Quantinuum Built a Universal Gate Set With 28 Qubits, Not Hundreds

In my last post I wrote about how I often take my time learning about complex things. This one has been percolating for a while - the first experimental demonstration of switching between two different error-correcting codes to build a universal gate set, using 28 physical qubits instead of the hundreds that brute-force magic state distillation usually needs. Here we go!

Chapter 6 in my Quantum book covers Quantinuum's H2 trapped-ion computer through its gate fidelity, meaning how often a single operation on a qubit comes out correct. That number sits at 99.0 to 99.5 percent, close to IonQ's 99.99 percent result also cited in that chapter. A single clean operation is not the same thing as a working quantum computer. You need to run thousands or millions of operations in sequence, and you need every type of operation a quantum algorithm requires, not just the easy ones. A team from Quantinuum and UC Davis showed a way to get every type of operation working together reliably, using only 28 qubits where earlier approaches needed hundreds.

Let's start with some basics. A classical computer builds everything out of simple logic gates, AND, OR, NOT. A quantum computer builds everything out of quantum gates instead, operations that rotate or combine qubits in specific ways. Some quantum gates are considered easy to protect with error correction. Others are considered hard. That split matters more in quantum computing than it does in classical computing, and it is the whole reason this experiment is worth explaining.

The easy gates are called Clifford gates. Hadamard, CNOT, and the phase gate all fall into this group. Error correcting codes, like the Steane code already described in Chapter 6, were designed around these gates. Run a Clifford gate on a protected, encoded qubit and the code keeps working the way it is supposed to. The catch is that Clifford gates by themselves are not enough. A computer that only ever runs Clifford gates can be copied and simulated by an ordinary laptop. Nothing quantum about the result. To get an actual advantage over classical computing, you need one more type of gate, called the T gate, and it does not play by the same rules. Try to run a T gate directly inside most error correcting codes and the protection breaks down. If you want the fuller story on how trapped-ion qubits and error correction work together on this hardware, Chapter 6's background on QCCD architecture and logical qubits covers that ground.

Rather than force the T gate to behave, researchers build it a workaround. They prepare a separate, specially crafted qubit ahead of time, called a magic state, and use a process similar to quantum teleportation to transfer its effect onto the qubit that needs the T gate. The protected data qubit never runs the risky operation directly. The magic state absorbs the risk instead. The problem shifts from protecting a difficult gate to manufacturing a clean enough magic state in the first place.

Building a magic state clean enough to trust normally means distillation: take several noisy magic states, run a check on them, and keep only the ones that pass. Repeat that over several rounds and the result gets cleaner, but each round eats more qubits. Estimates for reaching Quantinuum's target fidelity through this brute-force approach ran into the hundreds of physical qubits, well beyond what most trapped-ion computers carry today.

Estimated qubit cost of brute-force distillation versus the demonstrated cost of code switching.

Quantinuum's team used a different trick called code switching. Instead of distilling one magic state over and over inside a single code, they built the state inside a 15-qubit code called the quantum Reed-Muller code, chosen because the T gate happens to work cleanly inside it with no extra steps. They then moved that already-clean state into the 7-qubit Steane code, the same code already in Chapter 6, which handles the rest of the gate set. The move works like a teleportation with a built-in check: if the check fails, that attempt gets thrown out rather than trusted. About 17 percent of attempts failed and were discarded, leaving a usable magic state in the remaining 83 percent.

The code-switching pipeline: build the state where the T gate is easy, check it, then move it to the code that runs everything else.

The number that matters most: the finished magic state had an infidelity of about 5.1 times ten to the negative fourth, roughly 2.7 times lower than the error rate of the physical qubits used to build it. In plain terms, the finished, protected result was cleaner than the raw hardware that made it. That is the entire promise of error correction, and no one had shown it for this particular gate before. The total qubit cost was 28: 22 data qubits and 6 more used just to run the checks. The full technical writeup, published in Physical Review X, is worth a look if you want the underlying math.

