For a public outreach talk I wanted to start with the importance of the Cosmic Microwave Background (CMB) for our understanding of the evolution of the universe. Then I remembered this anecdote that you can “see” the CMB radiation in the noise of your analog TV (if you still have one) and started wondering if that is actually true…
On the web there are several sources claiming that 1% of the noise between the channels of your TV programme are CMB, but I couldn’t find any actual calculation. So I tried my own.
Since I’m not an antenna expert and couldn’t immediately find some meaningful numbers for the radiation for analog terrestrial TV, I used this to come up with an order of magnitude number:
The old analog sender on top of mount Wendelstein in Upper Bavaria radiated at 0.4 kW in channel 48 according to the Wikipedia page. Channel 48 is at about 680 MHz and has a bandwidth of about 8 Mhz. This sender was apparently only used to broadcast to Bayrischzell which is about 2 km away. The sender had a round radiation pattern, i.e. it radiated in all directions, but only in one plane. However, since the town of Bayrischzell has a finite length, the half-power beam-width cannot have been too small. I assume here an H/R of ~ 0.2, i.e. at 2 km distance the half-power beam-width should be ~ 400m (i.e. illuminating an area of 5e6 m^2 at that distance). This is of course only a crude estimate, but for an order of magnitude calculation it should be OK. The specific flux received in Bayrischzell from this sender is thus
0.4 kW / (5e6 m^2 * 8e6 Hz) = 1e-11 W(m^2 Hz) or about 1e15 Jansky (in radio astronomers’ units)
OK, now let’s look at the specific flux of the CMB. This is easy, we just need to substitute proper values (2.7 K, 680 MHz) in the Planck equation and arrive at a specific flux of about 5.4e5 Jansky at the frequency used for the local TV station.
Now we need to compare this not to the signal strength estimated above, but to the estimated noise level of a typical analog TV receiver system. This is a bit tricky, but typical carrier-to-noise ratios (CNR) should be of some help. The carrier-to-noise ratio is the signal-to-noise ratio of a modulated signal. I didn’t find any recommended CNR values for terrestrial analog TV, but other CNR values for TV might give some guidance. In an article published with the Society of Cable Telecommunications Engineers, this guidance is given:
The FCC’s minimum CNR is 43 dB, which, in my opinion, is nowhere near good enough in today’s competitive environment. Indeed, most cable operators have company specs for end-of- line CNR somewhere in the mid to high 40s, typically 46 to 49 dB.
The National Association of Broadcasters Engineering Handbook (p. 1755) has a similar statement:
Noise will become apparent in pictures as the carrier-to-noise ratio (CNR) approaches 43-44 dB […]; a good design target is 48-50 dB.
So let’s assume the sender on mount Wendelstein is calibrated such that is achieves a CNR of 50 dB for the terrestrial analog broadcasting of the local TV station in nearby Bayrischzell. This means the signal is a factor 100,000 (1e5) stronger than the noise.
In this case, the noise level in the TV is about 1e10 Jy or about 200.000 times larger than the CMB signal. So, if this calculation is correct, it seems unlikely that you would be able to see the CMB signal while searching for signal with your analog terrestrial TV.
Recently my iPhone had fallen on the street and the sapphire protection glas of the iSight camera cracked. Pictures could still be taken and they looked OK, but stark contrasts would lead to artefacts. Also, the aluminium shell of the phone got a few bruises. A few days later I received a notice that my iPhone 6 Plus was part of a replacement programme. Now that’s lucky given the circumstances…
On 5 Feb, I went to the Apple store in the Munich Olympia-Einkaufszentrum (OEZ) to get the camera replaced. When they tested the iPhone, however, they found that my camera was actually OK and would not need replacement. But after showing them the cracked sapphire glas and the bruises on the shell, they agreed to swap — not just the camera — but the entire phone by a new one! I was really surprised by this level of service.
Mysterious heavy use of mobile data in “System Services > Documents & Sync”
After restoring the backup I made just before leaving to the OEZ, my brand-new iPhone behaved very much like the old one and all data had been restored, too. After some time, however, I noticed that it was losing battery very quickly. I checked the usual culprits and found that, indeed, the phone was using lots of mobile data. Turning off mobile data showed that the phone had a healthy battery.
