Quantum Detection of Sequency-Band Structure
- URL: http://arxiv.org/abs/2602.08393v1
- Date: Mon, 09 Feb 2026 08:47:51 GMT
- Title: Quantum Detection of Sequency-Band Structure
- Authors: Alok Shukla, Prakash Vedula,
- Abstract summary: We present a quantum algorithm for estimating the amplitude content of user-specified sequency bands in quantum-encoded signals.<n>The method employs a sequency-ordered Quantum Walsh-Hadamard Transform (QWHT), a comparator-based oracle that coherently marks basis states within an arbitrary sequency range.<n>This enables the detection of structured signal components, including both high- and low-sequency features, as well as the identification of rapid sign-change behavior associated with noise or anomalies.
- Score: 0.5729426778193398
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: We present a quantum algorithm for estimating the amplitude content of user-specified sequency bands in quantum-encoded signals. The method employs a sequency-ordered Quantum Walsh-Hadamard Transform (QWHT), a comparator-based oracle that coherently marks basis states within an arbitrary sequency range, and Quantum Amplitude Estimation (QAE) to estimate the total probability mass in the selected band. This enables the detection of structured signal components, including both high- and low-sequency features, as well as the identification of rapid sign-change behavior associated with noise or anomalies. The proposed method can be embedded as a module within a larger quantum algorithm; in this setting, both the input and output remain fully quantum, enabling seamless integration with upstream and downstream quantum operations. We show that the sequency-ordered QWHT can be implemented with circuit depth $O(\log_2 N)$ (equivalently $O(n)$ for $N=2^n$) when acting on an amplitude-encoded quantum state, whereas computing the full Walsh-Hadamard spectrum of an explicit length-$N$ classical signal requires $O(N\log_2 N)$ operations via the fast Walsh-Hadamard transform. This results in an exponential quantum advantage when the QWHT is used as a modular block within a larger quantum algorithm, relative to classical fast Walsh-Hadamard transform-based approaches operating on explicit data. From an application perspective, the proposed sequency band-energy estimation may be interpreted as a structure-based anomaly indicator, enabling the detection of unexpected high-sequency components relative to a nominal low-sequency signal class. The algorithm is applicable to quantum-enhanced signal processing tasks such as zero-crossing analysis, band-limited noise estimation, and feature extraction in the Walsh basis.
Related papers
- Quantum Circuit-Based Adaptation for Credit Risk Analysis [27.308408027453012]
Noisy and Intermediate-Scale Quantum, or NISQ, processors are sensitive to noise, prone to quantum decoherence, and are not yet capable of continuous quantum error correction for fault-tolerant quantum computation.<n>We experimentally study how hardware-aware variational quantum circuits on a superconducting quantum processing unit can model distributions relevant to specific use-case applications for Credit Risk Analysis.
arXiv Detail & Related papers (2026-01-11T11:17:37Z) - Continual Quantum Architecture Search with Tensor-Train Encoding: Theory and Applications to Signal Processing [68.35481158940401]
CL-QAS is a continual quantum architecture search framework.<n>It mitigates challenges of costly encoding amplitude and forgetting in variational quantum circuits.<n>It achieves controllable robustness expressivity, sample-efficient generalization, and smooth convergence without barren plateaus.
arXiv Detail & Related papers (2026-01-10T02:36:03Z) - Variational noise mitigation in quantum circuits: the case of Quantum Fourier Transform [35.18016233072556]
We perform numerical simulations for two qubits under both coherent and incoherent noise.<n>Our results show that the variational circuit can reproduce the QFT with higher fidelity in scenarios dominated by coherent noise.<n>This demonstrates the potential of the approach as an effective error-mitigation strategy for small- to medium-scale quantum systems.
arXiv Detail & Related papers (2025-11-07T14:35:55Z) - Quantum Approximate Optimization Algorithm for MIMO with Quantized b-bit Beamforming [47.98440449939344]
Multiple-input multiple-output (MIMO) is critical for 6G communication, offering improved spectral efficiency and reliability.<n>This paper explores the use of the Quantum Approximate Optimization Algorithm (QAOA) and alternating optimization to address the problem of b-bit quantized phase shifters both at the transmitter and the receiver.<n>We demonstrate that the structure of this quantized beamforming problem aligns naturally with hybrid-classical methods like QAOA, as the phase shifts used in beamforming can be directly mapped to rotation gates in a quantum circuit.
