ID 
Date 
Author 
Type 
Category 
Subject 
83

Wed Sep 28 22:11:31 2022 
Jennifer Hritz  General  Optical Contacting  Looked at Thor Lab slides 
While finalizing my work plan for the quarter, I decided to look at the Thor Lab slides. This was instructive because they highlighted the troubles I will have with working with silicone. They are fragile and their small, thin sizes makes cleaning and manipulating them (without contamination) much more difficult compared to the glass sides from before.
I tried cleaning and bonding them the same way as the larger slides. Rubbing them together did not work like with the larger sides, but that may also be a function of being more careful, as not to break them. Once I cleaned them, it only took a tap from my finger to get the center to bond, but the bonded surface area still did not spread out like it did in the YouTube videos (http://youtu.be/se3K_MWR488?t=80). By pressing down around the bonded area, I could expand it slighty. Note that I did crack one slide in the process of doing this, as shown in the pictures.
Because the slides are so thin, I think they will benefit greatly from being left under a heavy object, although it may be difficult to put the weight on the slides without them breaking. 
Attachment 1: thor_lab_slides_first_bond_PXL_20220929_045352675.MP.jpg


Attachment 2: thor_lab_slides_after_attempting_to_expand_bond_area_PXL_20220929_045510075.MP.jpg


8

Wed Mar 24 17:36:46 2021 
Paco  General  Design specs  Least common multiple stacks and varL cost 
Update on ETM/ITM coating design;
 Following what seemed like a good, intuitive suggestion from Anchal, I implemented a parameter called Ncopies , which takes a stack of mbilayers and copies it a few times. The idea here was to have stacks where m is the least common multiple of the wavelength fractional relation e.g. m(2/3) = 6 so as to regain some of the coherent scattering in a stack. Unfortunately, this didn't work as planned for m=6, 3, and 2.
 While the target transmissivities are reached with comparably fewer layers using this method, the sensitivity and the surface E field are affected and become suboptimal. The good thing is we can do the old way just by setting Ncopies = 0 in the optimization parameters yaml file.
 An example of such a coating is in Attachment 1.
 I decided to just add the 'varL ' scalar cost to the optimizer. Now we minimize for the variance in the coating stack thicknesses. As a target I started with 40% but will play with this now.

Attachment 1: ETM_Layers_210323_0925.pdf


44

Tue Oct 26 08:09:08 2021 
Jiri Smetana  General  General  Lagrangian Suspension Model  Extended Body 
I've been testing out the extended body lagrangian models and I'm trying to understand the ground motion and force coupling to the test mass displacement. I've compared the two pointmass model to the extended model and, as expected, I get very similar results for the ground coupling. Attachment 1 shows the comparison and asside from more agressive damping of the pointmass model making a small difference at high frequency, the two models look the same. If I look at the force coupling, I get a significantly different result (see attachment 2). I think this makes sense because in the pointmass model I am driving purely horizontal displacement as there is no moment of inertia. However, for the extended body I drive the horizontal position of the centre of mass, which then results in an induced rotation as the change propagates through the dynamics of the system. To obtain a consistent result with the pointmass model, I would need to apply a force through the CoM as well as a counteracting torque to maintain a purely horizontal displacement of the mass. What I am wondering now is, what's the correct/more convenient way to consider the system? Do I want my lagrangian model to (a) couple in pure forces through the CoM and torques around the CoM and then find the correct actuation matrix for driving each degree of freedom in isolation or (b) incorporate the actuation matrix into the lagrangian model so that the inputs to the plant model are a pure drive of the test mass position or tilt? 
Attachment 1: comparison_xg.png


Attachment 2: comarison_F.png


49

Wed Nov 17 09:27:04 2021 
Jiri Smetana  General  General  Lagrangian Model  Translation & Pitch 
I've been having a look at the transfer functions for the translation and pitch of both masses. I'm attaching the plot of all inputtooutput transfer functions of interest so far. Here I've identified the pitch resonances of the two masses (one each) as well as the two pendulum modes. I need to now investigate if they occur in the correct places. I have confirmed the DC response by directly solving the statics problem on paper. 
Attachment 1: plant_all_tfs.png


