Quantum News
Sign InSign Up
Home/Quantum Technology/Quantum Computing Drug Discovery: Pharma Applications & Molecular Simulation

Quantum Computing Drug Discovery: Pharma Applications & Molecular Simulation

Quantum computing drug discovery news: pharmaceutical quantum simulation, molecular modeling, protein folding. Roche, Merck & biotech partnerships.

2,410 Articles
Updated Daily

Quantum computing promises to transform pharmaceutical research by enabling first-principles molecular simulation of drug-target interactions, protein folding dynamics, and chemical reaction mechanisms that classical computers cannot accurately model. The pharmaceutical industry represents one of the highest-value near-term markets for quantum computing.

The Classical Bottleneck

Drug discovery relies heavily on molecular dynamics simulations and density functional theory (DFT) to predict how small-molecule drug candidates bind to protein targets. Classical computers cannot simulate strongly correlated electronic systems without exponential approximation errors, forcing reliance on expensive, time-consuming laboratory screening.

India's Pharmaceutical Quantum Computing Landscape

India's pharmaceutical industry, the world's third-largest by volume and a major global supplier of generic drugs, represents a strategic application domain for quantum computing under the National Quantum Mission. The NQM's Quantum Computing Thematic Hub at IISc Bengaluru includes drug discovery and molecular simulation among priority applications. Indian pharmaceutical companies including Sun Pharma, Dr. Reddy's Laboratories, Cipla, and Lupin are exploring quantum computing partnerships through collaborations with Indian quantum startups and global quantum cloud providers. The Department of Biotechnology (DBT) supports quantum biology research at institutions including IISc Bengaluru, TIFR Mumbai, and IISER Pune. The NQM targets developing quantum computers capable of simulating molecular systems relevant to drug discovery within the mission's 8-year timeline.

Near-Term Applications (NISQ Era)

Near-term applications in the NISQ era include quantum machine learning for molecular property prediction, quantum optimization of clinical trial design, quantum simulation of small molecules (10-50 atoms) for lead optimization, and hybrid approaches integrating quantum and classical molecular dynamics.

Designing robust molecular spins for quantum technologies with theoretical chemistryquantum-computing

Designing robust molecular spins for quantum technologies with theoretical chemistry

--> Quantum Physics arXiv:2608.13744 (quant-ph) [Submitted on 13 Aug 2026] Title:Designing robust molecular spins for quantum technologies with theoretical chemistry Authors:Timothy J. Krogmeier, Pranay Venkatesh, Mikayla Z. Fahrenbruch, Anthony W. Schlimgen, Andres Montoya-Castillo, Kade Head-Marsden View a PDF of the paper titled Designing robust molecular spins for quantum technologies with theoretical chemistry, by Timothy J. Krogmeier and 5 other authors View PDF HTML (experimental) Abstract:Molecular spins represent a versatile platform for quantum information science, with the potential to offer chemically tunable, addressable qubits. However, achieving this requires understanding and mitigating quantum decoherence. This Chapter provides a theoretical overview of current state-of-the-art chemical theory connecting ab initio electronic structure with open quantum system dynamics to guide the rational design of long-lived molecular qubits. Beginning at the electronic level, multi-reference and relativistic electronic structure methods to parameterize effective spin Hamiltonians are discussed, with a primary focus on accurately capturing $g$-tensors, zero-field splitting, and hyperfine interactions. These parameters feed into models of spin-phonon and spin-spin coupling to quantify $T_1$ and $T_2$ relaxation across various environmental regimes. This Chapter evaluates a hierarchy of dynamical methods, ranging from factorization to matrix product state approaches, balancing computational cost against accuracy and generalizability. Ultimately, mapping these theoretical models to molecular architecture can establish design principles, such as isotopic substitution and spatial spin delocalization, to understand and extend coherence lifetimes. Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2608.13744 [quant-ph]   (or arXiv:2608.13744v1 [quant-ph] for this version)   https://doi.org/10.48550/arXiv.2608.13744 Focus to learn more arXiv-issued DOI via Data

arXiv Quantum PhysicsLoading...0
Who’s News: Strategic Appointments at PsiQuantum, EigenQ, Qunova Computing, and Optica Quantumquantum-computing

Who’s News: Strategic Appointments at PsiQuantum, EigenQ, Qunova Computing, and Optica Quantum

