33,940 research outputs found
Quantum error correction in crossbar architectures
A central challenge for the scaling of quantum computing systems is the need
to control all qubits in the system without a large overhead. A solution for
this problem in classical computing comes in the form of so called crossbar
architectures. Recently we made a proposal for a large scale quantum
processor~[Li et al. arXiv:1711.03807 (2017)] to be implemented in silicon
quantum dots. This system features a crossbar control architecture which limits
parallel single qubit control, but allows the scheme to overcome control
scaling issues that form a major hurdle to large scale quantum computing
systems. In this work, we develop a language that makes it possible to easily
map quantum circuits to crossbar systems, taking into account their
architecture and control limitations. Using this language we show how to map
well known quantum error correction codes such as the planar surface and color
codes in this limited control setting with only a small overhead in time. We
analyze the logical error behavior of this surface code mapping for estimated
experimental parameters of the crossbar system and conclude that logical error
suppression to a level useful for real quantum computation is feasible.Comment: 29 + 9 pages, 13 figures, 9 tables, 8 algorithms and 3 big boxes.
Comments are welcom
A Parallel Tensor Network Contraction Algorithm and Its Applications in Quantum Computation
Tensors are a natural generalization of matrices, and tensor networks are a natural generalization of matrix products. Despite the simple definition of tensor networks, they are versatile enough to represent many different kinds of "products" that arise in various theoretical and practical problems. In particular, the powerful computational model of quantum computation can be defined almost entirely in terms of matrix products and tensor products, both of which are special cases of tensor networks. As such, (classical) algorithms for evaluating tensor networks have profound importance in the study of quantum computation.
In this thesis, we design and implement a parallel algorithm for tensor network contraction. In addition to finding efficient contraction orders for a tensor network, we also dynamically slice it into multiple sub-tasks with lower space and time costs, in order to evaluate the tensor network in parallel. We refer to such an evaluation strategy as a contraction scheme for the tensor network. In addition, we introduce a local optimization procedure that improves the efficiency of the contraction schemes we find.
We also investigate the applications of our parallel tensor network contraction algorithm in quantum computation. The most ready application is the simulation of random quantum supremacy circuits, where we benchmark our algorithm to demonstrate its advantage over other similar tensor network based simulators. Other applications we found include evaluating the energy function of a Quantum Approximate Optimization Algorithm (QAOA), and simulating surface codes under a realistic error model with crosstalk.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163098/1/fangzh_1.pd
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
Performance analysis and optimization of the FFTXlib on the Intel knights landing architecture
In this paper, we address the decreasing performance of the FFTXlib, the Fast Fourier Transformation (FFT) kernel of Quantum ESPRESSO, when scaling to a full KNL node. An increased performance in the FFTXlib will likewise increase the performance of the entire Quantum ESPRESSO code one of the most used plane-wave DFT codes in the community of material science. Our approach focuses on, first, overlapping computation and communication and, second, decreasing resource contention for higher compute efficiency. In order to achieve this we use the OmpSs programming model based on task dependencies. We allow overlapping of computation and communication by converting all steps of the FFT into tasks following a flow dependency. In the same way, we decrease resource contention by converting each FFT into an individual task that can be scheduled asynchronously. In both cases, multiple FFTs can be computed in parallel. The task-based optimizations are implemented in the FFTXlib and show up to 10% runtime reduction on the already highly optimized version. Since the task scheduling is done dynamically during execution by the parallel runtime, not statically by the user, it also frees the user from finding the ideal parallel configuration himself.We gratefully acknowledge the support of the MaX and POP projects, which have received funding from the European Union’s Horizon 2020 research and innovation programme
under grant agreement No. 676598 and 676553, respectively.Peer ReviewedPostprint (author's final draft
Decoherence-Free Subspaces for Multiple-Qubit Errors: (II) Universal, Fault-Tolerant Quantum Computation
Decoherence-free subspaces (DFSs) shield quantum information from errors
induced by the interaction with an uncontrollable environment. Here we study a
model of correlated errors forming an Abelian subgroup (stabilizer) of the
Pauli group (the group of tensor products of Pauli matrices). Unlike previous
studies of DFSs, this type of errors does not involve any spatial symmetry
assumptions on the system-environment interaction. We solve the problem of
universal, fault-tolerant quantum computation on the associated class of DFSs.Comment: 22 pages, 4 figures. Sequel to quant-ph/990806
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