Quantum Processes: A Novel Optimization for Quantum Simulation

The simulation of quantum algorithms in classic computers is a task which requires high processing and storing capabilities, limiting the size of quantum systems supported by the simulators. However, optimizations for reduction of temporal and spatial complexities are promising and expanding the capabilities of some simulators. The main contribution of this work consists in designing optimizations by the description of quantum transformations using Quantum Processes and Partial Quantum Processes conceived in the qGM theoretical model. These processes, when computed on the VPE-qGM execution environment, result in lower execution time and better performance, allowing the simulation of more complex quantum algorithms. The performance evaluation of this proposal was carried out by benchmarks used in similar works and included the sequential simulation of quantum algorithms up to 24 qubits. The results show a great improvement when compared to the previous version of the environment and indicate possibilities of advances in this research.

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Expanding the VPE-qGM Environment Towards a Parallel Quantum Simulation of Quantum Processes Using GPUs

CLEI electronic journal ◽

10.19153/cleiej.16.3.3 ◽

2013 ◽

Vol 16 (3) ◽

Cited By ~ 1

Author(s):

Adriano Maron ◽

Renata Reiser ◽

Mauricio Pilla ◽

Adenauer Yamin

Keyword(s):

Quantum Computer ◽

Parallel Implementation ◽

Quantum Algorithms ◽

Parallel Simulation ◽

Quantum Computers ◽

Memory Consumption ◽

Quantum Processes ◽

Significant Performance ◽

Temporal And Spatial ◽

Sequential Implementation

Quantum computing proposes quantum algorithms exponentially faster than their clas- sical analogues when executed by a quantum computer. As quantum computers are currently unavailable for general use, one approach for analyzing the behavior and re- sults of such algorithms is the simulation using classical computers. As this simulation is inefficient due to the exponential growth of the temporal and spatial complexities, solutions for these two problems are essential in order to increase the simulation capa- bilities of any simulator. This work proposes the development of a methodology defined by two main steps: the first consists of the sequential implementation of the abstractions corresponding to the Quantum Processes and Quantum Partial Processes defined in the qGM model for reduction in memory consumption related to multidimensional quantum transformations; the second is the parallel implementation of such abstractions allowing its execution on GPUs. The results obtained by this work embrace the sequential simu- lation of controlled transformations up to 24 qubits. In the parallel simulation approach, Hadamard gates up to 20 qubits were simulated with a speedup of ≈ 50× over an 8-core parallel simulation, which is a significant performance improvement in the VPE-qGM environment when compared with its previous limitations.

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Cyclic quantum causal models

Nature Communications ◽

10.1038/s41467-020-20456-x ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Jonathan Barrett ◽

Robin Lorenz ◽

Ognyan Oreshkov

Keyword(s):

Causal Reasoning ◽

Causal Structure ◽

Bell Inequalities ◽

Quantum Correlations ◽

Quantum Systems ◽

Causal Models ◽

Causal Order ◽

Quantum Processes ◽

Causal Explanations ◽

Causal Structures

AbstractCausal reasoning is essential to science, yet quantum theory challenges it. Quantum correlations violating Bell inequalities defy satisfactory causal explanations within the framework of classical causal models. What is more, a theory encompassing quantum systems and gravity is expected to allow causally nonseparable processes featuring operations in indefinite causal order, defying that events be causally ordered at all. The first challenge has been addressed through the recent development of intrinsically quantum causal models, allowing causal explanations of quantum processes – provided they admit a definite causal order, i.e. have an acyclic causal structure. This work addresses causally nonseparable processes and offers a causal perspective on them through extending quantum causal models to cyclic causal structures. Among other applications of the approach, it is shown that all unitarily extendible bipartite processes are causally separable and that for unitary processes, causal nonseparability and cyclicity of their causal structure are equivalent.

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Selective Phase Rotation Quantum Gate Entangler

Open Systems & Information Dynamics ◽

10.1142/s1230161209000293 ◽

2009 ◽

Vol 16 (04) ◽

pp. 407-412

Author(s):

Hoshang Heydari

Keyword(s):

Integral Transform ◽

Quantum Algorithms ◽

Quantum Systems ◽

Quantum Gate ◽

Multipartite Quantum Systems ◽

Phase Rotation ◽

Quantum Integral ◽

Qubit States

We construct a quantum gate entangler for multi-qubit states based on a selective phase rotation transform. In particular, we establish a relation between the quantum integral transform and the quantum gate entangler in terms of universal controlled gates for multi-qubit states. Our result gives an effective way of constructing topological and geometrical quantum gate entanglers for multipartite quantum systems, which could also lead to a construction of geometrical quantum algorithms.

