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Rich people more likely to steal children’s sweets, finds Ig Nobel prize-winning study

We round up the winners at awards for achievements that ‘first make people laugh and then make them think’

Sep 3 • 1:00 PM EDT • Science • theguardian.com

'Soiled' undies and vicious friends research honoured at Ig Nobels

Each year, the Ig Nobel prizes celebrate research that makes you laugh, then makes you think. This year's winners include an "underwear index", a cumbersome kissing definition and why we want friends that will happily stab someone in the eye.

Sep 3 • 1:00 PM EDT • Science • abc.net.au

Scientists observe Einstein's gravity in the quantum world

An international team including Nobel Prize-winning physicist Professor Sir Roger Penrose has observed a long-predicted effect of gravity on a falling quantum object for the first time. The result shows ...

Sep 2 • 2:00 PM EDT • Science • phys.org

Ig Nobel Prizes leave U.S. amid concerns about Trump policies

This year's Ig Nobel Prizes will be held in Zurich, Switzerland, Sept. 3.

Sep 1 • 11:10 AM EDT • Science • bostonglobe.com

LZ Sees Surprising Result in Search for Dark Matter

Key Takeaways Dark matter is the mysterious substance that accounts for the vast majority of matter in our universe. LUX-ZEPLIN (LZ) is a world-leading dark matter detector and specializes in searching for WIMPs, or weakly interacting massive particles. A new LZ study found one particle interaction that is difficult to explain with known background processes and could potentially have been caused by a WIMP. LZ continues to run to see if additional data strengthens or weakens the hint of a dark matter interaction. For the better part of a century, people have been trying to understand dark matter. This invisible substance makes up roughly 85% of the mass in the universe but has never been directly detected. Determining exactly what it is remains one of the biggest questions about our world. Now, a new analysis from the LUX-ZEPLIN (LZ) experiment has recorded a single particle interaction that researchers have great difficulty explaining with known background signals from normal matter. The result does not yet meet the statistical threshold required to claim a discovery, but is the most compelling hint of dark matter reported by the experiment to date. LZ is an international collaboration of 250 scientists and engineers from 39 institutions. The detector is managed by the U.S. Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab) and operates nearly one mile below ground at the Sanford Underground Research Facility (SURF) in South Dakota. The experiment uses 10 tonnes of ultrapure liquid xenon to search for dark matter and is optimized to look for WIMPs, or weakly interacting massive particles. The results were presented in a scientific talk at the 2026 TeV Particle Astrophysics conference in Japan. The paper will be released on the online repository arXiv and submitted to the journal Physical Review Letters. “We’re very intrigued to see this event in the data, in the region where we expect dark matter to show up and the competing backgrounds are very low,” said Rick Gaitskell, a professor at Brown University and the spokesperson for LZ. “With only one event, we don’t want to get ahead of ourselves. We are not claiming to have seen dark matter. But we have seen something interesting that we want to share with the scientific community for their input.” The LZ collaboration studies experimental data in batches. In the new result, researchers analyzed 220 live days of data collected between March 2023 and April 2024. The collaboration had previously searched this dataset for faint signals from the simplest kinds of WIMP interactions. The new analysis searched for a broader range of possible WIMP interactions that could deposit more energy in the detector. LZ is particularly sensitive to such signals while also minimizing false positives. “This was a detailed study in a region we hadn’t explored within this dataset, and we spent months of additional effort to understand all the possible causes of background events,” said Sam Eriksen, a senior research associate at the University of Bristol in the U.K. and lead author of the study. “We understand our detector and the backgrounds so well that even a single outstanding event, like the one we found, is important. We expect dark matter events to be extremely rare, so only a handful could mark the first detection of WIMP dark matter.” If the anomalous event was caused by dark matter, the WIMP that generated it would likely have a mass of at least 200 GeV/c2 (gigaelectronvolts), or more than 200 times the mass of a proton. It would also suggest a specific type of interaction between WIMPs and ordinary matter beyond the simplest model. The LZ results have not reached “5-sigma” significance, the statistical threshold considered a discovery in physics. The new analysis is 2.6 sigma, meaning there is approximately a 0.5% chance that the event could be explained by known backgrounds. With additional data, researchers can test whether the finding continues to grow in significance or fades away. LZ has already accumulated the world’s largest dark matter dataset and will continue to accrue WIMP search data at SURF, substantially improving their search statistics. LZ searches for dark matter by looking for signature flashes of light from energy deposited in the detector. The collaboration leverages multiple methods to prevent or account for particle interactions caused by normal matter. This includes the mile of rock that shields the detector from cosmic rays from space, a water tank and outer detectors that protect the central detector from background neutrons, and a suite of computational tools that disentangle particle interactions and reject dark matter mimics. “Outlier events in the data are not unexpected, but they usually stand out as a background of some kind when you look at them deeper,” said Aaron Manalaysay, a physicist at Berkeley Lab and the chair of LZ’s Institutional Board. “This is the first example in any experiment I’ve worked on of an outlier that appears valid in every way. Of course, we’re still twisting our brains trying to think if there’s a rare background mechanism we could’ve missed, but it’s thrilling to wonder if this could be the first hint of a dark-matter observation.” LZ is supported by the U.S. Department of Energy, Office of Science, Office of High Energy and Nuclear Physics, and the National Energy Research Scientific Computing Center, a DOE Office of Science user facility. LZ is also supported by the Science & Technology Facilities Council of the United Kingdom; the Portuguese Foundation for Science and Technology; the Swiss National Science Foundation; the Australian Research Council Centre of Excellence for Dark Matter Particle Physics; and the Institute for Basic Science, Korea. Thirty-nine institutions of higher education and advanced research provided support to LZ. The LZ collaboration acknowledges the assistance of the Sanford Underground Research Facility. ### Lawrence Berkeley National Laboratory (Berkeley Lab) is committed to groundbreaking research focused on discovery science and solutions for abundant and reliable energy supplies. The lab’s expertise spans materials, chemistry, physics, biology, earth and environmental science, mathematics, and computing. Researchers from around the world rely on the lab’s world-class scientific facilities for their own pioneering research. Founded in 1931 on the belief that the biggest problems are best addressed by teams, Berkeley Lab and its scientists have been recognized with 17 Nobel Prizes. Berkeley Lab is a multiprogram national laboratory managed by the University of California for the U.S. Department of Energy’s Office of Science. DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science.

Sep 1 • 10:00 AM EDT • Science • newscenter.lbl.gov

Vitamin C won’t prevent most colds, but it may do one small thing

The belief that huge doses of vitamin C can ward off colds was popularized more than 50 years ago by Nobel Prize winner Linus Pauling. Since then, larger studies have found that vitamin C does not prevent most people from catching a cold, although regularly taking it may make severe symptoms slightly shorter or milder.

