From First Principles

Krishna Choudhary and Lester Nare
  • 4.9 (195)
  • Science
  • Updated Weekly

From First Principles is a fast, funny, and rigorous breakdown of the biggest science stories of the week, hosted by Lester Nare and physicist Krishna Choudhary, PhD. We go past headlines into the actual mechanics: what happened, why it matters, and what everyone’s missing. Expect physics, space, AI, energy, biotech, and the occasional “wait… is that real?” story. If you’re curious, skeptical, and you like learning in public — you’re in the right place.

  1. 20h ago

    Nobel Prize in Physics 2026 Explained: IceCube & Neutrinos

    Why build a telescope inside a billion tons of Antarctic ice? The 2026 Nobel Prize in Physics recognizes Francis Halzen's work on IceCube and the discovery of high-energy neutrinos from the cosmos. In Episode 62 of From First Principles, Lester Nare and Krishna Choudhary explain neutrinos from the ground up: why these elusive particles make powerful cosmic messengers, how faint flashes of Cherenkov light reveal their interactions, and why detecting them requires an observatory buried deep beneath the South Pole. We follow the path from beta decay and the first neutrino experiments to AMANDA, IceCube's construction, the 2013 astrophysical breakthrough, a distant blazar, and a neutrino map of the Milky Way. Along the way: cosmic rays, the Oh-My-God particle, tracks versus cascades, and the international collaboration behind the discovery. CHAPTERS00:00 Hunting ghost particles beneath Antarctica01:16 Hello Internet and Nobel Prize05:30 What are neutrinos?10:00 Neutrinos as cosmic messengers15:02 The Oh-My-God particle16:21 Cosmic-ray energies19:07 Cosmic particle accelerators22:28 Why look for neutrinos?25:52 How to detect a neutrino29:23 Cherenkov light33:13 Building a neutrino observatory37:17 From Antarctic ice to AMANDA42:21 Building IceCube44:59 Reading tracks and cascades49:30 Backgrounds and the 2013 discovery52:46 Tracing cosmic neutrino sources54:16 Mapping the Milky Way58:23 IceCube collaboration and Gen21:01:05 Closing and Nobel week RESEARCH & FURTHER READINGAMANDA in Antarctic ice (2001): https://doi.org/10.1038/35068509IceCube detector and instrumentation (2017): https://doi.org/10.1088/1748-0221/12/03/P03012First PeV neutrinos (2013): https://doi.org/10.1103/PhysRevLett.111.021103Astrophysical neutrino evidence (2013): https://doi.org/10.1126/science.1242856Blazar TXS 0506+056 (2018): https://doi.org/10.1126/science.aat1378Archival blazar neutrino emission (2018): https://doi.org/10.1126/science.aat2890Milky Way neutrino map (2023): https://doi.org/10.1126/science.adc9818Gamma-ray burst constraints (2012): https://doi.org/10.1038/nature11068IceCube overview: https://icecube.wisc.edu/science/icecube/ EDITORIAL NOTESIntro: the 2013 breakthrough was high-energy astrophysical neutrinos. Lower-energy supernova neutrinos were detected in 1987. On-screen clarifications:06:45 Beta-minus decay produces a proton, electron and electron antineutrino.11:10 Davis studied solar neutrinos; Koshiba's team detected SN 1987A neutrinos.17:50 The cosmic-ray knee and ankle are not fixed distance boundaries.19:38 Required accelerator size depends on magnetic-field strength.24:18 Ground-based telescopes also detect gamma rays through air showers.27:48 W interactions produce charged leptons; Z scattering preserves neutrino flavor.34:06 The underwater concept dates to 1960; DUMAND developed in the 1970s.36:09 Baikal holds about one-fifth of unfrozen surface freshwater.38:53 Earth filters muons but also absorbs many very-high-energy neutrinos.41:26 Pressure converts air bubbles into clathrates, reducing light scattering.42:28 Construction finished in December 2010; full operations began in May 2011.44:27 Sensors are DOMs; DeepCore is a densely instrumented detector region.45:47 Timing gives direction; light yield and pattern help estimate energy.49:44 Upgoing events can still be atmospheric neutrinos.53:12 TXS 0506+056 is about 3.7 billion light-years away.56:38 Long GRBs often involve collapsing stars; short GRBs often involve mergers. WATCH & FOLLOWFull video: https://youtu.be/eMahxeBj5k0Episode notes: https://ffppod.com/episodes/ep62Medicine Nobel explained: https://youtu.be/PKAYqhy8xf8Follow @FFPPod on Instagram, TikTok, X and Facebook. From First Principles: Breaking down science news so it makes sense to curious people everywhere.

