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The quantum approximate optimization algorithm (QAOA) has become a cornerstone of contemporary quantum applications development. Here we show that the \emph{density} of problem constraints versus problem variables acts as a performance…

Quantum Physics · Physics 2021-08-31 V. Akshay , H. Philathong , I. Zacharov , J. Biamonte

We give new quantum algorithms for evaluating composed functions whose inputs may be shared between bottom-level gates. Let $f$ be an $m$-bit Boolean function and consider an $n$-bit function $F$ obtained by applying $f$ to conjunctions of…

Quantum Physics · Physics 2021-09-22 Mark Bun , Robin Kothari , Justin Thaler

Given a matrix $A \in \mathbb{R}^{n\times n}$, we consider the problem of maximizing $x^TAx$ subject to the constraint $x \in \{-1,1\}^n$. This problem, called MaxQP by Charikar and Wirth [FOCS'04], generalizes MaxCut and has natural…

Data Structures and Algorithms · Computer Science 2020-12-16 Danny Hermelin , Leon Kellerhals , Rolf Niedermeier , Rami Pugatch

Optimization of quantum circuits using an efficient compiler is key to its success for NISQ computers. Several 3rd party compilers are evolving to offer improved performance for large quantum circuits. These 3rd parties, or just a certain…

Quantum low-density parity-check (qLDPC) codes are an important component in the quest for quantum fault tolerance. Dramatic recent progress on qLDPC codes has led to constructions which are asymptotically good, and which admit linear-time…

Quantum Physics · Physics 2024-11-08 Louis Golowich , Venkatesan Guruswami

The quantum approximate optimization algorithm (QAOA) has numerous promising applications in solving the combinatorial optimization problems on near-term Noisy Intermediate Scalable Quantum (NISQ) devices. QAOA has a quantum-classical…

Quantum Physics · Physics 2022-02-17 Xinwei Lee , Yoshiyuki Saito , Dongsheng Cai , Nobuyoshi Asai

Quantum hardware suffers from high error rates and noise, which makes directly running applications on them ineffective. Quantum Error Correction (QEC) is a critical technique towards fault tolerance which encodes the quantum information…

Quantum Physics · Physics 2024-04-24 Hanrui Wang , Pengyu Liu , Yilian Liu , Jiaqi Gu , Jonathan Baker , Frederic T. Chong , Song Han

Quadratic programming (QP) forms a crucial foundation in optimization, encompassing a broad spectrum of domains and serving as the basis for more advanced algorithms. Consequently, as the scale and complexity of modern applications continue…

Optimization and Control · Mathematics 2025-01-28 Augustinos D. Saravanos , Hunter Kuperman , Alex Oshin , Arshiya Taj Abdul , Vincent Pacelli , Evangelos A. Theodorou

Forward Error Correction (FEC) provides reliable data flow in wireless networks despite the presence of noise and interference. However, its processing demands significant fraction of a wireless network's resources, due to its…

Quantum Physics · Physics 2024-08-22 Srikar Kasi , James Sud , Kyle Jamieson , Gokul Subramanian Ravi

The Quantum Approximate Optimization Algorithm (QAOA) is a promising candidate algorithm for demonstrating quantum advantage in optimization using near-term quantum computers. However, QAOA has high requirements on gate fidelity due to the…

Quantum Physics · Physics 2023-03-20 Xiaoyuan Liu , Ruslan Shaydulin , Ilya Safro

We consider the decoding of LDPC codes over GF(q) with the low-complexity majority algorithm from [1]. A modification of this algorithm with multiple thresholds is suggested. A lower estimate on the decoding radius realized by the new…

Information Theory · Computer Science 2015-02-25 Alexey Frolov , Victor Zyablov

Quantum computing requires effective error correction strategies to mitigate noise and decoherence. Quantum Low-Density Parity-Check (QLDPC) codes have emerged as a promising solution for scalable Quantum Error Correction (QEC) applications…

Machine Learning · Computer Science 2025-11-04 Ameya S. Bhave , Navnil Choudhury , Kanad Basu

Combinatorial optimization lies at the heart of numerous real-world applications. For a broad category of optimization problems, quantum computing is expected to exhibit quantum speed-up over classic computing. Among various quantum…

Quantum Physics · Physics 2025-09-23 Zixu Wang , Jack Mandell , Yangyang Xu , Jian Shi

The surface code is one of the most promising candidates for combating errors in large scale fault-tolerant quantum computation. A fault-tolerant decoder is a vital part of the error correction process---it is the algorithm which computes…

Quantum Physics · Physics 2015-09-15 Fern H. E. Watson , Hussain Anwar , Dan E. Browne

Quantum low-density parity-check (qLDPC) codes are a promising construction for drastically reducing the overhead of fault-tolerant quantum computing (FTQC) architectures. However, all of the known hardware implementations of these codes…

Fault tolerance is a prerequisite for scalable quantum computing. Architectures based on 2D topological codes are effective for near-term implementations of fault tolerance. To obtain high performance with these architectures, we require a…

Quantum Physics · Physics 2018-10-23 Ben Criger , Imran Ashraf

Practical large-scale quantum computation requires both efficient error correction and robust implementation of logical operations. Three-dimensional (3D) color codes are a promising candidate for fault-tolerant quantum computation due to…

Quantum Physics · Physics 2025-12-23 Friederike Butt , Lars Esser , Markus Müller

We present a protocol to encode and decode arbitrary quantum states in the parity architecture with constant circuit depth using measurements, local nearest-neighbor and single-qubit operations only. While this procedure typically requires…

Quantum Physics · Physics 2024-04-17 Anette Messinger , Michael Fellner , Wolfgang Lechner

As the quantum computing ecosystem grows in popularity and utility it is important to identify and address the security and privacy vulnerabilities before they can be widely exploited. One major concern is the involvement of third party…

Quantum Physics · Physics 2023-05-05 Suryansh Upadhyay , Swaroop Ghosh

Consider the following distributed optimization scenario. A worker has access to training data that it uses to compute the gradients while a server decides when to stop iterative computation based on its target accuracy or delay…

Machine Learning · Computer Science 2022-04-28 Chung-Yi Lin , Victoria Kostina , Babak Hassibi
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