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We propose a generalization of the graphical ZH calculus to qudits of prime-power dimensions $q = p^t$, implementing field arithmetic in arbitrary finite fields. This is an extension of a previous result by Roy which implemented arithmetic…

Quantum Physics · Physics 2026-01-15 Dichuan Gao

Quantum Tiq-Taq-Toe is a well-known benchmark and playground for both quantum computing and machine learning. Despite its popularity, no reinforcement learning (RL) methods have been applied to Quantum Tiq-Taq-Toe. Although there has been…

Artificial Intelligence · Computer Science 2024-11-12 Catalin-Viorel Dinu , Thomas Moerland

It is imperative that useful quantum computers be very difficult to simulate classically; otherwise classical computers could be used for the applications envisioned for the quantum ones. Perfect quantum computers are unarguably…

Quantum Physics · Physics 2020-11-26 Yiqing Zhou , E. Miles Stoudenmire , Xavier Waintal

Recent advances in deep reinforcement learning (RL) have demonstrated its potential to learn complex robotic manipulation tasks. However, RL still requires the robot to collect a large amount of real-world experience. To address this…

Robotics · Computer Science 2020-03-12 Bohan Wu , Feng Xu , Zhanpeng He , Abhi Gupta , Peter K. Allen

This paper positively solves the quantum subroutine problem for fully quantum oracles. The quantum subroutine problem asks whether a quantum computer with an efficiently computable oracle can be efficiently simulated by a non-oracle quantum…

Quantum Physics · Physics 2007-05-23 Harumichi Nishimura , Masanao Ozawa

We give examples of curves of arbitrarily high Clifford index such that the Prym map is not injective at any of their \'etale double covers.

Algebraic Geometry · Mathematics 2010-01-21 E. Izadi , H. Lange

To efficiently implement many-particle quantum simulations on quantum computers we develop and present methods for inverting the Campbell-Baker-Hausdorff lemma to 3rd and 4th order in the commutator. That is, we reexpress exp{-i(H_1 + H_2 +…

Quantum Physics · Physics 2007-05-23 A. T. Sornborger , E. D. Stewart

We unconditionally prove that it is NP-hard to compute a constant multiplicative approximation to the QUANTUM MAX-CUT problem on an unweighted graph of constant bounded degree. The proof works in two stages: first we demonstrate a generic…

Quantum Physics · Physics 2025-10-10 Stephen Piddock

The $q$-calculus is reformulated in terms of the umbral calculus and of the associated operational formalism. We show that new and interesting elements emerge from such a restyling. The proposed technique is applied to a different…

Classical Analysis and ODEs · Mathematics 2019-09-04 G. Dattoli , B. Germano , K. Górska , M. R. Martinelli

In [5] Soare and Stob prove that if $A$ is an r.e. set which isn't computable then there is a set of the form $A \oplus W^A_e$ which isn't of r.e. Turing degree. If we define a properly $n+1$-REA set to be an $n+1$-REA set which isn't…

Logic · Mathematics 2022-12-20 Peter A. Cholak , Peter M. Gerdes

Under conditions that prevent tangential intersection, we prove quadratic convergence of a projection algorithm for the feasibility problem of finding a point in the intersection of a smooth curve and line in $\mathbb{R}^2$. This nonconvex…

Optimization and Control · Mathematics 2025-10-22 Jordan Collard , Scott B. Lindstrom

In this paper, we address Linear Quadratic Regulator (LQR) problems through a novel iterative algorithm named EXtremum-seeking Policy iteration LQR (EXP-LQR). The peculiarity of EXP-LQR is that it only needs access to a truncated…

Optimization and Control · Mathematics 2025-06-13 Guido Carnevale , Nicola Mimmo , Giuseppe Notarstefano

After the release of the PLANCK data, it is evident that inflationary paradigm has stood the test of time. Even though, it is difficult to realise inflationary paradigm in a particle physics model as the present observations have ruled out…

Cosmology and Nongalactic Astrophysics · Physics 2017-12-29 Suratna Das , Girish Kumar Chakravarty , Gaetano Lambiase , Subhendra Mohanty

Given a coin with unknown bias $p\in [0,1]$, can we exactly simulate another coin with bias $f(p)$? The exact set of simulable functions has been well characterized 20 years ago. In this paper, we ask the quantum counterpart of this…

Quantum Physics · Physics 2018-03-13 Jiaqing Jiang , Jialin Zhang , Xiaoming Sun

The set of pure terms which are typable in the $\lambda$$\Pi$-calculus in a given context is not recursive. So there is no general type inference algorithm for the programming language Elf and, in some cases, some type information has to be…

Logic in Computer Science · Computer Science 2023-06-14 Gilles Dowek

RECAST is an analysis reinterpretation framework; since analyses are often sensitive to a range of models, RECAST can be used to constrain the plethora of theoretical models without the significant investment required for a new analysis.…

Data Analysis, Statistics and Probability · Physics 2019-10-24 Alex Schuy , Lukas Heinrich , Kyle Cranmer , Shih-Chieh Hsu

We show that the effective factorization of Ore polynomials over $\mathbb{F}_q(t)$ is still an open problem. This is so because the known algorithm in [1] presents two gaps, and therefore it does not cover all the examples. We amend one of…

Rings and Algebras · Mathematics 2015-05-28 Jose Gomez-Torrecillas , F. J. Lobillo , Gabriel Navarro

We show in this Comment that the interpretation of experimental data as well as the theory presented in Atat\"ure et al. [Phys. Rev. Lett. 84, 618 (2000)] are incorrect and discuss why such a scheme cannot be used to "recover"…

Quantum Physics · Physics 2009-11-06 Yoon-Ho Kim , Sergei P. Kulik , Morton H. Rubin , Yanhua Shih

We develop an accurate square-root-free algorithm for constructing real Givens rotations. On processors that support the fused multiply-add operation in hardware, the algorithm is competitive with square-root based algorithms using a…

Numerical Analysis · Mathematics 2025-08-28 Carlos F. Borges

Multi-task Inverse Reinforcement Learning (IRL) is the problem of inferring multiple reward functions from expert demonstrations. Prior work, built on Bayesian IRL, is unable to scale to complex environments due to computational…

Machine Learning · Computer Science 2018-07-17 Adam Gleave , Oliver Habryka