Gerd Faltings has been awarded the prestigious 2026 Abel Prize, often regarded as the “Nobel Prize of Mathematics,” in recognition of his revolutionary proof that reshaped mathematics in 1983. His seminal work laid the foundation for arithmetic geometry, a crucial domain in contemporary mathematics.
Faltings’ landmark achievement was his proof of the Mordell Conjecture, for which he was honored with the Fields Medal in 1986. This theorem, initially proposed by Louis Mordell in 1922, asserts that complex equations yield fewer solutions as their complexity increases.
Based at the Max Planck Institute for Mathematics in Germany, Faltings expressed his honor upon receiving the award, maintaining a modest view of his contributions. “Someone remarked that climbing Mount Everest was a challenge merely because the mountain exists,” Faltings stated. “While solving the Mordell Conjecture is a significant achievement, it doesn’t lead to cures for cancer or Alzheimer’s; it merely expands our understanding.”
The Mordell Conjecture pertains to Diophantine equations—an extensive category encompassing renowned equations like a² + b² = c², associated with the Pythagorean theorem, and aⁿ + bⁿ = cⁿ, pivotal to Fermat’s Last Theorem. The conjecture investigates which of these equations have infinitely many solutions and which possess only finite solutions.
Mordell suggested that by rewriting these equations as complex numbers, essentially two-dimensional numbers plotted on surfaces, the number of solutions is influenced by the number of “holes” in those surfaces. He postulated that surfaces with more holes than a donut could only possess a finite number of rational solutions but lacked proof for this hypothesis.
Faltings’ validation of Mordell’s intuition over six decades later astonished the mathematical community—not only for its findings but also for the innovative methods employed. His proofs harmonized concepts from distinct mathematical realms, including geometry and arithmetic. “It’s remarkably concise, almost miraculous,” states Akshay Venkatesh from the Institute for Advanced Study in Princeton. “Spanning just 18 pages, it intricately navigates various techniques and perspectives.”
Faltings attributes his success to his ability to embrace uncertainty and take bold risks based on unverified hunches. “Sometimes, you’re ahead of those who attempt to prove everything immediately, yet you may also err,” he observes.
“One remarkable aspect of his argument is its extensive coverage and coherence,” Venkatesh notes. “One wonders how he could trust the interconnection of these pieces before knowing how they would align.”
Many conjectures that Faltings resolved, along with the methodologies he pioneered, now underpin the most significant areas of mathematical research. For instance, p-adic Hodge theory explores the relationships between the geometry of shapes and their underlying structure while utilizing an entirely different number system. His work paved the way for Andrew Wiles’ proof of Fermat’s Last Theorem and mentored Shinichi Mochizuki, the prominent mathematician credited with resolving the ABC conjecture.
Faltings admits that his aim was never to tackle phenomena with such monumental implications. “My philosophy is that you shouldn’t pursue fame or wealth, but rather pursue what you love,” he concludes. “It’s far more enjoyable to work in a field that you are passionate about.”
John Martinis is a leading expert in quantum hardware, who emphasizes hands-on physics rather than abstract theories. His pivotal role in quantum computing history makes him indispensable to my book on the subject. As a visionary, he is focused on the next groundbreaking advancements in the field.
Martinis’s journey began in the 1980s with experiments that pushed the limits of quantum effects, earning him a Nobel Prize last year. During his graduate studies at the University of California, Berkeley, he tackled the question of whether quantum mechanics could apply to larger scales, beyond elementary particles.
Collaborating with colleagues, Martinis developed circuits combining superconductors and insulators, demonstrating that multiple charged particles could behave like a single quantum entity. This discovery initiated the macroscopic quantum regime, forming the backbone of modern quantum computers developed by giants like IBM and Google. His work led to the adoption of superconducting qubits, the most common quantum bits in use today.
Martinis made headlines again when he spearheaded a team at Google that built the first quantum computer to achieve quantum supremacy. For nearly five years, this machine could independently verify the outputs of random quantum circuits, though it was eventually surpassed by classical computers in performance.
Approaching seven decades of age, Martinis still believes in the potential of superconducting qubits. In 2024, he co-founded QoLab, a quantum computing startup proposing revolutionary methodologies aimed at developing a genuinely practical quantum computer.
Carmela Padavich Callahan: Early in your career, you fundamentally impacted the field. When did you realize your experiments could lead to technological advancements?
John Martinis: I questioned whether macroscopic variables could bypass quantum mechanics, and as a novice in the field, I felt it was essential to test this assumption. A fundamental quantum mechanics experiment intrigued me, even though it initially seemed daunting.
Our first attempt was a simple and rapid experiment using contemporary technology. The outcome was a failure, but I quickly pivoted. Learning about microwave engineering, we tackled numerous technical challenges before achieving subsequent successes.
Over the next decade, our work on quantum devices laid a solid foundation for quantum computing theory, including the breakthrough Scholl algorithm for factorizing large numbers, essential for cryptography.
How has funding influenced research and the evolution of technology?
Since the 1980s, the landscape has transformed dramatically. Initially, there was uncertainty about manipulating single quantum systems, but quantum computing has since blossomed into a vast field. It’s gratifying to see so many physicists employed to unravel the complexities of superconducting quantum systems.
Your involvement during quantum computing’s infancy gives you a unique perspective on its trajectory. How does that inform your current work?
Having long experience in the field, I possess a deep understanding of the fundamentals. My team at UC Santa Barbara developed early microwave electronics, and I later contributed to foundational cooling technology at Google for superconducting quantum computers. I appreciate both the challenges and opportunities in scaling these complex systems.
