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Amazon.com: Customer reviews: MP3 Player, 16GB MP3 Player with Bluetooth 4.0, Portable HiFi Lossless Sound MP3 Music Player with FM Radio Voice Recorder E-Book 2.4'' Screen, Support up to 128GB (Headphone, Sport Armband Included)
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MP3 Player, 16GB MP3 Player with Bluetooth 4.0, Portable HiFi Lossless...
Customer reviews
Customer reviews
4.2 out of 5 stars
4.2 out of 5
2,877 customer ratings
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MP3 Player, 16GB MP3 Player with Bluetooth 4.0, Portable HiFi Lossless Sound MP3 Music Player with FM Radio Voice Recorder E-Book 2.4'' Screen, Support up to 128GB (Headphone, Sport Armband Included)
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W. Kwok
5.0 out of 5 stars
Nearly Perfect! Tremendous value feature-packed MP3 music player
April 6, 2019
I would give this a 4.5 since I have a few gripes with this music player but they are minor enough that I've bumped the review up to a 5.
The Soulcker (pronounced Soul Seeker) for the most part exceeded my expectations.
What's in the package:
MP3 music player
Screen protector
Micro USB charge cord
After reading through the included manual I got started using the player. The manual is actually quite well written in English and not in broken English like so many made in China items. It is also in German, French, Spanish, and Italian languages. Speaking of languages, this MP3 player boasts up to 26 languages you can select, which includes Asian languages. Color me impressed!
In the packaging, you get 1 screen protector, which I suggest you apply with tweezers so you don't get your fingerprints on it. I wish the company included an extra set for mess-ups, but that is my first minor gripe. The MP3 player comes encased in a protetive sleeve. The included earbuds are basic but will get the job done if you don't have a higher quality set of earbuds. My second gripe is that the earbuds are the kind where you have to pull apart the wiring to separate them (see my picture). I guess the company did this so you can adjust the length of the earbud wire separation to your desired length but I'd prefer it'd be already done. The included Micro USB charge cord is 21". Charging is supposed to take 1-3 hours and the unit was already partially charged when I started charging it so it took less than an hour for me to max out the charge before my first usage. The armband has a plastic see-through cover and the band appears to be neoprene, which is expandable and breathable. Battery life is phenomenal and I believe the 55 hour rating. I left it on overnight and it was still at 4 full bars when I woke up. The manual says music playback time is 48 hours with headphones and 13 hours with the internal speaker. Video playback time is 9 hours with headphones and 5 hours with the speaker.
The main folder menu is easy to navigate with the following selection options: Music, Videos, FM radio, Recordings, Bluetooth, Pictures, EBook, Settings, Folder View. Setting up the date and time was a breeze. You have your choice of date display formats and 12 or 24 hour time formats. One thing that I really liked about the MP3 player was the ability to lock buttons. This prevents you from accidentally turning off the unit. You also can turn on or off the LED selection buttons or leave them on, but my major gripe is that the brightness of the LED buttons can't be adjusted if you leave it on. They are bright blue! The bluetooth pairing worked great with my speaker. If you don't connect an earbud or speaker, the MP3 player has an internal speaker, but don't expect great sound. It's just basic enough and loud enough for you to hear what you need. There is a calendar function, which just serves as reference. What a really liked was the alarm. You can set the alarm once, daily, or on work days (M-F?). Unfortunately, you can't set what qualifies as a work day. You can use an included ring for the alarm or choose music from your internal or card memory. There's also a stopwatch and pedometer. COOL! However, you can't start the pedometer and have it continue to function once you go to your music screen. You must either stay on the pedometer or stopwatch screen for their functions to work. However, if you had music playing prior to their usage, your music will continue to play. The FM radio will only work if you have earbuds connected to the 3.5mm audio jack. You won't be able to listen to the radio through bluetooth without an audio wire connected because the wire acts as an antenna. Cool add-on bonuses include the ability to record the broadcast you're listening to or even to record stand alone voice memos. Music playback is great. It'll take MP3, Flac, APE, WMA and Wav formats. I'm pretty sure it'll take other audio formats but I didn't try them out. It'll also recognize LRC lyric files. You can set your own playlist or select from your existing playlists. You can also sort your music by artists, albums, genres. Pretty standard features. I could not test any videos, but I can tell you it won't play mkv files, since I had a few movies in MKV format on my card that weren't picked up. It will only play AMV video files. Overall, this is a jam-packed music player the had way more than I expected and far exceeded my expectations. It's like they thought of everything possible and tried to jam it into one device. You're getting a bargain for the price they're charging, because this is a an excellent value for the quality and features of the device.
The good:
Excellent battery - rated 55 hours
Internal speaker
Bluetooth pairing
Button lock
Comprehensive manual in 5 languages
16GB internal memory, expandable to 128GB Micro SD card (recognized my 200GB card)
Recording Radio/Voice memos
Ebook reader
Video playback
FM radio
The could be better:
Only 1 screen protector included
Pedometer/Stopwatch won't allow multitasking
LED light up button brightness isn't adjustable
Video is limited to AMV video format
Alarm can't select a specific date
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416 people found this helpful
Top critical review
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1.0 out of 5 stars
This is not the iPod nano replacement you're looking for
June 5, 2019
I needed a MP3 player to take on runs, so I ordered this Soulcker to replace my old iPod nano which finally died. It is not suitable for running.
Reason 1: Weight and Size. The Soulcker weighs 108g vs the Nano's 34g. It might not seem like a lot, but the Soulcker bounces around excessively in my pocket when I run. I could use the included armband, but I find the headphone cord gets in my way then, especially when I need to look over my shoulder to check for turning cars. The Soulcker measures 105mm by 50mm by 10mm vs the Nano's 90mm by 40mm by 4mm. This is not as big of a deal but still was larger than I hoped.
Reason 2: Music management. Things were a huge mess trying to move from my iTunes library to the Soulcker. Many albums were jammed into one, or even unattributed or misattributed to artists. My tags had worked fine in iTunes. Even after re-downloading and massaging some tags, Soulcker still wants to awkwardly jam double albums into a mess.
Reason 3: Battery life. 55 hours is a joke. I just charged this to full on 2019-05-31, used it for 2 hours on 2019-06-01, used it for 30 minutes 2019-06-03, and the battery was dead this morning 2019-06-05. It is a pretty slow charge too, because for 10 minutes charge I only got 12 minutes of play on this morning's run.
Don't waste your money on this trash.
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47 people found this helpful
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3.0 out of 5 stars
Good quality MP3 player but needs much better instructions
May 2, 2019
Verified Purchase
I bought this to use at home, the gym and going outside for walks. It is a sleek, compact and modern player. The small screen is actually easy to read and well lit. Unfortunately, the instructions I found, are very difficult to follow and understand. I was able to figure some things out by trial and error and managed to get the time and date entered followed by my favorite radio station. However, my iMac, would not recognize the player and I followed the trouble shooting at the end of the instructions, only to end up at their web page and help and support that was not in English so not helpful. The player itself has an interface that is easy to read and very well lit and again with trial and error I managed to get the buttons working in the correct order. This player seems to have a lot of functions, music, radio, pictures, videos, recording and more but figuring them out is difficult with the included instructions as they are not explanatory and not helpful. It has great battery life and 16GB of memory but the included headphones were painful after a few minutes. This MP3 player has many very nice qualities, but it must resolve its instruction manual problems so that people can understand and enjoy all of its good functions and that is the reason for the 3 star rating.
14 people found this helpful
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3.0 out of 5 stars
Limited functionality
July 22, 2019
Verified Purchase
Overall I like the form factor and feel of the device. I was disappointed to find I can only setup 3 playlists and can't name the playlists other than the default "Playlist 1, Playlist 2" etc. Adding mp3 files to a playlist is long and tedious. I have audiobooks that have 50+ chapters. Adding the mp3's one at a time is annoyingly time consuming. It would be nice if there was an app that would allow me to add files and drag\drop them into the correct order. Using folders as playlists is fine except when all the files in one folder finish it starts playing from the next folder. The sleep timer and auto shut off don't seem to work at all.
UPDATE: I figured out how to create my own playlists:
1. Format the device (this will delete all your content and erase all folders but you can re-create the folders when the device is connected to your PC.
2. I'm using an app called Playlist Creator 3.6.2
3 connect the device to your PC and create 3 folders Music, Audiobooks (if u use them) and Playlists
4 Add content back to the device in the appropriate folders.
5. Open Playlist Creator. Drag the content you want to make a playlist out of into the player.
6. Make sure the output type is set to .m3u.
7. Copy the playlist to the device. put it into the playlist folder.
When u go to the playlist menu you will see the 3 standard playlists (Playlist1, Playlist2 etc.) but your playlist will be there too.