Aug 26 • 8:00 PM EDT • Science • sciencedaily.com

Scientists Release Biggest 2D Map of the Universe

Key Takeaways The DESI Legacy Imaging Surveys combined more than 263,000 telescope exposures to make the largest 2D map of the universe in visible and near-infrared light. Astronomers can pair the Legacy Surveys map with their own observations to explore our universe and search for rare phenomena. The 2D map serves as the foundation for the Dark Energy Spectroscopic Instrument survey to measure the universe in 3D and investigate dark energy. Hold on to your telescopes: the DESI Legacy Imaging Surveys team has released the largest-ever 2D color map of the universe. The 5.6-trillion-pixel map contains nearly 4 billion celestial objects, primarily stars and galaxies. The data is available for all to use and publicly viewable through the Legacy Survey Sky Viewer. Astronomers and citizen scientists can explore the map or combine it with their own observations to better understand our universe. Researchers can search for rare phenomena like gravitational lenses, observe fleeting events like supernovae, and investigate two of physics’ biggest mysteries: dark matter, the invisible substance that accounts for most of the mass in our universe, and dark energy, the force driving our universe’s accelerating expansion. The new map builds on earlier versions from the DESI Legacy Imaging Surveys that have already proved invaluable. To date, more than 1,800 science papers that reference the Legacy Surveys data have been published. “It’s part of the fabric of astronomy research now,” said David Schlegel, a co-lead of the Legacy Surveys and scientist at the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab). “When you’re working with astronomical objects today, you often start by pulling up the Legacy Imaging Viewer to see what you’re looking at.” Covering roughly 75% of the sky in visible and near-infrared light, the updated map provides a deep view of the extragalactic universe not blocked by the dust and stars of our own Milky Way. Researchers expect it will remain the most comprehensive 2D map of our universe for years to come. More than 160 scientists contributed to data collection for the project, and a team of 20 produced the final dataset released today. It was built by combining 263,407 telescope exposures from three ground-based sky surveys: the Dark Energy Camera Legacy Survey (DECaLS) at NSF Cerro Tololo Inter-American Observatory, the Mayall z-band Legacy Survey (MzLS) at NSF Kitt Peak National Observatory, and the Beijing-Arizona Sky Survey (BASS) at the University of Arizona’s Steward Observatory. That was supplemented by years of data from NASA’s Wide-field Infrared Survey Explorer (WISE) satellite mission and additional public data. “For our team, these data are fundamental to our investigation of the expansion history of the universe and the formation of our galaxy,” said Arjun Dey, co-lead of the Legacy Surveys and an astronomer at NSF NOIRLab. “But the skies belong to everyone, and this survey gives everyone the chance to explore the sky and marvel at its wonders.” Here be galaxies The DESI Legacy Imaging Surveys were originally conducted to prepare for the Dark Energy Spectroscopic Instrument (DESI) survey. The Legacy Surveys’ 2D map is essentially a deep photograph of the sky; it records where galaxies and stars appear and how bright they appear. This crucial step enables DESI to select objects and measure their light in different wavelengths to determine their distances, building the largest high-resolution 3D map ever made. Scientists study the way galaxies have clustered at different ages of the universe to track dark energy over time. In April 2026, DESI completed its original five-year survey ahead of schedule and with vastly more objects than expected. The early results have shown surprising hints that dark energy’s impact may be weakening over time — a paradigm shift that could potentially shape the predicted fate of our universe. DESI expects to publish improved results using their first five years of data in 2027 and is continuing observations into 2028. DESI was so efficient at observing galaxies, the Legacy Surveys map needed to expand. Early on, “it became clear we might run out of galaxies to look at and run out of sky, and we better start doing something about that,” said Schlegel, who also works on DESI. The new Legacy Surveys map has been used to select DESI targets since June 2026 and will guide the telescope’s operations over the coming years. Computing the cosmos Merging hundreds of thousands of images taken on 2,285 nights, each with unique atmospheric and telescope conditions, was a massive computational effort. It took about a year to develop the computer code and eight weeks to process all the images at the Perlmutter supercomputer at the National Energy Research Scientific Computing Center (NERSC) at Berkeley Lab. Beyond supporting DESI, the Legacy Surveys will be a foundational reference for the next generation of telescopes. As new observatories like the NSF-DOE Vera C. Rubin Observatory (jointly funded by NSF and DOE’s Office of Science) and NASA’s Nancy Grace Roman Space Telescope come online, researchers can compare their observations with one of the deepest and most comprehensive views of the sky ever assembled. The Legacy Surveys data will also help scientists train artificial intelligence tools to analyze petabytes of astronomical data and accelerate new discoveries. It will be among the datasets used in an astrophysics pilot project within the American Science Cloud, part of the DOE’s Genesis Mission. The DESI Legacy Imaging Surveys are supported by the U.S. Department of Energy’s Office of High Energy Physics; the National Energy Research Scientific Computing Center, a DOE Office of Science user facility; the U.S. National Science Foundation, Division of Astronomical Sciences; and the partner institutions. DESI is supported by the DOE Office of Science and NERSC. Additional support for DESI is provided by the NSF; the Science and Technology Facilities Council of the United Kingdom; the Gordon and Betty Moore Foundation; the Heising-Simons Foundation; the French Alternative Energies and Atomic Energy Commission (CEA); the Secretariat of Science, Humanities, Technology and Innovation (SECIHTI) of Mexico; the Ministry of Science and Innovation of Spain; and by the DESI member institutions. ### Lawrence Berkeley National Laboratory (Berkeley Lab) is committed to groundbreaking research focused on discovery science and solutions for abundant and reliable energy supplies. The lab’s expertise spans materials, chemistry, physics, biology, earth and environmental science, mathematics, and computing. Researchers from around the world rely on the lab’s world-class scientific facilities for their own pioneering research. Founded in 1931 on the belief that the biggest problems are best addressed by teams, Berkeley Lab and its scientists have been recognized with 17 Nobel Prizes. Berkeley Lab is a multiprogram national laboratory managed by the University of California for the U.S. Department of Energy’s Office of Science. DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science.

Aug 10 • 11:00 AM EDT • Science • newscenter.lbl.gov

From a provincial lab, a Korean reach for a science Nobel Prize

Junsuk Rho,'s research into metamaterials sounds like science fiction -- invisibility cloaks, teleportation. It rests on bending light at will.

