pfoytik
Peter Foytik

https://pfoytik.github.io/

Modeling and Simulation Researcher at Old Dominion University

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npub1mhgj7rm3le7272kel93nn2c54s8tfdu0ynqfp5qm8yf2zrvy3qls6070rs

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nprofile1qqsdm5f0paclul909tvljcee4v22cr45k78jfsys6qdnjy4ppkzgs0cpz3mhxue69uhhyetvv9ujuerpd46hxtnfduqs6amnwvaz7tmwdaejumr0ds239msd

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offchain.pub

relay.damus.io

nos.lol

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npub1mhgj7rm3le7272kel93nn2c54s8tfdu0ynqfp5qm8yf2zrvy3qls6070rs

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Last Notes

2026-10-20 11:42:33 UTC

This is the future!
#nevent1q…95gs

2026-10-16 00:36:48 UTC

Sunset sailing!
https://npub1mhgj7rm3le7272kel93nn2c54s8tfdu0ynqfp5qm8yf2zrvy3qls6070rs.blossom.band/881e9b51fc7fc5e55275b52206d61dcc4c7fb7d2326ff9c24cd010b2fba033b4.jpg

2026-08-29 02:22:16 UTC

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Are there any exchanges stating they will trade that token?

2026-08-14 01:29:45 UTC

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There are a lot of complexities and variables to consider for forks :)

2026-08-13 01:47:01 UTC

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Without a price signal people and systems will just assume and the uncertainty can lead to poor decisions...

2026-08-08 16:44:03 UTC

Today Bip110 softfork activates via user activated soft fork. With or without miner support. Whatever happens, one thing the simulation makes clear: the variable that has the most influence for contested forks is the one nobody has been able to measure.
Economic Adoption.
Miner signaling is observable. Block heights are countable. Pool positions are public. These are legible signals you can watch them in real time on mempool.space.
Economic adoption, who holds BTC and which chain they'll price as canonical, is nearly invisible.
This isn't a modeling limitation, it's structural. Self-custody holders control the majority of supply but produce no observable fork preference signal. Exchanges hold less but dominate price discovery. Their positions aren't public until after they've committed.
The one mechanism that would make economic preferences legible in advance is a pre-fork futures market. Futures on the two fork tokens would let economic actors signal their preference before any block is mined, before the hash war begins.
That market doesn't exist for BIP110.
Without it, the hash war itself becomes the price discovery mechanism. Miners commit, chains diverge, prices follow and only then do economic actors have a signal to respond to. The two-layer structure we found in simulation reflects exactly this sequencing.
As flag day arrives: watch the miner signals, but know what they can and can't tell you. Hashrate commitment tells you about Layer 1. Whether economic actors follow is Layer 2, and that signal won't exist until Layer 1 resolves.
Contentious forks are an information problem.

2026-08-08 01:43:57 UTC

People assume a contentious Bitcoin fork would break Lightning. We ran 692 simulated fork scenarios on real bitcoind nodes to find out. The actual risk is narrower than you'd think and it has a precise shape. Lightning's security during a fork depends less on the protocol than on three things: whether you have hung HTLCs at inception, whether your peers stay online, and less obviously, whether your watchtower is running on both chains. A watchtower on the other chain restores the justice transaction deterrent even when your peer has switched allegiances. More on that in the paper.
https://image.nostr.build/94c86d6351b62deb3b7733812ace188798ffdc2cf468509e7e91b4ef720ce7b9.png
This is HTLC dual-resolution risk across 692 fork scenarios. X-axis: how much economic activity supports the new rules. Y-axis: how much mining hashrate is ideologically committed to the new rules. Colour: wall-clock minutes during which the same Lightning payment could resolve in opposite directions on two chains.
Most of the map is pale yellow. Near zero.
An in-flight HTLC has a block-height expiry. If the fast chain reaches that block before the slow chain does, the recipient can claim the payment on the fast chain while the sender reclaims a timeout refund on the slow chain. Same sats, two outcomes. The routing node in the middle absorbs the loss.
This only materialises if all three are true simultaneously:
① You're in the contested zone: that thin band where neither chain collapses quickly. ~6.6% of the full parameter space.
② You have a hung HTLC at fork inception: not just any payment, one where off-chain communication has already broken down before the fork.
③ That HTLC's expiry falls inside the divergence window before the slow chain's difficulty retarget normalises block times.
Each is uncommon. Their intersection is rare.
83.4% of scenarios show zero dual-resolution risk because the losing chain collapses before mining enough blocks for the race to even start. If you're on the dominant chain, Lightning is effectively fork-blind. Payments settle over TCP in milliseconds. No block confirmations involved. The fork is invisible.
The dark red cell (~35 days of exposure) sits at economic split ~0.65, pool committed ~0.43, the scenario where pools are ideologically split nearly 50/50 and economic support is right at the decision boundary. Neither chain dies. Both limp on for weeks. Any hung HTLC expiring in that window is at risk.
The orange blobs bottom-right are a different beast: decisive v26 wins where v27 dies slowly with almost no hashrate. The losing chain mines blocks so slowly that even a 40-block HTLC expiry takes weeks in wall-clock time. Counterintuitively, a clean fork resolution can be more dangerous for in-flight payments than a prolonged contest.
LND's default --bitcoin.timelockdelta is 40 blocks, roughly 7 hours of mainnet protection. In a contested fork scenario that 7-hour window gives you an 82.6% chance of dual-resolution exposure. Raising to 144 blocks drops that to 17.4%. Raising to 288 drops overall vulnerability below 0.3%.
This analysis didn't require new simulations. The Warnet sweep data already contained per-scenario block production timeseries for both chains. The key reframe: instead of modelling channel close timing, we asked whether the fast chain reaches a HTLC's expiry block before the slow chain and by how many wall-clock minutes. That gap is the figure above.
The threat model itself went through several iterations in conversation with Claude before the plan was written. Claude Code ran the analysis against 692 scenarios from the existing dataset. The whole pipeline from idea to figure took about a day.
The fork dynamics simulation paper this builds on is at
https://github.com/pfoytik/Bitcoin-Fork-Governance-Study

