Quantova engagement report
@Quantovafnd - 277K followers on X
Measured over 11 original posts from a 30-day window, last computed on October 25, 2026.
Engagement
A typical post picks up 30 interactions against 277K followers, an engagement rate of 0.011%. Measured over 11 original posts, its engagement rate beats 24% of 20,444 tracked accounts of a similar size. That is a reason to look at how the audience behaves - reply depth, saves, whether the followers are recent - rather than a conclusion about it on its own. Posts are seen about 16K times each, and 0.191% of those impressions turn into an interaction. That is about 5.66% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.73 post a day over the last 30 days, though only 37% of days saw any activity at all. Most posts go out around 05:00 UTC, and Monday is the busiest day of the week. Of the 11 posts sampled, 73% carry an image or video and 36% link out. The account's strongest tracked post pulled 1.7K interactions, about 55x its own typical post.
Measured over 11 original posts from a 30-day window, last computed on October 25, 2026.
Compared with accounts its own size
Quantova's engagement rate beats 24% of the tracked X accounts closest to it in follower count (20,444 accounts, accounts of similar size (decile 9 of 10)). A percentile is spread evenly by construction, so 50 really is the middle of that group and 90 really is its top tenth.
On engagement per impression rather than per follower it beats 11% of the same group. When those two numbers disagree, the gap is about how far its posts travel rather than how people react to them.
Where this sits in the catalog
At 0.011%, Quantova sits above the 10th percentile of the 204,956 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.024%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.024% |
| 50th percentile | 0.143% |
| 75th percentile | 0.678% |
| 90th percentile | 2.55% |
| 99th percentile | 82.4% |
This ruler is the whole measured catalog, not a size-matched group: it shows where the raw rate falls across every account we can measure, all of which are large. For a like-for-like comparison, read the size-band percentile above instead. See how the bands are built
Posting timing
This account posts most often around 05:00 UTC, and Monday is its busiest day of the week. The bars below are the catalog-wide pattern, with this account's own busiest slot marked. They do not show how this account performs at each hour: we keep one aggregate per account, not one per hour, so that measurement does not exist in our data.
Show engagement by hour posted, utc as a table
| Hour (UTC) | Vs author median | Posts |
|---|---|---|
| 00:00 UTC | -1% | 89K |
| 01:00 UTC | -2% | 90K |
| 02:00 UTC | -3% | 88K |
| 03:00 UTC | -4% | 94K |
| 04:00 UTC | -5% | 76K |
| 05:00 UTC | -4% | 75K |
| 06:00 UTC | -5% | 86K |
| 07:00 UTC | -5% | 93K |
| 08:00 UTC | -4% | 108K |
| 09:00 UTC | -4% | 124K |
| 10:00 UTC | -3% | 129K |
| 11:00 UTC | -3% | 141K |
| 12:00 UTC | -3% | 154K |
| 13:00 UTC | -3% | 167K |
| 14:00 UTC | -4% | 173K |
| 15:00 UTC | -2% | 176K |
| 16:00 UTC | -3% | 171K |
| 17:00 UTC | -3% | 159K |
| 18:00 UTC | -2% | 149K |
| 19:00 UTC | -2% | 141K |
| 20:00 UTC | -1% | 131K |
| 21:00 UTC | 0% | 116K |
| 22:00 UTC | -2% | 100K |
| 23:00 UTC | -1% | 90K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +5% | 393K |
| Monday | +1% | 483K |
| Tuesday | -2% | 520K |
| Wednesday | -3% | 472K |
| Thursday | -2% | 430K |
| Friday | -3% | 447K |
| Saturday | +2% | 393K |
Formats this account uses
Its own posting mix on the left, and what each of those formats does across every account we track on the right. Only formats where the effect clears our publish test appear here, so an empty row is a format we could not measure rather than one that does nothing.
| Format | This account | Catalog effect | 95% interval | Accounts behind it |
|---|---|---|---|---|
| Image or video | 73% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 36% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 73% of this account's sampled posts carry an image or video. Across the catalog, posts with an image or video run 111% above the same accounts' other posts.
- 36% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts.
- Its average post runs 455 characters, which falls in the over 280 characters band. Across the catalog, posts over 280 characters run 15% above the same accounts' other posts.
