Measurement-Based Quantum Computing
In the one-way model, computation proceeds by measuring qubits of a pre-built entangled cluster state, not by applying gates.
A different model
The circuit model applies unitary gates to qubits over time. Measurement-based quantum computing (MBQC), also called the one-way model, first prepares a large, highly entangled resource state and then computes purely by measuring its qubits one at a time. The entanglement is the resource; measurement drives the logic. It is provably equivalent in power to the circuit model.
Cluster states
The standard resource is a cluster state: qubits on a lattice, each initialized in superposition, with a controlled-phase entangling operation applied between neighbors. Once built, the state is not modified by further entangling gates; the computation lives entirely in a chosen pattern and basis of single-qubit measurements.
Adaptivity and feed-forward
- Each measurement yields a random outcome
- Later measurement bases are adjusted to compensate for earlier outcomes (feed-forward)
- This adaptivity is what makes the deterministic logical result emerge from random measurements
Why it fits photonics
Photonic hardware finds stored interactions hard but measurement easy, so building an entangled cluster once and then measuring it plays to its strengths. Fusion-based quantum computing generates small entangled resources and fuses them by measurement into a fault-tolerant fabric, a leading route for scalable photonic machines.
MBQC shows that gate sequences are only one way to express a quantum algorithm. The same computation can be encoded in the geometry of an entangled state and the schedule of measurements applied to it, which shifts the hardware burden from coherent control to reliable entanglement generation and fast detection.