p no Bhaswati Bhattacharyya On behalf of GHRSS team GHRSS survey and beyond : A SKA pathfinder interferometric survey Bhaswati Bhattacharyya On behalf of GHRSS team

p no Team University of Manchester: Bhaswati Bhattacharyya, Ben Stappers, Jayanta Roy, Mike Keith, Mateusz Malenta, Sally Cooper National Centre for Radio Astrophysics: Jayaram Chengalur, Sanjay Kudale West Virginia University: Maura MacLaughlin National Radio Astronomy Observatory: Scott Ransom Naval Research Laboratory: Paul Ray Ref: Bhattacharyya et al. 2016, ApJ Web page : http://www.jb.man.ac.uk/research/pulsar/Resources/ghrss.html

Prospects (1) PSR (4) RRAT (2) MSP GHRSS survey (3) FRB 1% known of ~105 Population study Emission mechanism Glitches Profile state changes Nulling, intermittency (1) PSR 83 known of ~105 Emission process Link with NS population (4) RRAT (2) MSP GHRSS survey 19 known, Event rate 6x103 FRBs sky-1day-1 Cosmological origin Probe of IGM Spectral index of emission (3) FRB 5% known of ~40,000 Test of gravity Gravitational waves Evolution

GHRSS Parameter space Similar to SKA1 Mid and Low Sky coverage Survey parameters GBT drift scan GBNCC GHRSS Parameter space of GHRSS vs SKA Frequency overlap with SKA1 Mid and Low SKA: Frequency resolution~15 kHz, Time resolution~ 64 μs Real-time compute need for SKA1~10 Peta-Ops (see Jayanta’s talk) Single SKA beam cost similar to GHRSS (~10 Tera-Ops)

GHRSS sensitivity 10% of SKA1 Re-detection of known in-beam pulsars with expected SNR confirms sensitivity Interfrometric vs cataloged flux density Interferometric flux density within ± 50% of catalogue Interferometric calibration by Kudale and Chengalur Discovery rate :12 pulsars in 1500 square degree Areal discovery rate 0.008  one of the highest (GBNCC rate 0.006 Stovall et al.) affected by low number statistics? Present status : 45% completed e confirmed

Pulsar discoveries 12 PSRs (1 MSP)

GHRSS features (1) High resolution mode (2) RFI mitigation J0248+4230 (2.5x sensitivity gain) Zero-DM RFI mitigation: Integrated profile, phasogram of B1007−47  Improvement of SNR a factor of 3 512 ch 61μs Before After Pulse phase Flux Frequency (MHz) 2048 ch 61μs Similar time, frequency resolution as SKA

GHRSS features Pulsars : Discover  Localise  Time Timing Residuals Incoherent array GHRSS features Pulsars : Discover  Localise  Time Phased array (3) Locatisation with gated imaging and timing Enabling phased array observations Timing Residuals 10’’ Localisation Residuals imaging by Chengalur and Roy Time  Time  Convergence in timing with a priori arc-sec position Pulsars discovered with SKA will have positions known up to 50’’

GHRSS features (4) Processing CPU vs GPU pipeline p no GHRSS features (4) Processing GHRSS survey data are concurrently processed by Time-domain acceleration search on GPU cluster using ‘BIFORST’ (developed by Mateusz Malenta) Frequency-domain acceleration search on CPU cluster (Hydrus, IBM) using PRESTO NS-BH NS-NS NS-WD CPU processing GPU processing CPU vs GPU pipeline Acceleration parameter 4x increased for GPU Dedispersion range increases 500 pc cm-3 to 2000 pc cm-3 Maximum acceleration (m/s2) Orbital period (hr)

GHRSS features GPU Processing: A Cluster with 20 Nvidia GTX 980 GPUs set up for GHRSS GPU cluster @ Manchester Benchmark : 0.25 x of real time on GTX 980 (1 hr to process 15 min) CPU pipeline: 192 core takes 10 hr to process 15 min i.e. 100 times less efficient than GPU pipeline (10x on performance X 10x for parameter space)

GHRSS features (5) Machine learning 500 (less RFI) Accuracy ~ 70% Number of Candidates per GHRSS pointing > 5000 (in presence of RFI) Total number of candidates ~ 1 Million Human investigation Difficult Solution : Machine Learning (based on Weka software) Developed by Lyon et al. 2016 Also applied to HTRU and LOFAR very-fast-decision-tree on Accuracy ~ 70%  35 genuine detections, 100% hit rate Trained with GHRSS detections + RFIs Similar methodology as SKA candidate optimisation and machine learning Credit : Rob Lyon

(FRB & RRAT) : No discoveries yet Radio transients (FRB & RRAT) : No discoveries yet FRB detection for GHRSS survey completion (500 hrs on-source time)  at 3 Jy-ms fluence (according to Champion et al. 2016) GHRSS  FRB survey with Interferometer Sensitivity for FRB searches Simultaneous localisation & identify the origin Lorimer Burst GHRSS Sensitivity 1.6 Jy for 10σ for 5ms  parameter space of 4 known FRBs Peak flux density (Jy) Full 500 hrs of GHRSS survey probe ~30% of FRB parameter space. Gives a non detection limit of < 2100 sky-1day-1 Pulse width (ms)

FRB Output of BIFORST pipeline with GPU Searching for dispersed (0-2000 pc cm-3) Bursts (1-100 ms) in quasi-realtime on GPU Output of BIFORST pipeline with GPU GHRSS on FRB parameter space DM (pc cm-3) DM (pc cm-3) SNR Candidate count S min(Jy) DM (pc cm-3) Time (s) Field of View X time (deg2 hr) 300 hrs of GHRSS survey cross single FRB detection line

GHRSS in uGMRT era Parameter space

FRBs with uGMRT No FRB detected < 800 MHz Low frequency search important Sensitivity for FRB searches GHRSS with uGMRT on FRB parameter space Peak flux density (Jy) S min(Jy) Pulse width (ms) Field of View X time (deg2 hr) 100 hrs of GHRSS with uGMRT cross single FRB detection line

Thank you Thank you

GHRSS sensitivity GHRSS green GBNCC blue Survey sensitivity GHRSS green GBNCC blue HTRU magenta Fermi-GMRTcyan Solid line : 50 pc cm -3 Dashed line :100 pc cm-3 Pulsar period (ms) Minimum detectable flux density (mJy) Interferometric flux density within ± 50% of catalogued flux Interferometric flux density (mJy) Interferometric calibration by Kudale and Chengalur Catalogued flux density (mJy) 12 pulsars in 1500 square degree discovered in GHRSS survey Areal discovery rate 0.008  one of the highest (GBNCC rate 0.006 Stovall et al.) affected by low number statistics? Present status : 50% completed with some candidates to be confirmed Related Publications: Survey description and initial discoveries: Bhattacharyya et al. ApJ, 2016 `Biforst’ analysis pipeline and FRBs : Malenta, Bhattacharyya et al. (in preparation)

FRB Event rates and fluence for different surveys

FRB Events/sky/day Frequency (MHz) Parkes VLA GHRSS GBT Molonglo LOFAR MWA No FRB detected < 800 MHz Low frequency search important Spectral index (α) from non-detection (w.r.t. Keane & Petroff 2015) :