Posters

Session 1: Tuesday, August 5, 2025

[2] Kondo impurity in an attractive Fermi-Hubbard bath: Equilibrium and dynamics.

Authors: Zhi-Yuan Wei (University of Maryland), Tao Shi (Institute of Theoretical Physics, CAS), Ignacio Cirac (Max Planck Institute for Quantum Optics) and Eugene Demler (ETH Zurich).

Presenter: Zhi-Yuan Wei
Abstract: We investigate the equilibrium and dynamical properties of a Kondo impurity coupled to either 1D or 2D superconductors, modeled by the attractive Fermi-Hubbard model. For the ground state, we find the singlet-doublet phase transition and π-phase shifts of the SC order parameter. For dynamics, first, we consider spin dynamics following an abrupt connection of the polarized impurity to the 2D bath. We find rapid relaxation of impurity polarization and directional emission of a magnetization pulse, which becomes damped as it propagates into the bulk. Then, we analyze transport between two SC leads coupled through the impurity at finite bias voltage. We uncover four distinct regimes in the transient dynamics and transport properties: (I) the AC Josephson effect regime; (II) dynamical competition between charge-density-wave (CDW) and SC orders with transient Kondo correlations; (III) the coexistence of AC and DC currents facilitated by partial Kondo screening and dynamical stabilization of the SC order; (IV) DC Kondo transport regime modified by the SC order. Regime II exhibits a dynamical transition from SC to CDW order that locally restores the U(1) symmetry. We argue that our findings for regime IV provide a theoretical explanation for the experimentally observed anomalous enhancement of DC conductance and suppression of the AC Josephson current.

Keywords: Nonequilibrium dynamics, Fermi-Hubbard model, Magnetic quantum impurity, Superfluid/superconductivity

[5] Comparative Analysis of Quantum Approximate Optimization Algorithms for Solving the Travelling Salesperson Problem.

Authors: Siddharth Chander (University of Illinois Urbana Champaign).

Presenter: Siddharth Chander
Abstract: The Quantum Approximate Optimization Algorithm (QAOA) was developed to tackle combinatorial optimization problems, such as the Travelling Salesman Problem (TSP), by approximating solutions through quantum mechanics. QAOA utilizes a unitary transformation to prepare a quantum state that encodes a potential solution, with the parameters of the unitary optimized by a classical optimizer. This study evaluates QAOA’s performance on the NP-hard TSP, comparing the standard version of the algorithm from Farhi and an enhancement, Warm-Start QAOA, to a classical solver. The TSP seeks the shortest possible route that visits a set of cities, a problem that is amenable to quantum formulation using platforms like Qiskit. Warm-Start QAOA initializes the algorithm’s parameters based on a solution to a relaxed version of the problem, offering potential improvements in optimization efficiency. By comparing these quantum algorithms to a classical solver, we provide a comprehensive assessment of their performance across key metrics, including route quality, execution time, and scalability. Through this analysis, we highlight the relative strengths and weaknesses of QAOA and its warm-start variant for solving the TSP, alongside the classical approach, offering insights into their potential for route optimization and practical applications in real-world settings. We conclude that, while the classical solver significantly outperforms QAOA and warm-start QAOA at smaller-scale problem cases, warm-Start QAOA has the potential to yield advantages at a larger scale when run on NISQ-era noisy hardware.

Keywords: Quantum Approximate Optimization Algorithm (QAOA), Warm-Start QAOA, Travelling Salesman Problem (TSP), Quantum Computing, Noisy Intermediate-Scale Quantum (NISQ), Hybrid Quantum-Classical Optimization, IBM Qiskit, Route Optimization.

[6] Stirring the false vacuum via interacting quantized bubbles on a 5,564-qubit quantum annealer.

Authors: Jaka Vodeb (Jülich Supercomputing Centre, Institute for Advanced Simulation, Forschungszentrum Jülich), Jean-Yves Desaules (Institute of Science and Technology Austria (ISTA)), Andrew Hallam (University of Leeds), Andrea Rava (Jülich Supercomputing Centre, Institute for Advanced Simulation, Forschungszentrum Jülich; RWTH Aachen University), Gregor Humar (Department of Complex Matter, Jožef Stefan Institute; Department of Physics, University of Ljubljana), Dennis Wilsch (Jülich Supercomputing Centre, Institute for Advanced Simulation, Forschungszentrum Jülich), Fengping Jin (Jülich Supercomputing Centre, Institute for Advanced Simulation, Forschungszentrum Jülich), Madita Willsch (Jülich Supercomputing Centre, Institute for Advanced Simulation, Forschungszentrum Jülich;), Kristel Michielsen (Jülich Supercomputing Centre, Institute for Advanced Simulation, Forschungszentrum Jülich) and Zlatko Papic (University of Leeds).

Presenter: Gregor Humar
Abstract: False vacuum decay—the transition from a metastable quantum state to a true vacuum state—plays an important role in quantum feld theory and non-equilibrium phenomena such as phase transitions and dynamical metastability. The non-perturbative nature of false vacuum decay and the limited experimental access to this process make it challenging to study, leaving several open questions regarding how true vacuum bubbles form, move and interact. Here we observe quantized bubble formation in real time, a key feature of false vacuum decay dynamics, using a quantum annealer with 5,564 superconducting fux qubits. We develop an efective model that captures both initial bubble creation and subsequent interactions, and remains accurate under dissipation. The annealer reveals coherent scaling laws in the driven many-body dynamics for more than 1,000 intrinsic qubit time units. This work provides a method for investigating false vacuum dynamics of large quantum systems in quantum annealers.

Keywords: quantum simulation, quantum many-body physics, false vacuum decay.

[8] Toward Digital and Analogue Quantum Processors Using Neutral Atom Arrays.

Authors: Abhishek Jamunkar (Centre for Quantum Technologies, National University of Singapore), Zilong Chen (Centre for Quantum Technologies, National University of Singapore), Tong-Yan Xia (Centre for Quantum Technologies, National University of Singapore), Vasu Dev (Centre for Quantum Technologies, National University of Singapore), Kai Xiang Lee (Centre for Quantum Technologies, National University of Singapore), Jinyu Zhou (Centre for Quantum Technologies, National University of Singapore), Vincent Mancois (Centre for Quantum Technologies, Nanyang Technological University), Jintao Yang (Centre for Quantum Technologies, National University of Singapore), Thanh Nguyen (Centre for Quantum Technologies, National University of Singapore), Ng Boon Long (Centre for Quantum Technologies, National University of Singapore), Kelvin Lim (Centre for Quantum Technologies, Nanyang Technological University), Zhengjiang Li (Centre for Quantum Technologies, Nanyang Technological University), Mujahid Aliyu (Centre for Quantum Technologies, National University of Singapore) and David Wilkowski (Centre for Quantum Technologies, Nanyang Technological University).

Presenter: Abhishek Jamunkar
Abstract: We have started an ambitious project aiming to build digital and analogue quantum processor prototypes that should be delivered in 2029. During the period 2025-2027, six equivalent experimental machines will be mounted using neutral atoms tweezer array techniques. Our objective will be to have more than 200 atoms arranged in a defect-free lattice with state-of-the-art performances in term of lifetime, loading rate, robustness, and control of the phase and amplitude of the addressing lasers. After 2027, each experimental platform will be used to develop the prototypes in a parallel approach. We aim to achieve > 99.9% and > 99% single and two qubit gate fidelity, respectively. Error-correction codes should be implemented to reduce further the error rate.

Keywords: Ultracold gases, Nanophotonics, Quantum Sensing, Quantum simulations, Quantum Computer

[9] Riemannian quantum circuit optimization based on matrix product operators.

Authors: Isabel Nha Minh Le (Technical University of Munich), Shuo Sun (Technical University of Munich) and Christian B. Mendl (Technical University of Munich)

Presenter: Isabel Nha Minh Le
Abstract: We significantly enhance the simulation accuracy of initial Trotter circuits for Hamiltonian simulation of quantum systems by integrating first-order Riemannian optimization with tensor network methods. Unlike previous approaches, our method imposes no symmetry assumptions, such as translational invariance, on the quantum systems. This technique is scalable to large systems through the use of a matrix product operator representation of the reference time evolution propagator. Our optimization routine is applied to various spin chains and fermionic systems described by the transverse-field Ising Hamiltonian, the Heisenberg Hamiltonian, and the spinful Fermi-Hubbard Hamiltonian. In these cases, our approach achieves a relative error improvement of up to four orders of magnitude for systems of 50 qubits. Furthermore, we demonstrate the versatility of our method by applying it to molecular systems, specifically lithium hydride, achieving an error improvement of up to eight orders of magnitude. This proof of concept highlights the potential of our approach for broader applications in quantum simulations.

Keywords: quantum circuits, quantum circuit compression, quantum circuit optimization, Hamiltonian simulation, tensor networks, quantum-classical hybrid method, differential geometry

[12] From Critical Dynamics to Coarsening: Bias-Tuned Quantum Phase Transitions on a 2400 Qubit Coherent Annealer.

Authors: Jaka Vodeb (Jozef Stefan Institute), Dennis Willsch (Julich Research Centre), Kristel Michielsen (Julich Research Centre), Jacek Dziarmaga (Jagiellonian University, Institute of Theoretical Physics), Marek Rams (Jagiellonian University, Institute of Theoretical Physics) and Francis Jr. Bayocboc (Jagiellonian University, Institute of Theoretical Physics).

