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Quantum Computing Drug Discovery: Pharma Applications & Molecular Simulation

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

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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.

Theory and experiment agree on quantum system’s quick changequantum-computing

Theory and experiment agree on quantum system’s quick change

Researchers from China and Luxembourg have experimentally validated a theoretical framework for understanding rapid changes in quantum systems. Using a trapped-ion quantum simulator, the team probed quenches initiated from a critical point, revealing how defect statistics scale with the speed of the change. The work demonstrates that these defect distributions exhibit predictable, universal behavior, establishing quench-depth scaling as a benchmark for studying quantum dynamics far from equilibrium. This research addresses a fundamental question in physics: determining when universal behavior emerges in complex quantum systems. Quantum Quenches Initiated at the Critical Point Laboratory experiments utilizing trapped ions in China and Luxembourg have provided detailed validation of theoretical predictions regarding rapid changes in quantum systems, specifically those initiated from a critical point. Researchers meticulously probed the creation of defects, localized disturbances, during these quenches, revealing how their distribution behaves under varying conditions. The study centers on the transverse-field quantum Ising model, a system frequently used to model magnetic materials and a cornerstone of condensed matter physics. Chen-Xu Wang, University of Science and Technology of China, and colleagues employed a trapped-ion quantum simulator to induce rapid transitions in this model, starting the process precisely at its critical point, a state of maximum instability. This precise starting point allowed for detailed observation of how defects form and evolve as the system is driven away from equilibrium. The cumulants of the defect number distribution, a measure of their statistical properties, exhibited universal scaling with the depth of the quench, demonstrating Gaussian behavior at leading order with systematic corrections at higher levels. A key finding revolves around the scaling of defect density. The research demonstrates that, contrary to some earlier predic

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Researchers Map Light, Matter Interaction at Intermediate Regimesquantum-computing

Researchers Map Light, Matter Interaction at Intermediate Regimes

Understanding resonant cavity, quantum system interactions was previously limited to pulsed or continuous-wave scenarios, with the intermediate regime largely unexplored. Mio Poortvliet from Leiden University and CNRS, and colleagues have achieved the first thorough modelling of dynamics where pulse duration matches cavity splitting and detunings, spanning energy scales of approximately 1 to 10GHz. The team modelled how light interacts with quantum dots within resonant cavities, tiny structures that can emit single photons, particles of light, with specific properties. Their new modelling approach explores an intermediate state between short bursts and continuous beams of light used to excite these systems. The work reveals how carefully designed cavities, specifically those splitting polarized light, can optimise photon quality and increase emission rates. Mio Poortvliet and colleagues and CNRS developed new modelling to explore this interaction; resonant cavities are essentially an echo chamber for light, amplifying specific colours or wavelengths. This intermediate regime bridges established understandings of short bursts versus continuous beams. It reveals that carefully engineered cavities can optimise photon quality and boost emission rates via the Purcell effect, similar to amplifying a singer’s voice on stage. These findings detail parameter regimes for maximising both photon extraction and purity but raise questions about how best to control these complex interactions. Further technical details regarding their quantum master-equation model are presented below. Resonant cavity optimisation yields tenfold increase in single-photon source purity Single-photon purity increased by over an order of magnitude, exceeding ten percent where previously it was limited to approximately one percent. This advance resulted from detailed modelling of light interaction with quantum dots within resonant cavities, spanning energy scales between 1 and 10GHz where neither pulsed

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Dakota Team Simulates Imaginary Time Using Real-Time Dataquantum-computing

