Tootfinder

Quantum Computing Technology Roadmaps and Capability Assessment for Scientific Computing -- An analysis of use cases from the NERSC workload
Daan Camps, Ermal Rrapaj, Katherine Klymko, Hyeongjin Kim, Kevin Gott, Siva Darbha, Jan Balewski, Brian Austin, Nicholas J. Wright
https://arxiv.org/abs/2509.09882

Quantum Computing Technology Roadmaps and Capability Assessment for Scientific Computing -- An analysis of use cases from the NERSC workload
The National Energy Research Scientific Computing Center (NERSC), as the high-performance computing (HPC) facility for the Department of Energy's Office of Science, recognizes the essential role of quantum computing in its future mission. In this report, we analyze the NERSC workload and identify materials science, quantum chemistry, and high-energy physics as the science domains and application areas that stand to benefit most from quantum computers. These domains jointly make up over 50% of t…

Quantum computing stocks jumped after JPMorgan announced a $10B strategic tech investment; Arqit, D-Wave, Rigetti, and IonQ each rose about 20% (Jaures Yip/CNBC)
https://www.cnbc.com/2025/10/13/quantum-stocks-jpmorgan-investing-push.html

Quantum stocks surge after JPMorgan investing push into strategic tech
JPMorgan announced it would invest $10 billion in 27 specific industries, including quantum computing.

HUGR: A Quantum-Classical Intermediate Representation
Mark Koch, Agust\'in Borgna, Seyon Sivarajah, Alan Lawrence, Alec Edgington, Douglas Wilson, Craig Roy, Luca Mondada, Lukas Heidemann, Ross Duncan
https://arxiv.org/abs/2510.11420

HUGR: A Quantum-Classical Intermediate Representation
We introduce the Hierarchical Unified Graph Representation (HUGR): a novel graph based intermediate representation for mixed quantum-classical programs. HUGR's design features high expressivity and extensibility to capture the capabilities of near-term and forthcoming quantum computing devices, as well as new and evolving abstractions from novel quantum programming paradigms. The graph based structure is machine-friendly and supports powerful pattern matching based compilation techniques. Inspi…

Introducing CQ: A C-like API for Quantum Accelerated HPC
Oliver Thomson Brown, Mateusz Meller, James Richings
https://arxiv.org/abs/2508.10854 https://arxi…

Introducing CQ: A C-like API for Quantum Accelerated HPC
In this paper we present CQ, a specification for a C-like API for quantum accelerated HPC, as well as CQ-SimBE, a reference implementation of CQ written in C99, and built on top of the statevector simulator QuEST. CQ focuses on enabling the incremental integration of quantum computing into classical HPC codes by supporting runtime offloading from languages such as C and Fortran. It provides a way of describing and offloading quantum computations which is compatible with strictly and strongly ty…

AEGISS -- Atomic orbital and Entropy-based Guided Inference for Space Selection -- A novel semi-automated active space selection workflow for quantum chemistry and quantum computing applications
Fabio Tarocco, Pi A. B. Haase, Fabijan Pavo\v{s}evi\'c, Vijay Krishna, Leonardo Guidoni, Stefan Knecht, Martina Stella
https://arxiv.org/abs/2…

AEGISS -- Atomic orbital and Entropy-based Guided Inference for Space Selection -- A novel semi-automated active space selection workflow for quantum chemistry and quantum computing applications
The selection of a balanced active space is a critical step in multi-reference quantum chemistry calculations, particularly for systems with strong electron correlation. Likewise, active space selection is a key to unlock the potential of contemporary quantum computing in quantum chemistry. Albeit recent progress, there remains a lack of a unified, robust, and fully automated framework for active space selection that performs reliably across a wide range of molecular systems. In this work, we…

Quantum measurement systems and applications to particle physics and cosmology
Masashi Hazumi
https://arxiv.org/abs/2508.10325 https://arxiv.org/pdf/2508.1…

Quantum measurement systems and applications to particle physics and cosmology
There are new detector proposals and R&D that utilize quantum enhancements not previously adopted. Examples include superconducting quantum sensors, atom interferometry, and quantum spin sensors. They are mainly motivated by industrial applications toward quantum computing, secure quantum communication systems, and high-sensitivity sensors. Given the excellent potential of the new quantum measurement systems, there are also new proposals to apply them in particle physics and cosmology. In this …

Amplified Directional Photoluminescence from CIS Quantum Dots and hBN Quantum Emitters using Tunable BIC Metasurfaces
Omar A. M. Abdelraouf
https://arxiv.org/abs/2510.10470 http…

Amplified Directional Photoluminescence from CIS Quantum Dots and hBN Quantum Emitters using Tunable BIC Metasurfaces
Integrated and tunable light sources are critical for advancing quantum nanophotonic chips in quantum computing, communications, and sensing. However, efficient and tunable emission amplification post-fabrication poses major challenges. Hybrid metasurfaces combining niobium pentoxide (Nb2O5), copper indium sulfide (CIS) quantum dots or hexagonal boron nitride (hBN), and antimony trisulfide (Sb2S3) as a low-loss phase-change material offer a compelling solution for dynamic control and amplificat…

Quantum algorithms based on quantum trajectories
Evan Borras, Milad Marvian
https://arxiv.org/abs/2509.10425 https://arxiv.org/pdf/2509.10425

Quantum algorithms based on quantum trajectories
Quantum simulation has emerged as a key application of quantum computing, with significant progress made in algorithms for simulating both closed and open quantum systems. The simulation of open quantum systems, particularly those governed by the Lindblad master equation, has received attention recently with the current state-of-the-art algorithms having an input model query complexity of $O(T \mathrm{polylog}(T/ε))$, where $T$ and $ε$ are the requested time and precision of the simulation re…

Quantum Alternating Direction Method of Multipliers for Semidefinite Programming
Hantao Nie, Dong An, Zaiwen Wen
https://arxiv.org/abs/2510.10056 https://a…

Quantum Alternating Direction Method of Multipliers for Semidefinite Programming
Semidefinite programming (SDP) is a fundamental convex optimization problem with wide-ranging applications. However, solving large-scale instances remains computationally challenging due to the high cost of solving linear systems and performing eigenvalue decompositions. In this paper, we present a quantum alternating direction method of multipliers (QADMM) for SDPs, building on recent advances in quantum computing. An inexact ADMM framework is developed, which tolerates errors in the iterates …

Thermoelectric effect at the quantum Hall-superconductor interface
Jordan T. McCourt, John Chiles, Chun-Chia Chen, Kenji Watanabe, Takashi Tanaguchi, Francois Amet, Gleb Finkelstein
https://arxiv.org/abs/2510.09798

Thermoelectric effect at the quantum Hall-superconductor interface
The interfaces of quantum Hall insulators with superconductors have emerged as a promising platform to realise interesting physics that may be relevant for topologically protected quantum computing. However, these interfaces can host other effects which obscure the detection of the desired excitations. Here we present measurements of the thermoelectric effect at the quantum Hall-superconductor interface. We explain the heat transport by considering the formation of a hotspot at the interface, w…

A Symmetry-Integrated Approach to Surface Code Decoding
Hoshitaro Ohnishi, Hideo Mukai
https://arxiv.org/abs/2509.10164 https://arxiv.org/pdf/2509.10164

A Symmetry-Integrated Approach to Surface Code Decoding
Quantum error correction, which utilizes logical qubits that are encoded as redundant multiple physical qubits to find and correct errors in physical qubits, is indispensable for practical quantum computing. Surface code is considered to be a promising encoding method with a high error threshold that is defined by stabilizer generators. However, previous methods have suffered from the problem that the decoder acquires solely the error probability distribution because of the non-uniqueness of co…

Assessing the Impact of Post-Quantum Digital Signature Algorithms on Blockchains
Alison Gon\c{c}alves Schemitt (PUCRS), Henrique Fan da Silva (UNIPAMPA), Roben Castagna Lunardi (PUCRS, IFRS), Diego Kreutz (UNIPAMPA), Rodrigo Brand\~ao Mansilha (UNIPAMPA), Avelino Francisco Zorzo (PUCRS)
https://arxiv.org/abs/2510.09271

Assessing the Impact of Post-Quantum Digital Signature Algorithms on Blockchains
The advent of quantum computing threatens the security of traditional encryption algorithms, motivating the development of post-quantum cryptography (PQC). In 2024, the National Institute of Standards and Technology (NIST) standardized several PQC algorithms, marking an important milestone in the transition toward quantum-resistant security. Blockchain systems fundamentally rely on cryptographic primitives to guarantee data integrity and transaction authenticity. However, widely used algorithms…

Trajectory-Protected Quantum Computing
Barbara \v{S}oda, Pierre-Antoine Graham, T. Rick Perche, Gurpahul Singh
https://arxiv.org/abs/2510.12771 https://arx…

Trajectory-Protected Quantum Computing
We introduce a novel method that simultaneously isolates a quantum computer from decoherence and enables the controlled implementation of computational gates. We demonstrate a quantum computing model that utilizes a qubit's motion to protect it from decoherence. We model a qubit interacting with a quantum field via the standard light-matter interaction model: an Unruh-DeWitt detector, i.e., the qubit, follows a prescribed classical trajectory while interacting with a scalar quantum field. We sw…

