Conference Schedule

Opening session by QTRic and SQ2

Quantum Computing: Promise, Peril and Responsible Sharing -- Quantum computing disrupts the computing paradigm by replacing binary representation and Boolean logic with quantum states and quantum logic. This shift enables quantum algorithms that can significantly reduce the complexity of certain problems and others that arguably deliver a practical quantum advantage over classical approaches. Rapid hardware advances like GPUs and software advances like tensor networks make quantum advantage harder to demonstrate, but are beneficial in generating so-called quantum inspired (classical) methods. Beyond the technical landscape, quantum computing is increasingly viewed as a sensitive, strategic and dual-use technology prompting restrictions on talent flows, trade and collaboration. In this context, responsible sharing of science offers a framework for sustaining global engagement in quantum computing while respecting legitimate security concerns.

• Invited Talk

Higher-order quantum learning algorithms for quantum channels -- Efficiently learning the properties of quantum objects is one of the key anticipated applications of quantum computers. We develop higher-order quantum algorithms for learning quantum channels, based on higher-order quantum computation, which transform a black-box quantum channel into either another quantum channel or a numerical quantity characterizing its properties. In this framework, a quantum computer acquires “quantum data” about the channel through black-box queries and then outputs the target channel or evaluates the desired properties coherently, without reconstructing a full classical description of the black box. We present two such fully quantum algorithms for learning black-box quantum channels: one for universal unitary inversion, and another for learning the singular-value moments of an unknown quantum channel.

• Invited Talk

Analog Quantum Simulation of Dirac Hamiltonian in Circuit QED -- Analog quantum simulation has emerged as a powerful tool for emulating complex quantum phenomena through tunable Hamiltonians. In this presentation, we demonstrate a versatile circuit QED platform that realizes the Dirac Hamiltonian by coupling a superconducting qubit to one or two cavity modes. This architecture allows for the precise simulation of both one- and two-dimensional relativistic dynamics, such as Zitterbewegung, within a highly controllable environment. By varying system parameters, we reproduce Dirac-like motion, supported by a close agreement between experimental observations and numerical calculations. Furthermore, we provide a detailed analysis of physical imperfections—including the breakdown of the rotating-wave approximation (RWA), sideband asymmetries, and Rabi-frequency instabilities—and their impact on simulation fidelity. Our results establish a robust approach to exploring relativistic effects, offering a scalable roadmap for future analog quantum simulations in superconducting circuits.

• Invited Talk

Speaker: Giacomo Franceschetto

• Oral Session

Speaker: V Vijendran

• Oral Session

Speaker: Michael Ragone, Dario Poletti, Apimuk Sornsaeng

• Oral Session

Speaker: Chattamas Manoworakul

• Oral Session

Electrometry of Extremely-Low Frequencies from kHz to Sub-Hz with a Rydberg-Atom Sensor -- Rydberg-atom electric-field sensors provide compact, broadband quantum receivers, but extending them to ultra-low frequencies has been hindered by electric-field screening in conventional vapor cells. We report an electrode-free strategy for low-frequency electrometry based on Rydberg-EIT in a paraffin-coated cesium vapor cell, combined with auxiliary field modulation and lock-in detection. The paraffin coating slows charge redistribution at the cell wall, creating a time window in which externally applied fields can be sensed before screening dominates. Using this approach, we detect electric fields from 0.5 Hz to 10 kHz within a unified operating scheme and measure sensitivities of 819 μV/cm/√Hz at 1 Hz, 33 μV/cm/√Hz at 10 Hz, 10 μV/cm/√Hz at 100 Hz, and 2 μV/cm/√Hz at 1 kHz. At the lowest frequencies, the sensor outperforms a same-size classical dipole receiver by one to two orders of magnitude, highlighting the potential of atomic receivers where compact classical antennas become increasingly ineffective. These results establish Rydberg vapor cells as a promising platform for compact low-frequency field sensing, with potential impact in underwater communication, geophysical and atmospheric measurements, low-frequency radio science, and multimodal quantum sensing.

• Invited Talk

Problem-informed graphical quantum generative learning -- Leveraging the intrinsic probabilistic nature of quantum systems, generative quantum machine learning (QML) offers the potential to outperform classical learning models. Current generative QML algorithms mostly rely on general-purpose models that, while being very expressive, face several training challenges. One potential way to address these setbacks is by constructing problem-informed models that are capable of more efficient training on structured problems. In particular, probabilistic graphical models provide a flexible framework for representing structure in generative learning problems and can thus be exploited to incorporate inductive bias into QML algorithms. In this work, we propose a problem-informed quantum circuit Born machine Ansatz for learning the joint probability distribution of random variables, with independence relations efficiently represented by a Markov network (MN). We further demonstrate the applicability of the MN framework in constructing generative learning benchmarks and compare our model's performance to previous designs, showing that it outperforms problem-agnostic circuits. Based on a preliminary analysis of trainability, we narrow down the class of MNs to those exhibiting favourable trainability properties. Finally, we discuss the potential of our model to offer quantum advantage in the context of generative learning.

