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Quantum Control. Quantum compiling Algorithms as closed loop control circuits Correcting quantum errors with unitary operations. Shaped Ultrafast Optical Pumping of NMR Systems. Jason Taylor / Neil Gershenfeld MIT Media Lab Daniel Morris / Phil Bucksbaum University of Michigan.

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Presentation Transcript
quantum control
Quantum Control
  • Quantum compiling
  • Algorithms as closed loop control circuits
  • Correcting quantum errors with unitary operations
shaped ultrafast optical pumping of nmr systems
Shaped Ultrafast Optical Pumping of NMRSystems

Jason Taylor / Neil Gershenfeld

MIT Media Lab

Daniel Morris / Phil Bucksbaum

University of Michigan

goals
goals
  • Increase nuclear polarization
    • Unity polarization would be nice for quantum computers
  • Decrease nuclear polarization
    • Resetting qubits is necessary for quantum error correction
  • Selectively polarize nuclei
nmr biology
NMR & Biology
  • Tools for accessible NMR
    • Table-top NMR (whole systems, amplifiers)
    • Automatic shimming
  • Ultimate goal:
    • Biological structure via NMR
      • Imaging
      • Structure calculations
      • ??
radio frequency graphical models implemented in analog circuits

Radio Frequency Graphical Models Implemented in Analog Circuits

Benjamin Vigoda

MIT Media Lab

soft gates for coding
Soft Gates for Coding

pz(1) = px(1) py(1)

pz(0) = px(0) py(0)

pz(1) = px(0) py(1) + px(1) py(0)

pz(0) = px(0) py(0) + px(1) py(1)

For Binary Symmetric Channel with Hard Decision

pz(x=1|y = 0) = p(x=0|y=1) = 1-A

pz(x=1|y = 1) = p(x=0|y=0) = A

translinear multiplier softgate
Translinear Multiplier SoftGate

Source Referenced Subthreshold MOSFET:

IDS = IO e KSVGS/t (1 – e -VDS/t )

For understanding circuit, think:

IDS = IO e KVGS

Circuit Computes:

pz(1) = px(0) py(1) + px(1) py(0)

pz(0) = px(0) py(0) + px(1) py(1)

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