Quantum Circuit for Random Forest Prediction

• URL: http://arxiv.org/abs/2312.16877v1
• Date: Thu, 28 Dec 2023 08:07:11 GMT
• Title: Quantum Circuit for Random Forest Prediction
• Authors: Liliia Safina, Kamil Khadieva, Ilnar Zinnatullina, and Aliya Khadieva
• Abstract summary: We present a quantum circuit for a binary classification prediction algorithm using a random forest model. One of our goals is reducing the number of basic quantum gates (elementary gates)
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this work, we present a quantum circuit for a binary classification prediction algorithm using a random forest model. The quantum prediction algorithm is presented in our previous works. We construct a circuit and implement it using qiskit tools (python module for quantum programming). One of our goals is reducing the number of basic quantum gates (elementary gates). The set of basic quantum gates which we use in this work consists of single-qubit gates and a controlled NOT gate. The number of CNOT gates in our circuit is estimated by $O(2^{n+2h+1})$ , when trivial circuit decomposition techniques give $O(4^{|X|+n+h+2})$ CNOT gates, where $n$ is the number of trees in a random forest model, $h$ is a tree height and $|X|$ is the length of attributes of an input object $X$. The prediction process returns an index of the corresponding class for the input $X$.

Related papers

• Linear Circuit Synthesis using Weighted Steiner Trees [45.11082946405984]
  CNOT circuits are a common building block of general quantum circuits. This article presents state-of-the-art algorithms for optimizing the number of CNOT gates. A simulated evaluation shows that the suggested is almost always beneficial and reduces the number of CNOT gates by up to 10%.
  arXiv  Detail & Related papers  (2024-08-07T19:51:22Z)
• Quantum hashing algorithm implementation [0.0]
  We implement a quantum hashing algorithm which is based on a fingerprinting technique presented by Ambainis and Frievalds, 1988, on gate-based quantum computers. We consider 16-qubit and 27-qubit IBMQ computers with the special graphs of qubits representing nearest neighbor architecture that is not Linear Nearest Neighbor (LNN) one.
  arXiv  Detail & Related papers  (2024-07-14T09:41:16Z)
• Lower $T$-count with faster algorithms [3.129187821625805]
  We contribute to the $T$-count reduction problem by proposing efficient $T$-counts with low execution times. We greatly improve the complexity of TODD, an algorithm currently providing the best $T$-count reduction on various quantum circuits. We propose another algorithm which has an even lower complexity and that achieves a better or equal $T$-count than the state of the art on most quantum circuits evaluated.
  arXiv  Detail & Related papers  (2024-07-11T17:31:20Z)
• Scalable quantum circuits for exponential of Pauli strings and Hamiltonian simulations [0.0]
  We design quantum circuits for the exponential of scaled $n$-qubit Pauli strings using single-qubit rotation gates, Hadamard gate, and CNOT gates. A key result we derive is that any two Pauli-string operators composed of identity and $X$ gates are permutation similar. We apply these circuit models to approximate unitary evolution for several classes of Hamiltonians using the Suzuki-Trotter approximation.
  arXiv  Detail & Related papers  (2024-05-22T12:57:09Z)
• Hybrid Quantum-Classical Scheduling for Accelerating Neural Network Training with Newton's Gradient Descent [37.59299233291882]
  We propose Q-Newton, a hybrid quantum-classical scheduler for accelerating neural network training with Newton's GD. Q-Newton utilizes a streamlined scheduling module that coordinates between quantum and classical linear solvers. Our evaluation showcases the potential for Q-Newton to significantly reduce the total training time compared to commonly used quantum machines.
  arXiv  Detail & Related papers  (2024-04-30T23:55:03Z)
• Constant-depth circuits for Boolean functions and quantum memory devices using multi-qubit gates [40.56175933029223]
  We propose two types of constant-depth constructions for implementing Uniformly Controlled Gates. We obtain constant-depth circuits for the quantum counterparts of read-only and read-write memory devices.
  arXiv  Detail & Related papers  (2023-08-16T17:54:56Z)
• On the average-case complexity of learning output distributions of quantum circuits [55.37943886895049]
  We show that learning the output distributions of brickwork random quantum circuits is average-case hard in the statistical query model. This learning model is widely used as an abstract computational model for most generic learning algorithms.
  arXiv  Detail & Related papers  (2023-05-09T20:53:27Z)
• Homomorphic Encryption of the k=2 Bernstein-Vazirani Algorithm [0.4511923587827301]
  We find an application of this scheme to quantum homomorphic encryption (QHE) which is an important cryptographic technology useful for delegated quantum computation. We develop QHE schemes with perfect security, $mathcalF$-homomorphism, no interaction between server and client, and quasi-compactness bounded by $O(M)$ where M is the number of gates $T$ in the circuit.
  arXiv  Detail & Related papers  (2023-03-30T14:49:15Z)
• Synthesis of Quantum Circuits with an Island Genetic Algorithm [44.99833362998488]
  Given a unitary matrix that performs certain operation, obtaining the equivalent quantum circuit is a non-trivial task. Three problems are explored: the coin for the quantum walker, the Toffoli gate and the Fredkin gate. The algorithm proposed proved to be efficient in decomposition of quantum circuits, and as a generic approach, it is limited only by the available computational power.
  arXiv  Detail & Related papers  (2021-06-06T13:15:25Z)
• Quantum Gram-Schmidt Processes and Their Application to Efficient State Read-out for Quantum Algorithms [87.04438831673063]
  We present an efficient read-out protocol that yields the classical vector form of the generated state. Our protocol suits the case that the output state lies in the row space of the input matrix. One of our technical tools is an efficient quantum algorithm for performing the Gram-Schmidt orthonormal procedure.
  arXiv  Detail & Related papers  (2020-04-14T11:05:26Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.