  2. 1d ago

    Nobel Prize in Medicine 2026 Explained: Optogenetics (EP 61)

    How do you prove what a brain cell actually does? The 2026 Nobel Prize in Medicine celebrates a remarkable answer: give cells a light-sensitive protein, then switch their activity on or off with light. In Episode 61 of From First Principles, Lester Nare and Krishna Choudhary explain optogenetics from the ground up and trace the discoveries of Peter Hegemann, Georg Nagel and Karl Deisseroth. We follow the story from algae swimming toward light to channelrhodopsins, precisely controlled neurons, and experiments probing memory, reward and behavior. Then we explore heart-brain connections, early attempts to restore vision, and what these experiments can and cannot tell us. CHAPTERS 00:00 The discovery that put brain cells under light control 02:34 Hello Internet 03:28 2026 Medicine Nobel and optogenetics 05:38 Understanding the brain 08:42 From correlation to causation 18:13 Controlling neurons with light 21:25 Early optogenetics and the chARGe system 24:17 Light-sensitive microbial proteins 26:26 Algae and phototaxis 31:42 Discovering channelrhodopsins 34:42 Nagel and light-gated ion channels 40:55 Controlling mammalian neurons 50:19 Expanding the optogenetic toolkit 56:10 Neural circuits and behavior 59:02 Memory, reward and reinforcement 1:02:53 Heart rhythm and emotion 1:04:02 Beyond the brain and toward medical treatments 1:06:56 Implications and limits 1:09:10 Closing and Nobel week RESEARCH & FURTHER READING Full paper list: https://ffppod.com/episodes/ep61 Nobel Prize announcement and background: https://www.nobelprize.org/prizes/medicine/2026/summary/ Optical control of neurons: https://doi.org/10.1038/nn1525 Memory recall in mice: https://doi.org/10.1038/nature11028 Partial visual recovery: https://doi.org/10.1038/s41591-021-01351-4 EDITORIAL NOTES On-screen clarifications are included at these timestamps: 13:46 The Jennifer Aniston neuron was recorded in human patients. Selective firing alone did not establish that it causes recognition. 30:34 Vertebrate rhodopsin is a GPCR. In rods and cones, light closes cGMP-gated channels and causes hyperpolarization. 35:12 Xenopus oocytes are immature frog egg cells, not embryos. 39:52 Calcium entry triggers neurotransmitter release; neurotransmitters carry the signal across the synapse. ChR2 conducts several positive ions, not just calcium. 52:17 Halorhodopsin is a light-driven chloride pump, not a channel. 1:03:18 The heart-pacing study expressed ChRmine in mouse heart muscle cells, not neurons. Animal studies and early clinical results are distinguished from established treatments. WATCH & LISTEN Watch this episode: https://youtu.be/PKAYqhy8xf8 Our Nobel predictions: https://open.spotify.com/episode/4xuoH7WhM5svq8vEJPL3Ce Support: https://ffppod.com/donate Contact: https://ffppod.com/contact Follow @FFPPod. Breaking down science news so it makes sense to curious people everywhere.

  3. 3d ago

    2026 Nobel Prize Predictions: Medicine, Physics & Chemistry (EP 60)

    Who could win the 2026 Nobel Prizes? From the science behind Ozempic to quantum interference and droplets inside living cells, Lester Nare and Krishna Choudhary make their picks for Medicine, Physics and Chemistry, and explain the discoveries behind them. In Episode 60 of From First Principles, we explore seven research areas with a case for Nobel recognition: GLP-1, optogenetics, optical coherence tomography, the Aharonov–Bohm effect, atomic force microscopy, biomolecular condensates and Buchwald–Hartwig coupling. We also discuss Michael Berry’s geometric phase and the awkward question of how a prize limited to three people recognizes discoveries built by larger teams. These are our predictions, recorded before the 2026 announcements. Medicine, Physics and Chemistry will be announced October 5–7. Which discovery, and which researchers, would you pick? Tell us in the comments, then join us for our Nobel week breakdowns. CHAPTERS 00:00 The science that could win a Nobel Prize 00:57 Hello Internet: our 2026 predictions 02:03 Medicine: GLP-1 and the science behind Ozempic 07:41 Medicine: optogenetics and controlling neurons with light 13:16 Medicine: optical coherence tomography 16:28 Golden Goose Awards and FFP updates 18:39 Physics: the Aharonov–Bohm effect and geometric phase 27:37 Physics: atomic force microscopy 32:04 Chemistry: biomolecular condensates 36:36 Chemistry: Buchwald–Hartwig coupling 38:42 Your predictions and our Nobel week plans RESEARCH & FURTHER READING Foundational papers and background for the discoveries discussed: GLP-1: Mojsov, Weir & Habener (1987) https://doi.org/10.1172/JCI112855 Optogenetics: Boyden et al. (2005) https://doi.org/10.1038/nn1525 Optical coherence tomography: Huang et al. (1991) https://doi.org/10.1126/science.1957169 Aharonov–Bohm effect (1959) https://doi.org/10.1103/PhysRev.115.485 Berry’s geometric phase (1984) https://doi.org/10.1098/rspa.1984.0023 Atomic force microscopy: Binnig, Quate & Gerber (1986) https://doi.org/10.1103/PhysRevLett.56.930 Biomolecular condensates: Brangwynne et al. (2009); Li et al. (2012) https://doi.org/10.1126/science.1172046 https://doi.org/10.1038/nature10879 Buchwald–Hartwig coupling: Paul et al. (1994); Guram et al. (1995) https://doi.org/10.1021/ja00092a058 https://doi.org/10.1002/anie.199513481 Official Nobel announcement schedule: https://www.nobelprize.org/prizes/about/prize-announcement-dates/ EDITORIAL NOTES 19:30 David Bohm later held a professorship at Birkbeck, University of London (1961–1987); he did not spend the rest of his career in Brazil. 33:23 The ribosome-producing compartment discussed is the nucleolus, not the nucleosome. These corrections also appear on screen. WATCH & EXPLORE YouTube: https://youtu.be/MgOpbh5VUGE Episode page and research library: https://ffppod.com/episodes/ep60 Support: https://ffppod.com/donate Follow @FFPPod on X / Instagram / TikTok / Facebook Breaking down science news so it makes sense to curious people everywhere.