Cryostat for Quantum Computers
Mattia Balsamini/Contrasto/Eyeline
What changes do you believe are necessary for quantum computers to become practical? What breakthroughs do you foresee on the horizon?
After my tenure at Google, I reevaluated the core principles behind quantum computing systems, leading to the founding of QoLab, which introduces significant changes in qubit design and assembly, particularly regarding wiring.
We recognized that making quantum technology more reliable and cost-effective requires a fresh perspective on the construction of quantum computers. Despite facing skepticism, my extensive experience in physics affirms that our approach is on the right track.
It’s often stated that achieving a truly functional, error-free quantum computer requires millions of qubits. How do you envision reaching that goal?
The most significant advancements will arise from innovations in manufacturing, particularly in quantum chip fabrication, which is currently outdated. Many leading companies still use techniques reminiscent of the mid-20th century, which is puzzling.
Our mission is to revolutionize the construction of these devices. We aim to minimize the chaotic interconnections typically associated with superconducting quantum computers, focusing on integrating everything into a single chip architecture.
Do you foresee a clear leader in the quest for practical quantum computing in the next five years?
Given the diverse approaches to building quantum computers, each with its engineering hurdles, fostering various strategies is valuable for promoting innovation. However, many projects do not fully contemplate the practical challenges of scaling and cost control.
At QoLab, we adopt a collaborative business model, leveraging partnerships with hardware companies to enhance our manufacturing capabilities.
If a large-scale, error-free quantum computer were available tomorrow, what would your first experiment be?
I am keen to apply quantum computing solutions to challenges in quantum chemistry and materials science. Recent research highlights the potential for using quantum computers to optimize nuclear magnetic resonance (NMR) experiments, as classical supercomputers struggle with such complex quantum issues.
While others may explore optimization or quantum AI applications, my focus centers on well-defined problems in materials science, where we can craft concrete solutions with quantum technologies.
Why have mathematically predicted quantum applications not materialized yet?
While theoretical explorations in qubit behavior are promising, real-life qubits face significant noise challenges, making practical implementations far more complex. Theoretical initiatives comprehensively grasp theory but often overlook the intricacies of hardware development.
Through my training with John Clark, I cultivated a strong focus on noise reduction in qubits, which has proven beneficial in experiments showcasing quantum supremacy. Addressing these challenges requires dedication to understanding qubit design intricacies.
As we pursue advancements, a dual emphasis on hardware improvements and application innovation remains crucial in the journey to unlock quantum computing’s full potential.
Image Credit: Christopher Michel/Contour RA by Getty Images
Civilizations often define their eras by significant materials. We speak of the Stone Age and the Bronze Age, and currently, we reside in the Silicon Age—marked by the prevalence of computers and mobile devices. What might the next defining era be? Omar Yagi from the University of California, Berkeley, posits that the innovative material he pioneered in the 1990s has promising potential: Metal-Organic Frameworks (MOFs). His groundbreaking work in this area made him a co-recipient of the 2025 Nobel Prize in Chemistry.
MOFs, along with their covalent organic frameworks (COFs) counterparts, are crystalline in structure and notable for their exceptional porosity. In 1999, Yagi and his team achieved a milestone by synthesizing a zinc-based structure known as MOF-5. This material is characterized by its numerous pores, boasting an internal surface area equivalent to that of a football field within merely a few grams (refer to the image below). Internally, the structure offers vastly more space than externally.
Over the years, Yagi has been a pioneer in the development of new MOFs and COFs, a field called reticular chemistry. Understanding how these materials can be utilized is a focal point of his research. Their porous nature allows them to absorb other molecules, making them invaluable for applications such as moisture extraction from arid desert air and atmospheric carbon dioxide capture. In an interview with New Scientist, Yagi expressed optimism about this research, discussing the past, present, and future of reticular chemistry and the impending era of these materials.
Karmela Padavic-Callaghan: What inspired your interest in reticular chemistry?
Omar Yagi: Initially, when we began our work with MOFs, we had no concept that we were addressing social issues; it was purely an intellectual pursuit. We aimed to construct materials molecule by molecule, akin to building a structure or programming using Legos. It was a formidable challenge in chemistry. Many doubted its feasibility and considered our efforts futile.
What made the design of materials seem unfeasible?
The primary hurdle in rationalizing material construction lies in the nature of component mixing, which typically results in disordered, complex arrangements. This aligns with physical laws, as nature tends to favor high entropy or disorder. Therefore, our goal was to engineer a crystal—an ordered entity with a recurring pattern.
It’s akin to instructing your children to form a perfect circle in their room—it demands significant effort. Even upon achieving that circle, if you release your hold, it may take too long to re-establish it. We were essentially attempting to crystallize materials in a day—what nature takes billions of years to accomplish. Nonetheless, I believed that with the right knowledge, anything could be crystallized.
In 1999, your intuition was validated with the publication:Synthesis of MOF-5. Did you foresee its potential utility?
We identified a valuable solvent for synthesizing stable MOFs and understanding its mechanism. This critical insight allows us to minimize disorder, effectively tuning the outcome. Subsequently, thousands of researchers have adopted this method.
Initially, I was just elated to create beautiful crystals. Observing their remarkable properties prompted thoughts of potential applications, particularly in trapping gases. Given their internal compartments, these substances can accommodate water, carbon dioxide, or other molecules.
What’s your perspective on creating these materials today?