Aug 3 • 10:03 AM EDT • Science • upi.com

When It Comes to Fusion, Materials Matter

Fusion at high temperatures powers the sun and, if harnessed, could provide a potential source of energy here on Earth. But controlling fusion reactions has other benefits. The process also generates subatomic particles called neutrons that are used in a range of applications spanning medicine, research, and national security. Now, scientists at the University of California, Davis (UC Davis), and the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab) have found that the materials surrounding a fusion reaction can dramatically increase how often it occurs, particularly at low energies where fusion is rare. The study was published July 18 in Nature Communications. Their approach sets up a way to study and engineer nuclear reactions within solid materials, opening a new field of “materials-driven fusion.” Instead of designing materials just to survive the harsh conditions of fusion, researchers might be able to design materials that boost the reaction in specific conditions, similar to the way catalysts speed up chemical processes. “It gives you a new knob to turn that you didn’t have before,” said Arun Persaud, head of the Fusion Science & Ion Beam Technology group in Berkeley Lab’s Accelerator Technology & Applied Physics (ATAP) Division. “If we understand this effect better, it opens the door to engineering new materials that would affect the fusion rate under certain conditions. Someday future progress might enable more compact and efficient neutron generators, which have all kinds of applications, like cargo screening, planetary science, and medical therapy and imaging.” In the experiment, researchers used two different methods to pack deuterium, a heavy form of hydrogen atoms that is often used in fusion, into thin foils of palladium and titanium. They then fired a beam of deuterium ions at the foils at different energies and measured how often fusion happened. Then they compared the rates from the different materials and methods with the “bare” fusion reaction (not in a material). The team found that fusion rates depended on how the deuterium was loaded into the metal foils. The biggest effect was at the lowest energies, below 2.5 kiloelectronvolts (keV), where theory predicts fusion rates drop off sharply. Instead, researchers found a surprising plateau: Some samples showed elevated fusion rates roughly a quintillion times higher than bare fusion reactions. (A quintillion is a 1 followed by 18 zeroes.) Researchers are not exactly sure why that’s happening, though they have some ideas and ways to test them. The electrons and defects within the material might partially shield repulsive electrostatic forces between deuterium nuclei, making it easier for them to get close together and fuse. Tuning the electronic structure, defects, and composition of materials could help make nuclear reactions happen more readily. “It comes down to better understanding the mechanism so that we can try to enhance it,” said corresponding author Jeremy Munday, a professor at UC Davis. “We’ve seen that we can increase fusion rates, but what is the limit? Can we bring it to lower temperatures or energies? There’s obviously a lot of interest and excitement about fusion, so if there’s something we can learn about the physics at these lower energy scales, maybe there’s something we can translate to other areas of nuclear science.” The team plans to explore a wider range of materials and continue probing the unexpected fusion plateau at lower energies. Their work establishes a reproducible experimental platform to study how solid materials influence nuclear reactions, creating a new area of research that links fusion science with materials science and chemistry. “The work shows conclusively that the material environment where fusion occurs at low temperatures is an active participant rather than a passive container,” said Cameron Geddes, director of ATAP. “That adds a new dimension to fusion research.” This work was funded by the U.S. Department of Energy’s Advanced Research Projects Agency-Energy (ARPA-E). ### Lawrence Berkeley National Laboratory (Berkeley Lab) is committed to groundbreaking research focused on discovery science and solutions for abundant and reliable energy supplies. The lab’s expertise spans materials, chemistry, physics, biology, earth and environmental science, mathematics, and computing. Researchers from around the world rely on the lab’s world-class scientific facilities for their own pioneering research. Founded in 1931 on the belief that the biggest problems are best addressed by teams, Berkeley Lab and its scientists have been recognized with 17 Nobel Prizes. Berkeley Lab is a multiprogram national laboratory managed by the University of California for the U.S. Department of Energy’s Office of Science. DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science.

Jul 23 • 11:00 AM EDT • Science • newscenter.lbl.gov

Susumu Tonegawa Dies at 86; Nobel Laureate Showed How Antibodies Fight Infection

The first Japanese scientist to win the Nobel Prize in Physiology or Medicine, he went on to discover how memories are stored, advancing understanding of how the brain works.

Jul 21 • 12:29 PM EDT • Science • nytimes.com

Scientists used children’s ‘silly sprinklers’ to solve a physics problem Richard Feynman could not; the reverse version spins 50 times slower

If you’ve ever watched a “silly sprinkler” in action (those bright, looping contraptions that twist and spray water in wild patterns) you’ve probably just seen them as summer fun. But a group of mathematicians have turned these backyard toys into tools for solving a famous physics puzzle that stumped even Nobel Prize–winning physicist Richard Feynman.

Jul 19 • 1:27 PM EDT • Science • timesofindia.indiatimes.com

Rudolph Marcus, Who Illuminated Electrochemical Processes, Dies at 102

He received a 1992 Nobel Prize for developing a theory that explained fundamental processes behind photosynthesis, respiration, oxidation and even how fireflies produce light.

Jul 17 • 1:51 PM EDT • Science • nytimes.com

Nobel Prize Dialogue

The 2026 Nobel Prize Dialogue in Seoul asks how AI will transform the future of science, and seeks to explore what these changes mean for our ability to develop scientific solutions to the urgent challenges we face.

Jul 13 • 6:12 AM EDT • Science • nobelprize.org

Nobel Prize winner leaving UC Berkeley for new role in China

Omar Yaghi will lead an AI institute at Tsinghua University in Beijing.

Jul 10 • 1:06 PM EDT • Science • latimes.com

Science should be developed away from being 'exclusive club' - Nobel prize winner to F24

Jul 6 • 5:44 AM EDT • Science • france24.com

KATALIN KARIKÓ

She was met with resistance, got demoted and eventually forced to leave academia – but Katalin Karikó never lost focus, doubling-down on her work to harness mRNA for new vaccines and therapies. Karikó’s Nobel Prize-awarded discovery enabled the development of effective vaccines against COVID-19, offering protection to millions of people.

Jun 29 • 7:40 AM EDT • Science • nobelprize.org

New Zealand scientists working on 'R' win major global award

Scientists working on the revolutionary 'R' programming language invented at the University of Auckland have won a top award intended to be a Nobel Prize for statisticians.