Presenter: Jaka Vodeb
Abstract: In this work, we explore the dynamics of quantum phase transitions and domain formation in a programmable quantum annealing platform based on a new, coherence-optimized version of the D-Wave quantum annealer, utilizing over 2400 qubits. By leveraging enhanced coherence times and control capabilities, we systematically investigate the role of externally applied symmetry-breaking fields on quantum dynamics across critical points in two qualitatively different systems: a one-dimensional (1D) chain and a two-dimensional (2D) square lattice.Our study reveals a clear dynamical crossover from the Kibble–Zurek (KZ) regime to adiabatic evolution, governed by the presence of a weak bias field. In the 1D chain, we benchmark our results against known analytical predictions and numerical tensor network simulations, finding excellent agreement in both the scaling of excitation suppression and the bias-controlled restoration of adiabaticity, consistent with the theoretical framework proposed in Rams et al [Physical Review Letters, 123(13), p.130603]. The critical bias strength required to bypass the freeze-out region scales in accordance with KZ theory modified by susceptibility divergence at the critical point, enabling us to tune the evolution between defect-generating and adiabatic regimes. Extending this analysis to more complex geometries, we observe a qualitatively similar crossover in the 2D square lattice. In particular, in the 2D lattice, we are able to track domain formation and post-critical coarsening with high spatial resolution. By quenching the system into the ordered phase under a symmetry-breaking bias, we observe the curvature and volume-driven dynamics of domain walls and demonstrate the influence of bias on the size distribution of domains. This behavior is characteristic of model A dynamics for systems with a non-conserved order parameter and is consistent with both classical and quantum coarsening theory. Strikingly, we find that the coarsening dynamics observed on the quantum annealer quantitatively match tensor network simulations based on projected entangled pair states and matrix-product-state methods, reinforcing the utility of the annealer as a reliable platform for simulating out-of-equilibrium many-body quantum systems. Altogether, our findings establish that coherent quantum annealing hardware can successfully emulate non-equilibrium quantum dynamics beyond the standard Kibble–Zurek picture, offering new opportunities to study universality, quantum coarsening, and phase ordering kinetics across different spatial dimensions. This work lays the groundwork for future exploration of collective dynamics in programmable quantum systems, especially in the presence of tunable disorder, long-range interactions, and metastable quantum phases.

Keywords: Quantum Phase Transition, Quantum Annealing, Coherent Dynamics, Non-equilibrium Dynamics, Post-critical Dynamics, One-dimensional Systems, Two-dimensional Systems, Kibble-Zurek mechanism, Adiabatic Evolution, Symmetry Breaking Bias, Tensor Networks, Projected Entangled Pair States, Matrix Product States, Quantum Coarsening, Model A Dynamics

[13] Accessing fast scrambling with nearest neighbor interactions.

Authors: Goksu Toga (North Carolina State University), Abhishek Samlodia (Syracuse University) and Alexander Kemper (North Carolina State University).

Presenter: Goksu Toga
Abstract: In this talk, we introduce the Hyperbolic Ising model, which is a mixed field Ising model that lives in the discretization of the AdS_2 space. Through the calculation of infinite and finite temperature OTOCs, we show that this model can be classified as a fast scrambler, and it saturates the bound on chaos, making this model maximally chaotic. Our model is easily simulatable on the current NISQ hardware using both gate-based and analog quantum computers. To demonstrate the application on gate-based computers, we simulate this model on IBM quantum hardware and measure OTOCs using randomized measurement protocols. We further sketch out the necessary setup for analog simulations using Rydberg arrays. Our results indicate that contrary to the common belief it is possible to achieve fast scrambling behavior in local models with carefully designed interactions motivated from holography. This provides us with models to study fast scrambling on quantum computers without worrying about the computational cost of simulating all-to-all or long-range interacting models while emphasizing the effects that a curved background can have on the dynamics of the model.

Keywords: Fast Scrambling, Quantum Simulation, Many-body quantum chaos

[15] Scalable quantum dynamics compilation via quantum machine learning.

Authors: Roeland Wiersema (Flatiron Institute), Yuxuan Zhang (University of Toronto), Juan Carrasquilla (ETH Zurich), Lukasz Cincio (Los Alamos National Lab) and Yong-Baek Kim (University of Toronto).

Presenter: Roeland Wiersema
Abstract: Quantum dynamics compilation is an important task for improving quantum simulation efficiency: It aims to synthesize multi-qubit target dynamics into a circuit consisting of as few elementary gates as possible. Compared to deterministic methods such as Trotterization, variational quantum compilation (VQC) methods employ variational optimization to reduce gate costs while maintaining high accuracy. In this work, we explore the potential of a VQC scheme by making use of out-of-distribution generalization results in quantum machine learning (QML): By learning the action of a given many-body dynamics on a small data set of product states, we can obtain a unitary circuit that generalizes to highly entangled states such as the Haar random states. The efficiency in training allows us to use tensor network methods to compress such time-evolved product states by exploiting their low entanglement features. Our approach exceeds state-of-the-art compilation results in both system size and accuracy in one dimension (1D). For the first time, we extend VQC to systems on two-dimensional (2D) strips with a quasi-1D treatment, demonstrating a significant resource advantage over standard Trotterization methods, highlighting the method’s promise for advancing quantum simulation tasks on near-term quantum processors.

Keywords: variational compilation, circuit compression, tensor networks

[16] Exponentially Decaying Quantum Simulation Error with Noisy Devices.

Authors: Jue Xu (University of Hong Kong), Chu Zhao (Tsinghua University), Junyu Fan (International Quantum Academy) and Qi Zhao (University of Hong Kong).

Presenter: Jue Xu
Abstract: Quantum simulation is a promising way toward practical quantum advantage, but noise in current quantum hardware poses a significant obstacle. We theoretically and numerically revealed that not only the physical error but also the algorithmic error in a single Trotter step decreases exponentially with the circuit depth. In particular, according to our results, we derive the optimal number of Trotter steps and the noise requirement to guarantee total simulation precision. At last, we demonstrate that our improved error analysis leads to significant resource-saving for fault-tolerant Trotter simulation. By addressing these aspects, this work systematically characterizes the robustness of Trotter simulation errors in noisy quantum devices and paves the way toward practical quantum advantage.

Keywords: quantum simulation, Trotter error, noisy circuit, NISQ, fault-tolerant

[18] Fast and direct preparation of a genuine lattice BEC via the quantum Mpemba effect.

Authors: Philipp Westhoff (Ludwig-Maximilians Universität München), Sebastian Paeckel (Ludwig-Maximilians Universität München) and Mattia Moroder (Trinity College Dublin).

Presenter: Philipp Westhoff
Abstract: Preparing high-fidelity Bose-Einstein condensates (BEC) is the key first step toward generating highly entangled states in the quantum simulators based on ultracold atoms in optical lattices. In this talk, I will present an efficient method for dissipatively preparing a BEC directly on a lattice, replacing the currently used slow, two-stage procedure prone to environment-induced decoherence and heating. The protocol drives the lattice subsystem into a non-equilibrium steady state exhibiting a lattice analog of a true BEC, with depletion controllable via the dissipation strength. A symmetry-based Mpemba effect allows analytical identification of simple, experimentally realizable initial states that converge exponentially faster than random ones. Additionally, I show how combining superfluid immersion with lattice shaking enables tuning the momentum of the prepared BEC. Theoretical predictions are confirmed by matrix-product state simulations, which quantify the speedups and fidelities achieved. This protocol offers a powerful tool for significantly enhancing the preparation of highly entangled states in analog quantum simulators.

Keywords: dissipative state preparation, quantum Mpemba effect, ultracold atoms in optical lattices, Bose-Einstein condensate (BEC)

[23] Noise-robust analog quantum simulation of noisy quantum systems.

Authors: Mingyu Kang (Duke University).

Presenter: Mingyu Kang
Abstract: This abstract suggests a path towards quantum advantage in simulating models of quantum phenomena in Nature, extended from our recent review [1] and experimental quantum simulation [2].
Open quantum systems are widely used to model physical, chemical, biological, and material systems. When characterizing quantum phenomena, a more detailed and accurate open quantum system model can be constructed at the cost of requiring a larger computational cost. For an example of energy transfer in molecular systems, starting from a model consisting of electronic states, vibrational modes are incorporated to account for the quantum nature of the environment, followed by the inclusion of the dissipation of vibrational modes. A characterization of the dissipation as mixed Gaussian relaxation and non-Gaussian dephasing adds crucial detail for understanding the long-time behavior of the quantum system. In the context of analog quantum simulation, I would like to share the perspective that the intrinsic noise of the quantum simulator can serve as a resource for simulating the dissipative component of the target quantum phenomena. This would require precise characterization of noise mechanisms in both the quantum simulator hardware and the open quantum system to be simulated. In Ref.~[1], we perform numerical simulations of the expected performance of noisy trapped-ion simulators, which leads to the conclusion that the noise level of the trapped-ion system needs to be reduced by roughly two orders of magnitude from the state-of-the-art in order to achieve a quantum advantage in simulating linear vibronic coupling models. However, the experimental results for simulating the spin-boson model in Ref.~[2] already achieve high accuracy, even though the evolution time of the quantum simulator is comparable to the time scale of the hardware noise. This is because the motional dephasing noise, a leading error source that is characterized and mitigated for high-fidelity two-qubit gates, is essentially injected and used as an ingredient for simulating the dephasing of the bath oscillator. Indeed, vibrational dephasing, together with vibrational relaxation, is known to be a significant decoherence mechanism in condensed-phase molecular dynamics, which leads to the study of the open quantum Rabi model with mixed bosonic relaxation and dephasing. A more detailed characterization of a quantum system leads to a more accurate prediction and control of its behavior, which applies to both the quantum simulator hardware and the quantum phenomena in Nature. Robustness to noise in analog quantum simulation is naturally achieved by using the inherent noise of the quantum simulator hardware to simulate the dissipative mechanisms. This approach could pave the way for near-term quantum advantage as well as inspire theoretical exploration of novel open quantum system models, with broad applicability across physical, chemical, and biological systems.

[1] M. Kang, H. Nuomin, S. N. Chowdhury, J. L. Yuly, K. Sun, J. Whitlow, J. Valdiviezo, Z. Zhang, P. Zhang, D. N. Beratan, and K. R. Brown, Seeking a quantum advantage with trapped-ion quantum simulations of condensed-phase chemical dynamics, Nat. Rev. Chem. 8, 340-358 (2024)

[2] K. Sun, M. Kang, H. Nuomin, G. Schwartz, D. N. Beratan, K. R. Brown, and J. Kim, Quantum simulation of spin-boson models with structured bath, arXiv:2405.14624, In Press, Nat. Comm.

