Amplitude Estimation (AE) |
AE aims to find an estimation for the amplitude of a certain
quantum state.
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Deutsch-Jozsa |
This algorithms determines, whether an unknown oracle mapping
input values either to 0 or 1 is constant (always output 1 or
always 0) or balanced (both outputs are equally likely).
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GHZ State |
The Greenberger-Horne-Zeilinger state is an entangled quantum
state with a certain type of entanglement.
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Graph State |
Graph states in quantum computing represent a graph with vertices
and edges through a quantum circuit.
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Ground State |
A famous application of quantum computing and specifically of VQE
algorithms is the ground state estimation of molecules. Here, we
provide two different molecules, H2 ("small") and LiH ("medium"),
and estimate their ground state using VQE with a TwoLocal ansatz.
The source code for the algorithmic level originates from
this page.
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Grover's (no ancilla) |
One of the most famous quantum algorithm known so far, Grover's
algorithm finds a certain goal quantum state determined by an
oracle. In our case, the oracle is implemented by a
multi-controlled Toffoli gate over all input qubits. In this no
ancilla version, no ancilla qubits are used during its
realization.
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Grover's (v-chain) |
Similar to the algorithm above with the difference, that the
ancillary mode is a v-chain in this algorithm.
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Portfolio Optimization with QAOA
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This algorithms solves the mean-variance portfolio optimization
problem for different assets. In this case, a QAOA algorithm
instance is used. The source code for the algorithmic level
originates from
this page.
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Portfolio Optimization with VQE |
This algorithms solves the mean-variance portfolio optimization
problem for different assets. In this case, a VQE algorithm instance
is used. The source code for the algorithmic level originates from
this page.
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Pricing Call Option |
This algorithm estimates the fair price of a european call option
using iterative amplitude estimation. The source code for the
algorithmic level originates from
this page.
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Pricing Put Option |
This algorithm estimates the fair price of a european put option
using iterative amplitude estimation. The source code for the
algorithmic level originates from
this page.
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Quantum Approximation Optimization Algorithm (QAOA)
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One of the most famous algorithm from the algorithmic class of
variational quantum algorithms. It is a parameterizable quantum
algorithms to solve optimization problems. Here, it solves a
max-cut problem instance.
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Quantum Fourier Transformation (QFT)
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QFT embodies the quantum equivalent of the discrete Fourier
transform and is a very important building block in many quantum
algorithms.
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Entangled QFT |
Applies regular QFT to entangled qubits.
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Quantum Neural Network (QNN) |
This algorithm class is the quantum equivalent to classical Neural
Network. The source code for the algorithmic level originates from
this page.
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Quantum Phase Estimation (QPE) exact
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QPE estimates the phase of a quantum operation and is a very
important building block in many quantum algorithms. In the exact
case, the applied phase is exactly representable by the number of
qubits.
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Quantum Phase Estimation (QPE) inexact
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Similar to QPE exact with the difference, that the applied phase
is not exactly representable by the number of qubits.
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Quantum Walk (no ancilla) |
Quantum walks are the quantum equivalent to classical random
walks. In this no ancilla version, no ancilla qubits are used
during its realization.
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Quantum Walk (v-chain) |
Similar to the algorithm above with the difference, that the
ancillary mode is a v-chain in this algorithm.
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Random Circuit |
This benchmark represents a random circuit which is twice as deep
as wide. It considers random quantum gates with up to four qubits.
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Routing |
This problem is similar to the travelling salesman problem with
the difference, that more than one vehicle may be used to travel
between those to be visited points, such that each point is
visited at least once. The source code for the algorithmic level
originates from
this page.
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Shor's |
This algorithm is one of the most famous quantum algorithms and
used to find prime factors of integers. Here, we provide quantum
algorithms solving this problem for the integers 9, 15, and 821.
The filename, e.g., shor_821_4_t-indep_42.qasm includes also the
to be factorized number (821) and the period used, namely 4.
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Travelling Salesman |
The travelling salesman problem is a very prominent optimization
problem of calculation the shortest path of a number of to be
visited points. Here, this is formulated as a quadratic problem
and solved using VQE with a TwoLocal ansatz. The source code for
the algorithmic level originates from
this page.
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Variational Quantum Eigensolver (VQE)
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VQE is also one of the most famous algorithm from the class of
variational quantum algorithms. It is a parameterizable quantum
algorithms with different possible choices of an ansatz function.
Here, a TwoLocal ansatz is chosen and applied to the same max-cut
problem instance as in QAOA.
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Efficient SU2 ansatz with Random Parameters
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VQE ansatz with randomly initialized values. Detailed information
can be found on
this page.
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Real Amplitudes ansatz with Random Parameters
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VQE ansatz with randomly initialized values. Detailed information
can be found on
this page.
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Two Local ansatz with random parameters
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VQE ansatz with randomly initialized values. Detailed information
can be found on
this page.
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W-State |
The W state is an entangled quantum state with a certain type of
entanglement.
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