50

Wed Dec 15 06:43:43 2021 
Jiri Smetana  General  General  Lagrangian Model  Translation & Pitch 
I've checked the validity of my state space model in a couple of ways so that we have confidence in the results that it gives. I've checked the DC gain of the transfer functions where it is nonzero. I did this by solving the static balance of forces problem in the extended body model by hand to get the DC CoM position as well as the pitch angle of both masses. In the previous ELOG entry I didn't quite do this for all transfer functions so here I completed the check. My values agree with the model's values to within 10% at the worst end and to within 0.1% at the best end. I performed a second check to see if the frequencies occur in the correct places by considering the case of very low coupling between the different resonant modes. It's difficult to check this in the case where the modes are strongly coupled (for example lengthpitch is strong or the two pitch modes are close together) but if I sufficiently separate them, I get very good agreement between my analytic approximation and the state space model.
The model can easily be converted from one that gives motion in X and RY into one that gives motion in Y and RX. Running the model for both directions gives the following list of resonances (note pendulum modes in X and Y direction are identical):
Resonance Type 
Frequency [Hz] 
Pendulum 1 
0.85 
Pendulum 2 
2.10 
Pitch 1 
0.46 
Pitch 2 
2.37 
Roll 1 
17.13 
Roll 2 
46.09 
Given that I think the model seems to give sensible values, I've pushed the updated model to the GitLab repository. It is now possible to quickly change the parameters of the suspension and very quickly see the corresponding shift in the resonances. To change the parameters, open the plain text file called 'params' and change the values to the new ones. Afterwards, run the file 'ss_extended.py', which will solve the state space model, save the resulting ABCD matrices to a folder and print out the values of the resonances to terminal.
Quote: 
I've been having a look at the transfer functions for the translation and pitch of both masses. I'm attaching the plot of all inputtooutput transfer functions of interest so far. Here I've identified the pitch resonances of the two masses (one each) as well as the two pendulum modes. I need to now investigate if they occur in the correct places. I have confirmed the DC response by directly solving the statics problem on paper.


67

Mon Jul 18 18:34:29 2022 
Paco  General  Design specs  HR coating update 
I've been running the HR coating optimization for mariner TMs. Relative to the specifications found here we now are aiming for
 ITM HR coating of 2000 ppm @ 2050.15 nm, and 1000 ppm @ 1550 nm
 ETM HR coating of 25 ppm @ 2050.15 nm, and 1000 ppm @ 1550 nm.
Both the PSL and AUX cavity finesses range the few couple of thousands, and the goal is not to optimize the coating stack for noise, but more importantly for the transmission values and tolerances. This way we ensure the average finesse and differential finesse requirements are met. Anyways, Attachment #12 shows the transmission plots for the optimized coating stacks (so far). Attachments #34 show the dielectric stacks. The code still lives in this repository.
I'm on the process of assessing the tolerance of this design stacks against perturbations in the layer thicknesses; to be posted in a followup elog. 
Attachment 1: ETM_R.pdf


Attachment 2: ITM_R.pdf


Attachment 3: ETM_Layers.pdf


Attachment 4: ITM_Layers.pdf


68

Fri Jul 22 13:36:55 2022 
Paco  General  Design specs  HR coating update 
Here are some corner plots to analyze the sensitivity of the designs in the previous elog to a 1% gaussian distributed perturbation using MCMC.
Attachment #1 shows the ETM corner plot
Attachment #2 shows the ITM corner plot.
I let the indices of both high and low index materials vary, as well as the physical thicknesses and project their covariances to the transmission for PSL and AUX wavelengths.
The result shows that for our designs it is better to undershoot in the optimization stage rather than meet the exact number. Nevertheless, 1% level perturbations in the optical thickness of the stack result in 30% deviations in our target transmission specifications. It would be nice to have a better constraint on how much each parameter is actually varying by, e.g. I don't believe we can't fix the index of refraction to better than 1%., but exactly what its value is I don't know, and what are the layer deposition tolerances? These numbers will make our perturbation analysis more precise. 
Attachment 1: ETM_corner.pdf


Attachment 2: ITM_corner.pdf


76

Tue Aug 16 09:58:23 2022 
Paco  General  Design specs  HR coating update 
A couple of coating stacks with better tolerance (transmission + 10%). Attachments #12 show the spectral reflectivities for ETM/ITM respectively, while Attachments #34 show the corner plots. I think the tolerances are inflated by the fact that all the stack indices and thicknesses are varying, while in reality these two effects are degenerate because what matters is the optical thickness. I will try to reflect this in the MCMC code next. Finally, attachments # 56 are the hdf5 files with the optimization results. 
Attachment 1: ETM_R_220816_094640..pdf


