Date and Time: Around 2:20 PM on May 21, 2025

Location and Temperature:

• Back of the room, around the working station: 85.5 °F
• Front of the room, around the doorway: 82.3 °F

Date and Time: Around 3:50 PM on June 2, 2025

Location and Temperature:

• Back of the room 1119, around the working station: 86 °F
• Front of the room 1119, around the doorway: 84.1 °F
• Back of the room 1129, around the working station: 78.6 °F
• Front of the room 1129, around the doorway: 78.3 °F
• In the hallway in front of room 1119: 75.2 °F

Date and Time: Around 4:50 PM on July 1, 2025

Location and Temperature:

• Back of the room 1119, around the working station: 85.7 °F
• Front of the room 1119, around the doorway: 83.5 °F
• Back of the room 1129, around the working station: 79.1 °F
• In the hallway in front of room 1119: 76.5 °F

Port 80 is kept closed by default. This might be causing the certbot auto-renewal cronjob to fail. Therefore we must renew the certificate manually.

Step 1: Open port 80. (This is needed as the certificate renewal process runs some tests which requires client communication over port 80)

Step 2: Run the following command

sudo certbot certonly --force-renew -d richardsonlab.ucr.edu

Step 3: Confirm the certificate was renewed by running the following command

sudo certbot certificates

Cross-linking instructions: How to run a Jupyter notebook in your custom Conda environment

1. Turn off the RGA filament and disconnect it.

2. Record the pressure and then close the angle valve and gate valve on the RGA line to isolate it from the system.

3. Turn off the backing and turbo pump and let the turbo pump spin to a stop by slowly leaking the chamber. The slower the safer.

4.Slowly open the vents on the chamber and the turbo pump. Making sure not to raise the pressure too fast.

5. Once done venting the chamber, open the lid by removing the bolts and prying the lid open with a long flat head screw driver.

6. Removed previous parts and placed them into clean bags. Place new parts inside of the chamber and group them together close to the center.

7. Place the lid back onto the chamber and tighten the bolts in a circular pattern until tightened all the way with the wrench.

8. Make sure all vents are closed and turn the backing pump back on.

9. The turbo pump can be turned back on when the pressure reaches e-1 torr.

10. Wait until the chamber reaches a pressure of e-6 torr before opening the angle and gate valve on the RGA line. After the RGA line is open and the pressure is still below e-6 torr, the RGA filament can be turned on and a leak test of the lid should be performed.

11. After the leak test shows no leaks, proceed with starting the low temp bake.

Avoiding Thread Contention When Using Multiprocessing with Finesse and Cython

When running Monte Carlo simulations or other computational workloads, it's common to use Python's ProcessPoolExecutor to parallelize multiple independent tasks. This approach works well—until it interacts with low-level libraries that themselves use multi-threading under the hood.

The Problem: Thread Over-Subscription

In a recent project, I ran into a significant performance issue while executing a large number of Monte Carlo trials using a process pool with 30 worker processes on Megatron (with 48 cores). Each trial ran a function that internally used cython.parallel.prange for fast, element-wise operations, which is what Finesse uses under the hood for many internal numerical calculations. Cython, via OpenMP, was configured to use all available CPU threads per process by default.

This resulted in severe thread over-subscription. With 30 parallel processes and each process attempting to use all 48 threads, the system was launching over 1,400 threads concurrently. The CPU quickly became saturated, and the tasks stalled. In some cases, the system became unresponsive, and the jobs had to be canceled repeatedly.

This happens because when the function calls into these libraries from within a Python multiprocessing context, each subprocess will attempt to use the full number of threads available to the machine.

The Solution: Limit Threads per Process

The solution is simple: explicitly limit the number of threads each subprocess is allowed to use. This can be done by setting the environment variable at the top of your script, before importing any thread-hungry libraries like Finesse.

      
import os
os.environ["OMP_NUM_THREADS"] = "1"

    

By setting OMP_NUM_THREADS to "1", we ensure that each multiprocessing worker uses only one thread internally, preventing them from overloading the system and allowing the tasks to run more efficiently.

Below are a basic diagram of what the RTD measurement circuit logically looks like and an example schematic of the actual wiring. The schematic wiring will be placed internally into a chassis, connected to the RTDs via DB25 cable.

The custom front and rear panels for the RTD readout chassis arrived last Friday. I installed them in the chassis frame to check their fit. They fit very well, so all that now remains is to complete the internal wiring and test the connections.

The chassis panel designs are archived to LIGO-D2300452 and LIGO-D2300453.

Below is the current state of the RTD readout chassis wiring. Initial continuity tests seem good, will run through one more time to confirm.

I performed another continuity test on the RTD chassis wiring, and everything seems to be set up correctly. The chassis should be ready for installation.

Below is the proposed schematic for FROSTI optical testing, chosen so enough space is allotted for prototype assembly.

Steps to be taken include:

1. Reconstruct FLIR staging apparatus
2. Move test mass stand-in to cleanroom
3. Mark FLIR camera position on cleanroom optical table at correct distance
4. Run ethernet cable into cleanroom
5. Move FLIR aside to allow for more assembly space
6. Upon assembly completion, reposition FLIR onto optical table again

Tentative plan is to begin setup early next week.

Group Meeting slides for Non-deterministic Heater Response.