From First Principles

What science should you be watching this fall? From Nobel Prize season to NASA’s Roman Space Telescope, Mars’ moons and Mercury, Lester Nare and Krishna Choudhary take a relaxed tour of the discoveries and missions on their radar. In Episode 57 of From First Principles, we explore why curiosity-driven research matters, what the Golden Goose Awards celebrate, and how questions that once sounded impractical can lead to unexpected breakthroughs. Then we turn to space: Roman’s search for dark energy and exoplanets, JAXA’s Martian Moons eXploration (MMX) mission, and the mysteries ESA and JAXA’s BepiColombo mission will investigate at Mercury. Along the way, we tour the updated FFP website, revisit some favorite episodes, and ask which stories you want us to cover in depth next. A note before we begin: the main conversation was recorded before Labor Day weekend. The opening announcement addresses your requests for a separate episode on OpenAI, Navier–Stokes and the wider AI conversation. This episode is our fall science rundown; that deep dive is still to come. CHAPTERS 00:00 Update on our upcoming Navier–Stokes and AI coverage 03:43 Episode intro and football banter 05:47 FFP intro 06:01 Nobel Prize season and our coverage plans 10:45 Golden Goose Awards: why basic research matters 21:02 FFP website tour and favorite episodes 42:24 Nancy Grace Roman Space Telescope 46:20 Microlensing, exoplanets and dark matter 51:25 MMX: where did Mars’ moons come from? 54:40 BepiColombo and the mysteries of Mercury 1:02:17 Your questions, future deep dives and sign-off 1:05:40 Outro SHOW NOTES NASA’s Nancy Grace Roman Space Telescope: https://science.nasa.gov/mission/roman-space-telescope/ JAXA’s Martian Moons eXploration (MMX): https://www.mmx.jaxa.jp/en/mission/ ESA / JAXA BepiColombo: https://www.esa.int/Science_Exploration/Space_Science/BepiColombo Explore the research and episodes we cover: https://ffppod.com Science R&D Funding Tracker: https://ffppod.com/funding Science Transfer Board: https://ffppod.com/transfers America 250: https://ffppod.com/America250 Support the show: https://ffppod.com/donate WATCH ON YOUTUBE https://youtu.be/snhQh0fjTX4 Follow @FFPPod on X / Instagram / TikTok / Facebook Breaking down science news so it makes sense to curious people everywhere. Which mission or research story deserves a full FFP deep dive? Tell us in the comments.

What can a yak living thousands of meters above sea level teach us about repairing the human brain? In Episode 56 of From First Principles , Lester Nare and Krishna Choudhary break down a new Neuron paper that traces an evolutionary adaptation found in high-altitude animals to a previously hidden pathway involved in building and repairing myelin. Summary What myelin actually does and why losing it disrupts neural communication How multiple sclerosis damages myelin and why the brain’s natural repair process eventually fails Why oligodendrocyte precursor cells can remain present in damaged tissue without successfully rebuilding myelin Why current therapies are better at slowing further damage than restoring what has already been lost The challenge of getting drugs across the blood-brain barrier while maintaining target specificity How evolutionary pharmacology has previously produced medicines from adaptations found in snakes and Gila monsters The RETSAT Q247R variant identified in animals adapted to the hypoxic environment of the Tibetan Plateau How researchers engineered the high-altitude variant into mice and tested its effect on myelin The surprising discovery that neurons — rather than the myelin-producing cells themselves — generate the key repair signal How RETSAT increases ATDR, which neurons convert into ATDRA How ATDRA activates RXR-γ in oligodendrocyte precursor cells and promotes their differentiation How administration of ATDR promoted remyelination across multiple preclinical models Why the result is scientifically promising but still far from a proven human treatment Featured Paper A gain-of-function Retsat variant from high-altitude adaptation promotes myelination via a neuronal dihydroretinoic acid-RXR-γ pathway Neuron, 2026 DOI: 10.1016/j.neuron.2026.01.013 Explore FFP ffppod.comffppod.com/fundingffppod.com/transfersffppod.com/America250 Support the show ffppod.com/donate Follow @FFPPod on X / Instagram / TikTok / Facebook