Keywords: robust quantum simulation, analog quantum simulation, open quantum system, quantum advantage, trapped ions.

[25] Circuit compilation for quantum dynamics of 2D systems with Pauli propagation.

Authors: Matteo D’Anna (ETH Zurich), Yuxuan Zhang (Vector Institute), Roeland Wiersema (Flatiron Institute) and Juan Carrasquilla (ETH Zurich).

Presenter: Matteo D’Anna
Abstract: As quantum processors progress toward practical utility, the need for efficient compilation algorithms grows. In particular, simulating real-time dynamics with limited quantum resources requires the compression of accurate, deep circuits into shallow, hardware-friendly forms (that retain the high levels of accuracy). We present a variational approach for compiling deep time evolution operators into optimized shallower ansaetze using the Pauli propagation framework. Our method minimizes a fidelity-based cost function over special classes of ensembles of product states, that relate to the Hilbert-Schmidt cost by some out-of-distribution bound from the literature. By avoiding reliance on global Haar randomness (required for computing the Hilbert-Schmidt cost) and leveraging locally scrambled distributions, we achieve scalable circuit compression suited for near-term architectures, especially systems with connectivities more challenging that 1D. This formulation allows us to replace standard simulation techniques, such as Trotterization, with a variational strategy tailored to reduce circuit depth. Our method is particularly well suited to 2D quantum systems, where hardware limitations make traditional approaches impractical. The compression technique introduced here thus opens the door to high-fidelity dynamical simulation on near-term quantum devices. Numerical results show that our approach can enhance dynamics simulations for current hardware and in the future. In general our circuits implement the dynamics orders of magnitude more accurately than Trotterization, and do so by using identical resources. We demonstrate this in an experimental setup, where we simulate the dynamics of a cloud of hard-core bosons on a lattice using Quantinuum’s H1 quantum chip. We show that by applying our compressed ansatz multiple times it’s possible to track the exact dynamics for much longer times than what would have been possible with standard Trotterization. Additionally, we can tackle the compression of large 2D systems, as we perform the compression for the dynamics of the transverse field Ising model on a 30×30 lattice.

Keywords: 2D dynamics, Circuit compression, Circuit compilation, Pauli propagation, Variational optimization.

[26] Mitigation of correlated readout errors without randomized measurements.

Authors: Adrian Skasberg Aasen (Universität Heidelberg), Andras Di Giovanni (Karlsruher Institut für Technologie), Hannes Rotzinger (Karlsruher Institut für Technologie), Alexey Ustinov (Karlsruher Institut für Technologie) and Martin Gärttner (Friedrich-Schiller-University Jena).

Presenter: Adrian Skasberg Aasen
Abstract: Quantum simulation, the study of strongly correlated quantum matter using synthetic quantum systems, has been the most successful application of quantum computers to date. It often requires determining observables with high precision, for example when studying critical phenomena near quantum phase transitions. Thus, readout errors must be carefully characterized and mitigated in data post-processing, using scalable and noise-model agnostic protocols. We present a readout error mitigation protocol that uses only single-qubit Pauli measurements and avoids experimentally challenging randomized measurements. The proposed approach captures a very broad class of correlated noise models and is scalable to large qubit systems. It is based on a complete and efficient characterization of few-qubit correlated positive operator-valued measures (POVMs), using overlapping detector tomography. To assess the effectiveness of the protocol, observables are extracted from simulations involving up to 100 qubits employing readout errors obtained from experiments with superconducting qubits.

Keywords: Readout error mitigation, Correlated errors, Overlapping tomography, Quantum detector tomography, Quantum state tomography

[27] Classical and Quantum simulation of Deconfined Quantum critical points in one-dimensional systems.

Authors: Niccolo Baldelli (Barcelona Supercomputing Center).

Presenter: Niccolò Baldelli
Abstract: Deconfined quantum critical points (DQCP) are exotic phase transitions not predicted by the Landau-Ginzburg symmetry-breaking paradigm. In particular, they are associated with a one-point gap closing between distinct locally ordered phases, thus to a continuous phase transition. This is in stark contrast with standard symmetry-breaking theories that predict a first-order phase transition between locally ordered phases. While predicted more than 20 years ago, the precise identification of systems showing DQCPs has been elusive due to the fine tuning of parameters needed to identify them. In this talk, we will present precise Tensor Networks calculations unveiling the presence of such transitions in one-dimensional bosons and fermionic systems. Moreover, we will show how a system with such physics can be implemented in a quantum simulator with ultracold will finally discuss the possibility of implementing a measurement protocol via a quench between the two phases connected by a DQCP.

Keywords: Quantum phase transition, Deconfined Quantum Criticality, Uniform MPS, Cold Atoms, Hubbard physics, Low-dimensional physics, Bosonization.

[28] Robust analog quantum simulators by quantum error-detecting codes.

Authors: Yingkang Cao (University of Maryland, College Park), Suying Liu (University of Maryland, College Park), Haowei Deng (University of Maryland, College Park), Zihan Xia (University of Southern California), Xiaodi Wu (University of Maryland, College Park) and Yuxin Wang (University of Maryland, College Park).

Presenter: Yingkang Cao
Abstract: Achieving noise resilience is an outstanding challenge in Hamiltonian-based quantum computation. To this end, energy-gap protection provides a promising approach, where the desired quantum dynamics are encoded into the ground space of a penalty Hamiltonian that suppresses unwanted noise processes. However, existing approaches either explicitly require high-weight penalty terms that are not directly accessible in current hardware, or utilize non-commuting 2-local Hamiltonians, which typically leads to an exponentially small energy gap. In this work, we provide a general recipe for designing error-resilient Hamiltonian simulations, making use of an excited encoding subspace stabilized by solely 2-local commuting Hamiltonians. Our results thus overcome a no-go theorem previously derived for ground-space encoding that prevents noise suppression schemes with such Hamiltonians. Importantly, our method is scalable as it only requires penalty terms that scale polynomially with system size. To illustrate the utility of our approach, we further apply this method to a variety of 1- and 2-dimensional many-body spin models, potentially extending the duration of high-fidelity simulation by orders of magnitude in current hardware.

Keywords: Analog quantum simulation, Quantum error suppression, Energy-gap protection

[32] Extracting the spin excitation spectrum of a fermionic system using a quantum processor.

Authors: Lucia Vilchez-Estevez (University of Oxford and Phasecraft Ltd.), Raul A. Santos (Phasecraft Ltd.), Sabrina Yue Wang (Phasecraft Ltd.) and Filippo Maria Gambetta (Phasecraft Ltd.).

Presenter: Filippo Maria Gambetta
Abstract: Understanding low-energy excitations in fermionic systems is crucial for their characterization. They determine the response of the system to external weak perturbations, its dynamical correlation functions, and provide mechanisms for the emergence of exotic phases of matter. In this work, we study the spin excitation spectra of the 1D Fermi-Hubbard model using a digital quantum processor. Introducing a protocol that is naturally suited for simulation on quantum computers, we recover the retarded spin Green’s function from the time evolution of simple observables after a specific quantum quench. We exploit the robustness of the protocol to perturbations of the initial state to minimize the quantum resources required for the initial state preparation, and to allocate the majority of them to a Trotterized time-dynamics simulation. This, combined with the intrinsic resilience to noise of the protocol, allows us to accurately reconstruct the spin excitation spectrum for large instances of the 1D Fermi-Hubbard model without making use of expensive error mitigation techniques, using up to 30 qubits of an IBM Heron r2 device.

Keywords: quantum simulation, time-dynamics simulation, quantum quench, Fermi-Hubbard model, spectroscopy, dynamical structure factor, low-energy excitations

[33] Shortcuts to Analog Preparation of Non-Equilibrium Quantum Lakes.

Authors: Nik Gjonbalaj (Harvard University), Rahul Sahay (Harvard University) and Susanne Yelin (Harvard University).

Presenter: Nik Gjonbalaj
Abstract: The dynamical preparation of exotic many-body quantum states is a persistent goal of analog quantum simulation, often limited by experimental coherence times. Recently, it was shown that fast, non-adiabatic Hamiltonian parameter sweeps can create finite-size “lakes” of quantum order in certain settings, independent of what is present in the ground state phase diagram. Here, we show that going further out of equilibrium via external driving can substantially accelerate the preparation of these quantum lakes. Concretely, when lakes can be prepared, existing counterdiabatic driving techniques — originally designed to target the ground state — instead naturally target the lakes state. We demonstrate this both for an illustrative single qutrit and a model of a Z2 Rydberg quantum spin liquid. In the latter case, we construct experimental drive sequences that accelerate preparation by almost an order of magnitude at fixed laser power. We conclude by using a Landau-Ginzburg model to provide a semi-classical picture for how our method accelerates state preparation.

Keywords: Analog state preparation, Counterdiabatic driving, Quantum spin liquids, Non-equilibrium states

[34] Status and Prospects of VQE for Quantum Simulation.

Authors: Mafalda Ramôa (Virginia Tech), Panagiotis Anastasiou (Virginia Tech), Luis P. Santos (INESC TEC, INL, University of Minho), Edwin Barnes (Virginia Tech), Nicholas Mayhall (Virginia Tech) and Sophia Economou (Virginia Tech).

Presenter: Mafalda Ramôa
Abstract: In this work, we discuss and compare leading proposals of ansatze for the electronic structure problem. Our main contribution is a comparison of key viability metrics: The CNOT count and measurement costs required to achieve a chemically accurate solution. We consider our novel CEO-ADAPT-VQE algorithm as well as several static VQEs: k-UpCCGSD, QNP, tUPS, oo-tUPS and pp-tUPS.
From the comprehensive set of ansatze we simulated, ADAPT-VQE markedly appears as the most viable approach, with other ansatze either failing to reach chemical accuracy or requiring a prohibitive number of measurements – five orders of magnitude larger than required by ADAPT-VQE, including all costs incurred throughout the adaptive ansatz construction. This surprising result contradicts the common belief that the adaptive ansatz construction incurs a measurement overhead: The optimization perks enjoyed by ADAPT-VQE easily compensate for any additional measurements required by the adaptive protocol.

