When you introduce yourself, don’t through your name out a mumbled string of syllables. It is difficult for those whose culture is not the same as yours to catch your first and last name (or others).
Say: My name is (short pause) <firstname> (one second pause) <lastname>.
It will be more memorable for everyone.
I am quite bad at remembering people’s names. A trick to help yourself is to use the name immediately in the first sentence you speak to them after they introduce themselves. “So Francis, what do you think about X?”.
I usually need to get to know a person first and build up some mental image of a person. That helps the person stick in my memory. That will be quite a bit later than when the time of exchanging names. However, I find usually people are not so offended if you say an hour or a day later: “Remind me, what was your name again?” It seems more important that you try.
Resources
Here is the video where I got the “say your name” from:
And two more videos on speaking clearly and slowly:
You can also undermine your communication by having a poor or uncalibrated microphone in telecon (Zoom) sessions. Test it occasionally by connecting both your phone and your laptop to the same session. Use headphones to listen from one device how the microphone picks up your audio. A laggy video, a oversteered or rough audio is similar to poor choice of dressing at the work place – it makes you look like a person who does not care how they appear to others. A crisp sound makes you appear more professional.
Co-authorship and acknowledgement are forms of recognition for direct contributions to a work. I want to elaborate on the policy I follow, influenced by the groups were I have worked.
There are multiple aspects of how to contribute to a paper: “conceiving the idea, designing the study/experiment, collecting the data, analysing the data, writing the manuscript”.
Acknowledging experiment design in astronomy
It is sort of obvious that you should offer co-authorship to someone who gave you the idea for the study you are executing. Unfortunately, there are people in astrophysics who take data and ideas from others without credit. One second-hand horror story from decades ago is that a young postdoc was giving a presentation in CalTech about an idea to observe M-dwarf spectra for the first time, and laying out a strategy to achieve it. During question time, a senior researcher said: “That’s a great idea! I’m gonna do that.” Another second-hand horror story is that a member of the NICER instrument team used his privileged position to monitored ad-hoc transient observing proposals (where the data go public immediately) and scooped people’s work. This became so bad that in transient conferences, people would hide their source coordinates; yet the person once went up to a speaker saying “Don’t think that just because you hide the coordinates I can’t find your source.”. We must not let these behaviours proliferate. Do not hire these people.
It is less obvious how to credit someone who enabled the data sets that your study builds upon.
At the start of my career I have underestimated the effort people put in writing observing proposals. This experiment design work is crucial and enables scientific studies. So if the data is public, it is professional to ask the PI of the observing proposal, if they have not published a paper on the observations yet, whether they would like to be co-authors. This would probably not apply if it has been more than 2-3 years since the data were taken, but funding issues, or a PhD student dropping out can delay data exploitation significantly. If you know the PI, you should always ask.
I do a lot of work on relatively old, archival observations, and that there is freely available, well-calibrated data is one of the best things of astronomy. I have acknowledged these effort with extensive citations. Here are two examples: (1) In a huge archival study of 900 gamma-ray bursts discovered by Swift, I cited over 165 Astronomer Telegrams, because they contain follow-up observations and key quantities like redshifts. (2) In a recent SED fitting paper analysing data from ultraviolet to infrared based on spectroscopically identified quasars, I spent 1.5 pages acknowledging the server infrastructure and all the surveys:
Acknowledging project-specific contributions
There are nice guidelines by some journals, that I agree with. Unfortunately, there does not seem to be a astronomy journal giving co-authorship guidelines, or at least I have not seen it.
My favorite guideline write-up is by the medical journal ICMJE, but the recommendations from Springer Nature are also similar):
Co-authorship requires:
Substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work; AND
Drafting the work or reviewing it critically for important intellectual content; AND
Final approval of the version to be published; AND
Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
The forth point means, that a co-author should be able to defend the paper in a conference discussion, when someone says the study is garbage. If they don’t want to have their name on it, don’t have your name on it.
The third point implies you need to get the okay of the person to submit it with their name on it, and indeed you absolutely cannot submit a paper to a journal with people’s names without them agreeing to be co-authors. So if you are not careful, you can end up in a difficult limbo, where you have put a person’s name on the co-author list, shared drafts, they never reply, and now you cannot submit. People in permanent positions can keep you, without a permanent position, in this state forever. That’s why, in my opinion, you should never put people’s name into the co-authors list in drafts before they have sent you comments, and thereby implicitly or explicitly saying they would like to be coauthors. That is, I believe in a opt-in co-authorship policy, rather than a opt-out policy, because it avoids the stalemate. It creates an incentive to say yes and send comments.