Which quantum computer will actually scale? In Part 2 of our quantum computing deep dive, Lester Nare and Krishna Choudhary move from theory to hardware—comparing superconducting qubits, trapped ions, neutral atoms, and silicon spin qubits before going inside the new Nature cover paper Krishna co-authored with the HRL Quantum Team and collaborators. The episode begins with a simple question: what makes a good quantum computer? We evaluate each architecture using three criteria: qubit quality, qubit control, and scalability and economics. Superconducting qubits offer extremely fast operations, but scaling them introduces challenges involving microwave control, frequency crowding, cryogenic wiring, physical size, and cooling. Trapped ions preserve quantum information for extraordinary lengths of time, but their slower gates and increasingly complex optical systems introduce a different set of tradeoffs. Neutral atoms can be arranged in dense, reconfigurable arrays using optical tweezers and entangled through Rydberg interactions, while raising questions involving atom loss, correlated noise, readout, and execution time. Then we get to silicon. Beginning with the Loss–DiVincenzo proposal, Krishna explains how individual electron spins can be confined inside semiconductor quantum dots, manipulated through exchange interactions, and measured using single-electron transistors. We then explore exchange-only qubits, where three electron spins encode a single qubit and quantum gates can be performed using electrical control. That leads to the Nature cover paper, A digitally controlled silicon quantum processing unit . The HRL system integrates 18 encoded qubits built from 54 quantum dots with cryogenic control electronics, a superconducting interconnect, automated calibration, and an engineered silicon-germanium heterostructure. Krishna also explains his own work using machine learning to automate quantum-device tuning—an essential problem if spin-qubit systems are ever going to grow from dozens of components to millions. The larger thesis is about manufacturing. The semiconductor industry has spent decades learning how to fabricate silicon devices at enormous scale. If quantum processors can inherit that infrastructure, the architecture that ultimately wins may not be the one that reaches the finish line first—but the one humanity already knows how to manufacture. Nature paper: A digitally controlled silicon quantum processing unitDOI: 10.1038/s41586-026-10754-7https://www.nature.com/articles/s41586-026-10754-7 Explore the FFP Science Transfer Portal: ffppod.com/transfers Support the show: ffppod.com/donate Follow: @FFPPod on X / Instagram / TikTok / Facebook

Quantum computers do not simply “try every answer at once.” So what do they actually do—and why have governments and technology companies spent billions trying to build them? In Part 1 of our two-part quantum computing deep dive, Lester Nare and Krishna Choudhary build the field from first principles. The series was prompted by a new Nature cover paper, A digitally controlled silicon quantum processing unit , co-authored by Krishna and members of the HRL Quantum Team and collaborators. Before getting into that hardware in Part 2, we first need to understand why anyone wanted to build a quantum computer in the first place. We begin with Bell’s theorem and the failure of local hidden-variable explanations of quantum mechanics. From there, we follow the realization that information is fundamentally physical through Rolf Landauer, reversible computation, Charles Bennett, Tommaso Toffoli, Paul Benioff, and the origins of quantum information science. Then Richard Feynman changes the question. Straightforward classical simulation of an interacting quantum system requires tracking a state space that grows exponentially with the number of particles. If nature itself is quantum mechanical, Feynman asks, why not build a computer that is quantum mechanical too? David Deutsch formalizes the universal quantum computer and introduces the first quantum algorithm. Using the Deutsch–Jozsa problem, the double-slit experiment, and Feynman’s path-integral intuition, we explain what a quantum algorithm is actually exploiting: carefully engineered constructive and destructive interference. Finally, we reach the discoveries that turned quantum computing from an academic curiosity into a strategic technology. Daniel Simon develops an early exponential quantum speedup. Peter Shor recognizes how the underlying mathematics can be used to attack problems central to public-key cryptography. Lov Grover follows with a quantum search algorithm—and suddenly governments have a very different reason to care about quantum machines. We also explore quantum money, quantum cryptography, the many-worlds interpretation, Google Willow and parallel-universe headlines, post-quantum security, and what useful quantum computers may ultimately be good for. Part 2: How do you actually build one? Nature paper: A digitally controlled silicon quantum processing unitDOI: 10.1038/s41586-026-10754-7 Link: https://www.nature.com/articles/s41586-026-10754-7 Explore the FFP science funding tracker: ffppod.com/funding Support the show: ffppod.com.com/donate Follow: @FFPPod on X / Instagram / TikTok / Facebook

