632nm

How do you measure something as small as a single electron or map quantum behavior at the nanoscale?

In this episode, Misha spoke with Amir Yacoby, professor at Harvard University, about the cutting edge of quantum sensing and the experimental tools redefining how we probe the quantum world.

Yacoby explains how physicists build ultra-sensitive detectors, from single-electron transistors to quantum dots and NV centers in diamond, that can measure charge, spin, and magnetic fields with extraordinary precision. These tools make it possible to study both strongly correlated systems, like those exhibiting the fractional quantum Hall effect, and isolated quantum systems used as qubits.

We explore how accidental discoveries in the lab can evolve into entirely new sensing techniques, including momentum-resolved tunneling and nanoscale imaging methods. The conversation also highlights how quantum sensors are enabling researchers to bridge two regimes: complex many-body systems and controllable quantum devices, opening the door to new insights in topological physics and quantum information processing.

Whether you're interested in quantum measurement, nanoscale imaging, or the future of quantum technologies, this episode offers a detailed look at how new instruments are driving discovery at the frontiers of physics.

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Mikhail Shalaginov: https://x.com/MYShalaginov

Michael Dubrovsky: https://x.com/MikeDubrovsky

Xinghui Yin: https://x.com/XinghuiYin

Subscribe:

Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269

Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR

Website: https://www.632nm.com

Timestamps:
00:00 - Intro
01:23 - The Process of Creating Quantum Tools
11:28 - Graduate School at Weizmann
14:51 - From Aerospace to Condensed Matter
26:53 - Starting at Harvard
39:44 - Working at Bell Labs
47:42 - Diamond NV Centers
1:00:52 - Spin Waves
1:16:10 - SQUIDs
1:29:57 - State of the Art Sensors
1:33:08 - Motivations for Building Better Sensors
1:36:52 - Fabrication Challenges
1:40:14 - New Sensors
1:45:49 - Majoranas
1:53:25 - Finding New Applications for Sensors
1:57:16 - The Use of AI in Physics
1:58:55 - Advice for Young Scientists 

How do you turn a flat piece of nanostructured material into a secure biometric sensor?

In this episode, we speak with Rob Devlin, co-founder and CEO of Metalenz, about how metasurfaces are transforming optics and enabling a new generation of biosecure sensing. Devlin explains how engineers can control light at the subwavelength scale to replace bulky lens stacks with a single flat surface, and why the real breakthrough isn’t just miniaturization, but the ability to mass-produce optics in semiconductor fabs.

We explore how Metalenz scaled metasurfaces from academic prototypes into millions of devices, and what it takes to design optics for manufacturing. Devlin breaks down the transition from building one perfect device in a cleanroom to producing millions that all meet tight specifications.

The conversation focuses on polarization imaging as a new information channel in consumer devices. Unlike traditional cameras that capture only intensity and color, polarization reveals material properties. This enables a new approach to facial recognition that is both more secure and more compact than existing systems.

Rob also shares the story behind Metalenz, from its origins in a Harvard lab to partnerships with major semiconductor manufacturers, and how the company navigated the challenges of finding product-market fit, scaling fabrication, and building a new sensing stack from scratch.

Whether you’re interested in optics, nanofabrication, consumer electronics, or the future of biometric security, this episode explores how controlling light at the nanoscale is opening entirely new possibilities for sensing and identity verification.

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Instagram: https://www.instagram.com/632nmpodcast?utm_source=ig_web_button_share_sheet&igsh=ZDNlZDc0MzIxNw==
LinkedIn: https://www.linkedin.com/company/632nm/about/
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Mikhail Shalaginov: https://x.com/MYShalaginov
Michael Dubrovsky: https://x.com/MikeDubrovsky
Xinghui Yin: https://x.com/XinghuiYin

Subscribe:
Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269
Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR
Website: https://www.632nm.com

Timestamps:
00:00 - Intro
01:22 - Making Metalenses Mass-Producible
10:58 - Metasurfaces for Polarimetry
17:10 - Face ID Security and Pitfalls
24:47 - Polar ID Principles
29:02 - Polar ID Demo
39:58 - Meeting Federico Capasso
50:43 - Developing Metasurface Fabrication Techniques
55:58 - Founding Metalenz 
1:11:44 - Future of Metalenz and Metasurfaces

#photonics #faceid #biometrics #metasurface #biosecurity #optics

Are data centers in space physically possible, or just another overhyped idea?

