Lossless Compression of SKA Data Sets

With the size of astronomical data archives continuing to increase at an enormous rate, the providers and end users of astronomical data sets will benefit from effective data compression techniques. This paper explores different lossless data compression techniques and aims to find an optimal compression algorithm to compress astronomical data obtained by the Square Kilometre Array (SKA), which are new and unique in the field of radio astronomy. It was required that the compressed data sets should be lossless and that they should be compressed while the data are being read. The project was carried out in conjunction with the SKA South Africa office. Data compression reduces the time taken and the bandwidth used when transferring files, and it can also reduce the costs involved with data storage. The SKA uses the Hierarchical Data Format (HDF5) to store the data collected from the radio telescopes, with the data used in this study ranging from 29 MB to 9 GB in size. The compression techniques investigated in this study include SZIP, GZIP, the LZF filter, LZ4 and the Fully Adaptive Prediction Error Coder (FAPEC). The algorithms and methods used to perform the compression tests are discussed and the results from the three phases of testing are presented, followed by a brief discussion on those results.

Dish Verification Antenna China for the SKA:design, verification and status

The Square Kilometre Array(SKA) will be the world’s largest synthesis radio telescope, which is designed to answer major scientific questions such as those relating to the cosmic origin and fundamental forces in the universe. With the SKA entering into the phase of pre-construction, more than 100 institutes in about 20 countries including China have been involved in the associated key technology development.The Dish Verification Antenna China(DVA-C) is a concept prototype which has been built to meet the requirements of the SKA’s scientific goals. It utilizes a unique skin-and-rib structure with single-piece panel reflectors. This paper presents details on the design and measured performances of DVA-C, as well as the preliminary observational results. Current applications of the DVA-C are also introduced.

Fiber-based multiple-access frequency synchronization via 1f–2f dissemination

Considering the reference frequency dissemination requirements of the Square Kilometre Array telescope（SKA）project,on the basis of the 1f–2f precision frequency synchronization scheme,we propose and demonstrate a fiber-based multiple-access frequency synchronization scheme.The dissemination reference frequency can be recovered at arbitrary nodes along the entire fiber link.It can be applied to antennas close proximity to the SKA central station,and will lead to a better SKA frequency synchronization network.As a performance test,we recover the disseminated 100-MHz reference frequency at an arbitrary node chosen as being 5 km away from the transmitting site.Relative frequency stabilities of2.0×10^（-14）/s and 1.6×10^（-16）/10~4 s are obtained.We also experimentally verify the feasibility of a frequency dissemination link with three access points.

Cosmology with fast radio bursts in the era of SKA

We present a forecast of the cosmological parameter estimation using fast radio bursts(FRBs)from the upcoming Square Kilometre Array(SKA),focusing on the issues of dark energy,the Hubble constant,and baryon density.We simulate 105and 106localized FRBs from a 10-year SKA observation,and find that:(1)using 106FRB data alone can tightly constrain dark-energy equation of state parameters better than CMB+BAO+SNe,providing an independent cosmological probe to explore dark energy;(2)combining the FRB data with gravitational-wave standard siren data from 10-year observation with the Einstein Telescope,the Hubble constant can be constrained to a sub-percent level,serving as a powerful low-redshift probe;(3)using 106FRB data can constrain the baryon density?bh to a precision of~0.1%.Our results indicate that SKA-era FRBs will provide precise cosmological measurements to shed light on both dark energy and the missing baryon problem,and help resolve the Hubble tension.

Science opportunities and challenges associated with SKA big data

The upcoming Square Kilometre Array (SKA) radio telescope will become the largest astronomical observation facility,and is expected to introduce revolutionary changes in major fields of natural sciences.These revolutionary changes help us to answer the fundamental questions related to the origins of the universe,life,cosmic magnetic field,the nature of gravity,and to search for extraterrestrial civilizations [1].

Parallel implementation of w-projection wide-field imaging

w-Projection is a wide-field imaging technique that is widely used in radio synthesis arrays. Processing the wide-field big data generated by the future Square Kilometre Array(SKA) will require significant updates to current methods to significantly reduce the time consumed on data processing. Data loading and gridding are found to be two major time-consuming tasks in w-projection. In this paper, we investigate two parallel methods of accelerating w-projection processing on multiple nodes: the hybrid Message Passing Interface(MPI) and Open Multi-Processing(OpenMP) method based on multicore Central Processing Units(CPUs) and the hybrid MPI and Compute Unified Device Architecture(CUDA)method based on Graphics Processing Units(GPUs). Both methods are successfully employed and operated in various computational environments, confirming their robustness. The experimental results show that the total runtime of both MPI + OpenMP and MPI + CUDA methods is significantly shorter than that of single-thread processing. MPI + CUDA generally shows faster performance when running on multiple nodes than MPI + OpenMP, especially on large numbers of nodes. The single-precision GPU-based processing yields faster computation than the double-precision processing; while the single-and doubleprecision CPU-based processing shows consistent computational performance. The gridding time remarkably increases when the support size of the convolution kernel is larger than 8 and the image size is larger than 2,048 pixels. The present research offers useful guidance for developing SKA imaging pipelines.

Status and progress of China SKA Regional Centre prototype

The Square Kilometre Array(SKA)project consists of delivering two largest radio telescope arrays being built by the SKA Observatory(SKAO),which is an intergovernmental organization bringing together nations from around the world with China being one of the major member countries.The computing resources needed to process,distribute,curate and use the vast amount of data that will be generated by the SKA telescopes are too large for the SKAO to manage on its own.To address this challenge,the SKAO is working with the international community to create a shared,distributed data,computing and networking capability called the SKA Regional Centre Alliance.In this model,the SKAO will be supported by a global network of SKA Regional Centres(SRCs)distributed around the world in its member countries to build an end-to-end science data system that will provide astronomers with high-quality science products.SRCs undertake deep processing,scientific analysis,and long-term storage of the SKA data,as well as user support.China has been actively participating in and promoting the construction of SRCs.This paper introduces the international cooperation and ongoing prototyping of the global SRC network,the basis for the construction of the China SRC and describes in detail the progress of the China SRC prototype.The paper also presents examples of scientific applications of SKA precursor and pathfinder telescopes performed using resources from the China SRC prototype.Finally,the future prospects of the China SRC are presented.

Forecast for weighing neutrinos in cosmology with SKA

We investigate what role the SKA neutral hydrogen(HI)intensity mapping(IM)and galaxy sky surveys will play in weighing neutrinos in cosmology.We use the simulated data of the baryon acoustic oscillation(BAO)measurements from the HI surveys based on SKA1(IM)and SKA2(galaxy)to do the analysis.For the current observations,we use the Planck 2015 cosmic microwave background(CMB)anisotropies observation,the optical BAO measurements,the type Ia supernovae(SN)observation(Pantheon compilation),and the latest H0 measurement.We consider three mass ordering cases for massive neutrinos,i.e.,the normal hierarchy(NH),inverted hierarchy(IH),and degenerate hierarchy(DH)cases.It is found that the SKA observation can significantly improve the constraints on?m and H0.Compared to the current observation,the SKA1 data can improve the constraints on?m by about 33%,and on H0 by about 36%;the SKA2 data can improve the constraints on?m by about 58%,and on H0 by about 66%.It is also found that the SKA observation can only slightly improve the constraints on∑mν.Compared to the current observation,the SKA1 data can improve the constraints on∑mνby about 4%,3%,and 10%,for the NH,IH,and DH cases,respectively;the SKA2 data can improve the constraints on∑mνby about 7%,7%,and 16%,for the NH,IH,and DH cases,respectively.