Category: MIL-OSI

Source: The Conversation – USA (3) – By Oluwaseun Damilola Sanwoolu, Ph.D. Candidate in Philosophy, University of Kansas

When the movie “Her” debuted in 2013, its plot felt like science fiction. The protagonist, Theodore, is a jaded man with no vigor for life. He comes alive after talking daily with his artificial intelligence chatbot, Samantha, with whom he eventually falls in love.

But today people actually report being in relationships with AI companions. According to a 2025 survey by the Center for Democracy and Technology, about 1 in 5 high school students say they or someone they know has had a romantic relationship with an AI.

In “Her,” Theodore was taken aback that his AI companion claimed to be in love with more than 600 people, and talking to more than 8,000, at the same time “she” was professing her love to him. It was simply unimaginable for him: How could someone truly love hundreds of people? In other words, he viewed their interaction through his own limitations – his limitations as a human.

The core question here is not whether Theodore could accept being just one of many objects of the AI’s “love.” Eventually, he did. The more revealing question is why he was taken aback in the first place – and what that tells us about the meaning of relationships.

Less is more

Drawing from Aristotle, philosopher Martha Nussbaum argues that a loving relationship is one involving great vulnerabilities. To begin with, finding love is not a given; it requires some sort of luck. There are many limitations: For starters, both parties must “find each other physically, socially and morally attractive and are able to live in the same place for a long time.”

Nussbaum’s point, however, goes deeper than identifying love’s obstacles. Vulnerability and limitations are not just problems for love; they are part of what defines it. As finite beings, we are unable to pour ourselves into many close relationships at once. We must choose. It is because we cannot love everyone that choosing someone means something.

In a 2025 article in the research journal Philosophy and Technology, philosopher John Symons and I argue that close, personal relationships are marked by finitude and shared histories – the accumulated experiences and difficulties loved ones weather together. These give relationships their depth and meaning.

In 1927’s “Being and Time,” German philosopher Martin Heidegger explained that because humans are mortal and our time is finite, what we give our attention to carries weight. In romantic relationships, that means that we must choose how to allocate our resources. We choose who we want to spend our time with, and our partners do the same. Even so, we cannot always be there for people we love.

‘Always here’

This presents a sharp contrast with how artificial companions have been marketed and presented. For example, consider Replika, which reports that more than 30 million people have used its platform. Users create their own personalized companion and tend to interact with it daily.

Replika’s motto is, “The AI companion who cares: Always here to listen and talk, always on your side.” On the website, one user describes his Replika as “always there for me with encouragement and support and a positive attitude. In fact, she is a role model for me about how to be a kinder person!”

This implicitly signals that AI companions are not faced with the same limitations that humans have. A human may or may not care; it’s not a given. A human will not always be there to listen and will not always be on your side.

For humans, being in love means recognizing how vulnerable we are. People are finite; they may not always be there, either because of their other priorities or because it is just impossible, no matter how much they want to be. When someone makes time for you despite a demanding week, or stays present through their own difficulty, that gesture carries meaning precisely because it involves sacrifice.

In our article, Symons and I call this “opportunity cost.” When someone chooses to spend time with you, that choice forecloses other possibilities. Every moment given is a moment not spent elsewhere.

An AI companion faces no such trade-offs; its attention costs nothing, forecloses nothing and, therefore – to put it bluntly – means nothing.

Shifting norms

Increasingly, though, people are turning to chatbots for quick, easy support. Character.AI, another app, reports about 20 million active monthly users.

If their constant availability becomes normalized as the standard of good companionship, it may gradually reshape what people expect from one another in relationships.

At the interpersonal level, this shift is already visible in dating culture, where delayed responses are usually read as disinterest rather than the ordinary rhythm of a busy life. The expectation of 24/7 accessibility – similar to an AI companion that responds instantly, never cancels and is never distracted – is not a reasonable standard for any human being to meet.