  4. Sep 29

    Golden Goose Awards 2026: The Science Behind the Winners (Part 1) (EP 59)

    What connects a noise complaint, holiday lights seen from space, and the physics of a coffee stain? Three unexpected paths from basic research to discoveries with real-world impact. Krishna Choudhary and Lester Nare explore the science behind the 2026 Golden Goose Awards: Zhen Xu's work on histotripsy, NASA's Black Marble nighttime satellite data, and Sidney Nagel's discoveries in soft matter physics. We start with focused ultrasound and the tiny bubbles that can break apart targeted tissue, tracing the journey from early laboratory experiments to clinical research on liver tumors. Then we look at how Earth's nighttime lights reveal power outages, disaster recovery, and changing human activity. Finally, falling drops, coffee stains, and jammed grains open up a world of robotic grippers and materials that can be trained and retrained. The thread connecting all three stories is the unexpected value of federally funded basic research. Part 2 will feature conversations with the award-winning researchers and AAAS CEO Sudip Parikh. CHAPTERS 00:00 Golden Goose Awards trailer 01:19 Introducing our Golden Goose special 02:42 Zhen Xu: From a noise complaint to histotripsy 05:57 The early ultrasound experiments 13:42 Controlling cavitation with microtripsy 20:29 Tumor destruction and the immune response 28:33 Histotripsy through the skull 37:23 The HOPE4LIVER clinical trial 43:55 Why basic research needs time 47:17 FFP updates and supporting the show 49:20 NASA Black Marble: Holiday lights from space 55:29 Turning night lights into reliable data 1:01:36 Hurricane Maria and unequal recovery 1:08:12 COVID-19 and changing nighttime activity 1:10:16 Mapping access to electricity 1:15:20 Where Earth is brightening and dimming 1:32:57 Sidney Nagel and the physics of everyday life 1:37:07 The science of a falling drop 1:46:02 Why coffee leaves a ring 1:51:04 Jamming: When grains become rigid 1:53:35 A robotic gripper filled with grains 1:55:39 Why air pressure changes a splash 1:58:55 Materials that can be trained and retrained 2:03:26 The payoff from curiosity 2:05:29 Coming in Part 2 2:07:06 Outro FEATURED RESEARCH Histotripsy: The #HOPE4LIVER single-arm pivotal trial (Radiology, 2024) https://doi.org/10.1148/radiol.233051 NASA's Black Marble nighttime lights product suite (Remote Sensing of Environment, 2018) https://doi.org/10.1016/j.rse.2018.03.017 Training and retraining liquid crystal elastomer metamaterials for pluripotent functionality (PNAS, 2025) https://doi.org/10.1073/pnas.2504304122 WATCH ON YOUTUBE https://youtu.be/rDInUEtTojg EXPLORE FFP Website: https://ffppod.com Science Funding Tracker: https://ffppod.com/funding Science Transfer Portal: https://ffppod.com/transfers America 250: https://ffppod.com/America250 SUPPORT THE SHOW https://ffppod.com/donate FOLLOW @FFPPod on X / Instagram / TikTok / Facebook

  5. Sep 24

    What OpenAI Actually Did to Navier-Stokes (EP 58)