Attachment 2: ITM_R_220816_095441..pdf


Attachment 3: ETM_corner.pdf


Attachment 4: ITM_corner.pdf


Attachment 5: ETM_Layers_220816_094640.hdf5

Attachment 6: ITM_Layers_220816_095441.hdf5

15

Fri Jun 4 11:09:27 2021 
Paco  General  Design specs  HR coating tolerance analysis 
The HR coating specifications are:
ETM Transmission specs
2128.2 nm 
5.0 ppm 2 ppm 
1418.8 nm 
50.0 ppm 2 ppm 
ITM Transmission specs
2128.2 nm 
2000.0 ppm 200 ppm 
1418.8 nm 
50.0 ppm 2 ppm 
Analysis
 Main constraint: Relative arm finesses @ 2128.2 nm should not differ by > 1%.
 Secondary constraint: Relative arm finesses @ 1418.8 nm may differ, but the ETM and ITM pair should ensure critically coupled cavity to benefit ALS calibration PD shot noise.
Just took the finesse of a single arm:
and propagated transmissivities as uncorrelated variables to estimate the maximum relative finesse. Different tolerance combinations give the same finesse tolerance, so multiple solutions are possible. I simply chose to distribute the relative tolerance in T for the test masses homogeneously to simultaneously maximize the individual tolerances and minimize the joint tolerance.
A code snippet with the numerical analysis may be found here.
Tue Jun 8 11:52:44 2021 Update
The arm cavity finesse at 2128 nm will be mostly limited by the T = 2000 ppm of the ITM, so the finesse changes mostly due to this specification. Assuming that the vendor will be able to do the two ETM optics in one run (x and y), we really don't care so much about the mean value achieved in this run as much as the relative one. Therefore, the 200 ppm tolerance (10% level) is allowed at the absolute level, but a 20 ppm tolerance (1% level) is still preferred at the relative level; is this achievable?. Furthermore, for the AUX wavelength, we mostly care about achieving critical coupling but there is no requirement between the arms. Here a 20 ppm tolerance at the absolute level should be ok, but a 2 ppm tolerance between runs is highly desirable (although it seems crazier); is this achievable? 
28

Sun Sep 19 18:52:58 2021 
Paco  General  Design specs  HR coating emissivity 
[Paco, Nina]
We have been working on an estimate of the wavelength dependent emissivity for the mariner test mass HR coatings. Here is a brief summary.
We first tried extending the thin film optimization code to include extinction coefficient (so using the complex index of refraction rather than the real part only). We used cubic interpolations of the silica and tantala thin film dispersions found here for wavelengths in the 1 to 100 um range. This allowed us to recompute the field amplitude reflectivity and transmissivity over a broader range. Then, we used the imaginary part of the index of refraction and the thin film thicknesses to estimate the absorbed fraction of power from the interface. The power loss for a given layer is exponential in the product of the thickness and the extinction coefficient (see eq 2.6.16 here) . Then, the total absorption is the product of all the individual layer losses times the transmitted field at the interface. This is true when energy conservation distributes power among absorption (=emission), reflection, and transmission:
The resulting emissivity estimate using this reasoning is plotted as an example in Attachment #1 for the ETM design from April. Two things to note from this; (1) the emissivity is vanishignly small around 1419 and 2128 nm, as most of the power is reflected which kind of makes sense, and (2) the emissivity doesn't quite follow the major absorption features in the thin film interpolated data at lower wavelengths (see Attachment #2), which is dominated by Tantala... which is not naively expected?
Maybe not the best proxy for emissivity? Code used to generate this estimates is hosted here. 
Attachment 1: ETM_210409_120913_emissivity.pdf


Attachment 2: interpolated_TF_k.pdf


33

Fri Oct 1 11:52:06 2021 
Paco  General  Design specs  HR coating emissivity 
[Paco, Nina, Aidan]
Updated the stack emissivity code to use the Kitamura paper fused silica dispersion which has a prominent 20 um absorption peak which wasn't there before... (data was up to 15 um, and extrapolated smoothly beyond). The updated HR stack emissivities are in Attachments #1  #2. A weird feature I don't quite understand is the discontinous jump at ~ 59 um ... 
Attachment 1: ETM_210409_120913_emissivity.pdf


Attachment 2: interpolated_n_k.pdf


56

Mon Jun 27 08:22:22 2022 
Juan  General  General  General Update/ Need to do task 
I've managed to cut and crimp wires for the power board for coil driver. I will begin adding components to the coil driver board.
 Add Components to Coil Driver board
 Replace some Sat Amp Componetns
 Still working on moving optical table to CAML
 Unsure if cryochamber has been cleaned and moved 
Attachment 1: coildrive.jpg


63

Mon Jul 11 17:27:39 2022 
Jennifer Hritz  General  Optical Contacting  First successful bond 
Note that the slides have "GLOBE" printed on one side. I always bond the opposite using the opposite side without the text.
On Monday (7/11), I began experimenting with bonding, starting with "airbonding," which is trying to make dry, gently cleaned slides stick. I achieved my first succesful optical contact with what I call "acidental waterassisted direct bonding" or "waterbonding," where I accidentally clasped two wet slides together while washing my dirty finger prints off them. After the accidental discovery, I repeated it by running water over the slides while there were clasped together and achieved the same result. After a few hours, I attempted partially sliding apart the second waterbonded sample. I could slowly push them apart by pressing my thumbs against the long edge, but it took quite a bit of force. I decided to let 4 samples sit overnight: 1 airbonded, 1 airbonded with the brass hunk on top of it, and 2 waterbonded. Neither time nor pressure improved the airbonded samples as they still slid apart very easily. The first waterbonded sample slid apart easier, but one part remained stubornly attached until I began shaking it violently. The second waterbonded sample was much harder to slide apart than the last time I tested it. With all the force of my fingers, I could barely make it budge. 
Attachment 1: PXL_20220712_223449788.MP.jpg


65

Wed Jul 13 13:16:33 2022 
Juan  General  General  Finished coil driver and sat amp 
I have finished all coil driver and sat amp chassis they all seem to be functioning properly.

