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We provide an analysis of a new family of device independent quantum key distribution (QKD) protocols with several novel features: (a) The bits used for the secret key do not come from the results of the measurements on an entangled state…

Quantum Physics · Physics 2015-12-09 Ramij Rahaman , Matthew G. Parker , Piotr Mironowicz , Marcin Pawłowski

Robust quantum computation requires encoding delicate quantum information into degrees of freedom that are hard for the environment to change. Quantum encodings have been demonstrated in many physical systems by observing and correcting…

Quantum Physics · Physics 2017-11-08 Maika Takita , Andrew W. Cross , A. D. Córcoles , Jerry M. Chow , Jay M. Gambetta

We develop the theory of cryptographic nondeterministic-secure pseudorandomness beyond the point reached by Rudich's original work (Rudich 1997), and apply it to draw new consequences in average-case complexity and proof complexity.…

Computational Complexity · Computer Science 2025-01-14 Iddo Tzameret , Lu-Ming Zhang

Bayesian inference is a widely used technique for real-time characterization of quantum systems. It excels in experimental characterization in the low data regime, and when the measurements have degrees of freedom. A decisive factor for its…

Quantum Physics · Physics 2025-07-10 Alexandra Ramôa , Raffaele Santagati , Nathan Wiebe

Quantum secret sharing (QSS) enables a dealer to securely distribute keys to multiple players. Device-independent (DI) QSS can resist all possible attacks from practical imperfect devices and provide QSS the highest level of security in…

Programmable quantum annealers are used as open-system samplers, but it is unclear when reverse annealing erases preparation memory and what the readout represents. Here we implement a subsystem-environment protocol on two D-Wave quantum…

Quantum Physics · Physics 2026-05-20 Luis Lozano

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

Goldreich suggested candidates of one-way functions and pseudorandom generators included in $\mathsf{NC}^0$. It is known that randomly generated Goldreich's generator using $(r-1)$-wise independent predicates with $n$ input variables and…

Cryptography and Security · Computer Science 2014-06-03 Ryuhei Mori , Takeshi Koshiba , Osamu Watanabe , Masaki Yamamoto

Is it possible to convert classical cryptographic reductions into post-quantum ones? It is customary to argue that while this is problematic in the interactive setting, non-interactive reductions do carry over. However, when considering…

Quantum Physics · Physics 2022-03-07 Nir Bitansky , Zvika Brakerski , Yael Tauman Kalai

The generation of random numbers via quantum processes is an efficient and reliable method to obtain true indeterministic random numbers that are of vital importance to cryptographic communication and large-scale computer modeling. However,…

Quantum Physics · Physics 2015-05-20 J. Y. Haw , S. M. Assad , A. M. Lance , N. H. Y. Ng , V. Sharma , P. K. Lam , T. Symul

Computational entropies provide a framework for quantifying uncertainty and randomness under computational constraints. They play a central role in classical cryptography, underpinning the analysis and construction of primitives such as…

Quantum Physics · Physics 2026-02-03 Noam Avidan , Rotem Arnon

We show that concrete hardness assumptions about learning or cloning the output state of a random quantum circuit can be used as the foundation for secure quantum cryptography. In particular, under these assumptions we construct secure…

Quantum Physics · Physics 2025-04-23 Bill Fefferman , Soumik Ghosh , Makrand Sinha , Henry Yuen

We revisit Nisan's classical pseudorandom generator (PRG) for space-bounded computation (STOC 1990) and its applications in streaming algorithms. We describe a new generator, HashPRG, that can be thought of as a symmetric version of Nisan's…

Data Structures and Algorithms · Computer Science 2024-01-05 Praneeth Kacham , Rasmus Pagh , Mikkel Thorup , David P. Woodruff

We propose and experimentally demonstrate the \emph{Quasi-Superposition Quantum-inspired System (QSQS)} -- a conceptual quantum system for randomness generation built on measuring two conjugate observables of a permutation sorting process:…

Quantum Physics · Physics 2025-11-06 Randy Kuang

While in classical cryptography, one-way functions (OWFs) are widely regarded as the "minimal assumption," the situation in quantum cryptography is less clear. Recent works have put forward two concurrent candidates for the minimal…

Quantum Physics · Physics 2025-05-27 Amit Behera , Giulio Malavolta , Tomoyuki Morimae , Tamer Mour , Takashi Yamakawa

Random numbers are central to cryptography and various other tasks. The intrinsic probabilistic nature of quantum mechanics has allowed us to construct a large number of quantum random number generators (QRNGs) that are distinct from the…

Quantum Physics · Physics 2023-12-21 Vaisakh Mannalath , Sandeep Mishra , Anirban Pathak

A quantum encryption scheme (also called private quantum channel, or state randomization protocol) is a one-time pad for quantum messages. If two parties share a classical random string, one of them can transmit a quantum state to the other…

Quantum Physics · Physics 2007-05-23 Andris Ambainis , Adam Smith

The Quantum Skip Gate (QSG) is a unitary circuit primitive that coherently superposes the execution and omission of an expensive quantum subroutine based on the outcome of a cheaper preceding subroutine, without mid-circuit measurement or…

Quantum Physics · Physics 2026-01-26 Kym Derriman

It is known that quantum computers can speed up Monte Carlo simulation compared to classical counterparts. There are already some proposals of application of the quantum algorithm to practical problems, including quantitative finance. In…

Quantum Physics · Physics 2020-09-02 Koichi Miyamoto , Kenji Shiohara

Neuro-symbolic AI bridges the gap between purely symbolic and neural approaches to learning. This often requires maximizing the likelihood of a symbolic constraint w.r.t the neural network's output distribution. Such output distributions…

Machine Learning · Computer Science 2024-01-30 Kareem Ahmed , Kai-Wei Chang , Guy Van den Broeck