I usually avoid elaborate cooking and prefer simple, healthy ingredients. This mindset parallels my approach to chemistry: striving for simplicity while utilizing only necessary chemicals. The first step involves selecting the backbone of material; the second, defining pore sizes; the third, administering chemistry on the backbone to incorporate trapping molecules. This process, while appearing simple, is intricately complex.
What pioneering technologies does this process enable?
By mastering molecular-level design, we foresee significant geological transformations. My vision, along with my company founded in 2020, Atco, encompasses progressing from molecules to practical societal applications—addressing material deficiencies in various tasks or enhancing poorly performed tasks with rational designs. Our advancements in material synthesis will elevate societal standards.
Recently, we unveiled COF-999, the most efficient material for capturing carbon dioxide. Undertaking extensive capture tests, we demonstrated its efficacy in collecting CO2 from the atmosphere for over 100 cycles here in Berkeley. Atoco aims to implement reticulated materials like COF-999 in carbon capture modules suitable for both industrial settings and residential buildings.
Additionally, we’ve devised a novel material capable of extracting thousands of liters of water daily from the atmosphere. This technology relies on our device which can pull moisture even in humidities below 20%, such as in desert locations like Nevada. I foresee that within the next decade, water harvesting will emerge as an everyday technology.
MOFs exhibit a crystalline structure filled with numerous small internal pores.
Image Credit: Eyes of Science/Science Photo Library
How do MOFs and COFs compare with other water and CO2 capture technologies?
We maintain a significant degree of control over the chemistry involved, allowing for sustainable device manufacturing. These devices are long-lasting, and when the MOF component eventually degrades, it can dissolve in water, thus preventing environmental contamination. Consequently, as MOFs scale to multi-ton applications, we should not anticipate a “MOF waste issue.”
For instance, we’ve developed a method to harness ambient sunlight for water release from harvesting devices, thereby enhancing energy efficiency. Similarly, carbon capture technologies can utilize waste heat from industrial processes, rendering them more economical and sustainable compared to competing systems.
However, challenges in scalability and precise molecular release control persist. While producing MOFs in large quantities is feasible, COFs production has not reached such scales yet. I am optimistic that improvements will come swiftly. Optimizing water retention is essential; we must strike the right balance between excessive and insufficient retention.
We are now leveraging artificial intelligence to streamline MOF and COF optimization, making the design process more efficient. Generally, while generating a basic MOF or COF is straightforward, achieving one with finely-tuned properties can be time-consuming, often taking a year. The integration of AI could significantly accelerate this timeline; our lab has successfully doubled the speed of MOF creation by employing large-scale language models.
What promising applications of reticular chemistry should capture public interest?
Reticular chemistry is a thriving field, with millions of new MOFs yet to be synthesized. One intriguing concept involves utilizing MOFs to replicate the catalytic functions of enzymes, enhancing the efficiency of chemical reactions important in drug development and other fields. Some MOFs have demonstrated capabilities comparable to enzymes but with improved longevity and performance, making them ripe for medical and therapeutic applications over the next decade.
An exciting future application lies in “multivariate materials.” This research, largely conducted in my lab, aspires to create MOFs with varied internal environments. By employing different modules paired with varying compounds, we can develop materials that selectively and efficiently absorb gases. This approach encourages chemists to expand their thinking beyond creating uniform structures toward designing heterogeneous frameworks that incorporate diverse elements.
What gives you confidence in the future of MOF and COF innovations?
We’ve merely scratched the surface, with no shortage of concepts for exploration. Since the 1990s, this field has flourished, and while interest in many areas declines over time, that hasn’t occurred here. An exponential rise in patents related to MOFs and COFs reflects ongoing curiosity and the pursuit of novel applications. I appreciate how this research links organic and inorganic chemistry, as well as engineering and AI, evolving beyond traditional chemistry into true scientific frontiers.
I genuinely believe we are at the cusp of a revolution. While it may not always feel that way, something extraordinary is transpiring. We can now design materials in unprecedented ways, connecting them to innovative applications that were once unimaginable.
This year’s Nobel Prize in Economics has been awarded to three experts who explore the influence of technology on economic growth.
Joel Mokyr from Northwestern University receives half of the prize, amounting to 11 million Swedish kronor (£867,000), while the remaining portion is shared between Philippe Aghion from the Collège de France, INSEAD Business School, and the London School of Economics, alongside Peter Howitt from Brown University.
The Royal Swedish Academy of Sciences announced this award during a period marked by rapid advancements in artificial intelligence and ongoing discussions about its societal implications, stating that the trio laid the groundwork for understanding “economic growth through innovation.”
This accolade comes at a time when nations worldwide are striving to rejuvenate economic growth, which has faced stagnation since the 2008 financial crisis, with rising concerns about sluggish productivity, slow improvements in living standards, and heightened political tensions.
Aghion has cautioned that “dark clouds” are forming amid President Donald Trump’s trade war, which heightens trade barriers. He emphasized that fostering innovation in green industries and curbing the rise of major tech monopolies are crucial for sustaining growth in the future.
“We cannot support the wave of protectionism in the United States, as it hinders global growth and innovation,” he noted.
While accepting the award, he pointed out that AI holds “tremendous growth potential” but urged governments to implement stringent competition policies to handle the growth of emerging tech firms. “A few leading companies may end up monopolizing the field, stifling new entrants and innovation. How can we ensure that today’s innovators do not hinder future advancements?”