Keywords: VQE, NISQ, ADAPT-VQE, Electronic structure, Adaptive ansatz, Ansatz

[35] Disambiguating Pauli noise in quantum computers

Authors: Edward Chen (IBM Quantum), Senrui Chen (University of Chicago), Laurin Fischer (IBM Quantum), Andrew Eddins (IBM Quantum), Luke Govia (IBM Quantum), Brad Mitchell (IBM Quantum), Andre He (IBM Quantum), Youngseok Kim (IBM Quantum), Liang Jiang (University of Chicago) and Alireza Seif (IBM Quantum).

Presenter: Senrui Chen
Abstract: Understanding noise in quantum computers is crucial for processing quantum information. However, fundamental limitations prevent us from uniquely identifying the noise model affecting a quantum processor. This raises the question of whether these limitations impact our ability to predict noisy dynamics and mitigate errors. Here, we show, both theoretically and experimentally, that when learnable degrees of freedom are self-consistently characterized, the unlearnable (gauge) degrees of freedom do not impact predictions of noisy dynamics or error mitigation. We use the recently introduced framework of Pauli gate set learning to efficiently and self-consistently characterize and mitigate noise of a complete gate set, including state preparation, measurements, and two-qubit entangling gates. We validate our approach through experiments with up to 92 qubits and show that while the gauge choice does not affect error-mitigated observable values, optimizing it reduces sampling overhead. Our findings address a longstanding issue involving the ambiguities in characterizing quantum noise.

Keywords: entanglement, quantum walks, error mitigation, noise learning, gauge models

[39] Learning Functions of Hamiltonians with Hamiltonian Fourier Features.

Authors: He Zheng (University of Oregon), Daniel Steck (University of Oregon) and Jonathan Mackrory (University of Oregon)

Presenter: Yuto Morohoshi
Abstract: We propose and experimentally demonstrate a quantum machine learning task that is provably easy for quantum computers and arguably hard for classical ones.
The task involves predicting quantities of the form $\mathrm{Tr}[f(H)\rho]$, where $f$ is an unknown function, given descriptions of $H$ and $\rho$. Using a Fourier-based feature map of Hamiltonians and linear regression, we theoretically establish the learnability and demonstrate it on a superconducting device with up to 40 qubits. Our results provide a machine learning task with practical relevance, provable quantum easiness, and near-term feasibility.

Keywords: Quantum Simulation, Quantum Machine Learning, Product Formula, NISQ

[40] Exponential Quantum Learning Advantage with Vanishingly Small Entanglement.

Authors: Minsoo Kim (Department of Physics, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea) and Changhun Oh (Department of Physics, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea).

Presenter: Minsoo Kim
Abstract: Quantum learning has emerged as a promising application of quantum technology that offers a quantum advantage. It is established that the use of quantum memory can exponentially reduce sample complexity for learning a quantum channel. However, in the proposed scheme, the preparation of maximally entangled states is necessary to realize the exponential advantage. In this work, we demonstrate that this exponential advantage in Pauli channel learning can still be attained using input states with vanishingly small entanglement. We construct an explicit input state with inverse-polynomial entanglement that enables the learning task to be completed with only polynomial sample complexity.
Additionally, we show that if the number of ancilla qubits is constrained, exponential sample complexity is necessary even for partial channel parameter learning. Our results establish how quantum resources can affect the sample complexity in quantum channel learning.

Keywords: Quantum Learning, Quantum Advantage, Pauli Channel Learning

[41] Observation of hysteresis in a disordered Heisenberg quantum spin system.

Authors: Eduard J. Braun (Physikalisches Institut, Universität Heidelberg, Im Neuenheimer Feld 226, 69120 Heidelberg, Germany), Moritz Hornung (Physikalisches Institut, Universität Heidelberg, Im Neuenheimer Feld 226, 69120 Heidelberg, Germany), Sebastian Geier (Physikalisches Institut, Universität Heidelberg, Im Neuenheimer Feld 226, 69120 Heidelberg, Germany), Titus Franz (Max-Planck-Institute for Quantum Optics, Hans-Kopfermann-Str.1, Garching D-85748, Germany), Gerhard Zürn (Physikalisches Institut, Universität Heidelberg, Im Neuenheimer Feld 226, 69120 Heidelberg, Germany) and Matthias Weidemüller (Physikalisches Institut, Universität Heidelberg, Im Neuenheimer Feld 226, 69120 Heidelberg, Germany).

Presenter: Eduard J. Braun
Abstract: Disorder plays an important role for the dynamics and the equilibrium properties of complex quantum systems. A Yuki Koizumi (The University of Tokyo), Kaito Wada (Keio University), Wataru Mizukami (Osaka University) and Nobuyuki Yoshioka (The University of Tokyo).paradigmatic model for exploring disordered and frustrated quantum spin systems are quantum spin glasses. Classical spin glasses are typically characterised by a temperature-dependent splitting between two different susceptibilities, which are referred to as zero-field cooled (ZFC) and field-cooled (FC). However, these cannot be measured directly in an isolated quantum system as they involve tuning of the temperature of an external bath coupled to the system. In this contribution we introduce analogues of these susceptibility measurements, tailored for isolated quantum spin systems. We denote them as zero-field annealing (ZFA) and field annealing (FA). We implement these protocols on a Rydberg atom quantum simulator to probe the phase structure of a dipolar-interacting Heisenberg spin model as a function of both energy and disorder. We observe a significant splitting between ZFA and FA susceptibilities in the strongly disordered regime at low energies, indicating multiple equilibrium states. This raises questions about the nature of this regime and its potential connection to a spin glass phase. Generally, the ZFA and FA protocols provide a novel framework for exploring energy-dependent equilibrium properties and hysteresis in isolated quantum many-body systems.

Keywords: Quantum Simulation, Many-body physics, Spin glass physics, Disorder and frustration, Dipolar interacting systems, Hysteresis

[44] Photonic realization of a Hopfield associative memory by multiphoton entanglement and interference.

Authors: Gennaro Zanfardino (Dipartimento di Ingegneria Industriale, Università degli Studi di Salerno), Stefano Paesani (NNF Quantum Computing Programme, Niels Bohr Institute, University of Copenhagen), Luca Leuzzi (Institute of Nanotechnology of the National Research Council of Italy, CNR-NANOTEC, Rome), Raffaele Santagati (Quantum Lab, Boehringer Ingelheim, 55218 Ingelheim am Rhein, Germany), Fabrizio Illuminati (Institute of Nanotechnology of the National Research Council of Italy, CNR-NANOTEC), Giancarlo Ruocco (Center for Life Nano- & Neuro-Science, Italian Institute of Technology, IIT, Rome) and Marco Leonetti (Institute of Nanotechnology of the National Research Council of Italy, CNR-NANOTEC, Rome).

Presenter: Gennaro Zanfardino
Abstract: In this talk we will discuss a recently discovered connection [1] between multiphoton quantum interference—a key component of emerging photonic quantum technologies—and Hopfield-like Hamiltonian models associated with classical neural networks, which are paradigmatic models of associative memory and machine learning in systems of artificial intelligence. A major challenge in this context is that simulating the dynamics of fully connected networks with multi-neuronal synaptic couplings requires a computational time that scales super-extensively with the number of neurons, typically scaling with M, the average per neuron connectivity index. Analog photonic computation offers a promising path to drastically reduce this computational cost as pointed out in a previous study [2] in which incoherent classical light was used to simulate a 2-body Hopfield model. In order to generalize this correspondence to the multi-synaptic, large-storage regime, an additional mechanism is required in the proposed photonic architecture for energy measurement: the use of entangled photons and interferometry. Specifically, we demonstrate that a system composed of N_p indistinguishable photons in superposition over M field modes, combined with a controlled array of M binary phase-shifters and a linear-optical interferometer, produces output photon statistics that can be described by a p-body Hopfield Hamiltonian. This Hamiltonian involves M Ising-like neurons (with states ±1), where the interaction order is given by p = 2N_​p. Hopfield models are characterized by two key parameters: the temperature T, and the storage load α, defined as the number of stored patterns per neuron. These models exhibit three distinct phases: the retrieval phase (low T, low α), the glassy phase (low T, high α), and the paramagnetic phase, which emerges at sufficiently high T. In our proposed photonic implementation, both of these parameters can be experimentally controlled, enabling the exploration of the different phases of the system. We performed a detailed study of the generalized 4-body Hopfield model arising from our design. We show that it undergoes a transition from a memory retrieval phase to a memory blackout (spin-glass) regime as the number of stored patterns increases. Our mapping provides a new avenue toward the implementation and investigation of disordered and complex classical systems via efficient photonic quantum simulators. Conversely, it allows for the interpretation of structured photonic systems through the lens of classical spin Hamiltonians.

References
[1] G. Zanfardino, S. Paesani, L. Leuzzi, R. Santagati, F. Illuminati, G. Ruocco, and M. Leonetti, Multiphoton quantum simulation of the generalized Hopfield memory model, doi.org/10.48550/arXiv.2504.00111 (Doi of the proposed work).

[2] M. Leonetti, E. Hormann, L. Leuzzi, G. Parisi, and G. Ruocco, Optical computation of a spin glass dynamics with tuneable complexity, Proceedings of the National Academy of Sciences 118, e2015207118 (2021).

Keywords: Hopfield model, Spinglass Hamiltonian, Multiphotonic Interference, Quantum Coherence

[45] Glued tree lattices with only compact localized states .

Authors: Andrew Osborne (Princeton University), Ciro Salcedo (Princeton University) and Andrew Houck (Princeton University).