Who’s News: Strategic Appointments at PsiQuantum, EigenQ, Qunova Computing, and Optica Quantum PsiQuantum has appointed Niklas Zennström to its Board of Directors, effective August 11, 2026. Zennström is the Founder and CEO of Atomico and co-founder of Skype. He succeeds Siraj Khaliq as Atomico’s representative on the board, following recent executive additions including Victor Peng as CEO, Rob Soderbery as Executive Vice President, and Sriram Sitaraman as Chief Information Officer. The appointment coincides with PsiQuantum’s ongoing construction of fault-tolerant quantum computing facilities in Chicago and Brisbane. The full official release is available here. EigenQ, Inc. has appointed Mark Pecen as Vice Chairman and promoted Alexander Truskovsky to the newly created role of Chief Information Security Officer (CISO). Pecen, who previously served as a board member and strategic advisor, co-founded the Quantum-Safe Cryptography Working Group at ETSI. Truskovsky previously served as Vice President of Cryptography and will now oversee EigenQ’s global cybersecurity strategy, risk management, and product compliance as the company prepares for its proposed merger with Silicon Valley Acquisition Corp. (Nasdaq: SVAQ). The complete announcement can be found here. Qunova Computing has expanded its executive leadership with the appointments of Jake Hwang as Chief Financial Officer (CFO) and Board Member, along with Evan Kang and Woomin Kyoung as Business Development Executives. Hwang previously served as Chief Strategy Officer and Chief Business Officer at Nearthlab. Kang brings over 20 years of pharmaceutical R&D and business experience from SK Chemicals and LG Chem, while Kyoung joins with nearly three decades of engineering experience from Hyundai Motor Company’s R&D Division to lead materials simulation and CFD initiatives. The news release details are available here. Optica Publishing Group has appointed Kartik Srinivasan as the new Editor-in-Chief of Optica Quan

Quantum Computing ReportLoading...0
Columbia hosted a workshop to connect quantum research with industryquantum-computing

Columbia hosted a workshop to connect quantum research with industry

Columbia University hosted its first Quantum Industry and Investor Workshop on August 10, indicating a new effort to translate a century of quantum research into practical applications. The event brought together industry leaders and 37 Columbia faculty members comprising the Columbia Quantum Initiative, experts in areas from quantum materials to networking. “These discussions are critical, especially now,” said Sharon Sputz, associate vice president of research initiatives and development at Columbia Research, emphasizing the need to combine university innovation with industry to advance quantum technologies. Participants explored collaborations focused on quantum networking, security, and sensing, and plans for continued conversations are already underway. Columbia Quantum Initiative Showcases Research & Industry Alignment Columbia University’s Quantum Initiative comprises 37 faculty members, a broad internal base of expertise spanning quantum materials, photonics, computing, networking, and sensing. The event was not simply a presentation of findings; it signaled a proactive effort to forge partnerships crucial for advancing the field, according to university leaders. Attendees explored potential collaborations focused on quantum networking, security protocols, and advanced sensing technologies, areas where current classical systems are reaching their limits. Roundtable discussions centered on practical implementation, including shared laboratory models and streamlined technology transfer processes, reflecting a focus on overcoming hurdles to market entry. Participants also voiced interest in post-quantum cryptography, a critical area for safeguarding data against future quantum-powered attacks. “This workshop was a phenomenal opportunity to receive input from industry leaders that will help shape Columbia’s quantum research projects, inform our quantum education priorities, and expedite the development and adoption of new quantum technologies for real-world

Quantum ZeitgeistLoading...0
Fraunhofer IAF review pushes for more robust quantum algorithm benchmarksquantum-computing

Fraunhofer IAF review pushes for more robust quantum algorithm benchmarks

The Fraunhofer Institute for Applied Solid State Physics IAF has published two papers challenging how quantum advantage is measured, suggesting current methods lack sufficient rigor. Researchers are pushing for more realistic benchmarks in quantum chemistry by questioning the common practice of modeling molecules as perfectly isolated systems. These idealized approaches, they argue, don’t reflect natural conditions where molecules constantly interact with their environment; a shift is needed to account for “open dynamics that are ubiquitous in nature.” “The exciting question is not just whether quantum computers can outperform classical computers, but when, why, and under what conditions,” says Dr. Florentin Reiter, head of the Quantum Systems business unit at Fraunhofer IAF. Open System Dynamics for Robust Quantum Chemistry This work challenges the prevailing practice of modeling molecules as closed systems perfectly isolated from their environment, asserting that real-world interactions are critical to accurately assessing potential quantum advantages. The review, “Beyond Unitary Quantum Simulation: Open-System Approaches for Quantum Chemistry Toward Quantum Advantage,” proposes a shift toward incorporating these interactions into quantum simulations, acknowledging the constant energy release and relaxation inherent in natural processes. This focus on open dynamics stems from the understanding that dissipative processes aren’t simply disturbances, but potentially valuable resources for quantum algorithms. Researchers suggest controlled dissipation can aid in preparing, stabilizing, and sampling quantum states relevant to chemistry, solid-state physics, and materials science. This contrasts with traditional approaches that primarily focus on Hamiltonian dynamics of closed systems, a simplification that may not translate to practical applications. A second publication examines the Quantum Approximate Optimization Algorithm (QAOA) and its ability to maintain efficien

Quantum ZeitgeistLoading...0
Rice University Researchers Engineer Tunable Finite-Temperature Reservoirs in Trapped-Ion Quantum Simulatorsquantum-computing

Rice University Researchers Engineer Tunable Finite-Temperature Reservoirs in Trapped-Ion Quantum Simulators