Quantinuum's newer Helios system has since carried the same idea further. In November 2025 it produced 48 logical qubits from 98 physical qubits, close to a 2 to 1 ratio, using a different checking scheme called the Iceberg code. None of this means a large, code-breaking quantum computer is close. It means the qubit cost of turning noisy hardware into something trustworthy has started to come down, on the same H-series machines Chapter 6 already covers. This is also the same territory last month's post on Quantinuum's topological-qubit workaround explored, using the H2 processor to test a different route to fault tolerance entirely.

What This Changes in the Book

Chapter 6 will get a new section on code-switching magic states alongside the existing H2 fidelity numbers, with the 28-qubit figure and the 5.1x10 to the negative 4 logical infidelity placed next to the 99.0 to 99.5 percent physical gate fidelity already cited, so readers can see the difference between a clean single operation and a clean chain of protected ones. Chapter 12, which covers the overhead problem in error correction, will note code switching as a second qubit-efficient alternative to brute-force distillation, alongside the NVIDIA AI-assisted calibration work already in that chapter.

This post will be folded into the next quarterly edition of Quantum from the Ground Up, due September 1. The current edition is available at the link above.

The Retirement Advantage

This morning I picked up a paper on topological qubits. Read a section, wrote some notes, set it down. Went out on the boat and did a chart plotter software update, thought about Microsoft's error correction claims, saw a dolphin and a manatee, checked my pinfish bait trap, talked to a neighbor, jumped in the pool, came back inside and read another section. No deadline, no meeting after, no student waiting on feedback. Twenty years ago I was directing NSF Centers of Excellence, first at STCC and later at UCF, and that kind of stretched-out thinking didn't exist. Staff, faculty, grant reports, site visits, advisory boards, proposal writing, college administration, students, airplanes, NSF program officers, audits. Fifteen minutes between fires, and quantum mechanics doesn't yield to fifteen minutes.

Growing older costs you some things, but not the ones people assume. I'm at the gym five days a week now and feel as strong as I have in years, so it isn't a story about decline. It's smaller than that: hearing aid glasses now, some unfortunate hair loss, a night on the boat that costs me more the next morning than it used to (I still love it.) 

At close to 70, semi-retired, I get to choose what earns my attention, and I've learned I do my best thinking in chunks now. Read something, write something, set it aside, let it sit while I'm doing something else entirely. Some mornings that means a quantum computing paper worked through in pieces over a week. It happens with my writing too - for example - I’ve been working on this post for a couple of weeks. Other mornings it means running the boat out of Clearwater before the wind picks up, no agenda beyond fish and water. Last week it meant France with the kids and it was spectacular! 

I've also had time to reconnect with people I let drift over four decades of building a career, old friends from K-12 and early consulting years, conversations that don't happen when every hour has a client attached to it.

My career has taught me plenty of technical things. It didn't teach me to work this way though, small pieces, long pauses, letting a hard idea sit until it loosens up on its own. The job never allowed for it. Semi-retirement has.

I’ll finish the topological qubit paper eventually. Not because I'm slower now. Because I finally have the room to work the way my mind actually wants to work, and the time to take my time.

IonQ and EPB Are Testing Quantum Memory on a Live Network

On August 4, IonQ and EPB announced plans for a Chattanooga research center built around quantum memory embedded in a live network. IonQ is committing $15 million over five years. EPB, which built the country's first citywide gigabit fiber network, is supplying the operational fiber for testing rather than a lab bench. The stated goal is to run what the partners describe as the first commercial quantum memory unit operating inside a real telecommunications network, not a simulated one.

Why You Can't Just Amplify a Quantum Signal

A classical repeater works because you can read a signal, clean it up, and retransmit a fresh copy. You cannot do that with a quantum signal. The no-cloning theorem rules out making an exact copy of an unknown quantum state, so you cannot just measure a photon carrying quantum information partway down a fiber and regenerate it downstream. Whatever fragile superposition or entanglement the photon was carrying gets destroyed the moment you try to read it directly. That single restriction is why quantum networking has stayed a laboratory subject for two decades while classical fiber scaled to terabits per second.