Presenter: Ciro Salcedo
Abstract: Flat band physics is a central theme in modern condensed matter physics. By constructing a tight–binding single particle system that has vanishing momentum dispersion in one or more bands, and subsequently including more particles and interactions, it is possible to study physics in strongly interacting regimes. Inspired by the glued trees that first arose in one of the few known examples of quantum supremacy, we define and analyze two infinite families of tight binding single particle Bose–Hubbard models that have only flat bands, and only compact localized states despite having any nonnegative number of translation symmetries. The first class of model that we introduce is constructed by replacing a sufficiently large fraction of the edges in a generic countable graph with glued trees modified to have complex hoppings. The second class arises from thinking of complex weighted glued trees as rhombi that can then be used to tile two dimensional space, giving rise to the familiar dice lattice and infinitely many generalizations thereof, of which some are Euclidian while others are hyperbolic.

Keywords: Localization, Lattices, Aharonov-Bohm caging, flat bands

[48] Exponential quantum speedups in quantum chemistry with linear depth.

Authors: Oskar Leimkuhler (University of California, Berkeley) and K. Birgitta Whaley (University of California, Berkeley).

Presenter: Oskar Leimkuhler
Abstract: We prove classical simulation hardness, assuming non-collapse of the polynomial hierarchy, for quantum circuit families with applications in near-term chemical ground state estimation. The proof exploits a connection to particle number conserving matchgate circuits with fermionic magic state inputs, which are shown to be universal for quantum computation under post-selection, and are therefore not classically simulable in the worst case, in either the strong (multiplicative) or weak (sampling) sense. We apply this result to quantum multi-reference methods designed for near-term hardware by ruling out certain dequantization strategies for computing the off-diagonal matrix elements. We demonstrate these quantum speedups for two choices of reference state that incorporate both static and dynamic correlations to model the electronic eigenstates of molecular systems: orbital-rotated matrix product states, which are preparable in linear depth, and unitary coupled-cluster with single and double excitations. In each case we discuss the implications for achieving exponential quantum advantage in quantum chemistry on near-term hardware.

Keywords: Quantum algorithms, Near-term, Electronic structure, Complexity theory, Tensor networks

[49] Improved sample-based quantum diagonalization via randomized Hamiltonian simulation.

Authors: Samuele Piccinelli (IBM Research Zurich), Francesco Tacchino (IBM Research Zurich), Alberto Baiardi (IBM Research Zurich), Max Rossmannek (IBM Research Zurich), Almudena Carrera Vazquez (IBM Research Zurich), Ivano Tavernelli (IBM Research Zurich), Antonio Mezzacapo (IBM Research US), Mario Motta (IBM Research US), William Kirby (IBM Research US), Kunal Sharma (IBM Research US) and Javier Robledo Moreno (IBM Research US).

Presenter: Samuele Piccinelli
Abstract: Quantum computing has emerged as a new computing paradigm capable of solving problems that have unfavorable scaling on classical computers. Quantum chemistry represents one of the main and most impactful avenues for applications of these new machines. However, the current landscape of algorithms suffers from a fundamental roadblock created by the trade-off between the limited resources of today’s noisy quantum hardware and algorithmic performance guarantees. In this work, we introduce an algorithm that allows this trade-off to be flexibly adjusted based on the available resources, offering both theoretical robustness and practical compatibility with near-term hardware. Our approach, based on a combination of Hamiltonian simulation via qDRIFT and the recently introduced scheme of sample-based quantum diagonalization, paves the way for enabling efficient quantum chemistry simulations on quantum computers and Krylov-based quantum diagonalization approaches for chemistry.

Keywords: Quantum simulations, Quantum chemistry, Sample-based quantum diagonalization

[51] Quantum matrix arithmetics with Hamiltonian evolution.

Authors: Christopher Kang (University of Chicago) and Yuan Su (Microsoft Quantum).

Presenter: Christopher Kang
Abstract: The efficient implementation of matrix arithmetic operations underpins the speedups of many quantum algorithms. We develop methods to perform quantum matrix arithmetics, with the result encoded in the off-diagonal blocks of a Hamiltonian, using Hamiltonian evolutions of input operators. This covers matrix multiplication, matrix addition, matrix inversion, Hermitian conjugation, fractional scaling, integer scaling, complex phase scaling, and singular value transformation. We show how to coherently reconstruct the Hamiltonian block encoding, so that matrix arithmetic operations can be composed one after another. Consequently, our methods require at most $2$ ancilla qubits throughout the entire quantum computation, in contrast to the standard approach that necessitates fresh ancillas at each step. We also develop an overlap estimation algorithm to extract classical properties of Hamiltonian block encoded operators, with complexity matching the well known Hadmard test, at no extra cost of qubit. When applied to quantum simulation, our methods inherit the commutator scaling from the Lie-Trotter-Suzuki formulas, while leveraging the power of matrix arithmetics to reduce the cost of each Trotter step. To illustrate this feature, we describe a quantum circuit for simulating the doubly factorized tensor hypercontracted electronic structure Hamiltonian, with total gate complexity $\alpha_{\text{comm},\eta}^{1+o(1)}n_Rn_Cn_Bn$. Our dependence on the rank $n_R$, copies $n_C$, base size $n_B$ and spin orbitals $n$ matches qubitization in the double factorization case. Our $\alpha_{\text{comm},\eta}$ is always lower than the normalization factor $\alpha$ of qubitization, and can be substantially lower when the number of particles $\eta$ is small or the coefficient tensors are nearly orthogonal. We achieve this using $1$ single ancilla qubit.

Keywords: Quantum simulation, Quantum algorithm, Lie group commutator product formula, Quantum singular value transformation

[53] Tensor Network enhanced Dynamic Multiproduct Formulas.

Authors: Niall Robertson (IBM Quantum), Bibek Pokharel (IBM Quantum), Bryce Fuller (IBM Quantum), Eric Switzer (NIST), Oles Shtanko (IBM Quantum), Mirko Amico (IBM Quantum), Adam Byrne (IBM Quantum), Andrea D’Urbano (IBM Quantum), Salome Hayes-Shuptar (IBM Quantum), Albert Akhriev (IBM Quantum), Nathan Keenan (IBM Quantum), Sergey Bravyi (IBM Quantum) and Sergiy Zhuk (IBM Quantum).

Presenter: Bibek Pokharel
Abstract: Tensor networks and quantum computation are two of the most powerful tools for the simulation of quantum many-body systems. Rather than viewing them as competing approaches, here we consider how these two methods can work in tandem. We introduce a novel algorithm that combines tensor networks and quantum computation to produce results that are more accurate than what could be achieved by either method used in isolation. Our algorithm is based on multiproduct formulas (MPF) – a technique that linearly combines Trotter product formulas to reduce algorithmic error. Our algorithm uses a quantum computer to calculate the expectation values and tensor networks to calculate the coefficients used in the linear combination. We present a detailed error analysis of the algorithm and demonstrate the full workflow on a one-dimensional quantum simulation problem on 50 qubits using two IBM quantum computers: ibm_torino and ibm_kyiv.

Keywords: Tensor Networks, Dynamics, Quantum-centric supercomputing

[54] Efficient variational low-temperature Gibbs state preparation without entropy measurements.

Authors: Bharath Sambasivam (Virginia Tech), Kyle Sherbert (Virginia Tech), Karunya Shirali (Virginia Tech), Nicholas J. Mayhall (Virginia Tech), Edwin Barnes (Virginia Tech) and Sophia E. Economou (Virginia Tech).

Presenter: Bharath Sambasivam
Abstract: Preparing Gibbs states, which describe systems in equilibrium at finite temperature, is of great importance, particularly at low temperatures. In this work, we propose a new method– TEPID-ADAPT– that prepares the thermal Gibbs state of a given Hamiltonian at low temperatures using a variational method that is partially adaptive and uses a minimal number of ancillary qubits. We achieve this using a truncated, parametrized eigenspectrum of the Hamiltonian. Beyond preparing Gibbs states, this approach also straightforwardly gives us access to the truncated low-energy eigenspectrum of the Hamiltonian, making it also a method that prepares excited states simultaneously. As a result of this, we are also able to prepare thermal states at any lower temperature of the same Hamiltonian without further optimization.

Keywords: Gibbs states, excited states, fixed-depth dynamics, ADAPT-VQE

[57] Fermion-qubit fault-tolerant quantum computing

Authors: Alexander Schuckert (University of Maryland), Eleanor Crane (Massachusetts Institute of Technology), Alexey Gorshkov (University of Maryland), Mohammad Hafezi (University of Maryland) and Michael Gullans (University of Maryland).

Presenter: Alexander Schuckert
Abstract: Simulating the dynamics of electrons and other fermionic particles in quantum chemistry, material science, and high-energy physics is one of the most promising applications of fault-tolerant quantum computers. However, the overhead in mapping time evolution under fermionic Hamiltonians to qubit gates renders this endeavor challenging. We introduce fermion-qubit fault-tolerant quantum computing, a framework which removes this overhead altogether. Using native fermionic operations we first construct a repetition code which corrects phase errors only. We then engineer a fermionic color code which corrects for both phase and loss errors. We show how to realize a universal fermionic gate set in this code, including transversal Clifford gates. Interfacing with qubit color codes we realize qubit-fermion fault-tolerant computation, which allows for qubit-controlled fermionic time evolution, a crucial subroutine in state-of-the-art quantum algorithms for simulating fermions. We show how our framework can be implemented in neutral atoms, overcoming the apparent inability of neutral atoms to implement non-number-conserving gates by introducing a neutral-atom braiding gate using photodissociation of bosonic molecules. As an application, we consider the fermionic fast Fourier transform, an important subroutine for simulating crystalline materials, finding an exponential improvement in circuit depth from O(N) to O(log(N)) with respect to lattice site number N and a linear improvement from O(N^2) to O(Nlog(N)) in Clifford gate complexity compared to state-of-the-art qubit-only approaches. Our work opens the door to fermion-qubit fault-tolerant quantum computation in platforms with native fermions such as neutral atoms, quantum dots and donors in silicon, with applications in quantum chemistry, material science, and high-energy physics.

Keywords: Fault-tolerant quantum simulation, Logical fermions, Quantum error correction, Fermionic quantum computing, Materials Simulation, Quantum Chemistry, Neutral atoms, Quantum dots, Tweezer arrays

[58] Exponential advantage in continuous-variable quantum state learning.

