29 research outputs found
Fast simulation of quantum algorithms using circuit optimization
Classical simulators play a major role in the development and benchmark of
quantum algorithms and practically any software framework for quantum
computation provides the option of running the algorithms on simulators.
However, the development of quantum simulators was substantially separated from
the rest of the software frameworks which, instead, focus on usability and
compilation. Here, we demonstrate the advantage of co-developing and
integrating simulators and compilers by proposing a specialized compiler pass
to reduce the simulation time for arbitrary circuits. While the concept is
broadly applicable, we present a concrete implementation based on the Intel
Quantum Simulator, a high-performance distributed simulator. As part of this
work, we extend its implementation with additional functionalities related to
the representation of quantum states. The communication overhead is reduced by
changing the order in which state amplitudes are stored in the distributed
memory, a concept analogous to the distinction between local and global qubits
for distributed Schroedinger-type simulators. We then implement a compiler pass
to exploit the novel functionalities by introducing special instructions
governing data movement as part of the quantum circuit. Those instructions
target unique capabilities of simulators and have no analogue in actual quantum
devices. To quantify the advantage, we compare the time required to simulate
random circuits with and without our optimization. The simulation time is
typically halved
On connectivity-dependent resource requirements for digital quantum simulation of -level particles
A primary objective of quantum computation is to efficiently simulate quantum
physics. Scientifically and technologically important quantum Hamiltonians
include those with spin-, vibrational, photonic, and other bosonic degrees
of freedom, i.e. problems composed of or approximated by -level particles
(qudits). Recently, several methods for encoding these systems into a set of
qubits have been introduced, where each encoding's efficiency was studied in
terms of qubit and gate counts. Here, we build on previous results by including
effects of hardware connectivity. To study the number of SWAP gates required to
Trotterize commonly used quantum operators, we use both analytical arguments
and automatic tools that optimize the schedule in multiple stages. We study the
unary (or one-hot), Gray, standard binary, and block unary encodings, with
three connectivities: linear array, ladder array, and square grid. Among other
trends, we find that while the ladder array leads to substantial efficiencies
over the linear array, the advantage of the square over the ladder array is
less pronounced. These results are applicable in hardware co-design and in
choosing efficient qudit encodings for a given set of near-term quantum
hardware. Additionally, this work may be relevant to the scheduling of other
quantum algorithms for which matrix exponentiation is a subroutine.Comment: Accepted to QCE20 (IEEE Quantum Week). Corrected erroneous circuits
in Figure