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Make a Spaceship With an Adjustable Slope

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Re: Make a Spaceship With an Adjustable Slope

Posted: October 18th, 2026, 1:13 am
by Goldtiger997
ENDW wrote: October 17th, 2026, 9:47 pm omniship3:
Nice!

If we're interested in making an even smaller omniship, I think the most effective way would be to switch to a different design. Specifically a loopship design similar to the speed orthogonal loopship.

Code: Select all

x = 724, y = 393, rule = LifeHistory
469.A$433.A34.A.A$432.A.A34.2A$432.2A9$490.A$489.A.A$490.2A$477.A$
476.A.A$476.2A$490.2A$458.2A30.A.A$457.A2.A30.2A9.A$458.A.A40.A.A$
459.A42.2A3$490.2A13.2A$457.A32.2A12.A2.A$456.A.A45.A.A$456.A.A46.A$
457.A31.2A$489.2A$477.A$477.A$463.A13.A$368.2A92.A.A$367.B2A2B3.2A84.
A2.A$368.4B2.B2AB84.2A$342.A21.B.6B3.2B164.2D$340.3A19.10B2.2B161.4D.
2D$322.2B15.A22.11B2A2B84.A75.6D$321.4B14.2A20.12B2A3B.B67.A12.A.A75.
4D$321.4B15.B20.18B2A65.A.A11.A2.A$317.B2.6B14.3B19.15B.B2A65.2A13.2A
22.D$316.2AB.2B2A2B13.6B16.15B3.B103.AC.D3.A3.A3.D3.D3.D3.D3.D3.D3.D
3.D3.D3.D$316.2A3BA2BA3B10.10B11.17B107.AD.AD2.A3.A3.D3.D3.D3.D3.D3.D
3.D3.D3.D3.D3.7D$317.2B.2B2A7B3.2B2.11B3.2B2.19B110.2C3.A3.A3.D3.D3.D
3.D3.D3.D3.D3.D3.D3.D3.D5.D$320.22B2A31B72.2A28.2D65.D$321.21B2A22B.
7B73.2A28.2D60.D3.D$321.45B2.6B167.D$321.45B2.7B80.A79.2D$320.45B4.6B
79.A.A32.2A40.4D.2D5.2D$318.B.13B2.B4.13B.4B10.6B81.A32.A.A40.6D3.3D.
2D$317.2AB.12B7.7B.B5.3B12.5B114.2A42.4D4.5D$317.2A14B19.4B13.6B108.
2A56.3D$318.2B.11B20.2A15.6B84.A23.A.A$321.11B21.A15.7B82.A.A5.A18.A
3.2A$321.10B19.3A16.7B81.A.A6.A18.2A2.2A$317.2A2.6B23.A17.8B81.2A7.A$
316.A.A9B40.8B102.2A$266.A49.A3.9B38.8B103.2A$266.3A46.2A3.9B39.2B2A
3B$269.A50.9B39.2B2A5B291.A$254.2A3.2A7.2A18.A31.9B35.13B102.2A185.3A
$253.B2AB.B2AB6.4B14.3A30.11B32.16B101.2A10.2A172.A$254.2B2.3B3.B5.3B
12.A33.11B32.17B112.A.A171.2A$255.3B.3B.4B3.4B11.2A32.12B31.16B114.2A
158.2A8.5B$247.2A5.7B.13B11.B26.B4.14B30.15B276.A8.3B$248.A5.23B9.3B
23.3B3.10B.4B30.13B277.A.AB4.6B$248.A.AB.19B.8B4.6B16.2B.6B2.16B30.
11B121.2A156.2AB.9B$249.2AB.29B2.10B10.5B.7B.17B27.13B121.A.A157.6B2A
5B$251.44B3.2B2.29B.4B25.14B122.2A157.5BA2BA5B$251.37B2A15BD25B2.4B
24.16B.B.B.B.B.B.B.B.B.B.B.B.B.B.B.B.B.B.B.B.B.B.B.B.B201.B.B.B.B.B.B
.B.B.B.B.B.B.B.B.B.6B2A7B$251.37B2A15BDBD23B3.4B23.65B198.48B$252.53B
3DB2A21B3.4B22.65B198.43B2.4B$254.53BDB2A21B4.4B22.64B44.2D151.42B5.
4B$252.81B4.4B19.66B30.2A11.4D152.42B4.4B$252.2A3.25B4.13B7.26B6.4B
17.2A65B30.A12.2D.2D149.B.38B2.2A5.4B$253.A3.20B4.B4.7B.B13.B2.20B8.
4B16.ABA16B.B.B.B.B.B.B.B.B.B.B.B.B.B.B.B.B.B.B.B.B.B.B.B.B31.3A11.2D
152.B.B.B.B.B.B.B.B.B.B.B.B.B.B.B.B.6B2.A7.4B7.A$250.3A6.15B7.2A27.
20B.B.B6.4B15.BA9B2A4B83.A2.3A6.2A183.5B5.3A5.4B6.3A$250.A8.11B12.A
26.24B2A6.4B14.6B.3BA2BA2B95.A2.A182.7B5.A6.4B8.A$258.13B8.3A27.24B2A
7.4B14.3B3.4B2A2B97.A.A6.A176.3B.2A.A11.4B6.A.A$257.15B7.A27.2AB2.5B
2.12B.2B9.4B20.6B99.A6.A.A170.2A2.B2A2.2AB3A10.4B5.A.AB$257.16B33.A.A
B2.4B3.13B12.4B105.2A25.A171.A2.A2.A3.B4.A10.4B5.A3B$257.17B32.A14.
11B.B11.4B103.A2.A197.5A3.2A.3A12.4B6.4B$257.16B32.2A14.12B2A11.4B10.
A6.6B80.A.A206.A.A15.4B5.6B$259.13B49.10B.B2A12.4B7.3A5.9B79.A200.A6.
A.A16.4B4.7B$259.3B.2B2A5B47.2AB.6B4.B14.4B5.A7.4B4.2A82.2A195.A.A6.A
18.4B2.8B.4B.B$257.4B2.2B2A3B48.A.AB.4B22.4B4.2A5.4B5.A83.A196.2A27.
17B.B2A$257.2A3.8B48.A5.5B21.9B4.4B7.3A78.A.A226.18B2A$258.A4.8B46.2A
8.2A22.6B5.4B10.A78.2A227.16B.2B$255.3A5.8B56.A23.8B2.4B319.16B$255.A
8.7B57.3A18.15B320.15B$264.7B59.A18.14B319.2AB.12B$256.A7.6B79.13B
319.A.AB2.11B$255.A.A6.6B77.2AB.10B320.A5.10B$255.A.A6.5B77.A.AB3.B2A
3B321.2A5.2B2A6B$253.3A.2A4.6B77.A6.B2A3B327.3B2A6B$252.A4.B6.6B75.2A
6.4B330.10B26.B$253.3AB2AB3.7B84.3B330.8B.B2A.A21.2B$255.A.2AB.8B86.
2B.BA326.7B3.B2AB3A18.3B$259.10B85.B2ABA.A325.6B6.B4.A16.4B$259.6B2A
3B83.BABABA.A326.6B4.2A.3A16.4B$259.6B2A2B5.2A75.A2.A.A.A.A.2A323.5B
6.A.A17.4B$259.10B5.A76.4A.2A2.A2.A322.6B6.A.A16.4B$258.11B2.BA.A80.A
4.2A324.6B7.A16.4B$258.12B.B2A79.A.A329.7B23.4B$257.15B81.2A330.7B8.A
13.4B$256.16B413.8B5.3A12.4B$253.2B.16B413.8B4.A14.4B$252.2A18B414.8B