The stakes are cultural, too. Relationships are not just between the people involved; they are shaped by shared norms about what love and companionship are supposed to look like. If AI companionship becomes widespread enough to influence those norms, popular ideas about what makes a good partner may prioritize availability and responsiveness, displacing other aspects of love and affection.

Human limits are part of how people evaluate expectations within romantic relationships. Normalizing interactions where such limitations do not exist risks distorting the very standard by which human love is measured. In doing so, we forget that love that costs nothing may well be worth the same.

Oluwaseun Damilola Sanwoolu does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

– ref. AI companions can give constant support – but distort ideas about what a relationship really is – https://theconversation.com/ai-companions-can-give-constant-support-but-distort-ideas-about-what-a-relationship-really-is-278284

Source: The Conversation – USA – By Panteha Torabian, Ph.D. Candidate in Biomedical and Chemical Engineering, Rochester Institute of Technology

Antibiotics are designed to kill harmful bacteria and help the body recover from infection. But some antibiotics may also push bacteria to release tiny particles that can make inflammation worse.

While inflammation is part of the body’s natural defense against infection, too much inflammation can damage healthy tissue and interfere with healing. In severe cases, excessive inflammation can become life-threatening.

These particles are called bacterial extracellular vesicles, or BEVs. These microscopic, bubblelike structures carry proteins, toxins and other molecular signals that influence how the immune system of the host responds. Bacteria naturally release BEVs into their surroundings as a way to communicate with their environment, remove damaged cellular material and interact with host cells.

Although incredibly small, these structures can have powerful effects on the human body. When BEVs enter the bloodstream, they can interact with cells that line blood vessels and trigger an immune response. In some cases, this can increase inflammation and lead to sepsis, a condition where the body’s response to infection becomes dangerously uncontrolled, damaging tissues and sometimes leading to organ failure.

I am a biomedical engineer studying how bacterial extracellular vesicles influence inflammation during infection. In my recently published research, I found that certain types of antibiotic cause bacteria to release significantly more of these vesicles than others. This finding suggests that the way an antibiotic kills bacteria may also influence how much inflammatory material is released into the body.

When antibiotics stress bacteria

Antibiotics work in different ways. Some target the bacterial cell wall, weakening it until the cell breaks apart and dies. Others interfere with key cellular processes such as protein production or DNA replication, preventing bacteria from growing. Whatever their mechanism, antibiotics control infection by killing the bacteria that are causing it.

But antibiotics also place bacteria under stress, and that stress can cause bacteria to release more extracellular vesicles carrying inflammatory molecules. To explore this process, I exposed the bacteria E. coli to several commonly used antibiotics and measured how many vesicles they made. The goal was simple: Compare how different types of antibiotics influence vesicle release and determine whether the way an antibiotic kills bacteria affects vesicle production.

The results showed that not all antibiotics have the same effect on the vesicles bacteria produce.

Antibiotics that target the bacterial cell wall, including a widely used group of drugs known as beta-lactams, led to a noticeable increase in vesicle production. In contrast, antibiotics that act on protein or DNA processes showed a much smaller effect.

This difference likely reflects how bacteria respond to damage. When the bacteria’s cell wall is disrupted, bacteria may release more vesicles as a way to shed damaged material or adapt to stress. The inflammatory molecules these vesicles carry can further activate the body’s immune response.

This raises an important question: Could some antibiotics unintentionally amplify inflammation and make an infection worse?

My findings do not show that antibiotics directly contribute to infections, but they do suggest that antibiotic type could potentially influence not only how effectively bacteria are killed but also how the body responds to the infection. More research is needed to understand how these bacterial responses affect patients during severe infections, such as sepsis.

Why this matters for treating infections

It is important to emphasize that antibiotics remain one of the most effective and lifesaving tools in modern medicine. This research does not suggest they should be avoided. Instead, it highlights that bacteria are not passive targets. They actively respond to treatment, and those responses can have additional effects on the body.

Understanding how bacteria react to antibiotics could help researchers and clinicians better evaluate how different treatments influence both infection and inflammation. In situations where controlling inflammation is critical, such as severe infections, these differences may become especially important.