Authors: Eugen Coroi (Korea Advanced Institute of Science and Technology (KAIST)) and Changhun Oh (Korea Advanced Institute of Science and Technology (KAIST)).

Presenter: Eugen Coroi
Abstract: We consider the task of learning quantum states in bosonic continuous-variable (CV) systems. We present a concrete experimentally feasible protocol that utilizes entangled measurements and reflected states to enable efficient learning of the characteristic function of CV quantum states with a sample complexity independent of the number of modes n. We then prove that any general adaptive learning scheme without entangled measurements requires a sample complexity that is exponential in n to accomplish the same task, demonstrating an exponential advantage provided by entangled measurements. Remarkably, we also prove that any general adaptive entanglement-assisted scheme also requires an exponential sample complexity if access to reflected states is prohibited. Hence, we establish a rigorous exponential advantage from entangled measurements and access to reflected states in learning CV quantum states.

Keywords: continuous-variable systems, CV systems, quantum learning, quantum learning theory, state learning, quantum state learning, CV state learning, exponential advantage

[59] Qubit-oscillator hybrid quantum simulator for conical intersection with multilevel nonlinear couplings: a case study of uracil cation.

Authors: Jungsoo Hong (SKKU Advanced Institute of Nano Technology (SAINT), Sungkyunkwan University, Suwon 16419, Republic of Korea), Seong Ho Kim (Department of Chemistry, Ulsan National Institute of Science and Technology, Ulsan, 44919, Republic of Korea), Seung Kyu Min (Department of Chemistry, Ulsan National Institute of Science and Technology, Ulsan, 44919, Republic of Korea) and Joonsuk Huh (Department of Chemistry, Yonsei University, Seoul 03722, Republic of Korea). 

Presenter: Jungsoo Hong
Abstract: Simulating the nonadiabatic dynamics of molecules is crucial for understanding photochemical processes, including nonradiative and ultrafast dissipation. However, it becomes classically intractable as system size increases due to the exponential scaling of vibrational modes. While linear vibronic coupling (LVC) models offer simplification, we provide numerical evidence that they are insufficient for accurately capturing the complex dynamics of the uracil cation, particularly involving its anharmonic potentials and three-state conical intersections. To address this challenge, we propose a quantum simulation approach mapping the nonadiabatic dynamics of the uracil cation, including its nonlinear potentials and multi-level couplings, onto a qubit-oscillator hybrid quantum system. We integrate generalized quantum signal processing (GQSP) within this architecture, utilizing it as a key subroutine to generate the nonlinear bosonic phase gates required to simulate dynamics on anharmonic potentials. We numerically demonstrate the construction of these potentials for the uracil cation and validate our quantum approach via comparative analysis against a classical method on a toy model. This work presents a framework for leveraging qubit-oscillator systems and GQSP to simulate complex, anharmonic potential molecular dynamics beyond the reach of classical methods.

Keywords: quantum computational chemisty, vibronic coupling, conical intersection, quantum signal processing

[61] Resource-efficient Variational Block-Encoding (VBE).

Authors: Leon Rullkötter (Fraunhofer IAO), Bharadwaj Chowdary Mummaneni (Fraunhofer IAO) and Sebastian Weber (University of Stuttgart).

Presenter: Leon Rullkötter
Abstract: Block-encoding operators are one of the essential components in algorithms based on Quantum Signal Processing. Their complexity largely determines the overall complexity of the full algorithm. Using variational methods we aim to compile block-encoding unitaries with near-optimal resource requirements for a large range of input matrices. We find that the number of variational parameters in the parameterized quantum circuit approaches the number of free parameters in the input matrices, depending whether they are real, complex and/or hermitian. Additionally, symmetries present in the input matrix can be incorporated into the ansatz circuit, reducing the parameter count further. While determining variational block-encodings ceases to be computational feasible for large system sizes, the constructed operators can be used as components of larger block-encodings via linear combination of variational block-encodings.

Keywords: Block-Encoding, Variational compilation, Symmetic Quantum Circuits, Hamiltonian Simulation, Quantum Signal Processing

[63] Beam-splitter interferometry for many-body spectroscopy in a quantum dot ladder.

Authors: Stefano Reale (QuTech and Kavli Institute of Nanoscience), Daniel Jirovec (QuTech and Kavli Institute of Nanoscience), Pablo C. Fariña (QuTech and Kavli Institute of Nanoscience), Xin Zhang (QuTech and Kavli Institute of Nanoscience), Elizaveta Morozova (QuTech and Kavli Institute of Nanoscience), Sander L. de Snoo (QuTech and Kavli Institute of Nanoscience), Stefan D. Oosterhout (Netherlands Organisation for Applied Scientific Research (TNO)), Menno Veldhorst (QuTech and Kavli Institute of Nanoscience) and Lieven M. K. Vandersypen (QuTech and Kavli Institute of Nanoscience).

Presenter: Stefano Reale
Abstract: Gate-defined semiconductor quantum dot arrays are a promising platform for digital and analog quantum simulations due to their scalability and precise control capabilities [1]. Recent advancements have enabled the engineering of interacting spin systems expected to exhibit signatures of complex many-body states [2]. However, characterizing the energy spectrum of such systems is challenging, since interactions give rise to many-body eigenstates that are far more complex than the simple spin-flip excitations that define the computational (Zeeman) basis. Here we demonstrate a time-domain spectroscopic technique that provides a one-to-one mapping from computational basis states prepared in the non-interacting regime to the many-body regime. We initialize quantum superpositions through Landau-Zener transitions at spin-orbit-induced anticrossings in Ge/SiGe quantum dots, then adiabatically evolve these states into the interacting regime and back, realizing a protocol similar to many-body Ramsey interferometry [3]. This approach allows us to selectively probe the energy states in the interacting regime and reconstruct the spectrum of a chain of up to 8 spins in a gate-defined Ge/SiGe quantum dot ladder. To our knowledge, this work presents the first comprehensive spectroscopic characterization of many-body states in a semiconductor quantum dot array of this scale, advancing our ability to study quantum phases of matter in scalable solid-state platforms.

[1] Hensgens, T., Fujita, T., Janssen, L. et al., Nature 548, 70–73 (2017).
[2] Appel, M.H., Ghorbal, A., Shofer, N. et al., Nature Physics 21, 368–373 (2025).
[3] Roberts, G., Vrajitoarea, A., Saxberg, B., et al., Science Advances 10, eado1069 (2024).

Keywords: Semiconductor quantum dots, Many-body spectroscopy, Interacting spin systems, Spin-orbit coupling, Solid-state quantum systems

[67] Variational Quantum Annealing for Quantum Chemistry.

Authors: Ka-Wa Yip (Northeastern University), Kubra Yeter-Aydeniz (The Mitre Corporation) and Sijia Dong (Northeastern University).

Presenter: Ka-Wa Yip
Abstract: We introduce a variational quantum annealing (VarQA) algorithm for electronic structure theory, in which we use the quantum annealer as a sampler and prepare an ansatz state through its statistics. We also introduce a strategy called the “digitizer” for searching the space of variational parameters efficiently. We demonstrate the effectiveness of VarQA by evaluating the ground-state potential energy surface
for molecules with up to 20 spin orbitals as well as an excited-state potential energy surface. This approach resembles the workings of the quantum Boltzmann Machines (QBMs), but is generalized to handle distributions beyond the Boltzmann distribution.
In VarQA, with the number of required logical qubits equal to the number of spin orbitals, a fully connected Ising Hamiltonian can be readily implemented in a large-scale quantum annealer as a scalable ansatz for electronic structure calculations.

Keywords: Many-body physics in quantum simulators, Analog quantum simulation, Adiabatic quantum computation, Quantum Annealing, Quantum Chemistry

[69] Exponential entanglement advantage in sensing correlated noise.

Authors: Yuxin Wang (Joint Center for Quantum Information and Computer Science, University of Maryland), Jacob Bringewatt (Harvard University), Alireza Seif (IBM Quantum), Anthony Brady (NIST/University of Maryland), Changhun Oh (Korea Advanced Institute of Science and Technology) and Alexey Gorshkov (NIST/University of Maryland).

Presenter: Yuxin Wang
Abstract: In this work, we propose a new form of exponential quantum advantage in the context of sensing correlated noise. Specifically, we focus on the problem of estimating parameters associated with Lindblad dephasing dynamics, and show that entanglement can lead to an exponential enhancement in the sensitivity (as quantified via quantum Fisher information of the sensor state) for estimating a small parameter characterizing the deviation of system Lindbladians from a class of maximally correlated dephasing dynamics. This result stands in stark contrast with previously studied scenarios of sensing uncorrelated dephasing noise, where one can prove that entanglement does not lead to an advantage in the signal-to-noise ratio. Our work thus opens a novel pathway towards achieving entanglement-based sensing advantage, which may find applications in characterizing decoherence dynamics of near-term quantum devices. Further, our approach provides a potential quantum-enhanced probe of many-body correlated phases by measuring noise generated by a sensing target. We also discuss realization of our protocol using near-term quantum hardware.

Keywords: Quantum sensing, Quantum noise estimation, Entanglement advantage, Correlation-function measurement

[70] Unitary channel certification.

Authors: Sangwoo Jeon (Agency for Defense Development) and Changhun Oh (Korea Advanced Institute of Science and Technology).

Presenter: Sangwoo Jeon
Abstract: Certifying the correct functioning of quantum processes is essential for achieving fault-tolerant quantum information processing. In this work, we address the unitary channel certification problem, which provides the fundamental hardness in quantum process certification. We show that for the worst-case unitary channels, certification requires exponentially many queries. On the other hand, we show that for the average-case unitary channel, certification can be accomplished within a constant number of queries. This exponential gap provides the foundation of efficient channel certification toward fault tolerance.

Keywords: Quantum process certification, Quantum algorithm, Unitary channel

[75] Subspace Variational Quantum Simulation with Fidelity Lower Bounds.

