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Daily Quantum Computing Research & News • March 30, 2026 • 04:31 CST

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📊 Today's Data Collection

Highlights: 5 top items selected
News items: 10 articles gathered
Technology papers: 10 papers fetched
Company papers: 8 papers from major players
Highlighted papers: 5 papers collected
Total sources: 6 data feeds processed

🌟 Highlights

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⭐ TOP PAPER

Automated near-term quantum algorithm discovery for molecular ground states

Fabian Finger, Frederic Rapp, Pranav Kalidindi, Kerry He, Kante Yin, Alexander Koziell-Pipe, David Zsolt Manrique, Gabriel Greene-Diniz, Stephen Clark, Hamza Fawzi, Bernardino Romera Paredes, Alhussein Fawzi, Konstantinos Meichanetzidis • 2026-03-27T12:37 Score: 0.55
Designing quantum algorithms is a complex and counterintuitive task, making it an ideal candidate for AI-driven algorithm discovery. To this end, we employ the Hive, an AI platform for program synthes...

📰 News Items

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📄 Technology Papers

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Kardashev scale Quantum Computing for Bitcoin Mining

Pierre-Luc Dallaire-Demers, BTQ Technologies Team • Published: 2026-03-26
Bitcoin already faces a quantum threat through Shor attacks on elliptic-curve signatures. This paper isolates the other component that public discussion often conflates with it: mining. Grover's algorithm halves the exponent of brute-force search, promising a quadratic edge to any quantum miner of Bitcoin. Exactly how large that edge grows depends on fault-tolerant hardware. No prior study has cos...

Unifying communication paradigms in measurement-based delegated quantum computing

Fabian Wiesner, Jens Eisert, Anna Pappa • Published: 2025-06-27
Delegated quantum computing (DQC) allows clients with low quantum capabilities to outsource computations to a server hosting a quantum computer. This process is often envisioned within the measurement-based quantum computing framework, as it naturally facilitates blindness of inputs and computation. Hence, the overall process of setting up and conducting the computation encompasses a sequence of t...

Scalable topological quantum computing based on Sine-Cosine chain models

A. Lykholat, G. F. Moreira, I. R. Martins, D. Sousa, A. M. Marques, R. G. Dias • Published: 2026-03-26
This work proposes a scalable framework for topological quantum computing using Matryoshka-type Sine-Cosine chains. These chains support high-dimensional qudit encoding within single systems, reducing the physical resource overhead compared to conventional qubit arrays. We describe how these chains can be used in Y-junction braiding protocols for gate operations and in extended memory architecture...

A unified quantum computing quantum Monte Carlo framework through structured state preparation

Giuseppe Buonaiuto, Antonio Marquez Romero, Brian Coyle, Annie E. Paine, Vicente P. Soloviev, Stefano Scali, Michal Krompiec • Published: 2026-03-26
We extend Quantum Computing Quantum Monte Carlo (QCQMC) beyond ground-state energy estimation by systematically constructing the quantum circuits used for state preparation. Replacing the original Variational Quantum Eigensolver (VQE) prescription with task-adapted unitaries, we show that QCQMC can address excited-state spectra via Variational Fast Forwarding and the Variational Unitary Matrix Pro...

Noise-resilient Universal Quantum Computing in the Presence of Anisotropic Noise

Yang-Yang Xie, Zhao-Ming Wang, Lian-Ao Wu • Published: 2025-08-06
We propose a universal gate set for quantum computing that operates in the presence of decoherence without the overhead of active error correction. We show that a broad class of anisotropic system--bath couplings can be effectively decoupled by preparing an appropriate system--bath entangled initial state. The initially established entanglement serves as a resource to cancel out the dominant decoh...

Uncertainty Quantification for Quantum Computing

Ryan Bennink, Olena Burkovska, Konstantin Pieper, Jorge Ramirez, Elaine Wong • Published: 2026-03-26
This review is designed to introduce mathematicians and computational scientists to quantum computing (QC) through the lens of uncertainty quantification (UQ) by presenting a mathematically rigorous and accessible narrative for understanding how noise and intrinsic randomness shape quantum computational outcomes in the language of mathematics. By grounding quantum computation in statistical infere...

Spectral methods: crucial for machine learning, natural for quantum computers?

