Skip to main content

九章光量子真机云接入软件包(jiuzhang SDK)

Project description

JiuZhang Photonic Quantum Cloud Platform Python SDK

jiuzhang-sdk is the Python SDK for the JiuZhang photonic quantum cloud platform. It helps Python scripts and Jupyter notebooks submit Gaussian Boson Sampling (GBS) tasks, poll task status, parse returned results, and run lightweight local analysis.

📥 Installation

Install the current pre-release:

pip install --pre jiuzhang-sdk

Install a specific version:

pip install jiuzhang-sdk==0.1.0a25

💡 Tip: If you want to experience the most complete workflow (including environment checks under Jupyter, HTML table rendering, and local sampling data analysis comparisons such as TVD, Hellinger distance, and JS divergence), it is recommended to check out the Jupyter Notebook Example (sdk_full_usage.ipynb) at the root of the repository.

🚀 Quickstart

Set your API Key and Project ID before running:

export JIUZHANG_API_KEY="your-api-key-here"
export JIUZHANG_PROJECT_ID="EXP-39dfbfdcab444d32"

PowerShell:

$env:JIUZHANG_API_KEY="your-api-key-here"
$env:JIUZHANG_PROJECT_ID="EXP-39dfbfdcab444d32"

Python:

import os
from jiuzhang import CloudClient, GBSParams

# Initialize client using environment API key and target API base URL
client = CloudClient(
    base_url="https://api.jiuzhang.com/api/v1",
    api_key=os.environ["JIUZHANG_API_KEY"],
)

# Build GBS task parameters (write other parameters directly in code)
params = GBSParams(
    project_id=os.environ["JIUZHANG_PROJECT_ID"],
    quantum_computer_id="PH_QC_04",
    mt=300,
    pump_energy_nj=4.6,
    task_name="GBS experiment 001",
)

result = client.run_gbs(params)
print(result.task_id)
print(result.status_name)
print(result.quantum_computer_id)

client.close()

🧩 Core Concepts

☁️ CloudClient

CloudClient.png

CloudClient is the main entry point of the SDK, used to establish HTTP communication with the remote JiuZhang Photonic Quantum Cloud Platform. It handles runtime complexity estimations, task submissions, and polling status queries.


⚛️ GBSParams

GBSParams is the typed task configuration object for GBS experiments.

from jiuzhang import GBSParams

params = GBSParams(
    project_id="EXP-39dfbfdcab444d32",
    quantum_computer_id="PH_QC_04",
    mt=300,
    pump_energy_nj=4.6,
    task_name="GBS experiment 001",
)
Field Type Required Description
project_id str Yes Project experiment_code on the cloud platform
quantum_computer_id str Yes Target cloud quantum computer ID (e.g. PH_QC_04)
mt int Yes Time-bin count, range 1 <= mt <= 500
pump_energy_nj float Yes Pump pulse energy in nJ
squeezing_param float | None No Squeezing parameter
task_name str No Custom display name for the task, up to 200 characters

📊 GBSResult

GBSResult is the parsed object that holds GBS task states and experimental result distribution curves.

Property Description
task_id Unique task ID generated by the cloud platform
status_name Normalized task status string (e.g., SUCCESS, FAILED, PENDING, RUNNING)
project_id Associated Project ID
quantum_computer_id Target quantum computer ID where the task ran
experimental_distribution Experimental distribution data points (experimental inside result_map_points)
ground_truth_distribution Reference ground-truth distribution data points (ground_truth inside result_map_points)
result_map_points All computed probability distribution curves returned by the server
download_url URL to download the raw sampling result data file from the cloud
raw The original raw response JSON dictionary from the cloud API

🏗️ Architecture

The SDK adopts a lightweight client-only architecture, shielding users from complex quantum hardware driver orchestration:

structure-chart.png

Layer Responsibility Key Components
User Layer Python scripts, Jupyter Notebooks, business applications User Code
SDK Layer Parameter validation, task lifecycle management, result parsing CloudClient, GBSParams, GBSResult
Transport Layer Request authentication, header injection, HTTP JSON transport TokenManager, HTTP Client
Cloud Platform Layer Quantum calculation services, classical complexity estimation JiuZhang Photonic Quantum Cloud Platform

