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The Long and Short of Quantum Wires

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Title: The Long and Short of Quantum Wires


1
The Long and Short of Quantum Wires
  • In a solid state device
  • Scott Beamer
  • GuanXiong Mao
  • Youming Yang

2
The Basics
  • Different from classical in many ways
  • Consequences of no cloning theorem means no fan
    out and calls for point to point transport of
    data
  • Decoherence (collapse of qubit through
    interaction with surroundings) means that wire
    lengths play a crucial role
  • Long and short range transport go by different
    processes
  • Similar to classical wires in many ways
  • Still used in principle to transport data from
    one location to another
  • Still relies on classical control mechanisms
  • Most practical (as of currently) implementation
    still relies heavily on classical circuitry

3
Ballistic Transport
Collector
Sending Mechanism
?gt
  • Why not
  • Decoherence of qubit state during transport
  • Inability to physically implement sending the
    qubit in many cases

4
Short range (Kane) proposal
  • Electron-coupled Phosphorous ions embedded in
    silicon
  • Qubits interact with nearest neighbor, exchanging
    information one cell at a time
  • Classical controls (AC driven electrodes) are
    placed above the Qubits
  • Latency of roughly 1µs60nm
  • 1µm of wire 17µs
  • Fidelity e-?t
  • ? time per operation (swap)10-6
  • t number of swaps
  • Maximum (error limiting) theoretical wire length
    (Threshold Theorem) 6µm
  • Practical wire length 60nm

5
Long Wires
  • Generally uses shifts to transport the EPR
    pairs
  • But assuming prepipelined EPR pairs (aka constant
    stream of pairs regardless of whether wire is
    being used or not), it can be simply treated as a
    system with entangled pairs available for
    processing
  • -gtLatency only depends on time required to
    perform teleportation 20µs
  • Decoherence e-?x10
  • independent of number of swaps!

6
Teleportation Unit A closer look
  • Key factor is the purification process, which
    creates an asymptotically perfect subset of EPR
    pairs from a set of degraded ones

Data Target
Purification Block
Coded Teleportation
Incoming EPR Pair
Incoming EPR Pair
Near perfect EPR Pairs
Incoming EPR Pair
Entropy Exchange (Provides 0gts)
7
Big Picture
  • When to use which?
  • Long wires require order of magnitude more
    overhead
  • Bandwidth of long wires/short wires e-2?/?
  • Error correction for short wires (swapping) also
    makes them more competitive against long wires
    for short lengths
  • But long wires have better latency past a certain
    point
  • Longer processing time more bandwidth dedicated
    to error correction

8
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9
Architecture Basics
  • Datapath
  • Contains all the data and operators
  • Contains the qubits
  • Control
  • Asserts appropriate control signals at correct
    times to make datapath do appropriate operations
  • Will be done classically for simplicity

10
Example Architecture
  • Implementing Swap Channel for Second Kane
    Architecture
  • Will examine two possible layouts
  • 1-D Configuration
  • 2-D Configuration
  • Both layouts
  • Produce a full duplex wire (bidirectional)
  • Will have one-directional bandwidth (ignoring
    error) that is half the maximum swapping
    frequency
  • Will simplify signals to classical control gates
    to be square
  • Actual signals will be fine tuned for electrons
    and transistor characteristics

11
1-D Configuration Layout
S4
S1
S2
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A1
A2
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Si
P Ion
P Ion
Side View
12
1-D Layout Swap Operations
S4
S1
S2
S4
A1
A2
S1
S3
Time
Hyperfine interaction
13
1-D Layout Swap Timing
Isailovic et al. 2004
14
1-D Layout Swap Control Logic
Isailovic et al. 2004
15
2-D Configuration Layout
S1
S2
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S4
S4
S3
S1
A
A
Si
A
A
P Ion
P Ion
S1
S2
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S3
Top View
16
2-D Layout Swap Operations
S1
S2
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A
A
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Step 1
Step 2
Step 3
Step 4
Hyperfine interaction (Step 5)
17
2-D Layout Swap Timing
Whitney et al. 2003
18
2-D Layout Swap Control Logic
Whitney et al. 2003
19
Comparison
  • At the cost of extra classical control gates
  • Control logic was simplified for 2-D
  • Less space, hardware, and energy
  • Less steps to execute due to parallelism
  • Lower probability of electrons interfering with
    each other since they are kept farther apart
  • Tradeoff
  • Datapath complexity vrs. Control complexity