• Invited Talk

Single-Photon-Interference-Mediated Remote Correlation for Long-Distance QKD and Long-Lived Entanglement Generation -- We report advances in quantum communication leveraging single-photon interference for efficient nodes interconnection. For prepare-and-measure quantum key distribution (QKD), we demonstrate end-to-end twin-field QKD transitioning from proof-of-principle experiments to complex field environments, repeatedly setting transmission distance records. For ion-trap quantum repeaters, we achieve high-fidelity remote ion-ion entanglement and subsequently realize device-independent QKD over 100 km. We further validate that the entanglement survival time exceeds the average waiting time for entanglement generation, a critical condition for repeater-based operation.

• Invited Talk

Speaker: Mario Herrero González, Sreeraj Rajindran Nair

• Oral Session

Quantum Communication in Thailand -- Quantum communication represents a significant real-world application arising from quantum information technology. Thailand is one of the Southeast Asian nations that has recently commenced progress in this domain through scientific research and practical implementation. In this presentation, I will highlight the current status of quantum communication research initiatives in Thailand, along with several fundamental technologies and experimental advancements achieved by our research teams thus far. Furthermore, in light of the forthcoming release of NIST’s Post-Quantum Cryptography (PQC) standards in 2024, I will examine Thailand’s present response and strategic direction concerning quantum-safe communication technologies and cybersecurity readiness.

• QTRic

Occam's Quantum Razor: On the Potential for Quantum Machines to Do More with Less -- Occam’s razor asks a fundamental question: what features of the past must we track in order to explain, predict, or react to what may occur in the future? By isolating such features, we can better understand underlying causal relations, enabling models and agents to do more with fewer memory resources by discarding data that never needed to be retained. The sharper the razor, the more unnecessary information we can shave away. The ideal construction is when they retain only information from the past that is relevant to the future - the metaphorical closest shave. Could a quantized Occam's Razor offer a closer shave? Here, I will explore this question in the context of online agents: machines that monitor and react to their environment in real time. I show that classical agents operating in such contexts often exhibit causal waste: to execute a target strategy, they are often forced to record information from the past that appears useless in hindsight. Thus, Occam's classical razor leaves an unavoidable 'stubble'. I then introduce quantum agents that can reduce this causal waste. We will first review recent results on agents that execute targeted input-output behaviour, showing that they can exhibit a memory advantage and an energetic advantage whenever causal waste exists. We then introduce ongoing work, showing how such causal waste manifests in the task of single-shot streaming classification, and how their mitigations lead to an unbounded memory separation between classical and quantum machines for labelling data-sequences online.

• Invited Talk

Speaker: Muhammad Taufiqi

• Oral Session

Quantum Computing and Coordinated Planning in Logistics & Supply Chain -- Applications of quantum computing in logistics and supply chain are often framed as next-generation optimization. This talk argues that many enterprise planning problems are better understood as coordination problems involving multiple teams, software systems, and AI agents. In such settings, business value depends not only on optimization, but also on explicit representations of data semantics and business logic, and on the ability to enumerate high-quality alternatives under uncertainty. From this perspective, quantum is relevant not only to optimization, but also to search for resilience ‘backup plans' via solution-space exploration. Some case studies with enterprise partners in logistics and petrochemicals will be presented. Quantum Technology Foundation (Thailand) Co., Ltd. (QTFT)

• Sponsor

Speaker: Josep Lumbreras, Xiangjing Liu

• Oral Session

Quantum Algorithms and Use Cases: Chemistry and CFD solvers -- Technical Leader / QAMD team’s director, Qunova Computing -- As quantum hardware matures, the central challenge shifts from theoretical promise to practical utility. Qunova Computing presents two hybrid quantum-classical algorithms delivering demonstrated Industrial Quantum Advantage on today's NISQ hardware. HI-VQE (Handover Iterative VQE) is a quantum chemistry solver that achieves chemical accuracy for molecular ground and excited state energy calculations, especially for strong correlation molecules (such as FeMoCo, 2Fe-2S, and iron-porphyrin) beyond 40 qubits. Commercially available via IBM Qiskit Functions and AWS Marketplace, HI-VQE finds applications in OLED design, catalyst development, and carbon capture reaction analysis. With the same hybrid variational philosophy, we developed the technique called HI-VQNS, that extends the hybrid variational framework to computational fluid dynamics (CFD), solving Navier-Stokes equations for single- and two-phase thermofluid problems. Targeting electronics cooling, automotive thermal management, and aerospace CFD, HI-VQNS could achieve up to 1 billion grid points with polylog qubits scale while maintaining accuracy. Therefore, both algorithms are compelling candidates for near-term quantum utility across industry.

• Sponsor

• Poster Session