Claude did not solve the Riemann Hypothesis. But what it actually did may be one of the clearest examples yet of how rapidly AI systems are changing the way difficult mathematics can be attacked. In Episode 53, Lester Nare and Krishna Choudhary go from first principles on arguably the most famous unsolved problem in mathematics. We begin with Euler and the Basel problem, build the Riemann zeta function from the ground up, explain its deep connection to prime numbers, move into the complex plane and analytic continuation, unpack the famous 1 + 2 + 3 + 4 + … = -1/12 result, and finally arrive at the Riemann Hypothesis itself: the claim that every non-trivial zero of the zeta function lies on the critical line. Then we get into Claude. An unreleased Anthropic model was prompted to take a serious run at the problem. It orchestrated roughly 60 autonomous sub-agents, tested hundreds of mathematical approaches, executed code, searched academic literature, challenged its own strategies, created adversarial referees to attack its work, and ultimately produced a result pushing a related mathematical bound well beyond the previous state of the art. The human behind the prompt was not a mathematician. One of his instructions was essentially: believe in yourself. We explain what Claude actually accomplished, what it absolutely did not accomplish, why moving a bound toward two-thirds does not mean the Riemann Hypothesis is “two-thirds solved,” and what the process tells us about agentic AI, mathematical research, scientific discovery, and AI safety. Then it’s transfer season. For the first FFP Summer Transfer Window for Scientists, we look at prominent researchers leaving American institutions for universities and research centers abroad. Using the language of football transfers, we examine major moves in chemistry, battery research, gravitational-wave astrophysics, and neuroscience—and what they reveal about research funding, immigration, scientific infrastructure, and the global competition for talent. Explore the FFP science funding tracker: ffppod.com/funding Help shape Year Two and enter the anniversary merch giveaway: ffppod.com/survey Support the show: ffppod.com/donate Follow: @FFPPod on X / Instagram / TikTok / Facebook

In this anniversary episode, Lester Nare and Krishna Choudhary look back at how two longtime friends turned their regular conversations about science into a show now shared by millions of people around the world, and what they hope to build with FFP Nation in Year Two. Then we turn to a new Nature paper challenging the idea that the precolonial Amazon was sparsely populated. Airborne LiDAR revealed hundreds of geometric earthworks hidden beneath the rainforest canopy. Combining the new survey with earlier archaeological evidence, the researchers estimate that the region could contain more than 20,000 earthworks and may have supported 1.25–3 million people around AD 100–300. Lester and Krishna explain how LiDAR sees through dense vegetation, why early European accounts of crowded Amazonian settlements were dismissed, how disease and forest regrowth could erase the visible traces of large societies, and what the findings mean for our understanding of the Amazon’s human and environmental history. The conversation then becomes a thought experiment: if our civilization disappeared, what would future archaeologists—or extraterrestrial visitors—recognize as our pyramids? Apollo landing sites, CERN, LIGO, and the James Webb Space Telescope become candidates for the enduring signatures of a curiosity-driven civilization. Finally, we christen the From First Principles library. Krishna shares the mathematics, physics, biology, history, and philosophy books that shaped how he thinks, including Baby Rudin, Landau–Lifshitz, Fermi, Jackson, Sakurai, Einstein, Schrödinger, Gibbs, Newton’s Principia , Plato, the Upanishads, and Adam Becker’s What Is Real? Help shape Year Two and enter the anniversary merch giveaway: ffpod.com/survey Support the show: ffppod.com/donate Research and show notes: Over 20,000 precolonial earthworks in the Southwest Amazonia Nature Research Briefing FFP episode archive and research library