3.2A12.4B$252.2AB.17B413.3B2A2B2.4B11.4B$253.B.4B.8B2.4B410.5B2A2B.3B
12.4B$260.7B4.4B409.13B11.4B$261.6B5.4B407.16B8.4B$263.4B6.4B405.17B
7.4B$265.3BA5.4B405.16B6.4B$266.BA.A5.4B405.15B5.4B$267.A.A6.4B398.2A
5.13B5.4B$268.A8.4B398.A6.10B6.4B$269.3A6.4B102.B294.A.AB3.10B5.4B$
271.A7.4B100.2B295.2AB.15B.4B$280.4B98.3B297.21B$281.4B96.4B298.19B$
282.4B94.4B291.2A5.20B$283.4B92.4B293.A4.22B$284.4B90.4B294.A.AB.23B$
285.4B88.4B296.2AB.22B$286.4B86.4B299.23B$287.4B84.4B300.22B$288.4B
82.4B302.18B$289.4B80.4B303.14B.5B$290.4B78.4B305.12B5.2A$291.4B76.4B
308.10B5.A$292.4B74.4B309.9B7.3A$293.4B72.4B310.8B10.A$294.4B70.4B
312.8B$295.4B68.4B318.4B$296.4B66.4B320.4B$297.4B64.4B322.4B$298.4B
62.4B324.4B$299.4B60.4B326.4B$300.4B58.4B328.4B$301.4B56.4B330.4B$
302.4B54.4B332.4B$303.4B52.4B334.4B$127.2A175.4B50.4B336.4B$126.A.A
176.4B48.4B338.4B$120.2A4.A179.4B46.4B340.4B$118.A2.A2.2A.4A176.4B44.
4B342.4B$118.2A.A.A.A.A2.A177.4B42.4B344.4B$121.A.ABABAB180.4B40.4B
346.4B$121.A.AB2AB182.4B38.4B348.4B$122.AB.2B184.4B36.4B350.4B$125.3B
184.4B34.4B352.4B$125.4B6.2A176.4B32.4B354.4B$123.3B2AB6.A178.4B30.4B
356.4B$123.3B2AB3.BA.A179.4B28.4B358.4B$121.10B.B2A181.4B26.4B360.4B$
120.13B184.4B24.4B362.4B$119.14B185.4B22.4B364.4B$118.15B186.4B20.4B
366.4B$117.4B2.8B189.4B18.4B368.4B$116.4B5.6B190.4B16.4B370.4B$115.4B
4.9B190.4B14.4B372.4B$115.3B5.2A4.4B190.4B12.4B$115.2B7.A5.4B190.4B
10.4B$115.B5.3A7.4B190.4B8.4B$121.A10.4B190.4B6.4B2D$133.4B190.4B4.4B
.D$328.4B2.4B4.D$322.2D5.8B.5D$323.D5.7B.D$323.D.DB.7B2.B3D$324.2DB.
7B3.2B.D$326.12B4D$326.7B2D3BDB2.2D$326.7B2D2B.B3D2.D$326.10B3.B.D.2D
$325.8B8.D$324.9B7.2D$323.4B2.3B$322.4B3.5B$321.4B7.2D$320.4B8.D$319.
4B10.3D$318.4B13.D$317.4B$316.4B$315.4B$314.4B$313.4B$312.4B$311.4B$
310.4B$309.4B$308.4B$307.4B$306.4B$305.4B$304.4B$303.4B$302.4B$301.4B
$300.4B$299.4B$298.4B$297.4B$296.4B$295.4B$294.4B$293.4B$292.4B$291.
4B$290.4B$289.4B$288.4B$287.4B$286.4B$285.4B$284.4B$283.4B$282.4B$
281.4B$280.4B$279.4B$278.4B$277.4B$276.4B$275.4B$274.4B$273.4B$272.4B
$271.4B$201.B68.4B$201.2B66.4B$201.3B64.4B$201.4B62.4B$202.4B60.4B$
203.4B58.4B$204.4B56.4B$205.4B54.4B$206.4B52.4B$207.4B50.4B$208.4B48.
4B$209.4B46.4B$210.4B44.4B$211.4B42.4B$212.4B40.4B$213.4B38.4B$214.4B
36.4B$215.4B34.4B$216.4B32.4B$217.4B30.4B$218.4B28.4B$219.4B21.B4.4B
16.A11.2A$9.A13.B196.4B19.3B2.4B16.A.A9.B2AB$9.3A10.2B197.4B10.2A5.9B
17.A.A9.3B$12.A8.3B198.4B10.A4.9B12.2A2.3A.2A9.B.B$11.2A7.4B199.4B9.A
.AB.8B13.A2.A4.B8.5B$11.5B3.4B201.4B9.2AB.9B3.4B2.BA.A3.3AB2A6.6B$13.
3B2.4B203.4B10.11B2.5B2.B2A6.A.2A4.8B$3.2A7.9B205.4B9.11B2.8B10.13B$
3.A8.8B207.4B8.21B12.13B$2A.A.B3.10B209.4B8.19B12.15B$A2.3AB.2B2A7B
210.4B6.19B2.B10.15B$.2A2.BA3B2A7B211.4B3.26B5.B.17B$3.4A12B212.4B.
51B$3.A.2B3.7B.B2A211.4B.21B2A13B2A13B$4.3AB2.7B.BA.A211.25B2A13B2A
14B$7.A4.4B5.A212.50B3.B2A$2.5A5.4B5.2A212.48B4.A2.A$2.A10.4B217.33B
2.2B2.B3.6B5.2A.A$4.A9.4B216.16B2.7B2.4B13.6B7.A$3.2A10.4B215.16B3.6B
17.9B6.2A$16.4B215.14B5.3B19.2A4.4B$17.4B217.9B.3B4.B21.A5.4B$18.4B
216.8B3.2A23.3A7.4B$239.4B6.A24.A10.4B$241.4B5.3A33.4B$243.2A7.A34.4B
$243.A44.4B$244.3A42.4B$246.A43.4B$291.4B$292.4B$293.4B$294.4B$295.4B
$296.4B$290.2A5.4B6.2A$287.A3.A5.4B6.A$286.A.A2.A.AB.7B.BA.A$286.A.A
3.2AB.7B.B2A$284.3A.2A4.5BA5B$283.A4.B5.4BABA4B$284.3AB2AB.6BABA4B$
286.A.2AB.7BA3B$290.12B$289.13B$287.2A13B$286.A.A12B$283.A2.A.B.2B.
10B$282.A.A.2A4.6B3.2A$282.2A2.A6.6B2.A$286.A.A3.6B4.3A$287.2A4.6B5.A
$292.6B$293.6B$292.6B$293.6B$292.6B$293.6B$292.6B$293.6B$292.6B15$
294.3A$293.A2.A$296.A$292.A3.A$296.A$293.A.A35$111.4B$112.4B10.A$113.
4B7.3A5.B$114.4B5.A7.2B$115.4B4.2A5.3B$116.9B4.4B$117.6B5.4B$117.8B2.
4B$115.15B$115.14B$115.13B$113.2AB.10B$112.A.AB3.B2A3B$112.A6.B2A3B$
111.2A6.4B$120.3B$121.2B.BA$120.B2ABA.A$119.BABABA.A$117.A2.A.A.A.A.
2A$117.4A.2A2.A2.A$121.A4.2A$119.A.A$119.2A!
The circuitry required for each half-period in this design is smaller than in ENDW's omniship, so I expect the tape will be substantially shorter as a result. Specifically, rather than having to build two G-to-MWSSs and two blinker puffer seeds, this loopship design just requires building one of each.

