Quantum Oracles Jesse Dhillon, Ben Schmid, & Lin Xu CS/Phys C191 Final Project December 1, 2005.
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Transcript of Quantum Oracles Jesse Dhillon, Ben Schmid, & Lin Xu CS/Phys C191 Final Project December 1, 2005.
![Page 1: Quantum Oracles Jesse Dhillon, Ben Schmid, & Lin Xu CS/Phys C191 Final Project December 1, 2005.](https://reader030.fdocuments.in/reader030/viewer/2022032800/56649d4d5503460f94a2b692/html5/thumbnails/1.jpg)
Quantum
Oracles
Jesse Dhillon, Ben Schmid, & Lin XuCS/Phys C191 Final Project
December 1, 2005
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Introduction
• An oracle is the portion of an algorithm which can be regarded as a “black box” whose behavior can be relied upon
– Theoretically, its implementation does not need to be specified
– However, in practice, the implementation must be considered
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Introduction
• Why do we use oracles?
– Allows complexity comparisons between quantum and classical algorithms
– Conceptually simplifies algorithms
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Oracle Challenges
• Criteria for a good oracle implementation
Speed
Generality
Feasibility
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Speed
• Oracle has to be fast or it may simply be hiding exponential expense of your algorithm in a black box
• For example, imagine an oracle for an algorithm for finding primes in a given range
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Generality
• Oracles test for answer– Implies reconfiguration of the oracle for each
question
• Feasible?
• Consider 1940s classical computers, compared to modern ones– First computers could only do specific tasks
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Feasibility
• QC supposed to be exponential speedup
• However, when n is small, exponential speedup is lost in overhead
• Intimately tied to method of physical realization
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Physical Implementations
• Survey of different proposed and realized oracle implementations
Optical
Josephson junctions
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Optical
• Is optical truly quantum?– Exponential increase in hardware
requirements as qubit count increases– Entanglement?
• Effects of entanglement, without ability to test Bell-inequality
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Optical
• But,– Very long coherence times– Single-qubit gates are easy to implement– Scalable cNOT and cSIGN have been
demonstrated
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Grover’s Optical Oracle
• Oracle in used in optical implementation of Grover’s search– Encoded with a marked state, flips the sign of
that state
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Grover’s Optical Oracle
• Oracles demonstrated so far– Toy implementations, do not actually search
through a database– Has a significant failure rate
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Optical Oracles
• Programming an optical oracle is currently achievable– Uses beam splitters, wave plates, diffraction
gratings, etc.
• Research suggests in certain cases, sub-exponential scalability may be possible
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Josephson Charge Qubits
• Superconducting islands coupled via Josephson junctions
• Control of Voltage and Flux allow construction of any single or 2-qubit gate
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How many possible oracles for general n-qubit test?Many!!
4 qubit Deutsch-Jozsa
1. Initialize
2. Hn
3. Oracle: |x(-1)f(x)|x4. Hn
5. Measure
• Determine whether a function f:{0,1}N {0,1}
• Oracle encodes a single function
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Single Qubit Gates
Z-rotations generated via charging voltage & time
X-rotations with zero charging voltage, andcontrolled by Josephson energy and time
These two gates allow construction of any single qubit gatei.e. Hadamard
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2 Qubit Gates
CNOT is universal: now we can build the Oracle!
Control Flux in interaction SQUID
Control time of interaction
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Constructing the Oracle
• Constructed of CNOT and controllable phase shifts
• Note: only nearest neighbor 2-qubit gates– Ring geometry
• Need 2n-1 controllable phase gates to implement any n-qubit Deutsch-Jozsa Oracle
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Josephson v. Optical
• Optical is cheap, simple– Exponential increases with N
• Josephson qubits can be entangled– Can construct any D-J oracle with multiple
2-qubit gates
• Josephson seems to offer better scalability and “true” quantum entanglement– Requires more research– Difficult to manufacture– Reconfigurability?
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References
• N. Schuch & J. Siewert, Phys. Stat. Sol. (b) 233, No. 3, 482-489 (2002)
• J. L. Dodd, T. C. Ralph, & G. J. Milburn, Phys. Rev. A 68, 042328 (2003)
• P. G. Kwait, et al. quant-ph/9905086 v1
• P. Londero, et al. Phys. Rev. A 69, 010302(R) (2004)
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