New SETI Sky Surveys for Radio Pulses
Andrew Siemiona,d , Joshua Von Korffc , Peter McMahond , Eric Korpelab , Dan Werthimerb,d , David Andersonb , Geoff
Bowera , Jeff Cobbb , Griffin Fostera , Matt Lebofskyb , Joeri van Leeuwena , William Mallardd , Mark Wagnerda University of California, Berkeley - Department of Astronomy, Berkeley, Californiab University of California Berkeley - Space Sciences Laboratory, Berkeley, California
c University of California, Berkeley - Department of Physics, Berkeley, California
d University of California, Berkeley - Berkeley Wireless Research Center, Berkeley, California

Abstract
Berkeley conducts 7 SETI programs at IR, visible and radio wavelengths. Here we review two of the newest efforts,
Astropulse and Fly’s Eye.
A variety of possible sources of microsecond to millisecond radio pulses have been suggested in the last several decades, among them such exotic events as evaporating primordial black holes, hyper-flares from neutron stars,
emissions from cosmic strings or perhaps extraterrestrial civilizations, but to-date few searches have been conductedcapable of detecting them. The recent announcement by Lorimer et al. of the detection of a powerful (≈ 30 Jy) andhighly dispersed (≈ 375 cm−3 pc) radio pulse in Parkes multi-beam survey data has fueled additional interest in suchphenomena.
We are carrying out two searches in hopes of finding and characterizing these uS to mS time scale dispersedradio pulses. These two observing programs are orthogonal in search space; the Allen Telescope Array’s (ATA)”Fly’s Eye” experiment observes a 100 square degree field by pointing each 6m ATA antenna in a different direction;by contrast, the Astropulse sky survey at Arecibo is extremely sensitive but has 1/3,000 of the instantaneous sky
coverage. Astropulse’s multibeam data is transferred via the internet to the computers of millions of volunteers.
These computers perform a coherent de-dispersion analysis faster than the fastest available supercomputers and allow
us to resolve pulses as short as 400 nS. Overall, the Astropulse survey will be 30 times more sensitive than the bestprevious searches. Analysis of results from Astropulse is at a very early stage.
The Fly’s Eye was successfully installed at the ATA in December of 2007, and to-date approximately 450 hours ofobservation has been performed. We have detected three pulsars (B0329+54, B0355+54, B0950+08) and six giant
pulses from the Crab pulsar in our diagnostic pointing data. We have not yet detected any other convincing bursts ofastronomical origin in our survey data.
Key words:

1. Introduction

advanced civilizations that use a lot of energy.

The Berkeley SETI group conducts seven searches at
visible, IR and radio wavelengths, covering a wide variety of signal types and spanning a large range of timescales: SETI@home searches for radio signals withtime scales ranging from mS to seconds. SEVENDIP
searches for nS time scale pulses at visible wavelengths.
ASTROPULSE and Fly’s Eye search for dispersed uS
and mS time scale radio pulses from extraterrestrial
civilizations, pulsars, or evaporating primordial black
holes. SERENDIP and SPOCK search for continuous
narrow band signals in the radio and optical bands respectively. DYSON searches for infrared excess fromSETI@home II, ASTROPULSE and SERENDIP V
are radio sky surveys at the 300 meter Arecibo telescope. Commensal observations have been conductedalmost continuously for the past ten years and are ongoing. Most beams on the sky visible to the Arecibo telescope have been observed four or more times. We rank
SERENDIP and SETI@home candidate signals basedon the number of independent observations, the strengthof the signals, the closeness of the signals in frequency
and sky position, and the proximity to stars, planetarysystems, galaxies, and other interesting astronomical
objects. SETI@home uses the CPU power of volun-

Preprint submitted to Elsevier

November 12, 2008

signal be pulsed, if so at what period? Fully investigating a wide range of these parameters requires innovative instruments and enormous computing power. Another possibility that, until now, has not been included in
SETI searches is that rather than directing large amountsof power into a narrow frequency band, an extraterrestrial intelligence might direct large amounts of power
into a narrow time window by sending a short duration
wide-band pulse. A wide band signal has the advantage of reducing the importance of the choice of observation frequency, and the unavoidable interstellar dispersion of a broad-band pulse reduces the confusion between terrestrial and extraterrestrial pulses. In an ionized medium, high frequencies propagate slightly fasterthan low frequencies at radio frequencies. Therefore RF
pulses will be dispersed in frequency during their travel
through the interstellar medium. The dispersion acrossa bandwidth ∆ν is given by