What happens when electronics can operate at temperatures hot enough to melt aluminum? In this deep-dive episode, Lester Nare and Krishna Choudhary examine a new high-temperature memory device developed by researchers at USC, the Air Force Research Laboratory, Kumamoto University, and their collaborators. Published in Science , the experimental memristor combines tungsten, hafnium oxide, and graphene. It operated reliably at 700°C—roughly 1,300°F—retained data for more than 50 hours, and survived more than one billion switching cycles. We begin by explaining why conventional electronics and flash memory fail when temperatures rise. From deep-earth drilling and hypersonic aircraft to nuclear systems and the surface of Venus, many environments where intelligent electronics would be useful remain inaccessible to today’s hardware. Krishna then builds the memristor from first principles. We explore the history of the “missing” fourth circuit element, how oxygen vacancies create low- and high-resistance memory states, why conventional platinum electrodes fail under extreme heat, and how graphene prevents tungsten atoms from diffusing through the device. Finally, we examine the implications for artificial intelligence. Memristors can potentially store neural-network weights and perform matrix multiplication in the same physical location, reducing the energy wasted moving information between processors and memory. Could that combination of heat tolerance and energy efficiency make AI data centers in space more practical? Lester and Krishna work through thermal radiation, radiator size, power consumption, radiation resilience, and the considerable engineering challenges that remain. Support the show Donate: FFPod.com/donate Follow: @FFPod on X / Instagram / TikTok / Facebook Research and Show Notes High-temperature memristors enabled by interfacial engineering USC: A memory device that operates at 700°C The development of carbon-neutral data centres in space NASA Venus facts

Hosted by Lester Nare and Krishna Choudhary , this episode moves from astrobiology to science policy to the rapidly changing frontier of artificial intelligence and mathematics. First, researchers analyzing pristine samples returned from asteroid Ryugu report all five canonical nucleobases used by DNA and RNA. We explain what that does—and does not—mean for the origin of life, how JAXA’s Hayabusa2 mission collected uncontaminated asteroid material, and why comparisons with NASA’s Bennu samples strengthen the case that prebiotic chemistry may be widespread across the Solar System. Next, we examine the fight over who controls federal research funding. A proposed overhaul of the rules governing federal grants would give political appointees greater influence over awards, reduce the controlling role of expert peer review, and expand the government’s power to stop grants that no longer align with an administration’s priorities. We break down the roles of Congress, OMB, federal agencies, universities, and the courts—and why this dispute could reshape the American research ecosystem. Finally, we go deep on an AI-assisted counterexample to the Jacobian conjecture, a major open problem in mathematics. Krishna explains coordinate transformations, Jacobian determinants, invertibility, special relativity, and why this result appears fundamentally different from simple brute force. We close with the growing debate over AI-generated mathematics, human verification, open science, attribution, and the future role of mathematicians. Summary All five canonical nucleobases found in pristine asteroid Ryugu samples Hayabusa2, Bennu, and the possibility of widespread prebiotic chemistry The fight over political control of federal research grants Congress, OMB, peer review, and the American science-funding system The Jacobian conjecture and an AI-assisted counterexample Special relativity, coordinate transformations, and invertibility AI-generated mathematics, open science, attribution, and verification Support the show Donate: FFPod.com/donate Follow: @FFPod on X / Instagram / TikTok / Facebook Show Notes A complete set of canonical nucleobases in asteroid Ryugu OMB proposed federal-grant rule Association of American Universities response Levent Alpöge’s Jacobian counterexample announcement Leiden Declaration on Artificial Intelligence and Mathematics Human-verified remarks on the OpenAI-generated Erdős result

In this special interview episode, Lester Nare speaks with Juan Busso , Senior Football Data Scientist at FIFA, and Arron Ackerman , FIFA’s Team Lead for Football Performance Analysis, about the data science behind the Match Momentum visualization featured throughout the 2026 World Cup. What does “momentum” actually mean in football—and how can it be measured without reducing the game to possession or shots? Juan and Arron explain how FIFA translates football principles into mathematical models, validates those models with coaches and technical experts, and turns complex tracking data into a graphic that fans can understand at a glance. We break down the underlying “threat” model, including kinetic pitch control, player speed and acceleration, ball trajectories, defensive spacing, distance to goal, sight lines, and the creation of space. Match Momentum is calculated from player-tracking data captured 50 times per second, allowing the model to recognize when a team is becoming dangerous even without dominating possession. The conversation also covers FIFA’s wider data ecosystem—including event data, skeletal tracking, and the connected match ball—why offside positioning can still create threat, whether hydration breaks alter momentum, and the next generation of football analytics focused on player energy and physical effort. Guests Juan Busso — Senior Football Data Scientist, FIFA Arron Ackerman — Team Lead, Football Performance Analysis, FIFA Support the show Donate: FFPod.com/donate Follow: @FFPod on X / Instagram / TikTok / Facebook