20
Optimization
  • Use a SIMD approach to speed it up
  • SIMD (Single Instruction Multiple Data)
  • Wire multiple swap cells to same control unit
  • Will work correctly if no other operations need
    to be done

Swap Control
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21
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22
Classical Versus Quantum Correction
  • Classically, we can use the majority voting
    procedure and redundancy to fix any number of
    errors. Example 0-gt000, 1-gt111 allows a maximum
    of 1 error.
  • Given error (bit flip) rate p, this scheme would
    fail with probability 3p2(1-p)p33p2-2p3 so
    for encoding to reduce error rate, we must have
    plt1/2.
  • Quantum Mechanically, we have 3 problems
  • No cloning
  • Errors are continuous
  • Measurement destroys quantum states.

23
Error Correction Conditions and Discretization of
Errors
  • Error E can be decomposed into operations Ei so
    that EpsigtltpsiSi EipsigtltpsiEi
  • Correctable Errors Ei. In order for error
    correction to succeed, we must have PEiEjPaijP
    for some Hermitian a of complex numbers.
  • The basis errors I, X, Z, and Y (XZ) form a
    discrete basis set for a single qubit errors.
  • Thus things like Shor codes can protect against
    any arbitrary single qubit errors.

24
Basic Code Bit-flip
  • Idea is to use a special code, with redudant
    ancillas designed so that a special (syndrome)
    measurement allows us to determine the error
    without collapsing the qubit.

The measurement results correspond to 4
projects P1000gtlt000111gtlt111 P2100gtlt100
011gtlt011 P3010gtlt010101gtlt101 P4001gtlt001
110gtlt110
(Nelson and Chuang)
25
  • The final step is recovery depending on
    measurement result, we flip the corresponding
    qubit.
  • Similarly, a phase-flip code is just a
    Hadamard-conjugated bit-flip code
    (phase-flipºbit-flip in hadamard basis).
  • Shor code is just concatenation of bit flip with
    phase-flip codes
  • where
  • 0gt º(000gt111gt) Ä3/2Ö2
  • and
  • 1gt º(000gt-111gt) Ä3/2Ö2

(Nelson and Chuang)
26
CSS and Steane Code
  • Calderbank-Shor-Steane codes are a class of
    error-correcting codes that uses 2 classical
    linear codes capable of correcting t errors into
    a quantum code capable of correcting t qubits.
  • Steane is the result of CSS used on classical
    Hammond codes.
  • Classical linear codes are compactly described by
    either an n-k by n parity check matrix or a n by
    k generator. Example For Hammond, a 4 bit input
    is converted to a 7 bit code block the parity
    matrix is H 0, 0, 0, 1, 1, 1, 1

  • 0, 1, 1, 0, 0, 1, 1
  • 1, 0, 1, 0, 1, 0, 1

27
Fault Tolerance
  • The aim of fault tolerance is to implement
    circuit gates using encoded gates so that encoded
    qubits do not need to be decoded or measure to be
    acted upon, while at the same time designing
    encoded gates so that errors do not propagate and
    also design similarly fault-tolerant error
    correction procedures.
  • Example UX1UX1UUX1X2U
  • Definition Fault-tolerant procedure is a
    procedure such that given the failure of any one
    component (wire, gate, preparation) causes at
    most 1 error in each encoded output block of
    qubits.

28
Error Model for Fault Tolerance
  • 1)Random Errors We have assumed that the errors
    have no systematiccomponent. Errors that have
    random phases accumulate like a randomwalk, so
    that the probability of error accumulates roughly
    linearly withthe number of gates applied. But it
    the errors have systematic phases,then the error
    amplitude can increase linearly with the number
    of gatesapplied. Hence, for our quantum computer
    to perform well, the ratefor systematic errors
    must meet a more stringent requirement than
    therate for random errors.2)Uncorrelated
    Errors errors are both spatially and temporally
    uncorrelated with each other.3)No leakage
    errors errors considered so far have either
    involved entanglement with the environment or
    some unspecified rotation qubit can leak out of
    2-dimensional Hilbert into larger space we need
    to repeated interrogate qubit for leakage and
    discard/replace4)Limitless supply of fresh
    ancilla qubits5)Error rate independent on number
    of qubits--this is related to physical
    implementation and needs to be tailored.6)
    Maximal parallelism. We have assumed that many
    quantum gates canbe executed in parallel in a
    single time step. This assumption enablesus to
    perform error recovery in all of our code blocks
    at once, and so iscritical for controlling qubit
    storage errors.