However, the disadvantage of this loopship design is the awkward requirement for the trigger signals to cross the single-channel stream. This is the same problem that afflicted the speed orthogonal loopship. The trigger signal needs to cross because the design is in a sense glide-reflective. Due to this, it might be that the design is not adjustable to all non-orthogonal velocities like ENDW's omniship is. Maybe it is, but sorting out the details of how to guarantee that neither of the trigger signals collide with signals in the tape is not something immediately obvious to me.

Another possibility is a loopship design which alternates between travelling orthogonally and diagonally. I'm envisioning something like this:

Code: Select all

x = 599, y = 652, rule = LifeHistory
441.4B40.4B$442.4B38.4B$443.4B36.4B$444.4B34.4B$445.4B32.4B$446.4B30.
4B$447.4B28.4B$448.4B21.B4.4B16.A11.2A$449.4B19.3B2.4B16.A.A9.B2AB$
450.4B10.2A5.9B17.A.A9.3B$451.4B10.A4.9B12.2A2.3A.2A9.B.B$452.4B9.A.A
B.8B13.A2.A4.B8.5B$453.4B9.2AB.9B3.4B2.BA.A3.3AB2A6.6B$454.4B10.11B2.
5B2.B2A6.A.2A4.8B$455.4B9.11B2.8B10.13B$456.4B8.21B12.13B$457.4B8.19B
12.15B$458.4B6.19B2.B10.15B$459.4B3.26B5.B.17B$460.4B.51B$461.4B.21B
2A13B2A13B$462.25B2A13B2A14B$463.50B3.B2A$464.48B4.A2.A$463.33B2.2B2.
B3.6B5.2A.A$463.16B2.7B2.4B13.6B7.A$463.16B3.6B17.9B6.2A$464.14B5.3B
19.2A4.4B$467.9B.3B4.B21.A5.4B$467.8B3.2A23.3A7.4B$468.4B6.A24.A10.4B
$470.4B5.3A33.4B$472.2A7.A34.4B$472.A44.4B$473.3A42.4B$475.A43.4B$
520.4B$521.4B$522.4B$523.4B$524.4B$525.4B$519.2A5.4B6.2A$516.A3.A5.4B
6.A$515.A.A2.A.AB.7B.BA.A$515.A.A3.2AB.7B.B2A$513.3A.2A4.5BA5B$512.A
4.B5.4BABA4B$513.3AB2AB.6BABA4B$515.A.2AB.7BA3B$519.12B$518.13B$516.
2A13B$515.A.A12B$512.A2.A.B.2B.10B$511.A.A.2A4.6B3.2A$511.2A2.A6.6B2.
A$515.A.A3.6B4.3A$516.2A4.6B5.A$521.6B$522.6B$521.6B$522.6B$521.6B$
522.6B$521.6B$522.6B59$547.D$546.3D3.3D$545.2D.D2.D2.D5.D$545.3D6.D4.
3D$545.3D2.D3.D3.2D.D$546.2D6.D3.3D$551.D2.D3.3D$553.2D3.3D$548.D10.
2D$547.3D$546.2D.D$546.3D4.3D$546.3D$546.3D$547.2D$553.3D4$553.3D4$
553.3D4$553.3D4$553.3D4$553.3D3$572.A$553.3D15.A.A$570.A2.A$571.2A$
576.2A$553.3D20.A.A$577.A3$528.2A23.3D$528.A.A$529.2A2$553.3A$533.2A$
533.A.A42.2A$534.2A36.2A4.A.A3.2A$542.2A3.2A4.3A12.2A2.2A5.2A3.A.A$
542.2A2.A.A19.2A15.A$546.2A$554.D$542.A10.CAD$542.3A8.C2.D$545.A8.DC$
544.2A8.2A2$517.A$516.A.A16.2A$517.A17.2A2.2A$539.2A10.2D29.A$551.2D
12.3A13.A.A$581.2A3$518.2A2.D$517.A2.A3D$518.A.AD.2D$519.A2.3D71.2A$
522.2D72.A.A$597.A2$541.3A2$520.A42.2A$520.A36.A4.A2.A$520.A35.A.A3.A
.A$556.A2.A3.A$543.A13.2A18.2A$520.2A20.A.A31.A2.A$512.A8.A19.A.A26.
2A5.A.A$510.3A8.A.A17.2A26.A2.A5.A$509.A12.2A24.A21.2A$509.2A3.2A31.A
.A$513.A2.A31.A$514.A.A$515.A4$551.2A4.A$551.2A3.A.A$556.2A12$596.A$
595.A.A$595.2A7$521.6B$522.6B$521.6B$522.6B$521.6B$522.6B$521.6B$522.
6B$521.6B$522.6B$521.6B$522.6B$521.6B$522.6B$521.6B$522.6B$521.6B$
522.6B$521.6B$522.6B$521.6B$522.6B$521.6B$522.6B$521.6B$522.6B$521.6B
$522.6B$521.6B$522.6B$521.6B$522.6B$521.6B$522.6B$521.6B$522.6B$521.
6B$522.6B$521.6B$522.6B$521.6B$476.4B42.6B$475.4B42.6B$474.4B44.6B$
473.4B44.6B$472.4B46.6B28.2A$471.4B46.6B28.B2AB$470.4B48.6B6.B21.2B$
469.4B48.6B6.3B21.2B3.B$468.4B37.2A10.7B4.6B18.4B.B2A$467.4B39.A9.8B
3.7B2.4B10.8B2A$466.4B40.A.AB5.27B2.2B2.6B2AB.B$465.4B42.2AB4.40B2A$
464.4B45.2B2.2BA40B$463.4B46.2B2.BABA16B2A25B$462.4B47.2B2.BABA16B2A
25B$461.4B48.2B2.2BA43B2A$460.4B48.3B2.25B5.B.14B2A$459.4B48.4B2.20B
2.B11.11B.B$458.4B48.4B4.19B15.10B$457.4B48.4B7.17B12.12B$456.4B48.4B
7.18B11.14B$455.4B36.2A10.4B8.11B.5B12.13B$454.4B38.A9.4B8.12B2.4B12.
13B$453.4B37.A10.4B9.3BA2B.4B19.8B.2B$452.4B38.5A5.4B5.2A3.2BABAB24.
7B$451.4B44.A4.4B5.A5.2B2A25.7B$450.4B42.3AB2.7B.BA.A34.6B$449.4B42.A
.2B3.7B.B2A34.7B$448.4B43.4A12B35.8B$447.4B42.2A2.BA3B2A7B34.8B$446.
4B42.A2.3AB.2B2A7B34.8B$445.4B43.2A.A.B3.10B32.2AB2.6B$444.4B47.A8.8B
30.A.AB.7B$443.4B48.2A7.9B29.A4.6B$442.4B59.3B2.4B27.2A4.6B$441.4B58.
5B3.4B32.6B$440.4B59.2A7.4B30.8B$439.4B61.A8.4B30.8B$438.4B59.3A10.4B
28.9B$437.4B60.A13.4B27.9B$421.2D13.4B76.4B26.10B$421.D.D11.4B78.4B
25.5B2A3B$423.D4.2D4.4B80.4B24.5B2A4B3.2A$419.4D.2D2.D2.D.4B82.4B23.
11B3.A$419.D2.D.D.D.D.2D4B84.4B22.12BA.A$421.BDBDBD.D2.4B86.4B23.8B2.
2A$422.B2DBD.D.4B88.4B22.7B$423.2B.BD.4B90.4B21.5B$422.3B3.4B92.4B20.
5B$413.2D6.4B2.4B94.4B18.7B$414.D6.B2D6B83.2A3.2A6.4B18.6B$414.D.DB3.
B2D5B83.B2AB.B2AB6.4B17.5B$415.2DB.10B84.2B2.3B3.B4.4B13.8B$417.13B
84.3B.3B.4B3.4B10.10B$417.14B75.2A5.7B.13B8.12B$417.15B75.A5.23B6.12B
$419.8B2.4B74.A.AB.19B.8B2.12B$419.6B5.4B74.2AB.29B.13B$418.9B4.4B75.
45B$417.4B4.2D5.4B74.47B$416.4B5.D7.4B73.44BA4B$415.4B7.3D5.4B73.42BA
BA4B$414.4B10.D6.4B74.40BABA4B$413.4B19.4B71.43BA4B$412.4B21.4B70.2A
3.25B4.B.2B3.5B$412.3B23.4B70.A3.20B4.B3.3B7.B$412.2B25.4B66.3A6.15B
7.2A2.B2AB5.3B$412.B27.4B65.A8.11B12.A3.2A6.B2AB$441.4B72.13B8.3A13.
2A$442.4B70.15B7.A$443.4B69.16B$444.4B68.17B$445.4B67.16B$446.4B68.
13B$447.4B67.3B.2B2A5B$448.4B64.4B2.2B2A3B$449.4B63.2A3.10B$450.4B63.
A4.2B3D4B$451.4B59.3A5.3BD4B$452.4B58.A8.2B3D2B$453.4B66.7B$454.4B65.
6B$455.4B64.6B$456.4B63.5B$457.4B62.5B$458.4B61.6B$459.4B59.7B$460.4B
