A Quantum Computer Watches Matter Form From Scratch

Chapter 11 of Quantum from the Ground Up covers an IBM quantum chip that helped simulate a large protein molecule in May 2026. A new result uses a chip from the same family for something further from everyday life: watching the pieces of an atom's nucleus form.

Here’s some background - protons and neutrons, the particles that make up the nucleus of an atom, are not the smallest things out there. Each one is built from smaller particles called quarks, held together by a force called the strong force. Physicists call any particle built from quarks a hadron. The process of quarks locking together into a hadron is called hadronization. It happens constantly inside stars, inside particle colliders, and, billions of years ago, in the early universe. Nobody has ever watched it happen step by step, because it unfolds too fast and too small to see, even with instruments as powerful as CERN's Large Hadron Collider.

Anthony Ciavarella, a scientist at Lawrence Berkeley National Laboratory, used 104 qubits on an IBM quantum processor to simulate a piece of this process instead of observing it directly. He reached the machine remotely through a Department of Energy cloud access program called QCUP, rather than owning the hardware himself. We’ve described qubits in past posts - the basic unit of information in a quantum computer, similar to a bit in a regular computer, but able to hold more complex states. More qubits generally means a computer can model a bigger or more detailed problem.

The number 104 is an interesting choice and not a hardware limit. IBM's chip has 156 qubits, and Ciavarella used only some of them. In his setup, each qubit stands in for one point on a one-dimensional line of quark positions, so the qubit count is really a choice about how long a line to simulate. He picked a line of 104 points, long enough to fit a stretched gluon string spanning most of it, so something called the snap could happen out in the middle where it is easy to see clearly, rather than run into the edge of the simulation before it finished stretching.

The specific piece he simulated is called string breaking. Quarks are linked by something physicists describe as a string made of particles called gluons. Pull two quarks apart and that string stretches, the way a rubber band stretches, until it holds so much energy that it snaps. When it snaps, the energy does not just disappear. It turns into a brand new pair of quarks, which is how new hadrons get built. Ciavarella simplified the problem by using heavier quarks, which move around less and are easier to track, and he set up his simulation using a method he helped develop for preparing a quantum computer's starting state cleanly.

The simulation's answer matched what earlier work on ordinary supercomputers had already found. That match is the actual achievement here. Nobody is claiming the quantum computer beat a classical one. The result, published in Physical Review D, shows that a real quantum computer can reproduce a calculation even though the model was simplified down to one dimension. The data also hinted that the gluon string might briefly act like a heated gas right before it snaps, a detail worth checking again once the simulations get less simplified.

Why This Matters

Quantum computers are noisy. Every operation carries a small error, and those errors add up as a circuit grows. Nobody trusts a quantum result on a problem nobody can already solve until the machine first proves it gets the right answer on a problem people already know. Matching the classical calculation is that proof. It confirms the way Ciavarella mapped quark positions onto qubits, prepared the starting state, and corrected for hardware noise all worked correctly on real hardware, not only on paper.

Ciavarella's model used heavy quarks in one dimension because that version is still solvable classically. Light quarks, three dimensions, and watching a collision unfold in real time rather than checking a single snapshot are where classical computers run out of room, since those calculations carry exactly the kind of entanglement a regular computer cannot represent efficiently. That regime is also the one closest to what actually happens inside a real collision at a facility like the Large Hadron Collider. As Ciavarella put it, physicists already have the theory for hadronization; they have lacked a way to calculate predictions from it. This result is the first step toward a machine that can.

This was not the first attempt at something like this. In 2024, some of the same researchers, working with the University of Washington and Berkeley Lab, used 112 qubits to build and track a hadron directly, watching it move over time in an earlier, related model on an earlier version of this same IBM chip. The 2026 result trades that moving picture for a sharper look at the single moment when a hadron forms. 

What This Changes in the Book

Chapter 5, which covers this family of IBM chips, gets a new data point: the same chip line now has a published result in particle physics, using 104 qubits, on top of the protein simulation already covered in Chapter 11. Chapter 11's claim that this hardware has uses beyond biology gets a second example, and a more direct one, since this simulation ran entirely on the quantum processor rather than splitting the work between a quantum computer and a classical one.

This post will fold into the next edition of Quantum from the Ground Up, due September 1. The current edition is free to download at gordostuff.com/p/quantum-from-ground-up-hardware.html.

