scholarly journals Quantum Speedup for Index Modulation

2021 ◽  
Author(s):  
Naoki Ishikawa
Keyword(s):  
Optimization Problems ◽  
Quantum Computer ◽  
Fault Tolerant ◽  
Promising Result ◽  
Quantum Circuit ◽  
Selection Problem ◽  
Index Selection ◽  
Feasible Solutions ◽  
Index Modulation ◽  
Quantum Speedup

This letter presents a quantum-assisted index modulation for next-generation IoT wireless networks. The NP-hard index selection problem is first formulated by a quadratic unconstrained binary optimization problem consisting of constraints of feasible solutions. To minimize the number of qubits required for a quantum circuit, this formulation is then simplified by a dictionary-based approach that partially exploits a classical computer. It is observed that the Grover adaptive search can provide the quantum speedup for the index selection problem. This promising result implies that a future fault-tolerant quantum computer may be useful for solving optimization problems encountered in wireless communications.

scholarly journals Quantum Speedup for Index Modulation

2021 ◽  
Author(s):  
Naoki Ishikawa
Keyword(s):  
Optimization Problems ◽  
Quantum Computer ◽  
Fault Tolerant ◽  
Promising Result ◽  
Quantum Circuit ◽  
Selection Problem ◽  
Index Selection ◽  
Feasible Solutions ◽  
Index Modulation ◽  
Quantum Speedup

This letter presents a quantum-assisted index modulation for next-generation IoT wireless networks. The NP-hard index selection problem is first formulated by a quadratic unconstrained binary optimization problem consisting of constraints of feasible solutions. To minimize the number of qubits required for a quantum circuit, this formulation is then simplified by a dictionary-based approach that partially exploits a classical computer. It is observed that the Grover adaptive search can provide the quantum speedup for the index selection problem. This promising result implies that a future fault-tolerant quantum computer may be useful for solving optimization problems encountered in wireless communications.

scholarly journals Quantum Speedup for Index Modulation

2021 ◽  
Author(s):  
Naoki Ishikawa
Keyword(s):  
High Performance ◽  
Fault Tolerant ◽  
Promising Result ◽  
Quantum Circuit ◽  
Selection Problem ◽  
Index Selection ◽  
Actual Measurement ◽  
Feasible Solutions ◽  
Index Modulation ◽  
Quantum Speedup

<div>This paper presents a quantum-assisted index modulation for next-generation IoT wireless networks. The NP-hard index selection problem is first formulated by a quadratic unconstrained binary optimization (QUBO) problem consisting of constraints of feasible solutions. To minimize the number of qubits required for a quantum circuit, this formulation is then simplified by a dictionary-based approach that partially exploits a classical computer. </div><div>For both formulations, the numbers of required qubits and non-zero elements in QUBO matrices are analyzed algebraically, and found to be in close agreement with the actual measurement. It is observed that the Grover adaptive search can provide the quantum speedup for the index selection problem. This promising result implies that the on-off structure of index modulation is suitable for quantum computation, and future fault-tolerant quantum computers may be useful for obtaining high-performance index activation patterns.<br></div><div><br></div><div>(c) IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.<br><br>Naoki Ishikawa, "Quantum speedup for index modulation," vol. 9, pp. 111114-111124, Aug. 2021.</div><div>DOI: 10.1109/ACCESS.2021.3103207<br></div>

Computation

2021 ◽  
pp. 168-222
Author(s):  
Jochen Rau
Keyword(s):  
Quantum Computing ◽  
Optimization Problems ◽  
Quantum Computer ◽  
Classical Case ◽  
Building Blocks ◽  
Quantum Circuit ◽  
Carry Over ◽  
Classical Computing ◽  
Classical Computer ◽  
Classical Optimization

