signs such as heart rate. They hope to begin testing these types of sensors in clinical trials within the next few years. 

If proven effective for people in high-risk situations, Traverso believes such sensors could become widely used by anyone who needs to monitor their temperature. 

“I think this could replace all thermometers, because it’s the most accurate way of taking temperature,” he says. “If we have miniature systems that can be easily swallowed and give very accurate data that’s superior to the current data, I think it can be helpful in so many ways.”

Other authors of the paper include Yubin Cai, Injoo Moon, Zhenming Yang, Peter Chai, Niora Fabian, Kailyn Schmidt, Alison Hayward, Andrew Pettinari, Maria Platero, Benedict Laidlaw, and Ashley Guevara.

The research was funded by the 711th Human Performance Wing, the Defense Advanced Research Projects Agency (DARPA), and the Advanced Research Projects Agency for Health (ARPA-H), which notes that the views and conclusions contained in this article are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the United States government.