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David/iqm5q march 2024 #126

Merged
merged 20 commits into from
May 10, 2024
Merged

David/iqm5q march 2024 #126

merged 20 commits into from
May 10, 2024

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DavidSarlle
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@DavidSarlle DavidSarlle commented Mar 11, 2024

Latest chracterization of iqm5q chip (1q gates).

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When all the qubits are operated at the same time the fidelities decrease a little bit until we chracterized the couplers:

  • q0: 80%
  • q1: 79%
  • q2: 76%
  • q3: 82%
  • q4: 83%

@@ -152,10 +152,11 @@ def create():

# flux
for i in range(6, 11):
channels[f"L4-{i}"].power_range = 0.8
channels[f"L4-{i}"].power_range = 9
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This is not a valid value for power range for this instrument. This is HDAWG, and for it the power range seems to be in volts (while for the other instruments it is DB). The valid values are 200mV, 400mV, 600mV, 800mV, 1V, 2V, 3V, 4V, 5V.

For testing my changes in qiboteam/qibolab#848 I used 1V, and things worked perfectly fine.

# flux couplers
for i in range(11, 15):
channels[f"L4-{i}"].power_range = 0.8
channels[f"L4-{i}"].power_range = 9
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same here

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DavidSarlle commented Mar 25, 2024

@hay-k thanks for the review. I set 9 because I could not find in the documentation what was the maximum value accepted in the PR and it is rounded to the higher allowed value. So, thanks for the comment, I will write a comment in this platform section for future characterization as I did with the PR values for the drive for example.

I will set the flux PR to 5, while trying to characterize the coupler because we need to shift the high freq qubit to put it near the low qubit freq. As you know, right now the qubits are not shifting with the flux amplitude so, until them, I think we need to amplify as much as possible the bias to observe a shift.

@DavidSarlle DavidSarlle requested review from hay-k and GabrielePalazzo and removed request for stavros11, igres26 and aorgazf April 2, 2024 07:05
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DavidSarlle commented Apr 18, 2024

I have checked again this runcard after the latest warm up and cool down and seems to be good. All the fidelities for single qubit are more or less the same (in fact are better for q1 95% and q2 85%). So, from my side this runcard can be merged into main.

http://login.qrccluster.com:9000/Lb1azQyVToandwv8Q4zgwg==

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DavidSarlle commented Apr 18, 2024

Refined all single qubit characterization:

Single shot classify (all qubits together) decreases a little bit as expected:
http://login.qrccluster.com:9000/LyKcYZnZTnCgADpOkuQK_w==

If the classifier is run qubit by qubit the fidelities are much better as expected:

q0 83%
q1 94%
q2 87.6%
q3 88%
q4 87%

From my side this runcard is ready to be merged into main.

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Since this is tested and working, we could consider merging to have available on main (in light of potential version updates).

@DavidSarlle DavidSarlle merged commit 1c15c16 into main May 10, 2024
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@DavidSarlle DavidSarlle deleted the david/iqm5q_March_2024 branch May 10, 2024 06:26
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4 participants