In this episode, we speak with Philip Johnston, CEO of Starcloud, about the technical and economic case for putting AI infrastructure in orbit. The idea has gone viral in recent months, drawing strong criticism from science communicators like Scott Manley, Kyle Hill, and Hank Green, but rarely with detailed engagement on the underlying assumptions.

We examine whether space-based data centers can compete with terrestrial infrastructure, and what constraints actually matter: energy generation, cooling, launch costs, and manufacturing at scale. Johnston walks through the core economic model behind Starcloud, including assumptions about SpaceX’s Starship, the cost of solar power in orbit, and why removing terrestrial constraints like land use, permitting, and energy storage could fundamentally change how compute is deployed.

We discuss the physics of radiative cooling in space, the challenges of operating GPUs in a radiation environment, and how orbital systems compare to Earth-based data centers in terms of efficiency and cost structure. The conversation also explores broader questions around AI’s growing energy demands, the limits of terrestrial infrastructure, and whether shifting compute off-world is a niche solution or a long-term inevitability.

Whether you’re interested in space technology, AI infrastructure, energy systems, or the economics of large-scale computing, this episode offers a detailed look at one of the most debated ideas in modern engineering, and a rare opportunity to hear its strongest arguments laid out in full.

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Substack: https://632nmpodcast.substack.com/

Follow our hosts!
Mikhail Shalaginov: https://www.linkedin.com/in/mikhail-shalaginov/
Michael Dubrovsky: https://x.com/MikeDubrovsky
Xinghui Yin: https://x.com/XinghuiYin

Subscribe:
Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269
Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR
Website: https://www.632nm.com

Timestamps:
00:00 - Intro
01:12 - What is Starcloud?
02:44 - Why do data centers need to go to space?
06:15 - Can’t we just build more solar panels on earth?
11:10 - Economic analysis of Starcloud
19:56 - How does Starcloud’s cooling work?
28:26 - Training an LLM in space
32:07 - Addressing critics on space Twitter
34:23 - Is Starcloud overfunded?
35:59 - Will demand for data centers keep going up?
38:11 - GPU lifespan and disposal in space
39:47 - Bus structures
41:43 - Starcloud’s origin and founders
49:29 - Fundraising, Competition, and Meeting Expectations
53:29 - Satellite size and collisions
56:29 - Manufacturing Bottlenecks
1:00:20 - Starcloud 1 tests
1:01:57 - Acceleration after YC
1:03:43 - Testing on Earth
1:05:06 - Motivations for Starcloud
1:06:45 - Data centers on the Moon
1:08:12 - Interacting with AI companies
1:08:18 - What’s next for Starcloud?
1:14:01 - Other uses for Starcloud satellites
1:17:56 - Lunar hotels and space elevators
1:24:28 - Complementary business ideas to Starcloud
1:29:51 - Philip’s competitive twin
1:32:18 - Philip and Mike’s thoughts on YC
1:34:45 - Advice for young entrepreneurs

#datacenter #aidatacenter #starlink #spacex #falcon9 #starcloud

How do you actually make quantum algorithms work on real hardware?

Build your own quantum circuits in Crumble: https://algassert.com/crumble

In this episode, we speak with Craig Gidney of Google Quantum AI, whose work focuses on the practical realities of building fault-tolerant quantum computers. Gidney explains how seemingly small implementation choices, like how you perform arithmetic, can dominate the cost of entire quantum algorithms.

We explore why factoring small numbers like 15 in Shor's algorithm can be misleadingly easy, and why scaling to larger numbers requires dramatically more resources due to operations like modular multiplication. He breaks down how quantum circuits are often dominated by classical reversible logic, and why optimizing these routines is critical for making quantum computing viable.

The conversation covers quantum error correction, including why T gates are especially expensive, how magic state factories works, and how different hardware architectures change what “cost” even means. Gidney also explains how resource estimates for breaking cryptography have dropped by orders of magnitude and what drove those improvements.

We also dive into the tools he built, including Stim, Quirk, and Crumble, which help researchers simulate noise, visualize circuits, and track how errors propagate through complex systems. Gidney shares his unconventional path into the field, the role of intuition and tooling in discovery, and how software engineering shapes modern quantum research.

Whether you’re interested in quantum computing, error correction, cryptography, or the engineering challenges behind scalable quantum systems, this episode offers a clear and grounded look at what it really takes to turn quantum algorithms into reality.