Dakota Team Simulates Imaginary Time Using Real-Time Data

Imaginary-Time Evolution (ITE) has historically proven comparatively difficult to obtain on quantum computers. A new algorithm now links ITE to more easily implemented real-time simulations by performing analytic continuation of measured correlation functions. The method was demonstrated using both classical diffusion processes and quantum mechanical scattering problems; numerical tests were performed utilising two qubits on IBM hardware. Peng Guo of the University of Birmingham and colleagues have created a computational method allowing determination of Imaginary-Time Evolution, or ITE, a process vital for certain quantum simulations, using capabilities already present in today’s quantum computers. This bypasses previous limitations requiring additional resources or producing unreliable outcomes, linking complex ITE calculations to more readily measurable real-time behaviours. Demonstrations utilising IBM computer hardware suggest this technique expands what near-term devices can achieve without needing further technological improvements. The team links ITE calculations to real-time simulations via analytic continuation, extending mathematical functions beyond their original range. Obtaining Imaginary-Time Evolution, essentially rewinding and replaying a physical process in reverse to understand its fundamental properties, has traditionally been difficult on these machines. Correlation functions, measuring how closely different aspects of a system change together over time, are central to the method but derived from readily measurable data. Two qubits enable accurate imaginary-time evolution via real-time measurement analysis An algorithm achieving Imaginary-Time Evolution (ITE) using only two qubits was demonstrated on IBM hardware by Previous methods either required additional ‘ancilla’ qubits, spare quantum bits used to aid computation, or suffered from accuracy limitations when modelling complex systems. Linking ITE calculations, traditionally difficult for qua

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Researchers Harness Simulation Errors for Improved Accuracyquantum-computing

Researchers Harness Simulation Errors for Improved Accuracy

Quantum systems formerly limited by accumulating errors during simulation are now modelled at scales ten times larger thanks to a new reinforcement learning framework called RL-Trotter. Previously treated as imperfections needing suppression, approximation errors are harnessed as resources for error correction. This approach optimises long-time behaviour by discovering sequences where later inaccuracies compensate for earlier ones, improving accuracy and reducing measurement overhead. Yu-Bo Shi of Tsinghua University and colleagues have created a method for quantum simulation which embraces imperfections rather than attempting their elimination. The team’s reinforcement learning framework uses unavoidable errors as tools to correct themselves during complex modelling, enabling simulations of previously inaccessible systems. This technique improves the accuracy of long-term behaviour by optimising sequences where later inaccuracies compensate for earlier ones, effectively increasing simulated system sizes tenfold compared with previous methods. Yu-Bo Shi and colleagues actively manage unavoidable inaccuracies instead of trying to remove them completely; this is vital as simulating increasingly complex systems pushes current methods to their limits. Their reinforcement learning framework, named RL-Trotter, functions like a training system for optimising the steps taken in modelling quantum behaviour. This allows simulations of systems formerly beyond reach due to accumulating errors, a problem analogous to adjusting stride length when walking: finding the right ‘step size’ ensures efficient and accurate progress. By using conservation laws as guiding signals, the researchers achieved an order of magnitude increase in simulated system sizes compared with prior techniques. Error compensation via reinforcement learning extends accessible quantum simulations Systems an order of magnitude larger are now simulated using this technique compared to previous methods. Prior lim

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Researchers Map Dark Matter Interactions Using Quantum Dot Barcodesquantum-computing

Researchers Map Dark Matter Interactions Using Quantum Dot Barcodes

Calculations detail how dark matter scatters on electrons within quantum dots, tiny semiconductor nanocrystals, creating a “barcode” effect. The barcode arises from variations in the shape of these quantum dots, encoding information about the mass and properties of interacting dark matter particles. The team considered experimental designs utilising one kilogram of this quantum dot material per section of the proposed detector to quantify their findings. The interaction of dark matter within quantum dots has been calculated; these are incredibly small semiconductor crystals used in displays and other technologies. This approach allows not only detection but also characterisation of fundamental dark matter qualities by analysing subtle differences across many uniquely shaped crystals. A new approach uses quantum dots, nanoscale semiconductor crystals akin to differently sculpted clay models, each possessing unique forms, for detecting dark matter. These tiny structures offer advantages over traditional detectors by potentially lowering energy thresholds needed to register interactions, a key feature as many theoretical dark matter candidates possess very low masses. Calculations were performed based solely on first principles, building up understanding from basic components without relying on pre-made assumptions, to determine how dark matter scatters within these materials and creates the “barcode” effect dependent upon crystal shape. This barcode encodes information about the mass and properties of interacting dark matter particles, allowing detection and characterisation of its fundamental qualities. Predicting dark matter interactions via first-principles simulations of confined electrons An ab initio calculation was central to this work, building up understanding from basic components without pre-made assumptions. It enabled prediction of interactions between dark matter and electrons within quantum dots free from prior biases or empirical data. Solving complex