For the second point, drafting the paper, you can help me a lot. Pointing out relevant papers to cite is a crucial contributions – literature review is a lot of work if you have the ambition to be thorough. Going beyond criticising text and providing improved text blocks is a crucial contribution for someone like me who has a hard time writing. I’m gonna love having you as a co-author if you do these, even if you did not touch the data or were in any discussion meetings.
Regarding the first point: Indirect contributions, such as holding workshops, making software and tutorials publicly available, are not part of acknowledgements or co-authorship. Maintaining the IT infrastructure of the institute is important to enable this and other project, but part of the affiliation as an implicit acknowledgement. Project-specific scientific software support that enables smooth project completion should be acknowledged. You can be as generous as you want in the acknowledgements! There is no cost and it only helps generate good will. Acknowledge reviewers, hallway discussions and encouragements. Custom code development enabling the project should count towards co-authorship.
Managing expectations: be upfront about your policy
You do not have to agree with my co-author ship policy, and I do not expect you to have my policy. But: be up-front about what your policy is. What threshold do you apply for co-authorship?
This can avoid frustration and conflicts by being upfront. I had two collaborations where I spent time in many meetings discussing the paper data analysis and interpretation, providing references from a literature review, and thought that I would be a co-author but the first author did not. Both cases were first authors from (astro)particle physics – I learned that they have a much higher threshold for co-authorship.
Personally, I think that is dumb: There is essentially no cost to including someone as a co-author. It is encouraging to continue collaborating. Can you imagine my excitement when I was included into the list of contributors to the VLC project? I became and remain a hard-core fan of the project. So err on the side of generosity. I realise, however, that telling people to be generous is futile; you can only grow the feeling of generosity by experiencing wealth, kindness and generosity from others setting an example. The counterargument that <=3 authors allows all to be named in the citation is, to be frank, pathetic.
In my most recent paper, I copied the ICMJE guidelines into the latex/overleaf as comments just above the co-author list, to be upfront. I kept a list of co-author names and their substantial contributions, but commented out until they gave comments.
Confidence in interview settings. I try too much to please people and say what I think they want to hear. I should instead be clear what I stand for and what I don’t, and argue clearly. It should not be that easy to rattle me.
Expressing my value clearly. Here there is something I don’t understand. Obviously my work has immense value, as seen by citations, invitation to give talks, and in almost every conference I meet someone who thanks me for my work. On the other hand, it does not seem to translate to the bottom line of a physics department?
Expressing my long-term vision clearly. I need to more clearly articulate how my approach differentiates from other’s use of AI and data science, and the long-term perspectives. I have to express this with high level language and not be too excited about explaining technical details.
Accepted funding proposals for a track record of self-sufficiency. However, two interview panels gave me feedback that they are not worried, and that I would be able to acquire sustained funding once hired.
Prizes and awards. I am not a fan of accolades and do not even want to think about being on a stage receiving an award. That said, it is a way for the community to recognize a person. The approach of encouraging others to suggest me for an award is really against my nature.
Handling rejections. Part of writing funding proposals or applying for a position is getting excited about the prospect, seeing opportunities, which vanish with a rejection letter, no matter how politely it is formulated. I should take it better, as a positive that I tried and put myself out there, and grow a thicker skin. I think I am improving on this already.
Exponential growth is unintuitive. The default heuristics of our brains is that things will continue as they are, or keep growing linearly.
In the most intense phases of COVID19, exponential growth of case numbers, and thus hospitalizations, and the trigger-happy reaction needed to stop this exponential growth curve early was understood by most people.
In the case of climate change, there is a similar phenomenon. We consider the warming curve of 0.x degrees per year, and it seems linear. However, the number of extreme heat days, and the number of extreme weather phenomena, are the tail end of a distribution that is widening. Their numbers is growing exponentially, and with it the cost, both monetary, of human lives, and life quality – the fraction of the year where it is safe to go outside into nature may shrink.
It is easy to become blackpilled and say it is all pointless because there is too little political will and action. Exponential climate change damage is extremely bad. Have a look at the details and compare the +2° +3°, +4°, +5°, +6° scenarios in the IPCC report (2023, 2014).
But there is a uplifting, positive side for exponentially bad impact.
Small actions, including and especially in the later stages past +2° warming, have a huge benefit in avoiding an even worse outcome.
Conflicts are common place when working in scientific collaborations, and with people in general, whether in private or professional settings. Be it, that others take undue credit, screw someone’s plans over, belittle contributions, are confrontational and rude, or mock someone.
Conflicts are stressful. Disappointment, anger, frustration, fear, insecurity, are intense emotions that can arise.
My gut reaction when conflicts arise — affecting me or someone else — is to avoid engaging with the conflict and hope it resolves itself. The trouble is, behaviours do not magically resolve themselves but perpetuate when left alone. The issue becomes bigger, frustration becomes bitterness, and, handling the situation is more difficult, if not impossible.