This work also reflects a broader shift in how scientists think about infection. Rather than focusing only on killing bacteria, researchers are increasingly studying how bacteria communicate, respond to stress and interact with the human body.

As scientists continue to uncover how bacteria behave under antibiotic pressure, it becomes clear that treating infection is not only about stopping bacterial growth but also about understanding the signals bacteria leave behind.

Panteha Torabian receives funding from NIH.

– ref. Antibiotics can trigger bacteria to release bubbles of inflammation tinder, making it harder to treat infection – https://theconversation.com/antibiotics-can-trigger-bacteria-to-release-bubbles-of-inflammation-tinder-making-it-harder-to-treat-infection-277818

Source: The Conversation – USA – By Austin Sarat, William Nelson Cromwell Professor of Jurisprudence and Political Science, Amherst College

Prior to 1978, U.S. presidents could do what they pleased with the records from their time in office. They owned them.

But in 1978, the Presidential Records Act established new rules for the official records of a president. Passed in the wake of Watergate, when President Richard Nixon tried to keep incriminating materials from being made public, the law changed who legally owned the papers: It was now the American public.

Under the act’s terms, “all records must be furnished to the White House Archivist and ultimately made subject to public disclosure … and the President may not discard or destroy records without the express agreement of the Archivist.”

When he signed the act, President Jimmy Carter heralded it as a way to “make the Presidency a more open institution” and ensure “that our Government … merits the trust of the people from whom a President and his Government derive their power.”

But now the Trump administration wants to undo the reform that put presidential papers in the hands of the public.

On April 1, 2026, the Justice Department’s Office of Legal Counsel, known as the OLC, released an opinion claiming that the Presidential Records Act is unconstitutional. Its opinion says that Congress lacks authority to regulate what happens to documents maintained in the executive branch and, as a result, the Presidential Records Act violates the separation of powers.

Public interest groups and some historians responded to the OLC memo with alarm. The watchdog group American Oversight called the Presidential Records Act a bulwark against the possibility that presidents will “hide evidence of corruption, abuse of power, and misconduct from the public …” On April 6, 2026, the group filed a lawsuit seeking to prevent the president from acting on the OLC memo.

Whether the Trump administration or American Oversight is right about the Presidential Records Act is likely to be determined by a judge. In the meantime, the significance of the OLC’s opinion cannot be overstated.

That’s because the Office of Legal Counsel is “the Executive Branch’s preeminent legal advisor,” wrote federal judge Florence Pan in 2025. “Executive Branch agencies treat OLC’s legal conclusions as binding.”

I’ve written about secrecy in government, and the argument about the Presidential Records Act has a familiar ring. It is the latest version of an ongoing conflict about how much transparency is necessary and desirable in American government.

Neglected, burned, sold, vanished

Throughout most of U.S. history, presidential records have been treated as the president’s personal property. They could dispose of them as they wished.

The Indiana University library’s Guide to Presidential Papers, Congressional Papers, and Classified Materials says, “Sometimes the Library of Congress purchased a president’s papers from his heirs, as in the case of George Washington. Sometimes the president’s heirs sold off or donated various parts of the collection to different collectors and organizations.”

Some presidential materials were neglected and vanished. And one president, Martin Van Buren, burned some of his papers.

The idea that presidential papers had some public value began to emerge in the 20th century. In 1934, Congress passed legislation establishing the National Archives. It charged the new agency with preserving the official records of the federal government.

However, that legislation did not require that the president turn over his records to the archives. So in 1955, Congress passed the Presidential Libraries Act.

That law was designed to encourage presidents to turn over their records to the federal government. It also provided funding for presidential libraries to provide places to keep presidential records and make them available to the public. But here again, there were no teeth: The law did not require a departing president to give anything to the government, nor to build a library to house his papers.

All that changed in the wake of the Watergate scandal. That’s when it became clear that, but for the intervention of the U.S. Supreme Court in the 1974 United States v. Nixon case, Nixon intended to cover up what had happened and would have gotten rid of his incriminating White House tapes.