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Substack: https://632nmpodcast.substack.com/

Follow our hosts!
Mikhail Shalaginov: https://www.linkedin.com/in/mikhail-shalaginov/
Yudong Cao: https://www.linkedin.com/in/yudong-cao-25b6a929/

Subscribe:
Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269
Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR
Website: https://www.632nm.com

Timestamps:
00:00 - Intro
01:22 - Shor’s Algorithm
04:02 - Why are Arithmetic Operations Important?
08:35 - Why are T-Gates Important for QEC?
13:47 - Motivations for Creating Crumble and STIM
18:40 - Can AI Code Quantum Simulators?
22:32 - Journey into Learning Quantum
26:50 - How to Enter the Field of Quantum Computing
31:16 - From Starcraft to Software Engineering
36:05 - Crumble Demo
53:18 - Quirk Demo
1:00:48 - Estimating Resources for Quantum Computation
1:08:58 - Optimizing Measurements for Computation
1:16:40 - How Many Qubits Do We Actually Need?
1:30:49 - Other Research Areas for Improving Fault Tolerance
1:41:23 - Elliptic Curve Discrete Logarithm Problem
1:46:55 - New Tools for Quantum Computing
1:50:23 - What Would Craig Do with Unlimited Funding?
1:52:28 - How Learning Has Changed for Craig with Experience
1:57:31 - Riding the Wave of Innovation vs Sticking to One Idea
1:59:53 - Advice for Young Scientists

#quantumcomputing #quantumphysics #computerscience #googleai #googlequantum

How do neurons convert electrical signals into chemical messages in under a millisecond?

In this episode, we speak with Thomas Südhof, Stanford neuroscientist and Nobel laureate whose discoveries revealed the molecular machinery that allows neurons to communicate at synapses. Südhof explains how an electrical impulse traveling down a neuron triggers the rapid release of neurotransmitters, transforming an electrical signal into a chemical one that can be received by the next cell.

We explore the remarkable precision of synaptic transmission, including how calcium ions trigger vesicle fusion, how specialized proteins organize the release machinery, and why this entire process unfolds on the timescale of a single millisecond. Südhof walks us through the molecular components that make this possible, including the proteins that dock neurotransmitter-filled vesicles and control their release.

The conversation also examines how these discoveries reshaped modern neuroscience by revealing the fundamental mechanisms underlying neuronal communication. Südhof discusses how synapses operate as highly specialized molecular machines and how disruptions in synaptic signaling are linked to neurological and psychiatric disorders.

Whether you’re interested in neuroscience, synapses, brain signaling, neurotransmitters, or the molecular basis of thought, this episode offers a clear explanation of how neurons translate electricity into chemistry, and how this microscopic process makes brain communication possible

Follow us for more technical interviews with the world’s greatest scientists:
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Michael Dubrovsky: https://x.com/MikeDubrovsky
Xinghui Yin: https://x.com/XinghuiYin

Subscribe:
Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269
Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR
Website: [https://www.632nm.com](https://www.632nm.com/)

Timestamps:
00:00 - Intro
01:23 - What is a Synapse?
07:01 - History of Synapse Discovery
12:54 - How Electron Microscopy Helped Neuroscience
15:11 - Early Electrophysiological Experiments
18:31 - Why are Neurotransmitters Needed At All?
21:25 - Electrical Connections Between Cells
22:48 - How Signal Diversity is Created in Synapses
29:04 - Why are Synapses Chemical?
31:06 - How Tom Began his Neuroscience Career
39:32 - Emerging Tools that Allowed for Researching Synapses
44:16 - Discerning Protein Function
49:36 - Discovering Mechanism through Data
52:15 - Isolating Membrane Proteins
55:09 - Voltage Gates
57:50 - How Synapses Change Over Time
1:02:14 - How are Synapses Formed?
1:10:22 - The Need for New Tools
1:11:53 - Implications for Drug Discovery
1:17:07 - Exploring the Mouse Hippocampus
1:22:35 - Tom’s Work on LDL Receptors
1:26:33 - Understanding Molecular Logic

#neuroscience #neuroplasticity #nobelprize #hubermanlab #neurobiology 

How do engineers solve problems that seem to violate the laws of physics?

In this episode, we speak with Dan Gelbart, a prolific inventor and precision engineer, about what it really means to work at the limits of physical law. From lasers and optical systems to ultra-precision manufacturing and semiconductor tools, Gelbart has spent decades designing systems where nanometers, noise, and nonlinearities matter, and where small misunderstandings of physics can block real progress.

