Computer Science Expert: “No one else seems to have figured out the exact three-digit multipliers that were used”


I received this from scientist John Gustafson:

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I’m a professor of Computer Science at the National University of Singapore; I’ve been expatriated from my US home for the last five years. If you are curious about my credentials, you can find them on www.johngustafson.net or Wikipedia’s entry for me:

I’d like to see this information more widely circulated, and also put into the hands of the Giuliani and Powell teams. There are web sites pointing out how precise vote ratios were maintained, but no one else seems to have figured out the exact three-digit multipliers that were used.

John Gustafson


As most of you know, I’m a numbers guy. It runs in the family.

This information is hard to find on the web. I stumbled on it when trying to find out how it is possible for a vote drop to have “negative votes” for Trump, decreasing his totals. I didn’t find a direct answer, but I found something far more interesting. Here’s a web site that has images of spreadsheets with numbers legible:


There are several web sites and videos calling attention to the fact that the incremental votes that came in after a certain time stamp were all in the same ratio of 50.051% for Biden and 49.949% for Trump, several days after the Georgia election until Biden overcame Trump’s substantial lead:

This chart starts at 10 PM Friday November 6. Or rather, 9:59:41.

It looks like the vote totals are being stored as 64-bit IEEE 754 floating-point values. Not integers. That’s what I found striking. Not integers?? Fractional values. And they are exactly tied to three decimal places. Biden and Trump each have exactly 2,454,662.782 votes.

The next thing that happens, right after that perfect tie at exactly 10:00 PM, is a one-time negative vote for Trump, adding –1,473.41 (yellow highlighted square). And a big vote dump of 3,495.54 for Biden, all in only 59 seconds. A tabulator can count 118 paper ballots per second?

The full number of significant figures is not propagated in the columns to the right of that one, but it is possible to recover it by doing the math a little more carefully.

The horizontal gray highlighted region is when the algorithm kicked in. In those two rows, the “votes” column shows a vote dump of 48 votes. (The next two columns show votes in the 2012 election and in 2016.) The vote for Biden was incremented by 23.712 votes, using all five significant figures. The vote for Trump was incremented by 23.664 votes. Those two figures sum to 47.376 votes, leaving 0.624 votes for the third-party candidates. Oh, this is interesting: 0.624 votes out of 48 is 1.3000000%. Exactly.

Now we can see that the ratios in the blue and pink columns are being maintained to five significant digits:

Biden: 23.712 / 47.376 × 100% = 50.050658561296859%, rounds to 50.051%.

Trump: 23.664 / 47.376 × 100% = 49.949341438703141%, rounds to 49.949%. Check.

But those are strange, long decimals. What if we divide by the full 48 votes, the way we discovered that the third-party candidates got exactly 1.3000000%?

Biden: 23.712 / 48 × 100% = 49.4000000% exactly.

Trump: 23.664 / 48 × 100% = 49.3000000%, exactly.

So the articles are not fully reverse engineering the algorithm, but it’s clear that they assigned 1.3% to the third-party votes, then created an exact 0.1000000% difference between the Biden votes and the Trump votes.

If you’re curious how it is possible to do such a hack on a voting machine, it’s called a “Man-In-The-Middle” cyberattack, and Dr. Kershavarz-Nia has detailed exactly how this was done and the IP addresses used to do it. An excellent article on that is here:

The ‘smartest man in the room’ has joined Sidney Powell’s team, American Thinker,

His sworn affidavit is here:


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