Hosted by Lester Nare and Krishna Choudhary , this episode returns to the FFP science rundown with stories spanning astrophysics, precision medicine, medical imaging, artificial intelligence, and World Cup technology. We begin with the Event Horizon Telescope and its evolving view of M87*, the supermassive black hole 55 million light-years away. How do you image something that appears about as small as a donut on the Moon? Krishna explains angular resolution, the Rayleigh limit, radio interferometry, and how telescopes across Earth can function like one planet-sized instrument. We then look at new observations showing the magnetic field around M87* changing over time—and why that may help explain black-hole jets and the mysterious shutdown of star formation in giant elliptical galaxies. Next, we turn to medicine. Researchers at Johns Hopkins have built personalized digital twins of patients’ hearts, allowing doctors to simulate ventricular-tachycardia treatments before entering the operating room. We break down how MRI data, electrical modeling, and virtual ablation could reduce procedures from hours to roughly 30 minutes. We also examine Midjourney Medical’s proposed whole-body ultrasound scanner: what the prototype appears to do, what its creators are claiming, and why it should be viewed as a potential addition to the medical-imaging toolbox rather than a replacement for MRI. Finally, we return to the World Cup. Krishna takes on “Are You Smarter Than a Scientist?” by guessing the most common injuries in professional football. Then we investigate the Norway–England Skycam controversy: did the ball strike a cable, and why did its internal sensor appear not to detect it? We close with the data behind home-field advantage, referee bias, and the natural experiment created by crowdless matches during the COVID-19 pandemic. Support the show Donate: FFPod.com/donate Follow: @FFPod on X / Instagram / TikTok / Facebook

Hosted by Lester Nare and Krishna Choudhary , this episode is part two of our July 4th America 250 special : a celebration of the scientific, technological, institutional, and cultural breakthroughs that helped shape the United States into one of the most important scientific nations in human history. In part one, we traced American science from Benjamin Franklin and the founding documents through Sputnik, NASA, DARPA, Bell Labs, the transistor, information theory, nuclear physics, molecular biology, and the birth of the modern American science state. In part two, we pick up after Sputnik and follow the explosion of American science from 1958 to today. This episode covers the visual system, solar wind, perceptrons, impact cratering, pacemakers, neurotransmitter reuptake, cochlear implants, the genetic code, quarks, Bell’s theorem, density functional theory, the fast Fourier transform, immigration policy, electroweak unification, ARPANET, Apollo 11, dark matter, MRI, GPS, Unix, gravitational waves, ozone depletion, lithium batteries, Voyager, RNA splicing, recombinant insulin, quantum computing, the Space Shuttle, prions, PCR, cellular networks, telomeres, laser cooling, backpropagation, the Hubble Deep Field, Deep Blue, Sagittarius A*, cosmic acceleration, the Human Genome Project, CRISPR, mRNA vaccines, reusable rockets, LIGO, transformer models, black hole imaging, quantum supremacy, and the James Webb Space Telescope. The larger story is not just that America produced extraordinary discoveries. It is that those discoveries came from an ecosystem: universities, national labs, government agencies, industrial research labs, immigrant scientists, public investment, basic research, private enterprise, and a culture that repeatedly turned curiosity-driven science into civilization-changing technology. The episode closes by connecting that 250-year legacy to the current debate over federal science funding and the future of American scientific leadership. Explore the interactive timeline ffppod.com/America250 Support the show Donate: FFPod.com/donate Follow: @FFPod on X / Instagram / TikTok / Facebook

