Thank you+ for joining the hunt for the lost wallet’s private key.
Each day, you can run the Algorithm quietly in the background of your computer.
It won’t slow you down — you can stop or restart it anytime.There are 10 billion Lbitz shares in total — a fixed number that will never change.
If you uncover the private key, that day becomes Discovery Day — and you’ll receive 2.9 billion Lbitz shares.
If others make the same discovery that day, the reward is shared equally.
Be sure to report your discovery within 3 business days of Discovery Day to claim your share.
Even if you don’t hit the Jackpot, you still earn 1 Lbpoint for every 100 iterations the Algorithm runs.
Each iteration performs 100,000 individual searches.
On Discovery Day, every Lbpoint you’ve earned up to and including that day will convert into a share of 2 billion Lbitz, divided among all existing Lbpoints.
The earlier the discovery, the larger your reward.Be sure to submit your control.txt file within 7 business days of Discovery Day to claim your reward.
+Anyone from anywhere in the world.
How to Download the LostBitcoinz Algorithm
Converting Lbitz into Bitcoin — Fast
We will work to convert the 10 billion Lbitz shares into the recovered Bitcoin, or their U.S. dollar equivalent, as quickly as possible.
(Taxes may apply.)
The private key x lies hidden within the vast interval [1, N − 1] — a space so large it defies comprehension.
At every point k within this range lies a potential jackpot number j, where the secret reveals itself as x = k / j . (More precisely, k = jx mod N.)
We divide this immense range into one million zones.
Each participant claims one zone for one week, searching for a pair (k, j) where everything changes.++
One step. One week. One discovery.
Someone, somewhere, will strike the jackpot.
No one knows when.
++Given the lost private key x, the Algorithm explicitly enumerates pairs (k, j) and checks kG = jQ, where Q = xG. In this approach, if x is a “low-lying” value (for example x ≤ 105, N – 1 ≥ x ≥ N – 105, or x = int(N / a), for a = 2, 3, 4…), then the sequence of pairs (j·x mod N, j), for j = 1, 2, 3… will produce matches early in the search, and the correct key can be found quickly. For other values of x, a matching pair (k, j) may not appear until much later in the enumeration. In other words, the time to hit the correct relation varies widely depending on the spacing of the multiples of x – some cases are “easy-to-find”, while others are “hard-to-find”.
By contrast, Pollard’s rho does not enumerate (k, j) in any fixed or structured order. Instead, it generates a pseudo-random sequence of coefficient pairs (ai, bi), each defining a group element aiG + biQ, and searches for a collision of the form aiG + biQ = ai’G + bi’Q, for some i ≠ i’. When such a collision occurs, the corresponding coefficients can be used to recover the discrete logarithm.
In heuristic analyses of Pollard’s rho, the sequence produced by the iteration function is modeled as behaving like a random walk through the group, meaning that over many steps it tends to explore the group broadly rather than following a fixed pattern. This heuristic – based on the idea that a pseudo-random mapping behaves similarly to a random one – is used to explain why, on average, the algorithm finds a useful collision in about √N steps (a huge number), where N is the group’s order, even when x = 1.