Attachment 1: IMG5553.jpg


5

Fri Mar 5 11:05:13 2021 
Stephen  General  Design specs  Feasibility of 6" optic size in CAD 
6" vs 4" optic size comparison using CAD  worth hopping into the 3D geometry using the link below, but also posting a couple of images below.
1) We can adjust all parameters relating to the suspension frame except the beam height. Is there enough clearance under the optic for the internal shield?
> Using the representation of the MOS structure asis, there is about 1" of clearance between the bottom panel of the first/internal shield under the 6" case, compared with 2" of clearance in the 4" case. This is not very scary, and suggests that we could use a 6" optic size.
2) Any other concerns at this point?
> Not really, there are degrees of freedom to absorb other issues that arise from the simple 4" > 6" parameter shift
EASM posted at https://caltech.app.box.com/folder/132918404089

Attachment 1: 4in_from_20210305_easm.png


Attachment 2: 6in_from_20210305_easm.png


47

Fri Nov 5 11:51:50 2021 
Paco  General  Design specs  Estimate of inair absorption near 2.05 um 
[Paco]
I used the HITRAN database to download the set of rovibrational absorption lines of CO2 (carbon dioxide) near 2.05 um. The lines are plotted for reference vs wavenumber in inverse cm in Attachment #1.
Then, in Attachment #2, I estimate the broadened spectrum around 2.05 um and compare it against one produced by an online tool using the 2004 HITRAN catalog.
For the broadened spectrum, I assumed 1 atm pressure, 296 K temperature (standard conditions) and a nominal CO2 density of 1.96 kg/m^3 under this conditions. Then, the line profile was Lorentzian with a HWHM width determined by self and air broadening coefficients also from HITRAN. The difference between 2050 nm and 2040 nm absorption is approximately 2 orders of magnitude; so 2040 nm would be better suited to avoid inair absorption. Nevertheless, the estimate implies an absorption coefficient at 2050 nm of ~ 20 ppm / m, with a nearby absorption line peaking at ~ 100 ppm / m.
For the PMC, (length = 50 cm), the roundtrip loss contribution by inair absorption at 2050 nm would amount to ~ 40 ppm. BUT, this is nevery going to happen unless we pump out everything and pump in 1 atm of pure CO2. So ignore this part.
Tue Nov 9 08:23:56 2021 UPDATE
Taking a partial pressure of 0.05 % (~ 500 ppm concentration in air), the broadening and total absorption decrease linearly with respect to the estimate above. Attachment #3 shows the new estimate.
For the PMC, (length = 50 cm), the roundtrip loss contribution by inair absorption at 2050 nm would amount to ~ 1 ppm. 
Attachment 1: HITRAN_line_strenghts.pdf


Attachment 2: broadened_spectrum.pdf


Attachment 3: PP_broadened_spectrum.pdf


48

Tue Nov 16 11:47:54 2021 
Paco  General  Design specs  Estimate of inair absorption near 2.05 um 
[Paco]
There was an error in the last plot of the previous log. This was correctly pointed out by rana's pointing out that the broadening from air should be independent of the CO2 concentration, so nominally both curves should coincide with each other. Nevertheless, this doesn't affect the earlier conclusions >
The PMC loss by background, pressure broadened absorption lines at 2049.9 nm by CO2 is < 1 ppm.
The results posted here are reflected in the latest notebook commit here. 
Attachment 1: PP_broadened_spectrum.pdf


10

Fri Apr 2 19:59:53 2021 
Paco  General  Design specs  Differential evolution strategies 
Differential evolution strategies 'benchmarking' for thin film optimization
Since I have been running the ETM/ITM coatings optimization many times, I decided to "benchmark" (really just visualize) the optimizer trajectories under different strategies offered by the scipy.optimize implementation of differential evolution. This was done by adding a callback function to keep track the convergence=val at every iteration. From the scipy.optimize.differential_evolution docs, this "val represents the fractional value of the population convergence".
Attachment 1 shows a modest collection of ~16 convergence trajectories for ETM and ITM as a function of the iteration number (limited by maxiter=2000 ) with the same targets, weights, number of walkers (=25), and other optimization parameters. The vertical axis plots the inverse val (so tending to small numbers represent convergence).
tl;dr: Put simply, the strategies using "binary" crossover schemes work better (i.e. faster) than "exponential" ones. Will keep choosing "best1bin" for this problem. 
Attachment 1: diffevostrategies.pdf