Australia is emerging as a prominent player in quantum computing, enabled by breakthrough academic work and sustained government funding since the 1990s (Nic Fildes/Financial Times)
https://www.ft.com/content/3bac2c02-4c59-4010-934d-2c0e2106d74a

Quantum-enhanced Computer Vision: Going Beyond Classical Algorithms
Natacha Kuete Meli, Shuteng Wang, Marcel Seelbach Benkner, Michele Sasdelli, Tat-Jun Chin, Tolga Birdal, Michael Moeller, Vladislav Golyanik
https://arxiv.org/abs/2510.07317

Quantum-enhanced Computer Vision: Going Beyond Classical Algorithms
Quantum-enhanced Computer Vision (QeCV) is a new research field at the intersection of computer vision, optimisation theory, machine learning and quantum computing. It has high potential to transform how visual signals are processed and interpreted with the help of quantum computing that leverages quantum-mechanical effects in computations inaccessible to classical (i.e. non-quantum) computers. In scenarios where existing non-quantum methods cannot find a solution in a reasonable time or comput…

Quasiparticle pairing encoding of atomic nuclei for quantum annealing
Emanuele Costa, Axel P\'erez-Obiol, Javier Men\'endez, Arnau Rios, Artur Garc\'ia-S\'aez, Bruno Juli\'a-D\'iaz
https://arxiv.org/abs/2510.10118

Quasiparticle pairing encoding of atomic nuclei for quantum annealing
Quantum computing is emerging as a promising tool in nuclear physics. However, the cost of encoding fermionic operators hampers the application of algorithms in current noisy quantum devices. In this work, we analyze an encoding scheme based on pairing nucleon modes. This approach significantly reduces the complexity of the encoding, while maintaining a high accuracy for the ground states of semimagic nuclei across the $sd$ and $pf$ shells and for tin isotopes. In addition, we also explore the …

Optimizing Inter-chip Coupler Link Placement for Modular and Chiplet Quantum Systems
Zefan Du, Pedro Chumpitaz Flores, Wenqi Wei, Juntao Chen, Kaixun Hua, Ying Mao
https://arxiv.org/abs/2509.10409

Optimizing Inter-chip Coupler Link Placement for Modular and Chiplet Quantum Systems
Quantum computing offers unparalleled computational capabilities but faces significant challenges, including limited qubit counts, diverse hardware topologies, and dynamic noise and error rates, which hinder scalability and reliability. Distributed quantum computing, particularly chip-to-chip connections, has emerged as a solution by interconnecting multiple processors to collaboratively execute large circuits. While hardware advancements, such as IBM's Quantum Flamingo, focus on improving inte…

Quantum Computing as a Service - a Software Engineering Perspective
Aakash Ahmad, Muhammad Waseem, Bakheet Aljedaani, Mahdi Fahmideh, Peng Liang, Feras Awaysheh
https://arxiv.org/abs/2510.04982

Quantum Computing as a Service - a Software Engineering Perspective
Quantum systems have started to emerge as a disruptive technology and enabling platforms - exploiting the principles of quantum mechanics via programmable quantum bits (QuBits) - to achieve quantum supremacy in computing. Academic research, industrial projects (e.g., Amazon Braket, IBM Qiskit), and consortiums like 'Quantum Flagship' are striving to develop practically capable and commercially viable quantum computing (QC) systems and technologies. Quantum Computing as a Service (QCaaS) is view…

De Sitter Complexity Grows Linearly in the Static Patch
Vyshnav Mohan, Watse Sybesma
https://arxiv.org/abs/2508.10093 https://arxiv.org/pdf/2508.10093

De Sitter Complexity Grows Linearly in the Static Patch
The observable universe has undergone periods of expansion that are well approximated by de Sitter (dS) space. Still lacking is a quantum mechanical description of dS, both globally and when restricted to the static patch. We develop a novel prescription for computing holographic complexity in the dS static patch to determine its microscopic features. Specifically, we propose that the natural candidate for dS complexity is the volume of extremal timelike surfaces restricted to the static patch,…

Unified Theory of Dark Count Rate and System Detection Efficiency for NbN, WSi Based Superconducting Single Photon Detectors
Daien He, Leif Bauer, Sathwik Bharadwaj, Zubin Jacob
https://arxiv.org/abs/2508.10816

Unified Theory of Dark Count Rate and System Detection Efficiency for NbN, WSi Based Superconducting Single Photon Detectors
Predicting the behavior of superconducting nanowire single photon detectors (SNSPDs) is important as their use becomes more widespread in fields ranging from quantum computing to quantum remote sensing. Here, we present a vortex crossing theory of photon detection which provides a unified definition of system detection efficiency and dark count rates. Our approach quantitatively captures the plateau region of system detection efficiency for NbN and WSi based SNSPDs. We concurrently predict the …

Quantum Markov Chain Monte Carlo for Cosmological Functions
Giuseppe Sarracino, Vincenzo Fabrizio Cardone, Roberto Scaramella, Giuseppe Riccio, Andrea Bulgarelli, Carlo Burigana, Luca Cappelli, Stefano Cavuoti, Farida Farsian, Irene Graziotti, Massimo Meneghetti, Giuseppe Murante, Nicol\`o Parmiggiani, Alessandro Rizzo, Francesco Schillir\`o, Vincenzo Testa, Tiziana Trombetti

Quantum Markov Chain Monte Carlo for Cosmological Functions
We present an implementation of Quantum Computing for a Markov Chain Monte Carlo method with an application to cosmological functions, to derive posterior distributions from cosmological probes. The algorithm proposes new steps in the parameter space via a quantum circuit whose resulting statevector provides the components of the shift vector. The proposed point is accepted or rejected via the classical Metropolis-Hastings acceptance method. The advantage of this hybrid quantum approach is that…

IBM is holding its own in the quantum computing race against Google, Microsoft, and others, as they tackle enormous scientific and engineering challenges (Christopher Mims/Wall Street Journal)
https://www.wsj.com/tech/ibm-quantum-compute…

Astigmatism-free 3D Optical Tweezer Control for Rapid Atom Rearrangement
Yue-Hui Lu, Nathan Song, Tai Xiang, Jacquelyn Ho, Tsai-Chen Lee, Zhenjie Yan, Dan M. Stamper-Kurn
https://arxiv.org/abs/2510.11451

Astigmatism-free 3D Optical Tweezer Control for Rapid Atom Rearrangement
Reconfigurable arrays of neutral atoms are a leading platform for quantum computing, quantum simulation, and quantum metrology. The most common method for atom reconfiguration using optical tweezers relies on frequency chirping of acousto-optic deflectors (AODs). However, chirp-induced acoustic lensing limits the speed of atom transport by deformation of the tweezer profile and warping of the tweezer trajectory. We use a three-dimensional acousto-optic deflector lens (3D-AODL) to mitigate both …

Toward quantum-safe scalable networks: an open, standards-aware key management framework
Ane Sanz, Asier Atutxa, David Franco, Jasone Astorga, Eduardo Jacob, Diego L\'opez
https://arxiv.org/abs/2509.09453

Toward quantum-safe scalable networks: an open, standards-aware key management framework
With the advent of quantum computing, the increasing threats to security poses a great challenge to communication networks. Recent innovations in this field resulted in promising technologies such as Quantum Key Distribution (QKD), which enables the generation of unconditionally secure keys, establishing secure communications between remote nodes. Additionally, QKD networks enable the interconnection of multinode architectures, extending the point-to-point nature of QKD. However, due to the lim…

Mitigating Exponential Mixed Frequency Growth through Frequency Selection and Dimensional Separation in Quantum Machine Learning
Michael Poppel, David Bucher, Maximilian Zorn, Nico Kraus, Jonas Stein, Claudia Linnhoff-Popien
https://arxiv.org/abs/2508.10533

Mitigating Exponential Mixed Frequency Growth through Frequency Selection and Dimensional Separation in Quantum Machine Learning
To leverage the potential computational speedup of quantum computing (QC), research in quantum machine learning (QML) has gained increasing prominence. Angle encoding techniques in QML models have been shown to generate truncated Fourier series, offering asymptotically universal function approximation capabilities. By selecting efficient feature maps (FMs) within quantum circuits, one can leverage the exponential growth of Fourier frequencies for improved approximation. In multi-dimensional set…

Gauging the variational optimization of projected entangled-pair states
Wei Tang, Laurens Vanderstraeten, Jutho Haegeman
https://arxiv.org/abs/2508.10822 https://

Gauging the variational optimization of projected entangled-pair states
Projected entangled-pair states (PEPS) constitute a powerful variational ansatz for capturing ground state physics of two-dimensional quantum systems. However, accurately computing and minimizing the energy expectation value remains challenging, in part because the impact of the gauge degrees of freedom that are present in the tensor network representation is poorly understood. We analyze the role of gauge transformations for the case of a U(1)-symmetric PEPS with point group symmetry, thereby …