Rice University Researchers Engineer Tunable Finite-Temperature Reservoirs in Trapped-Ion Quantum Simulators Physicists at Rice University have developed an experimental reservoir-engineering scheme that introduces independently tunable temperatures and dissipation rates to the vibrational modes of a trapped-ion quantum simulator. Published in Physical Review Letters (“Experimental Realization of Thermal Reservoirs with Tunable Temperature in a Trapped-Ion Spin-Boson Simulator“), the technique enables open-system quantum simulations of chemical reactions, charge transfer, and molecular exciton dynamics under realistic thermodynamic conditions. [ Rice University Engineered Thermal Reservoir Architecture ] │ ┌────────────────────────────────────────┴────────────────────────────────────────┐ ▼ ▼ Controlled Electric-Field Heating Targeted Laser Cooling • Broadcasts RF Signals with Stochastic Phases. • Removes Phonon Excitations from Selected Modes. • Delivers Random "Kicks" to Phonon Crystal. • Controls Dissipation & Equilibration Rates. • Induces Motional Heating (Tunable Bath Temp). • Stabilizes Finite-Temperature Steady States. The protocol overcomes a long-standing constraint in trapped-ion quantum simulation: while previous experiments operated either near absolute zero (ground state) or under unconstrained heating (effectively infinite temperature), the Rice framework establishes precise, continuous control across intermediate finite temperatures: Dual-Knob Environmental Control: By balancing a laser-cooling beam (which removes phonon excitations) against broadcast electric-field signals with stochastic phases (which inject random vibrational “kicks”), the researchers independently tune both the dissipation rate (γ) and the thermal bath temperature (T / average phonon occupation ⟨n⟩). Probing Finite-Temperature Charge Transfer: Using a dual-species trapped-ion chain to simulate Linear Vibronic Coupling (LVC) models, the team observed how finite temperatures al

Quantum Computing ReportLoading...0
Florida State University Launches Florida’s First Graduate Certificate in Quantum Information Science & Technologyquantum-computing

Florida State University Launches Florida’s First Graduate Certificate in Quantum Information Science & Technology

Florida State University Launches Florida’s First Graduate Certificate in Quantum Information Science & Technology Florida State University (FSU) has announced the launch of Florida’s first formal graduate credential in quantum information science and engineering: the Graduate Certificate in Quantum Information Science & Technology (QIST). Administered by the FSU Quantum Initiative, the 14-credit-hour interdisciplinary program is accepting applications through October 1, 2026, for its inaugural Spring 2027 enrollment cohort. The program bridges departments across the FSU College of Arts and Sciences and the FAMU-FSU College of Engineering—including Physics, Chemistry & Biochemistry, Computer Science, Mathematics, Materials Science & Engineering, Electrical & Computer Engineering, and Mechanical & Aerospace Engineering—to train graduate students and industry professionals across quantum materials, low-temperature device packaging, and quantum algorithm design. [ FSU QIST Graduate Certificate Ecosystem ] │ ┌─────────────────────────────────┼─────────────────────────────────┐ ▼ ▼ ▼ Core Academic Curriculum Specialized Research Facilities Industry & Center Networks • Mandatory Quantum Computing. • National MagLab (High Fields). • Commercial Partnerships (IonQ). • 3 Advanced Technical Electives. • Interdisciplinary Research Bldg. • Hardware Integration (Qblox, Keysight). • QSE Research Seminars. • Cleanroom & Cryogenic Dilution. • Quantum Software Labs (Amazon). Program structure and institutional research assets include: Curriculum Requirements: A 14-credit-hour framework comprising a mandatory core course in Quantum Information and Computing (3 credits), three specialized STEM electives (9 credits), and two semesters of the Quantum Science & Engineering Seminar (2 credits). Research Infrastructure Access: Enrolled students gain direct access to the National High Magnetic Field Laboratory (MagLab) and the newly constructed Interdiscip

Quantum Computing ReportLoading...0
Quantinuum, NVIDIA, and Pfizer Validate Generative Quantum AI (GenQAI) Framework for Pharmaceutical R&Dquantum-computing

Quantinuum, NVIDIA, and Pfizer Validate Generative Quantum AI (GenQAI) Framework for Pharmaceutical R&D

Quantinuum, NVIDIA, and Pfizer Validate Generative Quantum AI (GenQAI) Framework for Pharmaceutical R&D Researchers from Quantinuum, NVIDIA, and Pfizer Inc. have validated a Generative Quantum AI (GenQAI) framework designed to automate and accelerate quantum circuit synthesis for pharmaceutical research and electronic structure modeling. In their paper, “Learning to Prepare Molecular Ground States with Transformer Models“, the hybrid architecture combines classical High-Performance Computing (HPC), generative transformer models, and quantum processing units (QPUs) to compute ground-state preparation circuits for complex active pharmaceutical ingredients (APIs). The multi-institutional team introduced ADAPT-GQE, a generative AI model trained on quantum chemistry datasets generated via GPU-accelerated classical supercomputing. The model predicts complete ground-state quantum circuits for imipramine—a tricyclic antidepressant used as an industry benchmark for forced degradation and shelf-life stability studies—executing the resulting circuits on Quantinuum’s 98-qubit Helios-1 trapped-ion hardware. [ GenQAI / ADAPT-GQE Quantum Circuit Synthesis Pipeline ] │ ┌────────────────────────────────────────┼────────────────────────────────────────┐ ▼ ▼ ▼ HPC Data Generation (NVIDIA CUDA-Q) Generative AI Circuit Synthesis QPU Execution & Validation • GPU-Accelerated ADAPT-VQE Circuits. • Fine-Tuned NVIDIA Nemotron Models. • Quantinuum Helios-1 Processor. • OpenMM & MACE-OFF MD Conformers. • Gemma 3 / Nemotron-Nano Transformer. • InQuanto Chemistry Platform. • 12 to 16 Active-Space Qubit Maps. • 3-4 Orders of Magnitude Speedup. • Validated Imipramine Ground State. The experiment resolves a fundamental computational bottleneck in near-term variational quantum algorithms (VQEs): Bypassing Iterative Gradient Calculations: Standard adaptive algorithms like ADAPT-VQE require evaluating thousands of operator gradients and re-optimizing parameter landscapes at every step, ren