58.6B$461.4B57.6B$462.4B56.6B$463.4B54.8B$464.4B54.8B$465.4B52.9B$
466.4B51.9B$467.4B50.10B$468.4B49.5B2A3B$469.4B48.5B2A4B3.2A$470.4B
47.11B3.A$471.4B46.12BA.A$472.4B47.8B2.2A$473.4B46.7B$474.4B45.6B$
475.4B40.2A2.6B$476.4B38.A.A9B$477.4B37.A3.9B$478.4B35.2A3.9B$479.4B
39.9B$480.4B38.9B$481.4B36.11B$482.4B10.A24.11B$483.4B7.3A24.12B$484.
4B5.A21.B4.14B$485.4B4.2A19.3B3.10B.4B$478.2A6.9B17.6B2.16B$479.A7.6B
13.4B2.7B.16B$479.A.2A5.6B3.B2.2B2.29B2.B2A$313.A6.2A158.A2.A4.45B2.B
A.A$312.A.A4.A2.A158.2AB3.46B5.A$127.2A183.2A6.A.A159.14B2A13B2A21B4.
2A$126.A.A192.A161.13B2A13B2A21B$120.2A4.A357.51B$118.A2.A2.2A.4A353.
17B.B5.26B$118.2A.A.A.A.A2.A222.2D130.15B10.B2.20B$121.A.ABABAB225.2D
129.15B12.20B.B.B$121.A.AB2AB225.D132.13B12.24B2A$122.AB.2B223.2D136.
13B10.24B2A$125.3B224.D134.8B4.2A.A6.2AB2.5B2.12B.2B$125.4B6.2A176.2A
172.6B6.2AB3A3.A.AB2.4B3.13B$123.3B2AB6.A177.2A35.D2.D133.5B8.B4.A2.A
14.11B.B$123.3B2AB3.BA.A212.D.D2.2D5.2D125.B.B9.2A.3A2.2A14.12B2A$
121.10B.B2A212.D.D5.D5.2D125.3B9.A.A20.10B.B2A$120.13B196.2A5.2A8.D.D
4.D.D4.D126.B2AB9.A.A18.2AB.6B4.B$119.14B195.A2.A3.A.A2D5.D.D6.D2.2D
129.2A11.A18.A.AB.4B$118.15B196.A.A3.A3.2D3.D.D10.2D161.A5.5B$117.4B
2.8B165.A16.2A3.2A10.A3.2A2.D4.D.D173.2A8.2A$116.4B5.6B163.3A15.A2.A
2.A.A21.D.D184.A$115.4B4.9B161.A6.2A10.A.A4.2A20.D.D186.3A$115.3B5.2A
4.4B160.2A5.A12.A26.D.D189.A$115.2B7.A5.4B164.A.A38.D.D$115.B5.3A7.4B
163.2A38.D.D$121.A10.4B181.2A7.A10.D.D$133.4B180.A.A4.3A9.D.D$318.A4.
A11.D.D$323.2A9.D.D$333.D.D$332.D.D$308.A22.D.D$283.2A22.A.A21.2D$
282.A2.A22.2A$282.A2.A6.2A$283.2A7.A$290.A.A25.2A.A$290.2A20.2A3.A2.
2A$311.A2.A2.2A$312.A.A8.2A$313.A8.A.A$323.A$271.2A26.2A17.3A$270.A.A
26.2A4.2A$271.A32.A2.A$304.A2.A14.2A6.2A$300.A4.2A15.A.A4.A.A$299.A.A
22.A5.A$299.A.A14.3A5.2A7.2A$300.A27.A4.A$322.A5.A5.A$321.A.A4.A3.A.A
$321.A.A8.2A$322.A2$331.2A$330.A2.A$331.A.A$295.A36.A$294.A.A$294.A.A
19.2A19.2A$295.A19.A.A19.A.A$290.2A22.A.A8.2A11.A$289.A.A23.A8.A2.A$
288.A.A33.A2.A$289.A11.A23.2A$300.A.A$300.A.A12.2A$301.A7.2A3.A2.A$
309.A.A2.A.A$310.A4.A9.A$323.3A$322.A$322.2A5$325.2A$324.A2.A$317.A6.
A2.A$315.3A7.2A$314.A$314.2A4$274.4B$273.4B40.2A$272.4B40.A2.A$271.4B
41.A2.A$201.B68.4B43.2A$201.2B66.4B$201.3B64.4B37.2A$201.4B62.4B37.A.
A$202.4B60.4B38.A$203.4B58.4B38.2A$204.4B56.4B$205.4B54.4B$206.4B52.
4B$207.4B50.4B$208.4B48.4B$209.4B46.4B$210.4B44.4B$211.4B42.4B$212.4B
40.4B$213.4B38.4B$214.4B36.4B$215.4B34.4B$216.4B32.4B$217.4B30.4B$
218.4B28.4B$219.4B21.B4.4B16.A11.2A$9.A13.B196.4B19.3B2.4B16.A.A9.B2A
B$9.3A10.2B197.4B10.2A5.9B17.A.A9.3B$12.A8.3B198.4B10.A4.9B12.2A2.3A.
2A9.B.B$11.2A7.4B199.4B9.A.AB.8B13.A2.A4.B8.5B$11.5B3.4B201.4B9.2AB.
9B3.4B2.BA.A3.3AB2A6.6B$13.3B2.4B203.4B10.11B2.5B2.B2A6.A.2A4.8B$3.2A
7.9B205.4B9.11B2.8B10.13B$3.A8.8B207.4B8.21B12.13B$2A.A.B3.10B209.4B
8.19B12.15B$A2.3AB.2B2A7B210.4B6.19B2.B10.15B$.2A2.BA3B2A7B211.4B3.
26B5.B.17B$3.4A12B212.4B.51B$3.A.2B3.7B.B2A211.4B.21B2A13B2A13B$4.3AB
2.7B.BA.A211.25B2A13B2A14B$7.A4.4B5.A212.50B3.B2A$2.5A5.4B5.2A212.48B
4.A2.A$2.A10.4B217.33B2.2B2.B3.6B5.2A.A$4.A9.4B216.16B2.7B2.4B13.6B7.
A$3.2A10.4B215.16B3.6B17.9B6.2A$16.4B215.14B5.3B19.2A4.4B$17.4B217.9B
.3B4.B21.A5.4B$18.4B216.8B3.2A23.3A7.4B$239.4B6.A24.A10.4B$241.4B5.3A
33.4B$243.2A7.A34.4B$243.A44.4B$244.3A42.4B$246.A43.4B$291.4B$292.4B$
293.4B$294.4B$295.4B$296.4B$290.2A5.4B6.2A$287.A3.A5.4B6.A$286.A.A2.A
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284.3AB2AB.6BABA4B$286.A.2AB.7BA3B$290.12B$289.13B$287.2A13B$286.A.A
12B$283.A2.A.B.2B.10B$282.A.A.2A4.6B3.2A$282.2A2.A6.6B2.A$286.A.A3.6B
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293.6B$292.6B15$294.3A$293.A2.A$296.A$292.A3.A$296.A$293.A.A35$111.4B
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117.6B5.4B$117.8B2.4B$115.15B$115.14B$115.13B$113.2AB.10B$112.A.AB3.B
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A$117.A2.A.A.A.A.2A$117.4A.2A2.A2.A$121.A4.2A$119.A.A$119.2A!
This has the advantage of not being glide-reflective, so the trigger signals wouldn't need to cross over the single-channel stream to get where they need to be for the next period. However, the circuitry is more complex than the design described above.
I6_I6 wrote: October 9th, 2026, 11:56 am But couldn't you use the same method used to build the current omniship, but use mostly gliders instead of XWSSs to create an omniship that's rotated 45˚? It would be harder to get the wanted slope, but it would probably be smaller. Is there some part of the spaceship that prevents this?
Part of the requirements for being an omniship is that the spaceship can be adjusted to velocities arbitrarily close to the speed limit. Or at least, that's how I've been using the term. I recently wrote a wiki article about omniships, and it doesn't explicitly state that, but that is the implication of the second paragraph. If gliders were used instead of xWSSs, the spaceship would not be able to achieve velocities near the speed limit. You are right that using gliders instead of xWSSs could produce a smaller spaceship with an adjustable slope though.