Quantum Fisher Information as a Measure of Symmetry Breaking in Quantum Many-Body Systems
Shion Yamashika, Shimpei Endo, Hiroyasu Tajima
https://arxiv.org/abs/2509.07468 https:/…

Quantum Fisher Information as a Measure of Symmetry Breaking in Quantum Many-Body Systems
Symmetry breaking underlies diverse phenomena from phase transitions in condensed matter to fundamental interactions in gauge theories. Despite many proposed indicators, a general quantification of symmetry breaking that is faithful, computable, and valid in the thermodynamic limit has remained elusive. Here, within quantum resource theory, we propose the quantum Fisher information (QFI) as such a measure. We demonstrate its utility by computing QFI for paradigmatic models: in the BCS supercond…

Simulating Mass-Dependent Decoherence in Quantum Computers: Baseline Signatures for Testing Gravity-Induced Collapse
Viswak R Balaji, Samuel Punch
https://arxiv.org/abs/2508.10590

Simulating Mass-Dependent Decoherence in Quantum Computers: Baseline Signatures for Testing Gravity-Induced Collapse
We present a quantum computing simulation study of mass-dependent decoherence models inspired by Penrose's gravity-induced collapse hypothesis. According to objective reduction (OR) theory, quantum superpositions become unstable when the gravitational self-energy difference between branches exceeds a certain threshold, leading to a collapse time $τ\approx \hbar / E_G$. In this work, we implement a mass-dependent dephasing noise channel, $p(m) = 1 - e^{-k m^α}$, within the Qiskit AerSimulator,…

QUASAR: Quantum Assembly Code Generation Using Tool-Augmented LLMs via Agentic RL
Cong Yu, Valter Uotila, Shilong Deng, Qingyuan Wu, Tuo Shi, Songlin Jiang, Lei You, Bo Zhao
https://arxiv.org/abs/2510.00967

QUASAR: Quantum Assembly Code Generation Using Tool-Augmented LLMs via Agentic RL
Designing and optimizing task-specific quantum circuits are crucial to leverage the advantage of quantum computing. Recent large language model (LLM)-based quantum circuit generation has emerged as a promising automatic solution. However, the fundamental challenges remain unaddressed: (i) parameterized quantum gates require precise numerical values for optimal performance, which also depend on multiple aspects, including the number of quantum gates, their parameters, and the layout/depth of the…

Probabilistic Links Between Quantum Classification of Patterns of Boolean Functions and Hamming Distance
Theodore Andronikos, Constantinos Bitsakos, Konstantinos Nikas, Georgios I. Goumas, Nectarios Koziris
https://arxiv.org/abs/2510.12736

Probabilistic Links Between Quantum Classification of Patterns of Boolean Functions and Hamming Distance
This article investigates the probabilistic relationship between quantum classification of Boolean functions and their Hamming distance. By integrating concepts from quantum computing, information theory, and combinatorics, we explore how Hamming distance serves as a metric for analyzing deviations in function classification. Our extensive experimental results confirm that the Hamming distance is a pivotal metric for validating nearest neighbors in the process of classifying random functions. O…

Signal Protocol and Post-Quantum Ratchets
[…] The @… Protocol is a set of cryptographic specifications that provides end-to-end encryption for private communications exchanged daily by billions of people around the world. […]
🗨️ ht…

Signal Protocol and Post-Quantum Ratchets
We are excited to announce a significant advancement in the security of the Signal Protocol: the introduction of the Sparse Post Quantum Ratchet (SPQR). This new ratchet enhances the Signal Protocol’s resilience against future quantum computing threats while maintaining our existing security guar...

Computing moment polytopes - with a focus on tensors, entanglement and matrix multiplication
Maxim van den Berg, Matthias Christandl, Vladimir Lysikov, Harold Nieuwboer, Michael Walter, Jeroen Zuiddam
https://arxiv.org/abs/2510.08336

Computing moment polytopes - with a focus on tensors, entanglement and matrix multiplication
Tensors are fundamental in mathematics, computer science, and physics. Their study through algebraic geometry and representation theory has proved very fruitful in the context of algebraic complexity theory and quantum information. In particular, moment polytopes have been understood to play a key role. In quantum information, moment polytopes (also known as entanglement polytopes) provide a framework for the single-particle quantum marginal problem and offer a geometric characterization of ent…

Quantum Brush: A quantum computing-based tool for digital painting
Jo\~ao S. Ferreira, Arianna Crippa, Astryd Park, Daniel Bultrini, Pierre Fromholz, Roman Lipski, Karl Jansen, James R. Wootton
https://arxiv.org/abs/2509.01442

Quantum Brush: A quantum computing-based tool for digital painting
We present Quantum Brush, an open-source digital painting tool that harnesses quantum computing to generate novel artistic expressions. The tool includes four different brushes that translate strokes into unique quantum algorithms, each highlighting a different way in which quantum effects can produce novel aesthetics. Each brush is designed to be compatible with the current noisy intermediate-scale quantum (NISQ) devices, as demonstrated by executing them on IQM's Sirius device.

Light Storage and Retrieval in an Atomic Tripod System
Shan Zhong, A. J. Sudler, D. Blume, Alberto M. Marino
https://arxiv.org/abs/2508.10220 https://arxiv…

Light Storage and Retrieval in an Atomic Tripod System
Highly-efficient quantum memories are essential for advancing quantum information processing technologies, including scalable quantum computing and quantum networks. We experimentally demonstrate a light storage and retrieval protocol in a tripod system using an ensemble of laser-cooled $^{87}$Rb atoms. The tripod system, which consists of three ground states and an excited state, offers rich dynamics: its use to coherently store and retrieve a weak probe pulse in the $^{87}$Rb $F=1$ ground sta…

Replaced article(s) found for math.OC. https://arxiv.org/list/math.OC/new
[1/1]:
- A robust BFGS algorithm for unconstrained nonlinear optimization problems
Yaguang Yang
https://arxiv.org/abs/1212.5929
- Quantum computing and the stable set problem
Alja\v{z} Krpan, Janez Povh, Dunja Pucher
https://arxiv.org/abs/2405.12845 https://mastoxiv.page/@arXiv_mathOC_bot/112483516437815686
- Mean Field Game with Reflected Jump Diffusion Dynamics: A Linear Programming Approach
Zongxia Liang, Xiang Yu, Keyu Zhang
https://arxiv.org/abs/2508.20388 https://mastoxiv.page/@arXiv_mathOC_bot/115111048711698998
- Differential Dynamic Programming for the Optimal Control Problem with an Ellipsoidal Target Set a...
Sungjun Eom, Gyunghoon Park
https://arxiv.org/abs/2509.07546 https://mastoxiv.page/@arXiv_mathOC_bot/115179281556444440
- On the Moreau envelope properties of weakly convex functions
Marien Renaud, Arthur Leclaire, Nicolas Papadakis
https://arxiv.org/abs/2509.13960 https://mastoxiv.page/@arXiv_mathOC_bot/115224514482363803
- Automated algorithm design via Nevanlinna-Pick interpolation
Ibrahim K. Ozaslan, Tryphon T. Georgiou, Mihailo R. Jovanovic
https://arxiv.org/abs/2509.21416 https://mastoxiv.page/@arXiv_mathOC_bot/115286533597711930
- Optimal Control of a Bioeconomic Crop-Energy System with Energy Reinvestment
Othman Cherkaoui Dekkaki
https://arxiv.org/abs/2510.11381 https://mastoxiv.page/@arXiv_mathOC_bot/115372322896073250
- Point Convergence Analysis of the Accelerated Gradient Method for Multiobjective Optimization: Co...
Yingdong Yin
https://arxiv.org/abs/2510.26382 https://mastoxiv.page/@arXiv_mathOC_bot/115468018035252078
- History-Aware Adaptive High-Order Tensor Regularization
Chang He, Bo Jiang, Yuntian Jiang, Chuwen Zhang, Shuzhong Zhang
https://arxiv.org/abs/2511.05788
- Equivalence of entropy solutions and gradient flows for pressureless 1D Euler systems
Jos\'e Antonio Carrillo, Sondre Tesdal Galtung
https://arxiv.org/abs/2312.04932 https://mastoxiv.page/@arXiv_mathAP_bot/111560077272113052
- Kernel Modelling of Fading Memory Systems
Yongkang Huo, Thomas Chaffey, Rodolphe Sepulchre
https://arxiv.org/abs/2403.11945 https://mastoxiv.page/@arXiv_eessSY_bot/112121123836064435
- The Maximum Theoretical Ground Speed of the Wheeled Vehicle
Altay Zhakatayev, Mukatai Nemerebayev
https://arxiv.org/abs/2502.15341 https://mastoxiv.page/@arXiv_physicsclassph_bot/114057765769441123
- Hessian stability and convergence rates for entropic and Sinkhorn potentials via semiconcavity
Giacomo Greco, Luca Tamanini
https://arxiv.org/abs/2504.11133 https://mastoxiv.page/@arXiv_mathPR_bot/114346453424694503
- Optimizing the ground state energy of the three-dimensional magnetic Dirichlet Laplacian with con...
Matthias Baur
https://arxiv.org/abs/2504.21597 https://mastoxiv.page/@arXiv_mathph_bot/114431404740241516
- A localized consensus-based sampling algorithm
Arne Bouillon, Alexander Bodard, Panagiotis Patrinos, Dirk Nuyens, Giovanni Samaey
https://arxiv.org/abs/2505.24861 https://mastoxiv.page/@arXiv_mathNA_bot/114612580684567066
- A Novel Sliced Fused Gromov-Wasserstein Distance
Moritz Piening, Robert Beinert
https://arxiv.org/abs/2508.02364 https://mastoxiv.page/@arXiv_csLG_bot/114976243138728278
- Minimal Regret Walras Equilibria for Combinatorial Markets via Duality, Integrality, and Sensitiv...
Alo\"is Duguet, Tobias Harks, Martin Schmidt, Julian Schwarz
https://arxiv.org/abs/2511.09021 https://mastoxiv.page/@arXiv_csGT_bot/115541243299714775
toXiv_bot_toot