Hosted by Lester Nare and Krishna Choudhary , this episode is part one of our July 4th America 250 special : a celebration of the scientific, technological, institutional, and cultural innovations that helped shape the United States into one of the most important scientific nations in human history. For America’s 250th anniversary, we built an interactive timeline of the discoveries, inventions, institutions, and funding systems that enabled American science to grow from Benjamin Franklin’s experiments with electricity into the age of NASA, DARPA, Bell Labs, nuclear physics, molecular biology, modern computing, and big science. In part one, we go from Franklin’s discovery of the conservation of charge in 1747 through the Sputnik crisis in 1958. Along the way, we cover the Declaration of Independence, the Constitution’s science and patent clause, the first federal scientific agency, the rise of medical journals, the American system of manufacturing, the telegraph, anesthesia, land-grant universities, the telephone, Edison’s industrial R&D lab, the Michelson-Morley experiment, alternating current, the Wright brothers, the discovery of galaxies, the Manhattan Project, the transistor, information theory, the polio vaccine, the integrated circuit, and the mobilization of American science after Sputnik. This is not just a list of inventions. It is a story about compounding infrastructure: universities, journals, patents, philanthropy, federal agencies, industrial laboratories, war mobilization, immigrant scientists, basic research funding, and the feedback loop between science, technology, government, and culture. Explore the interactive timeline ffppod.com/America250 Support the show Donate: FFPod.com/donate Follow: @FFPod on X / Instagram / TikTok / Facebook

Hosted by Lester Nare and Krishna Choudhary , this episode is our World Cup special — a deep dive into the science, physics, engineering, and data behind the beautiful game. We start with the offside rule and the controversy around semi-automated VAR. How can a system decide whether a player is onside or offside by only a few inches? Krishna breaks the problem down like an experimental physicist: player speed, ball-contact time, camera frame rate, significant digits, and the error budget behind the line on screen. From there, we get into the actual technology: player tracking, digital twins, high-resolution cameras, and the connected match ball sensor that helps determine when the pass was played. Then we move from refereeing technology to the ball itself. Why does the 2026 World Cup ball look the way it does? How do Platonic solids, panel geometry, and surface seams affect the way a soccer ball flies? And why was the 2010 Jabulani ball so controversial? We go through drag, drag coefficients, wind tunnels, the drag crisis, golf ball dimples, and why the roughness of a ball can completely change its trajectory. Finally, we look at the hidden engineering of the World Cup pitch — real grass in NFL stadiums, LED grow lights, drainage systems, turfgrass science, and even 3D-printed cleat-foot testing devices — before ending with match momentum, possession value, hydration breaks, and the data science behind modern football analytics. Support the show Donate: FFPod.com/donate Follow: @FFPod on X / Instagram / TikTok / Facebook Show Notes Semi-automated offside technology and connected-ball systems Adidas Trionda — official 2026 World Cup match ball Aerodynamics of World Cup balls and the Jabulani drag-crisis controversy World Cup 2026 pitch engineering and turfgrass research Possession value and match momentum in football analytics

Hosted by Lester Nare and Krishna Choudhary , this episode marks Krishna’s return to the studio after paternity leave — and the timing could not be more fitting. Today’s deep dive is about inheritance: not just the classic Mendelian rules most of us learned in biology class, but the stranger, more dynamic world of non-Mendelian epigenetic inheritance . Starting from Gregor Mendel and his pea plants, Lester and Krishna rebuild the foundations of genetics from first principles: dominant and recessive alleles, Punnett squares, chromosomes, fruit flies, DNA, and the physical mechanism behind inherited traits. Then they move into the “software layer” of biology: epigenetics, DNA methylation, chromatin packaging, RNA interference, and paramutation — cases where the genetic code is present, but the cell’s machinery silences or rewrites how that code is used. The episode centers on a new Nature Genetics paper, “Non-Mendelian inheritance of DNA methylation patterns in mice,” which suggests that non-Mendelian epigenetic inheritance may be more widespread in mammals than previously understood. The conversation also covers why Oxford Nanopore sequencing made this kind of analysis possible, why methylation patterns can be hard to trace across generations, and what all of this could mean for disease risk, drug response, sex differences, evolution, and the long-running nature-versus-nurture debate. Summary Mendel’s rules — how pea plants, true-breeding lines, dominant and recessive traits, and Punnett squares gave us the first mathematical laws of inheritance. The first cracks in Mendel — how chromosomes, fruit flies, sex-linked traits, and linked genes showed that inheritance is more complicated than independent assortment. DNA as hardware, epigenetics as software — why having a gene is not the same thing as expressing it, and how methylation and chromatin packaging can silence parts of the genome. Paramutation — how one allele can change the expression state of another allele across generations, creating inheritance patterns that do not follow standard Mendelian expectations. Oxford Nanopore and the technology shift — why long-read sequencing and direct methylation detection make it possible to trace epigenetic marks back to the parent they came from. The mouse methylation paper — how researchers used collaborative cross mice to show that most methylation inheritance looks Mendelian, but a meaningful fraction appears to follow stranger non-Mendelian rules. Why it matters — potential implications for clinical genetics, disease risk, drug efficacy, sex-specific biology, and the relationship between nature and nurture. Support the show Donate: FFPod.com/donate Follow: @FFPod on X / Instagram / TikTok / Facebook

