ReadoutIQ Quantum measurement software

Readout and calibration optimization for superconducting quantum processors.

Superconducting quantum processors spend expensive wall-clock time on measurement, calibration, and certification. ReadoutIQ helps teams choose measurement windows that minimize time-to-confidence across many shots, not just maximize single-shot fidelity. In representative transmon-readout simulations, the wall-clock-aware setting reduces total certification time by about 9–11% without hardware redesign.

Representative result: ~9–11% lower certification time Mechanism: measurement-window optimization Deployment: software-first, no hardware redesign
01 · What it does

Calibration and readout, optimized for wall-clock throughput.

Current tool plus roadmap:
minimize time-to-confident-result on a running quantum processor.

Module · 01

Throughput-driven calibration

Treats readout as an information channel. Selects integration windows that minimize total certification wall-clock time, accounting for hardware overhead — not just single-shot fidelity.

Module · 02

Adaptive readout support

Future modules will evaluate when adaptive measurement strategies are useful in long-readout or high-overhead regimes. Detailed implementation is under development and is not required for the first measurement-window tool.

Module · 03

Information-extraction diagnostic

Quantifies how closely your measurement chain approaches the hypothesis-testing limit. Separates detection-inefficiency and decoherence contributions on a per-system basis.

Module · 04

Drop-in, no hardware changes

Deployed as a calibration or firmware update on existing RFSoC-class control systems. No new resonators, no new amplifiers, no requalification.

02 · Technical demo

Reproduce the result on your own parameters.

Technical demo notebooks.
Bring your own χ, κ, T₁, and hardware overhead.

measurement-window-demo

A reproducible notebook that takes your measurement-system parameters and returns the integration window that minimizes wall-clock certification time. Compares against the conventional fidelity-optimal operating point on the same hardware.

View on GitHub →
Language · Python 3.11+ Runtime · ~30 s on laptop Inputs · χ, κ, T₁, η, n̄, τoverhead Output · τrate, expected speedup
03 · Representative simulated result

The fidelity-optimal point is not the throughput-optimal point.

Parameters typical of contemporary transmon platforms.
Simulation; on-hardware validation in progress.

· Wall-clock vs. fidelity optima simulated · representative parameters
Comparison of fidelity-optimal and wall-clock-optimal readout windows
τfid — fidelity-optimal ~0.78 µs
τrate — throughput-optimal ~1.22 µs
wall-clock speedup ~9–11%
Fig. In this representative transmon-readout simulation, the single-shot-fidelity optimum and the wall-clock optimum occur at different measurement windows. Choosing the wall-clock-aware setting reduces total certification time by about 9–11% for the shown parameters. Hardware-specific results depend on the readout chain, overhead, efficiency, and noise model.
04 · Contact

Operating a superconducting QPU? Let’s talk.

Pilots, design partnerships,
and technical conversations.

Direct

Send your hardware parameters and we will return a representative speedup estimate within a few days.