Jun 19 • 8:07 AM EDT • Science • phys.org

New MatterChat Model Helps AI to ‘See’ the Language of Science

From writing emails to generating computer code, much of the artificial intelligence prevalent in our daily lives has succeeded by mastering one domain: text. However, this leaves a major blind spot in the physical sciences, where models depend on the high-resolution, three-dimensional data of the physical world, like the intricate lattice of atoms in a crystal. Delivering on the promise of using AI for science requires teaching these data-driven text models to seamlessly “talk to” physics-based models. Now, a new AI framework from Lawrence Berkeley National Laboratory (Berkeley Lab), called MatterChat, solves this problem by creating a specialized “bridge.” It connects the conversational power of a Large Language Model (LLM) with a physics-based AI that models “interatomic potentials”: the complex physical forces between atoms. The resulting system already significantly outperforms general-purpose AI tools like GPT-4 at predicting material properties, and the team hopes it can accelerate scientific discovery by serving as a robust research partner that provides grounded insights and generates step-by-step instructions for synthesizing novel materials. A paper describing this work was recently published in Nature Machine Intelligence. “Traditional simulations can provide the physical rigor required for materials science, yet their computational cost remains prohibitive for high-throughput screening. Conversely, while LLMs excel at rapid knowledge synthesis, they inherently lack the ‘structural vision’ to interpret materials directly from their underlying atomic coordinates,” said Yingheng Tang, a postdoctoral researcher in Berkeley Lab’s Applied Math and Computational Research Division (AMCR) and lead author on the paper. “MatterChat was built to solve this dilemma, empowering LLMs with a structural ‘vision’ that allows researchers to leverage their full potential for solving complex, real-world materials challenges.” Empowering language models to solve complex challenges in materials science To build MatterChat, the Berkeley Lab team drew inspiration from technologies like Vision Question Answering (VQA) and Text-to-Image (T2I) generation. In these tasks, AI must translate high-level text concepts into visual images, or vice versa. Doing so requires developers to build tools that “bridge” two fundamentally different forms of data. The researchers adapted this concept to the physical sciences. With MatterChat, they created a “bridge model” that successfully connects an LLM’s general knowledge with the deep understanding of the atomic-scale world encoded in scientific interatomic potentials. Until now, researchers using LLMs to solve materials problems usually had to feed them raw data files as if they were just strings of text. It’s like asking an AI to understand a complex 3D engine based only on a parts list: the LLM can read the names, but it can’t “see” how the atoms fit together in space. MatterChat solves this by training a specialized AI bridge model, pre-trained on millions of crystal structures and an LLM, to align the LLM’s representation of the world with the interatomic potential’s representation of the world. The bridge model can translate physical insights into a format the LLM can actually understand. By giving the LLM these “scientific eyes”— a scientific “inductive bias” in the terminology of AI — the Berkeley Lab team has transformed it into a robust research tool capable of providing grounded scientific insights into complex materials challenges, such as predicting thermal stability or analyzing electronic band gaps. “We think of atoms as living in a physical space, but from a machine learning perspective, they are just vectors living in some very non-trivially structured manifold in a high-dimensional Euclidean space; and, of course, the same is true for the sentences and paragraphs that we use to express our ideas about those atoms,” said co-author Michael Mahoney, Berkeley Lab’s Scientific Data Division (SDD) AI Initiative Research Lead. “The bridge model basically gets those two structures to ‘talk with’ each other.” As a proof-of-concept of this general approach, the team trained their bridge model on a dataset curated by pairing nearly 143,000 stable atomic structures from the Materials Project with their corresponding physical properties. This training data was automatically assembled using the Materials Project’s API and deliberately enriched with properties fundamental to microelectronics design — like formation energy and bandgap — allowing MatterChat to learn the complex patterns connecting a material’s atomic blueprint to its functional performance. To validate their model, the researchers benchmarked MatterChat against a suite of other AI systems, from general-purpose LLMs to other specialized scientific AI methods. The results show that MatterChat consistently outperformed its competitors across a range of tasks. The model was more accurate in classifying material types and demonstrated superior precision in predicting numerical properties. For example, it excelled at predicting a material’s bandgap, a property critical for designing new electronics from high-capacity energy storage to next-generation computer chips. “Our design is significantly more efficient because we don’t have to build a massive AI model from the ground up,” said co-author Zhi (Jackie) Yao, a research scientist in Berkeley Lab’s AMCR. “Instead, we take two powerful, pre-trained models — a structural encoder for materials physics and an open-source LLM — and use them off-the-shelf. The only component we actually train is the lightweight ‘bridge model’ that translates between them. It’s the difference between building an entire car factory and simply designing a smart adapter that connects a world-class engine to a world-class navigation system. This approach is not only computationally efficient, but also makes the system modular, so we can easily upgrade components or adapt the bridge for other scientific domains in the future.” Crucially, this modular design highlights exactly how institutions like Berkeley Lab and the Department of Energy are carving out a highly valuable niche in the booming AI landscape. Rather than competing with Silicon Valley tech giants to build ever-larger language models from scratch, the lab is focusing on the specialized connective tissue that makes commercial AI useful for hardcore science. Because the bridge model approach underlying MatterChat is forward-compatible, it is perfectly positioned to leverage these parallel tracks of innovation. As Mahoney pointed out, “We expect that industry will continue to develop improved LLMs, and we expect domain scientists and facilities will continue to generate new data. An important part of scientific machine learning is not simply to solve problems on today’s data, but instead to develop general methods that will be forward-compatible with orders of magnitude more data, whether from scientific domains or from LLMs.” According to Yao, the MatterChat project, which was initially developed and enhanced with funding from a Berkeley Lab Laboratory Directed Research & Development (LDRD) Program, will now expand its capabilities. In a collaboration with Fermilab, MatterChat is already contributing to a U.S. Department of Energy Genesis Mission project — called Accelerating eXtreme Environment Specs-to-Silicon (AXESS) — that aims to speed up the development of next-generation, high-speed, radiation-hardened detectors for challenging particle physics experiments by using advanced 3D integrated circuits (chiplets) and AI-driven data analysis. In addition to the LDRD support, the team also credits supercomputing resources at the National Energy Research Scientific Computing Center (NERSC), located at Berkeley Lab, with MatterChat’s success. “We are incredibly grateful to NERSC; this research simply would not have happened without access to the Perlmutter supercomputer through their AI for Science program,” said Tang. Wenbin Xu, a NERSC postdoctoral fellow at the time, was also a major co-author of the work, as was Benjamin Erichson, a research scientist in Berkeley Lab’s SDD, highlighting the benefits of AMCR-SDD collaboration on AI for science. ### Lawrence Berkeley National Laboratory (Berkeley Lab) is committed to groundbreaking research focused on discovery science and solutions for abundant and reliable energy supplies. The lab’s expertise spans materials, chemistry, physics, biology, earth and environmental science, mathematics, and computing. Researchers from around the world rely on the lab’s world-class scientific facilities for their own pioneering research. Founded in 1931 on the belief that the biggest problems are best addressed by teams, Berkeley Lab and its scientists have been recognized with 17 Nobel Prizes. Berkeley Lab is a multiprogram national laboratory managed by the University of California for the U.S. Department of Energy’s Office of Science. DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science.

May 18 • 11:00 AM EDT • Science • newscenter.lbl.gov

Alarm grows over health of Iran’s female political prisoners

Rights activists have raised renewed concerns over the health of prominent female political prisoners after Nobel Prize laureate Narges Mohammadi was transferred to a hospital in Tehran and reports emerged of worsening conditions for jailed activist Fatemeh Sepehri.