Hosted by Lester Nare and Krishna Choudhary, this episode is the second interview in our ongoing collaboration series with Carnegie Observatories. Krishna sits down with Dr. Michael Blanton, the new Director of the Carnegie Observatories, for a wide-ranging conversation on how astronomy became one of the most data-rich sciences, how the Sloan Digital Sky Survey helped change the culture around open data, what the next era of astronomical data science and AI could look like, and one of the galaxy mysteries Blanton still wants to solve: why the most massive galaxies in the universe stop forming stars.The conversation starts with Blanton’s Princeton roots and his work connected to the Sloan Digital Sky Survey, then moves into the culture of public astronomical data, the NYU Value-Added Galaxy Catalog, Vera Rubin Observatory, Carnegie’s role in the future of astronomy, the Magellan telescopes, astronomical archives, MaNGA and eBOSS, galaxy formation, dark matter, and even the science behind the black hole visualizations in Interstellar.Audio note: this was one of our first out-of-studio interviews, and there are a few minor audio issues in parts of the conversation. We appreciate your patience, and we’ll be better prepared for future field interviews.Also, if you’re in Los Angeles, Krishna will be giving a talk at Exploring Physics at UCLA, hosted by UCLA’s physics outreach organization Continuum, on Saturday, June 6 at the Fowler Museum. His talk runs from 9:30–10:30 AM.Register here: https://luma.com/3al1hj5h

Hosted by Lester Nare , this episode features astrophysicist Dan Gilman for a deep conversation on one of the biggest open questions in modern physics: what dark matter actually is . Starting from first principles, Lester and Dan walk through why the evidence for dark matter is now so strong, how strong gravitational lensing works, why tiny distortions in lensed light can reveal invisible clumps of matter, and how the next generation of surveys may transform the field. Krishna is out on family leave for this one, but the conversation stays fully in the From First Principles lane: grounded, visual, and science-first. Summary What dark matter is — Dan explains the basic case for dark matter, why it appears to interact only through gravity, and why multiple independent observations now point to the same conclusion. How strong gravitational lensing helps — the episode uses intuitive analogies like tides, fish tanks, and flashlights to explain how astronomers can infer the presence and structure of dark matter without seeing it directly. What Dan actually studies — the core of Dan’s work is building and testing simulations of lensed systems to see which dark matter theories best match reality. Why the next few years matter — Rubin, Roman, Euclid, and AI-assisted lens finding could dramatically increase the number of usable lens systems and sharpen the search for dark matter’s fundamental nature. Show Notes Dan Gilman on strong gravitational lensing and dark matter substructure Euclid mission overview Rubin Observatory overview Roman Space Telescope mission context

Hosted by Lester Nare and Krishna Choudhary , this interview features John Mulchaey , the 12th President of Carnegie Science and former Director of the Carnegie Observatories. The conversation starts with his early work on galaxy groups and dark matter, then expands into how Carnegie works as a scientific institution, what the Giant Magellan Telescope could unlock for exoplanets and astronomy, how science funding actually works, and why eclipse chasing is still one of the most magical experiences in science. Summary Galaxy groups and dark matter — Mulchaey explains why small galaxy groups matter more than most people realize, and how X-ray observations of hot gas helped make their masses measurable. Carnegie’s model — the interview gets into what makes Carnegie unusual: scientific freedom, long time horizons, and room to pursue surprising questions. The Giant Magellan Telescope — a look at why bigger telescopes matter, what GMT changes, and why exoplanet atmospheres are one of the biggest goals ahead. The bigger picture — science funding, philanthropy, how astronomy has changed, and why total solar eclipses still inspire so many astronomers. Support the show Donate: FFPod.com/donate Follow: @FFPod on X / Instagram / TikTok / Facebook Show Notes John Mulchaey leadership bio — Carnegie Sciencehttps://carnegiescience.edu/about/leadershipCarnegie Science appoints John Mulchaey as its 12th Presidenthttps://carnegiescience.edu/news/carnegie-science-appoints-john-mulchaey-its-12th-presidentGiant Magellan Telescope — official overviewhttps://giantmagellan.org/about-us/1993 NASA write-up on Mulchaey’s dark matter result in galaxy groupshttps://science.nasa.gov/missions/hubble/dark-matter-found-in-a-typical-cluster-of-galaxies/Carnegie Science Great North American Eclipse outreach recaphttps://carnegiescience.edu/yearbook/2024/science/great-north-american-eclipsePerot Museum eclipse partnership recaphttps://www.perotmuseum.org/events/solar-eclipses/