The awards committee indicated that technological advancements have fueled continuous economic growth for the last two centuries, yet cautioned that further progress cannot be assumed.
Mokyr, a Dutch-born Israeli-American economic historian, was recognized for his research on the prerequisites for sustained growth driven by technological progress. Aghion and Howitt were honored for their examination of how “creative destruction” is pivotal for fostering growth.
“We must safeguard the core mechanisms of creative destruction to prevent sliding back into stagnation,” remarked John Hassler, chairman of the Economics Prize.
Established in the 1960s, the professional National Bank of Sweden awarded the Economics Prize in memory of Alfred Nobel.
Kitagawa, Richard Robson, and Omar Yaghi are honored with the 2025 Nobel Prize in Chemistry
Jonathan Nackstrand/AFP via Getty Images
The 2025 Chemistry Award recognizes Beijing U, Richard Robson, and Omar Yaghi for their innovative work on materials featuring cavities that can absorb and release gases like carbon dioxide, also known as metal-organic frameworks.
Heiner Linke, chair of the Nobel Committee on Chemistry, stated, “A small sample of such material can function like Hermione’s bag from Harry Potter.”
Tens of thousands of metal frameworks are currently in exploration. These materials present various potential applications, from capturing CO2 emissions to permanently purifying chemicals and extracting water from the atmosphere.
In the late 1980s, Richard Robson from the University of Melbourne pioneered the first metal-organic framework, drawing inspiration from the structural organization of diamonds. He discovered the feasibility of using metal ions as junctions connected by carbon-based or organic molecules.
When metal ions and organic compounds combine, they naturally form an organized framework. While the cavity in the diamond structure is petite, metal framework cavities can be significantly larger.
Robson’s metal-organic framework was initially filled with water. Kitagawa from Kyoto University in Japan was the first to devise a framework robust enough to retain stability when dried, allowing for gas to occupy the empty cavities.
“He demonstrated that gas could be absorbed, retained, and released by the material,” remarked Olof Ramström of the Nobel Committee on Chemistry.
Kitagawa also developed an organic-metal framework that changes form depending on gas absorption and release.
Omar Yaghi, from the University of California, Berkeley, achieved a more stable framework using clusters of zinc and oxygen metal ions along with linkers featuring carboxylate groups.
“This framework was remarkable due to its stability, enduring temperatures up to 300 degrees Celsius,” Ramström noted. “What’s even more impressive is that it possesses a vast surface area. Just a few grams of this porous material equate to the surface area of a large soccer field, similar to that of a small sugar cube.”
Yaghi also revealed that the cavities within these materials can be enlarged merely by extending their lengths.
Following these significant advancements, the field has seen rapid growth, as Ramström stated, “We are witnessing the development of new metal-organic frameworks almost on a daily basis.”
John Clarke, Michel Devolette and John Martinis awarded the 2025 Nobel Prize in Physics
Jonathan Nackstrand/AFP via Getty Images
The prestigious 2025 Nobel Prize in Physics was awarded to John Clarke, Michel Devolette, and John Martinis. Their research elucidates how quantum particles can delve through matter, a critical process that underpins the superconducting quantum technology integral to modern quantum computers.
“I was completely caught off guard,” Clarke remarked upon hearing the news from the Nobel Committee. “This outcome was unimaginable; it felt like a dream to be considered for the Nobel Prize.”
Quantum particles exhibit numerous peculiar behaviors, including their stochastic nature and the restriction to specific energy levels instead of a continuous range. This phenomenon sometimes leads to unforeseen occurrences, such as tunneling through solid barriers. Such unusual characteristics were first revealed by pioneers like Erwin Schrödinger during the early years of quantum mechanics.
The implications of these discoveries are profound, particularly supporting theories like nuclear decay; however, earlier research was limited to individual particles and basic systems. It remained uncertain whether more intricate systems such as electronic circuits, conventionally described by classical physics, also adhered to these principles. For instance, the quantum tunneling effect seemed to vanish when observing larger systems.
In 1985, the trio from the University of California, Berkeley—Clarke, Martinis, and Devolette—sought to change this narrative. They investigated the properties of charged particles traversing a superconducting circuit known as the Josephson Junction, a device that earned the Nobel Prize in Physics in 1973 for British physicist Brian Josephson. These junctions comprise wires exhibiting zero electrical resistance, separated by an insulating barrier.
The researchers demonstrated that particles navigating through these junctions behaved as individual entities, adopting distinct energy levels, clear quantum attributes, and registering voltages beyond expected limits without breaching the adiabatic barrier.
This groundbreaking discovery significantly deepened our understanding of how to harness similar superconducting quantum systems, transforming the landscape of quantum science and enabling other scientists to conduct precise quantum physics experiments on silicon chips.
Moreover, superconducting quantum circuits became foundational to the essential components of quantum computers, known as qubits. Developed by companies like Google and IBM, the most advanced quantum computers today consist of hundreds of superconducting qubits, a result of the insights gained from Clarke, Martinis, and Devolette’s research. “In many respects, our findings serve as the cornerstone of quantum computing,” stated Clarke.
Both Martinis and Devolette are currently affiliated with Google Quantum AI, where they pioneered the first superconducting quantum computer in 2019 that demonstrated quantum advantage over traditional machines. However, Clarke noted to the Nobel Committee that it was surprising to consider the extent of impact their 1985 study has had. “Who could have imagined that this discovery would hold such immense significance?”
Three distinguished scientists (two from the U.S. and one from Japan) have been awarded the Nobel Prize in Medicine for their pivotal discovery related to peripheral immune resistance.
