2 measurements taken within a single day. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 285–287 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
8 Aug 2026, 08:19
286
no change
7 Aug 2026, 13:08
286
first reading
Engagement
17 posts held, back to 21 October 2025 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.
ERR · 30 days
29.4%
avg views ÷ 286 subscribers
Avg views / post
84.0
1 post measured
Reaction rate
5.95%
reactions ÷ views · ER floor
Posts in window
1
of 17 held
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views— note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.
What these figures were computed from
Window
Rolling 30 days · latest post in window 24 July 2026
Posts held
17 (21 October 2025 – 24 July 2026)
Views total
84
Reactions total
5
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
8 Aug 2026, 08:19 UTC
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
What this channel posts
Photos
78
Videos
1
Links
89
Lifetime counters from Telegram’s own channel header, read 8 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
Reaction mix
79 reactions across 13 posts, in 8 distinct kinds. The most used accounts for 45.6% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
36
45.6%
❤
21
26.6%
👏
7
8.86%
🎉
5
6.33%
👍
3
3.80%
🤩
3
3.80%
🥰
3
3.80%
😁
1
1.27%
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 13 of the 17 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 79reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 17 most recent posts we hold, published 21 October 2025 to 24 July 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
Летняя школа Фонда «Интеллект» по ИИ продолжается: участники знакомятся с актуальными направлениями исследований, разбирают подходы к решению прикладных задач и обсуждают свои идеи с экспертами.
Вот что рассказал нам Бабкен Бегларян, аспирант химического факультета МГУ:
https://t.me/foundation_intellect/1558
Наши люди в Голливуде на летней школе Фонда Интеллект :)
🗓 Уважаемые коллеги!
Время летит быстро, и на горизонте замаячили майские хлопоты и «тяжелое» время у студентов, а значит, весенняя серия семинаров подходит к завершению. Надеюсь, что несмотря на вернувшуюся зиму, все здоровы и наполнены весенним настроением!
📍 Итак, финальное весеннее заседание состоится в ближайший понедельник 13.04 в 13:00 в аудитории 446 (ссылка Zoom по запросу).
Докладчик: к.ф.-м.н., н.с. Меш…
Коллеги!
Очередной семинар весеннего цикла 🌱пройдет в 446 аудитории 30.03 и онлайн (ссылка по запросу), в центре внимания — «астрономически важные» молекулы и их реакции, начало в 13.00.
студ. Полякова Анастасия Сергеевна
Изучение переходов в системе B1Π-X1Σ молекулы CaO по данным лазерно-индуцированной флуоресценции.
Исследование электронно-колебательно-вращательных (ровибронных) спектров молекулы CaO интересно о…
В конце февраля наши парни — Иван Крылов и Николай Сушков — отправились в солнечный Узбекистан, чтобы представить результаты своих исследований на Winter Symposium on Chemometrics🙏который в этом году прошёл уже в 15-й раз.
Поездка оказалась не только насыщенной научными обсуждениями, но и очень успешной. По итогам конференции Иван Крылов был удостоен приза за лучший устный доклад. В качестве награды Иван также получ…
📣 Дорогие коллеги!
Приглашаем вас на очередной семинар, который состоится в ближайший понедельник 16 марта в 13:00 (МСК) в аудитории 446, а также онлайн (ссылка по запросу). На этот раз мы вновь отправимся в увлекательное путешествие по миру космической пыли.
Доклад:
Моделирование состава льдов в протопланетных дисках со вспышками светимости 🪐
к.ф.-м.н., н.с. ИНАСАН Анастасия Павловна Топчиева
https://www.scopus.co…
Уважаемые коллеги!
Начинаем семестр с места в карьер 🏃 — уже в понедельник будем слушать первый доклад на нашем семинаре (совместно с межлабораторным семинаром «Структура и динамика атомно-молекулярных систем»).
🕒 15:00
📍 ауд. 446 (ссылка Zoom по запросу)
Докладчик:
к.ф.-м.н., в.н.с. AIRI
Ушенин Константин Сергеевич
https://www.scopus.com/authid/detail.uri?authorId=57024124800
Тема:
LAGNet — предсказание электрон…
Дорогие коллеги!
Немного потеплело, солнце светит уже совсем по-весеннему — самое время объявить весеннюю серию нашего семинара. Надеюсь, простуды обошли всех стороной и настроение у всех бодрое и рабочее 🙂
Где и когда встречаемся:
📍 ауд. 446 и онлайн (ссылка по запросу)
🗓 16.02, 02.03, 16.03, 30.03, 13.04
⚠️ Обратите внимание:
— заседание 16.02 проходит совместно с межлабораторным семинаром
«Структура и динамика …
Поздравляем нашего коллегу - Александра Закускина!
🎆🎆🎆
Стипендия МГУ 📢
#новостихимфакмгу
Стипендии Московского государственного университета имени М.В.Ломоносова молодым сотрудникам, аспирантам и студентам, добившимся значительных результатов в педагогической и научно-исследовательской деятельности на 2026 год в номинации Химические науки присуждены:
https://t.me/chemistryofmsu/7628
Уважаемые коллеги!
Завершающее 2025 год (нейросетевое) заседание семинара пройдет в 446 аудитории (ссылка Zoom по запросу) в ближайшую среду 17.12 в 12.30 МСК. Будем рады видеть всех очно или онлайн!
асп. 4 г.о. Рылов Александр Валерьевич
Нейросетевая модель для предсказания состава и параметров плазмы на основании спектральных данных
Наиболее известный подход к определению состава плазмы без использования образц…
🔥2
Showing the 12 most recent of 17 posts we hold for @laser_lab_MSU. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Forward network
Republishes
Channels on the register whose posts this channel has forwarded.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Mentions
Names
Channels on the register whose handles appear in this channel's posts.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
Handles this channel named that no longer answer
Dead references
1
handles named in this channel’s posts, vacant today
Evidenced gone
0
we ourselves saw one of these resolve, at some point
Never seen alive
1
vacant every time we have ever looked
@laser_lab_MSU named 1 handle that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all.A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
@rtnews named in 1 post, 9 August 2026 – 9 August 2026
Cite this entry
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 8 August 2026 — this
entry's latest reading, not the date you are reading this.
“@laser_lab_MSU” (@laser_lab_MSU), 286 subscribers as measured 8 August 2026. Telegram Register, tgregister.com/channel/laser_lab_MSU.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.