Non-unitary Time Evolution via the Chebyshev Expansion Method
\'Aron Holl\'o, D\'aniel Varjas, Cosma Fulga, L\'aszl\'o Oroszl\'any, Viktor K\"onye
https://arxiv.org/abs/2510.10643

Non-unitary Time Evolution via the Chebyshev Expansion Method
The Chebyshev expansion method is a well-established technique for computing the time evolution of quantum states, particularly in Hermitian systems with a bounded spectrum. Here, we show that the applicability of the Chebyshev expansion method extends well beyond this constraint: It remains valid across the entire complex plane and is thus suitable for arbitrary non-Hermitian matrices. We identify that numerical rounding errors are the primary source of errors encountered when applying the met…

A look at Rigetti Computing and D-Wave Quantum, whose shares have surged over 1,900% in the past year as the potential of quantum computing captivates investors (Felice Maranz/Bloomberg)
https://www.bloomberg.com/news/articles/20

Quantum Network-Based Prediction of Cancer Driver Genes
Patricia Marques, Andreas Wichert, Duarte Magano, Bruno Coutinho
https://arxiv.org/abs/2510.12628 https://

Quantum Network-Based Prediction of Cancer Driver Genes
Identification of cancer driver genes is fundamental for the development of targeted therapeutic interventions. The integration of mutational profiles with protein-protein interaction (PPI) networks offers a promising avenue for their detection [ 1, 2], but scaling to large network datasets is computationally demanding. Quantum computing offers compact representations and potential complexity reductions. Motivated by the classical method of Gumpinger et al. [3], in this work we introduce a supe…

Quantum Computing for Large-scale Network Optimization: Opportunities and Challenges
Sebastian Macaluso, Giovanni Geraci, El\'ias F. Combarro, Sergi Abadal, Ioannis Arapakis, Sofia Vallecorsa, Eduard Alarc\'on
https://arxiv.org/abs/2509.07773

Quantum Computing for Large-scale Network Optimization: Opportunities and Challenges
The complexity of large-scale 6G-and-beyond networks demands innovative approaches for multi-objective optimization over vast search spaces, a task often intractable. Quantum computing (QC) emerges as a promising technology for efficient large-scale optimization. We present our vision of leveraging QC to tackle key classes of problems in future mobile networks. By analyzing and identifying common features, particularly their graph-centric representation, we propose a unified strategy involving …

Quantum dots emission enhancement via coupling with an epsilon-near-zero sublayer
S. Stengel, A. B. Solanki, H. Ather, P. G. Chen, J. I. Choi, B. M. Triplett, M. Ozlu, K. R. Choi, A. Senichev, W. Jaffray, A. S. Lagutchev, L. Caspani, M. Clerici, L. Razzari, R. Morandotti, M. Ferrera, A. Boltasseva, V. M. Shalaev
https://arxiv.org/abs/2509.…

Quantum dots emission enhancement via coupling with an epsilon-near-zero sublayer
Quantum emitters operating at telecom wavelengths are essential for the advancement of quantum technologies, particularly in the development of integrated on-chip devices for quantum computing, communication, and sensing. Coupling resonant structures to a near-zero-index (NZI) environment has been shown to enhance their optical performance by both increasing spontaneous emission rates and improving emission directionality. In this work, we comparatively study emission characteristics of colloid…

JPMorgan Chase launches a decade-long plan to invest $10B in industries critical for national security, including "frontier" tech like AI and quantum computing (Hugh Son/CNBC)
https://www.cnbc.com/2025/10/13/jpmorgan-chase-to-invest-10-…

JPMorgan Chase says it will invest $10 billion into industries critical for national security
The move helps JPMorgan Chase organize its activities around national interests at a time of heightened tensions between the U.S. and China.

Comparative Studies of Quantum Annealing, Digital Annealing, and Classical Solvers for Reaction Network Pathway Analysis and mRNA Codon Selection
Milind Upadhyay, Mark Nicholas Jones
https://arxiv.org/abs/2509.09862

Comparative Studies of Quantum Annealing, Digital Annealing, and Classical Solvers for Reaction Network Pathway Analysis and mRNA Codon Selection
For various optimization problems, the classical time to solution is super-polynomial and intractable to solve with classical bit-based computing hardware to date. Digital and quantum annealers have the potential to identify near-optimal solutions for such optimization problems using a quadratic unconstrained binary optimization (QUBO) problem formulation. This work benchmarks two use cases to evaluate the utility of QUBO solvers for combinatorial optimization problems, in order to determine if…

Decoding Multimode Gottesman-Kitaev-Preskill Codes with Noisy Auxiliary States
Marc-Antoine Roy, Thomas Pousset, Baptiste Royer
https://arxiv.org/abs/2510.12677 https://

Decoding Multimode Gottesman-Kitaev-Preskill Codes with Noisy Auxiliary States
In order to achieve fault-tolerant quantum computing, we make use of quantum error correction schemes designed to protect the logical information of the system from decoherence. A promising way to preserve such information is to use the multimode Gottesman-Kitaev-Preskill (GKP) encoding, which encodes logical qubits into several harmonic oscillators. In this work, we focus on decoding the measurements obtained from Steane-type quantum error correction protocols for multimode GKP codes. We propo…

QUASAR: Quantum Assembly Code Generation Using Tool-Augmented LLMs via Agentic RL
Cong Yu, Valter Uotila, Shilong Deng, Qingyuan Wu, Tuo Shi, Songlin Jiang, Lei You, Bo Zhao
https://arxiv.org/abs/2510.00967

QUASAR: Quantum Assembly Code Generation Using Tool-Augmented LLMs via Agentic RL
Designing and optimizing task-specific quantum circuits are crucial to leverage the advantage of quantum computing. Recent large language model (LLM)-based quantum circuit generation has emerged as a promising automatic solution. However, the fundamental challenges remain unaddressed: (i) parameterized quantum gates require precise numerical values for optimal performance, which also depend on multiple aspects, including the number of quantum gates, their parameters, and the layout/depth of the…

Quantum Transport Reservoir Computing
Yecheng Jing, Pengfei Wang, Shuai Zhang, Zhoujie Zeng, Shi-Jun Liang, Wei Chen
https://arxiv.org/abs/2509.07778 https://

Quantum Transport Reservoir Computing
Reservoir computing (RC), a neural network designed for temporal data, enables efficient computation with low-cost training and direct physical implementation. Recently, quantum RC has opened new possibilities for conventional RC and introduced novel ideas to tackle open problems in quantum physics and advance quantum technologies. Despite its promise, it faces challenges, including physical realization, output readout, and measurement-induced back-action. Here, we propose to implement quantum …

The foundational value of quantum computing for classical fluids
Sauro Succi, Claudio Sanavio, Peter Love
https://arxiv.org/abs/2510.09178 https://arxiv.or…

The foundational value of quantum computing for classical fluids
Quantum algorithms for classical physics problems expose new patterns of quantum information flow as compared to the many-body Schrödinger equation. As a result, besides their potential practical applications, they also offer a valuable theoretical and computational framework to elucidate the foundations of quantum mechanics, particularly the validity of the many-body Schrödinger equation in the limit of large number of particles, on the order of the Avogadro number. This idea is illustrated …

Are Enterprises Ready for Quantum-Safe Cybersecurity?
Tran Duc Le, Phuc Hao Do, Truong Duy Dinh, Van Dai Pham
https://arxiv.org/abs/2509.01731 https://arxi…

Are Enterprises Ready for Quantum-Safe Cybersecurity?
Quantum computing threatens to undermine classical cryptography by breaking widely deployed encryption and signature schemes. This paper examines enterprise readiness for quantum-safe cybersecurity through three perspectives: (i) the technologist view, assessing the maturity of post-quantum cryptography (PQC) and quantum key distribution (QKD); (ii) the enterprise (CISO/CIO) view, analyzing organizational awareness, risk management, and operational barriers; and (iii) the threat actor view, eva…

Light coupling to photonic integrated circuits using optimized lensed fibers
Dengke Chen, Zeying Zhong, Sanli Huang, Jiahao Sun, Sicheng Zeng, Baoqi Shi, Yi-Han Luo, Junqiu Liu
https://arxiv.org/abs/2510.10635