Mary E. Blankku, Fred Ramsdell, and Sakaguchi Shiko were jointly recognized for their breakthrough that “has invigorated the field of peripheral tolerance and contributed to the advancement of medical treatments for cancer and autoimmune disorders,” as stated in a news release by the Nobel Committee. The three recipients will share a prize of 11 million Swedish Kronor (approximately $1.2 million).
“This could also enhance the success rates of organ transplants. Several of these therapies are currently in clinical trials,” he noted.
Autoimmune diseases may arise when T cells, which serve as the body’s main defense against harmful pathogens, malfunction.
Their collective discovery establishes an essential foundation for understanding alternative methods by which the immune system, known as peripheral resistance, functions.
To mitigate damage, our bodies attempt to eliminate malfunctioning T cells within the thymus, a lymphoid organ, through a mechanism termed central resistance. Associated Press.
The groundbreaking research began in 1995 when Sakaguchi, a prominent professor at the Center for Immunology Frontier Research at Osaka University in Japan, uncovered a previously unknown class of immune cells that defend against autoimmune diseases.
Six years later, in 2001, Mary Blankku, who now serves as a senior program manager at the Institute of Systems Biology in Seattle, along with Ramsdell, a scientific advisor to Sonoma Biotherapeutics in San Francisco, identified a specific genetic mutation responsible for a severe autoimmune disease known as IPEX.
They designated this gene as foxp3.
By 2003, Sakaguchi confirmed that the FOXP3 gene he had identified nearly a decade prior was crucial for cell development. These cells are now referred to as regulatory T cells, which are essential in monitoring other T cells to prevent their malfunction.
“Their discoveries were vital for understanding the immune system’s functioning and why serious autoimmune diseases don’t affect everyone,” remarked All Kampe, Chairman of the Nobel Committee.
Nobel Committee Executive Director Thomas Perman announced the award on Monday morning, stating that he was only able to reach Sakaguchi.
“I hugged him in his lab, and he expressed immense gratitude, stating it was a tremendous honor. He was quite moved by the news,” Perman mentioned.
The awards ceremony is scheduled for December 10th, coinciding with the anniversary of Alfred Nobel’s death, a Swedish industrialist who founded the award to honor individuals who have significantly contributed to humanity. The inaugural award was revealed in 1901, marking the fifth anniversary of his passing.
The Nobel Prize in Physiology or Medicine will be announced in Stockholm at the Karolinska Institute on Monday, followed by the prizes for Physics, Chemistry, and Literature on the ensuing days.
Mary Blankku, Fred Ramsdell, and Sato Shimajimajima have been announced as winners of the 2025 Nobel Prize in Physiology or Medicine by Committee Executive Director Thomas Perman.
Jonathan Nackstrand/AFP via Getty Images
The 2025 Nobel Prize in Physiology or Medicine has been awarded to three groundbreaking researchers: Mary Blank, Fred Ramsdel, and Shimon Sakaguchi. They have made significant discoveries regarding a unique type of immune cell that prevents the immune system from attacking its own body.
“We have opened up an entirely new area in immunology,” stated Marie Warren Hellenius from the Karolinska Institute in Sweden.
T cells, a type of immune cell, are crucial for detecting and neutralizing harmful viruses and bacteria. These cells are continuously produced throughout a person’s life.
At times, newly formed T cell receptors may mistakenly target the body’s own proteins instead of those from viruses or bacteria, resulting in autoimmune disorders like type 1 diabetes and rheumatoid arthritis.
The body possesses mechanisms to eliminate autoreactive T cells, with newly generated ones migrating to the thymus for evaluation. This has long been believed to be the sole process for the removal of self-targeting T cells.
Yet in 1995, Sakaguchi, now at Osaka University, demonstrated through a mouse study that other circulating cells in the bloodstream must provide some form of protection against autoreactive T cells. When the thymus is removed post-birth, mice develop autoimmune conditions; however, this outcome is averted when healthy T cells are introduced. His research identified that these particular T cells feature the CD25 protein on their surface, thereby classifying them as CD25-regulated T cells.
Meanwhile, Blankku, currently affiliated with the Institute of Systems Biology in Seattle, and Ramsdell, who advises Sonoma Bitherapeutics in San Francisco, studied mouse strains predisposed to autoimmune diseases. In 2001, Brunkow and Ramsdell identified that these mice possess mutations in a gene located on the X chromosome, specifically FOXP3.
Individuals with mutations in this gene are particularly susceptible to autoimmune disorders due to a condition known as IPEX syndrome. In 2003, Sakaguchi connected these findings, showing that the FOXP3 gene is integral to the development of the CD25-regulated cells his team had identified. Many researchers previously remained skeptical of Sakaguchi’s assertions, according to Warren Hellenius. However, the findings from Brunkow and Ramsdell solidified the case.
The discovery of regulatory T cells could pave the way for improved treatments across a variety of conditions. Increasing the presence of regulatory T cells may help mitigate autoimmune responses that lead to diseases like type 1 diabetes. Conversely, reducing these cells can amplify the immune system’s response against cancer. Numerous clinical trials are currently being conducted.
“Their discoveries have been fundamental in understanding the workings of the immune system and explaining why serious autoimmune diseases don’t universally develop,” remarked Orkenpe, the chairman of the Nobel Committee, in a statement.
