50 research outputs found
Time-Sliced Quantum Circuit Partitioning for Modular Architectures
Current quantum computer designs will not scale. To scale beyond small
prototypes, quantum architectures will likely adopt a modular approach with
clusters of tightly connected quantum bits and sparser connections between
clusters. We exploit this clustering and the statically-known control flow of
quantum programs to create tractable partitioning heuristics which map quantum
circuits to modular physical machines one time slice at a time. Specifically,
we create optimized mappings for each time slice, accounting for the cost to
move data from the previous time slice and using a tunable lookahead scheme to
reduce the cost to move to future time slices. We compare our approach to a
traditional statically-mapped, owner-computes model. Our results show strict
improvement over the static mapping baseline. We reduce the non-local
communication overhead by 89.8\% in the best case and by 60.9\% on average. Our
techniques, unlike many exact solver methods, are computationally tractable.Comment: Appears in CF'20: ACM International Conference on Computing Frontier
Optimized Surface Code Communication in Superconducting Quantum Computers
Quantum computing (QC) is at the cusp of a revolution. Machines with 100
quantum bits (qubits) are anticipated to be operational by 2020
[googlemachine,gambetta2015building], and several-hundred-qubit machines are
around the corner. Machines of this scale have the capacity to demonstrate
quantum supremacy, the tipping point where QC is faster than the fastest
classical alternative for a particular problem. Because error correction
techniques will be central to QC and will be the most expensive component of
quantum computation, choosing the lowest-overhead error correction scheme is
critical to overall QC success. This paper evaluates two established quantum
error correction codes---planar and double-defect surface codes---using a set
of compilation, scheduling and network simulation tools. In considering
scalable methods for optimizing both codes, we do so in the context of a full
microarchitectural and compiler analysis. Contrary to previous predictions, we
find that the simpler planar codes are sometimes more favorable for
implementation on superconducting quantum computers, especially under
conditions of high communication congestion.Comment: 14 pages, 9 figures, The 50th Annual IEEE/ACM International Symposium
on Microarchitectur
Optimal Quantum Circuits for Nearest-Neighbor Architectures
We show that the depth of quantum circuits in the realistic architecture
where a classical controller determines which local interactions to apply on
the kD grid Z^k where k >= 2 is the same (up to a constant factor) as in the
standard model where arbitrary interactions are allowed. This allows
minimum-depth circuits (up to a constant factor) for the nearest-neighbor
architecture to be obtained from minimum-depth circuits in the standard
abstract model. Our work therefore justifies the standard assumption that
interactions can be performed between arbitrary pairs of qubits. In particular,
our results imply that Shor's algorithm, controlled operations and fanouts can
be implemented in constant depth, polynomial size and polynomial width in this
architecture.
We also present optimal non-adaptive quantum circuits for controlled
operations and fanouts on a kD grid. These circuits have depth Theta(n^(1 /
k)), size Theta(n) and width Theta(n). Our lower bound also applies to a more
general class of operations.Comment: 24 pages, 6 figures. v1 introduces all the results. v2 and v3 make
minor improvements to the presentation and add additional reference
Noise-Adaptive Compiler Mappings for Noisy Intermediate-Scale Quantum Computers
A massive gap exists between current quantum computing (QC) prototypes, and
the size and scale required for many proposed QC algorithms. Current QC
implementations are prone to noise and variability which affect their
reliability, and yet with less than 80 quantum bits (qubits) total, they are
too resource-constrained to implement error correction. The term Noisy
Intermediate-Scale Quantum (NISQ) refers to these current and near-term systems
of 1000 qubits or less. Given NISQ's severe resource constraints, low
reliability, and high variability in physical characteristics such as coherence
time or error rates, it is of pressing importance to map computations onto them
in ways that use resources efficiently and maximize the likelihood of
successful runs.
This paper proposes and evaluates backend compiler approaches to map and
optimize high-level QC programs to execute with high reliability on NISQ
systems with diverse hardware characteristics. Our techniques all start from an
LLVM intermediate representation of the quantum program (such as would be
generated from high-level QC languages like Scaffold) and generate QC
executables runnable on the IBM Q public QC machine. We then use this framework
to implement and evaluate several optimal and heuristic mapping methods. These
methods vary in how they account for the availability of dynamic machine
calibration data, the relative importance of various noise parameters, the
different possible routing strategies, and the relative importance of
compile-time scalability versus runtime success. Using real-system
measurements, we show that fine grained spatial and temporal variations in
hardware parameters can be exploited to obtain an average x (and up to
x) improvement in program success rate over the industry standard IBM
Qiskit compiler.Comment: To appear in ASPLOS'1
Optimal State Transfer and Entanglement Generation in Power-law Interacting Systems
We present an optimal protocol for encoding an unknown qubit state into a
multiqubit Greenberger-Horne-Zeilinger-like state and, consequently,
transferring quantum information in large systems exhibiting power-law
() interactions. For all power-law exponents between
and , where is the dimension of the system, the protocol yields a
polynomial speedup for and a superpolynomial speedup for
, compared to the state of the art. For all , the
protocol saturates the Lieb-Robinson bounds (up to subpolynomial corrections),
thereby establishing the optimality of the protocol and the tightness of the
bounds in this regime. The protocol has a wide range of applications, including
in quantum sensing, quantum computing, and preparation of topologically ordered
states. In addition, the protocol provides a lower bound on the gate count in
digital simulations of power-law interacting systems.Comment: Updated Table I, Additional discussion on a lower bound for the gate
count in digital quantum simulatio
Exploiting Quantum Teleportation in Quantum Circuit Mapping
Quantum computers are constantly growing in their number of qubits, but
continue to suffer from restrictions such as the limited pairs of qubits that
may interact with each other. Thus far, this problem is addressed by mapping
and moving qubits to suitable positions for the interaction (known as quantum
circuit mapping). However, this movement requires additional gates to be
incorporated into the circuit, whose number should be kept as small as possible
since each gate increases the likelihood of errors and decoherence.
State-of-the-art mapping methods utilize swapping and bridging to move the
qubits along the static paths of the coupling map---solving this problem
without exploiting all means the quantum domain has to offer. In this paper, we
propose to additionally exploit quantum teleportation as a possible
complementary method. Quantum teleportation conceptually allows to move the
state of a qubit over arbitrary long distances with constant
overhead---providing the potential of determining cheaper mappings. The
potential is demonstrated by a case study on the IBM Q Tokyo architecture which
already shows promising improvements. With the emergence of larger quantum
computing architectures, quantum teleportation will become more effective in
generating cheaper mappings.Comment: To appear in ASP-DAC 202