English
Related papers

Related papers: Efficient simulation of random states and random u…

200 papers

Simulating physical systems on near-term quantum computers often requires preparing states within constrained subspaces, like those with fixed particle number or spin. We use Lie algebraic techniques to prove that hardware-efficient gates…

Quantum Physics · Physics 2026-05-05 Andreas Stergiou , Nicolas PD Sawaya

Recent active studies have demonstrated that cryptography without one-way functions (OWFs) could be possible in the quantum world. Many fundamental primitives that are natural quantum analogs of OWFs or pseudorandom generators (PRGs) have…

Quantum Physics · Physics 2024-11-06 Minki Hhan , Shogo Yamada

We present a quantum algorithm for combinatorial optimization using the cost structure of the search states. Its behavior is illustrated for overconstrained satisfiability and asymmetric traveling salesman problems. Simulations with…

Quantum Physics · Physics 2007-05-23 Tad Hogg , Dmitriy Portnov

We investigate how to determine whether the states of a set of quantum systems are identical or not. This paper treats both error-free comparison, and comparison where errors in the result are allowed. Error-free comparison means that we…

Quantum Physics · Physics 2015-06-26 Igor Jex , Erika Andersson , Anthony Chefles

From the minimal assumption of post-quantum semi-honest oblivious transfers, we build the first $\epsilon$-simulatable two-party computation (2PC) against quantum polynomial-time (QPT) adversaries that is both constant-round and black-box…

Cryptography and Security · Computer Science 2023-11-07 Nai-Hui Chia , Kai-Min Chung , Xiao Liang , Takashi Yamakawa

With a combination of the quantum repeater and the cluster state approaches, we show that efficient quantum computation can be constructed even if all the entangling quantum gates only succeed with an arbitrarily small probability $p$. The…

Quantum Physics · Physics 2009-11-11 L. -M. Duan , R. Raussendorf

We analyze the complexity of synthesizing random states and unitary operators in a multi-qudit system in two paradigms. In one case, we consider the situation in which we manipulate the system by applying a sequence of one- and two-qudit…

Quantum Physics · Physics 2026-05-11 Sahel Ashhab , Bora Basyildiz

The interplay between quantum physics and machine learning gives rise to the emergent frontier of quantum machine learning, where advanced quantum learning models may outperform their classical counterparts in solving certain challenging…

Quantum Physics · Physics 2022-12-07 Weiyuan Gong , Dong Yuan , Weikang Li , Dong-Ling Deng

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

We study first-order algorithms that are uniformly stable for empirical risk minimization (ERM) problems that are convex and smooth with respect to $p$-norms, $p \geq 1$. We propose a black-box reduction method that, by employing properties…

Machine Learning · Computer Science 2024-12-23 Simon Vary , David Martínez-Rubio , Patrick Rebeschini

Common random string model is a popular model in classical cryptography with many constructions proposed in this model. We study a quantum analogue of this model called the common Haar state model, which was also studied in an independent…

Quantum Physics · Physics 2024-04-11 Prabhanjan Ananth , Aditya Gulati , Yao-Ting Lin

Product formulas can be used to simulate Hamiltonian dynamics on a quantum computer by approximating the exponential of a sum of operators by a product of exponentials of the individual summands. This approach is both straightforward and…

Quantum Physics · Physics 2019-09-04 Andrew M. Childs , Aaron Ostrander , Yuan Su

The outcomes of quantum mechanical experiments are inherently random. It is therefore necessary to develop stringent methods for quantifying the degree of statistical uncertainty about the results of quantum experiments. For the…

Quantum Physics · Physics 2017-10-11 Daniel Suess , Łukasz Rudnicki , Thiago O. Maciel , David Gross

The complete learning of an $n$-qubit quantum state requires samples exponentially in $n$. Several works consider subclasses of quantum states that can be learned in polynomial sample complexity such as stabilizer states or high-temperature…

Quantum Physics · Physics 2023-09-19 Liming Zhao , Naixu Guo , Ming-Xing Luo , Patrick Rebentrost

This thesis presents an efficient quantum algorithm and explicit circuits for generating eigenstates of arbitrary SU(2) and SU(3) representations. These include a wide variety of highly entangled states. The algorithm uses Schur transform…

Quantum Physics · Physics 2013-09-12 Satya Sainadh U

State-space models (SSMs) are a highly expressive model class for learning patterns in time series data and for system identification. Deterministic versions of SSMs (e.g. LSTMs) proved extremely successful in modeling complex time series…

Black-box separations are a cornerstone of cryptography, indicating barriers to various goals. A recent line of work has explored black-box separations for quantum cryptographic primitives. Namely, a number of separations are known in the…

Quantum Physics · Physics 2025-07-25 Eli Goldin , Mark Zhandry

One of the key ingredients of many LOCC protocols in quantum information is a multiparticle (locally) maximally entangled quantum state, aka a critical state, that possesses local symmetries. We show how to design critical states with…

Quantum Physics · Physics 2021-05-04 Oskar Słowik , Adam Sawicki , Tomasz Maciążek

Simulating quantum algorithms with classical resources generally requires exponential resources. However, heuristic classical approaches are often very efficient in approximately simulating special circuit structures, for example with…

Quantum Physics · Physics 2018-08-17 Bjarni Jónsson , Bela Bauer , Giuseppe Carleo

Motivated by the prevailing paradigm of using unsupervised learning for efficient exploration in reinforcement learning (RL) problems [tang2017exploration,bellemare2016unifying], we investigate when this paradigm is provably efficient. We…

Machine Learning · Computer Science 2020-12-02 Fei Feng , Ruosong Wang , Wotao Yin , Simon S. Du , Lin F. Yang