It might be counterintuitive that only xWSSs allow velocities near the speed limit because after all, both xWSSs and gliders travel at the speed limit. However, the difference is that both components of a glider's velocity are below the speed limit. Consequently, if the desired velocity has a component which is faster than c/4, it will be impossible for the spaceship to achieve that velocity if it's "leading edge" is driven by the motion of gliders.

Re: Make a Spaceship With an Adjustable Slope

Posted: October 18th, 2026, 6:01 am
by ENDW
Goldtiger997 wrote: October 18th, 2026, 1:13 am Another possibility is a loopship design which alternates between travelling orthogonally and diagonally. I'm envisioning something like this:
I think I will do it a month later.
By the way, is there a script that make this omniship3?

Re: Make a Spaceship With an Adjustable Slope

Posted: October 23rd, 2026, 9:55 am
by ENDW
This is the last optimize. And this is the script.
Edit: correct the script.

Code: Select all

# make-omniship-v3.py
# This script makes the more reduced omniships posted by ENDW here: https://conwaylife.com/forums/viewtopic.php?p=238296#p238296
# ENDW, October 2026
# The base64 decoding code is borrowed from a script by dvgrn: https://conwaylife.com/forums/viewtopic.php?f=2&t=2936&start=25#p134875

import golly as g
import math
import base64
import os

response = g.getstring("Enter a non-orthogonal velocity below the speed limit, appending 'h' if you want a HashLife-friendly omniship:","(2,1)c/7h")
if response == "":
  g.exit("Script canceled due to lack of input.")
if response.endswith("h") or response.endswith("H"):
  response = response[:-1]
  hfriendly = True
else:
  hfriendly = False
if response.find("/")==-1:
  g.exit(f"Invalid format for velocity specification: \"{response}\".")
response_split = response.split("c/")
if len(response_split) != 2:
  g.exit(f"Invalid format for velocity specification: \"{response}\".")

disp, period = response_split
if not period.isdigit():
  g.exit(f"Invalid period \"{period}\".")
if len(disp) < 5 or disp[0] != '(' or disp[-1] != ')':
  g.exit(f"Invalid format for displacement specification: \"{disp}\".")
disp_split = disp[1:-1].split(",")
if len(disp_split) != 2:
  g.exit(f"Invalid format for displacement specification: \"{disp}\".")
if not disp_split[0].isdigit() or not disp_split[1].isdigit():
  g.exit(f"Invalid format for displacement specification: \"{disp}\".")
x = int(disp_split[0])
y = int(disp_split[1])
p = int(period)

if (x+y)*2 >= p:
  g.exit("This script can only create spaceships below the speed limit.")

if x == 0 or y == 0:
  g.exit("This script cannot create orthogonal spaceships.")

tempfile = os.path.join(g.getdir("temp"),"mcgz.tmp")

# WARNING:  this function uses the current Golly layer to retrieve cell data,
#   so if there's anything important in the current layer,
#   a new layer should be created before calling this function
def get_cells_from_mcgz_base64(s):
  base64bytes = s.encode("ascii")
  mcgzbytes = base64.b64decode(base64bytes)
  with open(tempfile, "wb") as f:
    f.write(mcgzbytes)
  g.open(tempfile)
  return g.getcells(g.getrect())