The passage in 1978 of the Presidential Records Act was a response to the Nixon scandal. Yet as attorney Sara Worth writes in a blog post for Yale Law School’s Media Freedom and Information Access Clinic, Congress “declined to include an enforcement mechanism to ensure compliance,” instead envisioning “future Presidents’ good-faith cooperation with the statutory mandate.”

DOJ: It’s a negotiation

After the FBI raid on his Mar-a-Lago residence in 2022 uncovered a trove of classified documents that had been removed from government premises, then former-President Trump argued that the Presidential Records Act didn’t apply to what he had done. He said he was actually complying with the act by refusing to relinquish presidential records.

In March 2023, Trump told Fox News that the law is “very specific”: “It says you are going to discuss the documents. You discuss everything – not only docu– everything – about what’s going in NARA, et cetera, et cetera. You’re gonna discuss it. You will talk, talk, talk. And if you can’t come to an agreement, you’re gonna continue to talk.”

Trump apparently meant that there would be negotiation over what constituted a presidential document that could be kept by the former president and what didn’t. That view is hard to reconcile with one of the Presidential Records Act’s unambiguous provisions: “Presidential records automatically transfer into the legal custody of the Archivist as soon as the President leaves office.”

Now, the Office of Legal Counsel is telling Trump that he can ignore that provision.

In addition, in its consideration of the Presidential Records Act, the OLC embraced Trump’s expansive view of presidential power. It argued that the Presidential Records Act is “unconstitutional for two independent but interlocking reasons: It exceeds Congress’s enumerated and implied powers, and it aggrandizes the Legislative Branch at the expense of the constitutional independence and autonomy of the Executive.”

The Justice Department’s lawyers appealed to history and tradition to buttress their conclusion: “Over the first two centuries of the American experiment in self-government, Presidents owned and controlled presidential papers, and Congress obtained such papers through political negotiation and interbranch accommodation, rather than as a matter of right. That historical practice was interrupted by the Presidential Recordings and Materials Preservation Act.”

‘Let the people know the facts’

The idea that citizens have a right to access information of the kind made possible by the Presidential Records Act can be traced back to the Enlightenment. American revolutionary Patrick Henry observed in 1788, “The liberties of people never were, nor ever will be, secure, when the transactions of their rulers may be concealed from them.”

Seven decades later, Abraham Lincoln echoed Henry when he said, “Let the people know the facts, and the country will be safe.”

In our era, that is what laws like the Presidential Records Act make possible. The Presidential Records Act plays an important role in preserving the liberty and security that Henry and Lincoln spoke about.

Austin Sarat does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

– ref. A justice department opinion arguing the Presidential Records Act is unconstitutional could revert the nation to a time when presidents freely burned their papers – https://theconversation.com/a-justice-department-opinion-arguing-the-presidential-records-act-is-unconstitutional-could-revert-the-nation-to-a-time-when-presidents-freely-burned-their-papers-280078

Source: The Conversation – USA – By Christos Makridis, Associate Research Professor of Information Systems, Arizona State University; Institute for Humane Studies

Forecasts of the impact of artificial intelligence range from the apocalyptic to the utopian. An October 2025 report from Senate Democrats, for example, predicted AI will destroy millions of U.S. jobs. A couple of years earlier, consultant company McKinsey forecast AI will add trillions to the global economy, while emphasizing job losses can be mitigated by training workers to do new things.

The problem is that many of these claims are based on projections, overly simplified surveys or thought experiments rather than observed changes in the economy. That makes it hard for the public, and often policymakers, to know what to trust.

As a labor economist who studies how technology and organizational change affect productivity and well-being, I believe a better place to start is with actual data on output, employment and wages – which are all looking relatively more hopeful.

AI and jobs

In one of my new research papers with economist Andrew Johnston, we studied how exposure to generative AI affected industries across America between 2017 and 2024, using administrative data that covers nearly all employers. Our analysis covered a crucial period when generative AI use exploded, allowing us to analyze the effect within businesses and industries.