Entanglement Swapping: How Quantum Memory Solves It

The workaround is entanglement swapping, and it is where quantum memory earns its name. Instead of relaying one signal over the full distance, you break the link into shorter segments and generate entanglement independently across each one. At teh node joining two segments, a Bell-state measurement on the two local qubits swaps the entanglement outward, so the two endpoints end up entangled with each other even though no photon ever traveled the full path directly. Doing that at scale requires something to hold each segment's entangled state steady while the neighboring segment catches up, since the segments rarely finish at the same instant. That holding function is quantum memory. Without it, the whole chain have to succeed simultaneously across every link, which becomes exponentially unlikely as you add distance. Two further techniques usually ride along with this scheme in a real design. Entanglement purification takes several noisy entangled pairs and consumes them to distill a smaller number of higher-fidelity pairs, trading rate for quality. Multiplexing runs many memory qubits or many frequency and time slots in parallel at each node so that a failed attempt on one channel doesn't stall the whole link while it waits for the next try. Both exist specifically because the base success probability per attempt, discussed below, is low enough that a single-channel, single-shot repeater would be too slow to be useful.

Entanglement swapping through a memory node. Each segment generates its own entangled pair, the memory node performs a Bell-state measurement on its two stored qubits, and the entanglement swaps outward to link the endpoints directly.

Why IonQ Is Betting on Trapped Ions

IonQ's version of this problem runs through trapped ions rather than crystals or atomic vapor cells, which is one of a few competing physical approaches to quantum memory. A trapped ytterbium or barium ion stores its qubit state in hyperfine or Zeeman sublevels of the ground state, energy levels with transition frequencies in the microwave range that are largely insulated from the electric and magnetic field noise that scrambles other qubit types. The same ion can be made to emit a single photon entangled with its internal state through spontaneous emission on an optical transition, which is the interface that lets a stationary trapped-ion memory talk to a photon traveling down fiber. The catch is that an ion radiates in essentially all directions, so a bare setup collects only a tiny fraction of those photons. The standard fix is to place the ion inside an optical cavity, which enhances emission into one preferred mode through the Purcell effect and can push photon-collection efficiency well above what an open microscope objective achieves. IonQ acquired this specific expertise directly: its 2025 acquisition of the Boston photonic-interconnect startup Lightsynq, founded by former Harvard quantum-networking researchers, brought in more than 20 patents covering quantum memory and multi-processor scaling, and that intellectual property is what the Chattanooga center is built to commercialize.

The Real Bottleneck: Entanglement Generation Rate

The number that actually limits this technology is the remote entanglement generation rate, and it is unglamorous compared to headline fidelity figures. Producing one heralded entangled pair between two distant ion nodes today runs on the order of 1 to 10 events per second under good lab conditions, and each attempt only succeeds a small fraction of the time because photon collection efficiency in most published experiments stays under 1 percent. A useful distributed computation or a real communication session needs thousands of these links established in sequence. At 10 Hz that is roughly seventeen minutes just to build 10,000 entangled pairs, before any of the actual computation or communication happens. The Duke-IonQ demonstration illustrates the same constraint at smaller scale: net end-to-end photon collection efficiency across the three nodes ranged from about 0.74 to 1.45 percent, and the ions needd periodic pauses for Doppler cooling between entanglement attempts because recoil from repeated photon scattering heats them out of the trap's ground state. Raising that collection efficiency, largely through better cavity coupling, is the specific engineering problem Lightsynq's patents target.

The Duke-IonQ Demonstration

The lab evidence behind this bet is recent and specific. In June 2026, a Duke University and IonQ team entangled three separately trapped barium-138 ions across independent network nodes, producing a GHZ state, the three-particle entangled resource that distributed quantum computing protocols need, at a fidelity between 84.1 and 88.1 percent. Each node held a single ion in its own four-rod Paul trap, separated by about two meters, with a static magnetic field of roughly 4.24 gauss splitting the qubit's Zeeman sublevels by about 11.9 MHz and defining the two logical states. The nodes were linked through a shared photon-collection setup rather than a direct chip-to-chip connection, and the entanglement generation rate came in at about 0.095 events per second, close to one every ten seconds. To confirm the entanglement was genuine rather than an artifact of the measurement, the team ran a Mermin-inequality test and measured a value of 3.203, above the maximum of 2 allowed by any theory built on local hidden variables and closer to the value of 4 predicted by ideal quantum mechanics. That is a small distance and a modest rate next to what a production network needs, but it demonstrated something the field had not shown before: individually controlled, independently addressable qubits generating multipartite entanglement over a photonic link without relying on local two-qubit gates to mediate it. Earlier three-node demonstrations in other qubit platforms depended on exactly that kind of shortcut, which does not scale to independently operated network nodes.

