Why Quantum Matters

Gregory Chassapis
14 hours ago
3 min read

Computers have fundamentally changed the world. Now, change seems to be coming for them.

Enter quantum computers.

The basic premise is that Quantum and Classical computers differ in that classical computers process information as bits that are either zero or one. In other words, the outcomes are clearly defined as one or the other and are limited to only those two outcomes. Quantum computers replace bits with qubits, which allow for multiples outcomes since qubits are in three states simultaneously and, by definition, can explore multiple outcomes at once. This allows certain problems such as molecular simulation, optimization across vast solution spaces, and breaking specific kinds of encryption to suddenly become possible in a way they are not on even the most advanced and powerful supercomputers.

That does not mean quantum computing will replace classical computing. Instead, for a narrow and economically important set of problems, it promises a step-change in capability and capacity.

From Concept to Viability

Two developments have turned quantum from a perpetual ten-years-out story into something investable and usable, today. First, in late 2024 and through 2025, Google's Willow processor demonstrated “below-threshold” quantum error correction, meaning that adding more physical qubits actually reduced the logical error rate rather than amplifying it. That had been a nearly thirty-year goal of the field. Published research on quantum error correction codes more than tripled in 2025, and competing approaches from IBM, Microsoft, IonQ and Quantinuum are all steadily advancing.

The second is commercial traction. Once the province of physics labs, quantum compute now has a growing roster of enterprise customers who have signed multi-year contracts, including Boehringer Ingelheim, JPMorgan, Airbus, and a long list of national laboratories. Access is also broadening, with AWS Braket, Microsoft Azure Quantum, and IBM Quantum Network now offering quantum compute as a cloud service, further enabling enterprise adoption.

Impact on the Future Computing Stack

Quantum will function as a specialized accelerator alongside classical computing, much like GPUs do for AI workloads today. The most credible near-term applications are in computational chemistry (designing drugs and catalysts), materials science (battery and semiconductor design), logistics and financial optimization, and machine learning. Equally important, quantum computing creates its own defensive market: post-quantum cryptography.

The encryption securing most banking, email, and web traffic (RSA and elliptic-curve cryptography) rests on math problems classical computers cannot solve in practical time, such as factoring very large numbers. Quantum computers would solve those problems quickly, rendering today's encryption obsolete and exposing any traffic adversaries have quietly archived for later decryption.

Real Risks Worth Acknowledging

Quantum computing is a high-variance theme, but there is an emerging consensus that quantum will meaningfully scale between 2028 and the mid-2030s. Cost is the central engineering challenge here. It takes hundreds of physical qubits today to construct a single fault-tolerant logical qubit, so cost per logical qubit (not per physical qubit) must fall by orders of magnitude before quantum becomes economically competitive at scale.

Cooling is a separate structural bottleneck.

Superconducting qubits, the dominant architecture, require operating temperatures near 10 millikelvin by circulating a mixture of helium-3 and helium-4. Helium-3 is scarce and has been rationed by the U.S. government for over a decade to ensure availability for national security-related applications. Technological risk compounds these constraints since the winning qubit architecture is not yet known, and well-funded entrants in China and Europe are advancing on parallel tracks. This includes the eventual cooling architecture that will help make the technology economically viable- one that might not necessarily require Helium 3.

Looking Ahead

To some, quantum computing today sits roughly where AI did in the early 2010s. The science is real, the first useful applications are visible, and the commercial inflection is plausible but not yet proven. The next several years will be defined by whether the field can convert technical milestones into durable economics and whether logical qubits can become cheap enough to deploy at scale. If, for example, DARPA and others can successfully fund and develop an alternative for cryogenic infrastructure that doesn’t rely on helium-3, it will have massive implications for sector growth.

Progress will be uneven, and adjacent markets such as post-quantum cryptography may reach commercial scale before general-purpose quantum computing does. Regardless, the breakthroughs in error correction, the depth of corporate offtake, and the government dollars flowing in point to an industry crossing from research project into something more durable.

Sources

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