243 research outputs found
Compiler Design for Distributed Quantum Computing
In distributed quantum computing architectures, with the network and communications functionalities provided by the Quantum Internet, remote quantum processing units (QPUs) can communicate and cooperate for executing computational tasks that single NISQ devices cannot handle by themselves. To this aim, distributed quantum computing requires a new generation of quantum compilers, for mapping any quantum algorithm to any distributed quantum computing architecture. With this perspective, in this paper, we first discuss the main challenges arising with compiler design for distributed quantum computing. Then, we analytically derive an upper bound of the overhead induced by quantum compilation for distributed quantum computing. The derived bound accounts for the overhead induced by the underlying computing architecture as well as the additional overhead induced by the sub-optimal quantum compiler--expressly designed through the paper to achieve three key features, namely, general-purpose, efficient and effective. Finally, we validate the analytical results and we confirm the validity of the compiler design through an extensive performance analysis
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
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
Optimal Remote Qubit Teleportation Using Node2vec
Much research work is done on implementing quantum teleportation and entanglement swapping for remote entanglement. Due to dynamical topological changes in quantum networks, nodes have to construct the shortest paths every time they want to communicate with a remote neighbour. But due to the entanglement failures remote entanglement establishment is still a challenging task. Also as the nodes know only about their neighbouring nodes computing optimal paths between source and remote nodes is time consuming too. In finding the next best neighbour in the optimal path between a given source and remote nodes so as to decrease the entanglement cost, deep learning techniques can be applied. In this paper we defined throughput of the quantum network as the maximum qubits transmitted with minimum entanglement cost. Much of research work is done to improve the throughput of the quantum network using the deep learning techniques. In this paper we adopted deep learning techniques for implementing remote entanglement between two non-neighbour nodes using remote qubit teleportation and entanglement swapping. The proposed method called Optimal Remote Qubit Teleportation outperforms the throughput obtained by the state of art approach
Freely Scalable Quantum Technologies using Cells of 5-to-50 Qubits with Very Lossy and Noisy Photonic Links
Exquisite quantum control has now been achieved in small ion traps, in
nitrogen-vacancy centres and in superconducting qubit clusters. We can regard
such a system as a universal cell with diverse technological uses from
communication to large-scale computing, provided that the cell is able to
network with others and overcome any noise in the interlinks. Here we show that
loss-tolerant entanglement purification makes quantum computing feasible with
the noisy and lossy links that are realistic today: With a modestly complex
cell design, and using a surface code protocol with a network noise threshold
of 13.3%, we find that interlinks which attempt entanglement at a rate of 2MHz
but suffer 98% photon loss can result in kilohertz computer clock speeds (i.e.
rate of high fidelity stabilizer measurements). Improved links would
dramatically increase the clock speed. Our simulations employed local gates of
a fidelity already achieved in ion trap devices.Comment: corrected typos, additional references, additional figur
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