29
Fault Tolerant Universal Gate Set
  • The Hadamard, CNOT, P/8, and Phase gate form a
    universal computational set.
  • By the transversal effect, both the encoded (for
    7 qubit Steane Codes) Hadamard and CNOT gates are
    already fault tolerant

(Nelson and Chuang)
30
Similarly, the P/8 gate can be constructed from
(Nelson and Chuang)
Where the ancilla qubit is prepared in state
(0gteip/41gt)/2 through a fault tolerant
measurement of eip/4SX. The phase gate is simply
two application of the P/8 gate.
31
  • We can construct fault tolerant measurements as
    below

(Nelson and Chuang)
32
Concatenation
  • If probability of failure for components at
    lowest code level is p, then for second level,
    its at most cp2 for third level, its c(cp
    2) 2 c3 p4.
  • In general, after k levels of encoding,
    probability is (cp)2k/c with the simulating
    circuiting being of size dk times size of
    original circuit where d is a constant
    representing maximum number of operations need by
    fault tolerant procedure for gate and error
    correction.

(Nelson and Chuang)
33
Threshhold Theorem
  • Theorem A quantum circuit containing p(n) gates
    may be simulated with probability of error at
    most e using O(Poly(log(p(n)/e)p(n)) gates on
    hardware whose components fail with probability
    at most p, provided p is below some constant
    threshold, pltpth and reasonable assumptions about
    the underlying hardware (such as the parallelism
    needed for wide-scale error correction and
    reliable classical computation to process error
    syndromes to determine recovery procedures.
  • Basically says that in theory at least, quantum
    computation is not destined to be error-prone as
    long as we can achieve pth .

34
Practical Example
  • Factoring a 130 digit (430 bit) number would take
    months classically to do.
  • Shor's algorithm would require 54322160 qubits
    and around 3109 Toffoli Gates error per gate
    needs to be less than 10EE-9
  • Steane found that if we use codes of block size
    55 that can correct up to 5 errors and use 400000
    qubits, then we'd need a gate error on the order
    of 10-5.

35
References
  • Datapath and Control for Quantum Wires, Nemanja
    Isailovic, Mark Whitney, Yatish Patel, John
    Kubiatowicz, Dean Copsey, Frederic T. Chong,
    Isaac L. Chuang, and Mark Oskin. Appears in
    Transactions on Architecture and Code
    Optimization (TACO),Vol 1, No. 1, pp 34-61, March
    2004
  • Toward a Scalable, Silicon-Based Quantum
    Computing Architecture, Dean Copsey, Mark Oskin,
    Francois Impens, Tzvetan Metodiev, Andrew Cross,
    Frederic T. Chong, Isaac L. Chuang, and John
    Kubiatowicz, Appears in Journal of Selected
    Topics in Quantum Electronics, Vol 9, No. 6, pp
    1552-1569. November/December 2003

36
References
  • Building Quantum Wires The Long and the Short of
    it, Mark Oskin, Frederic T. Chong, Isaac L.
    Chuang, and John Kubiatowicz. Appears in
    Proceedings of the 30th International Symposium
    on Computer Architecture (ISCA 2003)
  • The Effect of Communication Costs in Solid-State
    Quantum Computing Architectures, Dean Copsey,
    Mark Oskin, Tzvetan Metodiev, Frederic T. Chong,
    Isaac Chuang, and John Kubiatowicz. Appears in
    Proceedings of the 15th ACM Symposium on
    Parallelism in Algorithms and Architectures (SPAA
    2003)

37
References
  • Can we build Classical Control Circuits for
    Silicon Quantum Computers?, Mark Whitney, Yatish
    Patel, Nemanja Isailovic, and John Kubiatowicz. 
    Appears in Proceedings of the Second Workshop in
    Non-Silicon Computing (NSC2), June 2003
  • Nielsen, Michael A. and Chuang, Isaac L. Quantum
    Computation and Information, Chapter 10.
    Cambridge University Press 2000.
  • Preskill, John. Fault Tolerant Quantum
    Computation.
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