Vasilis Belis, Joseph Bowles, Rishabh Gupta, Evan Peters, Maria Schuld • Published: 2026-03-25
This article presents an argument for why quantum computers could unlock new methods for machine learning. We argue that spectral methods, in particular those that learn, regularise, or otherwise manipulate the Fourier spectrum of a machine learning model, are often natural for quantum computers. For example, if a generative machine learning model is represented by a quantum state, the Quantum Fou...

Thermalization of SU(2) Lattice Gauge Fields on Quantum Computers

Jiunn-Wei Chen, Yu-Ting Chen, Ghanashyam Meher, Berndt Müller, Andreas Schäfer, Xiaojun Yao • Published: 2026-03-25
We simulate the thermalization dynamics for minimally truncated SU(2) pure gauge theory on linear plaquette chains with up to 151 plaquettes using IBM quantum computers. We study the time dependence of the entanglement spectrum, Rényi-2 entropy and anti-flatness on small subsystems. The quantum hardware results obtained after error mitigation agree with extrapolated classical simulator results for...

Quantum Computing and Error Mitigation with Deep Learning for Frenkel Excitons

Yi-Ting Lee, Vijaya Begum-Hudde, Barbara A. Jones, André Schleife • Published: 2026-03-25
Quantum computers, currently in the noisy intermediate-scale quantum (NISQ) era, have started to provide scientists with a novel tool to explore quantum physics and chemistry. While several electronic systems have been extensively studied, Frenkel excitons, as prototypical optical excitations, remain among the less-explored applications. Here, we first use variational quantum deflation to calculat...

Toward scalable quantum computations of atomic nuclei

Chenyi Gu, Matthias Heinz, Oriel Kiss, Thomas Papenbrock • Published: 2025-07-19
We solve the nuclear two-body and three-body bound states via quantum simulations of pionless effective field theory on a lattice in position space. While the employed lattice remains small, the usage of local Hamiltonians including two- and three-body forces ensures that the number of Pauli terms scales linearly with increasing numbers of lattice sites. We use an adaptive ansatz grown from unitar...

🏢 Company Papers

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Broadband Magnetless Isolation in a Flux-Pumped, Dispersion-Engineered Transmission Line

M. Demarets, A. M. Vadiraj, C. Caloz, K. De Greve • Published: 2025-09-29
Isolators are commonly found in the amplification chain of microwave setups to shield sensitive devices such as superconducting qubits from noise and back-scattered signals. Conventional ferrite-based isolators are bulky, lossy and rely on strong magnetic fields, which pose challenges for their co-integration in large-scale superconducting devices. Although several magnetless approaches based on p...

Scene Grounding In the Wild

Tamir Cohen, Leo Segre, Shay Shomer-Chai, Shai Avidan, Hadar Averbuch-Elor • Published: 2026-03-27
Reconstructing accurate 3D models of large-scale real-world scenes from unstructured, in-the-wild imagery remains a core challenge in computer vision, especially when the input views have little or no overlap. In such cases, existing reconstruction pipelines often produce multiple disconnected partial reconstructions or erroneously merge non-overlapping regions into overlapping geometry. In this w...

CryptOracle: A Modular Framework to Characterize Fully Homomorphic Encryption

Cory Brynds, Parker McLeod, Lauren Caccamise, Asmita Pal, Dewan Saiham, Sazadur Rahman, Joshua San Miguel, Di Wu • Published: 2025-10-03
Privacy-preserving machine learning has become an important long-term pursuit in this era of artificial intelligence (AI). Fully Homomorphic Encryption (FHE) is a uniquely promising solution, offering provable privacy and security guarantees. Unfortunately, computational cost is impeding its mass adoption. Modern solutions are up to six orders of magnitude slower than plaintext execution. Understa...

SPECTRA: An Efficient Spectral-Informed Neural Network for Sensor-Based Activity Recognition

Deepika Gurung, Lala Shakti Swarup Ray, Mengxi Liu, Bo Zhou, Paul Lukowicz • Published: 2026-03-27
Real time sensor based applications in pervasive computing require edge deployable models to ensure low latency privacy and efficient interaction. A prime example is sensor based human activity recognition where models must balance accuracy with stringent resource constraints. Yet many deep learning approaches treat temporal sensor signals as black box sequences overlooking spectral temporal struc...