Testing Distance and Traffic

Distance and traffic are the two variables Chattanooga is built to test what a two-meter lab bench cannot. On distance, EPB's live fiber replaces a bench-top loop with a real metro network spanning real thermal drift, real splices, and real fiber aging. On traffic, a separate July 2026 study out of Northwestern's McCormick School of Engineering showed that entangled photons can share existing commercial fiber carrying 1.6 terabits per second of live internet traffic over 24.4 kilometers while holding 94.2 percent fidelity, which matters because it removes the assumption that a quantum network needs its own dedicated dark fiber to function. Put those two results together and the engineering question shifts from whether quantum memory works in principle to whether it holds up once it is buffering real entangled states against a live network's noise floor instead of a quiet lab bench.

What Chattanooga Isn't Yet

None of this makes Chattanooga a working quantum repeater yet. A full repeater chain needs memory nodes with coherence times long enough to wait for neighboring segments, entanglement generation rates fast enough to be useful, and Bell-state measurement hardware reliable enough to swap entanglement without introducing more error than it removes. The Tennessee center is explicitly an R&D lab, not a deployed product, and IonQ's own five-year funding horizon reflects that. What changed this year is that the missing piece, a memory node that can sit inside a live network instead of a shielded lab enclosure, now exists to be tested.

The Local Context

This is not Chattanooga's first move in quantum. EPB and IonQ already run the EPB Quantum Center, and this new center extends that relationship rather than starting cold. The partners project it will generate two to three times its $15 million cost in wider economic impact and support roughly two dozen jobs, mostly research scientists and trainees.

Why This Caught My Attention

My father was a telephone man. That is what we called him back then. He spent his career climbing poles and fixing lines, keeping copper telephone circuits working in all weather. I grew up around that trade before I ever studied it formally, and I ended up spending my own career on the technology that came after his: telecommunications and networking education. From 1997 to 2014 I was Co-Principal Investigator and later Principal Investigator and Executive Director of the National Center for Telecommunications Technologies at Springfield Technical Community College, an NSF-funded National Center of Excellence built around telecommunications and networking curriculum for community colleges nationwide. From 2014 to 2017 I served as  Co-Principal Investigator at OP-TEC, the National Center for Optics and Photonics Education at the University of Central Florida, another NSF National Center of Excellence, this one focused on the optics and photonics side of the field, which is exactly the physical layer that entangled-photon networking runs on. I also spent 1995 to 2016 as telecommunications faculty and New England curriculum development leader for Verizon's NextStep AAS degree program, building the courses that trained the technicians who kept Verizon's own fiber and copper networks running. Chattanooga's roughly two dozen jobs are a small number next to a $15 million investment, but that ratio is familiar from all three roles. A center like this rarely proves out on job count in its first few years. It proves out on whether the local workforce and research infrastructure are ready when the technology does mature, and whether that head start pulls in the next round of investment. That is also why I still do quantum workforce consulting, including on the Quantum Supply Chain Accelerator with the Massachusetts Technology Collaborative. Watching EPB and IonQ run a version of that same playbook, a regional utility and a specific technical niche, on quantum networking instead of manufacturing or biotech, is what held my attention past the headline. My father spent his career keeping a physical line working between two points. I have spent a good part of mine teaching people how to do the same thing with light instead of copper. This story is the next chapter of that same problem.

What This Changes in the Book

Chapter 1 will get a new section describing quantum memory repeaters as a second, complementary path to the fiber problem, distinct from telecom-native photon emission. The chapter will carry the mechanics above, the no-cloning restriction, entanglement swapping, purification, and multiplexing, alongside the entanglement generation rate as the real bottleneck rather than fidelity alone. It will also note that Chattanooga's live-network deployment is the first commercial attempt to test a memory-based repeater node outside a controlled lab environment, with the $15 million, five-year figure and the Duke-IonQ fidelity and rate numbers carried alongside the existing ytterbium-171 result so readers can see both tracks side by side rather than mistaking one for a replacement of the other.