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Researchers Simulate 2D Quantum States Using Monitored Circuitsquantum-computing

Researchers Simulate 2D Quantum States Using Monitored Circuits

For the first time, monitored quantum circuits evaluate two-dimensional quantum states without computationally expensive tensor network contraction. The method utilises variational projected entangled pair states with isometric constraints, effectively mapping complex calculations onto readily accessible circuit sampling techniques. Implementing this requires O(W log2 D) qubits, where W represents cylinder circumference and D is the virtual bond dimension. A new computational method models complex quantum materials using both standard computers and emerging quantum processors. By translating mathematical descriptions into patterns suitable for quantum circuits, the team overcame limitations previously hindering such simulations; this approach replaces difficult calculations with more manageable sampling techniques. This enables investigation of two-dimensional systems, those behaving differently in each direction, that were formerly too complicated to study effectively, potentially accelerating progress within condensed matter physics. The technique simulates complex quantum materials by sidestepping traditional computational bottlenecks. It uses blueprints describing how particles connect within a material, known as Projected Entangled Pair States or PEPS. These ‘blueprints’ previously required immense processing power to simplify due to calculating every interaction between components, similar to meticulously accounting for each brick in an elaborate architectural design. Instead, the calculations are mapped onto quantum circuits and use sampling techniques, reducing demand on both conventional computers and emerging quantum processors. This approach models two-dimensional systems, those behaving differently depending on direction, using approximately O(W log2 D) qubits where W represents cylinder circumference and D is virtual bond dimension; it also utilises conveyor belts moving properties around a simulated area, called a transfer matrix, to describe informati

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A strange new quantum droplet can hold itself togetherquantum-computing

A strange new quantum droplet can hold itself together

Science News from research organizations A strange new quantum droplet can hold itself together Date: August 21, 2026 Source: Monash University Summary: Two very different types of quantum particles may be able to form stable droplets that hold themselves together, challenging decades of conventional thinking. The prediction could soon be tested experimentally and may reveal an unexpectedly rich world of new quantum phases. Share: Facebook Twitter Pinterest LinkedIN Email FULL STORY A schematic of the Bose-Fermi droplet, which demonstrates the unique phase researchers observe in their theory. Credit: Monash University Researchers at Monash University have predicted an unusual new form of quantum matter that could overturn long-held assumptions about how ultracold particles behave. Their calculations suggest that, under the right conditions, two fundamentally different classes of quantum particles -- bosons and fermions -- can combine to create stable, self-bound "quantum droplets." Scientists had previously considered such droplets unlikely to form in strongly interacting Bose-Fermi systems. The findings offer researchers a new theoretical framework for future experiments and could improve scientists' understanding of quantum materials relevant to emerging technologies, including ultra-precise sensors and quantum computing. A Quantum Droplet That Holds Itself Together Lead author and Monash PhD candidate Sam Foster from the School of Physics and Astronomy said the results create opportunities to investigate entirely new quantum states. "Quantum systems can behave in ways that seem impossible in our everyday world. We've shown that these two very different types of particles can balance each other perfectly to create a stable droplet that effectively holds itself together." These quantum droplets are fundamentally different from ordinary drops of liquid. Their stability comes from the unusual laws of quantum mechanics. An attractive force pulling the particles togeth

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Antidots measure anyonic charge in graphenequantum-computing

