---
id: zhinst-timing-models
version: "26.7.0"
license: MIT
license_treatment: permissive
maintenance: active
---

# zhinst-timing-models — Feedback Data Latency model for PQSC, SHF- and HDAWG systems.

License: permissive · Maintenance: active · Downloads: 87.6K/mo

## What it is and what it does

This package provides a computational model for calculating feedback latencies in Zurich Instruments quantum control systems. It encapsulates timing parameters for PQSC, SHF, and HDAWG hardware, allowing users to query expected delays in quantum feedback loops given a system configuration (generator type, analyzer type, PQSC mode, and trigger source).

The package is designed for quantum researchers and engineers who need to understand or predict timing behavior in their quantum control setups. It depends on numpy and pyyaml and supports Python versions from 3.8 through 3.14. The API centers on instantiating a QCCSFeedbackModel with a system description, then calling methods to retrieve latency values in clock cycles.

Use it for:

- Calculate expected feedback loop latency for a given HDAWG-SHFQA-PQSC configuration before running experiments
- Validate timing assumptions in quantum control sequences by querying model latencies
- Determine whether a proposed system architecture meets latency requirements for real-time feedback
- Compare latencies across different trigger sources and PQSC modes to optimize system design

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Provides feedback latency model parameters for Zurich Instruments quantum control systems (PQSC, SHF, HDAWG), enabling calculation of timing delays in quantum feedback loops.

Yes, if you are working with Zurich Instruments quantum control hardware and need to understand or predict feedback latencies. The package is actively maintained, has no known vulnerabilities, and carries a permissive license. Install friction is low and the API is straightforward. Not relevant for users outside the Zurich Instruments ecosystem.

## Install

pip install zhinst-timing-models
uv add zhinst-timing-models
poetry add zhinst-timing-models

## Installing zhinst-timing-models

Before you install: Low friction install with only two lightweight runtime dependencies (numpy, pyyaml). Active maintenance with a release 15 days old indicates ongoing support.

License in practice: MIT license is permissive and places no restrictions on use, modification, or distribution in commercial or private projects.

Quickstart:

pip install zhinst-timing-models

from zhinst.timing_models import (
    QCCSFeedbackModel,
    get_feedback_system_description,
    SGType,
    QAType,
    PQSCMode,
    TriggerSource,
)

model = QCCSFeedbackModel(
    description=get_feedback_system_description(
        generator_type=SGType.HDAWG,
        analyzer_type=QAType.SHFQA,
        pqsc_mode=PQSCMode.DECODER,
        trigger_source=TriggerSource.ZSYNC,
    )
)
awg_clock_cycles = model.get_latency(...)

Verify before relying:

- Whether the package supports all PQSC, SHF, and HDAWG system variants or only a subset
- Whether latency calculations account for all sources of delay or only specific feedback paths
- Whether the model is validated against actual hardware measurements

## Package facts

- License: MIT (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 87.6K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

quantum feedback latency timing, PQSC HDAWG SHF timing models, quantum control system latency, feedback loop delay calculation, Zurich Instruments timing parameters, quantum processor timing analysis, QCCS feedback model, quantum-computing, hardware-timing

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