But the mobile data issue didn’t go away. I deactivated WiFi support and other known possibly problematic features. Eventually I deactivated iCloud documents and iCloud altogether, but the problem persisted: the phone was using up lots of mobile data — and almost all of it in “System Services > Documents & Sync”. I could almost watch it use up my mobile data quota as it was sucking (or pushing?) about one Megabyte for every two minutes or so.
I called Apple Service and they told me to reset my iPhone completely and set it up as a new one. Since I didn’t find time to do that immediately, I simply switched off mobile data for the time being and activated it only from time to time when I needed mobile internet access. At some point this started to annoy me sufficiently so that I wanted to tackle the problem again and so I activated mobile data again yesterday just to find that the problem had miraculously disappeared. With the same settings as before, the iPhone was now behaving as it should using less than 1 Megabyte in 3 hours or so for “Documents & Sync”.
I can only speculate as to the origin of the problem and why it has solved itself. Perhaps the iCloud sync was somehow confused by the phone swap and somehow ended up in an endless loop of syncing the phone to the cloud and vice versa and again? And then at some point a cleanup daemon deleted old sync files on Apple’s servers so that it now works again? I will probably never now.
The lesson I learned from this incident is, however, that it’s not always worth trying to solve a (minor) problem immediately since it may solve itself as time passes. 🙂
Since more than two years now I was using my Raspberry Pi B+ as an owncloud-Server. Triggered by the various spy scandals and fascinated by the possibilities of this small and efficient computer, I wanted to see if it is possible to use comfortable cloud services while also having control over my data (it is). I enjoy my private owncloud for keeping notes up-to-date across my devices, but also for sharing pictures and files with family and friends. The client connection was always pretty fast and since I recently upgraded my home internet connection to V-DSL with 100 MBit/s (upload 10 MBit/s), upload speed is no longer a big issue. However, the PHP web interface was always relatively slow on my old Raspy model B+ and so I invested in a new Raspy 2 to see if that would improve the speed. This new Raspy features a four-core ARM Cortex–A7 processor @ 900 MHz with 1 GB of fast RAM: Quite an improvement over my Raspy B+ with a single-core 700 MHz processor with 512 MB of RAM. I was hoping for a significant boost for the owncloud performance since the Apache server forks into many processes even for a single connection and should thus be able to make use of the new Raspyb’s multi-core CPU. And I was not disappointed!
There are long discussions about which is the best or “right” way to install Python, but in case you just want to use it, here are the only two lines of code you need to enter in a terminal on your Mac to install a working Python environment with the latest Python 3.x including the packages numpy, scipy, astropy and iPython (among many other things).
- Install Homebrew:
ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
- Install the latest Python 3.x and relevant packages:
brew install python3
And that’s it. You can now start using Python by typing
This will launch an interactive Python shell (which allows you to use tab-completion among many other neat things).
Recently I submitted another paper to astro-ph and I wanted to play the “first” game and try to get my paper on top of the daily listing. Now, it is well documented that the deadline for the daily submissions is 16.00 EST meaning that if you submit just after that deadline you’re paper is likely to appear on top of the next day’s mailing. (NB: the announcement is inverse on the web page)
But how likely do you get your paper on top if you submit right in time? For the above mentioned paper I had prepared everything before hand. This took a bit of time since arxiv.org didn’t accept a
after the abstract but only spewed out weird errors about lines that aren’t ending etc. So I had prepared everything, even submitted the paper and un-submitted it again.