We discuss the story of the first working laser, built by Theodore Maiman, and why it succeeded only after questioning widely accepted assumptions. Gelbart explains how many “impossible” engineering problems aren’t forbidden by physics at all: they’re constrained by measurement errors, incomplete models, or failure to explore edge cases like pulsed operation, material effects, and boundary conditions.

We explore precision metrology, high-resolution imaging for satellite systems, the culture of engineering education, and the difference between a true physical limit and a design constraint. Gelbart reflects on why mastering fundamentals, mechanics, optics, electromagnetism, matters more than chasing trends, and how breakthroughs often come from carefully re-examining what others assume cannot be done.

Whether you’re interested in physics, engineering, semiconductor manufacturing, lasers, or the philosophy of technological innovation, this conversation offers a rigorous look at how engineers operate at the edge of what nature allows, and sometimes push beyond what others think is possible.

Follow us for more technical interviews with the world’s greatest scientists:
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LinkedIn: https://www.linkedin.com/company/632nm/about/
Substack: https://632nmpodcast.substack.com/

Follow our hosts!
Mikhail Shalaginov: https://x.com/MYShalaginov
Michael Dubrovsky: https://x.com/MikeDubrovsky
Xinghui Yin: https://x.com/XinghuiYin

Subscribe:
Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269
Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR
Website: [https://www.632nm.com](https://www.632nm.com/)

Timestamps:
00:00 - Intro
01:35 - The World’s First Laser
07:53 - Solving Impossible Problems
23:37 - Underestimated Problems
39:36 - Dan’s Backstory
43:33 - How to Teach Yourself Anything
47:03 - Shortcomings of Modern Education
53:19 - Developing the Optical Tape Recorder
1:01:39 - Machine Obsolescence
1:08:04 - Why are Scientists Often Bad Businessmen?
1:15:17 - Developing Medical Devices
1:24:52 - Untapped Potential of Materials Science
1:30:47 - Accidental Inventions
1:35:37 - Surviving Bureaucracy
1:42:27 - Humanoid Robots
1:44:11 - Managing an Engineering Team
1:50:06 - Developing the First Good Mobile Data Terminal
1:54:15 - Building an Environment for Solving Problems
2:02:18 - Why Aren’t We Inventing New Things?

#machining #cnc #precisionengineering #metrology #machineshop

How does experience rewire the brain—and why is vision the ideal system for understanding neuroplasticity?

In this episode, we speak with Mark Bear, MIT neuroscientist and a pioneer in the study of experience-dependent plasticity. Bear explains how the visual cortex became a model system for uncovering the synaptic mechanisms that allow the brain to change, adapt, and learn, especially during early development.

We explore how visual experience shapes neural circuits, why the brain undergoes critical periods of heightened plasticity, and what classic experiments in visual deprivation revealed about how connections are strengthened or lost. Bear walks us through the discovery of binocular vision in the cortex, the role of inhibition in closing critical periods, and how these ideas reshaped our understanding of learning and memory.

The conversation also covers modern views of cortical plasticity, including perceptual learning, visual recognition memory, and how the brain distinguishes familiar from novel stimuli. Bear discusses how insights from vision extend to broader questions about brain development, neurological disorders such as amblyopia, and whether adult plasticity can be reopened.

Whether you’re interested in neuroscience, brain development, neuroplasticity, learning and memory, or the biology of vision, this episode offers a clear and authoritative look at how experience shapes the brain at the level of neural circuits and synapses.

Follow us for more technical interviews with the world’s greatest scientists:

Twitter: https://x.com/632nmPodcast
Instagram: https://www.instagram.com/632nmpodcast?utm_source=ig_web_button_share_sheet&igsh=ZDNlZDc0MzIxNw==
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Michael Dubrovsky: https://x.com/MikeDubrovsky
Xinghui Yin: https://x.com/XinghuiYin

Subscribe:
Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269
Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR
Website: https://www.632nm.com

Timestamps:
00:00 - Intro
00:54 - Neuroplasticity in the Visual Cortex
05:45 - Critical Periods for Neuroplasticity
16:50 - Brain Development in Blind People
19:25 - Hallucinations and Sensory Deprivation
25:36 - How Mark’s Vision Disorder Led Him to a Career in Neuroscience
31:35 - Intro to the Visual System
35:52 - Visual System Processing
40:52 - Pop Science Neuroplasticity
45:00 - Memory Enhancing Pharmaceuticals
50:18 - Other Ways of Modifying the Visual Cortex
1:14:50 - Declarative vs Procedural Memory
1:22:36 - Neural Networks and Memory Degradation
1:25:16 - Neuron Transplants and Neurogenesis
1:28:58 - Brain-Machine Interfaces
1:33:46 - Most Prominent Issues in the Field
1:40:47 - Fragile X Syndrome
1:51:10 - Advice for Young Scientists

#neuroplasticity #neuroscience #hubermanlab #braindevelopment #brainplasticity

How can flat surfaces shape light as powerfully as bulky lenses?