teered PCs to analyze data. Five million people in 226
countries have participated. Combined, their PCs form
Earth’s second most powerful supercomputer, averaging
482 TeraFLOPs and contributing over two million yearsof CPU time. Here we describe two of the newest SETI
searches, Astropulse and Fly’s Eye.
2. SETI Pulse Searches
One common assumption of SETI is that an alien
civilization wishing to make contact with others would
broadcast a signal that is easily detected and easily distinguished from natural sources of radio emission. One
way of achieving these goals is to send a narrow bandsignal. By concentrating the signal power in a very narrow frequency band, the signal can be made to stand out
among the natural, broad-band sources of noise. By thesame token, signals leaked from a civilization’s internal
communications may be narrow band, but would be significantly weaker than a direct attempt at extraterrestrial
contact.
Because of this, radio SETI efforts have concentrated
on detecting narrow band signals. When searching fornarrow band signals it is best to use a narrow searchwindow (or channel) around a given frequency. The
wider the channel, the more broadband noise is includedin addition to any signal. This broadband noise limits
the sensitivity of the system. Early systems used analog
technology to create narrow bandpass filters that could
observe at a single frequency channel. More recent systems use massive banks of dedicated fast Fourier transform (FFT) processors to separate incoming signals into
up to a billion channels, each of width ∼1 Hz.
There are, however, limitations to this technique. One
limitation is that extraterrestrial signals are unlikely to
be stable in frequency due to accelerations of the transmitter and receiver. For example, a receiver listening forsignals at 1.4 GHz located on the surface of the earth undergoes acceleration of up to 3.4 cm/s2 due to the earth’s
rotation. This corresponds to a Doppler drift rate of 0.16
Hz/s. If uncorrected, an alien transmission would drift
out of a 1 Hz channel in about 6 seconds, effectively limiting the maximum integration time to 6 seconds. Because of the inverse relationship between maximum frequency resolution and integration time (∆ν = ∆t1 ) there
is an effective limit to the frequency resolution that canbe obtained without correcting the received signal forthis effect.
There are other parameters of the signal that are unknown, for example: At what frequency will it be transmitted? What is the bandwidth of the signal? Will theδt = (8.3 µs )∆ν( MHz )DM
ν3 ( GHz )(1)

RL
where dispersion measure DM is defined as 0 ne dl andis usually quoted in units of cm−3 pc.
It is possible that a civilization intentionally creatinga beacon for extraterrestrial astronomers would choose
to create “pulses” which have a negative DM. Natural dispersion always causes higher frequency components to arrive first. A signal in which the low frequencies arrive first would stand out as obviously artificial.
As a check on this, as well as to establish our background noise limit, we examine both positive and negative dispersion cases. Unfortunately, sensitive detectionof broad-band pulses at an unknown dispersion measure
also requires enormous computing power.
We are currently conducting two searches for thesedispersed radio pulses. Astropulse at Arecibo Observatory and Fly’s Eye at the Allen Telescope Array (ATA).
The Allen Telescope Array is a joint project of the SETI
Institute and the University of California, Berkeley [10].
2.1. Pulses from Extraterrestrial Intelligence
Astropulse and Fly’s Eye consider the possibility
that extraterrestrials communicate using high intensity
and wideband but short timescale pulses. It turns outthat both the conventional (narrowband) method of datatransfer assumed by SETI@home and the wideband,
short timescale method assumed by Astropulse andFly’s Eye require the same amount of energy to senda message.
In each case, the energy required to send one bit of
information is proportional to the energy (per area) required to send the minimum detectable signal. And this2

energy is the same for the two methods, so energy considerations cannot rule out short timescale pulses as a
medium for extraterrestrials’ communication.
SETI@home’s sensitivity in searching for narrowband signals is given by:mass M emits radiation like a blackbody with a temperature T BH given by:

ασT sysp
G Npol Btint

This radiation emanates from the black hole event horizon and comes completely from the black hole’s mass.
For a non-accreting black hole, Stefan-Boltzmann
yields a lifetime of:
!3
M
10
(6)
τBH = 10 years
1012 kgT BH =(2)

where α = 2 is a loss from 1-bitting the data twice,σ = 24 is the threshold above noise, T sys = 28 K is
the system temperature, G = 10 K Jy−1 is the gain, andNpol = 1 is the number of polarizations.
SETI@home searches for narrowband signals with abandwidth of 0.075 Hz, and its longest integration timeis (0.075 Hz)−1 = 13.4 s. To compute the energy (perarea) required to send one bit, multiply by Btint = 1 toget 134 · 10−26 J m−2 .
On the other hand, Astropulse and Fly’s Eye aresearching for short pulses, so the sensitivity of these experiments will be given in Jansky microseconds, by aslightly different formula:√ασT sys tint(3)p
G Npol BM ~c3= 10−6
K
8πkGM
M