40

Tue Oct 12 12:49:42 2021 
Jiri Smetana  General  General  Damping Loop (PointMass Pendulums) 
Now that I have correct phase and amplitude behaviour for my MIMO state space model of the suspension and the system is being correctly evaluated as stable, I'm uploading the useful plots from my analysis. File names should be fairly selfexplanatory. The noise plots are for a total height of 550 mm, or wire lengths of 100 mm per stage. I've also attached a model showing the ground motion for different lengths of the suspension. 
Attachment 1: servo.png


Attachment 2: open_loop.png


Attachment 3: closed_loop.png


Attachment 4: noise.png


Attachment 5: length_change.png


41

Thu Oct 14 04:17:36 2021 
Jiri Smetana  General  General  Damping Loop (PointMass Pendulums) 
Here are the DAC and residual displacement spectra for different suspension heights ranging from 450 mm to 600 mm. I aimed to get the Q of the lower resonance close to 5 and the DAC output RMS close to 0.5 V but as this was just tweaking values by hand I didn't get to exactly these values so I'm adding the actual values for reference. The parameters are as follows:
Height [mm] 
Displacement RMS [nm] 
DAC Output RMS [V] 
Q Lower Resonance 
Q Higher Resonance 
Driver Resistor {Ohm] 
600 
560 
0.51 
5.3 
1.5 
175 
550 
580 
0.54 
5.1 
1.4 
175 
500 
610 
0.49 
5.0 
1.4 
150 
450 
630 
0.54 
5.0 
1.4 
150 
Quote: 
Now that I have correct phase and amplitude behaviour for my MIMO state space model of the suspension and the system is being correctly evaluated as stable, I'm uploading the useful plots from my analysis. File names should be fairly selfexplanatory. The noise plots are for a total height of 550 mm, or wire lengths of 100 mm per stage. I've also attached a model showing the ground motion for different lengths of the suspension.


Attachment 1: disp_600.png


Attachment 2: DAC_600.png


Attachment 3: disp_550.png


Attachment 4: DAC_550.png


Attachment 5: disp_500.png


Attachment 6: DAC_500.png


Attachment 7: disp_450.png


Attachment 8: DAC_450.png


19

Tue Jul 27 11:38:25 2021 
Paco  General  Design specs  DOPO single pass PDC efficiency 
Here is a set of curves describing the singlepass downconversion efficiency in the 20 mm long PPKTP crystals for the DOPO. I used the "nondepleted pump approximation" and assumed a planewave (although the intensity matches the peak intensity from a gaussian beam). Note that these assumptions will in general tend to overestimate the conversion efficiency.
The parameters use an effective nonlinear coefficient "d_eff" of 4.5 pm/V, and assume we have reached the perfect (quasi) phase matching condition where delta_k = 0 (e.g. we are at the correct crystal operating temperature). The wavelengths are 1064.1 nm for the pump, and 2128.2 nm for degenerate signal and idler. The conversion efficiency here is for the signal photon (which is indistinguishable from the idler, so am I off by a factor of 2?)...
Attachment 1 shows the single pass conversion efficiency "eta" as a function of the pump power. This is done for a set of 5 minimum waists, but the current DOPO waist is ~ 35 um, right in the middle of the explored range. What we see from this overestimates is an almost linearinpump power increase of order a few %. I have included vertical lines denoting the damage threshold points, assuming 500 kW / cm ^2 for 1064.1 nm (similar to our freespace EOMs). As the waist increases, the conversion efficiency tends to increase more slowly with power, but enables a higher damage threshold, as expected.
At any rate, the singlepass downconversion efficiency is (over)estimated to be < 5 % for our current DOPO waist right before the damage threshold of ~ 10 Watts, so I don't think we will be able to use the amplified pump (~ 2040 W) unless we modify the cavity design to allow for larger waist modes.
The important figure (after today's group meeting) would be a single pass downconversion efficiency of ~ 0.5 % / Watt of pump power at our current waist of 35 um (i.e. the slope of the curves below) 
Attachment 1: singlepass_eff_overest.pdf


21

Tue Aug 17 17:48:57 2021 
Koji  General  Equipment  Crackle SW model 
As a kickoff of the mariner sus cryostat design, I made a tentative crackle chamber model in SW.
Stephen pointed out that the mass for each part is ~100kg and will likely be ~150kg with the flanges. We believe this is with in the capacity of the yellow Skyhook crane as long as we can find its wheeled base. 
Attachment 1: Screen_Shot_20210817_at_17.44.32.png


64

Mon Jul 11 17:39:17 2022 
Juan  General  General  Coil driver chassis 
Finished all 3 Coil Drover chassis and power lines still need to install the rear cables will do that after I finish Sat Amp chassis tomorrow. 
Attachment 1: IMG5493.jpg


Attachment 2: IMG5494.jpg


61

Fri Jul 8 17:09:10 2022 
Juan  General  General  Coil Driver and Sat Amp 
All three coil driver boards are complete and have been tested. Modification for all 4 sat amp have been completed. Ideally, I would like to finish all the chassis on Monday I have one just about done.