arXiv Detail & Related papers (2025-10-07T17:53:02Z) - Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach [36.05085942729295]
This paper introduces a Quantum Natural Policy Gradient (QNPG) algorithm, which replaces the random sampling used in classicalNPG estimators with a deterministic gradient estimation approach.<n>The proposed QNPG algorithm achieves a sample complexity of $tildemathcalO(epsilon-1.5)$ for queries to the quantum oracle, significantly improving the classical lower bound of $tildemathcalO(epsilon-2)$ for queries to the Markov Decision Process (MDP)
arXiv Detail & Related papers (2025-01-27T17:38:30Z) - Entanglement-induced exponential advantage in amplitude estimation via state matrixization [11.282486674587236]
Estimating quantum amplitude, or the overlap between two quantum states, is a fundamental task in quantum computing.<n>We introduce a novel algorithmic framework for quantum amplitude estimation by transforming pure states into their matrix forms.<n>We reconstruct amplitude estimation algorithms within the novel matrixization framework through a technique known as channel block encoding.
arXiv Detail & Related papers (2024-08-25T04:35:53Z) - SWAP-less Implementation of Quantum Algorithms [0.0]
We present a formalism based on tracking the flow of parity quantum information to implement algorithms on devices with limited connectivity.
We leverage the fact that entangling gates not only manipulate quantum states but can also be exploited to transport quantum information.
arXiv Detail & Related papers (2024-08-20T14:51:00Z) - Mitigating Errors on Superconducting Quantum Processors through Fuzzy
Clustering [38.02852247910155]
A new Quantum Error Mitigation (QEM) technique uses Fuzzy C-Means clustering to specifically identify measurement error patterns.
We report a proof-of-principle validation of the technique on a 2-qubit register, obtained as a subset of a real NISQ 5-qubit superconducting quantum processor.
We demonstrate that the FCM-based QEM technique allows for reasonable improvement of the expectation values of single- and two-qubit gates based quantum circuits.
arXiv Detail & Related papers (2024-02-02T14:02:45Z) - A noise-limiting quantum algorithm using mid-circuit measurements for
dynamical correlations at infinite temperature [0.0]
We introduce a quantum channel built out of mid-circuit measurements and feed-forward.
In the presence of a depolarizing channel it still displays a meaningful, non-zero signal in the large depth limit.
We showcase the noise resilience of this quantum channel on Quantinuum's H1-1 ion-trap quantum computer.
arXiv Detail & Related papers (2024-01-04T11:25:04Z) - Quantum Algorithm for Signal Denoising [32.77959665599749]
The proposed algorithm is able to process textitboth classical and quantum signals.
Numerical results show that it is efficient at removing noise of both classical and quantum origin.
arXiv Detail & Related papers (2023-12-24T05:16:04Z) - Quantum Speedup for Higher-Order Unconstrained Binary Optimization and
MIMO Maximum Likelihood Detection [2.5272389610447856]
We propose a quantum algorithm that supports a real-valued higher-order unconstrained binary optimization problem.
The proposed algorithm is capable of reducing the query complexity in the classical domain and providing a quadratic speedup in the quantum domain.
arXiv Detail & Related papers (2022-05-31T00:14:49Z) - Automatic quantum circuit encoding of a given arbitrary quantum state [0.0]
We propose a quantum-classical hybrid algorithm to encode a given arbitrarily quantum state onto an optimal quantum circuit.
The proposed algorithm employs as an objective function the absolute value of fidelity $F = langle 0 vert hatmathcalCdagger vert Psi rangle$.
We experimentally demonstrate that a quantum circuit generated by the AQCE algorithm can indeed represent the original quantum state reasonably on a noisy real quantum device.
arXiv Detail & Related papers (2021-12-29T12:33:41Z) - Multistate Transition Dynamics by Strong Time-Dependent Perturbation in
NISQ era [0.0]
We develop a quantum computing scheme utilizing McLachlan variational principle in a hybrid quantum-classical algorithm.
Results for transition probabilities are obtained with accuracy better than 1%, as established by comparison to the benchmark data.
arXiv Detail & Related papers (2021-12-13T00:49:15Z) - Improving the Performance of Deep Quantum Optimization Algorithms with
Continuous Gate Sets [47.00474212574662]
Variational quantum algorithms are believed to be promising for solving computationally hard problems.
In this paper, we experimentally investigate the circuit-depth-dependent performance of QAOA applied to exact-cover problem instances.
Our results demonstrate that the use of continuous gate sets may be a key component in extending the impact of near-term quantum computers.
arXiv Detail & Related papers (2020-05-11T17:20:51Z)
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.