This chapter introduces the basic building blocks of quantum computing and a variety of specific algorithms. It begins with a brief review of classical computing and discusses how its key elements – bits, gates, circuits – carry over to the quantum realm. It highlights crucial differences to the classical case, such as the impossibility of copying a qubit. The quantum circuit model is shown to be universal, and a peculiar variant of quantum computing, based on measurements only, is illustrated. That a quantum computer can perform some calculations more efficiently than a classical computer, at least in principle, is exemplified with the Deutsch-Jozsa algorithm. Other examples covered in this chapter are the variational quantum eigensolver, which can be applied to the study of molecules and classical optimization problems; quantum simulation; and entanglement-assisted metrology.

scholarly journals Connectivity matrix model of quantum circuits and its application to distributed quantum circuit optimization

2021 ◽  
Vol 20 (7) ◽  
Author(s):  
Ismail Ghodsollahee ◽  
Zohreh Davarzani ◽  
Mariam Zomorodi ◽  
Paweł Pławiak ◽  
Monireh Houshmand ◽  
...  
Keyword(s):  
Quantum Computation ◽  
Quantum Computer ◽  
Quantum Circuit ◽  
Quantum Circuits ◽  
Connectivity Matrix ◽  
Circuit Optimization ◽  
Novel Approach ◽  
The Matrix ◽  
Minimum Number ◽  
Two Phases

AbstractAs quantum computation grows, the number of qubits involved in a given quantum computer increases. But due to the physical limitations in the number of qubits of a single quantum device, the computation should be performed in a distributed system. In this paper, a new model of quantum computation based on the matrix representation of quantum circuits is proposed. Then, using this model, we propose a novel approach for reducing the number of teleportations in a distributed quantum circuit. The proposed method consists of two phases: the pre-processing phase and the optimization phase. In the pre-processing phase, it considers the bi-partitioning of quantum circuits by Non-Dominated Sorting Genetic Algorithm (NSGA-III) to minimize the number of global gates and to distribute the quantum circuit into two balanced parts with equal number of qubits and minimum number of global gates. In the optimization phase, two heuristics named Heuristic I and Heuristic II are proposed to optimize the number of teleportations according to the partitioning obtained from the pre-processing phase. Finally, the proposed approach is evaluated on many benchmark quantum circuits. The results of these evaluations show an average of 22.16% improvement in the teleportation cost of the proposed approach compared to the existing works in the literature.

scholarly journals Practical Quantum Computing

2021 ◽  
Vol 2 (1) ◽  
pp. 1-35
Author(s):  
Adrien Suau ◽  
Gabriel Staffelbach ◽  
Henri Calandra
Keyword(s):  
Wave Equation ◽  
Quantum Computer ◽  
Quantum Algorithms ◽  
Quantum Algorithm ◽  
Quantum Circuit ◽  
Equation Solving ◽  
Small Quantum ◽  
Quantum Wave ◽  
Variational Algorithms ◽  
The One

In the last few years, several quantum algorithms that try to address the problem of partial differential equation solving have been devised: on the one hand, “direct” quantum algorithms that aim at encoding the solution of the PDE by executing one large quantum circuit; on the other hand, variational algorithms that approximate the solution of the PDE by executing several small quantum circuits and making profit of classical optimisers. In this work, we propose an experimental study of the costs (in terms of gate number and execution time on a idealised hardware created from realistic gate data) associated with one of the “direct” quantum algorithm: the wave equation solver devised in [32]. We show that our implementation of the quantum wave equation solver agrees with the theoretical big-O complexity of the algorithm. We also explain in great detail the implementation steps and discuss some possibilities of improvements. Finally, our implementation proves experimentally that some PDE can be solved on a quantum computer, even if the direct quantum algorithm chosen will require error-corrected quantum chips, which are not believed to be available in the short-term.

scholarly journals MEASUREMENT-BASED QUANTUM COMPUTATION WITH CLUSTER STATES

2009 ◽  
Vol 07 (06) ◽  
pp. 1053-1203 ◽  
Author(s):  
ROBERT RAUßENDORF
Keyword(s):  
Computational Model ◽  
Quantum Computation ◽  
Quantum Logic ◽  
Network Model ◽  
Quantum Computer ◽  
Fault Tolerant ◽  
Cluster State ◽  
Building Blocks ◽  
Network Simulator ◽  
Classical Level