tape_base_64 = "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"
single_channel_stream = get_cells_from_mcgz_base64(tape_base_64)
half_1 = g.parse("313bo$312bobo$311bo2bo$312b2o$317b2o$317bobo$318bo3$269b2o$269bobo$270b2o3$274b2o$274bobo42b2o$275b2o36b2o4bobo3b2o$283b2o3b2o19b2o2b2o5b2o3bobo$283b2o2bobo19b2o15bo$287b2o2$283bo10b2o$283b3o8bo$286bo9bo$285b2o8b2o2$258bo$257bobo16b2o$258bo17b2o2b2o$280b2o41bo$306b3o13bobo$322b2o3$259b2o$258bo2bo$259bobo$260bo76b2o$337bobo$338bo2$282b3o2$261bo42b2o$261bo36bo4bo2bo$261bo35bobo3bobo$297bo2bo3bo$284bo13b2o18b2o$261b2o20bobo31bo2bo$253bo8bo19bobo26b2o5bobo$251b3o8bobo17b2o26bo2bo5bo$250bo12b2o24bo21b2o$250b2o3b2o31bobo$254bo2bo31bo$255bobo$256bo4$292b2o4bo$292b2o3bobo$297b2o12$337bo$336bobo$336b2o24$377b2o$377bobo$378bo7$294b2o$294bobo$295bo27$28b2o4b2o$28b2o4b2o5$35b2o$35b2o7$23b2o$23b2o3$24b2o$24b2o$15b2o$14bobo$14b2o4$17bo$16bobo$16bobo$17bo8$21b2o$21b2o3$22b2o$22b2o2$184b2o$184b2o100b2o$286b2o5$232b2o$232b2o3$226b2o51b2o8bo$226b2o51bo8bobo$230b2o45bobo8bo2bo8bo$230b2o45b2o10b2o8bobo$270bo28b2o$251b2o16bobo$251b2o16bobo$225b2o43bo$225b2o5$293b2o$293bo6b2o$268bo26bo4b2o$267bobo5b2o14b5o$267b2o7bo13bo$276bobo12b3o$220bo56b2o15bo$219bobo69b4o$218bo2bo64b2o3bo3b2o$39bo179b2o65b2o4b3o2bo$38bobo204b2o47bob2o$37bo2bo13bo19bo170bobo46bo$38b2o12b3o18bobo171bo45b2o$51bo20bo2bo171b2o$51b2o20b2o153bo$38b2o187bobo55b2o$39bo187bo2bo54bo$39bobo186b2o19bo36b3o$40b2o206bobo37bo$48b2o199b2o$47bo2bo186b2o59bo$48b2o34b2o142b2o7b2o58bobo$83bobo143bo67bobo$84bo144bobo59b2o5bo$80b2o148b2o58bo2bo$79bo2bo196b2o9bobo$51b2o27bobo8b2o185bo2bo9bo$51bo18bo10bo9b2o186bobo$52b3o15b3o207bo$54bo18bo196b2o3b2o$47b2obo21bobo195b2o3b2o$38b2o3b2o2b2ob3o19bobo$38bo2bo2bo8bo19bo$39b5o3b2ob3o229b2o$48bobo231bo$41bo6bobo229bobo6b2o$40bobo6bo176b2o52b2o7b2o$40b2o46b2o135bo2bo$88b2o136b2o$235bo$234bobo$234bobo$68b2o20b2o143bo$67bobo20b2o185b2o$67bo209bo$66b2o7b2o166b2o3b2o28b3o$75b2o157b2o7b2o3bo31bo9bo$234b2o13b3o37bobo$60b2o21b2obo164bo37bobo$60b2o21b2ob3o201bo$89bo$83b2ob3o$84bobo$84bobo177b2o$85bo178b2o$272b2o$86bo185bo$84b3o162bo23b3o$83bo164bobo24bo$83b2o164b2o$75b2o197bo$75b2o196bobo6b2o$273bobo5bo2bo$272b2ob3o3bobo$278bo3bo$b2o269b2ob3o$b2o269b2obo$64b2o$65bo198b2o$2b2o61bobo27bo159b2o7b2o$2b2o62b2o26bobo159bo$93bo2bo159bobo$94b2o161b2o$61b2o$62bo$62bobo32b2o$63b2o31bo2bo177b2o$96bobo178b2o$97bo3$84b2o202bo$63bo20bo177bo24bobo$62bobo20b3o173bobo23b2o$61bo2bo22bo173bobo$62b2o198bo$2o257b3o$2o257bo2$69b2o$b2o65bobo$b2o66bo4$242b2o$241bo2bo$241bobo$242bo4$234bo$232b3o$231bo$231b2o21$254bo$253bobo$254b2o5$134bo$133bobo$133bo2bo$134b2o2$138bo$138b3o$141bo$140bobo$140bobo$141bo2$166bo$165bobo$165bobo$156b2o8bo$156b2o4$136b2o$135bobo$135bo$134b2o7b2o$143b2o2$151b2obo$151b2ob3o$132b2o23bo$127b2o3b2o17b2ob3o$127bobo22bobo$128bo23bobo6bo$123bo29bo6bobo$122bobo35b2o$121bo2bo29bo$122b2o28b3o$151bo$151b2o$143b2o$143b2o2$122bo$121bobo$121b2o2$132b2o$133bo$133bobo$134b2o3$129b2o60b2o$130bo43bo16b2o$130bobo40bobo$131b2o41b2o$191bo$190bobo$190b2o2$152b2o$152bo$153b3o$155bo!")