Light coupling to photonic integrated circuits using optimized lensed fibers
Efficient and reliable light coupling between optical fibers and photonic integrated circuits has arguably been the most essential issue in integrated photonics for optical interconnects, nonlinear signal conversion, neuromorphic computing, and quantum information processing. A commonly employed approach is to use inverse tapers interfacing with lensed fibers, particularly for waveguides of relatively low refractive index such as silicon nitride (Si3N4), silicon oxynitride and lithium niobate. …

Gate Teleportation vs Circuit Cutting in Distributed Quantum Computing
Shobhit Gupta, Nikolay Sheshko, Daniel J. Dilley, Alvin Gonzales, Manish K. Singh, Zain H. Saleem
https://arxiv.org/abs/2510.08894

Gate Teleportation vs Circuit Cutting in Distributed Quantum Computing
Distributing circuits across quantum processor modules will enable the execution of circuits larger than the qubit count limitations of monolithic processors. While distributed quantum computation has primarily utilized circuit cutting, it incurs an exponential growth of sub-circuit sampling and classical post-processing overhead with an increasing number of cuts. The entanglement-based gate teleportation approach does not inherently incur exponential sampling overhead, provided that quantum in…

High-Fidelity Single-Shot Readout and Selective Nuclear Spin Control for a Spin-1/2 Quantum Register in Diamond
Prithvi Gundlapalli, Philipp J. Vetter, Genko Genov, Michael Olney-Fraser, Peng Wang, Matthias M. M\"uller, Katharina Senkalla, Fedor Jelezko
https://arxiv.org/abs/2510.09164

High-Fidelity Single-Shot Readout and Selective Nuclear Spin Control for a Spin-1/2 Quantum Register in Diamond
Quantum networks offer a way to overcome the size and complexity limitations of single quantum devices by linking multiple nodes into a scalable architecture. Group-IV color centers in diamond, paired with long-lived nuclear spins, have emerged as promising building blocks demonstrating proof-of-concept experiments such as blind quantum computing and quantum-enhanced sensing. However, realizing a large-scale electro-nuclear register remains a major challenge. Here we establish the germanium-vac…

Quantum computing company IonQ raises $2B by selling 21.5M shares and pre-funded warrants to Heights Capital at $93 each, a 20% premium over October 9's close (David Morris/Bloomberg)
https://www.bloomberg.com/news/articles/20

Universal syndrome-based recovery for noise-adapted quantum error correction
Debjyoti Biswas, Prabha Mandayam
https://arxiv.org/abs/2510.08719 https://arxi…

Universal syndrome-based recovery for noise-adapted quantum error correction
Quantum error correction (QEC) is an essential tool for quantum computing that enables reliable information processing in the presence of noise. Syndrome measurements play a central role in QEC, making it possible to unambiguously identify the location and type of errors. While syndrome extraction is natural for conventional QEC protocols, where the errors satisfy certain algebraic constraints \emph{perfectly}, this feature is largely missing in the framework of approximate or noise-adapted QEC…

Quantum computing startup Infleqtion agrees to merge with a Michael Klein-led blank-check company, giving it a $1.8B pre-money valuation and $540M in funding (Bloomberg)
https://www.bloomberg.com/news/articles/2025-09-08/klein…

Special Issue: Commemorating the 110th Anniversary of TANG Au-chin's Birthday Calculation of the Green's function on near-term quantum computers via Cartan decomposition
Lingyun Wan, Jie Liu, Jinlong Yang
https://arxiv.org/abs/2509.09248

Special Issue: Commemorating the 110th Anniversary of TANG Au-chin's Birthday Calculation of the Green's function on near-term quantum computers via Cartan decomposition
Accurate computation of the Green's function is crucial for connecting experimental observations to the underlying quantum states. A major challenge in evaluating the Green's function in the time domain lies in the efficient simulation of quantum state evolution under a given Hamiltonian-a task that becomes exponentially complex for strongly correlated systems on classical computers. Quantum computing provides a promising pathway to overcome this barrier by enabling efficient simulation of quan…

Spin quantum computing, spin quantum cognition
Betony Adams, Francesco Petruccione
https://arxiv.org/abs/2510.07196 https://arxiv.org/pdf/2510.07196…

Spin quantum computing, spin quantum cognition
Over two decades ago, Bruce Kane proposed that spin-half phosphorus nuclei embedded in a spin-zero silicon substrate could serve as a viable platform for spin-based quantum computing. These nuclear spins exhibit remarkably long coherence times, making them ideal candidates for qubits. Despite this advantage, practical realisation of spin quantum computing remains a challenge. More recently, physicist Matthew Fisher proposed a hypothesis linking nuclear spin dynamics, specifically those of phosp…

Michel Devoret, a Google Quantum AI chief scientist, John Martinis, who left Google in 2020, and John Clarke win the Nobel in Physics for quantum computing work (Bloomberg)
https://www.bloomberg.com/news/articles/2025-10-…

Caltech says it built the world's largest neutral-atom quantum computer, with 6,100 qubits, 13 second coherence, 10x longer than the past, and 99.98% accuracy (Jason Nelson/Decrypt)
https://decrypt.co/341716/caltech-builds-worlds-largest-neutral-atom…

Caltech Builds World’s Largest Neutral-Atom Quantum Computer
Researchers kept more than 6,000 qubits coherent while operating with 99.98% accuracy. Here's why that matters for quantum computing.

Interfacing Quantum Computing Systems with High-Performance Computing Systems: An Overview
Konstantinos Rallis, Ioannis Liliopoulos, Georgios D. Varsamis, Evangelos Tsipas, Ioannis G. Karafyllidis, Georgios Ch. Sirakoulis, Panagiotis Dimitrakis
https://arxiv.org/abs/2509.06205

Interfacing Quantum Computing Systems with High-Performance Computing Systems: An Overview
The connection and eventual integration of High-Performance Computing (HPC) with Quantum Computing (QC) represents a transformative advancement in computational technology, promising significant enhancements in solving complex, previously intractable problems. This manuscript provides a comprehensive overview of the current state of HPC-QC interfacing, detailing architectural methodologies, software stack developments, middleware functionalities, and hardware integration strategies. It critical…

A Pathway to Practical Quantum Advantage in Solving Navier-Stokes Equations
Xi-Ning Zhuang, Zhao-Yun Chen, Ming-Yang Tan, Jiaxuan Zhang, Chuang-Chao Ye, Tian-Hao Wei, Teng-Yang Ma, Cheng Xue, Huan-Yu Liu, Qing-Song Li, Tai-Ping Sun, Xiao-Fan Xu, Yun-Jie Wang, Yu-Chun Wu, Guo-Ping Guo
https://arxiv.org/abs/2509.08807

A Pathway to Practical Quantum Advantage in Solving Navier-Stokes Equations
The advent of fault-tolerant quantum computing (FTQC) promises to tackle classically intractable problems. A key milestone is solving the Navier-Stokes equations (NSE), which has remained formidable for quantum algorithms due to their high input-output overhead and nonlinearity. Here, we establish a full-stack framework that charts a practical pathway to a quantum advantage for large-scale NSE simulation. Our approach integrates a spectral-based input/output algorithm, an explicit and synthesiz…

From Physical to Logical: Graph-State-Based Connectivity in Quantum Networks
Mateo M. Blanco, Manuel Fern\'andez-Veiga, Ana Fern\'andez-Vilas, Rebeca P. D\'iaz-Redondo
https://arxiv.org/abs/2509.08384

From Physical to Logical: Graph-State-Based Connectivity in Quantum Networks
Entanglement is a key resource in quantum communication, but bipartite schemes are often insufficient for advanced protocols like quantum secret sharing or distributed computing. Graph states offer a flexible way to represent and manage multipartite entanglement in quantum networks, enabling logical connectivity through local operations and classical communication (LOCC). In this work, we extend existing approaches based on bi-star configurations to more complex multi-star topologies. We analyz…

Toronto-based quantum computing company Xanadu says it will go public in the US and Canada via a SPAC, in a deal that values the combined business at ~$3.6B (Josh Scott/BetaKit)
https://betakit.com/xanadu-to-go-public-on-nasdaq-and-tsx-in-3-6-billion-u…

Xanadu to go public on Nasdaq and TSX in $3.6-billion USD SPAC deal
Toronto-based quantum computing firm Xanadu has struck a deal to go public by merging with a SPAC called Crane Harbor Acquisition Corp.