Quantum Computing ReportLoading...0
EPFL Integrates Quantinuum Trapped-Ion Cloud Access into SCITAS HPC Platformquantum-computing

EPFL Integrates Quantinuum Trapped-Ion Cloud Access into SCITAS HPC Platform

EPFL Integrates Quantinuum Trapped-Ion Cloud Access into SCITAS HPC Platform The EPFL Center for Quantum Science and Engineering (QSE), in collaboration with EPFL’s SCITAS high-performance computing (HPC) platform, has partnered with Quantinuum to provide cloud-based access to Quantinuum’s trapped-ion quantum computers. The agreement establishes EPFL as the first Swiss academic institution to natively integrate commercial QPU access directly into its institutional supercomputing infrastructure. [ EPFL SCITAS Hybrid Quantum-HPC Platform ] │ ┌─────────────────────────────────┴─────────────────────────────────┐ ▼ ▼ SCITAS HPC Infrastructure Interface Quantinuum Cloud QPU Hardware • Unified Academic Queue & Auth Workflow. • High-Fidelity Trapped-Ion Processors. • Integrated Digital Quantum Simulations. • Low Decoherence & High Gate Fidelity. • Native Integration for EPFL Researchers. • Digital Quantum & Many-Body Simulations. The partnership allows EPFL research groups to execute quantum algorithms, digital quantum simulations, and many-body physics calculations without navigating separate external management workflows: Research Applications: EPFL groups led by Prof. Giuseppe Carleo (Computational Quantum Science Laboratory) and Prof. Zoë Holmes (Quantum Information and Computing Group) are deploying the hardware to explore complex many-body quantum simulations and evaluate practical quantum algorithmic limits. SCITAS Integration: Developed alongside SCITAS Operational Director Gilles Fourestey, the integration allows researchers to submit hybrid classical-quantum jobs directly through familiar HPC batch job interfaces. Workforce & Academic Curriculum: Led by QSE Academic Director Prof. Vincenzo Savona and Master’s Program Co-Director Prof. Nicolas Macris, EPFL plans to extend hardware access to students enrolled in its Master’s program in Quantum Science and Engineering for hands-on circuit design and QPU execution. Review the official announcement on E

Quantum Computing ReportLoading...0
Rice Researchers Improve Trapped-Ion Quantum Simulation with New Temperature Controlsquantum-computing

Rice Researchers Improve Trapped-Ion Quantum Simulation with New Temperature Controls

Insider Brief Press release – Rice University physicist Guido Pagano and his team use a trapped-ion quantum simulator, which involves manipulating an ion crystal trapped in a vacuum system with electromagnetic fields, to study molecular electron transfer, or the way electrons travel from one molecule to another. While they have been able to precisely control many variables, previous […]

Quantum DailyLoading...0
Improved Measurement Cost Scaling in the Nonorthogonal Quantum Eigensolverquantum-computing

Improved Measurement Cost Scaling in the Nonorthogonal Quantum Eigensolver

--> Quantum Physics arXiv:2608.12830 (quant-ph) [Submitted on 13 Aug 2026] Title:Improved Measurement Cost Scaling in the Nonorthogonal Quantum Eigensolver Authors:Mingyu Kang, K. Birgitta Whaley View a PDF of the paper titled Improved Measurement Cost Scaling in the Nonorthogonal Quantum Eigensolver, by Mingyu Kang and K. Birgitta Whaley View PDF HTML (experimental) Abstract:Quantum subspace diagonalization methods are promising algorithms for quantum chemistry on near-term quantum computers. These methods can estimate low-lying energies of molecular systems using shallow quantum circuits, at the cost of many circuit repetitions to estimate the projected matrix elements. Errors in these matrix elements can be converted into much larger eigenvalue errors by an ill-conditioned overlap matrix. We study this bottleneck for the nonorthogonal quantum eigensolver (NOQE), which constructs a compact multireference subspace from dressed unrestricted Hartree-Fock states. We prove a finite-shot perturbation bound showing that, after overlap thresholding, the eigenvalue sensitivity is controlled by the condition number of the retained overlap matrix rather than by a worst-case dimension factor. With a scalable thresholding scheme, the upper bound on the per-matrix-element shot count required to reach a target accuracy scales as $\mathcal{O}(M)$, improving on the previously known $\mathcal{O}(M^3)$ bound, where $M$ is the number of reference states. Numerical experiments on hydrogen chains and rings suggest that, in practice, the measurement cost of structured NOQE instances can grow even more slowly than this linear bound. Comments: Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2608.12830 [quant-ph]   (or arXiv:2608.12830v1 [quant-ph] for this version)   https://doi.org/10.48550/arXiv.2608.12830 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Mingyu Kang [view email] [v1] Thu, 13 Aug 2026 05:05:55 UTC (67 KB) Ful

