New features and important updates
- Optimization of quantum cloud computing service interfaces.
1.The quantum cloud computing chip task has added the point_label option, which allows tasks to be submitted to specified chip area labels
2.The QResult class for quantum cloud computing task results has added an interface to return raw JSON data
Here is an example of the changes in code:
prog = QProg()
prog << H(0) << measure(0, 0) << measure(1, 1)
api_key = "3041020100301306042730309478de"
service = QCloudService(api_key=api_key)
backend = service.backend("72")
options = QCloudOptions()
options.set_point_label(2)
job = backend.run(prog, 1000, options)
import time
while True:
status = job.status()
if status == JobStatus.FINISHED:
break
time.sleep(5)
result = job.result()
print(result.origin_data())
for result_list in result.get_probs_list():
print(result_list)
The output is as follows:
{"success":true,"code":10000,"message":"success","obj":{"taskId":"FF85F6804299B7ED403888E0EBA7F4C1","pilotTaskId":"31683BBD11B4486A9CA8C24CBB9663CB","errCode":0,"startTime":1745327244015,"taskState":"3","convertQProg":["[{\"RPhi\":[3,270.0,90.0,0]},{\"Measure\":[[25,3],30]}]"],"mappingQProg":["QINIT 25\nCREG 2\nU3 q[2],(1.5707963267949,-3.14159265358979,3.14159265358979)\nMEASURE q[2], c[0]\nMEASURE q[24], c[1]\n"],"mappingQubit":["{SrcQubits:[0],TargetCbits:[1,2],MappingQubits:[2]}"],"measureQubitSize":[2],"aioTimeStamp":"9:1745327247251;8:1745327245103;7:1745327244086;2:1745327245577;","requiredCore":"0","taskType":"0","taskResult":["{\"key\":[\"0x0\",\"0x1\",\"0x2\",\"0x3\"],\"value\":[0.014375101774930954,0.980093777179718,0.00015337103104684502,0.005377839785069227]}"],"aioExecuteTime":3179,"queueTime":210,"compileTime":4,"amendTime":18,"totalTime":3407,"aioCompileTime":805,"aioPendingTime":1751,"aioMeasureTime":160,"aioPostProcessTime":48,"pulseTime":30.0,"cirExecuteTime":100000.0,"QMachineType":null}}
{'00': 0.014375101774930954, '01': 0.980093777179718, '10': 0.00015337103104684502, '11': 0.005377839785069227}