This post will be folded into the next quarterly edition of Quantum from the Ground Up, due September 1. The current edition is available at the link above.

Eddie Smith Didn't Sell Grady-White

I've owned two Grady-Whites, and I bought them for the same reasons everyone else does. Each model are engineered for versatility, comfort, and performance. Storage is abundant, the head compartments are integrated instead of an afterthought, and the SeaV² hull gives you a smooth, stable ride whether you're running offshore, cruising for the day, towing kids on a tube, or running over to a waterside restaurant for dinner. It's a fishing machine and a cruising machine in the same hull, and it doesn't compromise on either job. When you're 50 miles out and the weather turns on you, a Grady is a good place to be. The build quality is high, the layouts are refined, and resale value stays strong. None of that happens by accident. Grady-White treats customer feedback as a core part of the design process, whether refining a current model or building a new one from scratch. Mine current boat is a 2023 Freedom 325, and Grady is only last boat I'll ever buy in their model size range.

Eddie Smith bought Grady-White in 1968 at 26 years old, when the company was near bankrupt. He spent 58 years building it into one of the most respected names in boatbuilding. Two years ago, buyers offered him more than $400 million for it. He turned them down.

Instead, Smith transferred the company's voting stock into a new perpetual purpose trust, which means Grady-White can never be sold again. A newly formed 501(c)(4) nonprofit will receive the non-voting shares and direct the company's profits, likely tens of millions a year, toward conservation, education, and healthcare. It's the largest move of its kind in the United States since Patagonia did something similar in 2022, and the first in the marine industry. Smith modeled the decision on Patagonia founder Yvon Chouinard, who did the same thing with his own company. Smith gave up any tax benefit from donating the stock and expects a multimillion-dollar personal tax bill for the privilege of giving the company away.

Smith didn't grow up in boats. He graduated from UNC and was working at his father's mail-order pantyhose business when a chance meeting with Grady-White co-founder Don White changed his path. He bought the company at 26 and spent the next 58 years on it, working 100-hour weeks and giving up golf for decades to keep the business afloat when it was failing and to build it into what it is now. Giving the company away is not his first act of generosity in Greenville. He's funded the ECU Health Cancer Care Tower that bears his and his wife's names, along with the largest athletics gift in ECU history at the time. The family foundation he built along the way holds hundreds of millions of dollars for the same causes the Grady-White nonprofit now serves.

Smith said he'd watched too many friends sell their companies and lose them. New owners came in, culture died, and the thing that made the business worth buying disappeared with it. He wasn't willing to let that happen to Grady-White.

I bought Gradys because I know they are built to outlast me. Eddie Smith just made sure the company will too.

IonQ Buys Its Own Foundry

Chapter 6 in my quartery updated Quantum book covers IonQ as a trapped ion company: the Paul trap, the Molmer-Sorensen gate, the 99.99% two-qubit fidelity result from October 2025. That chapter is about physics. This post is about the part the book left out: who builds the chips that make the physics real.

On July 31, 2026, IonQ completed its $1.8 billion acquisition of SkyWater Technology, a Bloomington, Minnesota chipmaker that describes itself as the largest exclusively U.S. based semiconductor foundry. The deal had been announced in January and cleared its last regulatory hurdle two days earlier, on July 31, when the FTC voted to let the merger close without conditions after commissioners could not agree on what those conditions should be.

The disagreement is worth a paragraph on its own. Chairman Andrew Ferguson wanted IonQ to commit to fair access for rival quantum companies that already run production through SkyWater's foundry. Commissioner Mark Meador concluded the merger would not reduce competition and did not think conditions were warranted. With no agreement, Ferguson's stated position was that getting out of the way beat holding up the deal. SkyWater says it will keep serving its existing aerospace, defense, and commercial foundry customers alongside IonQ.