arXiv Quantum PhysicsLoading...0
Hybrid HPC-Quantum Simulations: DFT-Quantum Embedding for Molecular Systemsquantum-computing

Hybrid HPC-Quantum Simulations: DFT-Quantum Embedding for Molecular Systems

--> Quantum Physics arXiv:2608.12884 (quant-ph) [Submitted on 13 Aug 2026] Title:Hybrid HPC-Quantum Simulations: DFT-Quantum Embedding for Molecular Systems Authors:Namrata Manglani, Samrit Maity, Shashank Sharma, Tejjan Arora, Soham Phulare, Shreyas Kadam, Sanjay Wandhekar View a PDF of the paper titled Hybrid HPC-Quantum Simulations: DFT-Quantum Embedding for Molecular Systems, by Namrata Manglani and Samrit Maity and Shashank Sharma and Tejjan Arora and Soham Phulare and Shreyas Kadam and Sanjay Wandhekar View PDF HTML (experimental) Abstract:Scientific simulations demand methods combining scalability with predictive accuracy. Density Functional Theory (DFT) on High-Performance Computing (HPC) enables large-scale electronic-structure simulations but is limited by approximations affecting strongly correlated systems and band-gap predictions. Quantum computing offers a pathway to address this, though current Noisy Intermediate-Scale Quantum (NISQ) hardware remains constrained by qubit resources, noise, and execution cost. This work presents a hybrid DFT-Quantum Embedding (QDFT) framework integrating classical HPC-based DFT with a quantum electronic-structure solver. Large systems are partitioned to isolate a chemically relevant active space, treated via the Variational Quantum Eigensolver (VQE), while the remaining degrees of freedom are described by DFT. The framework incorporates active-space selection, embedded Hamiltonian construction, symmetry preservation, operator mapping, self-consistent density updating, and modular classical-quantum coupling. We focus on noiseless quantum simulation to systematically evaluate accuracy, convergence, active-space dependence, computational cost, and HPC scalability without hardware noise. Detailed profiling identifies computational bottlenecks and highlights limitations of CPU-based quantum simulation. A QPU runtime-estimation methodology is additionally developed to assess execution requirements on actual quantum hardware.

arXiv Quantum PhysicsLoading...0
Xanadu and Alberta U. seek better cancer drugs with quantum chipsquantum-computing

Xanadu and Alberta U. seek better cancer drugs with quantum chips

Xanadu (NASDAQ/TSX: XNDU) is investing in pharmaceutical research through a new partnership with the University of Alberta to accelerate the design of compounds for photodynamic therapy, a cancer treatment that avoids chemotherapy side effects. The collaboration unites Xanadu’s quantum computing framework with the published work of Professor Alex Brown on benchmarking photosensitizer simulations. “Current methodologies for developing effective photosensitizers are hampered by several hurdles,” said Dr. Christian Weedbrook, Founder and Chief Executive Officer of Xanadu, adding that leveraging quantum computers could make the technology a competitive method for drug discovery. This partnership aims to strengthen Xanadu’s workflow for drug design and address increasingly sophisticated challenges in photosensitizer development. Xanadu and Alberta U. Target Photosensitizer Challenges with Quantum Computing The collaboration focuses on accelerating the development of photosensitizers, light-activated compounds designed to selectively destroy tumor cells. Professor Brown’s research has identified limitations in current computational methods used to predict the effectiveness of these photosensitizers; standard techniques struggle to accurately model crucial interactions that determine their performance. Xanadu recently demonstrated the potential of quantum computers to simulate light-matter interactions within photosensitizers, revealing properties difficult to ascertain using classical approaches, including sensitivity to specific wavelengths and efficiency in triggering cell death. This builds on Xanadu’s existing open-source quantum computing platform, PennyLane, and represents an expansion of their quantum-based workflow for drug design. The partnership intends to address these hurdles by leveraging early fault-tolerant quantum computers to model complex light-matter interactions, potentially accelerating photodynamic drug discovery. Professor Brown emphasized the chall

Quantum ZeitgeistLoading...0
Queen Mary University of London builds quantum modules like computer componentsquantum-computing