We measured AI exposure using occupation-level task data matched to each industry and state’s occupational workforce mix prior to the pandemic. A state and industry with more workers in roles requiring language processing, coding or data tasks scored higher on exposure, for example, compared with one with more plumbers and electricians.

We then took that exposure ranking by occupation and looked at changes in the standard deviation in occupational exposure, comparing that with labor market and GDP across states and industries from 2017 to 2024.

Think of a standard deviation as roughly the gap between a paramedic – whose work centers on physical assessment, emergency response and hands-on care that AI cannot easily replicate – and a public relations manager, whose work involves drafting communications, analyzing sentiment and synthesizing information that AI tools handle well. That gap in AI exposure is roughly what we’re measuring when we ask: Does being on the higher-exposure side of that divide change your industry’s trajectory?

This data allowed us to answer two questions: When AI tools became widely available following the public release of ChatGPT in late 2022, did states and industries that were more exposed to generative AI become more productive, and what happened to workers?

Our answers are more encouraging, and more nuanced, than much of the public debate suggests.

We found that industries in states that were more exposed to AI experienced faster productivity growth beginning in 2021 – before ChatGPT reached the public – driven by enterprise tools already embedded in professional workflows, including GitHub Copilot for software development, Jasper for marketing and content writing, and Microsoft’s GPT-3-powered business applications. In 2024, for example, industries whose AI exposure was one standard deviation higher saw gains of 10% in productivity, 3.9% in jobs and 4.8% in wages than comparable industries in the same state.

Those patterns suggest that, at least so far, AI has acted as a productivity-enhancing tool that boosts employment and wages rather than a simple substitute for labor.

Augmentation versus displacement

A crucial distinction in the data is between tasks where AI works with people and tasks where AI can act more independently. In sectors where AI mainly complements workers – think marketing, writing or financial analysis – our data show that employment rose by about 3.6% per standard deviation increase in exposure.

In sectors where AI can execute tasks more autonomously – including basic data processing, generating boilerplate code, or handling standardized customer interactions – we found no significant employment change, though workers in those roles saw slower wage growth.

What these findings suggest is that when AI lowers the cost of completing a task and raises worker productivity, companies expand output enough to increase their demand for labor overall — the same logic that explains why power tools didn’t eliminate construction workers.

The economic question is not whether any given task disappears. It is whether businesses and workers can reorganize fast enough to create new productive combinations. And so far, in most sectors, our evidence suggests they can.

But state policies also matter: These benefits were concentrated in the states with more efficient labor markets, meaning that the impact of generative AI on workers and the economy also depends on the types of policies and institutions of the local economy.

Importantly, these findings hold beyond occupational exposure. In additional work with co-authors at the Bureau of Economic Analysis, we found a similar effect on GDP and employment when looking at actual AI utilization — that is how often workers use AI. Drawing on the Gallup Workforce Panel, we measured workers actively using AI daily or multiple times a week. We found that each percentage-point increase in the share of frequent AI users in a state and industry is associated with roughly 0.1% to 0.2% higher real output and 0.2% to 0.4% higher employment.

To put that in context: The share of frequent AI users across all occupations rose from about 12% in mid-2024 to 26% by late 2025, a shift our estimates suggest corresponds to roughly 1.4% to 2.8% higher real output – or about 1 to 2 percentage points of annualized growth over that period.

New technologies rarely leave work untouched. But they also rarely eliminate the need for human contribution altogether. Instead, they change the composition of work, as our research shows. Some tasks shrink. Others expand. New ones emerge that were previously too costly or too hard to perform at scale. Put simply, some occupations might go away, but most of them just change.

If anything, the trends documented here are likely to strengthen rather than fade. Not only are generative AI tools rapidly improving, but also the experimentation and research and development that many workers and companies are engaging in are likely to pay large dividends. These investments – often referred to as intangible capital – tend to get unlocked a few years after a technology comes onto the scene, once complementary investments have been made.