In this episode, we speak with Federico Capasso, Harvard physicist and pioneer of metasurfaces, metalenses, and nanophotonics. Capasso traces the path from his work at Bell Labs on quantum cascade lasers to the invention of metasurface optics, showing how a practical challenge—collimating light without traditional lenses—sparked a new way to control light.

We explore the physics behind metasurfaces and generalized Snell’s law, explaining how subwavelength structures enable precise control of wavefronts, phase, and polarization beyond what conventional diffractive optics or Fresnel lenses allow. Capasso clarifies common misconceptions, contrasts metasurfaces with diffraction gratings and phased arrays, and emphasizes the importance of physical intuition and simplicity.

The conversation covers metalenses, polarization optics, holography, and how these ideas moved from theory to large-scale manufacturing in semiconductor foundries, ultimately appearing in consumer devices like smartphones. Capasso also reflects on commercialization, the legacy of Bell Labs, and the blurred boundary between basic science and real-world technology.

Whether you’re interested in metasurfaces, metalenses, nanophotonics, optics, or the process behind breakthrough discoveries, this episode offers a clear and insightful look at how modern optical physics becomes transformative technology.

Follow us for more technical interviews with the world’s greatest scientists:
Twitter: https://x.com/632nmPodcast
Instagram: https://www.instagram.com/632nmpodcast?utm_source=ig_web_button_share_sheet&igsh=ZDNlZDc0MzIxNw==
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Michael Dubrovsky: https://x.com/MikeDubrovsky
Xinghui Yin: https://x.com/XinghuiYin

Subscribe:
Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269
Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR
Website: [https://www.632nm.com](https://www.632nm.com/)

Timestamps:
00:00 - Intro
01:53 - Transition from Bell Labs to Harvard
09:45 - Generalized Snell's Law
21:25 - Facing the Diffractive Optics Community
31:07 - Benefits of Well-Rounded Education
45:16 - Metalenses
55:55 - Can AI do Physics?
1:07:39 - Industry vs Academia
1:11:44 - Nanophotonics
1:14:44 - What Allowed for the First Metalenses?
1:17:38 - 632nm and Other Lasers
1:20:47 - Quantum applications of Metalenses
1:30:14 - Quantum Entanglement Redefines Spacetime
1:43:22 - Stokes Parameters
1:48:28 - Limits of Metasurface Pixel Size
1:55:20 - Advice for Young Scientists
2:01:45 - Critique of the H Index

#metasurface #metalenses #quantumphysics #materialscience #optics  #photonics

How do electrons behave when they’re confined to a single layer, and why do entirely new laws of physics emerge when dimensions shrink?

Papers discussed in this episode:
Experimental observation of the quantum Hall effect and Berry's phase in graphene: https://www.nature.com/articles/nature04235
Tunable Fractional Quantum Hall Phases in Bilayer Graphene: https://arxiv.org/abs/1403.2112
Room-Temperature Quantum Hall Effect in Graphene: https://arxiv.org/abs/cond-mat/0702408

In this episode, we speak with Philip Kim, Harvard physicist and a leading experimentalist in low-dimensional quantum materials. Kim traces the experimental path from high-temperature superconductors and charge-density waves to carbon nanotubes and the earliest graphene devices, revealing how advances in nanofabrication and quantum transport opened the door to modern 2D materials physics.

We dive deep into the Hall effect and quantum Hall effect, from their 19th-century origins to the discovery of quantized and fractional conductance, and explain why these effects were found experimentally before they were fully understood theoretically. Kim shares behind-the-scenes stories of early graphene experiments, mechanical exfoliation, Shubnikov–de Haas oscillations, and what it was like to be scooped by the work that launched graphene into the spotlight.

