4,853 research outputs found
Improved Simulation of Stabilizer Circuits
The Gottesman-Knill theorem says that a stabilizer circuit -- that is, a
quantum circuit consisting solely of CNOT, Hadamard, and phase gates -- can be
simulated efficiently on a classical computer. This paper improves that theorem
in several directions. First, by removing the need for Gaussian elimination, we
make the simulation algorithm much faster at the cost of a factor-2 increase in
the number of bits needed to represent a state. We have implemented the
improved algorithm in a freely-available program called CHP
(CNOT-Hadamard-Phase), which can handle thousands of qubits easily. Second, we
show that the problem of simulating stabilizer circuits is complete for the
classical complexity class ParityL, which means that stabilizer circuits are
probably not even universal for classical computation. Third, we give efficient
algorithms for computing the inner product between two stabilizer states,
putting any n-qubit stabilizer circuit into a "canonical form" that requires at
most O(n^2/log n) gates, and other useful tasks. Fourth, we extend our
simulation algorithm to circuits acting on mixed states, circuits containing a
limited number of non-stabilizer gates, and circuits acting on general
tensor-product initial states but containing only a limited number of
measurements.Comment: 15 pages. Final version with some minor updates and corrections.
Software at http://www.scottaaronson.com/ch
Simulation of quantum circuits by ow-rank sotabilizer decompositions
Recent work has explored using the stabilizer formalism to classically simulate quantum circuits containing a few non-Clifford gates. The computational cost of such methods is directly related to the notion of stabilizer rank, which for a pure state ψ is defined to be the smallest integer χ such that ψ is a superposition of χ stabilizer states.
Here we develop a comprehensive mathematical theory of the stabilizer rank and the
related approximate stabilizer rank. We also present a suite of classical simulation
algorithms with broader applicability and significantly improved performance over the
previous state-of-the-art. A new feature is the capability to simulate circuits composed
of Clifford gates and arbitrary diagonal gates, extending the reach of a previous algorithm specialized to the Clifford+T gate set. We implemented the new simulation
methods and used them to simulate quantum algorithms with 40-50 qubits and over
60 non-Clifford gates, without resorting to high-performance computers. We report a
simulation of the Quantum Approximate Optimization Algorithm in which we process
superpositions of χ ∼ 106
stabilizer states and sample from the full n-bit output distribution, improving on previous simulations which used ∼ 103
stabilizer states and
sampled only from single-qubit marginals. We also simulated instances of the Hidden
Shift algorithm with circuits including up to 64 T gates or 16 CCZ gates; these simulations showcase the performance gains available by optimizing the decomposition of a
circuit’s non-Clifford components
Exploring Quantum Computation Through the Lens of Classical Simulation
It is widely believed that quantum computation has the potential to offer an ex- ponential speedup over classical devices. However, there is currently no definitive proof of this separation in computational power. Such a separation would in turn imply that quantum circuits cannot be efficiently simulated classically. However, it is well known that certain classes of quantum computations nonetheless admit an efficient classical description. Recent work has also argued that efficient classical simulation of quantum circuits would imply the collapse of the Polynomial Hierarchy, something which is commonly invoked in clas- sical complexity theory as a no-go theorem. This suggests a route for studying this ‘quantum advantage’ through classical simulations. This project looks at the problem of classically simulating quantum circuits through decompositions into stabilizer circuits. These are a restricted class of quantum computation which can be efficiently simulated classically. In this picture, the rank of the decomposition determines the temporal and spatial complexity of the simulation. We approach the problem by considering classical simulations of stabilizer circuits, introducing two new representations with novel features compared to previous meth- ods. We then examine techniques for building these so-called ‘stabilizer rank’ decom- positions, both exact and approximate. Finally, we combine these two ingredients to introduce an improved method for classically simulating broad classes of circuits using the stabilizer rank method
Trading classical and quantum computational resources
We propose examples of a hybrid quantum-classical simulation where a
classical computer assisted by a small quantum processor can efficiently
simulate a larger quantum system. First we consider sparse quantum circuits
such that each qubit participates in O(1) two-qubit gates. It is shown that any
sparse circuit on n+k qubits can be simulated by sparse circuits on n qubits
and a classical processing that takes time . Secondly, we
study Pauli-based computation (PBC) where allowed operations are
non-destructive eigenvalue measurements of n-qubit Pauli operators. The
computation begins by initializing each qubit in the so-called magic state.
This model is known to be equivalent to the universal quantum computer. We show
that any PBC on n+k qubits can be simulated by PBCs on n qubits and a classical
processing that takes time . Finally, we propose a purely
classical algorithm that can simulate a PBC on n qubits in a time where . This improves upon the brute-force simulation
method which takes time . Our algorithm exploits the fact that
n-fold tensor products of magic states admit a low-rank decomposition into
n-qubit stabilizer states.Comment: 14 pages, 4 figure
Cross-level Validation of Topological Quantum Circuits
Quantum computing promises a new approach to solving difficult computational
problems, and the quest of building a quantum computer has started. While the
first attempts on construction were succesful, scalability has never been
achieved, due to the inherent fragile nature of the quantum bits (qubits). From
the multitude of approaches to achieve scalability topological quantum
computing (TQC) is the most promising one, by being based on an flexible
approach to error-correction and making use of the straightforward
measurement-based computing technique. TQC circuits are defined within a large,
uniform, 3-dimensional lattice of physical qubits produced by the hardware and
the physical volume of this lattice directly relates to the resources required
for computation. Circuit optimization may result in non-intuitive mismatches
between circuit specification and implementation. In this paper we introduce
the first method for cross-level validation of TQC circuits. The specification
of the circuit is expressed based on the stabilizer formalism, and the
stabilizer table is checked by mapping the topology on the physical qubit
level, followed by quantum circuit simulation. Simulation results show that
cross-level validation of error-corrected circuits is feasible.Comment: 12 Pages, 5 Figures. Comments Welcome. RC2014, Springer Lecture Notes
on Computer Science (LNCS) 8507, pp. 189-200. Springer International
Publishing, Switzerland (2014), Y. Shigeru and M.Shin-ichi (Eds.
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