    What does it mean to solve an equation that describes almost every fluid around us, from the air over a wing to the water swirling down a drain? In Episode 58 of From First Principles, Lester Nare and Krishna Choudhary build the Navier-Stokes equations from the ground up before digging into OpenAI’s claimed breakthrough and the debate surrounding it. Summary How Newton’s laws become equations for a moving fluidVelocity fields, incompressibility, pressure and the nonlinear convective termWhy viscosity smooths a fluid while nonlinear motion can create finer structureWhat finite-time blowup means, and why simulation is different from proofHow forced and unforced equations differ, and why those assumptions matterEarlier work on Euler, Boussinesq and related fluid equationsOpenAI’s claimed result, Lean verification and the scope of the theoremThe dispute over scientific credit and the human research behind AI-assisted workThe METR investigation of the Hugging Face incidentEmergence World and long-running multi-agent experimentsAI-assisted biological discovery, oversight and recursive self-improvementSeparating demonstrated capabilities from claims and future scenariosChapters 00:00 Can AI solve Navier-Stokes? 00:34 Episode introduction 02:20 Navier-Stokes: Mathematics Meets AI 10:20 Building the Equations of Fluid Motion 21:34 Velocity fields, divergence and incompressibility 34:33 Acceleration and the convective term 52:18 Why Fluid Motion Is Nonlinear 1:02:08 Pressure, Euler and the Missing Physics 1:14:50 How Viscosity Changes Everything 1:33:36 Solving Equations vs. Simulating Fluids 1:44:59 Can a Smooth Fluid Blow Up? 2:13:52 The Road to the Claimed Breakthrough 2:31:13 Inside the Claimed Navier-Stokes Proof 2:48:26 The Dispute Over Scientific Credit 3:07:23 From Chatbots to Agents 3:08:57 The METR report and Hugging Face incident 3:23:23 AI Risk, Oversight and the Race Ahead 3:38:51 AI Discovery Beyond Mathematics 3:52:47 Why “just turn it off” gets complicated 4:06:47 Closing thoughts and what comes next 4:08:46 Outro Featured Research OpenAI’s Navier-Stokes announcement Tristan Buckmaster’s statement METR investigation Emergence World AI-assisted enzyme discovery Explore FFP ffppod.com ffppod.com/funding ffppod.com/transfers ffppod.com/America250 Watch on YouTube youtu.be/NGfGw1tGxUY Support the show ffppod.com/donate Follow @FFPPod on X / Instagram / TikTok / Facebook

  6. Sep 14

    What’s Next in Science? Nobel Prizes, Space Missions & More (EP 57)

    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.

  7. Sep 7

    The Yak Mutation That Could Help Repair the Brain (EP 56)

    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 communicationHow multiple sclerosis damages myelin and why the brain’s natural repair process eventually failsWhy oligodendrocyte precursor cells can remain present in damaged tissue without successfully rebuilding myelinWhy current therapies are better at slowing further damage than restoring what has already been lostThe challenge of getting drugs across the blood-brain barrier while maintaining target specificityHow evolutionary pharmacology has previously produced medicines from adaptations found in snakes and Gila monstersThe RETSAT Q247R variant identified in animals adapted to the hypoxic environment of the Tibetan PlateauHow researchers engineered the high-altitude variant into mice and tested its effect on myelinThe surprising discovery that neurons — rather than the myelin-producing cells themselves — generate the key repair signalHow RETSAT increases ATDR, which neurons convert into ATDRAHow ATDRA activates RXR-γ in oligodendrocyte precursor cells and promotes their differentiationHow administration of ATDR promoted remyelination across multiple preclinical modelsWhy the result is scientifically promising but still far from a proven human treatmentFeatured 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 FFPffppod.comffppod.com/fundingffppod.com/transfersffppod.com/America250 Support the showffppod.com/donate Follow@FFPPod on X / Instagram / TikTok / Facebook

  8. Aug 31

    Why Spin Qubits Will Win the Quantum Race (Part 2) (EP 55)

    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

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4.9
out of 5
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About

From First Principles is a fast, funny, and rigorous breakdown of the biggest science stories of the week, hosted by Lester Nare and physicist Krishna Choudhary, PhD. We go past headlines into the actual mechanics: what happened, why it matters, and what everyone’s missing. Expect physics, space, AI, energy, biotech, and the occasional “wait… is that real?” story. If you’re curious, skeptical, and you like learning in public — you’re in the right place.

Information

  • Creator
    Krishna Choudhary and Lester Nare
  • Years Active
    2025 - 2026
  • Episodes
    62
  • Rating
    Explicit
  • Copyright
    © Krishna Choudhary and Lester Nare
  • Show Website
    From First Principles

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