May 10 • 7:50 PM EDT • Health • iranintl.com

Trends and challenges in higher education

Americans are both proud and critical of our higher educational system. More American universities are highly ranked than those in other countries. More international students come here than to any other country. And basic research at U.S. universities has earned more patents and Nobel Prizes than elsewhere. Yet trust in colleges and universities has dramatically declined. Costs have dramatically increased and more parents […]

May 10 • 8:00 AM EDT • Politics • coloradopolitics.com

The National Academy of Sciences Elects Two Berkeley Lab Researchers

Two Lawrence Berkeley National Laboratory (Berkeley Lab) scientists have been elected to the National Academy of Sciences (NAS) in recognition of their distinguished and continuing achievements in original research. They are part of a cohort of 120 new members and 25 international members. The National Academy of Sciences is a private, nonprofit institution that was established under a congressional charter signed by President Abraham Lincoln in 1863. It recognizes achievement in science by election to membership, and — alongside the National Academy of Engineering and the National Academy of Medicine — provides science, engineering, and health policy advice to the federal government and other organizations. The 2026 electees bring the total number of active members to 2,705 with 557 international members. Gary Karpen is a biologist senior faculty scientist in Berkeley Lab’s Biological Systems and Engineering Division and a Professor of Cell and Developmental Physiology in the Department of Molecular and Cell Biology at UC Berkeley. Karpen studies how the structure, organization, and maintenance of genetic material impact inheritance and cell function. His lab focuses on chromatin — a packaged form of DNA strands wrapped around proteins that comprises our chromosomes — with a particular emphasis on centromeres, rarely expressed sequences called heterochromatin, DNA repair, and regulatory RNAs. His research reveals insights into fundamental aspects of nuclear organization and genome regulation that are shared across the tree of life, broadening our understanding of cancer and other diseases, birth defects, and aging. Kam-Biu Luk is a Professor Emeritus of physics at UC Berkeley and a retired senior faculty scientist in Berkeley Lab’s Physics Division. He is an experimental particle physicist whose research has focused on neutrinos: nearly massless, electrically neutral elementary particles that can pass through matter virtually undetected. Neutrinos are created during radioactive decay processes, including the fusion process occurring in stars and the fission process that powers nuclear reactors. Luk initiated and co-led the Daya Bay Reactor Neutrino Experiment, a project based in China with more than 200 international collaborators. In 2012, the Daya Bay experiment discovered a new form of a phenomenon called “neutrino oscillation” in which neutrinos change from one type to another. For this discovery, Luk and his collaborator Yifan Wang received the 2014 American Physical Society Division of Particles and Fields W.K.H. Panofsky Prize for outstanding work in experimental particle physics, and he was also the co-recipient of the 2016 Breakthrough Prize. Luk is currently participating in the Deep Underground Neutrino Experiment (DUNE) hosted by Fermi National Accelerator Laboratory, which will investigate any potential difference in behavior between neutrinos and antineutrinos that may shed light on the evolution of the universe, especially why antimatter is absent in the present universe. ### Lawrence Berkeley National Laboratory (Berkeley Lab) is committed to groundbreaking research focused on discovery science and solutions for abundant and reliable energy supplies. The lab’s expertise spans materials, chemistry, physics, biology, earth and environmental science, mathematics, and computing. Researchers from around the world rely on the lab’s world-class scientific facilities for their own pioneering research. Founded in 1931 on the belief that the biggest problems are best addressed by teams, Berkeley Lab and its scientists have been recognized with 17 Nobel Prizes. Berkeley Lab is a multiprogram national laboratory managed by the University of California for the U.S. Department of Energy’s Office of Science. DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science.

May 7 • 11:00 AM EDT • Science • newscenter.lbl.gov

Great Women of Science Go Missing: The Matilda Effect

It’s now been two years since Great Women of Science debuted, featuring women who have made notable contributions to science, technology, or health and have largely gone unnoticed, often with Nobel prizes they deserved awarded to the men with whom they collaborated. There’s a name for this phenomenon - it’s called “the Matilda Effect.”

Apr 20 • 12:00 AM EDT • Science • acsh.org

Computer science was once a 'golden ticket' — now it's seeing the biggest enrollment drop of any major in 6 years

Nobel Prize–winning economist Simon Johnson said AI has "substantially wiped out" coding as a reliable source of opportunity.

Apr 19 • 10:05 AM EDT • Science • finance.yahoo.com

'The chances of you living 50 years are very small': Theoretical physicist explains why humanity likely won't survive to see all the forces unified

Live Science spoke with Nobel prize-winning physicist David Gross, who recently received the $3 million Special Breakthrough Prize in Fundamental Physics, about the quest to unite all the forces and why humanity might not live to see a unified theory.

Apr 19 • 10:00 AM EDT • Science • livescience.com

Computer science was once a 'golden ticket' — now it's seeing the biggest enrollment drop of any major in 6 years. What students are choosing instead

Nobel Prize–winning economist Simon Johnson said AI has "substantially wiped out" coding as a reliable source of opportunity.

Apr 19 • 8:00 AM EDT • Science • moneywise.com

Marc Abrahams, founder of the satirical Ig Nobel Prizes: ‘Scientists in the US are very angry. People are waking up’

The awards are moving to Switzerland, because their founder believes he can no longer guarantee the laureates’ safety in the United States

Mar 22 • 12:00 AM EDT • Science • english.elpais.com

Seattle’s biotech scene is world-class — Life Science Washington is teaching it how to brag

Despite world-class AI-biotech research, a Nobel Prize-winning protein design lab and proximity to global AI expertise, Washington's life sciences sector is still learning to tell its story.

Mar 20 • 12:49 PM EDT • Science • geekwire.com

Ig Nobel: Inside the World of Science That Makes People Laugh

Through the lens of Ig Nobel prizes, Upasana Sarraju investigates why society elevates some scientific questions while sidelining others in a new book.

Mar 6 • 12:35 AM EST • Science • the-scientist.com

For the first time, light mimics a Nobel Prize quantum effect

Scientists have pulled off a feat long considered out of reach: getting light to mimic the famous quantum Hall effect. In their experiment, photons drift sideways in perfectly defined, quantized steps—just like electrons do in powerful magnetic fields. Because these steps depend only on nature’s fundamental constants, they could become a new gold standard for ultra-precise measurements. The discovery also hints at tougher, more reliable quantum photonic technologies.