Sargassum and Other Irritants

Sargassum picture: https://www.aoml.noaa.gov/

I opened a favorite saltwater fishing forum and a member had posted an update about sargassum conditions offshore. A reasonable enough thing to share. Within a few comments, another person had pivoted to the reflecting pool in Washington and algae blooms. Someone else called them an idiot. It escalated to f-bombs from there. By the time I scrolled past, nobody was talking about offshore conditions anymore.

That pattern used to live mostly in politics. For the past decade, public political discourse has run on contempt. Politicians model it. Cable hosts reward it. Algorithms surface it because outrage keeps people scrolling. The message, repeated millions of times a day, is that disagreement justifies contempt. You are not just wrong; you are stupid, corrupt, or evil.

That message did not stay in politics. People learned a behavior. When you disagree with someone, you attack the person. You do not argue the point. You question their intelligence, their motives, their worth. That approach feels satisfying in the moment and accomplishes nothing, but it has become the default in comment sections, workplace threads, and online communities that have nothing to do with any election.

The anger usually has little to do with the post that triggered it. Psychologists point to a few consistent sources. Relative deprivation is one: people compare themselves to others constantly, social media makes that comparison unavoidable, and the gap between where someone is and where they think they should be produces resentment. Displaced frustration is another: anger from a dead-end job, a stalled relationship, or money problems needs somewhere to go, and a stranger online is a safe target. Regret works similarly. People who feel stuck tend to lash out at those who appear to be moving. It presents as contempt but it is closer to grief. None of that excuses the behavior. It does explain why the attack is almost never really about you.

The research on this is consistent. A 2022 study in Communication Research by Rossini found that uncivil and intolerant discourse in online political talk follows recognizable patterns, and that exposure to it normalizes hostile language more broadly. Contempt spreads. It does not stay in its lane. Once a culture accepts that attacking the person is a legitimate response to disagreement, that norm shows up everywhere. A 2021 study in Science Advances confirmed that social media platforms amplify outrage expressions over time through reinforcement and norm learning, whether or not the designers intended it.

I am not sure most people notice when it happens to them. They open a thread about a hobby, a product, a teaching method, and find themselves either absorbing insults or throwing them. It feels normal because it has become normal. The political arena did not invent human contempt, but it mainstreamed a particular expression of it and then exported it everywhere else. And if you push back with a calm, reasoned reply, the hater has one move left: profanity. The argument is over for them the moment you ask them to defend a position.

That sargassum thread had dozens of replies by the time I stopped scrolling. Nobody changed their mind. Nobody learned anything about the fishing conditions. I closed the tab and went back to work. Some people are there to fight, not to think. Recognize them early and do not engage. Life is too short, and your time is worth more than their anger.

The Quantum Chandelier

Photo MIT Technology Review

You've probably seen a photo like this - a tower of gold-plated discs wrapped in loops of wire, narrowing toward a point at the bottom. Google, IBM, and most quantum computing press releases use some version of this image. People call the assembly the chandelier, and it looks like the computer. It isn't. It's the life support system for a chip you can't even see in the photo.

Start with what's actually inside a quantum computer. A qubit is a physical device, usually a tiny loop of superconducting metal, that can hold a mix of two states at once instead of a single 0 or 1. That mixed state is fragile. A stray photon, a vibration, or a few millikelvin of extra heat can collapse it before you get a useful calculation out of it. Physicists call that collapse decoherence, and it's the central engineering problem in the entire field. Keeping decoherence at bay is the whole reason the chandelier exists.

Why It Has to Be That Cold

At room temperature, everything around a chip is radiating heat as stray photons, trillions of them, bouncing around and hitting anything nearby. For a normal computer chip that's irrelevant. For a superconducting qubit it's fatal, since a single one of those stray photons carries enough energy to flip the qubit's state. Cooling the chip down to the mixing chamber stage, near 10 millikelvin starves the environment of those stray photons and also lets the qubit's own wiring become superconducting, meaning it carries current with zero electrical resistance. Both effects are required. Without one or the other, the qubit decoheres in nanoseconds instead of the few hundred microseconds researchers need.