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Using quantum computing to create efficient algorithms

Journal of Physics Conference Series ◽

10.1088/1742-6596/2056/1/012059 ◽

2021 ◽

Vol 2056 (1) ◽

pp. 012059

Author(s):

I N Balaba ◽

G S Deryabina ◽

I A Pinchuk ◽

I V Sergeev ◽

S B Zabelina

Keyword(s):

Quantum Mechanics ◽

Quantum Computing ◽

Computational Model ◽

Exponential Growth ◽

Quantum Algorithms ◽

Quantum Systems ◽

Efficient Algorithms ◽

Historical Overview ◽

Computing Model ◽

Computational Strategy

Abstract The article presents a historical overview of the development of the mathematical idea of a quantum computing model - a new computational strategy based on the postulates of quantum mechanics and having advantages over the traditional computational model based on the Turing machine; clarified the features of the operation of multi-qubit quantum systems, which ensure the creation of efficient algorithms; the principles of quantum computing are outlined and a number of efficient quantum algorithms are described that allow solving the problem of exponential growth of the complexity of certain problems.

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Algorithms for Quantum Systems - Quantum Algorithms

Quantum Information Processing ◽

10.1002/3527603549.ch1 ◽

2005 ◽

pp. 1-13

Author(s):

Th. Beth ◽

M. Grassl ◽

D. Janzing ◽

M. Rötteler ◽

P. Wocjan ◽

...

Keyword(s):

Quantum Algorithms ◽

Quantum Systems

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Control Theoretical Expression of Quantum Systems And Lower Bound of Finite Horizon Quantum Algorithms

2007 American Control Conference ◽

10.1109/acc.2007.4282358 ◽

2007 ◽

Author(s):

Masahiro Yanagisawa

Keyword(s):

Lower Bound ◽

Quantum Algorithms ◽

Quantum Systems ◽

Finite Horizon ◽

Theoretical Expression

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Performance Evaluation for Dynamic Voltage and Frequency Scaling Using Runtime Performance Counters

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.284-287.2575 ◽

2013 ◽

Vol 284-287 ◽

pp. 2575-2579 ◽

Cited By ~ 1

Author(s):

Wen Yew Liang ◽

Ming Feng Chang ◽

Yen Lin Chen ◽

Jenq Haur Wang

Keyword(s):

Operating System ◽

Performance Evaluation ◽

Execution Time ◽

System Performance ◽

Evaluation Method ◽

Reducing Power ◽

General Purpose ◽

Frequency Scaling ◽

Dynamic Voltage ◽

Performance Evaluation Method

Dynamic voltage and frequency scaling (DVFS) is an effective technique for reducing power consumption. The system performance is not easy to evaluate through Dynamic Voltage and Frequency Scaling. Most of studies use the execution time as an indicator while measuring the performance. However, DVFS adjusted processor speed during a fixed-length period so it cannot rely on the execution time to evaluate the system performance. This study proposes a novel and simple performance evaluation method to evaluate the system performance when DVFS is activated. Based on the performance evaluation method, this study also proposes a DVFS algorithm (P-DVFS) for a general-purpose operating system. The algorithm has been implemented on the Linux operating system and used a PXA270 development board. The results show that P-DVFS could accurately predict the suitable frequency, given runtime statistics information of a running program. In this way, the user can easily control the energy consumption by specifying allowable performance loss factor.

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Performance evaluation of MapReduce using full virtualisation on a departmental cloud

International Journal of Applied Mathematics and Computer Science ◽

10.2478/v10006-011-0020-3 ◽

2011 ◽

Vol 21 (2) ◽

pp. 275-284 ◽

Cited By ~ 10

Author(s):

Horacio González-Vélez ◽

Maryam Kontagora

Keyword(s):

Parallel Computing ◽

Performance Evaluation ◽

Execution Time ◽

Programming Model ◽

Peak Performance ◽

Distributed Environment ◽

Maximum Peak ◽

Distributed Parallel Computing

Performance evaluation of MapReduce using full virtualisation on a departmental cloudThis work analyses the performance of Hadoop, an implementation of the MapReduce programming model for distributed parallel computing, executing on a virtualisation environment comprised of 1+16 nodes running the VMWare workstation software. A set of experiments using the standard Hadoop benchmarks has been designed in order to determine whether or not significant reductions in the execution time of computations are experienced when using Hadoop on this virtualisation platform on a departmental cloud. Our findings indicate that a significant decrease in computing times is observed under these conditions. They also highlight how overheads and virtualisation in a distributed environment hinder the possibility of achieving the maximum (peak) performance.

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