Large-scale Efficient Molecule Geometry Optimization with Hybrid Quantum-Classical Computing
Yajie Hao, Qiming Ding, Xiaoting Wang, Xiao Yuan
https://arxiv.org/abs/2509.07460 ht…

Large-scale Efficient Molecule Geometry Optimization with Hybrid Quantum-Classical Computing
Accurately and efficiently predicting the equilibrium geometries of large molecules remains a central challenge in quantum computational chemistry, even with hybrid quantum-classical algorithms. Two major obstacles hinder progress: the large number of qubits required and the prohibitive cost of conventional nested optimization. In this work, we introduce a co-optimization framework that combines Density Matrix Embedding Theory (DMET) with Variational Quantum Eigensolver (VQE) to address these l…

Hybrid Sequential Quantum Computing
Pranav Chandarana, Sebasti\'an V. Romero, Alejandro Gomez Cadavid, Anton Simen, Enrique Solano, Narendra N. Hegade
https://arxiv.org/abs/2510.05851

Hybrid Sequential Quantum Computing
We introduce hybrid sequential quantum computing (HSQC), a paradigm for combinatorial optimization that systematically integrates classical and quantum methods within a structured, stage-wise workflow. HSQC may involve an arbitrary sequence of classical and quantum processes, as long as the global result outperforms the standalone components. Our testbed begins with classical optimizers to explore the solution landscape, followed by quantum optimization to refine candidate solutions, and conclu…

Behind the scenes of the Quantum Extreme Learning Machines
A. De Lorenzis, M. P. Casado, N. Lo Gullo, T. Lux, F. Plastina, A. Riera
https://arxiv.org/abs/2509.06873 https://

Behind the scenes of the Quantum Extreme Learning Machines
In recent years, Quantum Machine Learning (QML) has grown rapidly, emerging as a promising approach to make quantum computing implementation competitive. In this work, we investigate Quantum Extreme Learning Machines (QELM), a quantum variant of Extreme Learning Machines where training is restricted to the output layer. The proposed architecture combines dimensionality reduction (via PCA or Autoencoders), quantum state encoding, evolution under an XX Hamiltonian, and measurement, providing feat…

On the convergence of the variational quantum eigensolver and quantum optimal control
Marco Wiedmann, Daniel Burgarth, Gunther Dirr, Thomas Schulte-Herbr\"uggen, Emanuel Malvetti, Christian Arenz
https://arxiv.org/abs/2509.05295

On the convergence of the variational quantum eigensolver and quantum optimal control
When does a variational quantum algorithm converge to a globally optimal problem solution? Despite the large literature around variational approaches to quantum computing, the answer is largely unknown. We address this open question by developing a convergence theory for the variational quantum eigensolver (VQE). By leveraging the terminology of quantum control landscapes, we prove a sufficient criterion that characterizes when convergence to a ground state of a Hamiltonian can be guaranteed fo…

A Framework for Quantum Data Center Emulation Using Digital Quantum Computers
Seyed Navid Elyasi, Seyed Morteza Ahmadian, Paolo Monti, Jun Li, Rui Lin
https://arxiv.org/abs/2509.04029

A Framework for Quantum Data Center Emulation Using Digital Quantum Computers
As quantum computing hardware advances, the limitations of single-chip architectures, particularly in terms of small qubit count, have sparked growing interest in modular quantum computing systems and Quantum Data Centers (QDCs). These architectures interconnect multiple quantum processor units (QPUs) to overcome physical constraints and support complex quantum algorithms. However, the implementation of distributed quantum computing (DQC) faces significant technical challenges, especially in th…

Robustness of quantum algorithms: Worst-case fidelity bounds and implications for design
Julian Berberich, Tobias Fellner, Robert L. Kosut, Christian Holm
https://arxiv.org/abs/2509.08481

Robustness of quantum algorithms: Worst-case fidelity bounds and implications for design
Errors occurring on noisy hardware pose a key challenge to reliable quantum computing. Existing techniques such as error correction, mitigation, or suppression typically separate the error handling from the algorithm analysis and design. In this paper, we develop an alternative, algorithm-centered framework for understanding and improving the robustness against errors. For a given quantum algorithm and error model, we derive worst-case fidelity bounds which can be explicitly computed to certify…

Quantum Zeno effect versus adiabatic quantum computing and quantum annealing
Naser Ahmadiniaz, Dennis Kraft, Gernot Schaller, Ralf Sch\"utzhold
https://arxiv.org/abs/2509.04057

Quantum Zeno effect versus adiabatic quantum computing and quantum annealing
For the adiabatic version of Grover's quantum search algorithm as proposed by Roland and Cerf, we study the impact of decoherence caused by a rather general coupling to some environment. For quite generic conditions, we find that the quantum Zeno effect poses strong limitations on the performance (quantum speed-up) since the environment effectively measures the state of the system permanently and thereby inhibits or slows down quantum transitions. Generalizing our results, we find that analogou…

Scalable parallel simulation of quantum circuits on CPU and GPU systems
Guolong Zhong, Yi Fan, Zhenyu Li
https://arxiv.org/abs/2509.04955 https://arxiv.org…

Scalable parallel simulation of quantum circuits on CPU and GPU systems
Quantum computing enables parallelism through superposition and entanglement and offers advantages over classical computing architectures. However, due to the limitations of current quantum hardware in the noisy intermediate-scale quantum (NISQ) era, classical simulation remains a critical tool for developing quantum algorithms. In this research, we present a comprehensive parallelization solution for the Q$^2$Chemistry software package, delivering significant performance improvements for the f…

Anchor: Reducing Temporal and Spatial Output Performance Variability on Quantum Computers
Yuqian Huo, Daniel Leeds, Jason Ludmir, Nicholas S. DiBrita, Tirthak Patel
https://arxiv.org/abs/2510.06172

Anchor: Reducing Temporal and Spatial Output Performance Variability on Quantum Computers
Quantum computing, which has the power to accelerate many computing applications, is currently a technology under development. As a result, the existing noisy intermediate-scale quantum (NISQ) computers suffer from different hardware noise effects, which cause errors in the output of quantum programs. These errors cause a high degree of variability in the performance (i.e., output fidelity) of quantum programs, which varies from one computer to another and from one day to another. Consequently,…

From quantum feature maps to quantum reservoir computing: perspectives and applications
Casper Gyurik, Filip Wudarski, Evan Philip, Antonio Sannia, Hossein Sadeghi, Oleksandr Kyriienko, Davide Venturelli, Antonio A. Gentile
https://arxiv.org/abs/2510.01797

From quantum feature maps to quantum reservoir computing: perspectives and applications
We explore the interplay between two emerging paradigms: reservoir computing and quantum computing. We observe how quantum systems featuring beyond-classical correlations and vast computational spaces can serve as non-trivial, experimentally viable reservoirs for typical tasks in machine learning. With a focus on neutral atom quantum processing units, we describe and exemplify a novel quantum reservoir computing (QRC) workflow. We conclude exploratively discussing the main challenges ahead, whi…

QNPU: Quantum Network Processor Unit for Quantum Supercomputers
Peiyi Li, Chenxu Liu, Ji Liu, Huiyang Zhou, Ang Li
https://arxiv.org/abs/2509.02827 https://

QNPU: Quantum Network Processor Unit for Quantum Supercomputers
As quantum computing progresses, the need for scalable solutions to address large-scale computational problems has become critical. Quantum supercomputers are the next upcoming frontier by enabling multiple quantum processors to collaborate effectively to solve large-scale computational problems. The emergence of quantum supercomputers necessitates an efficient interface to manage the quantum communication protocols between quantum processors. In this paper, we propose the Quantum Network Proce…

Toward Quantum Enabled Solutions for Real-Time Currency Arbitrage in Financial Markets
Suman Kumar Roy, Rahul Rana, M Girish Chandra, Nishant Kumar, Manoj Nambiar
https://arxiv.org/abs/2509.09289

Toward Quantum Enabled Solutions for Real-Time Currency Arbitrage in Financial Markets
Currency arbitrage leverages price discrepancies in currency exchange rates across different currency pairs to gain risk-free profits. It involves multiple trading, where short-lived price discrepancies require real-time, high-speed processing of vast solution space, posing challenges for classical computing. In this work, we formulate an enhanced mathematical model for the currency arbitrage problem by adding simple cycle preservation constraints, which guarantee trading cycle validity and eli…

RobQFL: Robust Quantum Federated Learning in Adversarial Environment
Walid El Maouaki, Nouhaila Innan, Alberto Marchisio, Taoufik Said, Muhammad Shafique, Mohamed Bennai
https://arxiv.org/abs/2509.04914

RobQFL: Robust Quantum Federated Learning in Adversarial Environment
Quantum Federated Learning (QFL) merges privacy-preserving federation with quantum computing gains, yet its resilience to adversarial noise is unknown. We first show that QFL is as fragile as centralized quantum learning. We propose Robust Quantum Federated Learning (RobQFL), embedding adversarial training directly into the federated loop. RobQFL exposes tunable axes: client coverage $γ$ (0-100\%), perturbation scheduling (fixed-$\varepsilon$ vs $\varepsilon$-mixes), and optimization (fine-tun…

Improving fermionic variational quantum eigensolvers with Majorana swap networks
D. E. Fisher, S. A. Fldzhyan, D. V. Minaev, S. S. Straupe, M. Yu. Saygin
https://arxiv.org/abs/2509.07855

Improving fermionic variational quantum eigensolvers with Majorana swap networks
Simulating computationally hard fermionic systems is a promising application of quantum computing. However, mapping nonlocal fermionic operators to qubits often produces deep circuits, rendering such simulations impractical on near-term hardware. We introduce two Majorana swap network techniques for variational quantum eigensolvers that reduce circuit depth and two-qubit gate count, thereby limiting error accumulation. First, we develop a cyclic compilation algorithm that localizes all two-part…