4 people found this helpful
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AMZ Customer
3.0 out of 5 stars
Not bad but don't expect anything fancy
June 25, 2019
Verified Purchase
This is a very basic product. However the sound playback is better than I expected (when listening via headphones or portable speakers). The playback via device speaker is mediocre. This device is NOT touchscreen which takes getting used to in this day & age. The device comes with a usb cord for device transfer & battery charging but is very short and does NOT come with the charger base. The headphone port is on the bottom of the device which also takes getting used to. The kit comes with an arm band holder that has an open spot for access to both the headphone and usb ports but NOT for the power or volume buttons on the side of the device. This is frustrating because the screen eventually turns off (to save battery) so if I want to change the song, I have to blindly locate the power button through the band material & press it really hard to turn the screen back on. Good thing is, you can press the buttons on the front of the device through the plastic cover of the armband holder.
The MAIN issue I have is the advertised picture is a little misleading because album art does NOT show on this device. Lastly, one thing I really like about this device is that there's a feature that can speed up or slow down the tempo of a song. There's always that one song that would sound great if it was more upbeat, so this feature is great for that.
Overall, if you are looking for a very simple device to play your music, this is great. This is nowhere near a mini tablet or upscale multimedia device.
2 people found this helpful
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David Hunter
3.0 out of 5 stars
Beware the "rebate" scam
December 10, 2019
Verified Purchase
I bought one of these for my oldest son (14), and he enjoyed it so much that his younger brother (13) wanted one as well for his birthday. They enjoy not just the music, but the extra features like the microphone and being able to read books (formatted as text files - you can't use epub or other book formats). Getting music from my computer onto the MP3 player wasn't too bad, and the boys soon got the hang of getting the player to do what they wanted. The problem I have is with the seller, who included with the second MP3 player a card promising that I had won a 50% rebate for the cost of purchasing it. I was a little skeptical, but thought I'd look into it. I follow the instructions on the card (email the seller with the order number), and right away he emails back asking for all this other information, including my Paypal. I tried writing back several times but just got the same instructions mailed back to me over and over. It smells very fishy to me. So I have no problem with the MP3 player - it's not flashy, but for the money it does what it says it will do. But beware if you get one of those little cards as well.
2 people found this helpful
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3.0 out of 5 stars
July 24, 2019
Verified Purchase
My Touchscreen Zune HD died after 10 years so I needed a new Mp3 player.
+ Pretty cheap
+ Comes with arm band
+ Plug in Computer and put songs into folders without 3rd party software (my Zune needed Zune Player to upload songs)
- Unlike every smart phone that is made these days, volume buttons are on the bottom right, very uncomfortable to use
- touch button are not very touch sensitive, gotta press relatively hard on them compare to touch screen
- User Interface is awful:
- Something is wrong with shuffle mode. For example if you are listening to song A then press next to listen to Song B, when you press back button to go back to song A it won't. It will choose a random song, like song C. If you press forward it won't go back to song B, but will find another random song. So it's not shuffle, it's random.
- If you have like 1,000 songs in one folder or playlist searching by song name, artist or whatever is limited to scrolling the entire thing (with analog buttons it is extra pain to scroll since you can't just flick the screen). For example, Zune would let you skip to a specific letter.
I looked at pictures of other Mp3 players and they are all similar design and have similar User Inferace. I think they are all made in a same factory but have slightly different shell and different button design for inferface.
One person found this helpful
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3.0 out of 5 stars
It's a matter of what you want.
May 31, 2019
Verified Purchase
First, I am only interested in the Mp3 capabilities, Podcast, Lesson Plans, AudioBooks. I don't care about the eBooks, photo, clock, radio, etc..
The user interface is easy to understand for the most part. It has a solid heft to it, which to me inspires a bit of confidence. The large screen size is a nice touch for a glance at the album art. The speaker, for my uses, is quite good. I did not expect Klipsch, or Bose quality. The battery life is outstanding, even while using the speaker. One of my favorite features is the variable speed playback. I almost always listen to non-music, spoken word sources at a higher speed. There is little distortion at the higher speeds, and is easily intelligible!
Now for the negatives (which perhaps could be addressed by a software update?):
The buttons are a bit sensitive. I often hit one when putting it down, and find myself on the next source, which brings up a real negative! Yes, it will remember your position if the source remains the same, but if you change sources, it will star at the beginning. If you're listening to a lesson plan, need a break, and listen to music, then go back to the lesson plan, the lesson plan will start at the beginning, and you will have to search for your position. This is where putting it down, and accidentally hitting a button really hurts!
A minor annoyance: I only used the earphones once, but you have to manually stop the speaker. Simply plugging in the earphone will not work.
Multiple chapter audio doesn't work in order when in random mode, even when ID3v1, ID3v2.3, ID3v2.4 compliant. Random mode should work only for the Music folder, not all folders. Folder play should be exclusive to that folder.
I've only had this for a month, so I don't know how long it will last, but for the money, it's acceptable.
2 people found this helpful
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Stephen M. Witty
3.0 out of 5 stars
Caveat Emptor
January 15, 2020
Verified Purchase
The title/headline of this review is based on a few things, and though my criteria for this player was simple, (I wanted an inexpensive digital music player), the player itself had a couple of surprises.
The first surprise was finding that the player does not actually support WMA format files, though that capability is claimed in the User Manual as well as on the Amazon listing itself. Each time a WMA file was encountered the player displayed the words "File format not supported". Fortunately there are reputable, reliable media format converters online so I was able to get past the incompatible format issue, but, I should not have had to do so. Had the player's listed capabilities been accurate I would have purchased a different player.
The second surprise is that yes, music can be put into playlists, but only the playlists that are already on the player itself. There is no way to transfer a playlist from your computer, nor is there any way to create a new playlist on the player itself. The buyer is stuck with three (3) generic playlists with the following titles:
1. Playlist on the go [1]
2. Playlist on the go [2]
3. Playlist on the go [3]
These playlists do not show up in the Folder view when the player is connected to a computer so the music has to be transferred to the player which displays all the tunes in a big, long list, then you have to add each tune separately to one or more of the aforementioned generic playlists.
Insofar as the good things about this player, I can say that yes, it plays the music I transferred to it; the EQ section works decently, particularly the Custom option as that has a 5-band graphic EQ to play with, and after a short while the front-panel interface gets easier to use, though it can still be frustrating as the selector can be touchy.
I have not yet played a video so I can't speak to that, but, the FM reception is about what I expected: it ain't all that.
In short, it isn't an iPod, a tablet, a laptop, or a PC with a 7.1 surround-sound speaker system attached, it's an inexpensive digital music player, and with that I recommend you don't expect too much from it, but it'll do in a pinch.
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Seattle Dweller
3.0 out of 5 stars
OK, but lacks necessary features
August 29, 2019
Verified Purchase
Bought this to save battery time on my cell, which I play most of my music on right now. Spent close to three hours loading my MP3 files onto it, so far so good. Try playing music only to find that the interface is very bad for large music collections. THERE IS NO SEARCH FUNCTION!!!!!!! This means you have to scroll through every music file sequentially to get to the selection you want. UGHH!!! Otherwise it seems to work OK, will just have to see how well it works otherwise. The fm radio function is nice. I bought a set of Sony sport headphones because I hate earbuds, never could get them to stay and be comfortable. PIcture display is a bit pixelated and low res too on this device. Well, you get what you pay for. As a basic player it should do OK, but just barely. I am amazed this got "Amazon's Choice" listing, I would have expected a lot more for that.
One person found this helpful
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3.0 out of 5 stars
Works fine but has issues you should know about.
January 8, 2020
Verified Purchase
Music player works well, has great sound quality, good internal memory, is compact, and has 12-15 hour battery life for a decent price (depending on how much the display is on).
Things I don't like that may have changed my decision to purchase are...
1. Player is limited to about 4000 songs. While that is a good sized library, if you want to buy a large micro SD card and load 5000+ songs, you cant do it. The alternative is to buy multiple micro SD cards and limit each to 4000 songs.
2. Interface is somewhat annoying. A-Each time I synced with a bluetooth speaker, then turn off the unit, you must re-sync again every time you power up, and that requires moving through several steps to get to the bluetooth screen. I would prefer keeping the bluetooth connection until I choose to turn it off. B-Once display goes to sleep while music is playing, it is slow and hard to awaken again. I sometimes have to push buttons many times to get it to respond. C-The display/playlist seems inaccurate. I like to group Christmas songs in a single folder to have continuous play without changing folders every 45 minutes. With over 2000 songs loaded in a single folder, I can play through 20-30 songs, then when awakening to view the current song, the tiny letters were often inaccurate and usually show the first song I began with but not current one. If I scroll up and down the list of songs it isn't accurate either. D-There is no search mode, so when I want to find a song in the folder I mentioned, I literally must move through several hundred songs at times to find the place I want to start.
Overall, for the price, this unit is fine if you know of these quirks and are OK dealing with them. I didn't know about them ahead of time or I may not have bought this item.
