Hardware

Quantum Hardware Compared: Superconducting vs Trapped-Ion vs Photonic vs Neutral-Atom

The four leading qubit modalities have wildly different tradeoffs: gate speed, connectivity, coherence time, scalability, and cost. This tutorial is an opinionated side-by-side based on 2026 hardware numbers — what each modality is best at, where each hits walls, and how to pick the right backend for a given benchmark.

intermediate · ~21 min · prereq: Tutorial 19: Surface Code and Willow

Transmon Qubits: How the Most-Deployed Superconducting Qubit Actually Works

Transmons are the single most-deployed qubit type in quantum computing — every IBM, Google, and Rigetti processor as of 2026 is built on transmons or close cousins. This tutorial builds the transmon from the underlying Cooper-pair-box physics, explains why the design tradeoff matters, surveys current 2026 hardware numbers (T1, T2, two-qubit gate error, the Willow below-threshold result), and gives an honest verdict on what the platform's hard scaling problems actually are.

advanced · ~21 min · prereq: Tutorial 20: Quantum Hardware Compared

Trapped Ion Quantum Computing: The Platform with the Best Gate Fidelities and the Slowest Gates

Trapped ions hold the published-fidelity records on essentially every quantum-hardware metric. They have the longest coherence times, the cleanest two-qubit gates, and the most natural all-to-all connectivity. They are also the slowest platform by orders of magnitude, with system architectures that are harder to scale than superconducting alternatives. This tutorial covers the physics, the leading systems (Quantinuum H2/Helios, IonQ Tempo), the QCCD architecture, and where the trapped-ion advantage actually matters.

advanced · ~21 min · prereq: Tutorial 33: Transmon Qubits

Neutral Atom Quantum Computing: The Platform That Closed the Gap in Three Years

Neutral-atom quantum computers — Rydberg arrays of laser-trapped atoms — went from research curiosity to flagship-tier platform between 2022 and 2025. Atom Computing crossed 1,000 qubits in 2023; QuEra and Pasqal demonstrated logical qubits in 2024-2025; the 2025 Sales Rodriguez logical magic-state distillation experiment was on neutral atoms. This tutorial covers the optical-tweezer / Rydberg architecture, current 2026 numbers, and why neutral atoms are the most-improved platform of recent quantum-computing history.

advanced · ~19 min · prereq: Tutorial 34: Trapped Ion Quantum Computing

Photonic Quantum Computing: The Dark Horse Architecture That Skips Cryogenics

Photonic quantum computers use photons as qubits and measurements as the source of nonlinearity — a fundamentally different architecture from transmon, ion, and neutral-atom platforms. PsiQuantum, Xanadu, ORCA, Quandela, and QuiX are the leading commercial efforts; the fusion-based quantum computing model gives photonics a credible path to fault tolerance without ever needing a long-lived coherent quantum state. This tutorial covers the architecture, the leading companies, and where the gamble actually pays off.

advanced · ~19 min · prereq: Tutorial 35: Neutral Atom Quantum Computing

Cryogenic Control Electronics: The Unsung Bottleneck of Scaling Superconducting Quantum Computers

Every superconducting qubit needs control wires running from room-temperature electronics through a dilution refrigerator down to ~10 mK. Naively, scaling to a million qubits would require a million wires through cryostats — physically impossible. The solution is cryogenic control electronics: classical control logic operating at 4 K or 10 mK, multiplexed control of many qubits per wire. This tutorial covers the hardware, the heat-budget engineering, and why this is one of the harder scaling problems of fault-tolerant quantum computing.

advanced · ~14 min · prereq: Tutorial 33: Transmon Qubits

Quantum Control Theory: GRAPE, CRAB, and the Pulse Engineering of High-Fidelity Gates

A quantum gate is, on real hardware, a shaped microwave pulse. Designing pulses that produce desired unitaries while suppressing leakage, decoherence, and crosstalk is the discipline of quantum optimal control. GRAPE (Khaneja 2005) is the gradient-based workhorse; CRAB (Caneva 2011) is the gradient-free alternative; modern automatic-differentiation methods extend the toolkit. This tutorial covers the methods, the cost functions, and the engineering tradeoffs.

advanced · ~14 min · prereq: Tutorial 33: Transmon Qubits, Tutorial 61: Cryogenic Control Electronics

Randomized Benchmarking: How to Measure Gate Fidelity Without Tomography

Randomized benchmarking (RB) is the standard protocol for measuring gate fidelities on real quantum hardware. Run random Clifford sequences of varying length, measure how the survival probability decays, fit an exponential, and extract the per-gate error. RB is fast, scalable, and produces a single robust fidelity number that is the standard quoted hardware metric. This tutorial covers the protocol, the math behind why exponential decay happens, the variants (interleaved, simultaneous, mirror), and the limitations.

intermediate · ~14 min · prereq: Tutorial 25: The Clifford Group, Tutorial 33: Transmon Qubits

Gate-Set Tomography: The Detailed-and-Expensive Twin of Randomized Benchmarking

Gate-set tomography (GST) is the most detailed hardware-characterization protocol available. Unlike randomized benchmarking which gives one number per gate, GST returns a full description of every gate's action including coherent errors, incoherent errors, and SPAM errors. The price: a much larger data set, hundreds-to-thousands of distinct circuits, and complex post-processing. This tutorial covers what GST measures, why it differs from RB, and when the extra detail is worth the cost.

advanced · ~14 min · prereq: Tutorial 47: Density Matrices and Mixed States, Tutorial 63: Randomized Benchmarking