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Quantum computing is an emerging field of science which will eventually lead us to new and powerful logic devices with capabilities far beyond the limits of current transistor-based technology. There are certain types of problems which…

Quantum annealing is a generic algorithm using quantum-mechanical fluctuations to search for the solution of an optimization problem. The present paper first reviews the fundamentals of quantum annealing and then reports on preliminary…

Disordered Systems and Neural Networks · Physics 2010-06-10 Masayuki Ohzeki , Hidetoshi Nishimori

Quantum algorithms could efficiently solve certain classically intractable problems by exploiting quantum parallelism. To date, whether the quantum entanglement is useful or not for quantum computing is still a question of debate. Here, we…

Quantum Physics · Physics 2018-01-24 He-Liang Huang , Ashutosh K. Goswami , Wan-Su Bao , Prasanta K. Panigrahi

The new model of quantum computation is proposed, for which an effective algorithm of solving any task in NP is described. The work is based and inspired be the Grover's algorithm for solving NP-tasks with quadratic speedup compared to the…

Computational Complexity · Computer Science 2014-12-10 Sergey Sysoev

Quantum computing promises transformational gains for solving some problems, but little to none for others. For anyone hoping to use quantum computers now or in the future, it is important to know which problems will benefit. In this paper,…

Data Structures and Algorithms · Computer Science 2023-10-25 Sukwoong Choi , William S. Moses , Neil Thompson

Quantum computing holds great promise to solve to problems where classical computers cannot reach. To the point where it already arouses the interest of both scientific and industrial communities. Thus, it is expected that hybrid systems…

Software Engineering · Computer Science 2025-02-03 Javier Rojo , David Valencia , Javier Berrocal , Enrique Moguel , Jose Garcia-Alonso , Juan Manuel Murillo Rodriguez

Quantum annealers aim at solving non-convex optimization problems by exploiting cooperative tunneling effects to escape local minima. The underlying idea consists in designing a classical energy function whose ground states are the sought…

Quantum Physics · Physics 2018-09-12 Carlo Baldassi , Riccardo Zecchina

Quantum computers are known to provide an exponential advantage over classical computers for the solution of linear differential equations in high-dimensional spaces. Here, we present a quantum algorithm for the solution of nonlinear…

Quantum algorithms for Hamiltonian simulation and linear differential equations more generally have provided promising exponential speed-ups over classical computers on a set of problems with high real-world interest. However, extending…

Quantum Physics · Physics 2025-05-14 Noah Brüstle , Nathan Wiebe

A quantum algorithm succeeds not because the superposition principle allows 'the computation of all values of a function at once' via 'quantum parallelism,' but rather because the structure of a quantum state space allows new sorts of…

Quantum Physics · Physics 2010-05-17 Jeffrey Bub

Quantum algorithms for several problems in graph theory are considered. Classical algorithms for finding the lowest weight path between two points in a graph and for finding a minimal weight spanning tree involve searching over some space.…

Quantum Physics · Physics 2007-05-23 Mark Heiligman

Combining quantum computers with classical compute power has become a standard means for developing algorithms that are eventually supposed to beat any purely classical alternatives. While in-principle advantages for solution quality or…

Quantum Physics · Physics 2026-01-23 Simon Thelen , Wolfgang Mauerer

We consider a version of Shor's quantum factoring algorithm such that the quantum Fourier transform is replaced by an extremely simple one where decomposition coefficients take only the values of $1,i,-1,-i$. In numerous calculations which…

Quantum Physics · Physics 2007-05-23 Felix M Lev

We demonstrate that locally connected networks of machines that have primitive learning capabilities can be used to perform a deterministic, event-based simulation of quantum computation. We present simulation results for basic quantum…

Quantum Physics · Physics 2007-05-23 K. Michielsen , K. De Raedt , H. De Raedt

Algorithmic approach is based on the assumption that any quantum evolution of many particle system can be simulated on a classical computer with the polynomial time and memory cost. Algorithms play the central role here but not the…

Quantum Physics · Physics 2007-05-23 Yuri Ozhigov

Shor and Grover demonstrated that a quantum computer can outperform any classical computer in factoring numbers and in searching a database by exploiting the parallelism of quantum mechanics. Whereas Shor's algorithm requires both…

Mesoscale and Nanoscale Physics · Physics 2016-08-31 Michael N. Leuenberger , Daniel Loss

Quantum tunneling, a phenomenon in which a quantum state traverses energy barriers above the energy of the state itself, has been hypothesized as an advantageous physical resource for optimization. Here we show that multiqubit tunneling…

Problem instances of a size suitable for practical applications are not likely to be addressed during the noisy intermediate-scale quantum (NISQ) period with (almost) pure quantum algorithms. Hybrid classical-quantum algorithms have…

Quantum Physics · Physics 2022-12-05 Randall Correll , Sean J. Weinberg , Fabio Sanches , Takanori Ide , Takafumi Suzuki

Is the universe computable? If yes, is it computationally a polynomial place? In standard quantum mechanics, which permits infinite parallelism and the infinitely precise specification of states, a negative answer to both questions is not…

Quantum Physics · Physics 2009-11-13 R. Srikanth

Simulating quantum circuits using classical computers lets us analyse the inner workings of quantum algorithms. The most complete type of simulation, strong simulation, is believed to be generally inefficient. Nevertheless, several…

Quantum Physics · Physics 2013-02-25 T. H. Johnson , J. D. Biamonte , S. R. Clark , D. Jaksch
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