Mar 1 • 7:00 AM EST • Science • sciencedaily.com

Five Berkeley Lab Scientists Receive DOE Early Career Research Awards

Five scientists from Lawrence Berkeley National Laboratory (Berkeley Lab) have received Early Career Research Program (ECRP) awards from the Department of Energy. The ECRP program, now in its 16th year, was established to bolster the nation’s scientific workforce by supporting exceptional researchers at the outset of their careers, when many scientists do their most formative work. Recipients use the funding to pursue projects that have the potential to solve scientific challenges and advance the country’s STEM capabilities. To be eligible for the program, a researcher must be an untenured, tenure-track assistant or associate professor at a U.S. academic institution, or a full-time employee at a DOE national laboratory or Office of Science user facility, who is within 10 years of having earned their doctorate. Awards to an institution of higher education will be approximately $875,000 over five years, and awards to a DOE national laboratory or Office of Science user facility will be approximately $2,750,000 over five years. This year’s Berkeley Lab awardees and their projects are listed below: Timon Heim: Better detectors for more powerful particle colliders Timon Heim is a staff scientist in the Physics Division. His ECRP project will develop a new type of detector that can track the particles generated by collisions in particle colliders with high spatial and temporal resolution. Current detectors in use at high-energy colliders, like the ATLAS detector at the Large Hadron Collider (LHC) at CERN, can track the trajectory and measure momentum of particles, but they can’t track a particle’s time of arrival with sufficient precision to discern from which of the many particle interactions they originate. Heim’s proposed technology — called a 4D tracking detector, because it captures data about particles’ positions in space and time — aims to solve this challenge, allowing researchers to glean more precise data from collision experiments to uncover new insights into fundamental forces and potentially discover new particles. The enhanced capabilities of 4D detectors will be a necessity for experiments at future colliders, such as the Muon Collider or Future Circular Collider. The project will develop custom microelectronics that process the signal of a pixelated silicon sensor that can register charged particles passing through it in an extreme radiation environment that these colliders produce during operation. The goal is to measure individual particles’ position with 50-micro-meter spatial and 50 pico-second (one trillionth of a second) temporal precision, for an incoming flux of around 1 billion particles per second per square centimeter. Harrison Lisabeth: Studying underground processes to unleash abundant energy Harrison Lisabeth is a research scientist in the Energy Geoscience Division focused on combining real-world experiments and AI to guide development of geothermal energy systems. His project will explore how deep underground rock formations – where geothermal wells are dug – are stressed by chemical reactions of the minerals and mechanical strain from movements in the Earth. A better understanding of subsurface stresses is essential to engineer safe and reliable geothermal wells that access the heat of deep rocks to produce electricity. It is estimated that the U.S. could generate ten times the amount of energy needed to power the grid using geothermal sources. Lisabeth plans to simulate how minerals grow, dissolve, and influence the behavior of surrounding rock in geothermal reservoirs by tracking chemical changes in rock samples under pressure in the lab. The project will also develop machine learning models to predict geologic strain based on field measurements and refine existing models that describe how common rock types deform under stress. Combining these approaches, Lisabeth hopes to develop a framework to predict stress to improve stability and longevity of geothermal wells. Daniel Carney: Pushing the quantum boundaries of particle measurement Daniel Carney is a staff scientist in the Physics Division who uses quantum information science to study particle physics and gravity. At very small scales, “quantum noise” — random fluctuations from the act of measurement — can drown out faint signals from rare processes. Carney’s ECRP project, “Fundamental Physics at the Quantum Limits of Measurement,” aims to build a new mechanical quantum sensor that can measure extremely small particle interactions below the limits of that quantum noise. The approach uses lasers to hold a tiny bead containing radioactive atoms; when one decays, the system measures the bead’s motion and the energy of any particles emitted. The experiment’s initial goal is to search for heavy sterile neutrinos, hypothetical particles predicted by some extensions of the Standard Model. The system could also help measure the mass of the neutrino, study the way particles interact through the electromagnetic and weak forces, and hunt for low-mass dark matter — all unsolved mysteries in particle physics. Callum Wilkinson: Using machine learning to demystify neutrinos Callum Wilkinson is a staff scientist in the Physics Division and part of the international Deep Underground Neutrino Experiment (DUNE) hosted by Fermi National Accelerator Laboratory. DUNE will create an intense beam of neutrinos that interact in detectors in Illinois and, after an 800-mile journey through the earth, in massive detectors in South Dakota. By precisely measuring neutrinos and how they change, researchers will get a better understanding of their fundamental properties and whether they are responsible for why there is so much more matter than antimatter in our universe. Wilkinson’s ECRP project will apply two machine learning techniques to improve the analysis of DUNE’s data and enhance the experiment’s precision. One approach will look for hidden patterns in how neutrinos interact and produce low-energy particles, while the other will help correct for distortions in what the detectors record. The methods will be tested on one of DUNE’s prototype detectors and could be used in other neutrino experiments, improving their measurements and helping scientists build better models. Aditi Krishnapriyan: Machine learning methods that scale as datasets grow Aditi Krishnapriyan is a faculty scientist in Berkeley Lab’s Applied Mathematics and Computational Research Division (AMCR) and assistant professor at UC Berkeley. Her project, awarded through UC Berkeley, will develop machine learning methods that scale with dataset size for modeling complex, multi-scale phenomena. The resulting tools can be applied in a wide range of research, including the study of new electrolytes for batteries or the examination of molecular interactions. ### Lawrence Berkeley National Laboratory (Berkeley Lab) is committed to groundbreaking research focused on discovery science and solutions for abundant and reliable energy supplies. The lab’s expertise spans materials, chemistry, physics, biology, earth and environmental science, mathematics, and computing. Researchers from around the world rely on the lab’s world-class scientific facilities for their own pioneering research. Founded in 1931 on the belief that the biggest problems are best addressed by teams, Berkeley Lab and its scientists have been recognized with 17 Nobel Prizes. Berkeley Lab is a multiprogram national laboratory managed by the University of California for the U.S. Department of Energy’s Office of Science. DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science.

Feb 18 • 11:00 AM EST • Science • newscenter.lbl.gov

Alarm as US mulls prioritising citizens in research funding

A senior White House official said the Trump administration is considering ways to prioritise research funding to American citizens, triggering alarm in the research community that the country could destroy its century-long status as a magnet for overseas talent.Michael Kratsios, director of the White House Office of Science and Technology Policy (OSTP), said last week that it is “important for us to continue to emphasise the use of federal R&D dollars towards American scientists and technologists that are staffed by Americans in their labs.” Asked about support for Chinese students during a Congressional hearing, Kratsios went on to say that in future funding announcements, the OSTP would “emphasise” that “we're funding American students.”The precise meaning of his impromptu comments, and what they could mean in policy terms, isn’t yet clear. The OSTP did not respond to multiple requests for clarification from Science|Business.But given that US science and technology has relied on overseas talent for the past century, Kratsios’s words have alarmed former US science officials.Immigrants have made up around 30-40% of US Nobel Prize winners since the 1940s, for example. Except for some sensitive projects, countries typically grant research funding on a nationality-blind basis, lest they deter foreign scientists from immigrating. “If director Kratsios’s statements are taken literally and become official policy of the White House, [research-intensive] universities will likely have to close labs if not entire research divisions,” said David Biggs, a former science and technology official in the US State Department. In their most extreme interpretation, Kratsios’s comments would imply that foreign scientists established in the US would see access to funding curtailed. This would “result in many world-leading professors who work in the United States in fields that this administration considers a priority (like fusion energy, artificial intelligence, and quantum computing) leaving the country,” said Cole Donovan, a former US science diplomat, and now associate director at the Federation of American Scientists.CripplingHowever, given the context of the conversation, Kratsios may have been referring more narrowly to funding for doctoral or postdoctoral students. At the hearing, he said he wanted to see labs staffed by US citizens. But even this would have devastating consequences for the US science system, say former officials, because the country is so dependent on early-career foreign researchers. Recent statistics show that nearly half of those in the US with a PhD in science, technology, engineering or mathematics (STEM) are considered short-term visitors, or non-residents in the official terminology. If this included residents who are not yet citizens, the proportion would likely be even higher. “Foreign PhD students are really a significant and core part of the university STEM workforce, and postdocs is similarly large,” said Donovan. Preventing US-based academics from hiring them from overseas would be a serious blow, he said. “If it's the case that this administration intends to limit funding to labs staffed only with US citizens, the effect will be to cripple the American scientific enterprise,” said Chris Marcum, a former OSTP official. “To think that these researchers can simply be replaced is a pipe dream. The labs will close,” said Marcum. Go elsewhereAround half of US-trained postdocs are foreign-born, said Biggs. “If these top international students cannot get funding to do their research, or even if they hear that funding for foreign students has been greatly restricted and will be super competitive, they will no longer choose to study in the US and will go elsewhere.” It’s unclear for now if Kratsios’s comments will translate into a real policy shift. But they could add to turmoil in the US science system since Donald Trump took over as president one year ago. Related articlesNIH turmoil risks reciprocal EU-US access to health research fundingUS set to close office responsible for global science and technology dealsTrump halts new NIH grants to international health-research partnersSince then, nearly 8,000 grants at the National Institutes of Health and National Science Foundation have been frozen or terminated, Naturereports. Courts have overturned most of these cancellations, but the disruption caused remains significant. Both those agencies have also dished out around a quarter fewer grants this year than normal, the journal reported. International student enrolment is also down by 17%. The Trump administration also proposes to cut research budgets by around a third, although Congress may mollify the cuts.

