An efficient quantum circuit analyser on qubits and qudits

This paper presents a highly efficient decomposition scheme and its associated Mathematica notebook for the analysis of complicated quantum circuits comprised of single/multiple qubit and qudit quantum gates. In particular, this scheme reduces the evaluation of multiple unitary gate operations with many conditionals to just two matrix additions, regardless of the number of conditionals or gate dimensions. This improves significantly the capability of a quantum circuit analyser implemented in a classical computer. This is also the first efficient quantum circuit analyser to include qudit quantum logic gates

Generating and using truly random quantum states in Mathematica

The problem of generating random quantum states is of a great interest from the quantum information theory point of view. In this paper we present a package for Mathematica computing system harnessing a specific piece of hardware, namely Quantis quantum random number generator (QRNG), for investigating statistical properties of quantum states. The described package implements a number of functions for generating random states, which use Quantis QRNG as a source of randomness. It also provides procedures which can be used in simulations not related directly to quantum information processing.Comment: 12 pages, 3 figures, see http://www.iitis.pl/~miszczak/trqs.html for related softwar

qTorch: The Quantum Tensor Contraction Handler

Classical simulation of quantum computation is necessary for studying the numerical behavior of quantum algorithms, as there does not yet exist a large viable quantum computer on which to perform numerical tests. Tensor network (TN) contraction is an algorithmic method that can efficiently simulate some quantum circuits, often greatly reducing the computational cost over methods that simulate the full Hilbert space. In this study we implement a tensor network contraction program for simulating quantum circuits using multi-core compute nodes. We show simulation results for the Max-Cut problem on 3- through 7-regular graphs using the quantum approximate optimization algorithm (QAOA), successfully simulating up to 100 qubits. We test two different methods for generating the ordering of tensor index contractions: one is based on the tree decomposition of the line graph, while the other generates ordering using a straight-forward stochastic scheme. Through studying instances of QAOA circuits, we show the expected result that as the treewidth of the quantum circuit's line graph decreases, TN contraction becomes significantly more efficient than simulating the whole Hilbert space. The results in this work suggest that tensor contraction methods are superior only when simulating Max-Cut/QAOA with graphs of regularities approximately five and below. Insight into this point of equal computational cost helps one determine which simulation method will be more efficient for a given quantum circuit. The stochastic contraction method outperforms the line graph based method only when the time to calculate a reasonable tree decomposition is prohibitively expensive. Finally, we release our software package, qTorch (Quantum TensOR Contraction Handler), intended for general quantum circuit simulation.Comment: 21 pages, 8 figure

Quantum computing modelling on field programmable gate array based on state vector and heisenberg models

As current trend of miniaturization in computing technology continues, modern computing devices would start to exhibit the behaviour of nanoscopic quantum objects. Quantum computing, which is based on the principles of quantum mechanics, becomes a promising candidate for future generation computing system. However, modelling quantum computing systems on existing classical computing platforms before the realization of viable large-scale quantum computer remains a major challenge. The exploration on the modelling of quantum computing systems on field programmable gate array (FPGA) platform, which offers the potential of massive parallelism and allows computational optimization at register-transfer level, is crucial. Due to the exponential growth of resource utilization with the increase in the number of quantum bits (qubit), existing works on modelling of quantum systems on FPGA platform are restricted to simple case studies using small qubit sizes. This work explores the modelling of quantum computing for emulation on FPGA platform based on two types of data structure: (a) state vector model and (b) Heisenberg model. For the conventional state vector modelling approach, an efficient datapath design that is based on serial-parallel hardware architecture, which allows resource sharing between unitary transformations, is proposed. Heisenberg model has been proven to be efficient in modelling stabilizer circuits, which are critical in error correction operations. In the effort to include the consideration of vital quantum error correction in practical quantum systems, a novel FPGA emulation framework that is based on the Heisenberg model is proposed. Effective algorithms for accurate global phase maintenance are proposed to facilitate the modelling of quantum systems based on the Heisenberg representation. The feasibility of the proposed state vector and Heisenberg emulation models are demonstrated based on a number of case studies with different characteristics, which include quantum Fourier transform, Grover’s search algorithm, and stabilizer circuits. Based on the state vector approach, this work has demonstrated the advantage of FPGA emulation over software simulation where hardware emulation of 7-qubit Grover’s search is about 3 × 104 times faster than the software simulation performed on Intel Core i7-4790 processor running at 3.6GHz clock rate. In contrast to the 8-qubit implementation based on the state vector model, the proposed FPGA emulation framework based on the Heisenberg model has successfully modelled 120-qubit stabilizer circuits on the Altera Stratix IV FPGA. In summary, the proposed work in this thesis contributes to the formulation of a proof-of-concept of efficient FPGA emulation framework based on the state vector and Heisenberg models

Classification of real and complex 3-qutrit states

In this paper we classify the orbits of the group SL(3,F)^3 on the space F^3\otimes F^3\otimes F^3 for F=C and F=R. This is known as the classification of complex and real 3-qutrit states. We also give an overview of physical theories where these classifications are relevant

QDENSITY/QCWAVE: A Mathematica quantum computer simulation update

The Mathematica quantum computer simulation packages QDENSITY and QCWAVE are updated for Mathematica 9-10.3. An overview is given of the new QDensity, QCWave, BTSystem and Circuits packages, which includes: (1) improved treatment of tensor products of states and density matrices, (2) major extension to include qutrit (triplet), as well as qubit (binary) and hybrid qubit/qutrit systems in the associated BTSystem package, (3) updated sample quantum computation algorithms, (4) entanglement studies, including Schmidt decomposition, entropy, mutual information, partial transposition, and calculation of the quantum discord. Examples of Bell’s theorem and concurrence are also included. This update will hopefully aid in studies of QC dynamics. The previous version of this program (ADXH_v3_0) may be found at http://dx.doi.org/10.1016/j.cpc.2011.04.010

QDENSITY/QCWAVE: A Mathematica quantum computer simulation update

This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2018) Abstract The Mathematica quantum computer simulation packages QDENSITY and QCWAVE are updated for Mathematica 9-10.3. An overview is given of the new QDensity, QCWave, BTSystem and Circuits packages, which includes: (1) improved treatment of tensor products of states and density matrices, (2) major extension to include qutrit (triplet), as well as qubit (binary) and hybrid qubit/qutrit systems in the associated BTSystem package, (3) updated sample quantum computation algorithms, (4) entanglement studi... Title of program: QDensity, QCWave, BTSystem, Circuits Catalogue Id: ADXH_v4_0 Nature of problem Simulation of quantum algorithms, Qubit and Qutrit hybrid systems, entanglement criteria. Versions of this program held in the CPC repository in Mendeley Data ADXH_v1_0; QDENSITY; 10.1016/j.cpc.2005.12.021 ADXH_v2_0; QDENSITY 2.0; 10.1016/j.cpc.2008.10.006 ADXH_v3_0; QCWAVE; 10.1016/j.cpc.2011.04.010 ADXH_v4_0; QDensity, QCWave, BTSystem, Circuits; 10.1016/j.cpc.2015.12.01