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Related papers: Efficient quantum algorithms for $GHZ$ and $W$ sta…

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Quantum compiling means fast, device-aware implementation of quantum algorithms (i.e., quantum circuits, in the quantum circuit model of computation). In this paper, we present a strategy for compiling IBM Q -aware, low-depth quantum…

Quantum Physics · Physics 2020-03-13 Davide Ferrari , Michele Amoretti

A common requirement of quantum simulations and algorithms is the preparation of complex states through sequences of 2-qubit gates. For a generic quantum state, the number of gates grows exponentially with the number of qubits, becoming…

Quantum Physics · Physics 2024-07-08 Matan Ben Dov , David Shnaiderov , Adi Makmal , Emanuele G. Dalla Torre

Graph states are an important class of multipartite entangled states. Previous experimental generation of graph states and in particular the Greenberger-Horne-Zeilinger (GHZ) states in linear optics quantum information schemes is subjected…

Quantum Physics · Physics 2022-03-01 Sheng Zhang , Yu-Kai Wu , Chang Li , Nan Jiang , Yun-Fei Pu , Lu-Ming Duan

The generation of a large amount of entanglement is a necessary condition for a quantum computer to achieve quantum advantage. In this paper, we propose a method to efficiently generate pseudo-random quantum states, for which the degree of…

Quantum Physics · Physics 2023-04-05 Gabriele Cenedese , Maria Bondani , Dario Rosa , Giuliano Benenti

$W$ states are quantum correlated states possessing both bipartite and multipartite entanglement, which makes them useful for several quantum algorithms. We propose a protocol to generate these states by exploiting {\it topological ring…

Quantum state tomography (QST) is plagued by the ``curse of dimensionality'' due to the exponentially-scaled complexity in measurement and data post-processing. Efficient QST schemes for large-scale mixed states are currently missing. In…

Quantum Physics · Physics 2023-08-15 Wen-jun Li , Kai Xu , Heng Fan , Shi-ju Ran , Gang Su

Effective quantum computation relies upon making good use of the exponential information capacity of a quantum machine. A large barrier to designing quantum algorithms for execution on real quantum machines is that, in general, it is…

Quantum Physics · Physics 2020-05-12 Adam Holmes , A. Y. Matsuura

Schemes to generate Greenberger-Horne-Zeilinger(GHZ) and W states of three distant atoms are proposed in this paper. The schemes use the effects of quantum statistics of indistinguishable photons emitted by the atoms inside optical…

Quantum Physics · Physics 2009-11-13 Chang-shui Yu , X. X. Yi , He-shan Song , D. Mei

Gate model quantum computers promise to solve currently intractable computational problems if they can be operated at scale with long coherence times and high fidelity logic. Neutral atom hyperfine qubits provide inherent scalability due to…

Image-based data is a popular arena for testing quantum machine learning algorithms. A crucial factor in realizing quantum advantage for these applications is the ability to efficiently represent images as quantum states. Here we present a…

Quantum Physics · Physics 2023-10-10 Jason Iaconis , Sonika Johri

Highly entangled quantum states are an ingredient in numerous applications in quantum computing. However, preparing these highly entangled quantum states on currently available quantum computers at high fidelity is limited by ubiquitous…

Quantum Physics · Physics 2025-02-27 Sebastian Brandhofer , Ilia Polian , Stefanie Barz , Daniel Bhatti

While quantum computers are capable of simulating many quantum systems efficiently, the simulation algorithms must begin with the preparation of an appropriate initial state. We present a method for generating physically relevant quantum…

Quantum Physics · Physics 2009-05-29 Nicholas J. Ward , Ivan Kassal , Alán Aspuru-Guzik

A prerequisite to the successful development of quantum computers and simulators is precise understanding of physical processes occurring therein, which can be achieved by measuring the quantum states they produce. However, the resources…

We propose an efficient quantum state tomography method inspired by compressed sensing and threshold quantum state tomography that can drastically reduce the number of measurement settings to reconstruct the density matrix of an $N$-qudit…

Quantum Physics · Physics 2025-04-01 Giovanni Garberoglio , Maurizio Dapor , Diego Maragnano , Marco Liscidini , Daniele Binosi

As quantum technology advances and the size of quantum computers grow, it becomes increasingly important to understand the extent of quality in the devices. As large-scale entanglement is a quantum resource crucial for achieving quantum…

Quantum Physics · Physics 2024-10-07 John F Kam , Haiyue Kang , Charles D Hill , Gary J Mooney , Lloyd C L Hollenberg

Considering recent advancements and successes in the development of efficient quantum algorithms for electronic structure calculations --- alongside impressive results using machine learning techniques for computation --- hybridizing…

Quantum Physics · Physics 2018-10-24 Rongxin Xia , Sabre Kais

The experimental realization of increasingly complex quantum states underscores the pressing need for new methods of state learning and verification. In one such framework, quantum state tomography, the aim is to learn the full quantum…

Quantum Physics · Physics 2025-01-30 Antonio Anna Mele , Yaroslav Herasymenko

Quantum computing promises to provide exponential speed-ups to certain classes of problems. In many such algorithms, a classical vector $\mathbf{b}$ is encoded in the amplitudes of a quantum state $\left |b \right >$. However, efficiently…

Quantum Physics · Physics 2022-08-10 Prithvi Gundlapalli , Junyi Lee

We experimentally explore the state space of three qubits on an NMR quantum information processor. We construct a scheme to experimentally realize a canonical form for general three-qubit states up to single-qubit unitaries. This form…

Quantum Physics · Physics 2018-02-12 Shruti Dogra , Kavita Dorai , Arvind

We describe a quantum algorithm for preparing states that encode solutions of non-homogeneous linear partial differential equations. The algorithm is a continuous-variable version of matrix inversion: it efficiently inverts differential…

Quantum Physics · Physics 2019-09-11 Juan Miguel Arrazola , Timjan Kalajdzievski , Christian Weedbrook , Seth Lloyd
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