Queen Mary University of London builds quantum modules like computer components

Researchers from Queen Mary University of London, Imperial College and University of Oxford have unveiled Clavina, a new modular photonic quantum computing architecture capable of combining both linear and nonlinear quantum operations within a single system. Published in Nature Photonics, this development addresses a longstanding challenge in building universal photonic quantum computers, which have previously struggled to incorporate essential nonlinear operations. The flexible design allows for specialized quantum modules to be added or removed as required, mirroring the component-based design of conventional computers. “Photonic quantum computing has enormous potential,” said Shang Yu, first author at Imperial, “but one of its greatest limitations has been the lack of a practical way to combine scalable optical circuits with the nonlinear operations required for universal quantum computing.” Clavina Architecture Integrates Linear and Nonlinear Photonic Operations This achievement, detailed in Nature Photonics, addresses longstanding limitations preventing photonic quantum computers from reaching their full potential, as existing designs struggled to incorporate the necessary nonlinear capabilities for advanced algorithms. This flexibility enables a broader range of quantum computing tasks to be performed on a single platform, eliminating the need for separate, purpose-built experimental setups. The team demonstrated several advanced applications using this architecture, including large-scale quantum simulations and the generation of quantum states crucial for future error correction, calculations previously impractical with existing photonic hardware. Experiments underpinning these demonstrations were conducted in the laboratory of Professor Ian Walmsley and Dr. Raj B. Patel at Imperial. Theoretical work led by Dr. Jinzhao Sun of Queen Mary University of London, in collaboration with Professors Vlatko Vedral from Oxford and Myungshik Kim and Roberto Bondesan from

Quantum ZeitgeistLoading...0
Xanadu and University of Alberta Partner to Accelerate Photodynamic Cancer Drug Discoveryquantum-computing

Xanadu and University of Alberta Partner to Accelerate Photodynamic Cancer Drug Discovery

Xanadu and University of Alberta Partner to Accelerate Photodynamic Cancer Drug Discovery Photonic quantum computing developer Xanadu Quantum Technologies Limited (NASDAQ/TSX: XNDU) has announced a strategic research partnership with the University of Alberta to engineer novel quantum algorithms for oncology and pharmaceutical drug design. Led by Xanadu’s algorithms team and Professor Alex Brown, Chair of the Department of Chemistry at the University of Alberta, the project focuses on modeling complex light-matter interactions in photosensitizers—light-activated chemical compounds utilized in targeted photodynamic cancer therapy (PDT). Photodynamic therapy uses light-activated compounds to selectively destroy localized tumor cells while minimizing systemic damage associated with traditional chemotherapy. However, designing photosensitizer molecules classically presents a severe computational bottleneck: predicting excited-state dynamics, wavelength sensitivity, and singlet oxygen generation efficiency requires modeling non-adiabatic light-matter coupling that traditional density functional theory (DFT) and classical quantum chemistry approximations struggle to resolve. [ Xanadu & UAlberta Photodynamic Quantum Workflow ] │ ┌────────────────────────────────────┼────────────────────────────────────┐ ▼ ▼ ▼ Photosensitizer Target Systems Photonic Quantum Simulation Stack Early Fault-Tolerant Application • Excited-State Photodynamics. • PennyLane Quantum Software Stack. • Quantum Photodynamic Algorithms. • Wavelength Sensitivity Mapping. • Light-Matter Coupling Solvers. • Accelerates PDT Oncology Pipeline. • Singlet Oxygen Efficiency. • Photonic Fault-Tolerant Roadmaps. • Bypasses Classical Simulation Limits. The collaboration pairs Xanadu’s fault-tolerant algorithm pipeline and PennyLane open-source software stack with Professor Brown’s benchmarking expertise in computational photodynamics: Light-Matter Simulation: Developing fault-tolerant quantum algorithms capable

Quantum Computing ReportLoading...0
SDT Joins Canadian Non-Profit Open Quantum Design as Official Manufacturing Partnerquantum-computing

SDT Joins Canadian Non-Profit Open Quantum Design as Official Manufacturing Partner

SDT Joins Canadian Non-Profit Open Quantum Design as Official Manufacturing Partner South Korean quantum equipment developer and systems integrator SDT has joined Canadian non-profit organization Open Quantum Design (OQD) as a primary hardware manufacturing partner. Announced at Quantum Korea 2026, the strategic agreement tasks SDT with translating OQD’s open-source hardware blueprints into physical trapped-ion quantum processing units (QPUs) and integrating their supporting control infrastructure. OQD develops full-stack, open-source trapped-ion quantum computers—publishing complete schematics for ultra-high vacuum (UHV) chambers, microfabricated surface ion-trap electrodes, laser control optics, and open software stacks. As the designated manufacturing partner, SDT will fabricate and assemble complete QPU hardware modules, build control electronics, and co-develop user-interface software to make open-source quantum computers commercially reproducible for global universities, research laboratories, and defense agencies. [ OQD & SDT Open-Source Trapped-Ion Ecosystem ] │ ┌──────────────────────────────────┴──────────────────────────────────┐ ▼ ▼ OQD Open-Source Hardware & Software Blueprints SDT System Integration & Manufacturing • Public UHV Chamber & Electrode Designs. • Precision Fabrication of Vacuum & Ion Traps. • Open Control Electronics Schematics. • Free-Space Optical Assembly & Laser Systems. • Open-Source Software Stack & Drivers. • QuREKA QCaaS Cloud & Interface Integration. Additionally, SDT has joined the preferred-supplier network for LightFlow, a cloud-based design and manufacturing platform for free-space optical systems, securing its role in producing optical subsystems and ion-trap assemblies for OQD systems. Concurrently, SDT is deploying its QuREKA Quantum Computing as a Service (QCaaS) platform to support hybrid CPU-GPU-QPU research across South Korea’s bio-pharmaceutical sector. Operating out of its Quantum-AI Hyb

