Resource-efficient Variational Block-Encoding
- URL: http://arxiv.org/abs/2507.17658v1
- Date: Wed, 23 Jul 2025 16:24:21 GMT
- Title: Resource-efficient Variational Block-Encoding
- Authors: Leon Rullkötter, Sebastian Weber, Vamshi Mohan Katukuri, Christian Tutschku, Bharadwaj Chowdary Mummaneni,
- Abstract summary: We find that the number of variational parameters in the parameterized quantum circuit approaches the number of free parameters in the input matrices.<n>symmetries present in the input matrix can be incorporated into the ansatz circuit, reducing the parameter count further.<n>While determining variational block-encodings ceases to be computationally feasible for large system sizes, the constructed operators can be used as components of larger block-encodings.
- Score: 0.6424596066997003
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Block-encoding operators are one of the essential components in quantum algorithms based on Quantum Signal Processing. Their gate complexity largely determines the overall gate complexity of the full algorithm. Using variational methods, we aim to compile block-encoding unitaries with near-optimal resource requirements for a large range of input matrices. We find that the number of variational parameters in the parameterized quantum circuit approaches the number of free parameters in the input matrices, depending on whether they are real, complex and/or hermitian. Additionally, symmetries present in the input matrix can be incorporated into the ansatz circuit, reducing the parameter count further and making optimization possible for up to n=8 qubits. While determining variational block-encodings ceases to be computationally feasible for large system sizes, the constructed operators can be used as components of larger block-encodings via a linear combination of block-encodings.
Related papers
- Fast correlated decoding of transversal logical algorithms [67.01652927671279]
Quantum error correction (QEC) is required for large-scale computation, but incurs a significant resource overhead.<n>Recent advances have shown that by jointly decoding logical qubits in algorithms composed of logical gates, the number of syndrome extraction rounds can be reduced.<n>Here, we reform the problem of decoding circuits by directly decoding relevant logical operator products as they propagate through the circuit.
arXiv Detail & Related papers (2025-05-19T18:00:00Z) - An Efficient Quantum Classifier Based on Hamiltonian Representations [50.467930253994155]
Quantum machine learning (QML) is a discipline that seeks to transfer the advantages of quantum computing to data-driven tasks.<n>We propose an efficient approach that circumvents the costs associated with data encoding by mapping inputs to a finite set of Pauli strings.<n>We evaluate our approach on text and image classification tasks, against well-established classical and quantum models.
arXiv Detail & Related papers (2025-04-13T11:49:53Z) - Binary Tree Block Encoding of Classical Matrix [6.334095794072344]
Block-encoding is a critical computation in quantum computing.<n>Our protocol is named Binary Tree Block-encoding (textttBITBLE)
arXiv Detail & Related papers (2025-04-08T02:53:43Z) - Optimizing Quantum Transformation Matrices: A Block Decomposition Approach for Efficient Gate Reduction [5.453850739960517]
The paper introduces an algorithm designed to approximate quantum transformation matrix with a restricted number of gates.<n>Inspired by the Block Decompose algorithm, our approach processes transformation matrices in a block-wise manner.<n> Simulations validate the effectiveness of the algorithm in approximating transformations with significantly fewer gates.
arXiv Detail & Related papers (2024-12-18T14:54:45Z) - Deep Learning Assisted Multiuser MIMO Load Modulated Systems for
Enhanced Downlink mmWave Communications [68.96633803796003]
This paper is focused on multiuser load modulation arrays (MU-LMAs) which are attractive due to their low system complexity and reduced cost for millimeter wave (mmWave) multi-input multi-output (MIMO) systems.
The existing precoding algorithm for downlink MU-LMA relies on a sub-array structured (SAS) transmitter which may suffer from decreased degrees of freedom and complex system configuration.
In this paper, we conceive an MU-LMA system employing a full-array structured (FAS) transmitter and propose two algorithms accordingly.
arXiv Detail & Related papers (2023-11-08T08:54:56Z) - On efficient quantum block encoding of pseudo-differential operators [6.134067544403308]
Block encoding lies at the core of many existing quantum algorithms.
This paper presents a study of the block encoding of a rich family of dense operators: the pseudo-differential operators (PDOs)
arXiv Detail & Related papers (2023-01-21T07:18:57Z) - End-to-end resource analysis for quantum interior point methods and portfolio optimization [63.4863637315163]
We provide a complete quantum circuit-level description of the algorithm from problem input to problem output.
We report the number of logical qubits and the quantity/depth of non-Clifford T-gates needed to run the algorithm.
arXiv Detail & Related papers (2022-11-22T18:54:48Z) - Automatic and effective discovery of quantum kernels [41.61572387137452]
Quantum computing can empower machine learning models by enabling kernel machines to leverage quantum kernels for representing similarity measures between data.<n>We present an approach to this problem, which employs optimization techniques, similar to those used in neural architecture search and AutoML.<n>The results obtained by testing our approach on a high-energy physics problem demonstrate that, in the best-case scenario, we can either match or improve testing accuracy with respect to the manual design approach.
arXiv Detail & Related papers (2022-09-22T16:42:14Z) - Optimization-based Block Coordinate Gradient Coding for Mitigating
Partial Stragglers in Distributed Learning [58.91954425047425]
This paper aims to design a new gradient coding scheme for mitigating partial stragglers in distributed learning.
We propose a gradient coordinate coding scheme with L coding parameters representing L possibly different diversities for the L coordinates, which generates most gradient coding schemes.
arXiv Detail & Related papers (2022-06-06T09:25:40Z) - FABLE: Fast Approximate Quantum Circuits for Block-Encodings [0.0]
We propose FABLE, a method to generate approximate quantum circuits for block-encodings of matrices in a fast manner.
FABLE circuits have a simple structure and are directly formulated in terms of one- and two-qubit gates.
We show that FABLE circuits can be compressed and sparsified.
arXiv Detail & Related papers (2022-04-29T21:06:07Z) - Adaptive pruning-based optimization of parameterized quantum circuits [62.997667081978825]
Variisy hybrid quantum-classical algorithms are powerful tools to maximize the use of Noisy Intermediate Scale Quantum devices.
We propose a strategy for such ansatze used in variational quantum algorithms, which we call "Efficient Circuit Training" (PECT)
Instead of optimizing all of the ansatz parameters at once, PECT launches a sequence of variational algorithms.
arXiv Detail & Related papers (2020-10-01T18:14:11Z) - Approximate Quantum Circuit Synthesis using Block-Encodings [0.0]
One of the challenges in quantum computing is the synthesis of unitary operators into quantum circuits with polylogarithmic gate complexity.
We propose a novel approximate quantum circuit synthesis technique by relaxing the unitary constraints and interchanging them for ancilla qubits via block-encodings.
arXiv Detail & Related papers (2020-07-02T22:30:28Z)
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.