Kashiwara’s work is very abstract, but is seen as important
Peter Bagde / Typos1 / The Abel Prize
Red-tailed For his research on algebraic analysis, he received the 2025 Abel Prize, known as the Nobel Prize in Mathematics.
Professor of Kashiwara Kyoto UniversityJapan received the award “for his fundamental contributions to algebraic analysis and representational theory, particularly for the development of the theory of D-modules and the discovery of crystal bases.”
His work involves the use of algebra, focusing on investigating geometry and symmetry, and using those ideas to find solutions to differential equations that include the relationship between mathematical functions and their rate of change. Finding solutions to such equations can be particularly difficult, especially for functions with several variables, and therefore with several rates of change. These are known as partial differential equations (PDEs).
Kashiwara’s important work on the D-module, a highly specific area of algebraic analysis, including Linear PDE, was conducted surprisingly early in his career during his doctoral dissertation. He has worked with over 70 collaborators. Kashiwara said New Scientist He was pleased to win the Abel Prize, but he is still active and would like to make further contributions.
“I’m currently working on representative theory of quantum affine algebra and its related topics,” he says. “There’s a great guess: [the] “Affine epicenter speculation,” but I still don’t know how to solve it. ”
David Craven At the University of Birmingham, UK, Kashiwara’s work is very abstract and far from a direct real-world application, and even basic summary says that a minimum of a doctorate in mathematics is required. “That’s the level of these things being difficult,” he says. “It’s incredibly esoteric.”
However, Craven says that Kashiwara had a major impact on his field. “What he did is permeate theories of expression. If you want to do geometrical expression theory, you can’t escape from Kashiwara.
Gwyn Bellamy “All the big results on the field are [algebraic analysis] It was more or less due to him, and Kashiwara’s Abel Prize victory has been a long time.
Named after Norwegian mathematician Neils Henrik Abel, the Abel Prize is awarded annually by the King of Norway. Last year, Michelle Taragland won for his work in extreme studies of probability theory and randomness.
Kashiwara Kuniki, a Japanese mathematician, has been awarded the Abel Prize, considered the equivalent of the Nobel Prize in mathematics. Dr. Kashiwara’s work combines algebra, geometry, and differential equations in a unique and abstract manner.
The Norwegian Academy of Sciences and Letters, responsible for the Abel Prize, announced the honor on Wednesday morning.
“He resolved difficult open speculations and connected previously unknown areas, surprising mathematicians,” said Helge Holden, chairman of the awards committee.
Mathematicians can use connections between different mathematical domains to address complex problems and gain a deeper understanding.
Kawakaze, 78, from Kyoto University, is considered “very important in many different fields of mathematics,” stated Holden.
Dr. Kashiwara, when asked if his work solved real-world problems, responded with a negative. The honor comes with approximately $700,000 in prize money.
Unlike Nobel Prize winners, Dr. Kashiwara was informed of his accolade a week prior to the public announcement.
The Norwegian Academy surprises Abel Prize winners with notifications similar to surprise birthday parties.
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Marit Westerguard, executive director of the Norwegian Academy, personally informed Dr. Kashiwara of his selection as Abel of the year.
Dr. Kashiwara, initially confused due to internet issues, was eventually able to grasp the news conveyed to him in Japanese.
Having been attracted to mathematics from a young age, Dr. Kashiwara’s work reflects his passion for algebraic analysis.
Real-world phenomena are explained using real and imaginary numbers, showcasing the interconnection between mathematics and the physical world.
Dr. Kashiwara’s impactful work in mathematics links abstract ideas to insightful combinations for mathematicians across various disciplines.
His innovative approaches, such as the Crystal Base, have opened new avenues of research in the field.
It's the most celebratory time of the year, as some of the brightest minds in science win Nobel Prizes. Recent winners have a few things in common. They definitely have a great body of work. And they're all men, they live in high-income countries, and none of them are black.
Gary Lubukun and Victor Ambrose received the Physiology or Medicine Prize for their discovery of microRNAs and their role in gene regulation to help treat cancer. A series of papers led to this discovery, many of which listed Ambrose's wife, Rosalind Lee, as the author. The Nobel Committee for Physiology and Medicine We would like to recognize Ms. Lee on social media.but did not go as far as awarding a medal. They may think that one device per family is enough.
Lee's omission may seem familiar. In 1962, James Watson, Francis Crick, and Maurice Wilkins received the award for their discovery of the molecular structure of DNA. This was the opposite Of the three papers published in the same issue nature. One was co-authored by Wilkins, another was co-authored by Watson and Crick, and the third was an image captured by Rosalind Franklin of DNA with two strands. Prior to publishing the image, It ended up in the hands of Watson and Crick.I then told them that their DNA model was a double helix. Franklin was removed from the Nobel Prize trophy.
Perhaps the committee dislikes the name Rosalind. but 972 people won the Nobel Prize Since our founding in 1901, 64 were women. This year's physics prize, awarded to John Hopfield and Geoffrey Hinton for discoveries related to machine learning, had a particularly poor hit rate, with only five women winning the award so far.
At least women in science are getting some recognition. No black person has ever won a science Nobel Prize, and only 17 black people have won the peace, literature, and economics prizes combined. Many people argue that Charles Drew says: African American man discovers a way to store plasma long-termmedicine was supposed to win, but Percy Julian figured it out. How to synthesize medicines from plantsneglected because of chemistry.
Geography also appears to play an important role in determining the winner. More than half of the prizes I went to the people of North America.and the few winners from low-income countries, most of whom had immigrated to North America or Europe by the time they won the award.