Hosted by Lester Nare and Krishna Choudhary , this rundown episode covers four new science stories at a high level: a huge new 3D ant imaging database built with synchrotron X-ray microtomography, a lunar agriculture experiment that grew chickpeas in simulated moon soil using fungi and worm waste, AI-assisted discovery of strange objects in the Hubble archive, and a new programmatic roadmap for room-temperature superconductivity. There is also another round of Are You Smarter Than a Scientist? in the middle. Summary Particle accelerators meet biodiversity — researchers built a massive high-resolution ant imaging resource, covering nearly 800 species and thousands of specimens, with AI-assisted 3D reconstruction. Moon farming gets weird — chickpeas were grown in lunar regolith simulant with help from mycorrhizal fungi and worm-derived compost, a first step toward sustainable off-world agriculture. AI found hidden anomalies in Hubble’s archive — AnomalyMatch sifted through roughly 100 million source cutouts in just days and surfaced new candidate lenses, mergers, and other rare objects. The superconductivity long game — a new PNAS perspective argues that room-temperature superconductivity is not ruled out by physics, and calls for a coordinated push to get there. Support the show Donate: FFPod.com/donate Follow: @FFPod on X / Instagram / TikTok / Facebook Show Notes High-throughput phenomics of global ant biodiversity — Nature Methods Bioremediation of lunar regolith simulant through mycorrhizal fungi and plant symbioses enables chickpea to seed — Scientific Reports Identifying astrophysical anomalies in 99.6 million source cutouts from the Hubble legacy archive using AnomalyMatch — Astronomy & Astrophysics The path to room-temperature superconductivity: A programmatic approach — PNAS

Hosted by Lester Nare and Krishna Choudhary , this special episode ranks the 26 scientists shown in Christopher Nolan’s Oppenheimer by one standard only: their contribution to fundamental science. Starting with the Manhattan Project figures near the bottom and working up through the giants of quantum mechanics, relativity, nuclear physics, and logic, the episode turns a movie cast list into a surprisingly deep walk through the history of modern physics. Summary A ranking framework that actually means something — this list is based on scientific achievement, not movie prominence, clout, or vibes. A tour of 20th-century science — from nuclear chain reactions and black holes to MRI, GPS, quantum mechanics, and information theory. The great debates — several placements are designed to provoke real argument, especially around how Oppenheimer compares to the physicists around him. A top tier full of monsters — the back half of the episode becomes a speedrun through some of the most influential scientific minds of the modern era. Support the show Donate: FFPod.com/donate Follow: @FFPod on X / Instagram / TikTok / Facebook

Hosted by Lester Nare and Krishna Choudhary , this episode is a deep dive into one of the strangest and most hard-fought materials science stories in decades: the claim that researchers have finally synthesized bulk hexagonal diamond, also known as lonsdaleite. They break down why this material matters, how it differs from ordinary cubic diamond, why scientists argued about its existence for more than 50 years, and what the new Nature paper actually did to convince skeptical reviewers. Summary Why hexagonal diamond matters — if real, it is a long-sought carbon phase that could be slightly harder than conventional diamond and useful in extreme industrial settings. The first-principles chemistry — carbon allotropes, x-ray crystallography, cubic diamond, and the ABAB stacking that makes hexagonal diamond different. The experimental breakthrough — how the new team engineered around the default pathway to ordinary diamond by controlling graphite orientation and pressure direction. The controversy — why the peer review was intense, and how the new paper relates to an earlier 2025 Nature paper with a similar claim. Support the show Donate: FFPod.com/donate Follow: @FFPod on X / Instagram / TikTok / Facebook