Trump’s 2028 Quantum Computer Bet Crashes Into Reality

On June 22nd, Washington set a 2028 target for a quantum computer powerful enough for scientific discovery even though no quantum computer has conclusively performed a single useful task.

That timing is the story. Donald Trump's science adviser promised a “quantum computer powerful enough for scientific discovery by 2028,” and Trump issued a new executive order the same day to speed up the US quantum computing industry in its competition with China, according to The Verge. The political clock is now running faster than the machines.

XOOMAR analysis: the order treats quantum computing as strategically urgent, but urgency doesn't solve the core technical problem. Today's systems are still too small and error-prone for commercially relevant work. The gap between “national priority” and “useful machine” is where the hype lives.

June 22nd put a deadline on a quantum computer that still hasn't proved utility

The strongest case for quantum computing remains theoretical. Proponents expect future machines to help simulate molecules, develop battery materials or medicines, and eventually threaten RSA encryption. But current quantum computers, including Google's Willow, are still primitive chips, not production systems for drug discovery or cryptography.

That distinction matters. A government can accelerate funding, procurement, and coordination. It cannot order physical qubits to become stable.

The Verge frames the current contradiction cleanly: researchers have made genuine progress, but the progress is incremental, expensive, and often too technical for public narratives. Over the last decade, Google, IBM, Amazon, Microsoft, governments, and startups have poured billions into the field. In May, the Trump administration said it would provide $2 billion to nine quantum computing companies, with IBM receiving $1 billion. In June, IBM said it plans to invest more than $10 billion over the next five years.

The money is real. The useful quantum computer is not.

The quantum gap is measured in errors, not press releases

Raw qubit counts make good headlines, but they don't equal computing power. The useful unit is the logical qubit, an error-corrected unit built from multiple noisy physical qubits. Fewer physical qubits per logical qubit makes scale easier.

The recent numbers show progress, not arrival:

That looks encouraging. It also shows why a useful machine is hard. Algorithms for valuable applications tend to be long, and long quantum algorithms compound errors. Better qubits help because they hold information longer, which allows more operations before noise ruins the result.

Andrew Houck of Princeton University and colleagues reported last November that they had made a superconducting qubit that holds information three times longer than the previous record holder. Houck described the improvement as “all very subtle tweaks.” That phrase should sit next to every 2028 or 2029 roadmap. The field advances through hard materials work, fabrication control, and error correction, not through calendar targets.

Microsoft's June Majorana 2 claim turned a physics dispute into a product timeline

In June, Microsoft announced a quantum chip called Majorana 2 and said the hardware advance accelerated its path to a “scalable, practical quantum computer” by 2029. The company is betting on Majorana particles, which, if demonstrated and controlled as Microsoft claims, could produce qubits with fewer errors and reduce the burden of error correction.

That “if” is enormous.

Henry Legg, a physicist at the University of St. Andrews and a longtime Microsoft critic, told The Verge:

“This is complete codswallop.”

Legg published a Nature paper on June 24th criticizing Microsoft’s quantum claims from a year earlier and pointing to what he sees as discrepancies between papers and press releases. He argues Microsoft has not successfully created a Majorana particle, the core building block of its design.

Microsoft rejected the criticism. Its quantum lead, Chetan Nayak, told The Verge:

“We 100 percent stand behind our results. We stand by our roadmap.”

XOOMAR analysis: this is the pattern investors and policymakers need to understand. A claimed hardware milestone is not the same thing as a machine that performs a useful computation better than classical alternatives. Quantum firms often compress uncertainty into timelines because timelines attract money, talent, and political attention.

From 2019 quantum advantage to 2025 benchmark wins, usefulness keeps slipping away

The industry has already shown that quantum devices can beat classical computers on narrow tasks. In 2019, Google announced that its quantum computer had performed a task faster than the best supercomputer, a milestone widely called quantum advantage. The task involved generating random numbers and had no practical application.

Last October, Google claimed another quantum advantage demonstration, using simulations of molecules with 15 and 28 atoms to study magnetic behavior in a specific scenario. Dries Sels, a physicist at Boston University, told The Verge the experiment showed “high precision” in machine control but was designed to show advantage rather than usefulness.

“It doesn’t simulate anything interesting,” Sels said.

Google spokesperson Jason Freidenfelds defended the result, saying Google's 2025 result in Nature was “the first demonstration of verifiable quantum advantage on hardware” and “an indicator of rapid progress towards useful quantum computing.”

Both can be true. The demos can be scientifically meaningful and commercially irrelevant. That is the central tension.

For XOOMAR readers tracking how technical ambition collides with delivered economics, the same discipline applies across hardware-heavy tech. Roadmaps need proof points, whether in AI Data Centers Turn RAM Prices Against Cheap New PCs or Xbox Price Increase Shoves Series X to $799 in Cost Shock. A roadmap is not a product. A benchmark is not a business case.

Researchers, companies, and governments are not chasing the same quantum future

Researchers see a long engineering fight. Companies need confidence, customers, capital, and talent. Governments are focused on strategic competition, including China, and on future cryptographic risk.

That creates three different incentives:

• Scientists: reward replication, error reduction, and better control.
• Companies: reward milestones, roadmaps, and attention.
• Governments: reward domestic capability, security planning, and speed.

The encryption issue is the clearest near-term policy concern. In 1994, Peter Shor developed a quantum algorithm that should be able to break RSA encryption on a sufficiently powerful machine. On June 22nd, Trump also issued another executive order aimed to “migrate” government computers to “post-quantum cryptography” by 2030 or 2031.

That migration may matter sooner than quantum drug discovery. It does not require a useful quantum computer to exist today. It requires taking the future threat seriously without pretending the future has already arrived.

By 2028, better demos would not prove the promised revolution

XOOMAR analysis: the most likely near-term outcome is more funding, more lab progress, more specialized chips, and more arguments over benchmark claims. That would still be progress. It just wouldn't validate the 2028 promise.

The evidence that would change the thesis is specific: replicated Majorana results across multiple chips, logical qubits scaling into long algorithms, and a useful task solved better than classical alternatives. The evidence that would weaken the hype is also specific: more contrived advantage demos, more disputed press releases, and more roadmaps that move faster than error correction.

A useful quantum computer may eventually matter enormously. The industry will earn broader trust when it stops selling the destination as if it has already arrived.

Impact Analysis

• Washington is putting a firm political deadline on a technology that has not yet demonstrated practical utility.
• The funding push could accelerate research but cannot by itself solve quantum computing's core engineering problems.
• The gap between national-security urgency and technical readiness is likely to fuel more hype around the sector.