It has been a while since I last discussed the so-called 'GZK' neutrinos, neutrinos which are produced when ultra-high energy cosmic-rays interact with cosmic microwave background (CMB) photons. As you may recall, CMBR photons were produced during the big bang; they have cooled off during the roughly 14 billion years since then. They are now mostly at microwave frequencies, with a peak at 6.6 GHz, corresponding to an average photon energy of 0.00024 electron Volt, or a temperature of 2.725 degrees Kelvin (i.e. above absolute zero). Although this is not much energy, it can be enough to excite ultra-high energy protons into a state called the Delta-plus (basically an excited proton). When the Delta-plus decays, it produces a proton and a neutral pion, or a neutron and a positively charged pion. When the positively charged pions decay, they produce a neutrino and a muon; when the muon decays, it produces two more neutrinos and an electron.
We know that ultra-high energy cosmic rays exist, and we know that CMB photons exist, so these are often considered to be a 'guaranteed' source of neutrinos. These neutrinos are the main goal of radio-detection experiments like ARIANNA, ARA and, of course, ANITA. However, there are a few caveats. If the highest energy cosmic rays are mostly iron, rather than protons, then the flux of these GZK neutrinos will be drastically reduced, below the point where these experiments can see them. Also GZK neutrinos have been produced continuously since the early universe (and are almost never absorbed), so the number of GZK neutrinos existing today depends on how many ultra-energetic cosmic-rays there were in the early universe; this is a much smaller uncertainty than due to the proton vs. iron (or something in between) question.
Until recently, all searches have been negative. The one possible exception is an anomalous event observed by the ANITA experiment, the fourth, 'anomalous' event in their recent paper. I have previously discussed ANITA; this event emerged from a reanalysis of data from their first flight. The ANITA Collaboration describes the event as consistent from a primary source that emerged from the earth; this might be from a neutrino or a long-lived tau lepton. The tau lepton could have been produced in an air shower, and travelled through the Earth, before emerging to produce this shower. The event could also be a mis-reconstructed downward-going shower. Although the event is very interesting, we do see the difficulty of trying to draw conclusions based on one event. It is also clear that the ANITA collaboration feels this difficulty; the event is one of four presented in a paper on downward-going cosmic-rays, rather than highlighted on its own.
Of course, IceCube is also looking for GZK neutrinos. Our latest search, based on 6 years of data, has recently appeared here. To cut to the chase, we didn't find any GZK neutrinos; the analysis did find two lower energy (by GZK standards) events, including the previously announced energy champ. From this non-detection, we set limits that are finally reaching the 'interesting' region. The plot below shows our upper limits as a function of energy, compared with several models.
One needs to be careful in interpreting the curves on the figure. One needs to understand how the curves were made to understand the implications. The limit curve is a 'quasi-differential limit, in decades of energy. Basically, this means that, at each energy, the solid line limit is produced by assuming a continuous neutrino flux with an E^-1 energy spectrum; the E^-1 is chosen to roughly approximate the GZK neutrino flux; more detailed analyses, also given in the paper, use the entire spectrum to calculate 'Model Rejection Factors' to rule out (or not) the different calculations of GZK neutrinos. We are now starting to rule out some models.
Monday, July 25, 2016
Wednesday, July 20, 2016
Funding
One of the most painful parts of being a scientist is searching for money. Funding is a necessary evil, but finding it is getting harder and harder. More and more scientists are chasing a relatively constant pool of money, so the success rates for proposals are dropping.
This is probably most pronounced for the National Institutes of Health, which funds most U. S. health care related research. A blog post by Dr. Michael Lauer, NIH's Deputy Director for Extramural Research, gives some recent, and very sobering numbers. For Fiscal Year 2015, the most recent available, the success rate for new proposals is down to 16.3%, or one proposal in six. For renewals, the success rate is 37.3%, or a bit better than one in three.The new proposal rate has declined precipitously over the past decade or so.
The National Science Foundation, which funds IceCube, and much other basic research in the U.S., the overall success rate is, per a blog post by Jeremy Fox, per principle investigator (not per proposal; some PIs submit multiple proposals) is 35%, or comparable to the NIH renewal rate. These rates are not healthy.
On average, scientists have to write three proposals for each one funded. That's a lot of writing, not to mention work for the reviewers and program managers. Furthermore, it can't be any fun being a program officer at a funding agency and having to tell so many people 'No.'
The low renewal rate makes it very hard to do long-term planning; this may put an unwonted emphasis on short-term results. It also makes it much harder to hire people. Particularly for long-term experiments like IceCube, continuity is important, and it would make no sense to fund one group one year, and a different group the next year. Fortunately, most funding agencies do recognize this, and renewals seem easier than new proposals; at the least, the success rates are higher. On the other hand, it is very difficult for young faculty trying to break into the system.
This discourages "the best and the brightest" (whoever they are) from going into academia. When I was in grad school, academia was the preferred career. We all knew it would be tough, but it seemed viable. Now, many of the best students prefer jobs in Silicon Valley, or the financial industry, or working with "big data." There are multiple reasons, but funding expectations are high on the list. Graduating students should certainly pursue their dreams, but, long term, this is not good for the health of U.S. (or international) science. Beyond this, discouragement trickles down, and the funding situation can discourage bright undergraduates from further science education, steering them toward something with better returns, like finance, law or engineering.