The Five Stages

The gold structure is a dilution refrigerator, built from stacked stages that grow colder toward the bottom. A pulse tube cryocooler, essentially a specialized mechanical compressor, does the first heavy lifting, dropping the system from room temperature to about 40 Kelvin and then 4 Kelvin using compressed helium gas. Below that, the fridge switches to a different method. A chamber called the still boils off helium-3 to reach roughly 0.7 Kelvin, and a series of heat exchangers pushes the temperature down further, through about 0.1 Kelvin, to the mixing chamber at the very bottom. A mixture of helium-3 and helium-4 drives that last stage. The full cooldown from room temperature to base takes 24 to 48 hours, and it has to happen every time the system needs to be opened for maintenance.

Each gold disc in the photo is one of these stages, plated in gold because gold conducts heat well, resists corrosion, and doesn't interfere magnetically with the qubits. Each stage nests inside the next, shielding the colder one below it from the warmer one above.

Figure: the chandelier's cooling stages, colored from gold at the warmest to blue at the coldest, with the qubit chip mounted at the base.

The Wiring Problem

Every wire running through those stages carries control signals down to the qubits and readout signals back up to room-temperature electronics. A signal heading down gets attenuated at each stage on the way, stripping out electrical noise picked up from the warmer stages above. A signal heading up gets amplified, since the qubit's own readout signal is too faint to detect at room temperature. Every one of those wires is also a heat leak. Heat travels down a wire just as easily as a signal does, and the cooling power at the base stage is measured in microwatts, barely enough to warm a fraction of a grain of rice. A single wire that's improperly thermalized can add more heat than the entire fridge can remove.

That tradeoff is why wiring, not the qubits themselves, has become one of the field's biggest scaling obstacles. Each qubit needs its own set of control and readout lines, so the number of cables required grows directly with qubit count, eventually exceeding what a single cryostat can physically hold. Labs are now racing to move some control electronics inside the fridge itself, onto chips that can survive the cold, so fewer wires have to cross from room temperature down to the millikelvin stage. A single dilution refrigerator system runs one to five million dollars, and most of that cost is solving this wiring problem.

What's Actually Quantum

The qubit chip itself sits at the very bottom, bolted to the mixing chamber, a few millimeters across. It's small enough to miss in most photos of the chandelier, which is the point. Everything above it, every gold disc, every coil of coax, every attenuator and amplifier, exists for one reason: to keep that small chip cold and quiet enough to hold a quantum state long enough to be useful. Chapter 3 of Quantum from the Ground Up makes this argument directly: physics works, engineering makes it work. The chandelier is that argument built out of gold-plated copper and helium-3.

Next time a chandelier photo turns up in your feed, look past the wiring for the small chip at the bottom. That chip is the entire quantum computer. Everything else in the picture is plumbing.

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

The Second June 22, 2026 Quantum Executive Order

In a post Tuesday, I covered the executive order setting hard federal deadlines for post-quantum cryptography migration: key establishment by 2030, digital signatures by 2031. That order dealt with defense. On the same day, June 22, the president signed a second order that deals with offense.

Executive Order 14413, "Ushering in the Next Frontier of Quantum Innovation," directs the federal government to build a large-scale quantum computer for scientific use. The centerpiece is the Quantum Computer for Application Development and Discovery Science effort, called QC-ADDS. The order directs the Department of Energy to deliver at least one QC-ADDS system to a DOE facility and make it available to the scientific community.

Here's some details - within 90 days, DOE must publish the technical specifications required for QC-ADDS to perform transformative scientific applications beyond current classical computer capabilities. Within 180 days, DOE must explore private-sector partnership models and report on cost, scope, and delivery timeframe. DOE has already responded: its Quantum Genesis initiative targets a fault-tolerant, scientifically relevant quantum computing capability by 2028, with a National Quantum Supercomputing User Facility to give U.S. researchers access to systems across multiple qubit modalities.

The Commerce Department must develop a plan for advance market commitments to pull in commercial quantum vendors. The Defense Department gets its own track, establishing programs for national security applications of quantum computing, potentially including a dedicated center. The order also establishes a national center for quantum performance assessment and directs a government-wide quantum workforce recruitment strategy, including special pay rates and retention incentives.

The workforce section carries the most direct relevance for technical education programs. The order tasks NSF to stand up a network of National QIST Workforce Development Institutes within 180 days. Federal money for hands-on QIST training will flow somewhere; the question is where.

There is a thread connecting both orders. The PQC migration order sets a deadline for protecting existing systems. EO 14413 sets a timeline for building the systems that will eventually make those protections necessary. Both orders treat 2030 as the planning horizon. Harvard's Mikhail Lukin put fault-tolerant, large-scale quantum computers at end-of-decade in a recent assessment, five to ten years ahead of earlier estimates.