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jc norton
3.0 out of 5 stars
Not Bad When it Works
February 15, 2020
Verified Purchase
This is pretty much a piece of junk. It's very unstable, working fine for a while, then not at all. Sometimes, it starts a song, plays for ten seconds, then jumps to the next one and the next one and so on, until you turn it off. When you turn it back on, maybe it will work fine, maybe it won't. Just very frustrating. Loading music to it is easy enough and it plays the FLAC and MP4 file I put on it. Battery life is better than my old iPOD, but nothing close to what's advertised. I'd say maybe twelve hours? The challenge is, what's the alternative? The reviews of all of these players show the same thing -- lots of happy campers, other people saying it's junk, and that seems to be true at every price point. For now, I don't want the hassle of getting another one and spending hours loading music to it. This is a piece of crap, but it works most of the time and the sound quality is fine. Just have to live with the problems and resist the impulse to take a hammer to it lol.
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Former Sanawar teacher alleges harassment at the hands of school authorities
ganpat1956 posted a topic in RTI in MediaChandigarh, February 20: A former teacher of Sanawar School, DR Rajinder Singla, today alleged that he was sacked after he demanded some information from the school under the Right To Information Act (RTI). Addressing a press conference at Press Club, Sector 27, Singla alleged that the school has a number of irregularities and the school authorities were not ready to confront it. Singla said, "When the school authorities were not ready to answer my queries I went through the RTI and submitted a 13 page application to the regional officer of CBSE at Panchkula. A few weeks later I received a letter from the headmaster of the school stating that my services had been terminated with immediate effect.†He further said, " While I was denied the information the first time I had asked for it under the RTI act, the regional officer at the CBSE office in Panchkula, Kushal Singh later directed the headmaster of the school to provide me with the required information.†Singla also alleged that the school authorities direct the teachers to act and function as per their wishes, failing which they are harassed. He added, " those who have been harassing the teachers include R P Aggarwal, Chairman of board of governors and education secretary to the Government of India, Jai Singh Gill, former chief secretary, Government of Punjab, Omar Abdullah, MP from Jammu and Kashmir and Lt General A N Aul, chief of staff, HQ Western Command, Chandimandir. Many teachers have been sacked by the school without serving any notice or explaining the reason of doing the same.†Meanwhile, refuting the allegation, Praveen Vasisht, Headmaster Sanawar School, said, "Singla had a poor record. He has been sacked as per the decision taken by the board of directors and not because he requested for information. He is making false allegations about the school because he himself is at fault.†Singla also said that he would be filing a case against the school authorities in the District Courts soon. Former Sanawar teacher alleges harassment at the hands of school authorities

subset: commoncrawl


text:
Challenger Basketball
A program designed for young athletes from the special needs community who are looking for an opportunity to learn basic skills and play basketball! Each athlete will be paired with a High School student/athlete buddy. Each buddy will assist the athlete with developing their skills, raising self-esteem and having fun while making new friends!
Boys and Girls Grades 1-8 (South Windsor Residents only) Saturdays, 12:30-1:30pm 1/4/20-2/8/20 $20/family Location: Eli Terry School
Please register child that is participating and siblings who might join them.


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(4h) Bullish @ Higher and Lower Degree RSI Divergence
FX:NZDUSD Dolar New Zealand/Dolar U.S
Dilihat 589 kali
Oct 13
Komen: Small adjustement on Fibs and Targets;
Oct 17
Komen: 1st target
Oct 18
Dagangan ditutup: sasaran tercapai:
Idea Berkaitan
Thanks for the post! I just had a question though, how come you have said that this is a Butterfly pattern, but the pattern you've drawn on the chart doesn't fit those rules?
sandhusukhjit KG6450
No replies! But posts got updated. Hmm


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Real Student Innovation in Action
Don Wettrick withEric Heinzman, Mikaela Gilbert, and Haley Lutz
Students share their experiences with an innovative class assignment that blossomed into real-world possibilities.
Follow: @donwettrick @hayley_lutz23 @mikaelakimberly @eric_heinzman,
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November 26, 2014 InnovatED
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Don Wettrick is an innovations class teacher at Nobleville High, in which he joins his classroom students Eric Heinzman, Mikaela Gilbert, and Haley Lutz.
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text: Lemondeduerl 2,398 Report Posted August 13, 2019 (edited) What a disappointment... I'm gonna watch the show because of Rosalia. Where are Normani, Madonna, Ariana, Blackpink, Billie Eilish, Katy, Charli, Nicki, Cardi, Selena Gomez, Avril Lavigne, Halsey...?. Edited August 13, 2019 by Lemondeduerl 2 Quote Share Link to post Share on other sites Facebook Twitter


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David Hasselhoff is already known for being an alcoholic, due to Hasselhoff's infamous drunk video tape a few years ago. This helped make Hasselhoff an Internet sensation and a punchline for his alcoholism, in addition to being a punch line for much of his actual career. But the joke was not funny for David Hasselhoff over the weekend, according to reports. RadarOnline.com broke the alleged story that David Hasselhoff had to be rushed to the hospital with an urgent case of alcohol poisoning.
At Encino, California, the Baywatch star was reported to be found unconscious by his daughter Hayley. In fact, Hasselhoff's ex-wife, Pamela Bach, had to be the one to drive over and rush her former husband to the hospital, where his life was narrowly saved.
RadarOnline claims that Hasselhoff's alcohol level was .39, nearly five times over the legal limit in the state. The site also claims that this incident is the seventh time Hasselhoff has had alcohol poisoning, and possibly the 10'th time he has been to the hospital in the last few years.
TMZ, of all sites, tried to put some cold water on this story. They reported that Hasselhoff's representatives say that he is just fine, and that everything was exaggerated. In fact, his lawyer, Mel Goldsman, accused Pamela Bach of being behind the story just to slander him, as part of their bitter separation.
TMZ's sources tell them that Hasselhoff is fine, and that he was already out of the hospital to celebrate his father's birthday.
David Hasselhoff made a story like this a bit too easy to believe at face value, due to his famed drunken video tape incident in 2007. In it, Hasselhoff was drinking in the bathroom while eating a hamburger at the same time, in an instant YouTube classic.
In that case, Hasselhoff's ex-wife was also accused of using the tape, which was made by daughter Hayley, for personal gain. He later got himself into rehab, but it may not have stuck.
Hasselhoff, barring no further problems or scandals, will be back at his summer job as judge of America's Got Talent in several weeks. Until then, the latest David Hasselhoff alcoholic jokes can kick off, depending on how much more funny or sad this latest story gets.
Radar Online- "EXCLUSIVE BREAKING NEWS: David Hasselhoff Alcohol Poisoning; Rushed To Hospital" www.radaronline.com/exclusives/2009/05/exclusive-breaking-news-david-hasselhoff-alcohol-poisoning-rushed-hospital
TMZ- "Hasselhoff Too Much Drinky, But Just Fine" www.tmz.com/2009/05/03/david-hasselhoff-the-hoff-drunk/
New York Post- "David Hasselhoff's Boozy Tape" www.nypost.com/seven/05042007/gossip/pagesix/david_hasselhoffs_boozy_tape_pagesix_.htm


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S. Barker1,2 - R. de Grijs1,3 - M. Cerviño4
1 - Department of Physics & Astronomy, The University of Sheffield, Hicks Building, Hounsfield Road, Sheffield S3 7RH, UK
2 - Isaac Newton Group of Telescopes, Apartado de correos 321, 38700 Santa Cruz de la Palma, Canary Islands, Spain
3 - National Astronomical Observatories, Chinese Academy of Sciences, 20A Datun Road, Chaoyang District, Beijing 100012, PR China
4 - Instituto de Astrofísica de Andalucía (CSIC), Camino Bajo de Huétor 50, Granada 18008, Spain
Received 26 February 2008 / Accepted 9 April 2008
We analyse high-resolution Hubble Space Telescope/Advanced Camera for Surveys imaging of the nuclear starburst region of M 82, obtained as part of the Hubble Heritage mosaic made of this galaxy, in four filters (Johnson-Cousins equivalent B, V, and I broad bands, and an H narrow-band filter), as well as subsequently acquired U-band images. We find a complex system of 150 star clusters in the inner few 100 pc of the galaxy. We do not find any conclusive evidence of a cluster-formation epoch associated with the most recent starburst event, believed to have occurred about 4-6 Myr ago. This apparent evidence of decoupling between cluster and field-star formation is consistent with the view that star cluster formation requires special conditions. However, we strongly caution, and provide compelling evidence, that the ``standard'' simple stellar population analysis method we have used significantly underestimates the true uncertainties in the derived ages due to stochasticity in the stellar initial mass function and the corresponding sampling effects.