(5)

For stellar mass black holes, this theory predicts lifetimes of order 1034 years, much too long to ever expect
to observe. However, some cosmologies predict the creation of numerous small (M ∼ 1012 g) primordial black
holes in the early universe, which according to theory
could be evaporating now [17].
The specific mechanism by which the evaporating
black hole produces a strong radio pulse has not been
fully elucidated, but in short, it is thought that the process is similar to the EMP that accompanies supernova explosions. In such a process, a highly conductive plasma fireball expanding into an ambient magnetic
field can exclude the field and create an electromagnetic
pulse. For typical values of the interstellar magnetic
field, this pulse would be peaked near 1GHz [4].
An observation of these pulses would not only provide a significant confirmation of Hawking radiation,
but would also give strong evidence of the existence ofprimordial black holes.

where the variables have the meanings as before, except that now tint is the timescale of the pulse and B theentire bandwidth.
For Astropulse, tint is 0.4 µs and B = 2.5 MHz. Also,
α = 1.4 because Astropulse 1-bits the data only once,
Npol = 2, and σ = 21.5. The resulting sensitivity is
24 Jy µs. To compute the energy per area required tosend one bit, multiply by B = 2.5·106 Hz to get 60·10−26
J m−2 .
For both narrow frequency and broadband pulse
cases, the expression for the minimum detectable energy has the form√
ασT sys Btint(4)p
G Npol√with Btint = 1, so similar answers are expected.
Because these energies are comparable, we havea chance to detect ETI communications in this new
regime.

3. Fly’s Eye: Searching for Bright Pulses with the
ATA
The Allen Telescope Array has several advantages
over other telescopes worldwide for performing transient searches, particularly when the search is for brightpulses. The ATA has 42 independently-steerable dishes,
each 6m in diameter. The beam size for individual
ATA dishes is considerably larger than that for mostother telescopes, such as VLA, NRAO Green Bank,
Parkes, Arecibo, Westerbork and Effelsberg. Thismeans that the ATA can instantaneously observe a farlarger portion of the sky than is possible with othertelescopes. Conversely, when using the ATA dishes
independently, the sensitivity of the ATA is far lower
than that of other telescopes.

2.2. Pulses from Evaporating Black Holes
Another intriguing possible source of short duration
pulses comes from a suggestion by Martin Rees in 1977[44] that primordial black holes, evaporating via the
Hawking Process, could emit a large electromagnetic
signature. According to Hawking [16], a black hole of

The Fly’s Eye instrument was purpose built to searchfor bright radio pulses of millisecond duration at the3

ATA. The instrument consists of 44 independent spectrometers using 11 CASPER IBOBs. Each spectrometer processes a bandwidth of 210MHz, and produces
a 128-channel power spectrum at a rate of 1600Hz(i.e. 1600 spectra are outputted by each spectrometer
per second). Therefore each spectrum represents time
domain data of length 1/1600Hz=0.000625s=0.625ms,
and hence pulses as short as 0.625ms can be resolved1 .
We have to-date performed roughly 400 hours of observing with the Fly’s Eye. Figures 1 and 2 show thebeam pattern and sky coverage using all 42 antennas.

Figure 2: From [? ]. The sky coverage of the ATA for an observing period of 24 hours. Both the coverages for southern and northern pointings (corresponding to the respective contiguous regions) are
shown.

Figure 1: From [? ]. The beam pattern of the 42 beams at ATA,
with the diameters equal to the half-power width. This hexagonal
packing is pointing north. A south pointing results in poor interference
properties, due to the highly populated areas south of the ATA.

3.1. System Architecture
The overall architecture of the Fly’s Eye system isshown in Figure 3. Each IBOB can digitize four analogue signals, and 11 IBOBs are provided so that 44 signals can be processed. The ATA has 42 antennas, eachwith two polarization outputs. A selection2 of 44 of theavailable 84 signals is made, and these are connectedto the 44 iADC inputs. The IBOBs are connected to acontrol computer and a storage computer via a standard
Ethernet switch.
3.2. Fly’s Eye Offline Processing
The analysis required for the Fly’s Eye experimentis, in principle, fairly simple – we wish to search over a
Figure 3: Fly’s Eye System Architecture. A selection of 44 analogue
signals from 42 dual polarization antennas are connected to 44 independent spectrometers implemented in 11 IBOBs.