🧱 Components

module.png

  • ☁️ CloudClient: Connects to the cloud service, submits tasks, queries status, and gets GBS results.
  • ⚛️ GBSParams: Wraps physics and run configuration parameters for GBS GBS tasks.
  • 📊 GBSResult: Parses and holds task statuses and distribution curves.
  • 🔐 TokenManager: Validates API Keys and handles log masking/protection.
  • 📈 jiuzhang.gbs.analysis: Local lightweight analysis toolbox (e.g., TVD, Hellinger distance, JS divergence).
  • 📒 jiuzhang.jupyter: Jupyter Notebook integration helpers (HTML formatting and environment checks).

🌐 Cloud API Contract

The SDK interacts with the cloud service via these RESTful HTTP endpoints:

SDK method HTTP path Description
estimate_runtime(...) / estimate_gbs(params) POST /estimate Estimate classical simulation runtime
submit_task(...) / submit_gbs(params) POST /tasks/submit Submit a GBS GBS experiment task
get_result(task_id) GET /tasks/{task_id} Fetch task status and distribution curves
run_experiment(...) / run_gbs(params) Integrated Workflow Estimate -> Submit -> Poll -> Parse

All communication is authenticated via the X-Jiuzhang-API-Key header. The SDK parses response payloads, validates internal code status, and raises specific exceptions if code != 0.


📒 Jupyter Notebook Integration

The SDK provides specialized helpers to optimize Jupyter interactive workflows. For the complete Notebook example, please refer to: sdk_full_usage.ipynb.

from jiuzhang.jupyter import display_gbs_result, get_notebook_client, show_environment

# 1. View masked current environment variables
show_environment()

# 2. Get client automatically and execute a GBS task
client = get_notebook_client()
result = client.run_gbs(params)

# 3. Render a beautiful HTML table summary in the notebook cell
display_gbs_result(result)

🛠️ Development & Testing

Under the code/ directory:

# Format code style
ruff format src tests
# Run static checks
ruff check src tests
# Run strict static typing checks
mypy src
# Run test suite
pytest

📄 License

Proprietary. Copyright 2026 JiuZhang Quantum. All rights reserved.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

jiuzhang_sdk-0.1.0a25.tar.gz (29.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

jiuzhang_sdk-0.1.0a25-py3-none-any.whl (26.8 kB view details)

Uploaded Python 3

File details

Details for the file jiuzhang_sdk-0.1.0a25.tar.gz.

File metadata

  • Download URL: jiuzhang_sdk-0.1.0a25.tar.gz
  • Upload date:
  • Size: 29.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.11.24 {"installer":{"name":"uv","version":"0.11.24","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":null,"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}

File hashes

Hashes for jiuzhang_sdk-0.1.0a25.tar.gz
Algorithm Hash digest
SHA256 fdcccd4ccf58c3b379cd36c0a681c8aa4996dea15e3b552a21d8484b3a72cfe8
MD5 3e42dd01d97b5f5b52cf5c709b408827
BLAKE2b-256 e98524b63b080658560545f2a0297436522c05db7de076358012a8c6c62ce992

See more details on using hashes here.

File details

Details for the file jiuzhang_sdk-0.1.0a25-py3-none-any.whl.

File metadata

  • Download URL: jiuzhang_sdk-0.1.0a25-py3-none-any.whl
  • Upload date:
  • Size: 26.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.11.24 {"installer":{"name":"uv","version":"0.11.24","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":null,"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":null}

File hashes

Hashes for jiuzhang_sdk-0.1.0a25-py3-none-any.whl
Algorithm Hash digest
SHA256 ccb7e6005e8416b3fb635a85199068734d2121adf55395d3dae8cd71a727dfc4
MD5 651b97a46a7680f31d607a671117f73b
BLAKE2b-256 778f63368ab54a536f9273a3400585f55c3282489c8356165df9345191100ba7

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page