Key words: galaxies: individual: M 82 - galaxies: interactions - galaxies: photometry - galaxies: starburst - galaxies: star clusters - galaxies: stellar content
Supermassive star clusters or ``super star clusters'' (SSCs) are highly luminous and massive, yet compact star clusters. They result from the most intense star-forming episodes that are believed to occur at least once in the lifetime of nearby starburst galaxies, and most probably also in merging galaxies at high redshift (Smith et al. 2006). Super star clusters have been observed using the Hubble Space Telescope (HST) in interacting, amorphous, dwarf, and starburst galaxies (e.g., Arp & Sandage 1985; Melnick et al. 1985; Holtzman et al. 1992; Meurer et al. 1992; Whitmore et al. 1993, 1999; Hunter et al. 1994, 2000; O'Connell et al. 1994; Ho & Filippenko 1996; Conti et al. 1996; Watson et al. 1996; Ho 1997; Carlson et al. 1998; de Grijs et al. 2001; de Grijs et al. 2003a,b, and references therein) and are thought to be contemporary analogues of young globular clusters. For this reason, the study of SSCs can lead to an understanding of the formation, evolution, and destruction of globular clusters (see the review by de Grijs & Parmentier 2007) as well as of the processes of star formation in extreme environments.
A current issue of strong contention relates to the stellar initial mass function (IMF) in starburst environments, and particularly whether it is ``abnormal'' due to preferential production of higher-mass stars (we will touch on this issue below, where we explore the effects of stochasticity in the IMF). Furthermore, SSCs are involved in the activation and feeding of supergalactic winds (e.g., Tenorio-Tagle et al. 2003; Westmoquette et al. 2007a,b). In addition, SSCs can be age-dated individually using either spectroscopic or multi-passband imaging observations, and as such they can be used as powerful tracers of the starburst history across a given galaxy.
The target galaxy discussed in this paper, M 82, is the prototype nearby starburst galaxy. The starburst is five times as luminous as the entire Milky Way, and it has one hundred times the luminosity of the centre of our Galaxy (O'Connell et al. 1995, and references therein). At a distance of 3.9 Mpc (Sakai & Madore 1999), many of M 82's individual clusters can easily be resolved by the HST. O'Connell et al. (1995) performed an optical imaging study of the central region of M 82 using the HST's Wide Field / Planetary Camera (WF/PC), and unveiled over one hundred candidate SSCs (in their nomenclature) within the visible starburst region, with a mean mag (based on an adopted distance of 3.6 Mpc). At the present time, this is brighter than any globular cluster in the Local Group (e.g., Ma et al. 2006, and references therein). A more recent study by Melo et al. (2005) used HST/Wide Field and Planetary Camera-2 (WFPC2) observations to reveal 197 young massive clusters in the starburst core (with a mean mass close to , largely independent on the method used to derive these masses), confirming this region as a most energetic and high-density environment (see also Mayya et al. 2008).
Unfortunately, studies of the core are inhibited by M 82's almost edge-on inclination ( ; Lynds & Sandage 1963; McKeith et al. 1995) and the great deal of dust within the galactic disk (see Mayya et al. 2008, and references therein). Although the dust provides the raw material for the clusters' formation, it also obscures and reradiates most of the light from the starburst in the infrared (Keto et al. 2005). However, despite all the bright sources associated with the active starburst core suffering from such heavy extinction (in the range -25 mag; e.g., Telesco et al. 1991; McLeod et al. 1993; Satyapal et al. 1995; Mayya et al. 2008, and references therin), many individual clusters remain bright enough to obtain good photometry and spectroscopy for (see, for example, Smith et al. 2006; McCrady & Graham 2007).
The starburst galaxy M 82 has recently experienced at least one tidal encounter with its large spiral neighbour galaxy, M 81, resulting in a large amount of gas being channelled into the core of the galaxy over the last 200 Myr (e.g., Yun et al. 1994). The most major recent encounter is believed to have taken place roughly (2- yr ago (Brouillet et al. 1991; Yun et al. 1994; see also Smith et al. 2007), causing a concentrated starburst and an associated pronounced peak in the cluster age distribution (e.g., de Grijs et al. 2001, 2003c; Smith et al. 2007). This starburst continued for up to 50 Myr at a rate of 10 yr-1 (de Grijs et al. 2001). Two subsequent starbursts ensued, the most recent of which (roughly 4-6 Myr ago; Förster Schreiber et al. 2003, hereafter FS03; see also Rieke et al. 1993) may have formed at least some of the core clusters (Smith et al. 2006) - both SSCs and their less massive counterparts (see Sect. 3.6).
The active starburst region in the core of M 82 has a diameter of 500 pc and is defined optically by the high surface brightness regions, or ``clumps'', denoted A, C, D, and E by O'Connell & Mangano (1978). These regions correspond to known sources at X-ray, infrared, and radio wavelengths, and as such they are believed to be the least obscured starburst clusters along the line of sight (O'Connell et al. 1995). The galaxy's signature bi-polar outflow or ``superwind'' appears to be concentrated on regions A and C (Shopbell & Bland-Hawthorn 1998; Smith et al. 2006; Silich et al. 2007), and is driven by the energy deposited by supernovae, at a rate of 0.1supernova yr-1 (e.g., Lynds & Sandage 1963; Rieke et al. 1980; Fabbiano & Trinchieri 1984; Watson et al. 1984; McCarthy et al. 1987; Strickland et al. 1997; Shopbell & Bland-Hawthorn 1998; see also de Grijs et al. 2000, for a review)
This paper is organised as follows. In Sect. 2 we give an overview of the observations, source selection, and image processing techniques applied to our sample of star clusters in the core of M 82. Sect. 3 describes the methods and results of the age determinations, and the complications due to stochasticity in the IMF, and Sect. 4 provides a summary and discussion of these results, where we place our star cluster results in the context of the star-formation history of the galaxy.
During March 2006, a large four-filter six-point mosaic data set of M 82 was obtained as part of the Hubble Heritage Project (HST proposal GO-10776) using the Advanced Camera for Surveys/Wide Field Channel (ACS/WFC; pixel size 0.05 arcsec). Exposure times were 1600, 1360, 1360, and 3320 s for observations in the F435W (equivalent to Johnson B), F555W (V), F814W (I), and F658N(H) filters, respectively. For each of these filters, four exposures were taken at six marginally overlapping pointings, or ``tiles''. The four exposures within each tile were dithered to improve the rejection of detector artefacts and cosmic rays, and to span the interchip gap of the ACS/WFC. The final mosaic of the ACS/WFC fields was pipeline-processed by the HST data archive's standard reduction routines; for full details of the observing programme, image processing, and calibration, see Mutchler et al. (2007).
Whereas O'Connell et al. (1995) had access to two broad-band filters only (F555W and F785LP, the latter corresponding to a broad R-band filter), the present study uses these four-filter high-resolution ACS Hubble Heritage observations of M 82 as well as subsequently acquired F330W (U-band) data, observed as part of proposal GO-10609 (PI Vacca), and obtained from the HST data archive. The F330W observations centred on M 82 A and C were obtained on UT December 7 and 8, 2006, respectively, with the ACS/High Resolution Camera (ACS/HRC; pixel size arcsec). The respective exposure times were 4738 and 3896 s, with the ACS/HRC pointed under a position angle of 90.08 and 90.06(East with respect to North), respectively. The two final pipeline-processed and flux-calibrated images cover adjacent fields, largely coincident with the central starburst area selected for further study in the current paper (see Sect. 2.2).
It should also be noted that O'Connell et al. (1995) used pre-COSTAR data, acquired before the first HST servicing mission. The increased volume and quality of data now available to us provides more evidence with which to distinguish clusters from point sources (i.e., stars), and in principle allows for better constrained age estimates, making the data set ideally matched for the first comprehensive comparison of the various star-formation modes in one of the most violent environments in the local Universe.
|Figure 1: The starburst core region of M 82 used for the main analysis in this paper. The four panels show the region's appearance as a function of wavelength (B: F435W; V: F555W; I: F814W; H: F658N). Each panel is 29.55 arcsec on a side; a scale bar of 5 arcsec length (corresponding to 95 pc at the distance of M 82) is shown in the bottom right-hand panel. In the top right-hand panel, we show the outlines of regions A, C, D, and E, defined by O'Connell & Mangano (1978), superposed on the V-band image. The bottom left-hand panel includes the positions of clusters A1 and B2-1 (see Smith et al. 2006). The individual panels are displayed at optimum dynamic range, in order to emphasise the low-level structure.
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The final drizzled B, V, I, and H images were first aligned using the IRAF/STSDAS tasks IMALIGN and ROTATE, using a selection of conspicuous sources common to each frame as guides. They were then cropped to a common size of pixels ( arcsec) in order to include only the very core of the galaxy, the region of particular interest in this paper. The U-band images were rotated, aligned and scaled to the Hubble Heritage data set using a similar selection of point-like sources common to both data sets, where available. This ensured that the astrometric solutions of all images were calibrated to a common frame of reference.
The selected region was chosen to specifically encompass the areas A, C, D, and E (O'Connell & Mangano 1978), as well as cluster B2-1 (de Grijs et al. 2001; Smith et al. 2006) for reasons of both image alignment and for photometric consistency checks. The starburst region studied in detail in this paper is shown in Fig. 1. In Fig. 2 we show the complementary, mosaicked F330WACS/HRC observations, rotated to the same orientation as the fields in Fig. 1.