Inside the ST54M: One Chip, Three Jobs, and a Post-Quantum Upgrade

Yesterday I wrote about our government setting a new deadline for quantum-safe encryption. At the end of the post I briefly mentioned STMicroelectronics introduced the ST54M, the first mobile chip with a dedicated hardware accelerator for post-quantum algorithms. I got a question from a reader – what the heck does that mean....?!  Fair question! Here’s some detail on what that chip does, and how it works. If you use your phone for payments – this is a very good thing.

Tap your phone against a payment terminal and several things have to happen in well under a second. The device has to prove its identity, encrypt the exchange, and complete the transaction before you lift your hand away. Most people never think about the chip doing that work. STMicroelectronics just gave that chip a significant upgrade.

The new chip is called the ST54M. It is a single chip that combines three functions that used to live on separate pieces of silicon: an NFC controller, a secure element, and eSIM support. NFC is the short range radio that lets your phone talk to a payment terminal, a transit gate, or a hotel door lock. The secure element is a locked vault inside the chip that holds your credentials and keys. eSIM is the embedded SIM that lets your carrier profile live in the device itself instead of a removable card. Folding all three into one die (small piece of silicon that contains the electronic circuits needed) simplifies the phone and tightens the security boundary between them.

The bigger story is what ST54M adds on top: a hardware accelerator built for post-quantum cryptography. Today's encryption relies on math problems that are hard for ordinary computers to solve. A sufficiently capable quantum computer could solve some of those problems quickly, which would undermine the locks protecting your payments and your identity data. ST54M supports two newer algorithms, ML-KEM and ML-DSA, designed to resist that kind of attack. Building the acceleration into hardware means a phone can run this stronger cryptography without slowing down.

STMicroelectronics has samples available now, with production and certification targeted for July 2026. The certifications matter for adoption; payment networks and government identity programs will not deploy a chip until it clears those bars.

None of this changes what happens when you tap your phone tomorrow. It changes what is quietly defending that tap a few years from now.

Government Sets New Deadline for Quantum-Safe Encryption

A student in one of my summer courses asked the question I get every time encryption comes up in discussion: why does this matter now? RSA (Rivest-Shamir-Adleman) and ECC (elliptic curve cryptography) have protected data for decades. The quantum computer that breaks them does not exist yet. 

My usual answer leans on Q-Day estimates: Google's Gidney put the threshold at roughly one million physical qubits to break RSA-2048, and an IonQ fidelity result last October pushed the realistic window to somewhere between 2029 and 2033. Most expert estimates before that sat closer to 2035. On June 22, the federal government answered the student's question for me. President Trump signed 

an executive order setting hard deadlines for federal post-quantum cryptography migration (PQC): agencies must move high value assets to post-quantum key establishment by December 31, 2030, and post-quantum digital signatures by December 31, 2031. Federal contractors get the same 2030 deadline for FIPS (Federal Information Processing Standards) compliance.

That replaces the prior government baseline. Under the Biden administration's National Security Memorandum 10, agencies were planning around 2035. The new order compresses that by four to five years and adds teeth: agencies must name a PQC migration lead within 30 days, the Commerce Department must run a migration pilot by the end of 2027, and contractors face FIPS enforcement through procurement rules. 

Coverage from Cybersecurity Dive notes the order also pushes CISA (the Cybersecurity and Infrastructure Security Agency) to publish guidance on cryptographic bills of materials, the inventory work agencies need before they can migrate anything.

How the Industry Responded

Two days after the signing, STMicroelectronics introduced the ST54M, the first mobile chip with a dedicated hardware accelerator for post-quantum algorithms. It runs ML-KEM (Module-Lattice-Based Key-Encapsulation Mechanism) and ML-DSA (Module-Lattice-Based Digital Signature Algorithm), the NIST (National Institute of Standards and Technology) standards finalized in 2024, on a single die alongside NFC (near-field communication), secure element, and eSIM (embedded SIM) functions. Commercial sampling is available now, with certification targeted for July 2026. That is the hardware path the federal order is pushing the rest of industry toward on the same compressed timeline.

I tell students today: nobody knows the exact day a cryptographically relevant quantum computer arrives, but the government just stopped waiting to find out. And.... I would not be surprised at all to see the deadline moved forward again.... soon.