Quantum Computing ReportLoading...0
Improved quantum sampling methods for molecular simulationsquantum-computing

Improved quantum sampling methods for molecular simulations

--> Quantum Physics arXiv:2608.11569 (quant-ph) [Submitted on 12 Aug 2026] Title:Improved quantum sampling methods for molecular simulations Authors:Connor van Rossum, Jeffery Cohn, Sally Shrapnel, Riddhi Gupta View a PDF of the paper titled Improved quantum sampling methods for molecular simulations, by Connor van Rossum and 3 other authors View PDF HTML (experimental) Abstract:Quantum-selected configuration interaction (QSCI) methods use a quantum computer to identify dominant electronic configurations in the molecular ground state, while a classical computer diagonalizes the Hamiltonian within the reduced subspace spanned by those configurations. Sample-based quantum diagonalization (SQD), a leading QSCI approach, uses iterative classical post-processing to correct noisy quantum measurement to ensure that the corresponding configurations remain physically sensible. In this work, we show that SQD performance can be strongly influenced by uncontrolled growth of the classical diagonalization subspace. When classical resources are not explicitly constrained, classical uniform random sampling can reproduce SQD benchmarks as noise increases the diversity of sampled configurations. We show any fair benchmarking protocol of SQD must explicitly control diagonalization size over unique samples. We then address the problem of efficiently discovering physically relevant, energy-lowering configurations by introducing a measurement protocol based on non-orthogonal configuration interaction (NOCI). By distributing measurements across orbital bases optimized with respect to the molecular Hamiltonian, we obtain improved sample efficiency relative to measurements performed solely in the Hartree--Fock basis. Importantly, these improvements persist even under fixed classical resource budgets, demonstrating that the resulting configurations are of higher quality rather than being more numerous. Under our proposed benchmarking procedure, we establish measurement-basis engineering as a

arXiv Quantum PhysicsLoading...0
D-Wave Awarded NRC Funding to Advance Commercial Annealing Algorithms and Softwarequantum-computing

D-Wave Awarded NRC Funding to Advance Commercial Annealing Algorithms and Software

D-Wave Awarded NRC Funding to Advance Commercial Annealing Algorithms and Software Quantum computing provider D-Wave Quantum Inc. (NASDAQ: QBTS) has been awarded up to CAD $300,000 ($299,025) in funding from the National Research Council of Canada’s (NRC) Applied Quantum Computing Challenge program. Conducted at D-Wave’s Quantum Centre of Engineering Excellence in Burnaby, British Columbia, the joint project aims to develop next-generation graph-embedding algorithms and open-source software tools tailored for commercial quantum annealing systems. The collaboration focuses on engineering advanced graph minor-embedding algorithms optimized for D-Wave’s Zephyr™ chip topology. Minor embedding is the foundational mathematical translation layer that maps complex, highly connected discrete optimization problems onto the physical qubit graph of an annealing QPU. By integrating these algorithms directly into D-Wave’s open-source Ocean™ Software Development Kit (SDK), the project aims to expand the scale, variable density, and problem complexity that can be solved natively on the company’s 4,400+ qubit Advantage2™ quantum annealing processors across commercial domains such as supply chain logistics, manufacturing scheduling, financial portfolio optimization, machine learning, and quantum chemistry simulations. [ NRC & D-Wave Algorithmic Embedding Pipeline ] │ ┌─────────────────────────────────┴─────────────────────────────────┐ ▼ ▼ Open-Source Ocean™ SDK Integration Zephyr™ Topology Hardware Execution • Advanced Graph Minor-Embedding Algorithms. • 4,400+ Qubit Advantage2™ Annealing Systems. • Translates High-Density Graph Problems. • 20-Way Inter-Qubit Connectivity (Zephyr). • Optimizes Ising & QUBO Problem Formulations. • Enables Larger Scale Logistics & Simulation. Operating under Canada’s broader National Quantum Strategy, the NRC’s Applied Quantum Computing Challenge program aligns federal research infrastructure with domestic industry leaders to accelerate th

Quantum Computing ReportLoading...0
Argonne Lab maps atomic flaws that cause silicon qubit errorsquantum-computing