At first glance, the images in the individual passbands exhibit a number of striking similarities as well as differences. It is clear that the M 82 core is undergoing vigorous star formation, as indicated by the strong H and F330W-band emission. A first impression of the various named regions indicates that region C may be the youngest (since it does not exhibit strong emission in the I-band filter), while region E might be somewhat older or most affected by extinction (given that it is progressively easier to identify as a function of increasing wavelength). We will quantify these first impressions in Sect. 3.
|Figure 2: Complementary F330W observations of the M 82 A (east) and M 82 C (west) pointings obtained with the ACS/HRC. The position angle is identical to that of the four images shown in Fig. 1; clusters A1, B2-1, and F (e.g., Gallagher & Smith 1999) are indicated for orientation. The mosaic is displayed at optimum dynamic range, in order to emphasise the low-level structure. The linear features on the left-hand side of each of the two mosaicked pointings, seen under an angle of about 30, are instrumental artefacts due to the HRC's coronographic finger. The occulting finger is not retractable and is therefore present in every ACS/HRC exposure.
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The standard deviations of the number of counts of seemingly empty sections of all images were established to ascertain a ``sky'' background count for each filter. Multiples of this background count were then used as thresholds above which the number of sources in each filter was calculated, using the IDL FIND task. Figure 3 shows that the most suitable, conservatively chosen thresholds for source inclusion were 0.08, 0.20, and 0.90 counts s-1, for the B, V, and I bands, respectively. (In view of the more stringent requirements applied in the next steps in the construction of our final sample, the exact values of these thresholds are unimportant, as long as they are chosen such that no real objects are omitted a priori at this stage.) For all three passbands, initially the number of detections decreases rapidly with increasing threshold value. This is an indication that our ``source'' detections are noise dominated. Where the rapid decline slows down to a more moderate rate, our detections become dominated by ``real'' objects (either stars, clusters, or real intensity variations in the background field). In Fig. 3 we have indicated the approximate count rates of these transitions by the vertical dashed lines; in the remainder of this paper we will only consider the objects in the ``source-dominated'' domain, as indicated in the three panels.
We point out that the curve delineated by the data points is not as smooth as perhaps expected at face value. This is due to our use of a number of different ranges of relatively low background flux in which we determined the standard deviations of the counts. We subsequently ran our FIND routine based on detection thresholds in multiples of the various standard deviations. The deviations from continuous smooth curves are therefore a good indication of the intrinsic variations in seemingly empty field regions at low flux levels.
|Figure 3: Number of objects detected as a function of threshold level for the B, V, and I images. The vertical dashed lines show the thresholds adopted here for source-dominated (as opposed to noise-dominated) ranges. See the text for details (Sect. 2.3).
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We subsequently employed a cross-identification procedure to determine how many sources were visible and coincident with intensity peaks within 1.4 pixels of each other in all three filters (i.e., allowing for 1-pixel mismatches in both spatial directions), yielding over 900 potential clusters. Sources found to be present in all filters were then confirmed individually by eye, owing to the lack of a more robust verification procedure in the presence of the highly variable background and significantly variable extinction across our field of view (cf. de Grijs et al. 2001; Smith et al. 2007). This verification process was performed independently by two of us, and the small number of disagreements (less than a few tens of objects) were discussed and revisited in detail in order to construct the most robust and impartial cluster sample possible.
In our next step we used the ``Tiny Tim'' software package (Krist & Hook 1997) to generate HST point-spread functions (PSFs). We determined the best-fitting Gaussian profile for each candidate cluster, as well as for the Tiny Tim PSFs. The width of the latter was found to be best represented by a Gaussian profile of pixels, in the V band. Any candidate cluster with (significantly) below this value was considered most likely to be a star (or an artefact either of the CCD or due to cosmic rays) and was consequently discarded. Artificial clusters were then created using the BAOLAB package (Larsen 1999), using HST/ACS PSFs, and their values were compared with those determined by our IDL routine. This provided an additional constraint with which to distinguish clusters from stars, leaving 208 clusters for further analysis. We note that although realistic cluster luminosity profiles may well deviate from the simple Gaussian profile adopted here, its consistent and systematic application to our observations allows us to robustly differentiate between objects of different sizes, irrespective of their true profiles, provided that the profiles of the individual objects do not differ too much from object to object. In Fig. 4 we display the distribution of our final cluster sample across the face of the M 82 starburst core in the V band. This final sample was used for further analysis in all of the U, B, V, I, and H images.
The right-hand panel of Fig. 4 shows the distribution of the H excess across the region. To produce this panel, we constructed the interpolated H continuum from a combination of the V and I-band images, scaled by their filter widths and exposure times. The image shows the ratio of the H image and its continuum. The darkest shading corresponds to the most significant H excess; the lightest shading to no (or a negligible) excess. We will discuss this image in Sect. 3.6.
|Figure 4: (Left) Distribution of our final, cross-matched cluster sample across the face of the M 82 starburst core, superposed on the V-band image. (Right) H excess distribution. The darkest shading corresponds to the most significant H excess; the lightest shading indicates no (or an insignificant) excess. The orientation and scale of the images are as in Fig. 1.
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Two photometry tasks were used, in IDL, with the aim of robustly determining the magnitudes of as many clusters as possible. The APPHOT task was used with source radii ranging from 1-10 pixels and a standard sky annulus with radii from 10 to 15 pixels, corresponding to a linear scale of 10 to 14 pc at the distance of M 82. In addition, our custom-written task PHOTOM utilises radii individualised for each cluster (based on visual inspection). The resulting ``instrumental'' magnitudes (in the U, B, V, and I bands) of the 152 clusters for which our tasks could robustly obtain photometry were adjusted for their zero-point offsets (determined from the headers of the archival HST observations).
In Anders et al. (2006) we carefully considered the implications and remedies of taking ``sky'' annuli too close to a given cluster, in the sense that we would oversubtract the sky level because of the inclusion of flux from the cluster's outer profile. We generated an extensive and systematic grid of aperture corrections as a function of filter, radius of the sky annulus, and cluster profile. Using these improved aperture corrections, we corrected our cluster aperture photometry based on a fixed source aperture for the systematic effects introduced by our reduction procedure. Upon close examination of our aperture choice, we concluded that a 3-pixel (radius) source aperture resulted in the smallest photometric scatter for the cluster sample as a whole. We will adopt this source aperture below. The resulting average (aperture-corrected) magnitudes of the clusters were 20.0, 19.5, and 19.3 mag in the B, V, and I bands, respectively, with our cluster photometry spanning in excess of four magnitudes in all filters (5 mag in the I band).
Although the data reduction procedure employed does not allow us to perform a proper assessment of the observational completeness limits, the luminosity functions in the B, V, and I bands indicate that our detection limits are at , and mag. As also shown in Fig. 3, where we showed the number of detected objects as a function of our detection threshold, our combined BVI photometry is limited by the B and V-band observations.
In Sect. 3 we will analyse our cluster photometry based on the cluster colours. In essence, we will use a poor man's approach to cluster spectroscopy by using the broad-band spectral energy distributions (SEDs). Since a small change in colour could lead to a large change in the derived age, it is important to make sure that the application of the Anders et al. (2006) aperture corrections has not introduced unwanted systematic effects and/or offsets. Therefore, in Fig. 5 we compare the cluster colours derived from our variable-aperture photometry (obtained with the PHOTOM task) to those from the standard apertures (based on APPHOT) combined with the Anders et al. (2006) aperture corrections. Considering the representative uncertainties in the derived colours (shown in the bottom right-hand corners of both panels), both panels of Fig. 5 show excellent agreement between the two data sets. We are therefore confident that these aperture corrections will not introduce systematic offsets in the age determinations in Sect. 3.
|Figure 5: Comparison of our (B-V) and (V-I) colours obtained from variable-aperture photometry according to the actual cluster sizes, with fixed 3-pixel (radius) aperture photometry and aperture corrections from Anders et al. (2006). For reasons of clarity we have not added error bars to the data points; a representative set of error bars is shown in the bottom right-hand corner of each panel. The dotted lines of equality are shown to guide the eye.
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In this section we use the broad-band photometry derived in Sect. 2 to obtain estimates (or otherwise) of the star cluster ages in the M 82 starburst core. For optimum results, we do not only require a sufficiently high age resolution in our models, but also take into account the effects on the integrated luminosities of statistically sampling the stellar IMF (e.g., Cerviño et al. 2000; Cerviño et al. 2002; Cerviño & Luridiana 2004, 2006). We will first discuss issues related to statistically sampling the IMF (Sects. 3.1-3.4), and then apply the ``standard'' analysis, essentially ignoring these issues, in Sects. 3.5 and 3.6. This will highlight the differences caused by stochasticity in the IMF of incompletely sampled clusters.