Normally, this would be the point where I would provide some snappy suggestions about how to solve this problem. I don't have any brilliant ideas, but I will share a few thoughts
Contrary to what some science critics say (sometimes loudly), peer review for proposals is generally pretty successful, and I don't see a lot of wasted money in the system.
It is not easy to see how one could asks the scientists with grants to get by with significantly less money. Most of the money goes for graduate students and postdocs. Less money means less science, and, frequently, groups sizes are already smaller than is optimal. By optimal, I mean most efficient. There may be some small gains in getting faculty to work together, using a single grant, but not enough to make major improvements. This will also reduce the breadth of coverage at each university.
One could also try to shift some funding from large facilities (particle accelerators, neutron sources, etc.) toward smaller grants. This makes some sense, in that there is no point in building a large facility if there is no money to operate it, but the large facilities are there for very good reasons. To give one example, many areas of science rely ultra-intense X-ray beams to atomically image all sorts of stuff; producing sufficiently intense X-ray beams requires >$100M facilities. That said, a case could be made that some areas of science would benefit from a little shifting.
Of course, the best solution to the acceptance rate problem is additional funding. Unfortunately, this solution can only come from Congress. Right now, given the current political deadlocks, significant additional funding seem unlikely. But, it can't hurt to contact your senators and representatives.
From the standpoint of individual scientists, the only even partially bright point is that funding may be reaching the point where it is self-limiting. Success rates are so low that universities are forced to acknowledge this when assessing faculty. With less money flowing in, they may be more reluctant to hire new science faculty, and will certainly be forced to limit the number of graduate students, to match the available funding. Long-term, this does not seem healthy for the U. S. STEM (science technology engineering math) enterprise, but it is a natural reaction.
I wish this were more upbeat, but it's not. Next time, I'll focus on something cheerful, like science.
This is probably most pronounced for the National Institutes of Health, which funds most U. S. health care related research. A blog post by Dr. Michael Lauer, NIH's Deputy Director for Extramural Research, gives some recent, and very sobering numbers. For Fiscal Year 2015, the most recent available, the success rate for new proposals is down to 16.3%, or one proposal in six. For renewals, the success rate is 37.3%, or a bit better than one in three.The new proposal rate has declined precipitously over the past decade or so.
The National Science Foundation, which funds IceCube, and much other basic research in the U.S., the overall success rate is, per a blog post by Jeremy Fox, per principle investigator (not per proposal; some PIs submit multiple proposals) is 35%, or comparable to the NIH renewal rate. These rates are not healthy.
On average, scientists have to write three proposals for each one funded. That's a lot of writing, not to mention work for the reviewers and program managers. Furthermore, it can't be any fun being a program officer at a funding agency and having to tell so many people 'No.'
The low renewal rate makes it very hard to do long-term planning; this may put an unwonted emphasis on short-term results. It also makes it much harder to hire people. Particularly for long-term experiments like IceCube, continuity is important, and it would make no sense to fund one group one year, and a different group the next year. Fortunately, most funding agencies do recognize this, and renewals seem easier than new proposals; at the least, the success rates are higher. On the other hand, it is very difficult for young faculty trying to break into the system.
This discourages "the best and the brightest" (whoever they are) from going into academia. When I was in grad school, academia was the preferred career. We all knew it would be tough, but it seemed viable. Now, many of the best students prefer jobs in Silicon Valley, or the financial industry, or working with "big data." There are multiple reasons, but funding expectations are high on the list. Graduating students should certainly pursue their dreams, but, long term, this is not good for the health of U.S. (or international) science. Beyond this, discouragement trickles down, and the funding situation can discourage bright undergraduates from further science education, steering them toward something with better returns, like finance, law or engineering.
Normally, this would be the point where I would provide some snappy suggestions about how to solve this problem. I don't have any brilliant ideas, but I will share a few thoughts
Contrary to what some science critics say (sometimes loudly), peer review for proposals is generally pretty successful, and I don't see a lot of wasted money in the system.
It is not easy to see how one could asks the scientists with grants to get by with significantly less money. Most of the money goes for graduate students and postdocs. Less money means less science, and, frequently, groups sizes are already smaller than is optimal. By optimal, I mean most efficient. There may be some small gains in getting faculty to work together, using a single grant, but not enough to make major improvements. This will also reduce the breadth of coverage at each university.
One could also try to shift some funding from large facilities (particle accelerators, neutron sources, etc.) toward smaller grants. This makes some sense, in that there is no point in building a large facility if there is no money to operate it, but the large facilities are there for very good reasons. To give one example, many areas of science rely ultra-intense X-ray beams to atomically image all sorts of stuff; producing sufficiently intense X-ray beams requires >$100M facilities. That said, a case could be made that some areas of science would benefit from a little shifting.
Of course, the best solution to the acceptance rate problem is additional funding. Unfortunately, this solution can only come from Congress. Right now, given the current political deadlocks, significant additional funding seem unlikely. But, it can't hurt to contact your senators and representatives.
From the standpoint of individual scientists, the only even partially bright point is that funding may be reaching the point where it is self-limiting. Success rates are so low that universities are forced to acknowledge this when assessing faculty. With less money flowing in, they may be more reluctant to hire new science faculty, and will certainly be forced to limit the number of graduate students, to match the available funding. Long-term, this does not seem healthy for the U. S. STEM (science technology engineering math) enterprise, but it is a natural reaction.
I wish this were more upbeat, but it's not. Next time, I'll focus on something cheerful, like science.