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We study the quantum-classical polynomial hierarchy, QCPH, which is the class of languages solvable by a constant number of alternating classical quantifiers followed by a quantum verifier. Our main result is that QCPH is infinite relative…

Quantum Physics · Physics 2025-12-04 Avantika Agarwal , Shalev Ben-David

Let $f$ denote length preserving function on words. A classical algorithm can be considered as $T$ iterated applications of black box representing $f$, beginning with input word $x$ of length $n$. It is proved that if $T=O(2^{n/(7+e)}), e…

Quantum Physics · Physics 2007-05-23 Yuri Ozhigov

Hybrid quantum-classical systems make it possible to utilize existing quantum computers to their fullest extent. Within this framework, parameterized quantum circuits can be regarded as machine learning models with remarkable expressive…

Quantum Physics · Physics 2019-11-15 Marcello Benedetti , Erika Lloyd , Stefan Sack , Mattia Fiorentini

A fundamental model of quantum computation is the programmable quantum gate array. This is a quantum processor that is fed by a program state that induces a corresponding quantum operation on input states. While being programmable, any…

Quantum Physics · Physics 2020-05-20 Leonardo Banchi , Jason Pereira , Seth Lloyd , Stefano Pirandola

We present a simple, yet general, end-to-end deep neural network representation of the potential energy surface for atomic and molecular systems. This methodology, which we call Deep Potential, is "first-principle" based, in the sense that…

Computational Physics · Physics 2020-07-20 Jiequn Han , Linfeng Zhang , Roberto Car , Weinan E

We formulate quantum computing solutions to a large class of dynamic nonlinear asset pricing models using algorithms, in theory exponentially more efficient than classical ones, which leverage the quantum properties of superposition and…

Pricing of Securities · Quantitative Finance 2025-08-26 Eric Ghysels , Jack Morgan

Generative modeling has seen a rising interest in both classical and quantum machine learning, and it represents a promising candidate to obtain a practical quantum advantage in the near term. In this study, we build over a proposed…

Quantum Physics · Physics 2025-07-31 Mohamed Hibat-Allah , Marta Mauri , Juan Carrasquilla , Alejandro Perdomo-Ortiz

Quantum-inspired classical algorithms has received much attention due to its exponential speedup compared to existing algorithms, under certain data storage assumptions. The improvements are noticeable in fundamental linear algebra tasks.…

Quantum Physics · Physics 2025-12-08 Hyunho Cha , Jungwoo Lee

An effective, accessible abstraction hierarchy has made using and programming computers possible for people across all disciplines. Establishing such a hierarchy for quantum programming is an outstanding challenge, especially due to a…

Quantum computers (QCs) must implement quantum error correcting codes (QECCs) to protect their logical qubits from errors, and modeling the effectiveness of QECCs on QCs is an important problem for evaluating the QC architecture. The…

Quantum Physics · Physics 2009-11-13 Eric Chi , Stephen A. Lyon , Margaret Martonosi

Commercially available Noisy Intermediate-Scale Quantum (NISQ) devices now make small hybrid quantum-classical experiments practical, but many tools hide configuration or demand ad-hoc scripting. We introduce the Quantum Experiment…

Quantum Physics · Physics 2025-11-07 Vincent Gierisch , Wolfgang Mauerer

Recent breakthroughs in generative machine learning, powered by massive computational resources, have demonstrated unprecedented human-like capabilities. While beyond-classical quantum experiments can generate samples from classically…

Classical programming languages cannot model essential elements of complex systems such as true random number generation. This paper develops a formal programming language called the lambda-q calculus that addresses the fundamental…

Quantum Physics · Physics 2007-05-23 Philip Maymin

Quantum neural networks have been widely studied in recent years, given their potential practical utility and recent results regarding their ability to efficiently express certain classical data. However, analytic results to date rely on…

Quantum Physics · Physics 2023-06-13 Eric R. Anschuetz , Hong-Ye Hu , Jin-Long Huang , Xun Gao

Quantum computers hold promise for solving problems intractable for classical computers, especially those with high time or space complexity. Practical quantum advantage can be said to exist for such problems when the end-to-end time for…

Quantum Physics · Physics 2025-09-22 Parikshit Pareek , Abhijith Jayakumar , Carleton Coffrin , Sidhant Misra

A growing body of work has established the modelling of stochastic processes as a promising area of application for quantum techologies; it has been shown that quantum models are able to replicate the future statistics of a stochastic…

Quantum Physics · Physics 2020-03-25 Matthew Ho , Mile Gu , Thomas J. Elliott

We present a formal and constructive theory showing that probabilistic finite automata (PFAs) can be exactly simulated using symbolic feedforward neural networks. Our architecture represents state distributions as vectors and transitions as…

Machine Learning · Computer Science 2025-09-24 Sahil Rajesh Dhayalkar

We define two extensions of the typed linear lambda-calculus that yield minimal Turing-complete systems. The extensions are based on unbounded recursion in one case, and bounded recursion with minimisation in the other. We show that both…

Logic in Computer Science · Computer Science 2016-11-28 Sandra Alves , Maribel Fernández , Mário Florido , Ian Mackie

Lawvere showed that generalised metric spaces are categories enriched over $[0, \infty]$, the quantale of the positive extended reals. The statement of enrichment is a quantitative analogue of being a preorder. Towards seeking a logic for…

Logic in Computer Science · Computer Science 2024-02-14 Giorgio Bacci , Radu Mardare , Prakash Panangaden , Gordon Plotkin

Hybrid variational quantum algorithms (VQAs) are promising for solving practical problems such as combinatorial optimization, quantum chemistry simulation, quantum machine learning, and quantum error correction on noisy quantum computers.…

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