These are catalog-wide differences applied to this account's own posting mix, not a measurement of how each format performs for this account specifically. We keep one median per account, not one per format per account, so the second thing is not something this data can tell you.
Best tweets
- Jul 28, 202655x their median
BREAKING: Anthropic's Claude Mythos just found a way to break post quantum encryption. Claude Mythos, Anthropic's most advanced AI model, cracked two different encryption systems. The first is a newer type of encryption designed to stay secure even against future quantum computers. Claude found a flaw that cuts its security in half, meaning it's now twice as easy to break as experts thought. The second is the encryption standard used to protect most everyday internet traffic, things like your email, banking, and browsing. When researchers first asked Claude to attack the second system, it refused, saying the task was basically impossible and that nothing new could be found. Researchers pushed back and told it to keep trying. Over the next three days, working almost entirely on its own, Claude generated hundreds of millions of words of analysis and eventually discovered the winning method on its own. Both of these were done on test versions built specifically to study weaknesses, not the real systems actually protecting your data today. So nothing you use right now is at risk. Each of these discoveries cost Anthropic roughly $100,000 in computing costs to produce.
- Jul 24, 202618x their median
I'm happy to see the unclonable encryption problem solved; Prabhanjan Ananth and Amit Sahai report their findings, with the help of the UCLA harness (link below). This was a challenge for the quantum crypto community for the last 6 years.
- Oct 17, 202610x their median
The core step of a quantum attack on Bitcoin and Ethereum now fits in under 900 logical qubits within Google's gate budget. In three published attack designs, the machine would shrink by zero to about 28%. On October 13, Jieyi Long of Theta Labs posted an 893-qubit circuit to ECDSA Fail, an open benchmark for the point addition that Shor's algorithm repeats to recover a private key. A day later he posted an 874-qubit version. Both stay below the 1,175 qubits and 2.7 million Toffoli gates Google proved for its own circuit in March. Narrower circuits exist, down to 676 qubits, but all of them exceed Google's gate count. The 676-qubit one needs about 150 times as many. Pierre-Luc Dallaire-Demers, a co-author of the ECDSA Fail paper, put the physical saving at 25% for the IonQ, Oratomic and Google attack designs. I checked each one. - Google: about a quarter, if every part of the machine shrank with the qubit count. - Oratomic: nothing with its published codes, and at most 16% with a code sized for 893 qubits. - IonQ: about 28% fewer ions, but longer attempts, because the circuit needs about 1.6 times IonQ's Toffoli gates per addition. Nobody has compiled a full attack around either circuit yet. https://t.co/KBkyqpaknc #QuantumComputing #PostQuantumCryptography #PQC #QuantumSecurity #Cryptography #Bitcoin #Ethereum #Cybersecurity
- Jul 4, 20267.7x their median
Quantum security is starting to move from theory into actual infrastructure planning across crypto. Over the past few months, several major players have stepped up their post-quantum plans, as governments, tech companies and blockchain ecosystems prepare for a future where today's cryptography may no longer be enough. The shift is not about panic. It is more about timing. A few highlights: * Algorand has outlined a roadmap to make its network broadly quantum-resistant * Ethereum has been expanding its post-quantum research and future-proofing work * Google is targeting a 2029 timeline for parts of its post-quantum migration * NIST has already finalized key post-quantum encryption standards * Governments are beginning to treat quantum-safe migration as a national security priority The main point is that moving a live blockchain to quantum-resistant cryptography is not something that can happen overnight. Wallets, validators, signatures, smart contracts and core protocol infrastructure may all need changes over time. That is why more networks are starting the discussion before quantum computers become an immediate threat. For crypto, the next security cycle may be less about reacting to hacks after they happen and more about building systems that can survive the next generation of computing.
- Aug 10, 20267.4x their median
A major result in post-quantum cryptography. A key security assumption behind Classic McEliece, a public-key encryption system considered to resist quantum computers, has been undermined. Researchers found a provable quasipolynomial-time method for detecting the hidden mathematical structure in its public keys. The attack is still astronomically expensive and cannot yet decrypt messages, but this is a serious weakening of one of the oldest post-quantum cryptosystems. McEliece is not broken practically today, but an important assumption underlying its theoretical security has been broken. For the Classic McEliece parameter sets, the estimated cost of the best known structural distinguisher drops from roughly 2^298-2^691 operations to about 2^114-2^124. That is huge. https://t.co/b5RMDiaCcM
- Jul 20, 20266.5x their median
Interesting work on low-space quantum elliptic curve point addition: https://t.co/AddkJ0Mx3Z I knew ~800 qubits for n=256 was doable, but I expected like 100x more Toffolis than they achieved. And that's despite them wasting a lot of Toffolis by using non-approximate circuits!
