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Viv Kendon Durham University viv.kendon@durham.ac.uk HPC & - PowerPoint PPT Presentation

Hybrid Quantum & Classical Computing JQC & QLM Physics Dept Viv Kendon Durham University viv.kendon@durham.ac.uk HPC & Quantum Summit 2019 (Westminster Hall) Tuesday 5th February 2019 Key collaborators: Susan Stepney (York


  1. Hybrid Quantum & Classical Computing JQC & QLM Physics Dept Viv Kendon Durham University viv.kendon@durham.ac.uk HPC & Quantum Summit 2019 (Westminster Hall) Tuesday 5th February 2019 Key collaborators: Susan Stepney (York Cross-disciplinary Centre for Systems Analysis) Nick Chancellor (UKRI Innovation Fellow, Durham) Funding: EPSRC Fellowship in Quantum T echnologies

  2. Hybrid Quantum Computing February 3, 2019 GOAL: increase computing power . . . ⋆ current computers already very powerful – two barriers to more computing power: 1. silicon chip technology reaching limits 2. energy consumption far from optimal: – resource limits; global warming note these are related: can’t cool Si chips any faster 2/13 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

  3. Hybrid Quantum Computing February 3, 2019 beyond silicon . . . quantum: IBM 5 qubit BZ reaction chemical reservoir computer rat neuron on silicon encoding for DNA computer ⋆ plenty of examples ⋆ 3/13 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

  4. Hybrid Quantum Computing February 3, 2019 hybrid computers . . . practice: co-processors: unconventional: control + substrate: conventional: • quantum • NMR • graphics cards • reservoir • ASIC application-specific integrated circuit • slime mould • FPGA field-programmable gate array ⋆ hybrid computational systems are the norm ⋆ theory: single paradigm: • classical – T uring Machine • analog – Shannon’s GPAC • quantum – gate model, QTM . . . • linear optics (Bosons) [Aaronson/Arkhipov STOC 2011 ECCC TRI-10 170] 4/13 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

  5. Hybrid Quantum Computing February 3, 2019 quantum information processing Quantum Information is built on the idea that: Quantum Logic allows greater efficiency than Classical Logic classical quantum bits, 0 or 1 qubits, α | 0 � + β | 1 � yes or no, binary decisions yes and no, superpositions HEADS or TAILS, random numbers random measurement outcomes ⇒ quantum gives different computation from classical: how different? • computability – what can be computed? • complexity – how efficiently can it be computed? ⇒ quantum computability is the same as classical complexity differs: some problems can be computed more EFFICIENTL Y 5/13 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

  6. Hybrid Quantum Computing February 3, 2019 measurement-based quantum computing [Raussendorf/Briegel PRL 86, 518 (2001)] classical controls integral part of the architecture: control layer base layer Richard Jozsa [ar χ iv:quant-ph/0508124v2] – first to highlight the role of classical processing in quantum computing 6/13 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

  7. Hybrid Quantum Computing February 3, 2019 measurement-based quantum computing Anders/Browne PRL 102 050502 (2009): control computer ⊕ L (parity-L) track parity of each qubit P (universal classical – Clifford group) correlated resource combination gives BQP (universal quantum computing) 7/13 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

  8. Hybrid Quantum Computing February 3, 2019 �������� �������� �������� �������� �������� �������� �������� �������� �������� �������� �������� �������� �������� �������� �������� �������� �������� �������� �������� �������� heterotic Computing �������� �������� �������� �������� �������� �������� �������� �������� �������� �������� �������� �������� from the greek: heterosis ≡ hybrid vigour compose different types of computational devices −→ more powerful hybrid computers characterise in terms of the computational power of the parts – if the whole is more than the sum of the parts: heterotic −→ not specifically quantum: Theo Murphy Meeting at Chicheley Hall 7–8 Nov 2013 Phil. Trans. Royal Soc. A 2015 373 20150091; DOI: 10.1098/rsta.2015.0091. Heterotic computing: exploiting hybrid computational devices 8/13 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

  9. Hybrid Quantum Computing February 3, 2019 reservoir computing use stage engineering stage A Substrate-Independent Framework to Characterise Reservoir Computers , Matthew Dale, Julian F . Miller, Susan Stepney, Martin A. Trefzer ar χ iv:1810.07135 9/13 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

  10. Hybrid Quantum Computing February 3, 2019 hybrid algorithms . . . ⋆ hardware is first step towards maximising computing power . . . algorithms need to exploit the full capabilities of hardware example hybrid quantum-classical algorithms: E X state algorithms match hardware: quantum annealers with limited precision Nick Chancellor: New Journal of Physics 19, 2, 023024 (2017) (local searches) Nick Chancellor: arXiv:1609.05875 (genetic algorithms) 10/13 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

  11. Hybrid Quantum Computing February 3, 2019 quantum computing diversity 11/13 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

  12. Hybrid Quantum Computing February 3, 2019 continuous-time quantum computing QA open family of computational models: em • discrete – qubits for efficient encoding • continuous time evolution using system Hamiltonians noise (high • coupling to low temp bath – open system effects cooling QW AQC unitary −→ makes sense because qubits do superpositions; classical bits don’t Quantum search with hybrid adiabatic-quantum walk algorithms and realistic noise Morley/Chancellor/Bose/VK, to appear in PRA, ar χ iv:1709.00371 12/13 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

  13. Hybrid Quantum Computing February 3, 2019 future of computing: huge investment in silicon: continuing to develop: • squeeze more performance out by making specialised chips • team up with quantum computer developers + quantum co-processors • cloud services and networked devices – chips with everything ( – is your toaster spying on you??) networked embodied hybrid smarter multicore co-processors optimized future −→ diversified 13/13 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

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