In this thesis, we describe the one-way quantum computer [Formula: see text], a scheme of universal quantum computation that consists entirely of one-qubit measurements on a highly entangled multiparticle state, i.e. the cluster state. We prove the universality of the [Formula: see text], describe the underlying computational model and demonstrate that the [Formula: see text] can be operated fault-tolerantly. In Sec. 2, we show that the [Formula: see text] can be regarded as a simulator of quantum logic networks. In this way, we prove the universality and establish the link to the network model — the common model of quantum computation. We also indicate that the description of the [Formula: see text] as a network simulator is not adequate in every respect. In Sec. 3, we derive the computational model underlying the [Formula: see text], which is very different from the quantum logic network model. The [Formula: see text] has no quantum input, no quantum output and no quantum register, and the unitary gates from some universal set are not the elementary building blocks of [Formula: see text] quantum algorithms. Further, all information that is processed with the [Formula: see text] is the outcomes of one-qubit measurements and thus processing of information exists only at the classical level. The [Formula: see text] is nevertheless quantum-mechanical, as it uses a highly entangled cluster state as the central physical resource. In Sec. 4, we show that there exist nonzero error thresholds for fault-tolerant quantum computation with the [Formula: see text]. Further, we outline the concept of checksums in the context of the [Formula: see text], which may become an element in future practical and adequate methods for fault-tolerant [Formula: see text] computation.

Efficient reversible quantum design of sig-magnitude to two's complement converters

2020 ◽  
Vol 20 (9&10) ◽  
pp. 747-765
Author(s):  
F. Orts ◽  
G. Ortega ◽  
E.M. E.M. Garzon
Keyword(s):  
Quantum Computing ◽  
Scientific Community ◽  
Quantum Computer ◽  
Fault Tolerant ◽  
State Of The Art ◽  
The Other ◽  
Quantum Computers ◽  
Binary Number ◽  
Quantum Cost ◽  
The One

Despite the great interest that the scientific community has in quantum computing, the scarcity and high cost of resources prevent to advance in this field. Specifically, qubits are very expensive to build, causing the few available quantum computers are tremendously limited in their number of qubits and delaying their progress. This work presents new reversible circuits that optimize the necessary resources for the conversion of a sign binary number into two's complement of N digits. The benefits of our work are two: on the one hand, the proposed two's complement converters are fault tolerant circuits and also are more efficient in terms of resources (essentially, quantum cost, number of qubits, and T-count) than the described in the literature. On the other hand, valuable information about available converters and, what is more, quantum adders, is summarized in tables for interested researchers. The converters have been measured using robust metrics and have been compared with the state-of-the-art circuits. The code to build them in a real quantum computer is given.

scholarly journals Error mitigation with Clifford quantum-circuit data

Quantum ◽  
2021 ◽  
Vol 5 ◽  
pp. 592
Author(s):  
Piotr Czarnik ◽  
Andrew Arrasmith ◽  
Patrick J. Coles ◽  
Lukasz Cincio
Keyword(s):  
State Energy ◽  
Quantum Computer ◽  
Quantum Circuit ◽  
Training Data ◽  
Quantum Circuits ◽  
Accurate Estimation ◽  
Error Mitigation ◽  
Order Of Magnitude ◽  
Quantum Observables ◽  
Near Term

Achieving near-term quantum advantage will require accurate estimation of quantum observables despite significant hardware noise. For this purpose, we propose a novel, scalable error-mitigation method that applies to gate-based quantum computers. The method generates training data {Xinoisy,Xiexact} via quantum circuits composed largely of Clifford gates, which can be efficiently simulated classically, where Xinoisy and Xiexact are noisy and noiseless observables respectively. Fitting a linear ansatz to this data then allows for the prediction of noise-free observables for arbitrary circuits. We analyze the performance of our method versus the number of qubits, circuit depth, and number of non-Clifford gates. We obtain an order-of-magnitude error reduction for a ground-state energy problem on 16 qubits in an IBMQ quantum computer and on a 64-qubit noisy simulator.

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