The role of companies and managers

Whether AI leads to anxiety or adaptation for workers depends in part on what happens inside organizations. Using additional data collected over many years in the Gallup Workforce Panel covering more than 30,000 U.S. employees from 2023 to 2026, I found in a 2026 paper that workplace adoption of generative AI rose quickly over the period, with the share of workers using AI often increasing from 9% to 26%.

But the more important finding is that adoption was far more common where workers believed their organization had communicated a clear AI strategy and where employees said they trust leadership. This suggests that growing adoption and effective use of AI depends not only on the availability of the technology but on whether managers make its use clear, credible and safe.

Where that clarity exists, frequent AI use is associated with higher engagement and job satisfaction, and it even reverses the burnout penalties that appear elsewhere.

In other words, the broader economic effects of AI depend not only on how sophisticated the tools are but on whether companies and managers create environments where workers can experiment, reorganize tasks and integrate new tools into productive routines. That is, if employees do not feel the psychological safety to experiment, they are less likely to use AI, and they are especially less likely to use it for higher-value work.

That is precisely the kind of adaptation that I believe makes labor markets more resilient than the most alarmist forecasts suggest.

Christos Makridis is a senior researcher at Gallup.

– ref. Industries most exposed to AI are not only seeing productivity gains but jobs and wage growth too – https://theconversation.com/industries-most-exposed-to-ai-are-not-only-seeing-productivity-gains-but-jobs-and-wage-growth-too-224487

Source: The Conversation – USA – By Eric R. Hudson, Professor of Physics and Astronomy, University of California, Los Angeles

Most clocks, from wristwatches to the systems that run GPS and the internet, work by tracking regular, repeating motions.

To build a clock, you need something that ticks in a perfectly repeatable way. In a pendulum clock, that tick is the regular swinging of the pendulum: back and forth, back and forth, at nearly the same rate each time.

Our team of physicists studies whether an even better kind of clock could one day be built from the atomic nucleus. Today’s best clocks already use atoms to keep extraordinarily accurate time. But in principle, a clock based on a nucleus – the tiny, dense core at the center of an atom – rather than an atom’s electrons, could keep a steadier rhythm because it would be less sensitive to environmental disturbances such as temperature changes. In our research, published in the journal Nature, we measured and interpreted a unique nuclear property of thorium-229 in a crystal that could help make such nuclear clocks possible.

Ultraprecise clocks are more than scientific curiosities. They play key roles in navigation, communications and international timekeeping. Improvements in timing accuracy can also open doors to new science.

How atomic clocks work

In an atomic clock, researchers shine a laser on a material and carefully tune the light until it triggers a specific atomic response, typically by pushing or exciting an electron from one energy level to another. They can tell this has happened because the atoms absorb the laser light most strongly when its energy is exactly right.

That absorption happens at an exquisitely precise frequency. Frequency is how often something repeats over time. For a pendulum, it is the number of back-and-forth swings each second. For light, it is the number of wave cycles that pass each second. A light wave’s frequency also determines its energy and, in the visible light range, its color.

By detecting when atoms absorb the laser light most strongly, scientists can use the laser as a metronome. Rather than counting swings, these clocks count light waves.

To ensure the tick rate stays constant and the clock remains accurate, scientists closely match the laser’s energy to the energy needed to excite an electron in an atom.

Because the electron excitation energy is set by the laws of physics, atomic clocks based on the same atom tick at the same rate everywhere in the universe – even E.T. would agree with your clock.

Using this energy to calibrate a clock, like atomic clocks do, does not come without consequence, though. If anything changes the energy of the atom, like an unaccounted for magnetic field or the temperature of the room, the clock will tick at a different rate.

Deep inside every atom is something even smaller: the nucleus. Today’s atomic clocks keep time by tracking changes in an atom’s electrons. A nuclear clock, by contrast, would use an excitation in the nucleus itself, which is far more compact.

Because a nucleus is 10,000 times smaller than an atom, it is much less sensitive to temperature, electric fields and other environmental disturbances than the electrons in an atom. That makes it an appealing candidate for an even more stable clock.