The Royal Swedish Academy of Sciences, which administers the prizes in physics and chemistry, at least recognizes that this lack of diversity is a problem. Starting in 2019, recommenders are required to: When choosing candidates, pay attention to gender, ethnicity, and geographypeople who can't put themselves forward. Sounds good in theory, but since then, only six women and none of them have won in science, and none have been black.
You may be wondering why this is important. Awards are great honors, but they shouldn’t drive scientists. However, being a Nobel Prize winner opens doors for researchers and brings their work into the public consciousness. For many people, the annual Nobel Prize may be the only time they see a scientist's name in the news headlines, but this award plays a huge role in shaping our perception of science.
Part of the problem is that the prize structure, dictated by Alfred Nobel's will, tends to enforce a “great man of history” approach to science that does not reflect the realities of modern research. The rules state that no more than three people can share the award, but this does not explain why Lee was left out of the winning duo of Lubukun and Ambros. Additionally, donations cannot be received after death. Otherwise, Ms. Franklin, who died of ovarian cancer in 1958 at the age of 37, might have received the donations by now.
Of course, such issues are not new, and it seems unlikely that the Nobel Prize committee will deviate from the wishes of its sponsors, but that is no reason to ignore diversity. The committee needs to cast a wider net, not just for the sake of fairness, but if it wants to ensure that the awards continue to be taken seriously.
Alexandra Thompson is assistant news editor at New Scientist.
The 2024 Nobel Prize in Chemistry has been awarded to scientists David Baker, Demis Hassabis, and John Jumper, as announced by the awarding body on Wednesday. protein structure.
This prestigious award, worth 11 million Swedish crowns ($1.1 million), is bestowed by the Royal Swedish Academy of Sciences.
Baker received half of the prize for his work in “computational protein design,” while Hassabis and Jumper shared the other half for “protein structure prediction,” according to the academy.
Following the announcement of the Chemistry Award, this is the third of the awards given each year. Medicine and physics winners were revealed earlier this week.
Established by the will of Alfred Nobel, the inventor of dynamite, and a wealthy businessman, the Nobel Prize is awarded to individuals who have made significant contributions benefiting mankind the previous year.
Since its inception in 1901, the Nobel Prize has honored achievements in various fields including medicine, physics, chemistry, literature, and peace. The prize amount has been adjusted over the years, and the Economics Prize was later added by the Swedish Central Bank.
Chemistry, a field closely tied to Alfred Nobel’s work as an inventor, has seen notable recipients over the years, including pioneers like Ernest Rutherford and Marie Curie.
In the previous year, the chemistry prize was awarded to Mungi Bawendi, Luis Brus, and Alexei Ekimov for their discovery of quantum dots, tiny clusters of atoms widely used today in various technologies.
In addition to the monetary reward, the Nobel Prize winners will receive a medal from the King of Sweden on December 10th, followed by a grand banquet at Stockholm City Hall.
John Hopfield and Jeffrey Hinton jointly awarded 2024 Nobel Prize in Physics
Christine Olson/TT/Shutterstock
The 2024 Nobel Prize in Physics will be awarded to John Hopfield and Jeffrey Hinton for their work on fundamental algorithms that enable artificial neural networks and machine learning, which are key to today’s large-scale language models such as ChatGPT. was awarded.
Upon hearing the award announcement, Hinton told the Nobel Committee, “I’m shocked. I never expected something like this to happen.” “I’m very surprised.” Hinton, who has been vocal about his concerns about the development of artificial intelligence, also reiterated that he regrets the work he did. “I would do the same thing in the same situation, but I fear that the overall impact of this will ultimately be controlled by systems more intelligent than us.” he said.
AI may not seem like an obvious candidate for the Nobel Prize in physics, but the discovery of learnable neural networks and their applications are two fields closely related to physics, the Nobel Committee for Physics says. Committee Chair Ellen Moons said during the announcement. . “These artificial neural networks are being used to advance research across a variety of physics topics, including particle physics, materials science, and astrophysics.”
Many early approaches to artificial intelligence involved giving computer programs logical rules to follow to solve problems, allowing them to learn about new information and It has become difficult for me to encounter situations that I have never seen before. In 1982, Hopfield at Princeton University created an architecture for computers called the Hopfield Network. A Hopfield network is a collection of nodes or artificial neurons whose connection strengths can be changed by a learning algorithm invented by Hopfield.
This algorithm is inspired by the study of physics to find the energy of a magnetic system by describing it as a collection of small magnets. The technique involves repeatedly changing the strength of the connections between the magnets to find the energy minimum of the system.
That same year, Hinton at the University of Toronto began developing Hopfield’s ideas to help create a closely related machine learning construct called a Boltzmann machine. “I remember going to a conference in Rochester where John Hopfield was speaking and learning about neural networks for the first time.After this, Terry [Sejnowski] And I worked hard to find ways to generalize neural networks,” he said.
Hinton and colleagues showed that unlike previous machine learning architectures, Boltzmann machines can learn and extract patterns from large data sets. This principle, combined with large amounts of data and computational power, has led to the success of many of today’s artificial intelligence systems, such as image recognition and language translation tools.
However, although Boltzmann machines have proven to be capable, they are inefficient and slow, so they are not used in today’s modern systems. Instead, it uses faster, modern machine learning architectures like Transformer models that power large language models like ChatGPT.
