# Quantum Computing — A Different Kind of Computer

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Category: Future
Slides: 13
Updated: 2026-05-17T20:55:58.095Z
Tags: catalog, future, quantum, computing

## Summary

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. Key sections include: QUANTUM COMPUTING A different kind of computer.; A bit holds one answer. A qubit holds both.; Superposition. Entanglement.; The Bloch sphere; Feynman, 1982; Shor's algorithm breaks RSA; Grover: √N search; Four serious hardware bets; Qubits are delicate; Logical qubits, demonstrated.

## Slide Outline

1. QUANTUM COMPUTING A different kind of computer.
2. A bit holds one answer. A qubit holds both.
3. Superposition. Entanglement.
4. The Bloch sphere
5. Feynman, 1982
6. Shor's algorithm breaks RSA
7. Grover: √N search
8. Four serious hardware bets
9. Qubits are delicate
10. Logical qubits, demonstrated
11. Quantum advantage is hard to define
12. Years away. Worth building anyway.
13. Keep learning.

## Slide Transcript

### Slide 1: QUANTUM
COMPUTING
A different kind of computer.

- A primer on the future of compute
- 13 SLIDES · EST 12 MIN
- FIELD · PHYSICS / CS
- ERA · 1982 — NOW

### Slide 2: A bit holds one answer.
A qubit holds both.

- 02 — Foundations
- 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.

### Slide 3: Superposition. Entanglement.

- 03 — Two quantum resources
- 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."

### Slide 4: The Bloch sphere

- 04 — Geometry of a qubit
- 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.

### Slide 5: Feynman, 1982

- 05 — The seed idea
- "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

### Slide 6: Shor's algorithm breaks RSA

- 06 — The factoring algorithm
- 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.

### Slide 7: Grover: √N search

- 07 — 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.

### Slide 8: Four serious hardware bets

- 08 — Building the thing
- 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.

### Slide 9: Qubits are delicate

- 09 — The wall
- 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

### Slide 10: Logical qubits, demonstrated

- 10 — 2024–25 milestones
- 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.

### Slide 11: Quantum advantage is hard to define

- 11 — What counts as a win?
- 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.

### Slide 12: Years away. Worth building anyway.

- 12 — The honest read
- 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

### Slide 13: Keep learning.

- END · 13 / 13
- A field still being built. Pick a thread and pull.
- ▶ Quantum Computing Explained — YouTube
- ▶ Shor's Algorithm — YouTube
- REFS · NIELSEN & CHUANG · ARXIV:QUANT-PH · QUANTA MAGAZINE · GOOGLE QUANTUM AI BLOG


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