Antidots measure anyonic charge in graphene

Anyons are fractionally charged quasiparticles of the quantum Hall effect, and could one day power topological quantum computers. Trapping and measuring anyons remains difficult, but quasiparticle charges have now been measured using a gate-defined antidot in bilayer graphene. For hole-conjugate states, the parity of downstream integer edge modes sets the observed charge. This is a preview of subscription content, access via your institution Access options Access through your institution Access Nature and 54 other Nature Portfolio journals Get Nature+, our best-value online-access subscription $32.99 / 30 days cancel any time Learn more Subscribe to this journal Receive 12 print issues and online access $259.00 per year only $21.58 per issue Learn more Buy this articlePurchase on SpringerLinkInstant access to the full article PDF.USD 39.95Prices may be subject to local taxes which are calculated during checkout Fig. 1: Antidot device and measurement of fractional charge. Subjects Electronic properties and materials Quantum Hall ReferencesNayak, C., Simon, S. H., Stern, A., Freedman, M. & Das Sarma, S. Non-Abelian anyons and topological quantum computations. Rev. Mod. Phys. 80, 1083–1159 (2008). A review article about non-Abelian anyons and how braiding them could realize fault-tolerant topological quantum computation.Article  ADS  MathSciNet  Google Scholar  Glattli, D. C. Quantum shot noise of conductors and general noise measurement methods. Eur. Phys. J. Spec. Top. 172, 163–179 (2009). This review article covers experimental techniques for measuring current fluctuations, including methods for fractional charge detection.Article  Google Scholar  Dean, C., Kim, P., Li, J. I. A. & Young, A. in Fractional Quantum Hall Effects: New Developments (eds Halperin, B. I & Jain, J. K.) 317–375 (World Scientific, 2020). This book chapter reviews progress in understanding the fractional quantum Hall effects in graphene.Sim, H

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Super Mutual Information Captures Operator Correlations Directlyquantum-computing

Super Mutual Information Captures Operator Correlations Directly

Researchers at the University of Ottawa and the National Research Council Canada review the framework of operator Hilbert space and introduce the one- and two-particle super reduced density matrices (1-SRDMs and 2-SRDMs), as well as the super mutual information (SMI). The eigenvectors of the 1-SRDMs define what they term natural single particle operator bases, and provide a way to compress vibrational and vibronic Hamiltonians with controlled error. The SMI is defined from the operator entanglement entropy of the 1-SRDMs and 2-SRDMs, and captures the correlation between operators acting on different one-mode subspaces, which may be used to reveal and quantify both direct and indirect couplings that might otherwise be difficult to extract. Efficient numerical approaches for the calculation of SRDMs and the SMI are developed and applied to a set of prototypical vibrational and vibronic Hamiltonians, as well as approximations to the corresponding time-evolution operators. Researchers have demonstrated that commonly used vibronic Hamiltonians are amenable to extremely high levels of compression without compromising accuracy, a finding that underscores the potential for streamlining complex quantum simulations. The researchers explain that the SMI “captures the correlation between operators acting on different one-mode subspaces,” revealing both direct and indirect couplings that may be difficult to extract. These calculations show that vibrational and vibronic Hamiltonians are particularly well-suited for high-compression techniques. The SMI analysis provides a systematic way to identify and quantify couplings between modes, even those occurring indirectly through intermediary electronic-vibrational interactions. This detailed analysis of operator entanglement builds upon conceptual foundations that appeared independently across disciplines like chemical physics, condensed matter physics, and quantum computing. Tensor Network States for Many-Body Systems Existing method

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Polarization entanglement restored in solid-state photon sourcesquantum-computing

Polarization entanglement restored in solid-state photon sources

Ismail Nassar, Dan Cogan, and Ido Schwartz of the Technion-Israel Institute of Technology have demonstrated a method to restore polarization entanglement in photons emitted from a semiconductor quantum dot. The researchers applied synchronized, time-dependent operations directly to emitted photons, reversing accumulated phase shifts caused by internal dynamics within the quantum dot itself. This photonic-compensation protocol recovers entanglement without needing to filter data based on emission time or relying on precise detector timing. The work establishes a strategy for removing the impact of emitter dynamics on photonic entanglement. Using exciton fine-structure splitting of 8.80 ± 0.04 microelectronvolts in a semiconductor quantum dot as a model system, they implemented dynamic phase modulation and performed time-resolved two-photon polarization tomography. They show that this restores a stationary two-photon polarization state and recovers polarization entanglement without temporal post-selection and independently of detector timing resolution. Photonic-Compensation Reverses Phase Evolution in Quantum Dots Quantum dots offer a promising pathway to scalable entangled-photon sources, yet inherent properties of these semiconductor structures often degrade the quality of emitted entanglement. Specifically, exciton fine-structure splitting within the quantum dot introduces a deterministic, time-dependent phase shift on emitted photons, effectively scrambling the entanglement when averaged over stochastic emission times and limited detector resolution. This approach centers on applying synchronized, time-dependent coherent operations to emitted photons, reversing the accumulated phase shift regardless of when the photon was released from the quantum dot. The team utilized a semiconductor quantum dot as a model system, leveraging its exciton fine-structure splitting to induce a predictable phase evolution, then actively counteracted this evolution with dynamic phase

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Can We Entangle?quantum-computing

Can We Entangle?