2026-08-03 15:48:59 UTC

One of the more counterintuitive findings from the simulation:
Winning the hashrate war and achieving full economic adoption are two separate events controlled by different parameters and ordered in time for a structural reason.
Fork outcomes operate on two layers.
Layer 1: the hash war - which fork wins the mining competition. Driven by how much committed hashrate the upgrading fork can field.
Layer 2: economic adoption - whether economic actors fully migrate to the winning chain.
https://image.nostr.build/ccb6dc6b6c268b03cedbb0c1709a45d30eddee5c7ef471e4e2ff065cf1bae86c.png
The two layers are structurally ordered — hashrate cascade resolves first, economic adoption follows. Not because of how fast each actor type decides, but because of what information they need.
Economic nodes can't commit before the price signal exists.
We tested this directly by swapping decision rates so economic nodes decide 3× faster than pools. The ordering persisted; mean lag was essentially unchanged.
Bottleneck is the 60s price oracle, not decision cadence. Economic nodes can't act on information that doesn't exist yet.
The two layers are controlled by different parameters.
Layer 1: pool committed split, how much hashrate commits.
Layer 2: pool max loss tolerance, how quickly committed pools cascade after the retarget, which determines whether the price gap reaches economic nodes.
The practical implication: winning the hash war is necessary but not sufficient for full economic resolution.
A fork can win Layer 1 and still leave Layer 2 unresolved if the cascade is too slow to generate a large enough price signal.
Scope boundary: no futures market. In reality, futures on fork tokens can form before activation, then economic actors could fully commit before a single block is mined on the new chain. This ordering is a post-activation, spot-pricing result.
#nevent1q…8w6h

2026-08-03 11:27:26 UTC

"A gaping wound in Bitcoins soul, and the bleeding has not stopped yet"
#nevent1q…hfej

2026-07-27 15:42:03 UTC

A finding from the simulation that requires honest framing:
User nodes are non-pivotal in fork outcomes under the model, even when tested with majority Bitcoin custody. But understanding why reveals something precise about how UASF actually works. The model captures price-signal-driven fork adoption. Per-entity market weight matters more than aggregate custody. Exchanges and custodians individually move markets. Individual node operators don't, even in aggregate, their price oracle influence is marginal.
https://image.nostr.build/a62812ed0b2dad1871e1539d0a69b9b21957e06e37506c3685f15ad81cd4d5b0.png
Figure caption: "SP_user score across 598 scenarios values near zero indicate user nodes are structurally far from being pivotal under any tested parameter combination."
We tested this explicitly: even at UCF=0.65... user nodes holding majority custody outcomes barely moved. The null isn't primarily about observability. It's about how price influence works at the per-entity level in real markets. The model tests whether user custody weight directly moves fork prices. It doesn't... even at majority custody the price oracle barely responds, because it weights per-entity market impact, not aggregate raw custody.
What UASF proponents argue is a two-step mechanism: coordination pressure changes exchange positions, which then moves prices. Step one, users influencing economic actors, is outside the model's scope. Step two is exactly what the model tests.
The simulation does model user node enforcement, user nodes running v27 reject v26 blocks. But miners follow price, not validation headcount. User enforcement creates a valid partition; it doesn't make that partition profitable to mine.
This is why BIP148 required exchange commitment to be credible. User enforcement alone couldn't move miners, the price oracle was dominated by economic nodes. When exchanges signaled v27, price shifted, and miners had no rational choice but to follow.
Miner signaling and exchange positions are observable, attributable, weighted signals. User node counts aren't, many run behind Tor, can't be verified as non-Sybil, and carry no economic weight. They measure software version, not economic alignment.
#nevent1q…8w6h