CEO Niccolo de Masi has been explicit about the reasoning. In the acquisition announcement, he described the goal as building the only vertically integrated full-stack quantum platform company, covering computing, networking, security, and sensing, with chip design, fabrication, and packaging all under one roof. IonQ also pointed to shorter wafer iteration cycles and parallel prototyping as the practical payoff, on the way to functional testing of 200,000-qubit processors by 2028.

In Chapter 3 I drew a line between physics working in a lab and engineering making it work at scale, using solar, fusion, and transistors as the historical pattern. A trapped ion gate hitting 99.99% fidelity is a physics result. Owning the foundry that fabricates the ion traps, the control electronics, and the packaging around them is the engineering side of that same story. IonQ is not buying SkyWater because trapped ions need a chip fab in the way a superconducting qubit does. It is buying supply chain control, and betting that owning it beats depending on someone else's roadmap.

The Workforce Layer

SkyWater's job postings tell a different story from the press release. Alongside senior staff engineers, the company is hiring equipment maintenance technicians and process technicians, some roles carrying sign-on bonuses up to $7,500, and it says explicitly that it recruits first-time workforce entrants and military veterans into those positions, not just engineers with degrees. Engineering makes up roughly half of SkyWater's headcount. The other half runs the cleanroom floor, and those roles do not require a PhD or in most cases a four-year degree.

IonQ's stated 2028 target of 200,000-qubit processors depends on that second group as much as the first. A trapped ion chip with record fidelity does not fabricate, package, or ship itself. Chapter 18 already argues that the field needs adjacent skill sets and no-PhD-required roles, not just physicists. This acquisition puts a name and a hiring pipeline behind that argument. SkyWater was building that technician workforce before IonQ owned it. Now that workforce sits inside a quantum computing company's org chart, which is a stronger case for community college and workforce pathway programs than a hypothetical one.

What This Changes

Chapter 6 gets a new closing note: as of July 2026, IonQ is a chip manufacturer as well as a quantum computing company, and SkyWater's foundry work now sits inside the same corporate structure as the trapped ion systems. Chapter 13's timeline discussion, which already tracks IonQ's fidelity result as the reason the Q-Day estimate moved from roughly 2035 to a 2029-2033 range, gets a second data point: IonQ's own target of 200,000-qubit processors and 8,000 ultra-high fidelity logical qubits by 2028. That target came from the company that made the acquisition, so we need to treat it as a stated goal, not a verified result, until there is hardware to point to. Chapters 18 and 19 get a concrete example: a major quantum company now directly employs the technician-level, non-PhD workforce those chapters argue for, inside a foundry it acquired specifically to control its supply chain.

This post will fold into the next edition of Quantum from the Ground Up, due September 1.

Forty Years, No Matching Belt

Plotting World Fiber Domination in a tie at Microsoft 1998

A photo from Microsoft in 1998 - me in a tie, with a guy whose name I do not remember, 
sketching out fiber optic network technology plans at a whiteboard. This was my first time in Redmond and I wore that tie once, on my first day there, before I noticed nobody else there bothered with one. Back at the college, dress shoes were still a thing at least for me, and I never once got the belt and shoes to match. I did not even know that was a fashion rule. One would be brown, the other black….

Engineers a generation before mine wore bow ties and short sleeve shirts for a practical reason: a long tie or a loose cuff could catch in a running machine on the shop floor. That risk faded as engineering work moved from the floor to the desk, and clothing followed the same path from function to convention. By the early 1990s, tech had already dropped the tie. Engineering classrooms took another half decade or so to catch up.

The tie disappeared from teaching in the 1990s, replaced by a collared shirt and khakis. Business casual became standard by the 2000s. Remote teaching arrived next, showing only shoulders on camera. Students now attend lab in shorts and sandals, and nobody reacts.

Michael Girdley made a similar case on LinkedIn recently. He described clothing as a psychological lever and recommended sitting one notch above whatever baseline a room sets. A classroom's baseline shifted from suits to slacks to jeans across four decades. A professor one notch above jeans wears a collared shirt. Overdressing past that baseline signals distance from students.