I’m an MS research student working in quantum computing. Over the past 8 months, I’ve mainly been working with quantum ML, PennyLane, VQCs, GPU/CUDA, and quantum simulation. My guide has asked me to develop stronger expertise in quantum-computing software and simulation. I feel that I’m currently somewhere between a researcher and a software developer: I can implement pipelines, reproduce experiments, debug environments, and run simulations, but I don’t yet feel that I have a strong understanding of the underlying software/simulation stack. For people working in quantum computing/software: What skills, concepts, or projects would you recommend to develop genuine expertise in quantum-computing software and simulation? For example, should I focus more on building a simulator from scratch, circuit compilation, tensor networks, GPU acceleration, automatic differentiation, noise simulation, benchmarking, or something else? I’d particularly like to know what kind of projects would make someone go from “I can use PennyLane/Qiskit” to “I understand how quantum-computing software actually works.” submitted by /u/Ill-Operation-8238 [link] [comments]

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Caltech Team Uses Quantum Simulator to Probe Universal Rules of Quantum Matterquantum-computing

Caltech Team Uses Quantum Simulator to Probe Universal Rules of Quantum Matter

Insider Brief PRESS RELEASE — When different materials transition from one phase to another, such a water coming to a boil or a magnet losing its ability to attract metals, something remarkable can happen: They begin to behave identically, following the same mathematical rules. “Physicists call this trait universality—the messy, microscopic details wash out and […]

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Rydberg chain reveals energy ratios of quantum field theoriesquantum-computing

Rydberg chain reveals energy ratios of quantum field theories

Researchers have directly observed energy excitation spectra characteristic of underlying field theories using a variably tuned Rydberg chain at quantum phase transitions. The work recovers universal energy ratios characteristic of the underlying field theories, offering a new method for examining emergent universal properties of systems undergoing these transitions. Specifically, the team distinguished excitation parities with local control, and in a tricritical Ising chain, induced transitions between distinct spectra by changing boundary conditions. This modulation technique also provides a method for diagnosing previously unknown universality classes in future experiments. Rydberg Chain Modulation Spectroscopy Resolves CFT Spectra A ratio of energy levels characteristic of conformal field theory (CFT) was recovered, a result achieved using a chain of Rydberg atoms as a quantum simulator. Researchers developed and implemented a modulation technique to observe these energy excitation spectra, offering a new method for experimentally verifying the complex mathematical structures underlying quantum phase transitions. The experimental setup utilized a one-dimensional lattice of interacting Rydberg atoms, each acting as a qubit controlled by laser frequency and site-dependent detunings. By variably tuning the system to quantum phase transitions, the researchers were able to access regimes governed by either Ising or tricritical Ising CFTs. This precise control allowed for the implementation of a modulation technique, coherently driving transitions between many-body states within targeted symmetry sectors. Overcoming the challenge of dense energy levels in larger systems, the team adapted the technique to measure the dynamical structure factor at Ising criticality, revealing universal scaling functions of underlying field correlations. At the tricritical Ising point, the modulation technique demonstrated an ability to manipulate the system’s boundary conditions, induci

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Caltech and partners find universality in quantum matterquantum-computing