Jan 22 • 7:00 AM EST • Science • sciencebusiness.net

Alarm over US plan to prioritise citizens in research funding

The US’s leading science official has said the country will focus its research spending on scientists with US citizenship, triggering alarm that the country could destroy its century-long status as a magnet for overseas talent.Michael Kratsios, director of the White House Office of Science and Technology Policy (OSTP), said last week that it is “important for us to continue to emphasise the use of federal R&D dollars towards American scientists and technologists that are staffed by Americans in their labs.” Asked about support for Chinese students during a Congressional hearing, Kratsios went on to say that in future funding announcements, the OSTP would “emphasise” that “we're funding American students.”Kratsios’s precise meaning, and what it could mean in policy terms, isn’t yet clear. The OSTP did not respond to multiple requests for clarification from Science|Business.But given that US science and technology has relied on overseas talent for the past century, Kratsios’s words have stunned former US science officials.Immigrants have made up around 30-40% of US Nobel Prize winners since the 1940s, for example. Except for some sensitive projects, countries typically grant research funding on a nationality-blind basis, lest they deter foreign scientists from immigrating. “If director Kratsios’s statements are taken literally and become official policy of the White House, [research-intensive] universities will likely have to close labs if not entire research divisions,” said David Biggs, a former science and technology official in the US State Department. In their most extreme interpretation, Kratsios’s comments would imply that foreign scientists established in the US would see access to funding curtailed. This would “result in many world-leading professors who work in the United States in fields that this administration considers a priority (like fusion energy, artificial intelligence, and quantum computing) leaving the country,” said Cole Donovan, a former US science diplomat, and now associate director at the Federation of American Scientists.CripplingHowever, given the context of the conversation, Kratsios may have been referring more narrowly to funding for doctoral or postdoctoral students. At the hearing, he said he wanted to see labs staffed by US citizens. But even this would have devastating consequences for the US science system, say former officials, because the country is so dependent on early-career foreign researchers. Recent statistics show that nearly half of those in the US with a PhD in science, technology, engineering or mathematics (STEM) are considered short-term visitors, or non-residents in the official terminology. If this included residents who are not yet citizens, the proportion would likely be even higher. “Foreign PhD students are really a significant and core part of the university STEM workforce, and postdocs is similarly large,” said Donovan. Preventing US-based academics from hiring them from overseas would be a serious blow, he said. “If it's the case that this administration intends to limit funding to labs staffed only with US citizens, the effect will be to cripple the American scientific enterprise,” said Chris Marcum, a former OSTP official. “To think that these researchers can simply be replaced is a pipe dream. The labs will close,” said Marcum. Go elsewhereAround half of US-trained postdocs are foreign-born, said Biggs. “If these top international students cannot get funding to do their research, or even if they hear that funding for foreign students has been greatly restricted and will be super competitive, they will no longer choose to study in the US and will go elsewhere.” It’s unclear for now if Kratsios’s comments will translate into a real policy shift. But they could add to turmoil in the US science system since Donald Trump took over as president one year ago. Since then, nearly 8,000 grants at the National Institutes of Health and National Science Foundation have been frozen or terminated, Naturereports. Courts have overturned most of these cancellations, but the disruption caused remains significant. Both those agencies have also dished out around a quarter fewer grants this year than normal, the journal reported. International student enrolment is also down by 17%. The Trump administration also proposes to cut research budgets by around a third, although Congress may mollify the cuts.

Jan 22 • 7:00 AM EST • Science • sciencebusiness.net

Trump Has Machado’s Nobel Prize, but Neither Got What They Really Wanted

President Trump has María Corina Machado’s medal, but he is not recognized as the prize laureate. Ms. Machado did not win Mr. Trump’s endorsement to become Venezuela’s president.

Jan 16 • 6:58 PM EST • Politics • nytimes.com

Trump will keep Machado's 2025 Nobel Peace Prize

The Nobel Committee released a statement saying “A Nobel Prize can neither be revoked, shared, nor transferred to others."

Jan 16 • 12:27 PM EST • Politics • usatoday.com

The inventor of the CMOS camera sensor just won the "Nobel Prize of Engineering"

The godfather of the active-pixel CMOS sensor, Eric R Fossum, PhD, has been awarded the 2026 Charles Stark Draper Prize for Engineering

Jan 15 • 1:41 PM EST • Technology • digitalcameraworld.com

‘Lots of people don’t want to do it’: Paul Nurse on his controversial second term as Royal Society president

The Nobel prize winner discusses claims of a ‘boys’ club’, Elon Musk’s fellowship and rightwing attacks on science

Jan 11 • 6:00 AM EST • Science • theguardian.com

Celebrating worm science

MIT-affiliated biologists including Robert Horvitz discuss the history of Nobel Prize-winning advances made through scientific research in the microscopic roundworm C. elegans.

Jan 7 • 4:40 PM EST • Science • news.mit.edu

A former Trump economic advisor explains why tariffs still worry him heading into 2026

Stephen Moore, the former White House economist who once called for President Trump to receive a Nobel prize, has changed his tune a bit.

Dec 30, 2025 • 11:29 AM EST • Business • businessinsider.com

AlphaFold Changed Science. After 5 Years, It’s Still Evolving

WIRED spoke with DeepMind’s Pushmeet Kohli about the recent past—and promising future—of the Nobel Prize-winning research project that changed biology and chemistry forever.

Dec 24, 2025 • 5:00 AM EST • Technology • wired.com

AlphaFold Changed Science. After 5 Years, It’s Still Evolving

WIRED spoke with DeepMind’s Pushmeet Kohli about the recent past—and promising future—of the Nobel Prize-winning research project that changed biology and chemistry forever.