Automated near-term quantum algorithm discovery for molecular ground states

Fabian Finger, Frederic Rapp, Pranav Kalidindi, Kerry He, Kante Yin, Alexander Koziell-Pipe, David Zsolt Manrique, Gabriel Greene-Diniz, Stephen Clark, Hamza Fawzi, Bernardino Romera Paredes, Alhussein Fawzi, Konstantinos Meichanetzidis • Published: 2026-03-27
Designing quantum algorithms is a complex and counterintuitive task, making it an ideal candidate for AI-driven algorithm discovery. To this end, we employ the Hive, an AI platform for program synthesis, which utilises large language models to drive a highly distributed evolutionary process for discovering new algorithms. We focus on the ground state problem in quantum chemistry, and discover effi...

Flag at origin: a modular fault-tolerant preparation for CSS codes

Diego Forlivesi, David Amaro • Published: 2025-08-19
Fault-tolerant (FT) preparation of diverse logical stabilizer states in quantum error-correcting (QEC) codes is essential for FT computation. Existing constructions of these FT circuits are often constrained by classical computational resources or result in unnecessarily large quantum circuits. This work introduces a modular construction for FT preparation circuits in CSS codes of arbitrary distan...

Quantum-enhanced Markov Chain Monte Carlo for Combinatorial Optimization

Kate V. Marshall, Daniel J. Egger, Michael Garn, Francesca Schiavello, Sebastian Brandhofer, Christa Zoufal, Stefan Woerner • Published: 2026-02-05
Quantum computing offers an alternative paradigm for addressing combinatorial optimization problems compared to classical computing. Despite recent hardware improvements, the execution of empirical quantum optimization experiments at scales known to be hard for state-of-the-art classical solvers is not yet in reach. In this work, we offer a different way to approach combinatorial optimization with...

TurboESM: Ultra-Efficient 3-Bit KV Cache Quantization for Protein Language Models with Orthogonal Rotation and QJL Correction

Yue Hu, Junqing Wang, Yingchao Liu • Published: 2026-03-27
The rapid scaling of Protein Language Models (PLMs) has unlocked unprecedented accuracy in protein structure prediction and design, but the quadratic memory growth of the Key-Value (KV) cache during inference remains a prohibitive barrier for single-GPU deployment and high-throughput generation. While 8-bit quantization is now standard, 3-bit quantization remains elusive due to severe numerical ou...

📚 Highlighted Papers

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Quantum enhanced Monte Carlo simulation for photon interaction cross sections

Authors: Euimin Lee, Sangmin Lee, Shiho Kim • Submitted: Submitted • arXiv: arXiv:2502.14374
Abstract: …as the dominant attenuation mechanism, we demonstrate that our approach reproduces classical probability distributions with high fidelity. Simulation results obtained via the IBM Qiskit quantum simulator reveal a quadratic speedup in amplitude estimation compared to conventional Monte C...

Time-adaptive single-shot crosstalk detector on superconducting quantum computer

Authors: Haiyue Kang, Benjamin Harper, Muhammad Usman, Martin Sevior • Submitted: Submitted • arXiv: arXiv:2502.14225
Abstract: …in two scenarios: simulation using an artificial noise model with gate-induced crosstalk and always-on idlings channels; and the simulation using noise sampled from an IBM quantum computer parametrised by the reduced HSA error model. The presented results show our method's efficacy hing...

Quantum simulation of a qubit with non-Hermitian Hamiltonian

Authors: Anastashia Jebraeilli, Michael R. Geller • Submitted: Submitted • arXiv: arXiv:2502.13910
Abstract: …-broken regime surrounding an exceptional point. Quantum simulations are carried out using IBM superconducting qubits. The results underscore the potential for variational quantum circuits and machine learning to push the boundaries of quantum simulation, offering new methods for explor...

Comment on "Energy-speed relationship of quantum particles challenges Bohmian mechanics"

Aurélien Drezet, Dustin Lazarovici, Bernard Michael Nabet
In their recent paper [Nature 643, 67 (2025)], Sharaglazova et al. report an optical microcavity experiment yielding an "energy-speed relationship" for quantum particles in evanescent states, which they infer from the observed population transfer between two coupled waveguides. The authors argue tha...