Caltech and partners find universality in quantum matter

Caltech researchers have achieved the first direct measurement of energy levels predicted by the Ising and tricritical Ising conformal field theories, validating calculations made decades ago. The team, led by Manuel Endres and Jason Alicea, used quantum simulators, simplified quantum computers, to observe these universal patterns in synthetic quantum matter at temperatures near absolute zero. “Physicists call this trait universality—the messy, microscopic details wash out and only a few essential features survive,” explains Alicea, William K. Davis Professor of Theoretical Physics. This work connects Ernst Ising’s early 20th-century model of magnetism to modern quantum simulation techniques. Ising and Tricritical Ising Theories Tested with Quantum Simulators These measurements validate predictions stemming from work Ernst Ising completed in the 1920s, establishing a clear link between early 20th-century magnetism models and modern quantum simulation techniques. Unlike typical phase transitions observed in everyday phenomena, these experiments occurred at temperatures nearing absolute zero, driven by quantum effects rather than thermal changes. Researchers utilized arrays of neutral strontium atoms trapped by lasers, a technology initially developed for building quantum computers, to construct the quantum system. They excited the atoms into Rydberg states, inducing strong interactions between neighboring atoms and allowing the chain to behave as a unified entity. A novel technique, many-body modulation spectroscopy, was then employed to map the energy ladder of the system; this involved gently “shaking” the atomic chain with lasers and measuring the resulting response at various frequencies, similar to inducing resonance in a wine glass. Xiangkai Sun, a co-lead author of the study, explained that they repeated the experiment on chains of up to 35 atoms, and the spectra collapsed onto a single universal curve once rescaled for size. The team’s ability to individually

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IonQ, qBraid & NVIDIA achieve 54% fewer chemistry errors with quantum computing.quantum-computing

IonQ, qBraid & NVIDIA achieve 54% fewer chemistry errors with quantum computing.

IonQ, qBraid, and NVIDIA have achieved a 54 percent reduction in errors within quantum chemistry simulations through a combined platform solution, the company says. The collaboration addresses a core challenge in modeling molecular interactions by integrating Generalized Superfast Encoding and Clifford Noise Reduction with mid-circuit stabilizer measurement on trapped-ion systems. Trapped ions are particularly well-suited for this work due to their characteristics. This application-native mitigation approach, validated with accelerated software from NVIDIA, promises more accurate and efficient simulations for industries like drug discovery and materials science. GSE & CliNR Mitigate Errors in Quantum Chemistry Simulations A 54 percent reduction in error rates within complex chemistry simulations has been demonstrated through a collaborative effort between IonQ, qBraid, and NVIDIA, addressing a critical challenge in accurately modeling molecular interactions. Validated performance gains suggest a pathway to more reliable quantum simulations before the advent of fully fault-tolerant quantum computing. The combined approach does not merely mask errors; it actively intervenes to correct them during computation, a departure from traditional post-processing methods of error mitigation. Trapped ions proved central to this advancement due to their inherent characteristics; the systems possess exceptionally high gate fidelities and absolute all-to-all connectivity, allowing for robust and efficient quantum operations, according to NVIDIA. Researchers utilized a Barium-based development system similar to IonQ’s Barium trapped-ion Tempo-class quantum computing systems, creating a hybrid workflow where NVIDIA’s accelerated computing infrastructure and IonQ’s quantum processing units function as complementary technologies. This synergy allows for faster algorithmic operations, as any qubit can interact with any other regardless of physical distance. IonQ’s Tempo class also i

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Diraq Establishes First US Quantum Laboratory at Chicago’s IQMP On-Ramp Hubquantum-computing