In order to achieve these aims, we have made use of the CMD2.0 tool, which provides the isochrones and the mean integrated magnitudes for a number of photometric systems, including HST/ACS data in the ST system used here. We calculated the integrated magnitudes for simple stellar populations (SSPs) based on a Kroupa (2001) IMF (corrected for binaries), covering a mass range from 0.15 to 120 , from the solar metallicity (Z=0.019) isochrones of Girardi et al. (2002) and Marigo et al. (2008) for stars more massive than 7 , and the Bertelli et al. (1994) isochrones for low-mass stars. Near-solar metallicity should be a reasonable match to the young objects in M 82 (e.g., Gallagher & Smith 1999; see also Smith et al. 2006). Fritze-von Alvensleben & Gerhard (1994) also find, from chemical evolution models, that young clusters should have -1.0 . Magnitudes and other quantities are based on Kurucz (1992) atmosphere models, except for cool stars (see Girardi et al. 2000, for more details).
Our set of SSP models and isochrones covers an age range from 1 Myr to 10 Gyr. We note, as a caveat, that the models do not include nebular emission, which may systematically affect the results at the youngest ages (see also Anders & Fritze-von Alvensleben 2003). We will return to this issue below (Sect. 3.7), where we discuss the results from the H observations in detail.
Finally, we adopted the Galactic extinction law of Rieke & Lebofsky (1985; conveniently tabulated by Jansen et al. 1994) to correct our cluster photometry for foreground extinction in M 82. Referring to Fig. 1 of de Grijs et al. (2005), we note that the choice of extinction law in the optical wavelength range is relatively unimportant in the context of extinction corrections of broad-band photometry. Galactic foreground extinction was estimated based on Schlegel et al. (1998).
Estimates of physical parameters (such as mass or age) based on synthesis models assume a certain proportionality between the stars at different evolutionary phases for a given age. Of course, the use of the mean integrated luminosity provided by the SSP models only makes sense when this proportionality is robustly met. This implies that there must be sufficient numbers of stars in any and all evolutionary phases or, equivalently, that the IMF is well sampled in all relevant mass intervals (see Cerviño & Valls-Gabaud 2008, for a more detailed discussion).
The simplest test to identify whether the IMF is appropriately sampled is to use the ``lowest-luminosity limit'' (LLL) method (Cerviño & Luridiana 2004). The LLL method states that the IMF is not sufficiently well sampled if the integrated luminosity of a cluster is lower than the luminosity of the most luminous star included in the model for the relevant age (see Pessev et al. 2008, for an application). This implies that clusters fainter than this limit cannot be analysed using standard procedures, including minimisation of the observed values with respect to the mean SSP models (but see Sects. 3.5 and 3.6). Below the LLL, the proportionality assumed in the mean SSP value is not met, and the cluster colours do not reflect the cluster age of the entire population, but - instead - the colour combination of a given set of individual (luminous) stars. Consequently, in this case cluster ages and masses cannot be obtained self-consistently (although this caveat is largely ignored in most studies using SED fits to obtain cluster ages).
Figure 6 shows the LLL values as a function of age for the different filters used in this paper. These luminosities were obtained by identifying the most luminous star on each isochrone for the relevant passband. The dark-grey area corresponds to the ``source-dominated'' clusters (cf. Fig. 3), assuming a distance D = 3.9 Mpc to M 82. The light-grey area shows the cluster's maximum absolute luminosity, assuming an extinction of mag (roughly matching the mean extinction value of Melo et al. 2005; see also Mayya et al. 2008). The upper luminosity limit has been corrected for extinction using , and , i.e., the corresponding corrections for a G2V-type star using a Cardelli et al. (1989) extinction law and a total-to-selective extinction ratio, RV=3.1.
|Figure 6: Lowest-luminosity limit for the ACS/WFC filters used here. The dark-grey area corresponds to the ``source-dominated'' clusters (Fig. 3), assuming a distance to M 82 of D= 3.9 Mpc. The light-grey area shows the cluster's maximum absolute magnitude assuming an extinction of mag. See the text for details.
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We see that most of our clusters lie below the LLL, except in the age range around 2.5-6 Myr. When an extinction correction of mag is used, most clusters still lie below the LLL, particularly in the I band. This means that, in general, none of our clusters can host the most luminous star that would be present theoretically for the given cluster age. This does not mean, however, that our sample clusters cannot host the occasional massive, evolved, red star (see for examples, e.g., Bruhweiler et al. 2003; Jamet et al. 2004; Pellerin 2006). However, in this case, gaps in the sampling of the cluster mass function are an a posteriori consequence of applying the LLL test.
In the previous section we established that our clusters are affected by strong IMF sampling effects, so that age and mass estimates based on direct comparisons with SSP mean values are not valid (although we will show below what one would conclude in terms of cluster ages and the implications for the cluster-formation history in the centre of M 82 if we were to ignore this caveat). As an example, red cluster colours could be explained as being caused by the absence of massive stars, but this absence can - in turn - be explained by either an old population in which the massive stars have faded, or a young population without massive stars (at least not to the extent expected theoretically), because of sampling effects (i.e., there are not enough stars to fully populate the massive-star tail of the IMF). In an analogous manner, cluster masses cannot be obtained properly, since the mass-luminosity relation depends on both the age and the cluster mass itself, and both are unknown quantities.
However, we can still obtain partial information about the clusters from their integrated luminosities, taking advantage of the sensitivity of different observables with respect to both stellar populations and individual stars. In doing so, one needs to take into account several basic rules, which we will now discuss.
First, the position of single stars in a colour-colour diagram defines a partial envelope of all possible conditions. As shown by Cerviño & Luridiana (2006), the distribution of any possible integrated luminosity of any cluster containing N stars is the result of Nconsecutive convolutions of the stellar luminosity function (in units of flux). Hence, the possible colour distribution should - eventually - converge to the mean value predicted by the SSP models.
Secondly, there is a smooth transition between the positions of single stars in a colour-colour diagram and the colours of SSPs, and clusters that are more affected by sampling effects at a given age would cover a larger region in colour-colour space than clusters containing more stars (which are, hence, less affected by IMF sampling statistics). In practice, this situation can be visualised as a gradual collapse of the possible cluster colours towards the mean SSP prediction.
Thirdly, the colour-colour diagram used should show an asymmetric trend, in the sense that young clusters and hot stars have bluer colours than older clusters and cool stars and, in general, the bluest stars in a cluster correspond to the main-sequence turn off (for simplicity, we choose to ignore issues related to the nebular continuum in photo-ionised clusters here; the main effect of nebular flux would be to lead to redder cluster colours in a similar fashion as reddening due to extinction. As a consequence, some perceived ``intermediate''-age clusters may therefore be young).
These general considerations are shown graphically in Fig. 7.
|Figure 7: Graphical representation of the boundary conditions. The blue track shows the evolution of well-populated SSP models (from the bottom-left corner of the figure to redder colours as a function of increasing age). The black pentagrams highlight SSPs of ages as indicated. The red area defines the region within which only old (108 yr) clusters can reside; similarly, the blue area encompasses the region where we expect only young (5 Myr-old) clusters. The black dots show the positions of extremely underpopulated clusters (i.e., ``clusters'' composed of single stars, based on the isochrones discussed in Sect. 3.1). The green dots represent stars with luminosities below those of the clusters in our sample, whereas the grey dots are stars that are more luminous than our clusters (in any filter). The grey-shaded areas cannot host any clusters, since there is no possible combination of single stars that can produce such cluster colours (see the text for details). The extinction vector for mag is shown for reference.
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Since we are in a situation where not all stars defining the isochrone may be present in the cluster, we are bound by a number of additional rules. In essence, we need to work with the general considerations outlined above, but we also need to take into account only those stars that would be present in the cluster. This leads to two basic rules.
In Fig. 8 we show the colour-colour diagram of the observed clusters in the M 82 nucleus. We have also included the positions of the SSP models and of individual stars for a foreground extinction of and 4 mag, respectively. For mag, it appears that most of the clusters can be explained by an old age (108 yr). However, if we take into account the limitation imposed by the cluster luminosities, none of these clusters can host stars more massive than 6 , and the extreme (B-V) and (V-I) values are 1 mag. In this situation, neither clusters redder than (B-V) = 1 mag, nor those redder than the (V-I) values defined by the SSP models can be explained. This implies that at least some amount of extinction is required to match the distribution of the clusters in colour-colour space.
|Figure 8: Observed colour-colour diagram for the nuclear clusters in M 82. The blue and purple tracks show the evolution of SSP models affected by and 4 mag, respectively; the dark and light-grey dots represent the colours of individual stars affected by similar extinction values. The red shaded area is the region where we would expect only older (108 yr) clusters to be found; the extinction vector for mag is shown for reference.
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For mag, the model curve seems to imply that all clusters are young (5 Myr old). However, this choice of extinction value cannot explain any cluster with (B-V) < 0.5 mag, for which less extinction would be required.
