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Workshop-School on Theoretical Computer Science

Simulating the Quantum Fourier Transform

Francisco Revson F. Pereira, Elloá B. Guedes, Francisco de Assis

Published Oct 1, 2013• 3 citations
Publisher

Abstract

Quantum Computing is a computational paradigm that takes into account the laws of Quantum Physics in the steps of the computation which advantages were verified both in Computation and Communications. No scalable quantum computer was developed so far and to execute, to test, and to create new quantum algorithms the simulation of quantum computers on classical computers plays an important role. In this work, we show the design, tools and results obtained for the simulation of the Quantum Fourier Transform algorithm. As a result, we developed an open-source tool, called FTSimulator, and we could simulate up to 12 qubits according to the procedures specified by an experimental test.

DOI
10.1109/weit.2013.10

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Quantum Computing is a computational paradigm that takes into account the laws of Quantum Physics in the steps of the computation which advantages were verified both in Computation and Communications. No scalable quantum computer was developed so far and to execute, to test, and to create new quantum algorithms the simulation of quantum computers on classical computers plays an important role. In this work, we show the design, tools and results obtained for the simulation of the Quantum Fourier Transform algorithm. As a result, we developed an open-source tool, called FTSimulator, and we could simulate up to 12 qubits according to the procedures specified by an experimental test.
The Quantum Fourier Transform (QFT) has an important role in some of the most interesting and useful quantum algorithms, such as those for period finding, order finding, phase estimation and factoring. Most of the research carried out on the QFT has been developed using software simulators, however these do not emulate efficiently the quantum parallelism present in the quantum algorithms. Addressing this problem, this paper presents the hardware design of an emulator for computing the QFT using FPGAs. This emulator was designed considering a modular philosophy and it is expected to be a powerful tool to evaluate quantum algorithms that include a many-qubit QFT.
For discussing the solving methods of NP problems in classical computers and studying the circuit model which is the most representative in quantum computing to simulate the compute processes, this article discussed how to simulate the quantum Fourier transform by using the quantum logic gates, implemented the quantum Fourier transform and constructed the quantum information and compute simulation platform. The experiment introduced the quantum register structure to be the storage medium, which is better than the form of matrix in space. The operation processes adopted the bit manipulation to avoid the mass time for matrix multiplications. The results presented the changes of quantum amplitudes and probabilities of quantum states according to the quantum effect and compared with the approximate quantum Fourier transform. The experimental platform provided a groundwork for the further simulations of other important quantum algorithms and quantum circuits.
Quantum computing has emerged as a transformative paradigm capable of solving complex computational problems that are intractable for classical computers. Central to the advancement of this technology is the development of efficient quantum algorithms and high fidelity simulations that enable the design, testing, and optimization of quantum solutions before deployment on physical hardware. This study focuses on the design and implementation of quantum algorithms tailored for solving a variety of quantum problems, including quantum chemistry, optimization, and cryptography. Using state of the art simulation platforms such as Qiskit, Cirq, and Pennylane, algorithm performance was evaluated in terms of accuracy, execution time, scalability, and resilience to noise. Benchmarks demonstrate that algorithms such as the Variational Quantum Eigensolver (VQE) and Quantum Approximate Optimization Algorithm (QAOA) achieve significant speedups in problem specific domains, while hybrid quantum–classical methods provide robust pathways for near term quantum advantage. Simulation results reveal that algorithmic efficiency can be significantly improved through optimized circuit depth, qubit connectivity mapping, and advanced error mitigation techniques. The findings highlight the potential of simulation driven quantum algorithm development in accelerating the practical realization of quantum computing applications across disciplines such as materials discovery, molecular modeling, secure communications, and complex optimization tasks.
This thesis describes the design and implementation of an environment to allow quantum computation to be simulated on classical computers. Although it is believed that quantum computers cannot in general be efficiently simulated classically, it is nevertheless possible to simulate small but interesting systems, on the order of a few tens of quantum bits. Since the state of the art of physical implementations is less than 10 bits, simulation remains a useful tool for understanding the behavior of quantum algorithms. To create a suitable envrionment for simulation, we constructed a 32-node cluster of workstation class computers linked with a high speed (gigabit Ethernet) network. We then wrote an initial simulation environment based on parallel linear algebra libraries with a Matlab front end. These libraries operated on large matrices representing the problem being simulated. The parallel Matlab environment demonstrated a degree of parallel speedup as we added processors, but overall execution times were high, since the amount of data scaled exponentially with the size of the problem. This increased both the number of operations that had to be performed to compute the simulation, and the volume of data that had to be communicated between the nodes as they were computing. The scaling also affected memory utilization, limiting us to a maximum problem size of 14 qubits. In an attempt to increase simulation efficiency, we revisited the design of the simulation environment. Many quantum algorithms have a structure that can be described using the tensor product operator from linear algebra. We believed that a new simulation environment based on this tensor product structure would be substantially more efficient than one based on large matrices. We designed a new simulation envrionment that exploited this tensor product structure. Benchmarks that we performed on the new simulation environment confirmed that it was substantially more efficient, allowing us to perform simulations of the quantum Fourier transform and the discrete approximation to the solution of 3-SAT by adiabatic evolution up to 25 qubits in a reasonable time. Thesis Supervisor: Stephen A. Benton Title: Professor of Media Arts and Sciences