2026-07-22 11:27:01 UTC

While I could see miners playing this game, I think depending on the amount of held Bitcoin they could have more leverage as they would already have tokens on both chains. I'm not sure if miners would have the spare capital to do this based on how low the hash profit is right now.
Exchanges will already have large holdings on both chains and would make the game theory more complicated as to how the price of both tokens will be manipulated.
Interesting scenario either way.
#nevent1q…pu4z

2026-07-18 17:18:47 UTC

Inspired by Edil Medeiros
at the UW BRI workshop: Hearing the philosophy of Bitcoin made me feel like I was developing less for the machine and more for mankind
Great workshop thanks everyone!

2026-07-15 03:28:53 UTC

Presented at the UW Bitcoin Research Initiative yesterday. The full picture is now available as a decision boundary, all findings, and the interactive fork dynamics explorer.
Starting with the three questions that matter most during a contested fork.
1. Is economic adoption above ~60%?
If not, the upgrading fork struggles regardless of mining support.
Monitor: exchange proof-of-reserves, institutional custody migration, ETF flow data.
2. Has a pool controlling >20% of global hashrate committed to the upgrading chain?
This determines whether that pool is economically trapped on the upgrading chain or ideologically committed, a distinction that can reverse outcomes at moderate economic adoption levels.
3. Is economic adoption above ~75%?
If so, pool ideology and commitment structure become irrelevant to outcome. Mining dynamics still determine how disruptive resolution is, but not which side wins.
https://image.nostr.build/2891c818c2f7910cac25e3334fcc2db70b33920aece2ca646349c97cd31261c8.png
These thresholds come from 1,385 fork scenarios on real bitcoind nodes. Three statistical methods converge on the same boundary.
Caveat: numbers are calibrated to current pool distribution and modeling assumptions, mechanisms are general, specific values are not universal.
Full decision boundary, presentation, and data: https://github.com/pfoytik/Bitcoin-Fork-Governance-Study
Interactive fork explorer (adjust sliders, see predicted outcome): https://pfoytik.github.io/fork-explorer/index.html

2026-07-08 17:58:29 UTC

There's a live debate right now about whether user node signaling is sufficient to carry a soft fork, whether the current picture resembles past successful activations.
It's the right question. Here's what the simulation found about what actually determines fork outcomes.
First, a clarification on scope: this research isn't about BIP110 specifically. It's about the general conditions that determine whether a contested soft fork succeeds, fails, or splits the chain. BIP110 is a timely reason to share it.
The clearest result from 2,694 scenarios: there's a threshold in economic adoption below which no mining support can carry a fork and above which miners can't stop it.
https://blossom.primal.net/5e0631b0d049e697f6c581168c35f8e76835df8c4f58cb6dcc09a064d35440d1.png
Result holds across the range of pool profitability assumptions tested. The contested zone is narrow.
Below that lower threshold, a fork fails regardless of mining support. Above the upper threshold, it succeeds regardless of mining resistance.
What sits between is where mining dynamics actually matter and where most current governance debates are happening.
As for whether user node signaling translates into the kind of economic adoption that moves that threshold, that's a separate question the simulation addresses directly.
Full answer at the UW Bitcoin Research Institute workshop, July 13–17.
#Bitcoin #UWBRI #softfork

2026-07-05 22:41:26 UTC

I'll be briefing the local meetup on some of the soft simulation results!
#nevent1q…h9v4

2026-07-05 20:05:55 UTC

One thing the simulation makes viscerally clear: a contested fork doesn't resolve gradually. It stalls... then it doesn't.
Here's what the timeline actually looks like across 2,694 scenarios.
https://image.nostr.build/3f9eb1b310fb58f2ac4dc829f0d62a03caa6a2aa06755d0ae1acc6f414121360.png
After the split, two chains run in parallel and when it breaks, it breaks fast. In the cascade scenarios, the decisive hashrate shift often happens within the first 500 blocks.. Profit-seeking pools drift toward whichever fork the price signal favors. Ideologically-committed pools hold their ground. For a stretch, it looks like a standoff, both chains viable, neither winning cleanly.
What the chart doesn't show is what breaks the standoff. One chain accumulates 2016 blocks first. Its difficulty adjusts sharply down, its blocks become far cheaper to mine. The profitability math flips for every pool still on the other side. Resolution happens fast.
The race that matters in a contested soft fork isn't block-by-block. It's who reaches the difficulty adjustment first. That single event is a cascade trigger and it's why most observable action happens in a compressed window once that threshold is crossed.
Three outcome shapes visible in the data: a clean win for one side, a cascade win for the other, and a contested equilibrium where neither chain breaks through.
General findings and useful frame for any contested fork. Full picture at UW BRI, July 13–17.
#Bitcoin #softfork #UWBRI