Argonne Lab maps atomic flaws that cause silicon qubit errors

Argonne National Laboratory researchers have mapped atomic-level flaws that directly impact the performance of silicon spin qubits, a promising platform for scalable quantum computing. The team used the Chicago Quantum Computing Testbed, the first full-stack, solid-state qubit testbed at a U.S. research institution, to analyze industrial-grade silicon wafers and pinpoint the origin of qubit failure. Their study revealed that random atomic-scale fluctuations within the silicon quantum well layers are the primary cause of variability in valley splitting, a critical energy difference affecting electron stability. This work, the researchers state, “transforms valley splitting from an unexplained obstacle into a materials engineering challenge with clear paths toward improved silicon qubits.” Atomic-Scale Disorder Correlates with Valley Splitting Variability Silicon spin qubits offer a compelling route to scalable quantum computing because they leverage established semiconductor manufacturing techniques. The research institution has pinpointed a critical factor limiting their performance: atomic-scale disorder within the silicon quantum well layers. Researchers demonstrated a direct correlation between these material imperfections and the variability of valley splitting, a quantum property impacting electron stability and qubit fidelity. The team employed a sensitive electrical spectroscopy method to map valley splitting across individual quantum dots positioned within the silicon quantum well. By shifting the quantum dot’s location and measuring the resulting changes in valley splitting, they generated a nanoscale map revealing random atomic-scale fluctuations as the dominant source of variability. These fluctuations, occurring within the alloyed quantum well, directly influence the energy difference between electron valley states; a smaller split increases the risk of electrons leaking into unwanted states, introducing errors into calculations. This detailed mapping wa

Quantum ZeitgeistLoading...0
Machine Learning Now Prioritized for Quantum Chemistry’s Next Phasequantum-computing

Machine Learning Now Prioritized for Quantum Chemistry’s Next Phase

After decades of incremental progress, a fundamental barrier is emerging in quantum chemistry; density functional theory functionals have proliferated without converging toward the exact functional, according to a new position paper by Karen Sargsyan and Chao-Ping Hsu. The authors argue that traditional methods for approximating solutions to the quantum many-body problem, including both density functional theory and wavefunction methods, are yielding diminishing returns, particularly when addressing the long-standing challenge of strong correlation. This work reframes decades of method development as suggesting human intuition has largely exhausted the accessible hypothesis space. Consequently, the paper asserts machine learning represents the most promising path forward for quantum chemistry’s next phase, not as a logical necessity, but as a pragmatic decision based on observed limitations. ML-based potentials have demonstrated accuracy with 10³, 10⁵ parameters, a significant leap from previous methods. The potential of this approach extends to navigating the vastness of drug-like space, which contains between 10⁶⁰ and 10⁹⁰ possible molecules. Quantum Many-Body Problem & Computational Intractability The sheer scale of quantum systems renders exact solutions impossible, even with advanced computing power. Researchers now assert that machine learning offers the most promising route forward, not as a guaranteed solution, but as a strategically sound decision. The authors of a recent position paper reframe conventional method development as suggesting that human-driven innovation in this area has largely exhausted readily accessible avenues for improvement. This isn’t simply a matter of needing faster computers; the problem’s complexity is fundamental. Full Configuration Interaction (FCI), a high-accuracy method, scales factorially, while even the sophisticated CCSD(T) approximation scales as N⁵. “Exponential or high-order polynomial complexity cannot be defeated b

Quantum ZeitgeistLoading...0
Graph decomposition boosts resilience in quantum optimizationquantum-computing

Graph decomposition boosts resilience in quantum optimization

Jai Moondra of Carnegie Mellon University, Phillip C. Lotshaw of Oak Ridge National Laboratory, Greg Mohler of Georgia Tech Research Institute, and Swati Gupta of Massachusetts Institute of Technology have established the first provable guarantees for improving quantum noise resilience and reducing circuit complexity through graph sparsification and decomposition. Their work focuses on compilation schemes for the Quantum Approximate Optimization Algorithm (QAOA), specifically when solving the Max-Cut problem with trapped-ion simulators utilizing Pauli-X operations. The researchers demonstrate that graph sparsification directly reduces circuit complexity for edge-by-edge QAOA compilations, achieving an asymptotic improvement from O(n^2) to O(n log(n/ε)) for the number of Ising pulses. They anticipate these techniques will be useful tools in future quantum computing experiments. QAOA Compilation with Graph Sparsification for Reduced Complexity This advancement directly addresses a critical challenge in near-term quantum computing: longer circuits accumulate more noise, hindering the potential for solving complex optimization problems. The work, detailed in a publication released on 2026-08-07, volume 10, page 2185, focuses on compilation schemes tailored for trapped-ion simulators, though the principles extend to other quantum hardware platforms. Specifically, the team demonstrated improvements when solving the Max-Cut problem, a benchmark used to evaluate optimization algorithms, by leveraging Pauli-X operations and all-to-all Ising Hamiltonian evolution generated by Molmer-Sorensen or optical dipole force interactions. For trapped-ion quantum simulators, the new compilations reduce the worst-case number of Ising pulses from O(n^2) to O(n log(n/ε)) for n-node graphs, achieving an asymptotic improvement for any constant ε greater than zero. Simultaneously, the worst-case number of Pauli-X bit flips decreases from O(n^2) to O(n log(n/ε)/ε^2). This reduction in required

Quantum ZeitgeistLoading...0

Related Topics

Quantum Machine LearningQuantum Optimization LogisticsQuantum Cloud ServicesQuantum Software Development