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We propose upper and lower bounds on the maximum success probability for discriminating given quantum states. The proposed upper bound is obtained from a suboptimal solution to the dual problem of the corresponding optimal state…

Quantum Physics · Physics 2018-01-12 Kenji Nakahira , Tsuyoshi Sasaki Usuda , Kentaro Kato

Understanding algorithmic error accumulation in quantum simulation is crucial due to its fundamental significance and practical applications in simulating quantum many-body system dynamics. Conventional theories typically apply the triangle…

Quantum Physics · Physics 2024-11-11 Boyang Chen , Jue Xu , Qi Zhao , Xiao Yuan

In this paper we provide new quantum algorithms with polynomial speed-up for a range of problems for which no such results were known, or we improve previous algorithms. First, we consider the approximation of the frequency moments $F_k$ of…

Quantum Physics · Physics 2019-07-08 Yassine Hamoudi , Frédéric Magniez

The hopes for scalable quantum computing rely on the "threshold theorem": once the error per qubit per gate is below a certain value, the methods of quantum error correction allow indefinitely long quantum computations. The proof is based…

Quantum Physics · Physics 2014-01-17 M. I. Dyakonov

In the noisy intermediate-scale quantum (NISQ) era, the capabilities of variational quantum algorithms are greatly constrained due to a limited number of qubits and the shallow depth of quantum circuits. We may view these variational…

Quantum Physics · Physics 2024-11-05 Yabo Wang , Xin Wang , Bo Qi , Daoyi Dong

To overcome the limitations of classical partially connected Boltzmann machines and mainstream quantum Boltzmann machines (QBMs), this work extends the conventional circuit of the quantum approximate optimization algorithm (QAOA) to a…

Quantum Physics · Physics 2026-05-13 Jun Liu

We study quantum algorithms for approximating Lasserre's hierarchy values for polynomial optimization. Let $f,g_1,\ldots,g_m$ be real polynomials in $n$ variables and $f^\star$ the infimum of $f$ over the semialgebraic set $S(g)=\{x:…

Quantum Physics · Physics 2025-11-19 Daniel Stilck França , Ngoc Hoang Anh Mai

We design an efficient data structure for computing a suitably defined approximate depth of any query point in the arrangement $\mathcal{A}(S)$ of a collection $S$ of $n$ halfplanes or triangles in the plane or of halfspaces or simplices in…

Computational Geometry · Computer Science 2020-06-23 Dror Aiger , Haim Kaplan , Micha Sharir

In the era of noisy intermediate-scale quantum (NISQ) devices, the number of controllable hardware qubits is insufficient to implement quantum error correction (QEC). As an alternative, quantum error mitigation (QEM) can suppress errors in…

Quantum Physics · Physics 2022-11-02 Yuchen Guo , Shuo Yang

The quantum approximate optimization algorithm (QAOA) is one of the most prominent proposed applications for near-term quantum computing. Here we study the ability of QAOA to solve hard constraint satisfaction problems, as opposed to…

Quantum Physics · Physics 2022-08-16 Sami Boulebnane , Ashley Montanaro

Quantum linear system algorithms (QLSA) have the potential to speed up Interior Point Methods (IPM). However, a major challenge is that QLSAs are inexact and sensitive to the condition number of the coefficient matrices of linear systems.…

Optimization and Control · Mathematics 2023-10-12 Mohammadhossein Mohammadisiahroudi , Zeguan Wu , Brandon Augustino , Arriele Carr , Tamás Terlaky

Results are presented of a large-scale simulation of the quantum adiabatic search (QuAdS) algorithm in the presence of noise. The algorithm is applied to the NP-Complete problem Exact Cover 3 (EC3). The noise is assumed to Zeeman-couple to…

Quantum Physics · Physics 2007-05-23 Frank Gaitan

We show a power 2.5 separation between bounded-error randomized and quantum query complexity for a total Boolean function, refuting the widely believed conjecture that the best such separation could only be quadratic (from Grover's…

Quantum Physics · Physics 2019-07-10 Scott Aaronson , Shalev Ben-David , Robin Kothari

We consider approximation of diameter of a set $S$ of $n$ points in dimension $m$. E$\tilde{g}$ecio$\tilde{g}$lu and Kalantari \cite{kal} have shown that given any $p \in S$, by computing its farthest in $S$, say $q$, and in turn the…

Computational Geometry · Computer Science 2014-10-09 Sharareh Alipour , Bahman Kalantari , Hamid Homapour

Probabilistic metrology attempts to improve parameter estimation by occasionally reporting an excellent estimate and the rest of the time either guessing or doing nothing at all. Here we show that probabilistic metrology can never improve…

Quantum Physics · Physics 2014-05-21 Joshua Combes , Christopher Ferrie , Zhang Jiang , Carlton M. Caves

In this paper we present a new error bound on sampling algorithms for frequent itemsets mining. We show that the new bound is asymptotically tighter than the state-of-art bounds, i.e., given the chosen samples, for small enough error…

Data Structures and Algorithms · Computer Science 2017-03-27 Shiyu Ji , Kun Wan

We study the problem of designing minimax procedures in linear regression under the quantile risk. We start by considering the realizable setting with independent Gaussian noise, where for any given noise level and distribution of inputs,…

Statistics Theory · Mathematics 2024-06-19 Ayoub El Hanchi , Chris J. Maddison , Murat A. Erdogdu

Experimental characterizations of a quantum system involve the measurement of expectation values of observables for a preparable state |psi> of the quantum system. Such expectation values can be measured by repeatedly preparing |psi> and…

Quantum Physics · Physics 2009-11-13 Emanuel Knill , Gerardo Ortiz , Rolando D. Somma

Statistical query (SQ) algorithms are algorithms that have access to an {\em SQ oracle} for the input distribution $D$ instead of i.i.d.~ samples from $D$. Given a query function $\phi:X \rightarrow [-1,1]$, the oracle returns an estimate…

Machine Learning · Computer Science 2017-04-18 Vitaly Feldman

We analyse the forward error in the floating point summation of real numbers, from algorithms that do not require recourse to higher precision or better hardware. We derive informative explicit expressions, and new deterministic and…

Numerical Analysis · Mathematics 2021-07-06 Eric Hallman , Ilse C. F. Ipsen