Attachment 1: IMG5434.jpg


Attachment 2: IMG5421.jpg


Attachment 3: IMG5420.jpg


71

Wed Jul 27 14:50:20 2022 
Jennifer Hritz  General  Optical Contacting  Bonding without liquids and narrowing down heating issue 
I have found that, after cleaning the glass with methanol (or even sometimes with just a dry lensecleaning cloth), I can get glass slides to bond by rappidly rubbing them together until something sticks. This was inspired by watching "Wizard of Vaz" perform bonds on YoutTube. While cleaning, I now use enough strength to make the glass squeak, as advised by him.
Upon heating, I encountered the same issue as when I bonded them by putting a liquid (water, methanol, etc.) in the gap, which leads me to now believe that the broken bond is not due to the expansion of a liquid. Further, even at the low temperature of 60°C, placing the liquidless sample on the hotplate breaks the bond in seconds, which I caught on video. In the attached video*, you can see that, before the heat, the bond is strong enough that I cannot push it appart with my fingers, but after the heat, it slides easily. Note that, outside of taking the video, I always lay the entire slide on the center of the metal so the sample is evenly heated.
*This is my first time attaching a video. If it didn't attach properly, I'll add it on to a later log. I also want to record myself performing the rubbing bonding technique. 
Attachment 1: PXL_20220727_214658230.jpg


Attachment 2: PXL_20220727_214241668.mp4

62

Mon Jul 11 16:24:31 2022 
Jennifer Hritz  General  Optical Contacting  Baselining the temperature output of the Oster hot plate 
This was performed last Friday (7/8).
I secured a thermocouple perpendicular against the hotplate and recorded the maximum temperature the hotplate reached at Low, Medium, and High. It took about 5 minutes to reach a stable temperature, where stable means that the temperature stayed within +/ 0.5°C for a minute. The hotplate maintains a certain temperature by turning itself on and off, so the temperature would drop slightly (at most, a few °C) while the hotplate was off. The maximums were:
Low: 51°C
Medium: 185°C
High: 263°C
At the max temperature, I moved the perpendicular thermocouple around to roughly find the variation in tempearture at different locations on the hotplate. Facing the nob, the top right quadrant is about 1020°C cooler than the other quadrants, which are within 5°C of eachother. Excluding the cooler quandrant, the center and the outer edge are within 5°C of eachother. The temperature increases as one approaches half the radius, with it being about 2040°C greater than the center and outer edge. The highest recorded temparture was 289°C at half the radius in the bottom left quandrant. This was only meant to be a rough test to see how even the heating is. 
Attachment 1: PXL_20220708_230038748.jpg


Attachment 2: PXL_20220708_230234841.MP.jpg


14

Fri May 7 17:50:31 2021 
Nina Vaidya & Shruti Maliakal  General  Design specs  Arm Cavity Design 2021 update 
Here are the final slides with all the results on the Arm Cavity Design, please review.
For RoC of 56.2 +/ 1% things are working well. Tolerance of 0.5% will be better however, 1% is still working; as long as we do not want any peaks ~50kHz away.
For length, 38+0.5% = 38.19 (with RoC 56.2) not ideal, peak is close (48.8kHz) but maybe ok? @Rana thoughts? and 380.5% = 37.81 (with RoC 56.2) works well.
To summarise the design:
RoC = 56.2 +/ 1%
L = 38 +/ 0.5% 
Attachment 1: Arm_Cavity_Design_05072021_with_tolerances.pptx

Attachment 2: HOMhelper.py

def add_cavmodel(kat, T=0.001, Loss=5e6, theta=60, L_rt = 2*12.240, R_c = 20, f1 = 11e6, gamma1 = 0, f2 = 55e6, gamma2 = 0):
'''
T: Transmission of mirror (ITM)
Loss: Loss of mirror ETM
L_rt: Round trip length of cavity
R_c: Radius of curvature of ETM
'''
... 98 more lines ...

Attachment 3: Arm_HOManalysis.ipynb

{
"cells": [
{
"cell_type": "code",
"execution_count": 376,
"metadata": {},
"outputs": [],
"source": [
"from pykat import finesse\n",
"from pykat.commands import *\n",
... 825 more lines ...

