We show how the execution time of algorithms on quantum computers depends on the architecture of the quantum computer, the choice of algorithms (including subroutines such as arithmetic), and the “clock speed” of the quantum computer. The primary architectural features of interest are the ability to execute multiple gates concurrently, the number of application-level qubits available, and the interconnection network of qubits. We analyze Shor’s al gorithm for factoring large numbers in this context. Our results show that, if arbitrary interconn ection of qubits is possible, a machine with an application-level clock speed of as low as one-third of a (possibly encoded) gate per second could factor a 576-bit number in under one month, potentially outperforming a large network of classical computers. For nearest-neighbor-only architectures, a cl ock speed of around twenty-seven gates per second is required.
[1]
David P. DiVincenzo,et al.
Quantum information and computation
,
2000,
Nature.
[2]
Thomas G. Draper,et al.
A logarithmic-depth quantum carry-lookahead adder
,
2006,
Quantum Inf. Comput..
[3]
Thierry Paul,et al.
Quantum computation and quantum information
,
2007,
Mathematical Structures in Computer Science.
[4]
Phil Gossett.
Quantum Carry-Save Arithmetic
,
1998,
quant-ph/9808061.
[5]
Simon J. Devitt,et al.
Simulations of Shor's algorithm with implications to scaling and quantum error correction
,
2004
.
[6]
Thomas G. Draper,et al.
A new quantum ripple-carry addition circuit
,
2004,
quant-ph/0410184.
[7]
David Thomas,et al.
The Art in Computer Programming
,
2001
.
[8]
G. G. Stokes.
"J."
,
1890,
The New Yale Book of Quotations.