1 Pulses of duration <0.625ms can also be detected provided thatthey are sufficiently bright, but their length cannot be determined witha precision greater than the single spectrum length.
2 The selection is made with consideration for the goal of maximising field-of-view – in practice we selected at least one polarization
signal from every functioning antenna.

4

wide range of dispersion measures to find large individual pulses. Specifically our processing requires that all
the data be dedispersed with dispersion measures ranging from 50 cm−3 pc to 2000 cm−3 pc. At each dispersion measure the data needs to be searched for ‘bright’
pulses.
The processing chain is in practice significantly
more complicated than this description suggests.
Processing is performed on compute clusters, with
input data formatted, divided and assigned to worker
nodes for processing. In the worker node flow, thedata is equalized, RFI rejection is performed, andfinally a pulse search is performed through the rangeof dispersion measures. The results are written to a
database where they can be subsequently queried. The
key feature of the results is a table that lists, in order ofdecreasing significance, the pulses that were found andthe dispersion measures they were located at.
Average power equalization is performed on the frequency spectrum equalized values P0i (t). We computethe average power over all frequency channels for asingle integration (time sample t). The power average
PN−1 0Pi (t). N is the number
is defined as P0 (t) = N1 i=0of channels (for Fly’s Eye this is always 128). The
motivation for why it is possible to normalize the poweris that we expect pulses to be dispersed over manytime samples, so this procedure should not remove
extraterrestrial pulses.
Our strategy for mitigating constant narrowband RFI
is simply to identify the channels that are affected, andto exclude them from further processing. This channel
rejection is typically performed manually by looking
at a set of spectra and identifying obviously infectedchannels, which are then automatically excluded insubsequent processing runs.
Figure 4: Fly’s Eye Rack at the ATA. Two 6U CompactPCI crates (topand bottom) house the 11 IBOBs. The switch, data recorder computerand storage server are all visible.

Intermittent RFI is often quite difficult to automatically distinguish from genuine astronomical pulses,
and we followed a conservative approach to try toensure that we do not accidentally excise dispersed
pulses. Our statistic for intermittent RFI is the varianceof a single channel overa 10 minute data chunk,2   PT −1 2
1 PT 0 −12000σi = T0 t=0 Pi (t) − T10 t=0P00i (t) . Curvefitting determines a σ2i outside which it is likely thatchannel i contains time-varying RFI. Future reprocessing will likely use a more robust method, such as thatbased on a kurtosis estimator [36].
Our final RFI mitigation technique is manual – in5

our results it is easy to see high-σ hits that are a resultof RFI: these hits appear as simultaneous detections atmany dispersion measures.

3.3. Detection of Giant Pulses from the Crab Nebula
A suitable test of transient detection capability is
to observe the Crab pulsar and attempt to detect giant
pulses from it.
Figure 5 shows a diagnostic plot generated from a
one-hour Crab observation. The data is an incoherently
summed set from the 35 best inputs. The diagnostic
plot was generated after the raw data had been dedispersed using a range of dispersion measures from 5
to 200. The Crab pulsar has dispersion measure ≈ 57
cm−3 pc, so three giant pulses from the Crab pulsar
can be easily identified in the lower plot. The giant
pulses appear only at the expected dispersion measure,
whereas wideband RFI appears across a wide range ofdispersion measures.

Figure 6: A giant pulse from the pulsar in the Crab nebula. This pulse
was detected in a 60-minute dataset taken on 22 December 2007. The
dispersion of the pulse, correctly corresponding to DM = 56.78 cm−3
pc, is clearly visible.

4. Astropulse
4.1. Algorithm
Astropulse uses a unique approach to the problem ofsearching for dispersed pulses. This problem is wellknown to pulsar astronomers, and many solutions havebeen devised over the years. The traditional methodof searching for pulses of unknown dispersion measure(DM) is through incoherent de-dispersion, which is basically a filter bank - for each channel, the power is measured and integrated, then appropriate delays are added
to compensate for the dispersion. This can be made very
efficient through the use of a binary tree type algorithm.
We use a coherent de-dispersion algorithm, which preserves the phase of the signal, thus increasing sensitivity. It also allows us to have much better time resolution (down to the band limit at 0.4 µs ) than incoherent
methods, whose theoretical maximum time resolution
is determined by the individual channel bandwidths. (Inpractice, the time resolution for pulsar searches is typically 100 µs or greater.) The problem with coherent dedispersion is that it is very computationally intensive.
We are able to afford this by implementing the pulse
search in a distributed computing environment.
The coherent de-dispersion process is basically a convolution. The time domain data needs to be convolved
with an appropriate chirp function in order to remove
the dispersion smearing effect.