At the Nobel Prize press conference, Hinton was bullish about the impact of his and Hopfield’s discoveries. “It will be comparable to the industrial revolution, but instead of surpassing humans in physical strength, we will surpass humans in intellectual ability,” he said. “We’ve never experienced what it’s like to have something smarter than us. It’s going to be great in many ways…but we have We also have to worry about the negative consequences of this, especially the threat that these things can get out of control.”
French mathematician Michel Taragrand has won the 2024 Abel Prize for his work on probability theory and the description of randomness. As soon as he heard the news, new scientist We spoke to Tara Grand to learn more about his mathematical journey.
Alex Wilkins: What does it mean to win an Abel Prize?
Michel Taragran: I think everyone agrees that the Abel Prize is considered the equivalent of the Nobel Prize in mathematics. So this was completely unexpected for me and I never dreamed that I would win this award. And in fact, it is not so easy to do, since there is already a list of people who have received it. And in that list they are true giants of mathematics. And let me tell you, I don’t feel that comfortable sitting with them because it’s clear that their accomplishments are on a completely different scale than mine.
What are your qualities as a mathematician?
I can’t learn mathematics easily. I have to work. It took a lot of time and I have bad memories. I forget things. So I try to work despite my handicap, but my way of working has always been to try to understand simple things really well. Really, really, in detail. And it turned out to be a successful approach.
Why are you attracted to mathematics?
Once you learn mathematics and begin to understand how it works, it is completely fascinating and extremely fascinating. There are all kinds of levels and you are the explorer. First you have to understand what people before you understood, which is quite difficult, and then you start exploring on your own and soon you like it. Of course, it’s also very frustrating. Therefore, you must have the personality to accept frustration.
But my solution is that when I get frustrated with something, I put it aside, and when it’s clear that I’m not going to make any more progress, I put it aside and do something else, and come back to it later. . I used that strategy very efficiently. And the reason it’s successful is the way the human brain functions, things mature when you don’t look at them. The problem I’ve been dealing with for literally 30 years is back again. And in fact, even after 30 years, I was still making progress. That’s what’s amazing.
How did you get started?
Now, that’s a very personal story. First, it helped that his father was a math teacher, and of course that helped. But in reality, the deciding factor is that I was unlucky to be born with a retinal defect. Then, when I was 5 years old, I lost my right eye. When I was 15 years old, I suffered from multiple retinal detachments and was hospitalized for an extended period of time, taking 6 months off from school. It was very traumatic and I lived in constant fear of having another retinal detachment.
I started studying to escape from that. And his father really helped me very much when he knew how difficult it was. When I was in the hospital, my father visited me every day and started talking about simple math to keep my brain functioning. The reason I started studying difficult mathematics and physics was precisely to combat fear. Of course, once you start studying, you’ll get better at it, and once you’re good at it, it’s very attractive.
What is it like to be a professional mathematician?
There’s no one telling me what to do, so I have complete freedom to do whatever I want with my time. Of course, it suited my personality and I was able to fully devote myself to my work.
Michel Taragran won the 2024 Abel Prize, also known as the Nobel Prize of mathematics, for his work on probability theory and the description of randomness. The news came as a surprise to Taragrand. He learned what he thought was his Zoom call within the department. He said: “My brain completely shut down for five seconds. It was an amazing experience. I never expected anything like this.”
Tara GrandBased at the French National Center for Scientific Research (CNRS), he has spent much of his 40-year career on extreme characterization of random or stochastic systems. These problems are common in the real world. For example, a bridge builder may need to know the maximum wind strength expected from the local weather.
Such random systems are often very complex and may contain many random variables, but Talagrand’s method of converting these systems into geometric problems allows us to extract useful values. can. “He is a master at getting accurate estimates, and he knows exactly what to add or subtract to get an accurate estimate,” he says. Helge HoldenChairman of the Abel Prize Committee.
Taragrand also developed mathematical tools and equations for systems that are random but exhibit some degree of predictability within that randomness, a statistical principle called concentration of measurements. His equation, known as the Taragrand inequality, can be used for many systems that exhibit concentration of measurements. Asaf Naor At Princeton University, he developed famous algorithmic puzzles such as the Traveling Salesman Problem. “Not only is he a great discoverer in his own right, but he is also an influence. He has provided the world with an amazing collection of insights and tools,” Naor says.
Perhaps inspired by his own work, Taragrand says he views his career as a random process. “It’s really scary when you look at your life and the important things that happened. They were determined by small random influences and there was no plan at all,” he says.
Although many of his works were general, he also had a particular interest in the mathematical basis of spin glasses. Spin glass is an unusual magnetic arrangement in which the atoms of a material can act like tiny magnets, pointing in random directions and exhibiting no apparent order. Repeating crystal structure in ordinary glass.
“This award is definitely well-deserved,” he says Giorgio Parisi from Sapienza University in Rome, Italy, won the 2021 Nobel Prize in Physics for his work on spin glasses. Parisi and his colleagues first proposed a formula to describe these materials, named after Parisi, but it was not proven mathematically until the work of Taragrand and Italian physicist Francesco Guerra. . “It’s one thing to believe that a guess is correct, but it’s another to prove it. I believed it was a very difficult problem to prove,” Parisi says.
It also helped draw the field to the attention of other mathematicians, Parisi said. “This was a great proof and completely changed the game, because it was the starting point for a deeper understanding of the theory.”
For Taragrand, one of the keys to success was persistence. “You can’t learn mathematics easily. You have to work. It takes a lot of time and you have bad memories. You forget things. So despite these handicaps, I have to work. My way of working has always been to try to understand simple things really well.”
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