LLQ Series [Let's Learn the Quantum Series]

As we all embark on our journey towards Quantum systems, the first building block we stumble upon is the limit of the humble ‘bit’. For someone new to quantum, it’s important to understand why classical computers — however powerful — are approaching a wall on certain problems. This blog looks at the real Barrier classical computing is hitting, and introduces the Bit as the reliable Bruiser that got us this far — before showing why even a bruiser has its limits.

Barrier 1.

Moore’s Law is hitting a physical wall. Faster chips will keep solving bigger problems forever is a Myth.

Transistors v/s Physics

• For decades, Moore’s Law promised that transistor density (and therefore speed) would roughly double every two years.
• Transistors today are shrinking toward the size of just a few atoms — and at that scale, classical physics starts giving way to quantum physics, whether engineers want it to or not.
• A quick background on why this matters: at nanometer scale, electrons no longer always behave the way classical circuits expect. A phenomenon called quantum tunneling lets electrons “leak” through insulating barriers that should, classically, block them completely. When this happens inside a transistor that’s supposed to be switched off, current leaks through anyway — this is called leakage current. It wastes power, generates heat, and gets worse the smaller the transistor gets.
• Chipmakers have responded with multi-core designs and specialized hardware (GPUs, TPUs) — clever workarounds, but they don’t remove the underlying wall. They just delay hitting it.

Summary: This is a genuine physical barrier, not a design choice we can engineer our way past indefinitely. The closer transistors get to the atomic scale, the more classical computing runs into quantum effects it was never built to handle.

Bruiser 1.

The Bit — computing’s tireless heavyweight (still basic unit?)

• A bit holds exactly one of two values at any time: 0 or 1. No ambiguity, no in-between.
• Every computation — spreadsheets, video calls, AI models — is built from long sequences of bits, flipped one at a time by logic gates.
• For 70+ years, the bit has been the dependable workhorse of the digital age: simple, robust, and endlessly scalable — right up until physics itself started pushing back (Barrier 1).

Summary: The bit earned its reputation as computing’s toughest, most reliable unit. But being tireless doesn’t mean being limitless — a bruiser built to hold one value at a time was never going to be the right tool for problems that need to explore many values at once.

Barrier 2.

Some problems don’t scale — they explode.

Linear Power v/s Exponential Problems

• Adding more transistors, more cores, or more cloud servers gives linear or incremental gains in speed.
• Certain problems — simulating a molecule, breaking modern encryption, optimizing complex logistics — grow exponentially with size. Each additional variable doesn’t add work, it multiplies it.
• Example: Checking every possible route across just 20 delivery stops means evaluating roughly 10^18 combinations. A computer checking a billion routes a second would still take over 30 years to check them all — and this problem only has 20 stops.

Summary: This is the real barrier at the heart of this whole series: some problems grow so fast that even a perfect classical computer would take longer than the age of the universe.

The Real Need for Quantum

[“quanto ho capito”].

Keeping aside jargons, and the need for quantum computing comes down to this:

• We’re not running out of computing power in general — we’re running out of a specific kind of computing power, for a special kind of problem.
• The world increasingly needs answers to questions that are exponential by nature: designing new medicines and materials atom-by-atom, securing data as threats evolve, optimizing sprawling supply chains and energy grids, and helping AI search through massive possibility spaces.
• Classical bits, no matter how fast or how many, hit a wall on these problems — not because engineers aren’t clever enough, but because a bit that only holds one value at a time is structurally the wrong shape for a problem that needs to explore many values at once.
• Quantum computing isn’t “AI’s replacement” or “a faster computer.” It’s a different kind of unit — the qubit — built for exactly the shape of problem the bit was never designed to solve.
  That’s the real need, plainly put: not more power, but a fundamentally different kind of power for a fundamentally different kind of problem.

Just started, let’s discover the qubit — the unit built to meet this demand — in the following blog.

Glossary:

Byte (noun) — a classical unit of digital information, built from a fixed sequence of bits, each holding a single definite value.
Bound (noun) — a limit that constrains what something can achieve, no matter how it’s optimized.
Quantum tunneling (noun) — a quantum-physics effect where a particle passes through a barrier that classical physics says it shouldn’t be able to cross; at transistor scale, this causes unwanted leakage current.