half_2 = g.parse("167bo$166bobo$166b2o50$122b2o$106bo14bo2bo$104b3o15bobo$59bo21bo21bo19bo$58bobo19bobo20b2o$58b2o20b2o2$113bo$111b3o$110bo$110b2o$85bo$84bobo$84bobo$85bo$89b2o$88bobo$88bo$87b2o2$124b2o$92b2o30b2o$91bobo$91bo$90b2o6$101b2o$101b2o$109b2o$109bo$110b3o$112bo2$111bo$110bobo$110bobo$109b2ob3o$115bo$109b2ob3o$109b2obo2$85b2o14b2o$73b2o9bo2bo4b2o7b2o$72bo2bo9b2o6bo$72bobo18bobo$73bo20b2o2$86bo$85bobo$85b2o27b2o$80bo33b2o$79bobo$64b2o12bo2bo$16b2o46bobo6bo5b2o$2o14b2o47bo6bobo$obo2b2o65bobo24bo$bo3b2o56b5o3b2ob3o21bobo$62bo2bo2bo8bo20bobo$20b2o40b2o3b2o2b2ob3o22bo$20b2o49b2obo21b3o$78bo17bo$76b3o$75bo$75b2o5$72b2o$71bo2bo10b2o$72b2o11b2o$64b2o$63bobo23b2o$63bo24bo2bo$62b2o24bobo$75b2o12bo$75bo$76b3o$78bo53$411b2o4b2o$411b2o4b2o5$418b2o$418b2o$413b2o$413b2o3$408b2o$408b2o8$487b2o$487b2o3$440b2o51b2o$441bo51b2o$441bobo45b2o$442b2o45b2o$450bo$449bobo16b2o$449bobo16b2o$427bo7bo14bo43b2o$426bobo5bobo57b2o$426bobo5bobo$427bo7bo3$426b2o$427bo$425bo26bo$425b5o14b2o5bobo$430bo13bo7b2o$427b3o12bobo$426bo15b2o13b2o$426b4o27b2o$424b2o3bo3b2o$423bo2b3o4b2o$423b2obo47b2o$426bo46bobo$416b2o8b2o45bo$415bo2bo53b2o$416b2o$434b2o$435bo$390b2o4b2o34b3o36bo$390b2o4b2o34bo37bobo$470b2o$482b2o$431b2o49b2o7b2o$430bo2bo57bo$397b2o31bobo56bobo6b2o$397b2o32bo57b2o6bo2bo$440bo57b2o$439bobo$440b2o2$444b2o3b2o$444b2o3b2o3$437b2o$438bo$438bobo$439b2o3$485bo$484bobo$484bobo$485bo$442b2o$443bo$440b3o28b2o3b2o$440bo31bo3b2o7b2o$469b3o13b2o$469bo2$475b2o$474bo2bo5bo$475b2o5bobo$455b2o26b2o$455b2o$447b2o$448bo$445b3o$445bo$440b2o28b2o$439bobo4bo23b2o$440bo4bobo$445bobo$443b3ob2o$442bo$443b3ob2o$353b2o90bob2o$348b2o2bo2bo$348b2o3b2o100b2o$455b2o7b2o$441b2o21bo$440bobo19bobo$441bo20b2o4$442b2o$442b2o2$482bo$481bobo4bo$481bobo3bobo$458bo23bo4bo2bo$457bobo28b2o$457bobo$458bo22b2o$459b3o19b2o$461bo27bo$488bobo$489bo7b2o$497bo$495bobo$495b2o6$492b2obo$492b2ob3o$498bo$492b2ob3o$493bobo$493bobo$494bo4$467bo12b2o12bo$466bobo11b2o11bobo$465bo2bo24bobo$466b2o26bo4$490bo$489bobo$489bobo$463b2o8b2o13b2ob3o$462bo2bo7b2o19bo$463b2o23b2ob3o$488b2obo$507b2o4b2o15b2o4b2o$480b2o25b2o4b2o15b2o4b2o$471b2o7b2o$472bo$472bobo$473b2o$514b2o21b2o$514b2o21b2o2$493b2o$493b2o3$419bo$411bo6bobo$411b3o4bobo57bo$414bo4bo57bobo$413bobo61bobo$413bobo62bo$414bo60b3o$435bo39bo$434bobo$434b2o2$429b2o$429b2o4$409b2o$408bobo$408bo$407b2o7b2o$416b2o2$402b2o3b2o15b2obo$402bobo2bobo14b2ob3o$403bo4bo21bo$424b2ob3o$425bobo$425bobo$426bo2$427bo$425b3o$424bo$424b2o$416b2o$416b2o4$401bo$400bobo$399bo2bo2b2o$400b2o4bo$406bobo$407b2o4$405b2o$405b2o6$425b2o$425bo$426b3o$428bo4$408bo$407bobo$407bobo$408bo$420b2o$420b2o54$389b2o$388bobo$389bo20$390b2o$389bobo$390bo!")
g_to_mwss = g.parse("79bo$78bobo$78bo2bo$79b2o4$50bo41b2o$49bobo40b2o5b2o$49bobo19b2o26b2o$50bo15bo3bo2bo$64b3o3bobo$63bo7bo25b2o$63b2o32b2o$103b2o$103b2o$40b2o4b2o$40b2o3bo2bo$46b2o$66b2o$66b2o5$41b2o$41b2o$76b2o$77bo$74b3o$29bo11b2o26bo4bo$28bobo9bobo25bobo$28b2o10bo27b2o$39b2o53b2o$94b2o3$18bo$16b3o$15bo$15b2o$2o$bo$bob2o$2bo2bo$3b2o$18b2o13b2o$18b2o13b2o2$83b2o$83bobo$84bo9b2o$57b2o34bo2bo$57b2o35b2o$21b2obo6b2o$21b2ob3o3bobo$27bo2bo$21b2ob3o2b2o26b2o25bo$22bobo32b2o23b3o$10b2o10bobo18b2o36bo15b2o$10b2o11bo18bobo16bo19b2o14bo$42bo17bobo35b3o$41b2o8b2o6bo2bo37bo$24b2o25bo8b2o$23bo2bo25b3o$24bobo27bo$5b2o18bo$5b2o64b2o$70bobo5b2o29b2o$70bo7b2o29b2o$69b2o27b2o$39b2o10b2o44bo2bo$38bo2bo9b2o9b2o19bo13bobo$39b2o20bo2bo14b2obobo13bo$62bobo13bobobobo22b2o$63bo11bo2bobobobob2o19b2o$75b4ob2o2bo2bo$79bo4b2o$77bobo$65b2o10b2o$64bo2bo$65b2o29b2o$85b2o9bobo$85b2o10bo!")
g_to_mwss_deleter = g.parse("2bo$obo$b2o!")
trigger_1 = g.parse("3b2o$3ob2o$5o$b3o116$134091b2o$134088b3ob2o$134088b5o$134089b3o!")
trigger_2 = g.parse("134303b2o$134300b3ob2o$134300b5o$134301b3o113$b3o$5o$3ob2o$3b2o!")

