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The design of new quantum algorithms has proven to be an extremely difficult task. This paper considers a different approach to the problem, by studying the problem of 'quantum state generation'. This approach provides intriguing links…

Quantum Physics · Physics 2007-05-23 Dorit Aharonov , Amnon Ta-Shma

Many physical phenomena, including thermalization in open quantum systems and quantum Gibbs sampling, are modeled by Lindbladians approximating a system weakly coupled to a bath. Understanding the convergence speed of these Lindbladians to…

Efficient simulation of a quantum system generally relies on structural properties of the quantum state. Motivated by the recent results by Bakshi et al. on the sudden death of entanglement in high-temperature Gibbs states of quantum spin…

Quantum Physics · Physics 2026-01-21 Akshar Ramkumar , Yiyi Cai , Yu Tong , Jiaqing Jiang

Adiabatic quantum computation is a paradigmatic model aiming to solve a computational problem by finding the many-body ground state encapsulating the solution. However, its use of an adiabatic evolution depending on the spectral gap of an…

Quantum Physics · Physics 2024-06-13 Jaeyoon Cho

Understanding the entanglement structure of local Hamiltonian ground spaces is a physically motivated problem, with applications ranging from tensor network design to quantum error-correcting codes. To this end, we study the complexity of…

Quantum Physics · Physics 2026-05-29 Sevag Gharibian , Jonas Kamminga

Low-energy estimation and state preparation for general $k$-local Hamiltonians are fundamental challenges in quantum complexity theory. For constant relative accuracy, Buhrman et al. (PRL 2025) recently broke the natural Grover bound…

Quantum Physics · Physics 2026-05-19 Ranitha Mataraarachchi , François Le Gall , Suguru Tamaki

Gibbs sampling is fundamental to a wide range of computer algorithms. Such algorithms are set to be replaced by physics based processors$-$be it quantum or stochastic annealing devices$-$which embed problem instances and evolve a physical…

Quantum Physics · Physics 2019-06-27 H. Philathong , V. Akshay , I. Zacharov , J. Biamonte

It is known from Bell's theorem that quantum predictions for some entangled states cannot be mimicked using local hidden variable (LHV) models. From a computer science perspective, LHV models may be interpreted as classical computers…

Quantum Physics · Physics 2014-10-08 T. K. Chuan , T. Paterek

We present two quantum algorithms based on evolution randomization, a simple variant of adiabatic quantum computing, to prepare a quantum state $\vert x \rangle$ that is proportional to the solution of the system of linear equations $A…

Quantum Physics · Physics 2019-02-20 Yigit Subasi , Rolando D. Somma , Davide Orsucci

The preparation of non-trivial states is crucial to the study of quantum many-body physics. Such states can be prepared with adiabatic quantum algorithms, which are restricted by the minimum spectral gap along the path. In this letter, we…

Quantum Physics · Physics 2025-10-03 Kshiti Sneh Rai , Jin-Fu Chen , Patrick Emonts , Jordi Tura

In continuous-variable quantum computing, autonomous quantum error correction (QEC) can dissipatively steer a noisy quantum state into a target state or manifold, enabling robust quantum information processing without explicit syndrome…

Quantum Physics · Physics 2026-03-24 Keitaro Anai , Suguru Endo , Shuntaro Takeda , Tomohiro Shitara

We propose a linear optical quantum computation scheme using time-frequency degree of freedom. In this scheme, a qubit is encoded in single-photon frequency combs, and manipulation of the qubits is performed using time-resolving detectors,…

Quantum Physics · Physics 2023-06-13 Tomohiro Yamazaki , Tomoaki Arizono , Toshiki Kobayashi , Rikizo Ikuta , Takashi Yamamoto

We study the complexity of learning quantum states in various models with respect to the stabilizer formalism and obtain the following results: - We prove that $\Omega(n)$ $T$-gates are necessary for any Clifford+$T$ circuit to prepare…

Quantum Physics · Physics 2025-09-18 Sabee Grewal , Vishnu Iyer , William Kretschmer , Daniel Liang

Quantum state preparation is an important class of quantum algorithms that is employed as a black-box subroutine in many algorithms, or used by itself to generate arbitrary probability distributions. We present a novel state preparation…

Quantum Physics · Physics 2020-06-02 Yutaro Iiyama

For any local Hamiltonian H, I construct a local CPT map and stopping condition which converges to the ground state subspace of H. Like any ground state preparation algorithm, this algorithm necessarily has exponential run-time in general…

Quantum Physics · Physics 2023-09-25 Toby S. Cubitt

Calculating the properties of Gibbs states is an important task in Quantum Chemistry and Quantum Machine Learning. Previous work has proposed a quantum algorithm which predicts Gibbs state expectation values for $M$ observables from only…

Quantum Physics · Physics 2024-09-10 Arnav Sharma , Kevin Obenland

Models of quantum computation are important because they change the physical requirements for achieving universal quantum computation (QC). For example, one-way QC requires the preparation of an entangled "cluster" state followed by…

Quantum Physics · Physics 2010-09-28 Dave Bacon , Steven T. Flammia

This thesis investigates quantum algorithms for eigenstate preparation, with a focus on solving eigenvalue problems such as the Schrodinger equation by utilizing near-term quantum computing devices. These problems are ubiquitous in several…

Quantum Physics · Physics 2024-12-20 Joey Bonitati

Production of quantum states exhibiting a high degree of entanglement out of noisy conditions is one of the main goals of quantum information science. Here, we provide a conditional yet efficient entanglement distillation method which…

We prove a priori estimates and, as sequel, existence of Euclidean Gibbs states for quantum lattice systems. For this purpose we develop a new analytical approach, the main tools of which are: first, a characterization of the Gibbs states…

Probability · Mathematics 2007-05-23 Sergio Albeverio , Yuri G. Kondratiev , Tatiana Pasurek , Michael Röckner