STEM at Two Years: Community College Degrees That Pay

Most of my career has been at the community college. I directed an NSF Center of Excellence at Springfield Technical Community College and taught electronics, computer systems, and photonics there. At Holyoke Community College I still teach engineering transfer courses part time for students heading to four-year universities. Over forty years I have watched students come through two-year STEM programs and go directly into careers that surprised people who assumed a bachelor's degree was required. This post is the third in a series on degree choice and outcomes. The first two covered bachelor's programs and two-year degrees broadly. This one focuses specifically on STEM at the associate degree level: what the programs are, what they pay, and how the job outlook looks in 2026.

The macro case for STEM at any credential level is straightforward. The BLS projects STEM occupations will grow 8.1 percent between 2024 and 2034, nearly triple the 2.7 percent rate for all other occupations. The median salary across STEM occupations sits at $101,600, well above the all-occupation median. The two-year credential does not open every STEM door, but it opens more of them than most people expect, and it does so at a fraction of the cost and time of a four-year path.

The highest-paying two-year STEM programs in 2026, per BLS occupational data: information security analysts (cybersecurity) median at $119,860 with 32 percent projected job growth through 2032; radiation therapy at a median above $100,000; dental hygiene at $94,260; and registered nursing at $93,600. Below those, nuclear technicians median around $84,000, electronics engineering technicians around $67,550, and laser electro-optics technicians in the $55,000 to $65,000 range depending on industry and region. HVAC technology and computer network support round out the middle of the table at $58,000 to $62,000.

A point worth making clearly: the two-year STEM credential typically leads to technician and support roles, not engineering or research positions. That distinction matters for career planning, but it does not diminish the outcomes. An electronics engineering technician working in manufacturing or test and measurement earns $67,550 median with stable demand. A cybersecurity analyst with an associate degree and relevant certifications, CompTIA Security+ in particular, enters a field with 32 percent projected growth and a six-figure median salary. The ceiling in those careers depends more on certification, experience, and specialization than on whether the entry credential was a two-year or four-year degree.

The cost side of this decision matters as much as the salary side. Average annual tuition at a public two-year college runs about $3,990, versus over $11,500 at a public four-year institution. A student completing a two-year cybersecurity or nursing program graduates with little or no debt and enters a field paying $90,000 to $120,000. A student completing a four-year program in the same field earns more in some cases, but starts with average student loan debt above $29,000 and two additional years of foregone income. For STEM technician roles specifically, that math favors the two-year path more consistently than in most other fields.

Before committing to a two-year STEM program, check three things. First, verify that the program carries the right accreditation for your field. Nursing programs must be accredited by ACEN or CCNE for graduates to sit for the NCLEX. Engineering technology programs are credentialed by ABET. Second, check whether the career path requires licensure or certification beyond the degree itself, and build the cost and timeline for those credentials into your plan. Third, look at your specific college's job placement data for that program. National medians are a baseline; local labor market conditions move those numbers significantly in both directions.

One pathway that gets less attention than it deserves: the two-year degree as the first half of a four-year degree, paid for by an employer. Many community college STEM graduates enter the workforce directly, then pursue a bachelor's degree part time while their employer covers tuition. This is not rare. A significant share of working adults completing bachelor's degrees are doing exactly this, particularly in nursing, engineering technology, and information technology. The RN-to-BSN pathway is the most established example: a graduate earns an associate degree, passes the certification, enters the workforce as a registered nurse, and completes a BSN online or part time over two to three years, often with hospital tuition reimbursement covering most of the cost. The same model applies in engineering technology and cybersecurity, where employers in manufacturing, defense, and infrastructure actively fund continuing education. The credential upgrade from technician to technologist, meaning from associate to bachelor's degree, also typically comes with a pay bump and expanded career options. For students weighing cost, this route splits the financial risk: two years of low-cost community college tuition, then employer-subsidized completion of the bachelor's, with income throughout. The total credential is the same four-year degree. The debt load and the timeline are very different.

The community college students I’ve watched who did best in two-year STEM programs were not picking a fallback. They were picking a specific job in a specific field and treating the degree as the direct path to it. That approach still works in 2026. For some, the two-year degree is also the starting point for a four-year degree the employer ends up paying for. The programs are there. The jobs are there. Check the current numbers before you decide. Know the program, know the credential requirements, know the market.