Then, at 20.59.59 GMT and a split second I hit the submit button. It took more than three minutes for the server to handle this request. Still, I was quite amazed that the paper appeared only as #6 (#19 if counting also the cross-lists) from the bottom of the webpage (i.e. top of presumably more important mailing), despite having been registered by the server at 21.00.04 GMT. So I used my much-loved bash tools curl, awk and grep and extracted the submission times of all astro-ph submissions this year until October and found this:
There is a clear spike at 20.00 UT (which is 16.00 EDT = UTC-4) and a smaller one at 21.00 UT (corresponding to 16.00 EST = UTC-5) — most of the year so far has had (Northern hemisphere) summer time. I don’t have an explanation for the smaller and wider peaks at about 9.00 and 16.00 UT. Now we can also zoom in to the region around 20 / 21:
We see that the peak submission time (which is when the submission is registered by the server) is at about 12 seconds after the deadline. Going back to my case — submitting right at the deadline, registered 4 seconds after the deadline (despite server only replying 3 minutes later) — we can ask: what are the chances of getting on top if you submit within 4 seconds? Over these 10 months (ca. 200 submission days), there have been 26 submissions in this timeframe, i.e. your chances of getting on top if submitting so close in time should be almost 100%. It just so turns out, however, that on the particular day when I submitted, there were five papers submitted even closer to the deadline. Tough luck. 😉 Hopefully, however, this will play less of a role in the future as more and more people read their daily astro-ph through voxcharta or similar services where the announcement order is either randomized or sorted according to your preferences.
There is a lot of discussion about the dismal prospects for an academic career, especially in the German astronomy community, but there are hardly any numbers. Here I would like to provide some.
Since several years, the German Astronomical Society (Astronomische Gesellschaft) collects job offers for German (and some international) openings on their job register. While this is certainly not complete, it is pretty extensive and my impression is that most major jobs that are publicly advertised can also be found there. So I went through the list of about 300 offerings from 2011 to date and categorized all jobs into three categories “PhD position”, “Postdoc position” (i.e. academic non-tenured position) and “tenured or tenure-track position” (i.e. professorships, research assistants, but also PR jobs with close academic relations). I selected only jobs in Germany which shrinks the list to 248 positions (note that some offerings were for multiple positions). Without further ado, here’s the result:
A couple of notes:
- Assuming that most Ph.D. offerings lead to the production of 1 astronomer, the “production rate” of astronomers in Germany is about 30/year. (Note added 21 Oct 2015: Actually, the number is even higher since only a fraction of Ph.D. positions are advertised via this jobregister. In Heidelberg and Munich alone, two big astro places in Germany, there are probably about 30 Ph.D. offerings per year)
- The number of postdoc offerings is similar to the number of Ph.D. offerings suggesting that either almost all Ph.D.s stay in academia or that those who stay remain in the postdoc phase for a long time.
- The ratio of production rate (30/yr) to the “sink rate” (tenured or tenure-track position, 1.6/yr), let’s call this the oversubscription factor, is about 20.
- About half of the tenured positions are PR positions such as planetarium jobs or editors for astronomical magazines; the W1 junior professorship that were offered were not tenured or tenure-track. They are essentially junior groupleader positions with additional teaching.
A couple of thoughts:
- An oversubscription of about 10 (roughly the case for proposals to ALMA from Europe or the U.S.) is considered unproductive by many senior astronomers.
- It seems hard to avoid the conclusion that either the job register or the job market is flawed.
As the big observatories of the world observe ever more astronomical objects, their archives become powerful research tools. Finding out whether an object has been observed with a certain instrument is just a few mouse clicks away, if the observatory has a public archive like ESO provides for all VLT instruments.
For a research project, I recently needed to find all local AGNs ever observed with a certain instrument (SINFONI at the VLT). Since I didn’t know the target names or programmes, I got all unique observed coordinates, resolved them via Simbad (which also gives the class of an object) and then selected the AGNs among all the targets.
Since ESO unfortunately does not provide direct access to the archive database, a query like “give me all unique observed coordinates” is not possible per se. So I had to download all headers, parse the relevant information and build my own database (SQLite for the moment).
I have a script to collect the metadata, which does this:
- query the ESO archive for all observations of a day
- then parse the resulting html file for the unique identifiers of each dataset (“data product ID” or DPID, e.g. XSHOO.2015-04-13T04:46:11.730)
- download the header for the given DPID
- parse the header for relevant information and construct an SQL insert statement
- insert all into a database
There are also scripts that
- query the database for all programmes and search metadata (PI/CoI names, titles) for them
- get atmospheric data for all observations (querying the ambient conditions server)
- And there is a top-level script that calls all of these scripts in a meaningful way and that I call about once a month or when needed to update the database.