Addressing requirements for crosstalk-free quantum-gate operation in many-body nanofiber cavity QED systems
Tim Keller, Seigo Kikura, Rui Asaoka, Yasunari Suzuki, Yuuki Tokunaga, Takao Aoki
https://arxiv.org/abs/2509.08408

Addressing requirements for crosstalk-free quantum-gate operation in many-body nanofiber cavity QED systems
A distributed network architecture in which flying photons connect individual modules containing stationary atomic qubits is a promising approach for scaling up neutral-atom based quantum-computing platforms. We consider an all-fiber based platform consisting of nanofiber cavity QED systems interconnected via conventional optical fibers. Each nanofiber cavity is strongly coupled to multiple atoms through its evanescent field, and atom pairs within one cavity (local) or two distant cavities (rem…

Microwave-to-Optical Quantum Transduction of Photons for Quantum Interconnects
Akihiko Sekine, Ryo Murakami, Yoshiyasu Doi
https://arxiv.org/abs/2509.26349 https://

Microwave-to-Optical Quantum Transduction of Photons for Quantum Interconnects
The quantum transduction, or equivalently quantum frequency conversion, is vital for the realization of, e.g., quantum networks, distributed quantum computing, and quantum repeaters. The microwave-to-optical quantum transduction is of particular interest in the field of superconducting quantum computing, since interconnecting dilution refrigerators is considered inevitable for realizing large-scale quantum computers with fault-tolerance. In this review, we overview recent theoretical and experi…

Loss-tolerant parallelized Bell-state generation with a hybrid cat qudit
Z. M. McIntyre, W. A. Coish
https://arxiv.org/abs/2509.08577 https://arxiv.org/pdf…

Loss-tolerant parallelized Bell-state generation with a hybrid cat qudit
Having multiple Bell pairs shared by distant quantum registers provides a key resource for both quantum networks and distributed quantum computing. In this paper, we present a protocol for parallelized Bell-pair generation that uses the phase of a coherent light pulse to encode a qudit, enabling the simultaneous generation of multiple Bell pairs. By encoding a qudit in a basis of light-matter Schrödinger's cat states, the loss of a photon in transit can be detected through an $XX$ parity syndr…

Quantum Reservoir Computing for Credit Card Default Prediction on a Neutral Atom Platform
Giacomo Vitali, Chiara Vercellino, Paolo Viviani, Olivier Terzo, Bartolomeo Montrucchio, Valeria Zaffaroni, Francesca Cibrario, Christian Mattia, Giacomo Ranieri, Alessandro Sabatino, Francesco Bonazzi, Davide Corbelletto
https://arxiv.org/abs/2510.04…

Quantum Reservoir Computing for Credit Card Default Prediction on a Neutral Atom Platform
In this paper, we define and benchmark a hybrid quantum-classical machine learning pipeline by performing a binary classification task applied to a real-world financial use case. Specifically, we implement a Quantum Reservoir Computing (QRC) layer within a classical routine that includes data preprocessing and binary classification. The reservoir layer has been executed on QuEra's Aquila, a 256-qubit neutral atom simulator, using two different types of encoding: position and local detuning. In …

Plugging Leaks in Fault-Tolerant Quantum Computation and Verification
Theodoros Kapourniotis, Dominik Leichtle, Luka Music, Harold Ollivier
https://arxiv.org/abs/2510.03227 http…

Plugging Leaks in Fault-Tolerant Quantum Computation and Verification
With the advent of quantum cloud computing, the security of delegated quantum computation has become of utmost importance. While multiple statistically secure blind verification schemes in the prepare-and-send model have been proposed, none of them achieves full quantum fault-tolerance, a prerequisite for useful verification on scalable quantum computers. In this paper, we present the first fault-tolerant blind verification scheme for universal quantum computations able to handle secret-depende…

Quantum Relative Entropy Decay Composition Yields Shallow, Unstructured k-Designs
Nicholas Laracuente
https://arxiv.org/abs/2510.08537 https://arxiv.org/pd…

Quantum Relative Entropy Decay Composition Yields Shallow, Unstructured k-Designs
A major line of questions in quantum information and computing asks how quickly locally random circuits converge to resemble global randomness. In particular, approximate k-designs are random unitary ensembles that resemble random circuits up to their first k moments. It was recently shown that on n qudits, random circuits with slightly structured architectures converge to k-designs in depth O(log n), even on one-dimensional connectivity. It has however remained open whether the same shallow de…

Platform-Agnostic Modular Architecture for Quantum Benchmarking
Neer Patel, Anish Giri, Hrushikesh Pramod Patil, Noah Siekierski, Avimita Chatterjee, Sonika Johri, Timothy Proctor, Thomas Lubinski, Siyuan Niu
https://arxiv.org/abs/2510.08469

Platform-Agnostic Modular Architecture for Quantum Benchmarking
We present a platform-agnostic modular architecture that addresses the increasingly fragmented landscape of quantum computing benchmarking by decoupling problem generation, circuit execution, and results analysis into independent, interoperable components. Supporting over 20 benchmark variants ranging from simple algorithmic tests like Bernstein-Vazirani to complex Hamiltonian simulation with observable calculations, the system integrates with multiple circuit generation APIs (Qiskit, CUDA-Q, C…

HPQEA: A Scalable and High-Performance Quantum Emulator with High-Bandwidth Memory for Diverse Algorithms Support
Tran Van Duy, Tuan Hai Vu, Vu Trung Duong Le, Hoai Luan Pham, Yasuhiko Nakashima
https://arxiv.org/abs/2510.07110

HPQEA: A Scalable and High-Performance Quantum Emulator with High-Bandwidth Memory for Diverse Algorithms Support
In recent years, there has been a growing interest in the development of quantum emulation. However, existing studies often struggle to achieve broad applicability, high performance, and efficient resource and memory utilization. To address these challenges, we provide HPQEA, a quantum emulator based on the state-vector emulation approach. HPQEA includes three main features: a high-performance computing core, an optimized controlled-NOT gate computation strategy, and effective utilization of hi…

LATTE: A Decoding Architecture for Quantum Computing with Temporal and Spatial Scalability
Kai Zhang, Jubo Xu, Fang Zhang, Linghang Kong, Zhengfeng Ji, Jianxin Chen
https://arxiv.org/abs/2509.03954

LATTE: A Decoding Architecture for Quantum Computing with Temporal and Spatial Scalability
Quantum error correction allows inherently noisy quantum devices to emulate an ideal quantum computer with reasonable resource overhead. As a crucial component, decoding architectures have received significant attention recently. In this paper, we introduce LATTE, a FPGA-CPU hybrid decoding architecture aiming to address the key requirements of scaling up in lattice surgery quantum computation -- Latency, Accuracy, Throughput and Transmission Bandwidth, in an Eclectic manner. LATTE follows a hi…

MAQCY: Modular Atom-Array Quantum Computing with Space-Time Hybrid Multiplexing
Andrew Byun, Chanseul Lee, Eunsik Yoon, Minhyuk KimMinhyuk Kim, Tai Hyun Yoon
https://arxiv.org/abs/2510.02940

MAQCY: Modular Atom-Array Quantum Computing with Space-Time Hybrid Multiplexing
We present a modular atom-array quantum computing architecture with space-time hybrid multiplexing (MAQCY), a dynamic optical tweezer-based protocol for fully connected and scalable universal quantum computation. By extending the concept of globally controlled static dual-species Rydberg atom wires [1], we develop an entirely new approach using Q-Pairs, which consist of globally controlled and temporally multiplexed dual-species Rydberg blockaded atom and superatom pairs. Space-time hybrid mult…

Dynamic LOCC Circuits for Automated Entanglement Manipulation
Xia Liu, Jiayi Zhao, Benchi Zhao, Xin Wang
https://arxiv.org/abs/2509.07841 https://arxiv.org…

Dynamic LOCC Circuits for Automated Entanglement Manipulation
Due to the limited qubit number of quantum devices, distributed quantum computing is considered a promising pathway to overcome this constraint. In this paradigm, multiple quantum processors are interconnected to form a cohesive computational network, and the most natural set of free operations is local operations and classical communication (LOCC). However, designing a practical LOCC protocol for a particular task has been a tough problem. In this work, we propose a general and flexible framew…

Forecasting Low-Dimensional Turbulence via Multi-Dimensional Hybrid Quantum Reservoir Computing
L. Salatino, L. Mariani, A. Giordano, F. D'Amore, C. Mastroianni, L. Pontieri, A. Vinci, C. Gencarelli, L. Primavera, F. Plastina, J. Settino, F. Carbone
https://arxiv.org/abs/2509.04006

Forecasting Low-Dimensional Turbulence via Multi-Dimensional Hybrid Quantum Reservoir Computing
The prediction of complex dynamics remains an open problem across many domains of physics, where nonlinearities and multiscale interactions severely limit the reliability of conventional forecasting methods. Quantum reservoir computing (QRC) has emerged as a promising paradigm for information processing by exploiting the high dimensionality of the Hilbert space, where the dynamics of quantum systems take place. Here, we introduce a hybrid quantum-classical reservoir architecture capable of hand…

