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.
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Nobel Prize in Chemistry 2026 Explained: Mirror Molecules (EP 63)
Episode 63
Wednesday, October 7, 2026 • Duration 01:20:37
Why does life favor one molecular mirror image? The 2026 Nobel Prize in Chemistry honors Henri B. Kagan and Kenso Soai for nonlinear effects and autocatalysis in asymmetric organic synthesis.
Lester Nare and Krishna Choudhary unpack the science from first principles: chirality, Pasteur's crystals, enantiomeric excess, and how a tiny imbalance can grow into an overwhelming preference for one molecular hand.
We connect Kagan's catalyst discoveries and the Soai reaction to medicines, the origins of biological handedness, and the serious concerns around hypothetical mirror life. Plus: symmetry in physics, Frances Oldham Kelsey and thalidomide, and our interpretation of a Nobel illustration.
CHAPTERS 00:00 Why life has a molecular handedness 01:33 Hello Internet 02:49 The 2026 Chemistry laureates 06:24 Chirality and mirror-image molecules 12:10 Pasteur and the history of handedness 19:36 Why is life's chemistry one-handed? 24:35 Frank and the origin-of-life puzzle 29:14 Enantiomeric excess explained 30:30 Kagan and nonlinear effects 38:58 FFP and symmetry in physics 42:20 Soai and asymmetric autocatalysis 51:28 Why chirality matters for medicine 58:21 What this does and does not explain about life 1:00:25 Mirror life and biological risk 1:10:37 Examining the Nobel illustration 1:14:10 Recap and Nobel week reflections
EDITORIAL NOTES Intro: the 50:50 example describes an unbiased synthesis, not all chemistry. The Soai reaction is a clue to amplification, not proof of how life began.
On-screen clarifications: 04:38 B-DNA is right-handed; Z-DNA can form a left-handed helix. 13:56 Pasteur separated sodium ammonium tartrate crystals. 18:48 L/D configuration does not specify optical rotation. 19:10 Proteins mainly use L-amino acids; DNA/RNA use D-sugars. 22:55 Mentos mainly triggers CO2 bubble nucleation. 27:18 Asymmetric catalysis and autocatalysis are distinct. 34:07 0.25 × 0.25 = 0.0625 = 6.25%. 36:31 Inactive mixed catalyst pairs are a simplified model. 37:55 The normalized product-ratio curve need not be parabolic. 42:04 Wu: preferential emission opposite spin; antineutrinos also emitted. 45:30 5-pyrimidyl alkanol; an alkanol is an alcohol. 47:10 The tiny-imbalance result is Sato et al. (2003), cited above. 47:40 A demonstration of symmetry breaking by asymmetric autocatalysis. 49:09 Above 99.5% ee means above 99.75% majority form, not exactly 100%. 49:57 0.00005% excess is 1 part in 2,000,000. 52:44 Thalidomide enantiomers interconvert in the body. 53:36 Merrell applied in the U.S.; Kelsey withheld approval. Trial exposure occurred. 1:02:09 Mirror-life catastrophe is a serious risk, not an observed outcome. 1:03:28 Antibodies are adaptive immunity, not innate immunity. 1:03:53 Impaired recognition does not mean proven total immune invisibility. 1:04:27 Some treatments might work; ecosystem protection is very difficult. 1:04:56 No reproducing mirror organism has been reported. 1:09:19 Chimeras and genetic modification are not interchangeable. 1:10:37 The Nobel-diagram critique is our interpretation, not an official correction. 1:11:51 Solid wedge: toward; hashed wedge: away; ordinary line: neither.
Breaking down science news so it makes sense to curious people everywhere.
Nobel Prize in Physics 2026 Explained: IceCube & Neutrinos
Season 1 · Episode 62
Tuesday, October 6, 2026 • Duration 01:02:18
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.
CHAPTERS 00:00 Hunting ghost particles beneath Antarctica 01:16 Hello Internet and Nobel Prize 05:30 What are neutrinos? 10:00 Neutrinos as cosmic messengers 15:02 The Oh-My-God particle 16:21 Cosmic-ray energies 19:07 Cosmic particle accelerators 22:28 Why look for neutrinos? 25:52 How to detect a neutrino 29:23 Cherenkov light 33:13 Building a neutrino observatory 37:17 From Antarctic ice to AMANDA 42:21 Building IceCube 44:59 Reading tracks and cascades 49:30 Backgrounds and the 2013 discovery 52:46 Tracing cosmic neutrino sources 54:16 Mapping the Milky Way 58:23 IceCube collaboration and Gen2 1:01:05 Closing and Nobel week
RESEARCH & FURTHER READING AMANDA in Antarctic ice (2001): https://doi.org/10.1038/35068509 IceCube detector and instrumentation (2017): https://doi.org/10.1088/1748-0221/12/03/P03012 First PeV neutrinos (2013): Astrophysical neutrino evidence (2013): Blazar TXS 0506+056 (2018): Archival blazar neutrino emission (2018): Milky Way neutrino map (2023): Gamma-ray burst constraints (2012): IceCube overview:
Nobel Prize in Medicine 2026 Explained: Optogenetics (EP 61)
Season 1 · Episode 61
Monday, October 5, 2026 • Duration 01:11:23
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
2026 Nobel Prize Predictions: Medicine, Physics & Chemistry (EP 60)
Season 1 · Episode 60
Saturday, October 3, 2026 • Duration 40:31
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
Golden Goose Awards 2026: The Science Behind the Winners (Part 1) (EP 59)
Season 1 · Episode 59
Tuesday, September 29, 2026 • Duration 02:07:22
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
What OpenAI Actually Did to Navier-Stokes (EP 58)
Season 1 · Episode 58
Thursday, September 24, 2026 • Duration 04:09:02
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 fluid
Velocity fields, incompressibility, pressure and the nonlinear convective term
Why viscosity smooths a fluid while nonlinear motion can create finer structure
What finite-time blowup means, and why simulation is different from proof
How forced and unforced equations differ, and why those assumptions matter
Earlier work on Euler, Boussinesq and related fluid equations
OpenAI’s claimed result, Lean verification and the scope of the theorem
The dispute over scientific credit and the human research behind AI-assisted work
The METR investigation of the Hugging Face incident
Emergence World and long-running multi-agent experiments
AI-assisted biological discovery, oversight and recursive self-improvement
Separating demonstrated capabilities from claims and future scenarios
Chapters
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 Agents3:08:57 The METR report and Hugging Face incident3:23:23 AI Risk, Oversight and the Race Ahead3:38:51 AI Discovery Beyond Mathematics3:52:47 Why “just turn it off” gets complicated4:06:47 Closing thoughts and what comes next4:08:46 Outro
What’s Next in Science? Nobel Prizes, Space Missions & More (EP 57)
Season 1 · Episode 57
Monday, September 14, 2026 • Duration 01:03:30
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/
ESA / JAXA BepiColombo: https://www.esa.int/Science_Exploration/Space_Science/BepiColombo
The Yak Mutation That Could Help Repair the Brain (EP 56)
Season 1 · Episode 56
Monday, September 7, 2026 • Duration 01:35:37
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
Why Spin Qubits Will Win the Quantum Race (Part 2) (EP 55)
Season 1 · Episode 55
Monday, August 31, 2026 • Duration 03:46:20
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.
How Quantum Computing Actually Works (Part 1) (EP 54)
Season 1 · Episode 54
Thursday, August 20, 2026 • Duration 02:11:10
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.
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EDITORIAL NOTES Intro: 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.
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
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Breaking down science news so it makes sense to curious people everywhere.
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)
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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.