Authors: Seung Park (Institute for Convergence Research and Education in Advanced Technology, Yonsei University), Dongkeun Lee (Division of National Supercomputing, Korea Institute of Science and Tecshnology Information), Jeongho Bang (Institute for Convergence Research and Education in Advanced Technology, Yonsei University), Hoon Ryu (Department of Artificial Intelligence Engineering, Kumoh National Institute of Technology) and Kyunghyun Baek (Institute for Convergence Research and Education in Advanced Technology, Yonsei University).

Presenter: Seung Park
Abstract: We propose an algorithm to simulate the time evolution of a subspace based on the iterative variational method. This algorithm compresses the Trotter circuit into a shorter-depth parameterized quantum circuit (PQC) by optimizing fidelities between time-evolved basis and PQC-prepared states in our target subspace. We also provide the worst-case performance of our algorithm for arbitrary initial states in subspace via lower bounds on the fidelities.

Keywords: Trotterization, Quantum Simulation, Variational Quantum Algorithm, Subspace Time Evolution, Fidelity Lower Bound

[78] Faster Quantum Algorithm for Multiple Observables Estimation in Fermionic Problem.

Authors: Yuki Koizumi (The University of Tokyo), Kaito Wada (Keio University), Wataru Mizukami (Osaka University) and Nobuyuki Yoshioka (The University of Tokyo).

Presenter: Nobuyuki Yoshioka
Abstract: Achieving quantum advantage in efficiently estimating collective properties of quantum many-body systems remains a fundamental goal in quantum computing. While the quantum gradient estimation (QGE) algorithm has been shown to achieve doubly quantum enhancement in the precision and the number of observables to be estimated under an adaptive scheme, it remains unclear whether one benefits in practical applications such as quantum many-body simulation. In this work, we present a generalized framework of the adaptive QGE algorithm and further propose two variants which enable us to estimate the collective properties of fermionic systems using the smallest cost among existing quantum algorithms. The first method utilizes the symmetry inherent in the target state to speed up the process of encoding the information of observables into the phase of a probe system, and the second method successfully incorporates a parallel scheme of observable estimation with the adaptive strategy. We show that our proposal offers quadratic speedup compared with the prior QGE algorithm in the task of partial tomography without additional space complexity. Furthermore, we provide numerical demonstrations that, for the problem of estimating the 2-local reduced density matrix, our proposals improve the number of calls to the state-preparation oracle of the target state by a factor of 100 for the nitrogenase FeMo cofactor and by a factor of 500 for the Fermi-Hubbard model of 100 sites. Our work paves the way towards universal quantum enhancement for practitioners of quantum computation.

Keywords: Quantum Algorithm, Heisenberg limit, partial tomography, QSVT, many-body problem

[79] Probing Entanglement Scaling Across a Quantum Phase Transition on a Quantum Computer.

Authors: Qiang Miao (Duke University), Tianyi Wang (Duke University), Kenneth Brown (Duke University), Thomas Barthel (Duke University) and Marko Cetina (Duke University).

Presenter: Qiang Miao
Abstract: The investigation of strongly-correlated quantum matter is difficult due to the curse of dimensionality and intricate entanglement structures. These challenges are particularly pronounced in the vicinity of continuous quantum phase transitions, where quantum fluctuations manifest across all length scales. While quantum simulators give controlled access to a number of strongly correlated systems, the study of critical phenomena has been hampered by finite-size effects arising from diverging correlation lengths. Moreover, the experimental investigation of entanglement in many-body systems has been hindered by limitations in measurement protocols. To address these challenges, we employ the multiscale entanglement renormalization ansatz (MERA) and implement a holographic scheme for subsystem tomography on a fully-connected trapped-ion quantum computer. Our method accurately represents infinite systems and long-range correlations with few qubits, facilitating the efficient extraction of observables and entanglement properties, even at criticality. We observe a quantum phase transition with spontaneous symmetry breaking and reveal the evolution of entanglement properties across the critical point. For the first time, we demonstrate log-law scaling of subsystem entanglement entropies at criticality on a digital quantum computer. This achievement highlights the potential of MERA for the investigation of strongly-correlated many-body systems on quantum computers.

Keywords: Entanglement entropy, Quantum phase transition, Trapped-ion quantum computer, Tensor network state

[82] Quantum Entanglement in Rydberg Atom Arrays.

Authors: Hyeonjun Yeo (Department of Physics and Astronomy, Seoul National University), Kabgyun Jeong (Research Institute of Mathematics, Seoul National University) and Hyunchul Nha (Department of Physics, Texas A & M University at Qatar).

Presenter: Kabgyun Jeong
Abstract: Characterizing quantum transitions across different quantum phases is of crucial importance in many-body physics. This is usually addressed in terms of order parameters using physical quantities such as magnetization in spin-chain systems. We here propose entanglement-based order parameters that manifest different quantum phases providing insight into quantum correlation among constituent parts in strongly correlated systems. Our approach thereby offers a valuable tool to look into many-body physics across quantum phase transitions both theoretically and experimentally. As an illustration we investigate quantum entanglement for the array of Rydberg atoms in 2D optical tweezer arrays by employing concurrence as an entanglement quantifier while our proposal can be applied to any measure of entanglement. We also present an experimentally accessible method to witness phase transitions in the Rydberg atom array.

Keywords: Quantum simulation, Quantum entanglement, Rydberg atom arrays

[87] Two-dimensional Discrete Time Crystals with Anisotropic Heisenberg Coupling.

Authors: Eric Switzer (National Institute of Standards and Technology), Niall Robertson (IBM Quantum, IBM Research Europe), Nathan Keenan (IBM Quantum, IBM Research Europe), Ángel Rodríguez (Centro de Física de Materiales CFM/MPC (CSIC-UPV/EHU)), Andrea D’Urbano (IBM Quantum, IBM Research Europe), Bibek Pokharel (IBM T.J. Watson Research Center), Talat S. Rahman (University of Central Florida), Oles Shtanko (IBM T.J. Watson Research Center), Sergiy Zhuk (IBM Quantum, IBM Research Europe) and Nicolás Lorente (Donostia International Physics Center; Centro de Física de Materiales CFM/MPC (CSIC-UPV/EHU)).

Presenter: Eric D. Switzer
Abstract: Discrete time crystals (DTCs) represent a striking example of non-equilibrium quantum phases, characterized by robust subharmonic oscillations that spontaneously break discrete time-translation symmetry. We demonstrate a two-dimensional DTC with variable anisotropic Heisenberg interactions in a driven quantum many-body system, realized on the IBM Fez superconducting processor using 144 qubits on a decorated heavy-hexagon lattice. We observe clear evidence of DTC behavior and demonstrate that the polarized initial state displays long-lived oscillations, reflecting weak ergodicity breaking reminiscent of many-body scars. To support and validate our hardware experiments, we perform classical simulations using both Matrix Product States and two-dimensional tensor network states for small system sizes and specific low-entanglement regimes. We also utilize a novel noisy signal recovery method to extract high-precision noiseless collective observables from hardware measurements. Our results highlight how periodic driving, disorder, and quantum correlations stabilize exotic non-equilibrium phases in realistic quantum systems.

Keywords: discrete time crystal, non-equilibrium quantum phase, many-body scars, matrix product states, two-dimensional tensor network states, superconducting processor

[89] Exponential Speedup in Digital Quantum Simulation of Non-Abelian Gauge Theories.

Authors: Masanori Hanada (Queen Mary University of London). 

Presenter: Jad Halimeh
Abstract: Nearly two decades after the seminal work by Byrnes and Yamamoto, a scalable digital quantum simulation protocol for non-Abelian gauge theories, such as QCD, in more than one spatial dimension has remained elusive. Most approaches have focused on the Kogut-Susskind formulation, yet all known protocols to date suffer from exponentially growing costs (specifically, circuit depth and the number of classical input parameters) in terms of the number of qubits. This makes practical simulation of physically relevant regimes infeasible, even with fault-tolerant universal quantum computers.
In this talk, we present a class of digital quantum simulation protocols that achieve an exponential speedup in resource efficiency. Our approach is based on the orbifold lattice Hamiltonian, a generalization that encompasses the Kogut-Susskind Hamiltonian as a special case. The resulting quantum circuits are remarkably simple and written down by hand; they can be constructed explicitly using only CNOT gates and single-qubit rotations whose numbers are proportional to the lattice volume. Our protocol is universally applicable to SU(N) gauge theories in arbitrary spatial dimensions and with arbitrary matter content. These results mark a substantial step forward toward feasible quantum simulation of non-Abelian gauge dynamics, with potential implications for high-energy physics, quantum field theory, and beyond.
Reference: 2011.06576 [hep-th], 2401.12045 [hep-th], 2411.13161 [quant-ph], and three papers to appear

[96] Quantum Gibbs Sampling with Local Circuits.

Authors: Dominik Hahn (Oxford University), Ryan Sweke (African Institute for Mathematical Sciences, South Africa), Abhinav Deshpande (BM Quantum, IBM Research – Almaden, San Jose) and Oles Shtanko (IBM Quantum, IBM Thomas J. Watson Research Center, Yorktown Height).

Presenter: Dominik Hahn
Abstract: State preparation is a foundational task in the simulation of quantum many-body systems. Recently, specific classes of quasilocal Lindbladian operators have been proposed that drive systems toward Gibbs states al long times. In this talk, I will demonstrate an implementation of that dynamics on near-term quantum devices.
To achieve this, I show that a truncation of the jump operators to strictly local terms introduces controllable and well-characterized errors. This locality enables a Trotterization approach to simulate the Lindbladian dynamics via quantum circuits. I further demonstrate that these circuits can be compiled with moderate gate overhead, making them feasible for implementation on current noisy intermediate-scale quantum (NISQ) hardware.
Finally, I present numerical results that explore the robustness of this method under realistic noise models and discuss the trade-offs between convergence time, gate cost, and accuracy in achieving thermal states.