def round_up_to_nearest_multiple(to_round, factor):
  return factor * (1 + (to_round - 1)//factor)

x0 = 3130000
y0 = 3130000
p0 = 14100000

min_x_multiple = 1 + (x0 - 1)//x
min_y_multiple = 1 + (y0 - 1)//y
# in order for diag_adjust to be positive, we require that multiple >= (p0 - 2*x0 - 2*y0)/(p - 2*x - 2*y).
min_p_multiple = max(1 + (p0 - 1)//p, 1 + (p0 - 2*x0 - 2*y0 - 1)//(p - 2*x - 2*y))

multiple = max(min_x_multiple, min_y_multiple, min_p_multiple)
if hfriendly:
  multiple = 2**math.ceil(math.log(multiple,2))
else:
  x_multiple_for_required_divisibility = 4//math.gcd(x, 4)
  y_multiple_for_required_divisibility = 4//math.gcd(y, 4)
  p_multiple_for_required_divisibility = 8//math.gcd(p, 8)
  multiple_for_required_divisibility = max(x_multiple_for_required_divisibility, y_multiple_for_required_divisibility, p_multiple_for_required_divisibility)
  multiple = round_up_to_nearest_multiple(multiple, multiple_for_required_divisibility)

if y > x:
  danger_zone_lower = 536500 + (y0 - x0)
  danger_zone_upper = 537000 + (y0 - x0)
  if multiple*(y-x) > danger_zone_lower and multiple*(y-x) < danger_zone_upper:
    g.note("adjustment required")
    if hfriendly:
      multiple *= 2
    else:
      multiple = 1 + (danger_zone_upper - 1)//(y-x)
      multiple = round_up_to_nearest_multiple(multiple, multiple_for_required_divisibility)
elif x > y:
  danger_zone_lower = 536500 + (x0 - y0)
  danger_zone_upper = 537000 + (x0 - y0)
  if multiple*(x-y) > danger_zone_lower and multiple*(x-y) < danger_zone_upper:
    g.note("adjustment required")
    if hfriendly:
      multiple *= 2
    else:
      multiple = 1 + (danger_zone_upper - 1)//(x-y)
      multiple = round_up_to_nearest_multiple(multiple, multiple_for_required_divisibility)

x1 = x * multiple
y1 = y * multiple
p1 = p * multiple
# it should be guaranteed at this point that 4 | x1, 4 | y1, and 8 | p1

trigger_1_adjust = (x1 - x0)//4
trigger_2_adjust = (y1 - y0)//4
diag_adjust = (p1 - p0)//8 - trigger_1_adjust - trigger_2_adjust

g.new(f"Spaceship with speed {response}  =  ({x1},{y1})c/{p1}")
g.setrule("B3/S23")
g.putcells(single_channel_stream,0,0)
g.putcells(g_to_mwss,21,-10)
g.putcells(half_1,171,-192)
g.putcells(half_2,196974 + diag_adjust, 196909 + diag_adjust) 
g.putcells(half_1,197658 + diag_adjust, -2932705 + diag_adjust - 4*trigger_2_adjust, 0, -1, -1, 0)
g.putcells(g.evolve(trigger_1, 2*(trigger_1_adjust%2)), -916996 - trigger_1_adjust - (trigger_1_adjust%2), -41)
g.putcells(g.evolve(trigger_2, 2*(trigger_2_adjust%2)), -917078 - trigger_2_adjust - (trigger_2_adjust%2), -18)
g.putcells(g_to_mwss_deleter,-72 - 390750,-84 - 390750)
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