Attachment 4: HOMplot.py

import numpy as np
import scipy.constants as scc
import matplotlib as mpl, matplotlib.pyplot as plt
from matplotlib import cm
plt.rcParams.update({'text.usetex': False,
'lines.linewidth': 2,
'font.family': 'serif',
'font.serif': 'Georgia',
'font.size': 22,
... 132 more lines ...

12

Tue Apr 27 12:28:43 2021 
Nina Vaidya & Shruti Maliakal  General  Design specs  Arm Cavity Design 2021 
Rana’s code: R_c = 57.3
>New code with optimization: sweeping through a range of R_c, using a cost function that puts value on peak height, distance of the peaks from the zero order, and mode number. This cost function can be edited further to adapt to more aims (Slides attached). Currently (code attached) gives > R_c = 58.4 with very slightly different peaks and energy distribution in the modes
1) Range of R_c is 57 to 60, for some reason lower values of R_c in the range are giving error > debug this
2) Find how sensitive the model is for 1% change in R_c value
3) Make sure the side bands are not resonating 
Attachment 1: Arm_Cavity_Design_04232021.pptx

Attachment 2: Arm_HOM_optimization.ipynb

{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Mariner: Higher Order Mode Analysis of Arm Cavities for PhaseI trial\n",
"\n",
"This notebook contains a study of modematching for optical FabryPerot cavities using Finesse\n",
"\n",
... 943 more lines ...

26

Wed Sep 15 09:15:21 2021 
Jiri Smetana  General  General  Actuation Feedback Model and Noise 
I've implemented a more extensive feedback model that uses proper conversions between metres, volts, counts etc. and includes all the (inverse) (de)whitening filters, driver, servo and noise injections in the correct places. I then closed the loop to obtain the transfer function from horizontal ground motion and each noise source to test mass displacement. I tuned the servo gain to reduce the Q of both resonances to ~20.
Our idea was then to compensate servo gain with the output resistance of the coil driver to raise the RMS of the DAC output signal in order to raise SNR and thus suppress DAC noise coupling. I found that raising the output resistor by a factor of 10 above the nominal suggestion 2.4 kOhm gave me a DAC output RMS of 0.3 V, so in line with our safety factor of 10 requirements. This also coincidentally made all the noise sources intersect at approximately the same frequency when these noises begin to dominate over the seismic noise. All these initial tests are subject to change, particularly depending on the design of the servo transfer function. I'm attaching the relevant plots as well as the MATLAB script I used and the two files required for the script to run. 
Attachment 1: displacement_asd.png


Attachment 2: servo.png


Attachment 3: system_loop.m

% Get piezo stack transfer function
PZT_f = fscanf(fopen('ground_freq.txt'), '%f');
PZT_tf = fscanf(fopen('ground_xx.txt'), '%f');
% Set frequency vector and ground motion
freq = logspace(1, 2, 1e4);
grnd = ground(freq);
PZT = interp1(PZT_f, PZT_tf, freq);
% Set complex frequency variable
... 185 more lines ...

Attachment 4: ground_freq.txt

0.1
0.5
1
1.419178617
1.489659958
1.554545445
1.719720097
1.806748355
2.030363506
2.133112203
... 110 more lines ...

Attachment 5: ground_xx.txt

1
1.3
1.8
2.794167453
2.905480556
3.077890921
3.854210495
4.502922159
5.213856692
4.990356828
... 110 more lines ...

27

Thu Sep 16 10:02:47 2021 
Jiri Smetana  General  General  Actuation Feedback Model and Noise 
Here's the DAC voltage spectrum with its associated RMS.
Also, for clarity, this model is for a lossless pointmass double pendulum system with equal masses and equal lengths of 20 cm.
Quote: 
I've implemented a more extensive feedback model that uses proper conversions between metres, volts, counts etc. and includes all the (inverse) (de)whitening filters, driver, servo and noise injections in the correct places. I then closed the loop to obtain the transfer function from horizontal ground motion and each noise source to test mass displacement. I tuned the servo gain to reduce the Q of both resonances to ~20.
Our idea was then to compensate servo gain with the output resistance of the coil driver to raise the RMS of the DAC output signal in order to raise SNR and thus suppress DAC noise coupling. I found that raising the output resistor by a factor of 10 above the nominal suggestion 2.4 kOhm gave me a DAC output RMS of 0.3 V, so in line with our safety factor of 10 requirements. This also coincidentally made all the noise sources intersect at approximately the same frequency when these noises begin to dominate over the seismic noise. All these initial tests are subject to change, particularly depending on the design of the servo transfer function. I'm attaching the relevant plots as well as the MATLAB script I used and the two files required for the script to run.