Figure 5: Diagnostics on data taken from the Crab pulsar in a 60minute observation conducted on 22 December 2007. The data wasdedispersed using dispersion measures ranging from 0 to 200 cm−3
pc. Top-left: single-pulse SNR histogram. Top-centre: noise appears
at all DMs, but bright pulses (SNR> 7) from the Crab correctly appear
at DM ≈ 57 cm−3 pc. Top-right: inset of Figure 6. Bottom: pulse detections plotted on the DM versus time plane. Higher SNR detections
appear as larger circles. Three giant pulses from the Crab are clearlyvisible in this plot.

A frequency vs. time plot of the raw (summed) dataat the time when the brightest giant pulses was detected
is shown in Figure 6. The pulse is clearly visible inthe data, and a fit to the dispersion measure shows thatthe pulse is, nearly without doubt, from the Crab (asopposed to RFI).

t
∆νt)
δt
Here, δt is the amount of time stretching caused bydispersion over a bandwidth of ∆ν, which can be determined from equation 1.
fch (t) = exp(2πiν(t)t) = exp(2πi6The most efficient way to do this is through the useof FFT convolution. Here is a brief description of the
Astropulse detection algorithm:

polarizations (2). Inefficiencies in memory allocation
processes may contribute another factor of 5. In all, 100
TeraFLOP/s or more may be required. For comparison,an average desktop PC can compute at a speed of about
1 GigaFLOP/s.
This analysis does not take into account the amountof computation required for folding. Astropulse folds
on two different time scales, spending enough time onthese to triple the overall computation requirement.
This computation would take far too long on one
computer, or even on a modest sized Beowulf cluster.
Our solution to the problem is to distribute the data
publicly to volunteers who download a program which
will analyze it on their home computers. This is set
up as a screen saver, which will turn on and start computing when their computers would otherwise be idle.
[24] This approach has been remarkably successful for
SETI@home, which has an average computation rate ofabout 40 TeraFLOP/s.
We are able to implement this though the BOINC
software platform, also developed by our group at
Berkeley. The package, the Berkeley Open Infrastructure for Network Computing (BOINC), is a general purpose distributed computing framework. It takes
care of all the “management” aspects inherent to a distributed computing project - keeping records of user accounts, distribution of data and collection of results overthe network, error checking via redundant processing,sending out updates of the science code, etc. Many
lessons learned over the course of running the original SETI@home project went into BOINC, so that newgroups wishing to start computing projects don’t haveto “re-learn” these.
An interesting aspect of running a public distributed
computing project is that it has education and public outreach automatically built into it. People invest
their computer time into the project, and as a result
become interested in learning more about the science.
SETI@home has been enormously successful in this regard - the website averages 1.25 million hits per day,and the project has spawned many internet discussion
groups and independent websites. It is also used as partof the science curriculum by thousands of K-12 teachers
nationwide.

1. Take 13.4 s time-domain data, perform FFT on
32k-sample chunks. Overlap chunks by 50% to recover pulses which span a chunk boundary. Save
results on disk for later use.
2. For each DM,(a) Multiply frequency domain data by correct
chirp.
(b) Inverse FFT to go back to the time domain.
(c) Threshold the (de-dispersed) time data,
recording strong pulses.
(d) Co-add adjacent bins, and threshold to lookfor broad pulses.
(e) Search repeating pulses by using a folding or
harmonic search algorithm.
3. Repeat for next DM.
4. When DM range is covered, start at step 1 for next
13.4 s of data.
The optimal step size for DM is to step by theamount of dispersion which would cause 1 extra timesample length of stretching. Using the above expression for δt = 0.4 µs , this gives us a DM resolution of 0.055 pc cm−3 . We want to cover DMs
from 55 pc cm−3 to 830 pc cm−3 , which corresponds to
14,000 DM steps at this resolution. (DMs smaller thanabout 55 are inaccessible to us, or to any search that
employs one-bit sampling.)
The maximum DM we wish to search determines
the length of the FFTs. We want to look at DM up
to 830 pc cm−3 , which will cover most of the galaxy.
Using the same formula, this is a time stretch of δt =5600 µs , or about 14,000 samples. Our FFT size should
be at least twice this big, so we will use 32k point FFTs.
A FFT takes about 5N log N floating point operations(FLOPs) to compute, where N is the number of points
in the FFT. We are doing N = 215 point FFTs, and weneed to do one inverse transform for each DM, plus one
original forward transform. In addition, there are another N multiplies per DM for the chirp function, anda factor of 2 for the 50% overlap. This makes our total
number of operations for a 32k sample chunk of data:
Nops = 2(NDM + 1)N log N + 2NDM N = 1.8 × 1010

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