Photonic Hybrid Quantum Computing
Jaehak Lee, Srikrishna Omkar, Yong Siah Teo, Seok-Hyung Lee, Hyukjoon Kwon, M. S. Kim, Hyunseok Jeong
https://arxiv.org/abs/2510.00534 https://…

Photonic Hybrid Quantum Computing
Photons are a ubiquitous carrier of quantum information: they are fast, suffer minimal decoherence, and do not require huge cryogenic facilities. Nevertheless, their intrinsically weak photon-photon interactions remain a key obstacle to scalable quantum computing. This review surveys hybrid photonic quantum computing, which exploits multiple photonic degrees of freedom to combine the complementary strengths of discrete and bosonic encodings, thereby significantly mitigating the challenge of wea…

Quantum-Enhanced Natural Language Generation: A Multi-Model Framework with Hybrid Quantum-Classical Architectures
Chi-Sheng Chen, En-Jui Kuo
https://arxiv.org/abs/2508.21332 htt…

Quantum-Enhanced Natural Language Generation: A Multi-Model Framework with Hybrid Quantum-Classical Architectures
This paper presents a comprehensive evaluation of quantum text generation models against traditional Transformer/MLP architectures, addressing the growing interest in quantum computing applications for natural language processing. We conduct systematic experiments comparing five distinct models: Transformer (baseline), Quantum Kernel Self-Attention Network (QKSAN), Quantum RWKV (QRWKV), and Quantum Attention Sequence Architecture (QASA) across five diverse datasets including simple sentences, s…

Reproducible Builds for Quantum Computing
Iy\'an M\'endez Veiga, Esther H\"anggi
https://arxiv.org/abs/2510.02251 https://arxiv.org/pdf/2510.0…

Reproducible Builds for Quantum Computing
Reproducible builds are a set of software development practices that establish an independently verifiable path from source code to binary artifacts, helping to detect and mitigate certain classes of supply chain attacks. Although quantum computing is a rapidly evolving field of research, it can already benefit from adopting reproducible builds. This paper aims to bridge the gap between the quantum computing and reproducible builds communities. We propose a generalization of the definition of r…

Evidence of Compact Wavefunctions from Quantum-Selected Configuration Interaction
Tim Weaving, Angus Mingare, Alexis Ralli, Peter V. Coveney
https://arxiv.org/abs/2509.02525 htt…

Evidence of Compact Wavefunctions from Quantum-Selected Configuration Interaction
A recent direction in quantum computing for molecular electronic structure sees the use of quantum devices as configuration sampling machines integrated within high-performance computing (HPC) platforms. This appeals to the strengths of both the quantum and classical hardware; where state-sampling is classically hard, the quantum computer can provide computational advantage in the selection of high quality configuration subspaces, while the final molecular energies are evaluated by solving an i…

Quantum Machine Learning for Optimizing Entanglement Distribution in Quantum Sensor Circuits
Laxmisha Ashok Attisara, Sathish Kumar
https://arxiv.org/abs/2508.21252 https://

Quantum Machine Learning for Optimizing Entanglement Distribution in Quantum Sensor Circuits
In the rapidly evolving field of quantum computing, optimizing quantum circuits for specific tasks is crucial for enhancing performance and efficiency. More recently, quantum sensing has become a distinct and rapidly growing branch of research within the area of quantum science and technology. The field is expected to provide new opportunities, especially regarding high sensitivity and precision. Entanglement is one of the key factors in achieving high sensitivity and measurement precision [3].…

Quantum Leap in Finance: Economic Advantages, Security, and Post-Quantum Readiness
Gerhard Hellstern, Esra Yeniaras
https://arxiv.org/abs/2508.21548 https://

Quantum Leap in Finance: Economic Advantages, Security, and Post-Quantum Readiness
This paper provides an in-depth review of the evolving role of quantum computing in the financial sector, emphasizing both its computational potential and cybersecurity implications. Distinguishing itself from existing surveys, this work integrates classical quantum computing applications - such as portfolio optimization, risk analysis, derivative pricing, and Monte Carlo simulations with a thorough examination of blockchain technologies and post-quantum cryptography (PQC), which are crucial fo…

Digital quantum simulation of many-body systems: Making the most of intermediate-scale, noisy quantum computers
Alexander Miessen
https://arxiv.org/abs/2508.21504 https://

Digital quantum simulation of many-body systems: Making the most of intermediate-scale, noisy quantum computers
Quantum mechanical problems are among the hardest to simulate and, in some cases, remain intractable even for the most powerful computers. Quantum computing has emerged as a new technological platform to address such challenges, with rapid advances in recent years. Yet, current quantum devices remain noisy and limited in scale. Hence, it is essential to identify classically hard problems of practical interest and tractable with existing quantum devices. Among potential applications, the real-ti…

Near-Term Quantum-Computing-Inspired Sampling for Community Detection in Low-Modularity Graphs
Joseph Geraci, Luca Pani
https://arxiv.org/abs/2509.03864 https://

Near-Term Quantum-Computing-Inspired Sampling for Community Detection in Low-Modularity Graphs
Low modularity networks (Q < 0.2) challenge classical community detection algorithms, which get trapped in local optima. We introduce quantum inspired community detection algorithms leveraging non classical sampling techniques to escape modularity optimization plateaus. Using distributions inspired by quantum phenomena including Porter Thomas distributions, Haar random states, and hyperuniform point processes, our approach generates diverse high quality partitions that improve modularity on dif…

Magic and communication complexity
Uma Girish, Alex May, Natalie Parham, Henry Yuen
https://arxiv.org/abs/2510.07246 https://arxiv.org/pdf/2510.07246

Magic and communication complexity
We establish novel connections between magic in quantum circuits and communication complexity. In particular, we show that functions computable with low magic have low communication cost. Our first result shows that the $\mathsf{D}\|$ (deterministic simultaneous message passing) cost of a Boolean function $f$ is at most the number of single-qubit magic gates in a quantum circuit computing $f$ with any quantum advice state. If we allow mid-circuit measurements and adaptive circuits, we ob…

Anticoherent $k$-planes and coding techniques for a 3-qubit scheme of universal quantum computing
L. Arag\'on-Mu\~noz, C. Chryssomalakos, A. G. Flores-Delgado, V. Rasc\'on-Barajas, I. V\'azquez Mota
https://arxiv.org/abs/2509.23464

Anticoherent $k$-planes and coding techniques for a 3-qubit scheme of universal quantum computing
Toponomic quantum computing (TQC) employs rotation sequences of anticoherent $k$-planes to construct noise-tolerant quantum gates. In this work, we demonstrate the implementation of generalized Toffoli gates, using $k$-planes of spin systems with $s \geq k + 1$, and of the Hadamard gate for a 3-qubit system, using a spin $s \!= \! 15$ 8-plane. We propose a universal quantum computing scheme for 3-qubit systems (via Hadamard + Toffoli gates) based on coding techniques. A key advantage of this co…

Efficient quantum state tomography with Chebyshev polynomials
Hao Su, Shiying Xiong, Yue Yang
https://arxiv.org/abs/2509.02112 https://arxiv.org/pdf/2509.0…

Efficient quantum state tomography with Chebyshev polynomials
Quantum computing shows promise for addressing computationally intensive problems but is constrained by the exponential resource requirements of general quantum state tomography (QST), which fully characterizes quantum states through parameter estimation. We introduce the QST with Chebyshev polynomials, an approximate tomography method for pure quantum states encoding complex-valued functions. This method reformulates tomography as the estimation of Chebyshev expansion coefficients, expressed a…

Do Qubit States have to be non-degenerate two-level systems?
Zhuoran Bao, Daniel F. V. James
https://arxiv.org/abs/2510.04880 https://arxiv.org/pdf/2510.04…

Do Qubit States have to be non-degenerate two-level systems?
A qubit, or quantum bit, is conventionally defined as "a physical system for storing information that is capable of existing in either of two quantum states or in a superposition of both". In this paper, we examine the simple question of whether two distinct levels, each consisting of multiply degenerate sub-states, could serve as a practical quantum bit. We explore this idea using a well-characterized atomic system of the kind employed in several quantum computing implementations. We approxima…

Computation of the Smooth Max-Mutual Information via Semidefinite Programming
Christopher Popp, Tobias C. Sutter, Beatrix C. Hiesmayr
https://arxiv.org/abs/2509.07743 https://…

Computation of the Smooth Max-Mutual Information via Semidefinite Programming
We present an iterative algorithm based on semidefinite programming (SDP) for computing the quantum smooth max-mutual information $I^\varepsilon_{\max}(ρ_{AB})$ of bipartite quantum states in any dimension. The algorithm is accurate if a rank condition for marginal states within the smoothing environment is satisfied and provides an upper bound otherwise. Central to our method is a novel SDP, for which we establish primal and dual formulations and prove strong duality. With the direct applicat…