Employers see the same pattern at senior project presentations. A team presenting to an industry panel dresses one notch above the panel's own baseline, and that baseline now runs to polos and jeans. Reading the room correctly frees energy for the work itself.

I still own that tie (and a whole bunch more) from the Microsoft photo. I wore it exactly once there. I never did learn the belt and shoes rule I was supposedly breaking. Thirty years or so in, that problem solved itself: nobody expects the tie anymore and I like my tee shirts, shorts and flip-flops.

A Second Way to Build a Topological Qubit, and It Runs on Hardware Already Available

Chapter 10 of Quantum from the Ground Up tells one story about topological qubits: Microsoft growing an exotic nanowire material to host a particle called a Majorana zero mode. That approach needs new physics and new materials, and it has been slow going. A team at Quantinuum, working with researchers at Harvard, UChicago, and Stony Brook University, just showed a different way to get the same protection against errors. They published the result in Nature.

Here is the paper describing a universal topological gate set built from braiding and fusing exotic particles called anyons. They did not grow anything new. They took an ordinary trapped-ion quantum computer, Quantinuum's H2, and used 54 of its regular qubits to build a state of matter that behaves the way the exotic Majorana material is supposed to behave.

Start with what an anyon is. In everyday physics, particles come in two types: fermions, like electrons, and bosons, like photons. Anyons are not fundamental particles. They only show up inside certain engineered quantum systems, as patterns in how a group of qubits is entangled together. The interesting kind here are called non-Abelian anyons. If you take two of them and swap their positions, then swap two more in a different order, you get a different final result depending on which order you did the swapping in.

That sounds like a technicality, but it is the whole point. Because the result depends on the order of the swaps and not on small local wobbles or noise, information stored this way is naturally protected. Physicists call the swapping process braiding, since tracking two anyons moving around each other looks like braiding two strands of hair. In the diagram below, a1 passes in front of a2, shown by the small break in a2's line where it crosses behind. Swap them the other way, with a2 in front instead, and the anyons end up in a different state. Which one passes in front is not a drawing choice. It is the physical information the braid records.

Braiding by itself has a known gap. Researchers proved back in a 2003 proposal from physicist Carlos Mochon that for the simplest type of non-Abelian anyons, braiding alone cannot give you every operation a computer needs. You can protect information this way, but you cannot fully compute with it. Something was missing.

The Quantinuum team's answer was to add a second move: fusion. Instead of only moving anyons around each other, they also merge two anyons together and measure what comes out. Braiding plus fusion turns out to supply the missing operations, creating a mathematically complete set of gates capable of running any algorithm.

They built a 54-qubit state based on a mathematical structure called S₃—the smallest group that produces non-Abelian anyons—then stored information in the combined fusion outcomes of many anyons taken together rather than in any single qubit. Each unit of stored information could hold three states instead of the usual two (a qutrit rather than a qubit), since these anyons naturally support three possible fusion outcomes. Using braiding and fusion together, the team ran a computationally universal set of operations and read out the result correctly.

As a real test, they used the setup to build what is called a magic state, a specific resource that most fault-tolerant quantum computing schemes need. Normally, generating that resource requires an expensive extra process called magic state distillation, which eats up huge numbers of physical qubits just to produce one clean logical one. This approach made the same resource directly via topological operations without that extra step.

What This Changes in the Book

Chapter 10 needs a second section. Microsoft and Quantinuum are both chasing the same goal—a qubit that resists errors because of its shape rather than because of constant correction—but they are getting there in different ways. Microsoft is trying to grow a new material that hosts the right kind of particle directly. Quantinuum instead uses software and precise control to make an ordinary quantum computer behave as if that exotic material were there.

Chapter 6 gets an update too. The H2 processor was already in the book because of its record for entangling 56 qubits at once. Now it has a second claim to fame: it is a working testbed for this kind of engineered, error-resistant state of matter.

Neither team has built an actively error-corrected logical qubit that outperforms physical hardware yet. Both just found a more believable road toward one—and it turns out you do not need exotic new hardware to try.

This post will roll into the next edition, due September 1. The current edition is free at gordostuff.com/p/quantum-from-ground-up-hardware.html