My learning over the years has been that I should do the exact opposite of what my gut tells me: When I feel there is a social uncertainty or something off, immediately communicate about it. Say “This feels off to me, what do you think?”. I find people are happy to adjust and see the point if the issue is still small!
My challenge is usually that I might not have the right words to express issues clearly. But it is more important to have the right intentions than the right word.
A senior colleague of mine once said (paraphrasing):
“We can all manage to fill our week with things to do. It is not difficult to be busy. The challenge is to actively and consciously steer what you decide to spend our time on, and prioritize things that will have an impact.”
When you look back on the last week or two, have you spent the week on something that you are proud of? Something that positions you better for your future?
Busy work
The possibilities what to work on are endless (write observing proposals, write funding proposals, attend or organise conferences, read papers, advise students, collaboration policies, help prepare data for someone, give comments on papers, create press releases, give outreach talks, etc etc etc). Busy work creeps up over time. What you stepped up for once, you feel responsible to keep doing.
You will even feel productive and helpful when filling your work week with such items.
Tasks seem urgent. You may discover things needed immediately by other work. But you will not discover what no one has thought of. If you do not schedule time to stop and think, being creative about scientific ideas and thinking critically is difficult.
You start to feel like you are missing out on progress. You feel like you are getting dumber while young colleagues get science done.
But it is not true. Firstly, research shows that people do not become dumber quickly, with work performance peaking at about 55 years. But juggling more mental items can feel like walking through jam.
Advice and techniques (for myself)
One technique that I could use more is to create four quadrants for tasks:
urgent & important
urgent & not important
not urgent & important
not urgent & not important
Then prioritize important tasks.
When you are in charge of administrative tasks, there is a power imbalance. The other person needs some approval from you, whether this is a travel request or a pull request of code. But they are probably highly motivated and for them it is both urgent and important. One technique, that I have found is satisfying for both sides, is to offload much of your administrative work to the requester. To do this effectively and without being a nuisance, it is best to make the requirements for successful approval transparent upfront. But you can require them to make one iteration of improvements, ideally only one.
As I become more senior, I have become more aware of other scientific sub-areas and people working on them. Tracking this larger and larger scope is mentally taxing, regardless of whether out of interest or out of a feeling of competition.
More knowledge and a wider field of view helps anticipate hurdles down the road earlier, and thus spend more time planning projects in your head. This may feel like hesitation and slow progress. But it is actually active work on experiment and project design and increases the likelihood to deliver on time and the scientific impact.
I have learned one lesson in one sport, which I have found to be universally applicable to most other sports.
The lesson is as follows:
Imagine your shoulder points and your hips forming a rectangle. This rectangle needs to be mobile. Start any action by moving that rectangle. Not flailing the arms and legs. Move that rectangle and be agile.
Being quick and active with your hips, and engaging with your core is also a lesson I have learned in jiujitsu. I have found it applicable in:
table tennis
volleyball
basketball
snowboarding
windsurfing
martial arts
and bringing it up to others, they have confirmed it also for tennis.
🗹 get a paper published 🗹 get a paper rejected ☐ publish a letter 🗹 publish a research note 🗹 publish in A&A 🗹 publish in ApJ 🗹 publish in MNRAS 🗹 publish in PASP 🗹 publish a software package 🗹 publish a catalogue to vizier 🗹 play ArXiV astro-ph localtime roulette 🗹 referee a paper 🗹 discover a new observational relation 🗹 publish analysis of cosmological simulations 🗹 do a population study 🗹 have a observing proposal accepted 🗹 have a observing proposal rejected 🗹 have a TOO proposal accepted 🗹 have a DDT proposal accepted 🗹 have a funding proposal accepted 🗹 have a funding proposal rejected ☐ have a funding proposal for students or postdocs accepted 🗹 supervise student BSc thesis 🗹 supervise student MSc thesis ☐ supervise student PhD thesis 🗹 do observations in optical 🗹 do observations in radio 🗹 do observations in X-rays 🗹 work for NASA have NASA work for you 🗹 single-sentence abstract 🗹 give a conference talk 🗹 give a colloquium
How do people get emotionally attached to software?
I mean positively emotionally attached to the point of plastering stickers on their laptop, or negatively attached to the level of raising their voices in discussions.
Here I explore a few causes that I have seen.
1. Attachment to strict teachers
This cause of attachment is common with compilers (Rust, Stan) and program provers. They nitpick and force you into a lane. After significant investment and boxing your problem into the right shape, they are given the green light like a priest giving you a blessing. You are now a member.
The harsher the teacher, the more rigorous the trial, the more attached is the feeling of belonging to an elite club of survivors.
