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Related papers: Pseudorandom density matrices

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We show that quantum states with "low stabilizer complexity" can be efficiently distinguished from Haar-random. Specifically, given an $n$-qubit pure state $|\psi\rangle$, we give an efficient algorithm that distinguishes whether…

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

The pseudo-random number generators (PRNGs), sampling algorithms, and algorithms for generating random integers in some common statistical packages and programming languages are unnecessarily inaccurate, by an amount that may matter for…

Computation · Statistics 2018-10-29 Philip B. Stark , Kellie Ottoboni

Entanglement is a quantum resource, in some ways analogous to randomness in classical computation. Inspired by recent work of Gheorghiu and Hoban, we define the notion of "pseudoentanglement'', a property exhibited by ensembles of…

Predictive recursion (PR) is a fast algorithm for nonparametric estimation of a mixing density, with connections to sequential Bayesian updating under a Dirichlet process prior and rigorous frequentist consistency guarantees. Extending PR…

Methodology · Statistics 2026-05-05 Jonathan Lin , Surya Tokdar

Pseudo-hermitian matrices are matrices hermitian with respect to an indefinite metric. They can be thought of as the truncation of pseudo-hermitian operators, defined over some Krein space, together with the associated metric, to a finite…

Mathematical Physics · Physics 2022-02-03 Joshua Feinberg , Roman Riser

We show that measuring any two quantum states by a random POVM, under a suitable definition of randomness, gives probability distributions having total variation distance at least a universal constant times the Frobenius distance between…

Quantum Physics · Physics 2007-05-23 Pranab Sen

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

Reduced density matrices (RDMs) are fundamental in quantum information processing, allowing the computation of local observables, such as energy and correlation functions, without the exponential complexity of fully characterizing quantum…

Quantum Physics · Physics 2025-06-13 Zherui Jerry Wang , David Dechant , Yash J. Patel , Jordi Tura

We revise the problem first addressed by Braunstein and co-workers (Phys. Rev. Lett. {\bf 83} (5) (1999) 1054) concerning the separability of very noisy mixed states represented by general density matrices with the form $\rho_\epsilon =…

Pseudorandom unitaries (PRUs) are ensembles of efficiently implementable unitary operators that cannot be distinguished from Haar random unitaries by any quantum polynomial-time algorithm with query access to the unitary. We present a…

Quantum Physics · Physics 2024-02-23 Tony Metger , Alexander Poremba , Makrand Sinha , Henry Yuen

A Pseudo-Random Number Generator (PRNG) is any algorithm generating a sequence of numbers approximating properties of random numbers. These numbers are widely employed in mid-level cryptography and in software applications. Test suites are…

Cryptography and Security · Computer Science 2020-11-20 Luca Pasqualini , Maurizio Parton

While most power system small-signal stability assessments rely on the reduced Jacobian, which depends non-linearly on the states, uncertain operating points introduce nontrivial hurdles in certifying the system's stability. In this paper,…

Systems and Control · Electrical Eng. & Systems 2019-10-04 Parikshit Pareek , Hung D. Nguyen

Introduced in [CG24], pseudorandom error-correcting codes (PRCs) are a new cryptographic primitive with applications in watermarking generative AI models. These are codes where a collection of polynomially many codewords is computationally…

Cryptography and Security · Computer Science 2025-07-14 Surendra Ghentiyala , Venkatesan Guruswami

We consider the relation between three different approaches to defining quantum states across several times and locations: the pseudo-density matrix (PDM), the process matrix, and the multiple-time state approaches. Previous studies have…

Quantum Physics · Physics 2024-03-14 Xiangjing Liu , Zhian Jia , Yixian Qiu , Fei Li , Oscar Dahlsten

This paper introduces a novel approach to probabilistic deep learning, kernel density matrices, which provide a simpler yet effective mechanism for representing joint probability distributions of both continuous and discrete random…

Machine Learning · Computer Science 2024-05-01 Fabio A. González , Raúl Ramos-Pollán , Joseph A. Gallego-Mejia

Pseudorandom unitaries (PRUs), one of the key quantum pseudorandom notions, are efficiently computable unitaries that are computationally indistinguishable from Haar random unitaries. While there is evidence to believe that PRUs are weaker…

Quantum Physics · Physics 2025-09-30 Prabhanjan Ananth , Aditya Gulati , Yao-Ting Lin

Quantum Key Distribution(QKD) thrives to achieve perfect secrecy of One time Pad (OTP) through quantum processes. One of the crucial components of QKD are Quantum Random Number Generators(QRNG) for generation of keys. Unfortunately, these…

Cryptography and Security · Computer Science 2023-11-07 Arun Mishra , Kanaka Raju Pandiri , Anupama Arjun Pandit , Lucy Sharma

We show it is possible to obtain quantum pseudorandomness and pseudoentanglement from random subset states -- i.e. quantum states which are equal superpositions over (pseudo)random subsets of strings. This answers an open question of…

Quantum Physics · Physics 2023-12-15 Tudor Giurgica-Tiron , Adam Bouland

We present a new approach to constructing of pseudo-random binary sequences (PRS) generators for the purpose of cryptographic data protection, secured from the perpetrator's attacks, caused by generation of masses of hardware errors and…

Cryptography and Security · Computer Science 2018-09-10 Oleg Finko , Sergey Dichenko

This paper presents the Poisson-randomized gamma dynamical system (PRGDS), a model for sequentially observed count tensors that encodes a strong inductive bias toward sparsity and burstiness. The PRGDS is based on a new motif in Bayesian…

Machine Learning · Statistics 2019-10-30 Aaron Schein , Scott W. Linderman , Mingyuan Zhou , David M. Blei , Hanna Wallach