My database consists of one table for each ESO instrument that I am interested in (currently MIDI, SINFONI and X-SHOOTER), a table with programme meta data (PI/CoI names and titles), a table with atmospheric data as well as tables with basic information about calibrators and science objects that I use for matching up observations and building LaTeX tables in a scripted way. This has become quite handy over the recent years and has helped me in building the largest sample of interferometrically observed AGNs with MIDI (Burtscher et al. 2013) as well as the largest sample of local AGNs observed with SINFONI (Burtscher et al. 2015) and a follow-up paper (submitted).
In case you are interested in tables that I have already compiled and am maintaining, please contact me and I will be happy to share the database with you. It is currently about 700 MiB and I update it every month.
Apart from nice science, one can also use this database to create other plots of interest, like a map of the exposure depth of SINFONI for example:
Interestingly, the Galactic Center (at 17:45h, -29 deg) is not the field with the deepest SINFONI integration time (“just” about 400 hours). Instead the Extended Chandra Deep Field South is the deepest SINFONI field with about 600 hours of integration time. Another field with deep coverage is the COSMOS south field (10:00h, +02 deg). About 300 hours of total integration time have been spent on this field.
Update 12 Jan 2016: I have now put my codes and the database online. Please see the github project page for further details on how to use these.
awk behaves differently on different computers depending on the language and other local settings, the so called “locale“. This is especially annoying when working with floating point numbers (e.g. using awk as a calculator since bash can only deal with integers…). With my German locale, it then uses the comma instead of the point as the decimal point character. (The Wikipedia article on the decimal mark shows the world divided into “comma” and “point” countries…)
The way around this is, of course, to change the locale, e.g. like this:
In order to keep an overview of my references and also to quickly add them to publications, I add references that I find useful to the bibliography manager BibDesk. To add a paper, I would copy the BibTeX code on ADS into BibDesk and then link the PDF so that it can be easily retrieved later. I have set up BibDesk such that it uses simple cite codes (such as burtscher2015) and uses these codes also as the file name of the PDF. This way I can easily open the PDF from any application by activating Spotlight and typing in the cite code.
This “workflow” has served me well so far, but now I found a tool that makes this even more streamlined. The “Service” (i.e. a context-menu extension for Mac OS X) ADS to BibDesk allows to add a paper to BibDesk by simply right clicking on the bib code (among many other ways of ingesting references). It is essentially a Python script with a Workflow wrapper and works fine on my Mac with OS X 10.10.3. Thanks to Jonathan Sick and contributors for providing and maintaining such a useful tool!
(This is a German post about customer service by companies)
Kunden sind lästig und mit ihnen auch noch kommunizieren zu müssen kostet Geld und Nerven. Logisch, dass Firmen mit allerlei Tricks versuchen, Kontaktformulare gut zu verstecken und möglichst keine E-Mail-Adressen rausrücken. Wenn sich in dieser Kundenvermeidungsstrategie aber Risse auftun, ist es manchmal amüsant zu lesen, wie um den heißen Brei herum laviert wird. Hier z.B. eine E-Mail von DHL (Absender und Reply-To: noreplyKSDHLPaket@dhl.com) auf eine Anfrage zur Sendungsverfolgung (ein Paket war verloren gegangen):
Bei Fragen können Sie uns gerne jederzeit telefonisch oder per eMail kontaktieren.
Bitte antworten Sie nicht auf die eMail-Adresse “noreplyKSDHLPaket@dhl.com“, dieses Postfach wird nicht gelesen. Bitte benutzen Sie für die Kommunikation per eMail ausschließlich die “Antwort” Funktion Ihres eMail-Programmes.
Bei Fragen stehen wir Ihnen gern zur Verfügung.
Da weiß der Kunde dann wirklich nicht mehr, wo er dran ist und schreibt einfach einen Brief — aber vielleicht war das ja auch gewollt, denn DHL gehört schließlich der Deutschen Post…?