Quantum Circuits, Feature Maps, and Expanded Pseudo-Entropy: A Categorical Theoretic Analysis of Encoding Real-World Data into a Quantum Computer
- URL: http://arxiv.org/abs/2410.22084v1
- Date: Tue, 29 Oct 2024 14:38:01 GMT
- Title: Quantum Circuits, Feature Maps, and Expanded Pseudo-Entropy: A Categorical Theoretic Analysis of Encoding Real-World Data into a Quantum Computer
- Authors: Andrew Vlasic,
- Abstract summary: The aim of this paper is to determine the efficacy of an encoding scheme to map real-world data into a quantum circuit.
The method calculates the Shannon entropy of each of the data points from a point-cloud, hence, samples from an embedded manifold.
- Score: 0.0
- License:
- Abstract: This manuscripts proposes a new and novel numerical method to the determine the efficacy of an encoding scheme to map real-world data into a quantum circuit. The method calculates the Shannon entropy of each of the data points from a point-cloud, hence, samples from an embedded manifold, and calculates the expanded concept of pseudo-entropy applied to each respective quantum operator that comes from a given quantum feature map, and not the density operator. In the recent decade, there has been a continuous advancement of translating machine learning into a quantum circuit with many promising results. For quantum machine learning, a major underlying question is how to encode real-world data into a quantum circuit without losing information and adding noise. A few notable methods derived are expressibility, where the distribution of the output of states from the circuit are compared against the Haar probability measure with information theoretic techniques, and expressivity, a method that maps the expectation of a quantum circuit to the space of complex functions via a partial Fourier series, noting that more intricate the function the more expressive, and using the symmetry embedded within the data to derive a quantum feature map. The proposed pseudo-entropy method is discussed to and empirically shown to generalize these methods. Furthermore, this method is argued to also generalize symmetric quantum feature maps. The discussions and arguments are a reasonable basis for understanding the connections but require deeper mathematical analysis.
Related papers
- Quantum data encoding as a distinct abstraction layer in the design of quantum circuits [1.1510009152620668]
We formalize the concept of quantum data encoding, namely the format providing a representation of a data set through a quantum state.
We show how major quantum algorithms find a natural interpretation in terms of data loading.
The new conceptual framework is exemplified by considering its application to quantum-based Monte Carlo simulations.
arXiv Detail & Related papers (2024-09-14T07:00:58Z) - Efficient Learning for Linear Properties of Bounded-Gate Quantum Circuits [63.733312560668274]
Given a quantum circuit containing d tunable RZ gates and G-d Clifford gates, can a learner perform purely classical inference to efficiently predict its linear properties?
We prove that the sample complexity scaling linearly in d is necessary and sufficient to achieve a small prediction error, while the corresponding computational complexity may scale exponentially in d.
We devise a kernel-based learning model capable of trading off prediction error and computational complexity, transitioning from exponential to scaling in many practical settings.
arXiv Detail & Related papers (2024-08-22T08:21:28Z) - Lightcone Bounds for Quantum Circuit Mapping via Uncomplexity [1.0360348400670518]
We show that a minimal SWAP-gate count for executing a quantum circuit on a device emerges via the minimization of the distance between quantum states.
This work constitutes the first use of quantum circuit uncomplexity to practically-relevant quantum computing.
arXiv Detail & Related papers (2024-02-01T10:32:05Z) - Quantum algorithms: A survey of applications and end-to-end complexities [90.05272647148196]
The anticipated applications of quantum computers span across science and industry.
We present a survey of several potential application areas of quantum algorithms.
We outline the challenges and opportunities in each area in an "end-to-end" fashion.
arXiv Detail & Related papers (2023-10-04T17:53:55Z) - Realizing Non-Physical Actions through Hermitian-Preserving Map
Exponentiation [1.0255759863714506]
We introduce the Hermitian-preserving mapiation algorithm, which can effectively realize the action of an arbitrary Hermitian-preserving map by encoding its output into a quantum process.
Our findings present a pathway for systematically and efficiently implementing non-physical actions with quantum devices.
arXiv Detail & Related papers (2023-08-15T18:00:04Z) - Quantivine: A Visualization Approach for Large-scale Quantum Circuit
Representation and Analysis [31.203764035373677]
We develop Quantivine, an interactive system for exploring and understanding quantum circuits.
A series of novel circuit visualizations are designed to uncover contextual details such as qubit provenance, parallelism, and entanglement.
The effectiveness of Quantivine is demonstrated through two usage scenarios of quantum circuits with up to 100 qubits.
arXiv Detail & Related papers (2023-07-18T04:51:28Z) - Calculating the many-body density of states on a digital quantum
computer [58.720142291102135]
We implement a quantum algorithm to perform an estimation of the density of states on a digital quantum computer.
We use our algorithm to estimate the density of states of a non-integrable Hamiltonian on the Quantinuum H1-1 trapped ion chip for a controlled register of 18bits.
arXiv Detail & Related papers (2023-03-23T17:46:28Z) - Quantum process tomography of continuous-variable gates using coherent
states [49.299443295581064]
We demonstrate the use of coherent-state quantum process tomography (csQPT) for a bosonic-mode superconducting circuit.
We show results for this method by characterizing a logical quantum gate constructed using displacement and SNAP operations on an encoded qubit.
arXiv Detail & Related papers (2023-03-02T18:08:08Z) - Analysis of arbitrary superconducting quantum circuits accompanied by a
Python package: SQcircuit [0.0]
Superconducting quantum circuits are a promising hardware platform for realizing a fault-tolerant quantum computer.
We develop a framework to construct a superconducting quantum circuit's quantized Hamiltonian from its physical description.
We implement the methods described in this work in an open-source Python package SQcircuit.
arXiv Detail & Related papers (2022-06-16T17:24:51Z) - Improved Quantum Algorithms for Fidelity Estimation [77.34726150561087]
We develop new and efficient quantum algorithms for fidelity estimation with provable performance guarantees.
Our algorithms use advanced quantum linear algebra techniques, such as the quantum singular value transformation.
We prove that fidelity estimation to any non-trivial constant additive accuracy is hard in general.
arXiv Detail & Related papers (2022-03-30T02:02:16Z) - Information Scrambling in Computationally Complex Quantum Circuits [56.22772134614514]
We experimentally investigate the dynamics of quantum scrambling on a 53-qubit quantum processor.
We show that while operator spreading is captured by an efficient classical model, operator entanglement requires exponentially scaled computational resources to simulate.
arXiv Detail & Related papers (2021-01-21T22:18:49Z)
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.