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We propose DiffQ a differentiable method for model compression for quantizing model parameters without gradient approximations (e.g., Straight Through Estimator). We suggest adding independent pseudo quantization noise to model parameters…

Machine Learning · Statistics 2022-10-18 Alexandre Défossez , Yossi Adi , Gabriel Synnaeve

A new method of quantum state tomography for quantum information processing is described. The method based on two-dimensional Fourier transform technique involves detection of all the off-diagonal elements of the density matrix in a…

Quantum Physics · Physics 2009-11-07 Ranabir Das , T. S. Mahesh , Anil Kumar

Existing edge detection methods often suffer from noise amplification and excessive retention of non-salient details, limiting their applicability in high-precision industrial scenarios. To address these challenges, we propose CAM-EDIT, a…

Computer Vision and Pattern Recognition · Computer Science 2025-05-05 Ru-yu Yan , Da-Qing Zhang

Noisy intermediate-scale quantum (NISQ) devices offer unique platforms to test and evaluate the behavior of non-fault-tolerant quantum computing. However, validating programs on NISQ devices is difficult due to fluctuations in the…

Quantum Physics · Physics 2022-01-10 Megan L. Dahlhauser , Travis S. Humble

The Quantum Angle Generator (QAG) is a new full Quantum Machine Learning model designed to generate accurate images on current Noise Intermediate Scale (NISQ) Quantum devices. Variational quantum circuits form the core of the QAG model, and…

Quantum Physics · Physics 2023-10-24 Florian Rehm , Sofia Vallecorsa , Kerstin Borras , Dirk Krücker , Michele Grossi , Valle Varo

Quantum computers have the potential to advance material design and drug discovery by performing costly electronic structure calculations. A critical aspect of this application requires optimizing the limited resources of the quantum…

Edge detection remains a fundamental yet challenging task in computer vision, especially under varying illumination, noise, and complex scene conditions. This paper introduces a Hybrid Multi-Stage Learning Framework that integrates…

Computer Vision and Pattern Recognition · Computer Science 2025-03-31 Mark Phil Pacot , Jayno Juventud , Gleen Dalaorao

Efficient decoding to estimate error locations from outcomes of syndrome measurement is the prerequisite for quantum error correction. Decoding in presence of circuit-level noise including measurement errors should be considered in case of…

Current self-supervised denoising techniques achieve impressive results, yet their real-world application is frequently constrained by substantial computational and memory demands, necessitating a compromise between inference speed and…

Computer Vision and Pattern Recognition · Computer Science 2025-10-20 Tomáš Chobola , Julia A. Schnabel , Tingying Peng

Quantum computing technology has reached a second renaissance in the last decade. However, in the NISQ era pointed out by John Preskill in 2018, quantum noise and decoherence, which affect the accuracy and execution effect of quantum…

Quantum Physics · Physics 2020-01-09 Yu Zhang , Haowei Deng , Quanxi Li , Haoze Song , Leihai Nie

Current quantum devices have unutilized high-level quantum resources. More and more attention has been paid to the qudit quantum systems with larger than two dimensions to maximize the potential computing power of quantum computation. Then,…

Quantum Physics · Physics 2025-04-18 Shuai Yang , Lihao Xu , Guojing Tian , Xiaoming Sun

Efficient computation of molecular energies is an exciting application of quantum computing for quantum chemistry, but current noisy intermediate-scale quantum (NISQ) devices can only execute shallow circuits, limiting existing variational…

Specialized edge accelerators rely on low-bit quantization, but vendor compilers differ in scaling, clipping, and kernel support, often as black boxes. The same floating-point (FP) checkpoint can therefore yield inconsistent accuracy across…

Machine Learning · Computer Science 2025-11-21 Rayen Dhahri , Steffen Urban

Quantum non-demolition (QND) measurement of collective variables by off-resonant optical probing has the ability to create entanglement and squeezing in atomic ensembles. Until now, this technique has been applied to real or effective spin…

Quantum Physics · Physics 2015-05-19 M. Koschorreck , M. Napolitano , B. Dubost , M. W. Mitchell

Realizing the full potential of quantum computation requires quantum error correction (QEC), with most recent breakthrough demonstrations of QEC using the surface code. QEC codes use multiple noisy physical qubits to encode information in…

In 2017, John Preskill defined Noisy Intermediate Scale Quantum (NISQ) computers as an intermediate step on the road to large scale error corrected fault-tolerant quantum computers (FTQC). The NISQ regime corresponds to noisy qubit quantum…

Quantum Physics · Physics 2023-06-13 Olivier Ezratty

Implementing many important sub-circuits on near-term quantum devices remains a challenge due to the high levels of noise and the prohibitive depth on standard nearest-neighbour topologies. Overcoming these barriers will likely require…

Quantum Physics · Physics 2024-11-06 Angus Mingare , Anastasia Moroz , Marcell D Kovacs , Andrew G Green

Due to several physical limitations in the realisation of quantum hardware, today's quantum computers are qualified as Noisy Intermediate-Scale Quantum (NISQ) hardware. NISQ hardware is characterized by a small number of qubits (50 to a few…

Hardware Architecture · Computer Science 2020-10-08 Siyuan Niu , Adrien Suau , Gabriel Staffelbach , Aida Todri-Sanial

Quantum computers have rapidly improved in scale and fidelity, yet access to large systems remains limited for most researchers. This makes accurate and scalable noisy quantum simulation essential. While density matrix simulation provides…

Quantum Physics · Physics 2026-05-19 Siddharth Dangwal , Tina Oberoi , Ajay Sailopal , Dhirpal Shah , Frederic T. Chong

The aim of this paper is to propose a new approach for the pattern recognition of power quality (PQ) disturbances based on Empirical mode decomposition (EMD) and $k$ Nearest Neighbor ($k$-NN) classifier. Since EMD decomposes a signal into…

Signal Processing · Electrical Eng. & Systems 2019-08-16 Faeza Hafiz , Celia Shahnaz
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