QC // 01010110
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A primer on the future of compute

QUANTUM
COMPUTING
A different kind of computer.

13 SLIDES · EST 12 MIN
FIELD · PHYSICS / CS
ERA · 1982 — NOW
02 — Foundations

A bit holds one answer.
A qubit holds both.

Classical bits are switches: 0 or 1, definite at every instant. A qubit is a quantum object whose state is a continuous combination — a superposition — of 0 and 1, collapsing only when measured.

CLASSICAL BIT
0 | 1

Definite. Copyable. One state at a time.

QUBIT
α|0⟩ + β|1⟩

Probabilistic until measured. |α|² + |β|² = 1.

03 — Two quantum resources

Superposition. Entanglement.

Quantum advantage rides on two phenomena no classical machine can fake. Together they let an n-qubit register encode 2ⁿ amplitudes in parallel — and steer them with interference.

RESOURCE 01

Superposition

A single qubit lives on a continuum between |0⟩ and |1⟩. n qubits explore 2ⁿ possibilities at once — though we only get one classical answer when we look.

RESOURCE 02

Entanglement

Qubits can share a joint state that cannot be written as a product of parts. Measuring one instantly constrains the other — Einstein's "spooky action."

04 — Geometry of a qubit

The Bloch sphere

Every pure single-qubit state is a point on the surface of a unit sphere. The north pole is |0⟩, the south is |1⟩, and the equator is equal superposition. Operations are rotations; measurement collapses the vector to a pole.

|0⟩ |1⟩ |+⟩ |−⟩ |ψ⟩ θ
05 — The seed idea

Feynman, 1982

"Nature isn't classical, dammit." Simulating molecules and materials on classical hardware demands resources that grow exponentially with system size. Feynman's proposal: build a computer out of quantum stuff to model quantum stuff.

It would take another decade for the field to take shape — but every quantum algorithm that followed traces back to this lecture.

"Nature isn't classical, dammit, and if you want to make a simulation of nature, you'd better make it quantum mechanical."
— RICHARD FEYNMAN · MIT KEYNOTE · 1981/82
06 — The factoring algorithm

Shor's algorithm breaks RSA

In 1994 Peter Shor showed a quantum computer can factor an n-bit integer in polynomial time — exponentially faster than the best known classical method. RSA, which secures most of the internet, derives all its strength from factoring being hard.

CLASSICAL · BEST

~exp(n1/3)

General number field sieve. Sub-exponential, still ruinous at large n.

SHOR · QUANTUM

~n³

Polynomial. A 2048-bit RSA key falls in hours, given enough fault-tolerant qubits.

REQUIREMENT

~10⁷ qb

Recent estimates for breaking RSA-2048 with realistic error rates. We are not there yet.

07 — Search

Grover: √N search

Two years after Shor, Lov Grover showed how to find a marked item in an unsorted database of N entries using only ≈√N queries. Not exponential — but a quadratic speedup that applies to a vast class of search-shaped problems.

1996 · BELL LABS

Brute-force AES-256 drops from 2²⁵⁶ to 2¹²⁸ — still infeasible. The win is in optimization, satisfiability, ML kernels.

|0⟩ |0⟩ |0⟩ |0⟩ H H H H ORACLE DIFFUSER M M M M grover circuit · prepare → oracle ⟶ diffuse · ×O(√N)
08 — Building the thing

Four serious hardware bets

No consensus on the right physical substrate. Every approach trades coherence time, gate fidelity, connectivity and clock speed differently. The race is wide open.

Superconducting circuits
Google · IBM · Rigetti · Quantum Circuits

Fast gates, scalable lithography. Needs millikelvin dilution refrigerators.

Trapped ions
IonQ · Quantinuum · AQT

Long coherence, high fidelity, all-to-all connectivity. Slower clock.

Photonic
PsiQuantum · Xanadu

Room-temperature, networking-friendly. Probabilistic gates, high losses.

Neutral atoms
QuEra · Atom Computing · Pasqal

Reconfigurable arrays, recently scaled past 1000 atoms. Newest contender.

09 — The wall

Qubits are delicate

Decoherence, gate errors, readout errors — physical qubits today have error rates around 10⁻³ per operation. Useful algorithms need ~10⁻¹⁵. The fix is quantum error correction: encode one logical qubit across many noisy physical ones.

~1,000 phys
→ per logical qubit
10−3
today's gate error
10−15
target for shor-scale tasks
10 — 2024–25 milestones

Logical qubits, demonstrated

For the first time, logical qubits are outperforming their underlying physical components. Crossing this threshold means scaling adds reliability — error correction is no longer theoretical.

GOOGLE · 2024

Below threshold

Surface-code distance-7 logical qubit shows error suppression that improves as code distance grows.

QUANTINUUM · 2024

12 logical qubits

Trapped-ion processor entangles 12 high-fidelity logical qubits with magic-state distillation.

QUERA · 2024

48 logical qubits

Neutral-atom array runs algorithms on dozens of logical qubits — largest demo to date.

11 — What counts as a win?

Quantum advantage is hard to define

There are demonstrations where quantum hardware solves a contrived task faster than any known classical method — sampling random circuits, boson sampling, certain spin-glass problems. Whether they are useful is a separate question. Classical algorithms keep catching up too.

2019 · GOOGLE SYCAMORE

Random circuit sampling

53 qubits. First claimed "supremacy." Subsequent classical methods narrowed the gap.

2020 · USTC JIUZHANG

Photonic boson sampling

Independent demonstration on a fundamentally different platform.

2024 · GOOGLE

RCS at higher fidelity

Larger, harder-to-spoof random circuit sampling on the Willow chip.

OPEN

Useful advantage

No public, scientifically-significant problem yet solved faster on a quantum machine end-to-end.

12 — The honest read

Years away. Worth building anyway.

Quantum computing is over-hyped on the short horizon and arguably under-appreciated on the long one. The realistic timeline for broadly useful machines is measured in years to a decade-plus, not quarters. The prize, if it lands, is genuinely transformational.

NEAR TERM · BE SKEPTICAL

  • No commercial application yet pays for itself
  • NISQ-era machines too noisy for deep circuits
  • Crypto threat is real but years off — not tomorrow
  • Many "quantum" use-cases are classical in disguise

LONG TERM · TAKE IT SERIOUSLY

  • Chemistry & materials simulation: catalysts, batteries, drugs
  • Cryptanalysis — and post-quantum crypto is already deploying
  • Optimization with proven structure
  • Fundamental physics: the only computer that thinks like nature
END · 13 / 13

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