Whatever the case, clusters that are redder in (V-I) than the envelope of the SSP models with variable extinction (i.e., those redder than a line with a slope 1), are most likely explained by the presence of individual stars in the (V-I) tail at (B-V) = 1mag for mag. This tail corresponds to stars older than 100 Myr and, hence, these are ``old'' clusters. In this case, a moderate amount of extinction is needed if the clusters are to host such luminous red stars. However, we note that in view of the significant photometric uncertainties, some of the observed redder clusters could be consistent with younger clusters (107- old) affected by varying amounts of extinction.
Although we are clearly aware of the IMF sampling issues discussed in the previous section, we will now apply the ``standard'' SSP analysis to our cluster photometry, in order to show what effects ignoring IMF sampling effects would have on the derived results. In other words, we will simply obtain the cluster ages (and their masses) assuming that their IMFs are well populated, without resorting to the LLL test discussed above. This will give us a good handle on the age uncertainties introduced by ignoring IMF sampling effects, which we will highlight where appropriate and relevant.
In a series of recent papers, we developed a sophisticated tool for star cluster analysis based on broad-band SEDs, Analy SED, which we tested extensively both internally (de Grijs et al. 2003a,b; Anders et al. 2004b) and externally (de Grijs et al. 2005), using both theoretical and observed young to intermediate-age (3 ) star cluster SEDs, and the GALEV SSP models (Kurth et al. 1999; Schulz et al. 2002). The accuracy has been further increased for younger ages by the inclusion of an extensive set of nebular emission lines, as well as gaseous continuum emission (Anders & Fritze-von Alvensleben 2003). We concluded that the relative ages and masses within a given cluster system can be determined to a very high accuracy, depending on the specific combination of passbands used (Anders et al. 2004b). Even when comparing the results of different groups using the same data set, we can retrieve any prominent features in the cluster age and mass distributions to within and , respectively (de Grijs et al. 2005), which confirms that we understand the uncertainties associated with the use of our Analy SED tool to a very high degree - provided that our sample clusters have well-populated IMFs.
We therefore applied the Analy SED approach to our full set of broad-band UBVI cluster SEDs (we note that U-band photometry is only available for a subset of 127 clusters), assuming a Kroupa (2001) IMF (with a low-mass cut-off at 0.1 ) and Padova isochrones. Four-passband photometry is, in general, sufficient to yield robust cluster parameters with reasonable uncertainties (Anders et al. 2004b). However, given the highly variable galactic background in our field of view (see Fig. 1), we decided to fix the model cluster metallicities to the solar value, leaving both the cluster ages and extinction values as free parameters. The shape of the broad-band SEDs constrains the ages and extinction values, whereas the absolute flux level results in the corresponding cluster masses. Despite the significant photometric uncertainties, generally caused by the highly variable background, our SED matching approach was fairly successful in converging to a reasonably well-determined set of ages: of the 152 cluster candidates selected, we obtained ages for 142.
|Figure 9: (Top left and bottom left) Age and mass distributions of the clusters in the M 82 starburst core, based on the straightforward application of SED matching using standard SSP models; top right and bottom right: full () uncertainty ranges in age and mass, as a function of cluster age and mass, respectively. See the text for details.
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The resulting histogram of the best-fitting cluster ages is shown in the top left-hand panel of Fig. 9. The cluster age distribution shows a peak around log( Age / yr ) , with a broad distribution (of order 40% of the sample clusters) extending towards younger ages. Whether or not the apparent peak(s) at younger ages is (are) real depends on the uncertainties in our age estimates. The Analy SED output also provides realistic () uncertainty estimates (see Anders et al. 2004b). In the top right-hand panel of Fig. 9 we visualise the full uncertainty ranges for all our clusters, as a function of age. We emphasise that these uncertainties represent the full range from the minimum to the maximum ages allowed by the fitting routines; because of the logarithmic representation, we note that the uncertainty ranges are asymmetrical, however, so that it is impractical to show average values. As an aside, we also note that our results are not dominated by the age-extinction degeneracy inherent to the use of broad-band photometry, given that there is no discernible trend between the resulting cluster ages and their extinction values (a trend would be expected if this degeneracy were important). The use of both the U-band filter and a red optical passband (I) minimises any residual age-extinction degeneracy (e.g., Anders et al. 2004b).
We will now use these uncertainty estimates to provide an independent cross-check on the accuracy of our age determinations. Cluster A1 was found to have an age of Myr (and E(B-V) = 0.85+0.05-0.65 mag), which is - given the uncertainties - in good agreement with the age estimate of Myr of Smith et al (2006), based on spectroscopy and for an extinction of mag. For cluster B2-1 (de Grijs et al. 2001; Smith et al. 2006), the age derived here ( Gyr; for E(B-V) = 0.60+0.10-0.20 mag) is also consistent with previous age determinations: Smith et al. (2006) derived for mag (see also Smith et al. 2007), while de Grijs et al. (2001, 2003c) obtained -9.76 based on a small to negligible amount of extinction.
For completeness, the bottom left-hand panel of Fig. 9 shows the corresponding mass distribution of the nuclear M 82 clusters in our sample. This shows that there is a broad distribution of cluster masses around 105 , not too dissimilar to the cluster mass distribution in the post-starburst region ``B'' some 0.5-1.0 kpc from the centre of M 82 (e.g., de Grijs et al. 2001, 2003c). Although there is a non-negligible fraction of clusters more massive than 106 (which may, hence, qualify as SSCs), there is also a significant complement of fairly low-mass objects, down to 103 . The bottom right-hand panel shows the full mass ranges obtained for our sample clusters from the Analy SED fits, in a similar visualisation as shown in the top right-hand panel for the age uncertainties. A quick comparison of the general differences between both right-hand panels shows that, indeed, the average uncertainties in the cluster masses are relatively smaller than those for the ages, at least for masses 105 (in support of de Grijs et al. 2005).
We are fortunate in also having obtained an H image of the galaxy's starburst core. The addition of H photometry allows us to determine the number of sample clusters showing an Hexcess, which in turn will help us to constrain the cluster ages to 8 Myr. Of the 152 clusters in our sample, nineteen show a clear H excess exceeding the 1 photometric uncertainties of the clusters' total H flux. This relatively small number does not necessarily imply that most objects are faint in H flux, but rather that the photometric uncertainties are generally significant due to the highly variable background (see Fig. 1). For those clusters with a statistically significant H excess, the corresponding ages based on their broad-band SEDs are in all cases consistent with them being younger than 10 Myr.
Of these 19 clusters with a significant H excess, twelve are located in or near region C. This is consistent with the observation that region C might be the youngest part of the starburst (Sect. 2.2), although our age resolution does not allow us to conclude this robustly; for all practical purposes, we may assume that regions A and C are of similar (young) age (see also O'Connell & Mangano 1978; O'Connell et al. 1995). Alternatively, region C may represent the actual core region generating the minor-axis H ``plume'' coincident with the minor-axis ``superwind'' (cf. McCarthy et al. 1987; O'Connell et al. 1995; Westmoquette et al. 2007b). The right-hand panel of Fig. 4 shows the distribution of the H excess across the entire region. In this representation, region C clearly stands out in H emission, so it may indeed be the youngest core region.
We have presented high-resolution HST/ACS imaging in four filters (Johnson-Cousins equivalent B, V, and I broad bands, and an H narrow-band filter), as well as subsequently acquired U-band images, of the nuclear starburst region of M 82. The high spatial resolution of the HST images has allowed us to explore the central area of this galaxy in unparalleled detail. We find a complex system of 150 star clusters in the inner few 100 pc of M 82, encompassing sections A, C, D, and E (O'Connell & Mangano 1978). At face value, the resulting cluster age distribution gives us a strong handle on the global star cluster formation intensity across the galaxy's core region, which can then be compared to the field-star formation history.
As the archetypal local starburst galaxy, M 82 is believed to have undergone a tidal interaction with its neighbour, M81, 108 yr ago (e.g., Gottesman & Weliachew 1977; O'Connell & Mangano 1978; Lo et al. 1987; Yun et al. 1993, 1994), providing the means of activation of the intense episodes of starburst activity witnessed in M 82. It has been suggested that this interaction led to the ISM of M 82 experiencing large-scale torques, coupled with a loss of angular momentum as it was transferred towards the dynamical centre of the galaxy (FS03; also based on numerical simulations: e.g., Sundelius et al. 1987; Noguchi 1987, 1988; Mihos & Hernquist 1996). This led to an increased cloud-cloud collision rate in the disk of the galaxy, and large amounts of material accumulating and undergoing compression in the innermost regions, perhaps resulting in the first starburst episode (FS03).
We find (tentative) evidence of an enhanced cluster-formation epoch associated with the first starburst event (although we caution that the age uncertainties are significant), believed to have occurred about 100 Myr ago (or possibly as recently as 30 Myr ago; Rieke et al. 1993). We do not find any strong evidence of enhanced star cluster formation at an age of 5 Myr, however, believed to be the epoch when the more recent starburst event transpired in the region (FS03; supported by Smith et al. 2006). Perhaps this is due to the relatively small region studied here, in that it could be possible that the clusters analysed are not spatially associated with the more recent starburst event.