Along the way, we explore how disorder, dimensionality, and magnetic fields shape electronic behavior; why carbon nanotubes paved the way for graphene; and how many of the most important discoveries in condensed matter physics arise from intuition, timing, and new experimental tools.

Whether you’re interested in graphene, quantum transport, the quantum Hall effect, nanofabrication, superconductors, or the real stories behind breakthrough discoveries, this conversation offers a rare, technically rich look at how modern quantum materials research actually unfolds.

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Mikhail Shalaginov: https://x.com/MYShalaginov
Michael Dubrovsky: https://x.com/MikeDubrovsky
Xinghui Yin: https://x.com/XinghuiYin

Subscribe:
Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269
Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR
Website: [https://www.632nm.com](https://www.632nm.com/)

Timestamps:
00:00 - Intro
01:15 - How Philip Began Studying Graphene
20:06 - Old Methods of Creating Graphene
32:33 - Hall Effect and Quantum Hall Effect
48:29 - Philip's Work at Columbia
52:33 - Philip's First Experiments with Graphene
1:06:43 - Did Philip Get Scooped from a Discovery?
1:09:40 - The Power of Scotch Tape
1:24:57 - High Temperature Quantum Hall Effect
1:30:18 - Fractional Quantum Hall Effect
1:41:17 - Collaboration with Particle Physicists
1:54:13 - Single Layer Graphene
1:59:44 - Next Gen Electronics with 2D Materials
2:03:23 - Graphene Twisting
2:14:48 - Superconductivity in Other Materials
2:20:06 - Anyons
2:30:00 - Fault-Tolerant Quantum Computing
2:36:05 - Can AI and Big Data Help Physicists?
2:40:47 - What Would Philip Do with Unlimited Resources?
2:43:44 - Optimizing the Education System

#graphene #quantumphysics #materialscience #halleffect #electromagnetism

What makes high-temperature superconductors and “strange metals” some of the most perplexing systems in modern physics?

In this episode, we speak with Dr. Subir Sachdev: Harvard physicist and one of the leading architects of today’s understanding of quantum matter. Sachdev explains why strange metals refuse to behave like ordinary conductors, how quantum entanglement reshapes the landscape of many-body physics, and why the quest to understand cuprate superconductors continues to push both theory and experiment to their limits.

We explore the physics of the cuprate phase diagram, the collapse of quasiparticles, and the role of quantum criticality in creating universal, linear-in-temperature behavior. Sachdev walks us through the origins of the SYK model, its surprising connections to black-hole thermodynamics and holography, and how new lattice-based models may finally bridge the gap between solvable theory and real materials.

Whether you’re curious about superconductivity, quantum criticality, black-hole analogies, emergent gauge fields, or the deep physics behind strongly correlated electrons, this conversation offers a rare, accessible look at how frontier theoretical work is redefining our picture of quantum matter—from the lab bench to the edge of spacetime.

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Mikhail Shalaginov: https://x.com/MYShalaginov
Michael Dubrovsky: https://x.com/MikeDubrovsky
Xinghui Yin: https://x.com/XinghuiYin

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Website: https://www.632nm.com

Timestamps:
01:22 - Subir’s Path to Condensed Matter Physics
06:24 - Challenges in Discovering Cuprates
09:53 - History of Superconductivity
20:07 - Subir's PhD work
27:09 - Development of the SYK model
41:09 - Strange Metals
56:43 - Derivation of SYK Model
1:03:53 - Signatures of Strange Metals
1:09:58 - How Quantum Mechanics Affects Black Holes
1:17:10 - What Brought Subir to Black Holes?
1:19:43 - Black Hole Connections to SYK
1:29:28 - ADS CFT Correspondence
1:37:04 - Can Quantum Computers Help Advance the SYK Model?
1:40:17 - Is AI Useful for Theoretical Physics?
1:46:40 - How does Quantum Criticality Play into Superconductivity?
1:49:11 - Derivation Quantum Criticality
1:52:49 -  What is Holography?
1:55:07 - Holography
2:00:19 - Green’s Function
2:08:46 - Green’s equation slides
2:13:23 - Yukawa Model vs SYK
2:17:30 - Can AI Brute Force Physics Discoveries?
2:23:51 - What Would Subir Do With Unlimited Funding?
2:36:33 - Dissecting the Hype of Superconductivity
2:31:15 - Raising the Next Generation of Great Physicists

#theoreticalphysics #quantummaterials #astrophysics #superconductivity #superconductor #blackhole #quantumphysics #quantummechanics