2026-07-04 18:15:03 UTC

A few people asked how the fork simulation actually works. The modeling choices matter, and I'd rather they be on the table before I start sharing results. Here's the short version...
A contested soft fork (one where a chain split occurs because there isn't agreement in the network) is a decision problem for the entities who run Bitcoin's infrastructure. So the model represents them as three classes of actor, using the stakeholder taxonomy from the Blockchain Consensus Analysis Protocol (BCAP) as a starting point.
https://github.com/bitcoin-cap/bcap
Economic nodes: exchanges, institutional custodians, payment processors, merchants: weighted by the BTC they hold or the volume they transact. Mining pools: weighted by hashrate, each with its own ideology and tolerance for losses. User nodes: retail operators running their own full nodes with some amount of custodied Bitcoin and option to have hashrate representing solo miners.
Each actor re-evaluates the same way: first the rational choice (which fork is worth more / which do I hold), then ideology (am I committed enough to eat a loss), then inertia (is the gap big enough to justify moving). One pipeline, applied independently by every actor.
Then we vary what we can't know in advance, how adoption splits, how committed the pools are, how much conviction each actor has across thousands of scenarios on real Bitcoind nodes using warnet and watch what the network does.
https://github.com/bitcoin-dev-project/warnet
Results coming this week. Full picture at UW BRI, July 13–17.
#softfork #Bitcoin #UWBRI

2026-07-01 17:34:34 UTC

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Watching the BIP110 debate, I keep seeing the same honest admission from people who know Bitcoin deeply: past forks only tell us so much about this one. It's different. We'll have to wait and see.
They're right that it's different. But "wait and see" isn't the only option.
It's not that the past teaches us nothing, we learn plenty from earlier forks. It's that the outcome doesn't transfer directly. We map 2017 onto today, and the mapping breaks: Different hashrate concentration, different custody landscape, different players.
@nprofile…vvhl and @nprofile…dzev made sharp points: technical people tend to treat user behavior as more predictable. I think that's right. So the goal here isn't to predict how users will act... it's to respond systematically to the fact that we don't know.
To be clear, this isn't guessing, it's testing. You take structured assumptions about how users might influence the system, run each one, and ask whether any of them actually moves the outcome. The assumptions are explicit and on the table, not baked in and hidden.
That's the gap simulation fills. Not a crystal ball, you can't predict what a new rule set gets used for. But whether a contested fork resolves cleanly or splits the chain is something you can study under today's conditions, while staying honest about what you don't know.
#nevent1q…d22z

2026-06-30 18:09:39 UTC

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Yes! I will be leaking out the findings as we get closer to the workshop :)

2026-06-30 16:56:52 UTC

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@nprofile…dzev recently made a careful argument about BIP110: Bitcoin is a dynamic system, and you can't know a soft fork's consequences in advance. "I don't know the consequences," he wrote, "and neither do you."
He's right about the uncertainty and the limits of prediction. But there's a third option worth considering.
The choice isn't only between *knowing* an outcome (hubris) and *not knowing* it (watch and learn). For one specific question, will a contested fork succeed, fail, or split the chain? deep uncertainty doesn't mean zero information.
You can't predict a dynamic system's full trajectory. But you can bound it. You can map which conditions push a contested fork toward a clean win, which push it toward a sustained split, and where the boundary between them sits. https://blossom.primal.net/813b90bd5824dbe0f9c376cfccf9ec01576e7f2d23105ba2d3840b1dea4e758d.png
That's what simulation is for. We ran 2,694 contested-fork scenarios on real bitcoind nodes using Warnet with mining pools, exchanges, and users modeled as the actors BCAP (https://github.com/bitcoin-cap/bcap) defines, each making independent economic decisions to map exactly that boundary.
We don't claim to know whether BIP110 should activate. We claim something narrower: the success-or-failure of a contested fork isn't pure fog. It has structure, and that structure is measurable in advance.
Full methodology and findings at the University of Wyoming Bitcoin Research Institute workshop @nprofile…z73t , July 13–17. Thread to follow. https://github.com/pfoytik/Bitcoin-Fork-Governance-Study
Epistemic humility and quantitative analysis aren't opposites. You can hold both.
#nevent1q…gmzk