Attachment 1: DAC_voltage.png


29

Fri Sep 24 11:02:41 2021 
Koji  General  General  Actuation Feedback Model and Noise 
We had a meeting with the code open in ZOOM. Here are some points we discussed:
 The code requires another file ground.m. It is attached here.
 The phase of the bode plots were not wrapped. This can be fixed by applying the "PhaseWrapping" options as
opts=bodeoptions('cstprefs');
opts.PhaseWrapping = 'on';
bode(A,opts)
 We evaluated the openloop transfer function of the system. For this purpose, we added the monitor point ('F') at the actuator and cut the loop there like:
sys = connect(P, S, W, ADC, Winv, A2, DWinv, Dinv, DAC, DW, D, R, C, {'xg' 'nADC', 'nDAC', 'nd', 'nth'}, 'xt', {'F','VDAC'});
OLTF=getLoopTransfer(sys(1),'F');
figure(2)
clf
bode(OLTF,opts);
 We played with the loopgain (Ga2). When Ga2 is a positive number, the loop was stable. We had to shift the low pass cutoff frequency from 10Hz to 12Hz to make the damping of the 2nd peak stable.

Attachment 1: ground.m

function [grnd] = ground(freq)
grnd = 1e7*(freq<1)+1e7*(1(freq<1))./(freq.^2+1e50);
end

22

Tue Aug 24 08:15:37 2021 
Jiri Smetana  General  General  Actuation Feedback Model 
I'm posting a summary of the work I've done on the Lagrangian analysis of the Mariner suspension design and a state space model of the actuator control loop. The whole feedback mechanism can be understood with reference to the block diagram in attachment 1.
The dynamics of the suspension are contained within the Plant block. To obtain these, I derived the system Lagrangian, solved the EulerLagrange equations for each generalised coordinate and solved the set of simultaneous equations to get the transfer functions from each input parameter to each generalised coordinate. From these, I can obtain the transfer functions from each input to each observable output. In this case, I inserted horizontal ground motion at the pivot point (top of suspension) and a generic horizontal force applied to at the intermediate mass. These two drives become the two inputs to the Plant block. The two observables are x_{i}  the position of the intermediate mass, which is sensed and fed to the actuator servo, and x_{t}  the test mass position that we are most interested in. I obtained the transfer functions from each input to each output using a symbolic solver in Python and then constructed a MIMO state space representation of these transfer functions in MATLAB. For this initial investigation, I've modelled the suspension in the Lagrangian as a lossless pointmass double pendulum with two degrees of freedom  the angle to the horizontal of the first mass and the angle to the horizontal of the second mass. The transfer functions are very similar to the more advanced treatment with elastic restoring forces and moments of inertia and the system can always be expanded in a later analysis.
For the sensor block I assumed a very simple model given by
where G_s is the conversion factor from the physical distance in metres to the electronic signal (in, for example, volts or ADC counts) and n_s is the added sensor noise. A more general sensor model can easily be added at a later date to account for, say, a diminishing sensor response over different frequency ranges.
The actuator block converts the measured displacement of the intermediate mass into an actuation force, with some added actuator noise. The servo transfer function can be tuned to whatever filter we find works best but for now I've made two quite basic suggestions: a simple servo that actuates on the velocity of the intermediate mass, given by
and an 'improved' servo, which includes a rolloff after the resonances, given by
where p is the pole frequency at which we want the rolloff to occur. Attachment 2 shows the two servo transfer functions for comparison.
The state space models can then be connected to close the loop and create a single state space model for the transfer functions of the ground and each noise source to the horizontal test mass displacement. Attachment 3 contains the transfer functions from x_{g} to x_{t} and shows the effect of closing the loop with the two servo choices compared to the transfer function through just the Plant alone. We can see that the closed loop system does damp away the resonances as we want for both servo choices. The basic servo, howerver, loses us a factor of 1/f^2 in suppression at high frequencies, as it approximates the effect of viscous damping. The improved servo gives us the damping but also recovers the original suppression at high frequencies due to the rolloff. I can now provide the ground and noise spectra and propagate them through to work out the fluctuations of the test mass position. 
Attachment 1: actuator_feedback_diagram.png


Attachment 2: bode_servo.png


Attachment 3: bode_plant.png


11

Fri Apr 23 10:41:22 2021 
Aidan  General  Design specs  2 um photodiode requirements 
MCT HgCdTe requirements: https://docs.google.com/spreadsheets/d/1lajp17yusbkacHEMSobChKepiqKYesHWIJ6L7fgryY/edit?usp=sharing

17

Wed Jun 30 16:21:53 2021 
Stephen  General  Design specs  
[Stephen, Koji]
WIP  check layout of 60 cm suspension in chamber at 40m, will report here
WIP  also communicate the 