Diraq Establishes First US Quantum Laboratory at Chicago’s IQMP On-Ramp Hub

Diraq Establishes First US Quantum Laboratory at Chicago’s IQMP On-Ramp Hub Silicon spin-qubit hardware developer Diraq has opened its first U.S. research and measurement laboratory in Chicago, Illinois. Situated within the Illinois Quantum and Microelectronics Park (IQMP) On-Ramp program hosted at innovation center mHUB, the facility expands Diraq’s global R&D footprint beyond its headquarters in Sydney, Australia, to accelerate its roadmap toward utility-scale silicon quantum processors. [ Diraq Global R&D & Fabrication Architecture ] │ ┌──────────────────────────────────┴──────────────────────────────────┐ ▼ ▼ Sydney HQ & Device Fabrication Chicago IQMP Laboratory Hub • Silicon Spin-Qubit QPU Design. • 2 Dedicated Cryogenic Dilution Refrig. • CMOS-Compatible Semiconductor Fabs. • Cryo-CMOS & Control Component Testing. • Primary Fabrication & Theory Teams. • Continuous 24-Hour Cross-Time-Zone R&D. On-Site Cryogenic Capabilities and Global Operations The Chicago facility provides Diraq’s U.S. engineering team with dedicated cryogenic measurement infrastructure—including two dilution refrigerators—to test, characterize, and validate silicon spin-qubit chips and integrated cryogenic CMOS (cryo-CMOS) control electronics: 24-Hour Experimental Workflow: Operating across complementary time zones between Sydney and Chicago, Diraq executes continuous 24-hour experimental measurement cycles, accelerating device iteration and qubit characterization. IQMP Ecosystem Integration: Supported by IQMP and the Illinois Economic Development Corporation (IEDC), the On-Ramp program provides immediate laboratory access while the permanent 128-acre IQMP campus undergoes construction on Chicago’s South Side. Silicon CMOS Scaling Roadmap: Diraq’s architecture utilizes electron spin qubits in quantum dots fabricated with standard silicon CMOS semiconductor processes. This approach targets rack-scale quantum systems containing thousands of physical qubits by 2029,

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QC Ware hosts quantum conference in Copenhagen next Septemberquantum-computing

QC Ware hosts quantum conference in Copenhagen next September

QC Ware and a consortium of Danish organizations, including the Ministry of Foreign Affairs of Denmark, Novo Nordisk Foundation, and Novo Holdings, will co-host the Q2B Copenhagen Conference on September 9-10, 2026. The two-day event aims to connect quantum computing experts from artificial intelligence, finance, and automotive industries, among others, indicating a broadening view of the technology’s potential beyond fundamental research. “Quantum innovation depends on strong international partnerships,” said Susanne Hyldelund, State Secretary for Trade and Investments, Ministry of Foreign Affairs of Denmark. “We are proud to welcome the global quantum community to Copenhagen and connect international partners with the Danish quantum ecosystem.” Danish Consortium Co-Hosts 2026 Q2B Copenhagen Conference The 2026 Q2B Copenhagen Conference, confirmed for September 9-10, signals a sustained commitment to fostering quantum technology despite the field’s ongoing development. This collaboration extends beyond funding; the Danish Consortium will spearhead strategic discussions focused on translating quantum research into practical applications and bolstering international cooperation. Denmark’s emergence as a European quantum hub stems from a deliberate strategy connecting research advancements with industrial implementation. Strategic investment, combined with public-private partnerships, has cultivated a rapidly expanding quantum ecosystem within the country, positioning it to strengthen Europe’s global leadership in the field. Attendees will participate in keynotes, case studies, and panel discussions featuring experts from a diverse range of industries, including AI, high-performance computing, pharmaceuticals, finance, telecommunications, and automotive, suggesting a wider applicability of quantum computing than is often highlighted. The opening session will feature a panel of ambassadors discussing the importance of international collaboration, moderated by Louise Lu

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Exact quantum dynamics now possible with fewer dimensionsquantum-computing

Exact quantum dynamics now possible with fewer dimensions

Published on August 18, 2026, research in Quantum Science and Technology details a new method for simulating complex quantum systems with reduced computational demand. Peng Guo of the Harbin Institute of Technology achieved a finite-dimensional reduction of Wigner dynamics, a step toward more manageable quantum simulations. The work demonstrates that the algebra of extended Gaussian quasi-probability densities remains closed under specific conditions, reducing complex calculations to a system of ordinary differential equations that scale polynomially. This framework provides a systematic and efficient toolbox for modeling non-Gaussian open quantum dynamics. EGQPD Closure Enables Finite-Dimensional Wigner Dynamics Reduction Simulating the behavior of quantum systems has long been hampered by exponential scaling; the computational resources needed to model even moderately complex systems quickly become prohibitive. A crucial condition for this closure is that each jump operator must be at most linear; otherwise, the extended algebra requires polynomial prefactors. The framework also introduces a discrete measure of complexity that decreases as the quantum system evolves. This metric defines the minimal number of Gaussian components needed to describe the system’s state, offering a new way to quantify its complexity. The study validates this method through seven numerical experiments, encompassing Gaussian and non-Gaussian states, entanglement decay, and dynamics around exceptional points in PT-symmetric systems. These tests demonstrated machine-precision accuracy and exponential speedups compared to traditional grid and Fock methods. Source: https://iopscience.iop.org/article/10.1088/2058-9565/ae9184 Stay currentSee today’s quantum computing news on Quantum Zeitgeist for the latest breakthroughs in qubits, hardware, algorithms, and industry deals. Tags: Rusty Flint Rusty is a quantum science nerd. He's been into academic science all his life, but spent his formative y