Förster Schreiber et al. (2003) indeed suggest that the two events took place in different regions, with the first happening in the centre of M 82 and the second occurring predominantly in a circumnuclear ring and along the stellar bar. Alternatively, it could be the case that cluster formation is not always coincident with enhanced star-formation episodes. This type of scenario is, in fact, not unreasonable to expect, as evidenced by, e.g., the observed disparities between the cluster and field-star age distributions in the Magellanic Clouds and in NGC 1569 (see Anders et al. 2004a, for a discussion regarding the latter galaxy). In particular, the Large Magellanic Cloud exhibits a well-known gap in the cluster age distribution, yet the age distribution of the field stellar population appears more continuous; the field-star and cluster formation histories are clearly very different (e.g., Olszewski et al. 1996; Geha et al. 1998; Sarajedini 1998, and references therein). Although the case is less clear-cut for the Small Magellanic Cloud, Rafelski & Zaritsky (2005) provide tentative evidence that the cluster and field-star age distributions are also significantly different in this system (see also Gieles et al. 2007).
We caution, however, that our cluster age estimates may be severely affected by IMF stochasticity, given that the luminosities of most of our sample clusters imply that their mass functions are not fully sampled up to the most luminous stars included in the theoretical stellar isochrones. We show the effects of statistical IMF sampling issues in colour-colour space. This should be taken as a strong warning to anyone (including ourselves) attempting to apply standard SSP analysis to integrated cluster photometry of any but the most massive star clusters. As a consequence, the age estimates derived based on standard SSP analysis should be taken with extreme caution. It is most likely that our straightforward SSP-based age determinations are affected by (i) residual effects due to the age-extinction degeneracy, despite the availability of U-band and H observations, and - more importantly - (ii) significant stochastic effects.
It is our intention that this paper be taken by the community as a strong warning to consider stochasticity in the IMF for young clusters with undersampled stellar mass functions much more seriously than has been done to date (including by ourselves; e.g., de Grijs et al. 2003a,b).
We thank Peter Anders for his help with the analysis of our broad-band cluster photometry. S.B. thanks Sarah Moll for her help using the ISHAPE function of BAOLAB. S.B. and R.d.G. thank Paul Kerry for his invaluable help with all sorts of software-related issues. R.d.G. acknowledges useful discussions with Simon Goodwin, and hospitality at and research support from the International Space Science Institute in Bern (Switzerland). M.C. is supported by the Spanish MCyT and by FEDER funding of project AYA2007-64712, and by a Ramón y Cajal fellowship. The CMD2.0 tool was developed by Leo Girardi. We are grateful to the anonymous referee for a careful and constructive report that led to significant improvements in both our interpretation and the presentation of our results. This paper is based on archival observations with the NASA/ESA Hubble Space Telescope, obtained at the Space Telescope Science Institute (STScI), which is operated by the Association of Universities for Research in Astronomy, Inc. (AURA), under NASA contract NAS5-26555. This research project was funded by the Nuffield Foundation through Undergraduate Summer Bursary URB/34412. This research has made use of NASA's Astrophysics Data System Abstract Service.


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SDG12 Top Tips: How to embrace circular business models
Changing your business model from a linear take, make, dispose model can seem daunting, but there are concrete steps any business can take in pursuit of SDG12
Circularity requires the rethinking of products and services across their whole lifecycle in order to make them more durable, renewable, reusable, repairable or upgradable, and recyclable.
It is a daunting challenge for any business, requiring a fundamental re-think of how they design products and services, operate on a day to day basis, and execute long term strategies.
However, without such drastic reforms the pursuit of SDG12 and its vision of sustainable production and consumption becomes impossible.
How then can organisations transition away from resource flows and models that have defined their operations for decades, if not centuries, and deliver genuinely circular business models?
A good place to start, according to experts, is to analyse the biggest impacts and opportunities across the lifecycle of products and services. Think about the energy, materials, and water that the business is reliant on, and how the production and consumption of those core elements impacts nature.
Companies can then take this information and apply circular principles to design out waste, increase resource productivity, and decouple growth from natural resource consumption.
This is, of course, much easier said than done. As such BusinessGreen spoke to circular economy experts to get their top tips on where businesses should start as they develop a circular SDG12 strategy.
Target, measure, act
"Be really clear what your environmental impacts are, and measure them," advises Dr Richard Swannell, development director at WRAP. Start by measuring waste, then you quickly realise the scale of the opportunity for reducing it, and can act on that information, he says.
He also recommends that this audit process should extend beyond the organisation's four walls. "Work internally, then with your suppliers, and your customers," he says. "You begin to start to encourage system-wide change by your own actions as a business."
Gudrun Cartwright, environment director at Business in the Community, agrees accurate measurement of resource use and the establishment of a baseline is critical. "Once you know where your key challenges and opportunities are, set targets to address the issues most material to your business," he says. "It may be that these are not in your own operations, but that working with suppliers and customers will create the best impact."
He also advises that any targets eventually need to move belong per capita or resource intensity metrics. "Ultimately we need absolute change, not just relative to production units or sales," he argues.
Get over the fear
"A lot of businesses are paralysed by this goal, it touches so many products that they do not know where to start," says Claire Brady, programme manager of sustainable business at Bioregional, of the circular economy vision.
Consequently, it is critical to look at how circular economy models can evolve to open up new revenue streams. There are opportunities to build better relationships with customers through subscription-based models, Brady points out. "If you think creatively, there are ways that enable consumers help you close the loop on the flow of resources that are inherent in your product, and almost lock [customers] in through loyalty," she argues.
It's a business strategy
It is the primacy of these new business models that should be at the heart of any circular economy strategy. Stop thinking of the circular economy as an environmental strategy, advises Brendan Edgerton, director of circular economy, World Business Council for Sustainable Development. "There are environmental benefits that come with a circular model, but chief executives can recognise the opportunity and the economic value that it could bring through aligning financial and environmental priorities," he argues.
It is by highlighting the commercial benefits that support for circular economy models can be secured.
Look at the longer-term impacts
To ensure a product has a lower environmental impact during its production and consumption, you have to think through the whole lifecycle, including delivery to customer and end of life, says Beverley Cornaby, programme manager at the Cambridge Institute for Sustainability Leadership.
"Maybe your actual product is very sustainable, but is not delivered in a sustainable way," she observes. "What is your consumer base going to accept? What are the implications if it doesn't get properly managed at end of life? Then you're looking at a reuse model, or a different type of recycling. You're looking at trade-offs. There aren't straightforward answers at the moment."
Any credible circular economy model needs to recognise that there are lots of different scenarios that have to be modelled and managed.
Wipe the slate clean
Pentatonic undertakes thought experiments with clients, asking them to forget the experience they have gained through years in their sector, and think instead about how they would design the product now.
For example a skirt made of several different materials, including a metal button, represents a major recycling challenge that could easily be averted at the design stage. "You don't need to work out how to recycle the metal, just change the material it's made of," says Philip Mossop, chief operating officer at Pentatonic. "Bringing in a third party with no preconceptions can be the easiest way to get the answer."
Embed circularity across the business
You cannot create circularity as a silo within an organisation, continues Mossop. "Companies come to us with their sustainability team," he says. "But we need to meet the marketing manager, the operations manager, the service manager. Sustainability might affect some parts of the business more than others, but it has to be immersed across the business, not be seen as a silo."
Collaborate widely
Like most of the SDGs, sustainable production and consumption can not be engineered in isolation. Policymakers, customers, investors, and multiple businesses in lengthy global supply chains all have a role to play in developing truly circular industries.
Cartright recommends that any business serious about pursuing SDG12 needs to "engage your employees in creating an innovation culture, work with your suppliers to find new materials and methods, and make it easy for your customers to play their part in solving our shared challenges". Ultimately, SDG12 encompasses everyone.
Tap the resource base
Beyond the recommendations offered by the experts we spoke to a number of major reports have been produced by organisations working on the circular economy to help businesses get started or advance their strategies on sustainable consumption and production. For example, the New Big Circle by the World Business Council for Sustainable Development, the Circular Economy, Cracking the Challenge from Bioregional, and the Circular Office Guide by Business in the Community. They are all worth checking out.
More news
Global briefing: Al Gore launches climate concerned voter registration drive
All the green business news from around the world this week
'Long overdue': Financial Reporting Council to launch sweeping review of corporate climate disclosures and auditing practices
Financial accounting watchdog stresses companies already have a responsibility to report on environmental impacts and climate risks, as major new review hints at stronger enforcement action down the line
Finding a natural sense of urgency to act
Mike Hower takes a biomimicry hike and reflects on what sustainability executives can learn from the desert
General Mills, Danone dig deeper into regenerative agriculture with incentives, funding
Food giants cultivate new pilots and financing programs


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