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Scaling bottlenecks the making of digital quantum computers, posing challenges from both the quantum and the classical components. We present a classical architecture to cope with a comprehensive list of the latter challenges {\em all at…

Quantum computers progress toward outperforming classical supercomputers, but quantum errors remain their primary obstacle. The key to overcoming errors on near-term devices has emerged through the field of quantum error mitigation,…

Quantum Physics · Physics 2025-05-14 Haoran Liao , Derek S. Wang , Iskandar Sitdikov , Ciro Salcedo , Alireza Seif , Zlatko K. Minev

Loss and noise quickly destroy quantum entanglement. Nevertheless, recent work has shown that a quadrature-entangled light source can reap a substantial performance advantage over all classical-state sources of the same average transmitter…

Quantum Physics · Physics 2015-05-20 Saikat Guha , Jeffrey H. Shapiro

Quantum illumination employs entangled states to detect a weakly reflective target in a thermal bath. The performance of a given entangled state is evaluated from the minimum error probability in the asymptotic limit, which is compared…

Quantum Physics · Physics 2021-10-14 Changsuk Noh , Changhyoup Lee , Su-Yong Lee

In a recent study (Ref. [1]), quantum annealing was reported to exhibit a scaling advantage for approximately solving Quadratic Unconstrained Binary Optimization (QUBO). However, this claim critically depends on the choice of classical…

Quantum Physics · Physics 2025-05-29 J. Pawlowski , P. Tarasiuk , J. Tuziemski , L. Pawela , B. Gardas

High-quality control is a fundamental requirement for quantum computation, but practically it is often hampered by the presence of various types of noises, which can be static or time-dependent. In many realistic scenarios, multiple noise…

Quantum Physics · Physics 2024-03-04 Bowen Shao , Xiaodong Yang , Ran Liu , Yue Zhai , Dawei Lu , Tao Xin , Jun Li

Quantum imaging promises increased imaging performance over classical protocols. However, there are a number of aspects of quantum imaging that are not well understood. In particular, it has so far been unknown how to compare classical and…

Quantum Physics · Physics 2012-09-19 Carlos A. Pérez-Delgado , Mark E. Pearce , Pieter Kok

Quantum illumination leverages entanglement to surpass classical target detection, even in high-noise environments. Remarkably, its quantum advantage persists despite entanglement degradation caused by environmental decoherence. A central…

Quantum Physics · Physics 2025-07-24 Xin Chen , Zhibin Ye

We develop several algorithms for performing quantum phase estimation based on basic measurements and classical post-processing. We present a pedagogical review of quantum phase estimation and simulate the algorithm to numerically determine…

Quantum Physics · Physics 2013-07-30 Krysta M. Svore , Matthew B. Hastings , Michael Freedman

Quantum computers have enabled solving problems beyond the current computers' capabilities. However, this requires handling noise arising from unwanted interactions in these systems. Several protocols have been proposed to address efficient…

Quantum Physics · Physics 2021-09-14 Ali Shaib , Mohamad H. Naim , Mohammed E. Fouda , Rouwaida Kanj , Fadi Kurdahi

The use of mid-circuit measurement and qubit reset within quantum programs has been introduced recently and several applications demonstrated that perform conditional branching based on these measurements. In this work, we go a step further…

We develop a classical bit-flip correction method to mitigate measurement errors on quantum computers. This method can be applied to any operator, any number of qubits, and any realistic bit-flip probability. We first demonstrate the…

Quantum Physics · Physics 2022-09-02 Lena Funcke , Tobias Hartung , Karl Jansen , Stefan Kühn , Paolo Stornati , Xiaoyang Wang

Learning problems involving quantum data are natural candidates for demonstrating an advantage in quantum machine learning. Recent results indicate that, for certain tasks and under noiseless conditions, coherent processing of quantum data…

Quantum machine learning is often motivated by the idea that quantum systems can expose useful high-dimensional structure that is difficult to access with classical models. We isolate one central component of this claim: the fixed…

Quantum Physics · Physics 2026-05-26 Toheeb Ogunade , Taofeek Kassim , Etinosa Osaro

Towards the practical use of quantum computers in the NISQ era, as well as the realization of fault-tolerant quantum computers that utilize quantum error correction codes, pressing needs have emerged for the control hardware and software…

A key component of a quantum machine learning model operating on classical inputs is the design of an embedding circuit mapping inputs to a quantum state. This paper studies a transfer learning setting in which classical-to-quantum…

Quantum Physics · Physics 2022-12-01 Sharu Theresa Jose , Osvaldo Simeone

The development of emerging technologies in quantum optics demands accurate models that faithfully capture genuine quantum effects. Mature semiclassical approaches reach their limits when confronted with quantized electromagnetic fields,…

Existing protocols for benchmarking current quantum co-processors fail to meet the usual standards for assessing the performance of High-Performance-Computing platforms. After a synthetic review of these protocols -- whether at the gate,…

Quantum Physics · Physics 2021-07-27 Simon Martiel , Thomas Ayral , Cyril Allouche

Quantum technologies work by utilizing properties inherent in quantum systems such as quantum coherence and quantum entanglement and are expected to be superior to classical counterparts for solving certain problems in science and…

Quantum Physics · Physics 2023-04-10 Yusuke Hama , Hirofumi Nishi

In this paper, we theoretically and experimentally analyze sequential processors with limited communication between parts. We compare the expressivity of sequential quantum and classical processors under the same constraints. They consist…