10 papers · ranked by Valyu relevance
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This work provides a rigorous theoretical investigation of selective error correction strategies for variational quantum algorithms, with focus on understanding the interplay between error suppression, circuit trainability, and computational resource requirements. We develop a mathematical framework that characterizes…
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This paper develops a comprehensive theoretical framework for designing quantum memory systems with enhanced resilience to thermal decoherence through engineered lattice geometries and protective structures. We formulate a unified mathematical description connecting material properties, geometric configurations, and…
John J. Vastola, Tejas Ramdas, Samuel J. Gershman
Cells store information in part by attaching molecular marks to proteins and DNA. But because marks can be randomly removed (e.g., due to ambient phosphatase activity) and added (e.g., due to ambient kinase activity), information encoding may be poor, and in the worst case marks may only store information on the time…
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Computational chemistry has entered a new era where machine learning (ML) models—particularly graph neural networks and machine learning force fields—routinely deliver quantum mechanical accuracy at classical speeds, scaling to millions of atoms and reshaping workflows in drug discovery, catalysis, and materials…
Christos Papalitsas, Ioannis Mouratidis, Michail Patsakis, Evangelos Stogiannos + 2 more
The exponential growth of publicly available genomic data has created unprecedented opportunities for sequence-based discovery. Locating specific k-mers is fundamental to diverse applications, including metagenomic classification, pathogen and cancer detection, and variant calling yet efficient identification of…
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We present a comprehensive theoretical analysis of quantum subspace diagonalization methods for molecular electronic structure calculations, establishing rigorous complexity bounds and convergence guarantees. Building on recent developments in adaptive quantum algorithms for chemical systems, we formulate a general…
Sashikanta Barik, Parthasarathi Sahu, Koushik Ghosh, Hemachander Subramanian
Adaptive evolution depends on the supply of heritable variation, yet excessive mutation threatens viability by degrading essential molecular functions. Here, we show that this trade-off emerges naturally from the kinetic proofreading mechanism that controls replication fidelity. In our model, environmental shifts alter…
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We present a unified theoretical framework that classifies and analyzes quantum enhancement strategies for classical algorithms, establishing design paradigms that systematically combine quantum subroutines with classical procedures. The theory identifies four fundamental enhancement mechanisms: quantum search…
Namasi G Sankar, Georgios Miliotis, Simon Caton
Genome assembly is important in infectious disease surveillance, antimicrobial resistance monitoring, and cancer genomics. The task of reconstructing full genomic sequences from fragmented reads, can be framed as a large scale combinatorial optimisation problem. Recent advances in quantum computing have introduced new…
Basel Mansour, Daniel Kei Takahashi, George Rafaelyan
Accurate prediction of Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) properties is a central challenge in early-stage drug discovery, where experimental determination remains costly and time-consuming. In this work, we propose a quantum-inspired preprocessing framework in which statistical…