Keywords: Thermal state preparation, Quantum Gibbs sampling, Quantum simulation

[97] Threshold for Fault-tolerant Quantum Advantage with the Quantum Approximate Optimization Algorithm

Authors: Sivaprasad Omanakuttan (JP Morgan Chase), Zichang He (JP Morgan Chase), Zhiwei Zhang (JP Morgan Chase), Tianyi Hao (JP Morgan Chase), Arman Babakhani (JP Morgan Chase), Shouvanik Chakrabarti (JP Morgan Chase), Dylan Herman (JP Morgan Chase), Joseph Sullivan (JP Morgan Chase), Michael Perlin (JP Morgan Chase), Ruslan Shaydulin (JP Morgan Chase), Marco Pistoia (JP Morgan Chase) and Sami Boulebnane (JP Morgan Chase).

Presenter: Shouvanik Chakrabarti
Abstract: Hamiltonian evolution is one of the most common primitives in quantum algorithms. For example, optimal quantum algorithm for linear systems relies on adiabatic evolution with a continuously varying Hamiltonian. Consequently, careful compilation of Hamiltonian evolution circuits can dramatically reduce the resource requirements of quantum algorithms, impacting the threshold for quantum advantage. In this work, we compile and analyze the Quantum Approximate Optimization Algorithm (QAOA) combined with Amplitude Amplification (AA) applied to random 8-SAT at the satisfiability threshold. Our compilation involves careful optimization of circuits for Hamiltonian simulation, which may be of independent interest. We use the analytical scaling of the time-to-solution for QAOA identified by PRX Quantum 5, 030348 (2024) and find that with QAOA depth p=623, QAOA+AA achieves a crossover with state-of-the-art classical heuristics at 179 variables and 14.99 hours of runtime when executed on a surface-code-based fault-tolerant quantum computer with 73.91 million physical qubits, a physical error rate of 10−3, and a 1 μs code cycle time. Notably, we allow the classical solver to be parallelized as long as its total energy consumption is equal to that required for decoding in the surface code. We further show that this restriction on classical solver energy consumption can be relaxed given optimistic but plausible reductions in physical error rates and fault-tolerance overheads, enabling a crossover of 2.94 hours using 8.88 million physical qubits against a classical solver running on a supercomputer with 725,760 CPU cores. These findings support the hypothesis that large-scale fault-tolerant quantum computers will be useful for optimization based on Hamiltonian evolution.

Keywords: QAOA, Random Satisfiability, Surface Code, Fault Tolerant Quantum Computation, Fault Tolerant compilation

[98] Quantum-centric computation of molecular excited states with extended sample-based quantum diagonalization. 

Authors: Stefano Barison (Institute of Physics, Ecole Polytechnique Federale de Lausanne (EPFL)), Javier Robledo Moreno (IBM Quantum, IBM T. J. Watson Research Center) and Mario Motta (IBM Quantum, IBM T. J. Watson Research Center).

Presenter: Javier Robledo Moreno
Abstract: The quantum simulation of molecular electronic structure is an important application of quantum devices. Recent developments have demonstrated that quantum devices can be effectively combined with classical supercomputing resources in the context of the sample-based quantum diagonalization (SQD) algorithm. This allowed the largest electronic structure quantum simulation to date (77 qubits) and opened near-term devices to practical use cases in chemistry toward the hundred-qubit mark. However, the description of many important physical and chemical properties of those systems, such as photo-absorption/-emission, requires a treatment that goes beyond the ground state alone. In this work, we extend the SQD algorithm to determine low-lying molecular excited states. The extended-SQD method improves over the original SQD method in accuracy, at the cost of an additional computational step. It also improves over quantum subspace expansion based on single and double electronic excitations, a widespread approach to excited states on pre-fault-tolerant quantum devices, in both accuracy and efficiency. The extended SQD method is used to compute the first singlet (S1) and triplet (T1) excited states of the nitrogen molecule with a correlation-consistent basis set, and the ground- and excited-state properties of the [2Fe-2S] cluster

Keywords: Quantum Simulation, Quantum Chemistry, Excited States

[105] Towards Optimal Lindbladian Simulation.

Authors: Evan Borras (University of New Mexico) and Milad Marvian (University of New Mexico).

Presenter: Evan Borras
Abstract: Quantum simulation has emerged as a key application of quantum computing, with significant progress made in algorithms for simulating both closed and open quantum systems. The simulation of open quantum systems, particularly those governed by the Lindblad master equation, has received attention recently with the current state-of-the-art algorithms having an input model query complexity of O(Tpolylog(T/ε)), where T and ε are the requested time and precision of the simulation respectively. For Hamiltonian simulation it has been show that the optimal Hamiltonian query complexity is O(T + log(1/ε)), additive in nature between the two parameter, but for Lindbladian simulation this question remains open. In this work we provide evidence that the additive complexity of O(T + log(1/ε)) is reachable for the Lindbladian simulation problem by constructing a novel quantum algorithm achieving this query complexity for a large class of Lindbladians.

Keywords: Quantum simulation, Quantum algorithms, Open Quantum Systems

[113] Quantum Krylov Algorithm for Szegö Quadrature.

Authors: William Kirby (IBM Quantum), Roel Van Beeumen (Lawrence Berkeley National Laboratory), Daan Camps (Lawrence Berkeley National Laboratory), Anirban Chowdhury (IBM Quantum), Katherine Klymko (Lawrence Berkeley National Laboratory) and Yizhi Shen (Lawrence Berkeley National Laboratory).

Presenter: William Kirby
Abstract: We present a quantum algorithm to evaluate matrix elements of functions of unitary operators. The method is based on using the quantum computer to calculate nodes and weights comprising a quadrature rule, which can then be used to approximate matrix elements of any desired function of a fixed unitary operator between a fixed pair of states. The unitary operator could approximate a time evolution, opening the door to applications like estimating properties of Hamiltonian spectra and Gibbs states, but more generally could be any operator implementable via a quantum circuit. While the pair of states identifying the matrix element must be known a priori, once the quadrature rule is constructed it can be used to approximate the matrix element for any function of the unitary, with only the accuracy of the approximation depending on the choice of unitary. We expect this algorithm to be useful as a subroutine in other quantum algorithms, much like quantum signal processing or the quantum eigenvalue transformation of unitaries.

Keywords: quantum Krylov algorithms, numerical quadrature, quantum numerical linear algebra, quantum signal processing

[116] A sample-based quantum diagonalization framework for periodic solids.

Authors: Alan Duriez (IBM Research), Pamela Carvalho (IBM Research), Marco Antonio Barroca (IBM Research), Federico Zipoli (IBM Research), Ben Jaderberg (IBM Quantum), Rodrigo Barros Ferreira (IBM Research), Kunal Sharma (IBM Quantum), Antonio Mezzacapo (IBM Quantum), Benjamin Wunsch (IBM Research) and Mathias Steiner (IBM Research).

Presenter: Alan Duriez
Abstract: State-of-the-art techniques in computational materials science often fail to capture many-body interactions in periodic systems. One particular application is the electronic structure problem, where established approaches such as Density Functional Theory are applied to predict experimental results. In this contribution, we present a sample-based quantum diagonalization (SQD) workflow for simulating the electronic ground state of periodic materials, and for predicting their band gaps. We obtain a fermionic Hamiltonian for crystalline solids by first projecting the electronic density obtained by density functional theory onto a localized basis set and then adding interaction parameters obtained by a self-consistent field theory. We then build an approximation of the system’s ground-state wavefunction with the local unitary cluster Jastrow (LUCJ) ansatz. By sampling the quantum circuit and classically diagonalizing the Hamiltonian in the resulting configuration subspace, we predict the band gap energy of representative materials and obtain agreement with experimental results. The predicted bandgaps were obtained from calculations using 38 and 46 qubits, performed on a superconducting quantum processor, with minimal error-mitigation overhead. Our self-consistent approach offers a scalable pathway for utility-scale quantum simulation of materials.

Keywords: material science, quantum simulation, quantum computing

[124] Operator-Level Quantum Acceleration of Non-Logconcave Sampling.

Authors: Jiaqi Leng (University of California, Berkeley), Zhiyan Ding (University of California, Berkeley), Zherui Chen (University of California, Berkeley) and Lin Lin (University of California, Berkeley)

Presenter: Jiaqi Leng

Abstract: Sampling from distributions in the form $\sigma \propto e^{-\beta V}$ is a fundamental task in physics, chemistry, biology, computer science, and statistics. In general settings where $V$ is nonconvex (i.e., non-logconcave sampling), classical approaches such as Langevin dynamics are known to struggle. Despite the progress in quantum algorithms for accelerating discrete Markov chains over the past two decades, a quantum counterpart for accelerating Langevin dynamics has remained elusive. We introduce the first quantum algorithm that accelerates Langevin dynamics for general continuous potentials with provable speedups. Instead of attempting to solve the Langevin stochastic differential equation or the underlying Fokker–Planck equation on a quantum computer, our method encodes the target Gibbs measure into the amplitudes of a quantum state.  This encoded Gibbs state is characterized as the kernel of a specially constructed block matrix, which is closely related to the Witten Laplacian operator. Building on this framework, we also develop the first quantum algorithm that accelerates the classical replica exchange dynamics, a widely used classical technique beyond Langevin dynamics for sampling from rugged energy landscapes.

Keywords: Quantum algorithms, Non-logconcave sampling, Gibbs sampling, Ground state preparation, Quantum numerical linear algebra

[131] A mixed-species quantum simulator.

Authors: Yi Zhu (Harvard University), Haley Nguyen (Harvard University), Charles Staub (Harvard University), Bob Bao (Harvard University) and Giulia Semeghini (Harvard University).

Presenter: Yi Zhu
Abstract: We present our ongoing efforts toward creating a continuously reloaded, programmable neutral atom array based on a mixture of Rb and Yb. Single-species atom arrays have recently enabled exciting applications in quantum information, simulation, and metrology. The addition of a second atomic species opens new possibilities for implementing selective qubit control, engineering asymmetric inter- and intra-species Rydberg interactions, and exploring novel architectures for quantum simulation. Additionally, continuous replenishment of both atomic species is central to improving scalability and circuit depths, while decreasing cycle times. We present progress toward realizing this new quantum platform and discuss its applications to quantum simulation—from simulating lattice gauge theories to exploring fermionic models.

Keywords: atom array, dual-species, continuous reloading, Yb-Rb