2. Innovation in Sensing Bill Priedhorsky 13 September 2010

3. Landscape for innovation (partial) Nano-enabled scintillators and detectors Gamma-ray imaging (Compton) High resolution superconducting detectors Laser-driven sources for active interrogation Nuclear resonance imaging Integrating multiple radiographies Neutrino detection Muon radiography and muonic x-rays THz sources and detectors Quantum detectors: B, gravity, gradiometry Smart, mobile detectors to overcome R 2 Stable isotopics at a particular molecular site Grain-level chemical history Biochemical perturbations in plants and animals Ideas from LDRD and elsewhere

4. Example: Detection of nuclear radiations sounds easy… Gammas or neutrons from a nuclear threat

5. …but backgrounds can be crippling Same source in the presence of background Can anything be done? Yes!

6. 1. Get more signal with a bigger detector Same source, same background, 30 times larger detector Very large detectors

7. 2. Reduce the background Same source, 10 x less background (imaging or spectroscopic detector) Quantum-dot activated scintillator and semiconductor detectors

8. 3. Make the source brighter Source 10x brighter Active interrogation Event Bring sensor closer – distributed sensor nets

9. 4. Look at its shadow (radiography) Radiographic image Muon radiograph (C-clamp)

10. Analyzing possibilities for improvement S min =  min 4 π r 2  E 1/2  √(B  + I) A -1/2 T -1/2 (  fov /  scan ) -1/2  -1 or if B  >> I S min =  min 4 π r 2  E 1/2  B 1/2 A eff -1/2 T -1/2 (  fov /  scan ) -1/2 S min Source emission h s -1 into 4   min Minimum acceptable signal-to-noise rSource range cm  E Detector energy resolution keV  Detector angular resolution radians (pixel solid angle =  2 ) BDiffuse background h cm -2 s -1 keV -1 sr -1  Detector efficiency IIntrinsic detector background counts cm -2 s -1 keV -1 sr -1 ADetector area cm 2 A eff Detector effective area cm 2 TTotal observation time s  fov Solid angle viewed at any instant sr  scan Total solid angle to be monitored sr Detection of narrow-line point source

11. Points of leverage S min =  min 4 π r 2  E 1/2  B 1/2 A eff -1/2 T -1/2 (  fov /  scan ) -1/2 Spectral resolution Untangle complex spectra Proximity Angular resolution Untangle confused regions, map Area Brute force not much help Instantaneous f.o.v. Capture fast events Not captured in equation High time resolution Typically photon-limited Fast response multi-spectral Transient multi-physics

12. Landscape for innovation (repris) Nano-enabled scintillators and detectors Gamma-ray imaging (Compton) High resolution superconducting detectors Laser-driven sources for active interrogation Nuclear resonance imaging Integrating multiple radiographies Neutrino detection Muon radiography and muonic x-rays THz sources and detectors Quantum detectors: B, gravity, gradiometry Smart, mobile detectors to overcome R 2 Stable isotopics at a particular molecular site Grain-level chemical history Biochemical perturbations in plants and animals Ideas from LDRD and elsewhere

13. Cryogenic Microcalorimeters: First measurement of 235 U and 226 Ra splitting Courtesy Mike Rabin

14. Laser acceleration approaches 1 GeV/AMU Courtesy Mike Rabin  C +6 ions beam co-move with accelerating field  Highest energy ions propagate at an angle off laser axis  C +6 ions beam co-move with accelerating field  Highest energy ions propagate at an angle off laser axis  C +6 ions beam co-move with accelerating field  Highest energy ions propagate at an angle off laser axis  C +6 ions beam co-move with accelerating field  Highest energy ions propagate at an angle off laser axis courtesy K. Flippo

15. Mobility allows smart search & detection Simulated model-driven search. Belief in source location evolves with time, quickly converging on the correct (leftmost) bin A. Klimenko, W. Priedhorsky, N. Hengartner, and K. Borozdin, “Efficient Strategies for Low Statistics Nuclear Searches”, IEEE Trans. Nucl. Sci., (2006) time source bin background bins

16. Simulated smart search performance A. Klimenko, W. Priedhorsky, N. Hengartner, and K. Borozdin, “Efficient Strategies for Low Statistics Nuclear Searches”, IEEE Trans. Nucl. Sci. (2006) Smart search Not-so-smart search

17. Distributed sensors face reality Fundamental issues –Power –Communications –Placement and localization –Reliability –Sensor miniaturization –Security Watch for commercial developments!

18. Vision: ask questions of a model, not a measurement Model Measurement World Measurements drive the model The needs of the model drive measurement Users should interact with the model Not with the measurements

19. Collaborate across disciplines – but thoughtfully Wolfgang Pauli Nobel Physics 1945 Physics: Postulates neutrino Chemistry: Exclusion principle essential to electron orbitals She runs off with a chemist 1930 Marries Berlin dancer Käthe Deppner 1929

20. Backup slides

21. Detection faces problems of scale Cuba 1962: 0.1 km 2 missile field in a 100,000 km 2 country Terrorism today: 1 m 2 target in a 1,000,000 km 2 region Cuba 1962 Afghanistan/Pakistan today