Dec 24, 2025 • 5:00 AM EST • Science • wired.com

The disunity of science is a feature, not a bug

Mathematical models wield miraculous power, but mistaking them for reality has trapped science in a destructive quest for a “Theory of Everything.” Physicist and philosopher Ragner Fjelland argues that this leads to bloated, Frankenstein theories kept alive by clumsy, ad-hoc amendments, which reduce rather than boost science’s power. Fjelland calls for a radical shift in our attitude: we must reorientate towards creating entirely new theories, celebrating rather than lamenting disunity and diversity in science. Science, from the scientific revolution in the seventeenth century to the present day, has more or less developed in a “reductionist” way. The fundamental assumption is that all sciences may be ordered in a hierarchy that can be represented as an upside-down pyramid. At the top we find the human sciences, and at the bottom physics. Strong (or “ontological”) reductionism maintains that all theories at one level can be completely reduced to the lower level, all the way down to theories of atoms and elementary particles, or whatever is “at the bottom.” In the end, all diversity in the world can be unified in one fundamental theory. Hence it is called a final theory, or a Theory of Everything.One of the central figures in developing the idea of a Theory of Everything is the Dutch theoretical physicist Gerard 't Hooft, who received a Nobel Prize in physics in 1999 for his work. He emphasizes the non-empirical status of the theory:There exists no closely resembling alternative theory. This means that any slight change brought about in the rules would make the theory unlikely or inelegant. The theory will be a "package deal": take it, or leave it. This should hold both for the local laws and for the boundary conditions.This endeavor is not new. On the contrary, it goes all the way back to the birth of Western philosophy 2,500 years ago. The Babylonians made regular astronomical observations during a period of 600 years, from 747 BCE until 150 ACE. They developed mathematical techniques to predict astronomical phenomena, but they made no attempts at explaining them. However, the Greeks developed models, both material and theoretical, to explain the observed phenomena.The best example is Plato’s late dialogue Timaeus. Here he introduces a divine craftsman, the Demiurge, who has constructed the universe according to an original plan. Plato seems to have thought that the original plan is what is actually real, while the material world is merely an imperfect realization of it. He therefore does not, in the Timaeus, reconstruct the material universe, but the original plan, which can then be used to explain the material universe.Plato’s aim in producing a theoretical model is to reconstruct the original plan. That is what he carries out in Timaeus—and some modern physicists have embarked on the same project. For example, Einstein’s basic attitude is reflected in the title of Abraham Pais’ biography: “Subtle is the Lord...,” echoing Einstein’s comment, “Subtle is the Lord, but malicious He is not.” In an interview Einstein compared our situation to a child who enters a huge library. The child knows that someone has written the books, but he does not know the languages in which they are written. He suspects that there is a mysterious order, but he does not know what it is.___“We have all been working in what Husserl called the Galilean style; that is, we have all been making abstract mathematical models of the universe to which at least the physicists give a higher degree of reality than they accord the ordinary world of sensation.”Steven Weinberg, Nobel Prize in Physics (1979)___This Platonist view is contrary to a widespread impression of science, symbolized by the picture of the “father” of modern science, Galileo Galilei, with his telescope. According to this impression, Galileo liberated himself from the dominating metaphysics of his day—basically Aristotelian philosophy—and constructed a telescope that he directed towards the sky, showing that Jupiter has four moons. He also performed experiments with bronze balls rolling down inclined planes and found the law of freely falling bodies.However, in other cases Galileo emphasized the unreliability of our senses. It is easy to see why. He defended Copernicus’ heliocentric hypothesis. According to this hypothesis, we are not at rest at the center of the universe, but moving at a tremendous speed through space. Why don’t we observe this motion? Galileo praises Copernicus because “with reason as his guide he resolutely continued to affirm what sensible experience seemed to contradict.” In other places he directly refers to Plato. SUGGESTED VIEWING The quest for a final theory With Michio Kaku Galileo’s Platonism goes back to his early writings. In The Assayer, published as early as 1623, Galileo compared the universe to a grand book that is written in the language of mathematics, and “its characters are triangles, circles, and other geometric figures without which it is humanly impossible to understand a single word of it.” Therefore, things that cannot be described by mathematics—for example, colors, smells and odors—are not real. They are merely subjective.This division into subjective and objective, advocated by Galileo and his younger contemporary René Descartes, is normally associated with a mechanistic world view, which is regarded as the opposite of Platonism. When we reduce something to, for example, molecules and atoms, we move “downwards.” In contrast, the Platonist moves “upwards,” to abstract entities. However, it only shows that when we address fundamental questions, we should be careful in applying everyday spatial metaphors like “up” and “down.”___Nature is complex, and we cannot in general construct mathematical models that adequately describe the world.___The endeavor of finding a Theory of Everything has been heavily criticized. In 2006, the theoretical physicist Lee Smolin published “The Crisis in Fundamental Physics.” He argued that one of the most fundamental principles of science is that we should only regard theories as scientific if we have the possibility to show that they are false by experiments. Although he did not refer to Karl Popper, other critics have referred to Popper and argued that a theory is not scientific if it cannot be falsified (see for example Ellis & Silk 2014).These were not the first physicists to be anti-reductionists. In 1972, the journal Science published an article by the physicist Philip Anderson with the title “More Is Different.” This is the kind of article a scientist would normally write only after he has won a Nobel Prize. However, Anderson won the Nobel Prize for physics five years later, in 1977. The article is amazing, not primarily because it argues in favor of anti-reductionism in general, but because it argues for anti-reductionism within physics itself. Anderson’s conclusion was:At each stage entirely new laws, concepts, and generalizations are necessary, requiring inspiration and creativity to just as great a degree as in the previous one. Psychology is not applied biology, nor is biology applied chemistry.We may say that Plato started the “unity of science movement,” based on Euclidean geometry as the model of all knowledge. A distinguishing mark of geometry is that all possible constructions can be reduced to a few fundamental principles. We have to acknowledge that this approach has limitations. In general, we can easily model technological systems. In addition, we may construct simplified and idealized models that capture important aspects of systems, from various perspectives and for various purposes. But nature is complex, and we cannot in general construct mathematical models that adequately describe the world. In a complex system, each level has its distinct, emergent, properties that are characteristic of this level. Therefore, a complex system should be investigated at different levels and from different perspectives. Instead of exclusively pursuing a scientific ideal based on the unity of science, we should acknowledge the diversity—or even the disunity—of science.

Dec 23, 2025 • 7:00 AM EST • Science • iai.tv

Laughing about science more important than ever: Ig Nobel founder

With science increasingly coming under attack, using humor as a way to get people interested in scientific research is more important than ever, the founder of the satirical Ig Nobel prizes said.

Dec 12, 2025 • 4:30 AM EST • Science • phys.org

Trump Administration Rules Threaten Nobel Prizes Won by Immigrants

As three immigrants claim Nobel Prizes in science for the United States this year, experts warn that immigration crackdowns could undo American innovation.

Dec 10, 2025 • 5:03 AM EST • Science • nytimes.com

'Godfather of AI' Geoffrey Hinton says computer science degrees 'will remain valuable' — and students should learn to code

AI pioneer and Nobel Prize winner Geoffrey Hinton said students who want to become AI researchers need to focus on critical thinking.

Dec 7, 2025 • 5:00 AM EST • Science • businessinsider.com