- Sep 28, 20264.3x their median
⚛️I still read that only ~30% of bitcoin would be at risk from a quantum computer, because the other ~70% sits behind a hash of the public key. This is a very bad argument for two independent reasons. Glassnode's May figure is real: 30.2% of issued supply already has its spending public key on-chain. The rest does not, at rest. That measures the chain. Secrecy is a different property. 1️⃣A public key is supposed to be public. ECDSA was not built to hide it, and neither were wallets. If the key is absent from the UTXO set, it can still sit in an xpub, on your computer, a PSBT, a log, a backend DB, an RPC node, or a backup... 2️⃣ The hash also ends at the exact moment you spend. Moving the coins publishes the public key in the mempool, and until miners include the transaction, anyone who can derive the private key can fee-replace you. Bitcoin's mean block interval is 10 minutes. (And 10 minutes is not even TX finality.) In March, Google Quantum AI estimated Shor on secp256k1 at about 9 minutes from a primed state, on a fast-clock machine that does not exist yet. Half of the computation depends only on secp256k1, not on your public key. An attacker can run it in advance, then wait for your transaction. Once your public key appears, only the remaining ~9 minutes are needed. In their model the chance of taking that spend is just under 41%, and a few minutes less, or a handful of primed machines, makes it worse. And you should expect this result to be greatly improved in the near future. Hashing public keys is not a mitigation. The only solution is the Post Quantum Cryptography migration. Stay safe. Stay honest about your trust assumptions.
- Jul 9, 20263.7x their median
Why we cannot wait for better post-quantum signature algorithms: ML-DSA will have to do. But searching for better is still important! https://t.co/hHG81Fxk89
- Oct 17, 20262.1x their median
Most of crypto spent @token2049 talking about the next cycle. We spent it on the next threat. @Quantovafnd in Singapore. Built for the day quantum computers arrive https://t.co/O2hfxCErIA
- Aug 6, 20261.6x their median
1/ Making a blockchain post quantum is not one change. It is at least five, and missing any one leaves a hole. Quantova made all five 🧵 https://t.co/2r3qYy2IHo
Ranked by total interactions across everything we have tracked for this account, which is a longer history than the 30-day window the rates above use. The multiple compares each post to this account's own median.
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Reading these numbers
A typical post picks up 30 interactions against 277K followers, an engagement rate of 0.011%. Measured over 11 original posts, its engagement rate beats 24% of 20,444 tracked accounts of a similar size. That is a reason to look at how the audience behaves - reply depth, saves, whether the followers are recent - rather than a conclusion about it on its own. Posts are seen about 16K times each, and 0.191% of those impressions turn into an interaction. That is about 5.66% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.73 post a day over the last 30 days, though only 37% of days saw any activity at all. Most posts go out around 05:00 UTC, and Monday is the busiest day of the week. Of the 11 posts sampled, 73% carry an image or video and 36% link out. The account's strongest tracked post pulled 1.7K interactions, about 55x its own typical post.
- What is Quantova's engagement rate on X?
- Quantova (@Quantovafnd) has an engagement rate of 0.011%, based on the median interactions across 11 original posts from the last 30 days against 276,962 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.011%, Quantova sits above the 10th percentile of the 204,956 accounts in this comparison. Those comparison accounts are all large ones, because our scanning cadence is weighted towards big accounts, so this is a ranking among peers of similar scale rather than a ranking across X.
- Does @Quantovafnd have real engagement?
- Its engagement rate beats 24% of the tracked X accounts closest to it in follower count (20,444 accounts), which puts it in the bottom quarter for its size group. Ranking inside a size band matters because engagement rate falls as accounts grow, so a raw rate would mostly re-measure the follower count. It is a starting point for a look at follower quality, not a verdict on it.
- When does @Quantovafnd post?
- Most posts go out around 05:00 UTC, and Monday is its busiest day, at roughly 0.73 posts per day across the measured window.