2. Attachment to what you have spent building
Just spending a lot of time building something causes you to be attached to it. Firstly, design decisions can be personal expressions. Secondly, after spending many long nights or even months working on it, there is a sunken cost. It’s hard to consider that you have “wasted” your time. If someone tells you, “why don’t you use tool Y”, you’d laugh it off, not even trying to learn tool Y because you understand your imperfect work of love.
A more open minded point of view is to think of the “sunken cost” as an investment to deeply understand the challenges in that domain. Even if the developer drops the tool and switches over to something else, they now know the concepts and challenges deeply, at an expert level.
Unconvincing value propositions
Building new software is fun! Because of the two points above, the author is likely to proselytize around, trying to convert people to their great tool.
The expressed value propositions can harbor a communication mismatch: The inside view of the developer is not the outsider view. Their values of “it is well understood” and “easy to change” do not translate to the next person who has not edited the software yet. Likely, the outsider has also seen a few people proselytize, and then the difference in value may be difficult to see.
Work without impact to science
Every week there are papers on arXiv where someone invested months of work on a new data analysis technique and finally finds that it does not outperform the classic benchmark.
Sometimes this is stated outright. I think it is great science to try something new. But there are other cases.
Sometimes the benchmark is a setting unlike how the analysis will be applied in the future (for example: complete data, spectroscopic redshifts, known noise), or the benchmark statistic is non-standard to the field. In any case, whether the new technique is better or worse, the abstract invariable ends with “And therefore, our technique is a promising platform for future data sets.”
It is disheartening to think of the many person months wasted, because people did not think longer about what they should optimize for.
Personal reflection
I think I also suffer from some sunken cost w.r.t. nested sampling. It is quite addictive for me to think about algorithm variations.
That “no one uses my software” is not a problem I have though. What keeps me grounded is seeing a clear need in conference and hallway dialogs, combined with critical thinking to crystallize out what the core question is.
What is the shape and location of the hot X-ray corona? We know it is compact (<10Rg, from microlensing) and parallel to the disc (from polarimetry). But how is it powered? In practical terms: what sets the LUV-LX relation? The relation can be reproduced with AGNSED models, but this requires the corona to change with the accretion rate. What is causing this? Why is the dependence with luminosity and not Eddington ratio, which is different to all other dependencies?
What is the shape and location of the “soft excess”? Is it the Comptonized disc? Why does the Comptonization radius depend on Eddington ratio but not luminosity?
How much central engine diversity is there, or do fundamental parameters (MBH, lam_edd) set the geometry? Broad line variability studies suggest there is geometric diversity.
What sets the LMIR-LX relation? Why do the X-rays become relatively X-ary weak at high luminosities? Why is there a tight relation to 6µm and 12µm instead of vast scatter? Is it because whenever the AGN is on, there is likely dust nearby?
Are all bolometric corrections Eddington-ratio dependent? Does the LUV-LX relation bend over at high luminosities? The LMIR-LX does, so it would make sense if the LUV-LX does as well. How does the fundamental plane of black hole activity (LX-Lrad-MBH) play along here?
What causes the covering factor to change with Eddington ratio, and why does this happen at different redshifts at different Eddington ratios? If the Eddington limit, modified to account for dust instead of just electron scattering, shapes the nuclear region (how exactly is it regulated? what is its shape? what is its distance?), then it is puzzling why this nuclear process should be limited differently at different redshifts. I suspect that instead, the regulation of the Eddington limit is due to the availability of gas, setting both covering factor and luminosity distribution. Like a small gas tank on a car with exponential hunger over time, the gas is unlikely to be full when power is at the maximum.
To think a bit more systematically, here are the eleven components:
Black hole – MBH, lam_edd
Hot corona
Warm corona
Accretion disc
BLR
Hot dust
Cold torus
Outflows (UFO, atomic, ionised, molecular)
Nuclear attenuation
Host stellar potential
Galaxy attenuation
Host star formation
1 is related to everything <8 by the Eddington ratio being important.
4 is related to everything as a power source.
are 2&3 related? lags perhaps suggest so.
5 may be influenced by 2&3 through over-ionisation.
6&7 is related to?
4 -> 8 -> 10 -> 12 is a key process, potentially with involvement of 3 and 9.
No funding agency cares about obscuration and the torus. Framing via fundamental black hole physics is essential.
Transients probe accretion processes in a unique way, but the fueling is different and may not be the same because of the magnetic field structure. How to stand out in 30 years of AGN research?
To test the empty fuel hypothesis, need SPHEREx + Euclid + eROSITA + SDSS-V.
To test geometry of corona, need eROSITA + SDSS-V.
To test co-evolution, need {eROSITA, NewAthena} + LS10 + Euclid + {SDSS-V,4MOST}.