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D-Wave Quantum vs. Microsoft: Which Is the Better Quantum Computing Stock to Own for the Next 5 Years?quantum-computing

D-Wave Quantum vs. Microsoft: Which Is the Better Quantum Computing Stock to Own for the Next 5 Years?

Quantum computing has significant potential to transform a host of technologies, including cybersecurity, artificial intelligence, materials science, and drug discovery. But it's still in a relatively early stage of development, which makes it difficult to guess now which quantum computing stocks might be winners over the long term. Two companies on many investors' quantum computing radar are pure-play D-Wave Quantum (QBTS -6.42%) and tech giant Microsoft (MSFT +0.27%). Given where the quantum computing market is right now, and considering Microsoft's financial advantages, Microsoft stock is the no-brainer winner. Image source: Getty Images. What's happening with D-Wave right now? I get the appeal of owning a piece of D-Wave. At face value, who wouldn't want to invest in a leading quantum computing company that's betting everything on its ability to develop some of the most advanced computing systems ever to exist? The company has recently scored some meaningful wins, too, including a 1,120% increase in bookings to $35.5 million in the second quarter. Bookings are potential revenue, not actual sales yet, but they are a good indicator that customers are very interested in D-Wave's quantum annealing technology. AT&T is one such customer that has just agreed to expand its use of D-Wave's quantum computers, and may use them for "complex optimization challenges across its network operations." The telecom will experiment with the tech to improve its outage detection and response, manage technician routes, and plan new network expansions. ExpandNASDAQ: QBTSD-Wave QuantumToday's Change(-6.42%) $-1.34Current Price$19.53Key Data Points*:nth-last-child(-n+2)]:border-b-0">Market Cap$7.3BMarket cap calculated using publicly traded shares outstanding only. Does not include unlisted, private, or dual-class non-traded shares. Implied market cap may vary.Day's Range$19.45 - $20.7152wk Range$12.75 - $46.75Volume54.3KAvg Vol28.3MGross Margin-730.78% But bookings aren't sales, and

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Quantum phase estimation with optimal confidence interval using three control qubitsquantum-computing

Quantum phase estimation with optimal confidence interval using three control qubits

AbstractQuantum phase estimation is an important routine in many quantum algorithms, particularly for estimating the ground state energy in quantum chemistry simulations. This estimation involves applying powers of a unitary to the ground state, controlled by an auxiliary state prepared on a control register. In many applications the goal is to provide a confidence interval for the phase estimate, and optimal performance is provided by a discrete prolate spheroidal sequence. We show how to prepare the corresponding state in a far more efficient way than prior work. We find that a matrix product state representation with a bond dimension of 4 is sufficient to give a highly accurate approximation for all dimensions tested, up to $2^{24}$. This matrix product state can be efficiently prepared using a sequence of simple three-qubit operations. When the dimension is a power of 2, the phase estimation can be performed with only three qubits for the control register, making it suitable for early-generation fault-tolerant quantum computers with a limited number of logical qubits.Featured image: Overview of the phase estimation procedure. A matrix product representation is used to prepare a DPSS state, which provides the phase estimate with optimal confidence interval. By utilizing mid-circuit measurements, no more than three qubits are required for the control register to achieve any desired precision. Popular summaryQuantum phase estimation (QPE) is an important and widely used quantum algorithm. The purpose of QPE is to perform a measurement on a quantum computer that determines the value of a phase, corresponding to the eigenvalue of a unitary operator. Like any estimation procedure, QPE's output comes with a confidence interval, a range in which the true phase is likely to lie. In QPE, the size of the confidence interval is determined by a control state prepared on an auxiliary register. In the textbook version of QPE, the proposed control state is a uniform superpositi

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