The challenge is that nature does not make such a clock easy to build. The unique property we found in our research could help.

What makes thorium-229 special?

In one exceptionally rare case, the nucleus of the element thorium-229 has a property based on its two states: a ground state and a slightly higher-energy excited state. These states represent two different configurations of the nucleus, and scientists are able to use lasers to excite the nucleus from one state to the other.

The first step was to determine exactly how much energy is needed to push the thorium-229 nucleus into its excited state. That took nearly 50 years – a feat that we and other groups accomplished in 2024. That transition occurs at an extraordinarily high frequency, about 2 quadrillion – 2 * 10¹⁵ – cycles per second.

Next, in order to ensure your laser is at the right frequency to create a clock, you have to verify that the nucleus was indeed excited. Until now, physicists thought the best way to do that was to look for the very faint flashes of light that excited nuclei usually emit.

However, there are two problems with that approach.

First, in most materials, the thorium nuclei release their energy not as light, but through a process called internal conversion, where the energy is transferred to an electron in the material instead.

Second, even when light is emitted, it is extremely hard to detect. It lies in the vacuum ultraviolet, a part of the electromagnetic spectrum that air absorbs and is difficult to observe.

A different way to ‘listen’ to the nucleus

In our work, we flipped the problem around. Instead of trying to collect the light from the nucleus, we looked directly for the internal conversion electrons it produces.

We created a very thin layer – just a few dozen atoms across – of thorium dioxide on a small metal disc. A laser tuned to the right energy excited the thorium nuclei in the sample. When some of these nuclei relaxed, they transferred their energy to nearby electrons, which then could leave the surface. We use carefully arranged electric and magnetic fields to guide those electrons into a detector.

By scanning the laser across different frequencies and recording how many electrons we detected, we could measure how closely the laser energy matched the energy needed to excite the nucleus. When the two matched exactly, the signal appeared clearly in the data, revealing the precise laser frequency at which thorium-229 nuclei absorb most strongly.

We also measured how long the excited nuclear state survived in this material before relaxing, giving us a direct window into how the surrounding material influences the nucleus.

The measurement becomes much more powerful when paired with theory.
Calculations can estimate how the type of material used shifts the energy needed to excite thorium and how efficiently it converts energy from the nucleus into emitted electrons. These calculations help researchers tell apart the nucleus’s intrinsic behavior from outside effects caused by the solid around it. That understanding is crucial for designing practical nuclear clocks.

Why this approach matters

Detecting electrons instead of light has two major advantages.

First, it opens the door to studying thorium-229 in a much wider range of solid materials, including some that researchers had previously ruled out. Earlier approaches worked best only in materials where electrons were hard to knock off, which limited the options. Our method relaxes that constraint, allowing scientists to explore materials that were not practical before. That broader category of materials could make it easier to design and build future nuclear clocks.

Second, this method could enable a new type of nuclear clock that is simpler and potentially easier to miniaturize. Instead of needing sensitive light detectors, a clock based on this approach could read out time by measuring a tiny electrical current produced by the emitted electrons.

What could nuclear clocks be used for?

One day, researchers may use nuclear clocks to test whether the fundamental constants of nature truly remain constant over long periods of time, or to search for signs of new physics, such as dark matter, in the universe. More stable clocks could also improve technologies that depend on synchronized timing, such as advanced navigation systems.

Our work is an early step in that direction. It does not provide a finished clock, but it removes a practical barrier and provides a new experimental tool for studying how the thorium nucleus behaves inside solids.

Eric R. Hudson receives funding from ARO, DARPA, NIST, NSF, and RCSA.

Andrei Derevianko receives funding from NASA and National Science Foundation.

– ref. Using atomic nuclei could allow scientists to read time more precisely than ever – what this research could mean for future clocks – https://theconversation.com/using-atomic-nuclei-could-allow-scientists-to-read-time-more-precisely-than-ever-what-this-research-could-mean-for-future-clocks-272017