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All sources NASA NTRS DOE OSTI

DOE OSTI2020

Chiral topologically ordered insulating phases in arrays of interacting integer quantum Hall islands

Here, we study networks of Coulomb-blockaded integer quantum Hall islands with even fillings ν = 2 k ( k being an integer), including cases with 2 k layers each of ν = 1 fillings. Allowing only spin-current interactions between the islands (i.e., without any charge transfer), we obtain solvable models leading to a rich set of insulating S U ( 2 ) k topologically ordered phases. The case with k = 1 is dual to the Kalmeyer-Laughlin phase, k = 2 to Kitaev's chiral spin liquid and the Moore-Read state, and k = 3 contains a Fibonacci anyon that may be utilized for universal topological quantum computation. Additionally, we show how the S U ( 2 ) k topological phases may be obtained also in an array of islands with ν = 2 k integer quantum Hall states and critical spin chains in a checkerboard pattern. The array and checkerboard constructions gap out the charge mode and additional “flavor” modes by virtue of their geometry. Furthermore, we find that a fine tuning of the system parameter is not needed in the checkerboard configuration and the ν = 2 case. We also discuss their bulk excitations, and show that their thermal Hall conductance is universal, reflecting the central charge c = 3 k / ( k + 2 ) of the chiral edge modes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Scalable stable comb-to-tone integrated RF photonic drive for superconducting qubits

The recent advent of quantum computing has the potential to overhaul security, communications, and scientific modeling. Superconducting qubits are a leading platform that is advancing noise-tolerant intermediate-scale quantum processors. The implementation requires scaling to large numbers of superconducting qubits, circuit depths, and gate speeds, wherein high-purity RF signal generation and effective cabling transport are desirable. Fiber photonic-enhanced RF signal generation has demonstrated the principle of addressing both signal generation and transport requirements, supporting intermediate qubit numbers and robust packaging efforts; however, fiber-based approaches to RF signal distribution are often bounded by their phase instability. Here, we present a silicon photonic integrated circuit-based version of a photonic-enhanced RF signal generator that demonstrates the requisite stability, as well as a path towards the necessary signal fidelity.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Modular chip-integrated photonic control of artificial atoms in diamond waveguides

A central goal in creating long-distance quantum networks and distributed quantum computing is the development of interconnected and individually controlled qubit nodes. Atom-like emitters in diamond have emerged as a leading system for optically networked quantum memories, motivating the development of visible-spectrum, multi-channel photonic integrated circuit (PIC) systems for scalable atom control. However, it has remained an open challenge to realize optical programmability with a qubit layer that can achieve high optical detection probability over many optical channels. Here, we address this problem by introducing a modular architecture of piezoelectrically actuated atom-control PICs (APICs) and artificial atoms embedded in diamond nanostructures designed for high-efficiency free-space collection. The high-speed four-channel APIC is based on a splitting tree mesh with triple-phase shifter Mach–Zehnder interferometers. This design simultaneously achieves optically broadband operation at visible wavelengths, high-fidelity switching (>40dB) at low voltages, submicrosecond modulation timescales (>30MHz), and minimal channel-to-channel crosstalk for repeatable optical pulse carving. Via a reconfigurable free-space interconnect, we use the APIC to address single silicon vacancy color centers in individual diamond waveguides with inverse tapered couplers, achieving efficient single photon detection probabilities (∼15%) and second-order autocorrelation measurements g (2) (0)<0.14 for all channels. The modularity of this distributed APIC–quantum memory system simplifies the quantum control problem, potentially enabling further scaling to thousands of channels.

47 OTHER INSTRUMENTATION↗

NASA NTRS1996

Dynamical Simulation of Probabilities

It has been demonstrated that classical probabilities, and in particular, probabilistic Turing machine, can be simulated by combining chaos and non-Lipschitz dynamics, without utilization of any man-made devices(such as random number generators). Self-orgainizing properties of systems coupling simulated and calculated probabilities and their link to quantum computations are discussed. Special attention was focused upon coupled stochastic processes, defined in terms of conditional probabilities, for which joint probability does not exist. Simulations of quantum probabilities are also discussed.

number generators quantum probabilities↗

NASA NTRS2024

Modeling Entanglement-Based Quantum Key Distribution for the NASA Quantum Communications Analysis Suite

One of the most practical, and sought after, applications of quantum mechanics in the field of information science is the use of entanglement distribution to communicate quantum information effectively. Similar to the continued improvements of functional quantum computers over the past decade, advances in demonstrations of entanglement distribution over long distances may enable new applications in aeronautics and space communications. The existing NASA Quantum Communications Analysis Suite (NQCAS) software models such applications, but limited experimental data exists to verify the model’s theoretical results. There is, however, a large body of experimental data in the relevant literature for entanglement-based quantum key distribution (QKD). This paper details a Monte Carlo based QKD model that uses NQCAS input parameters to generate an estimated QKD link budget for verification of NQCAS. The model generates link budget statistics like key rates, error rates, and S values that can then be compared to the experimental values in the literature. Preliminary comparisons show many similarities between the simulated and experimental data, supporting the model’s validity. A verified NQCAS model will inform experimental work conducted in Glenn Research Center’s (GRC) NASA Quantum Metrology Laboratory (NQML), supporting the United States Quantum Initiative and potential NASA missions.

NASA Quantum Communications Analysis Suite↗

DOE OSTI2025

Classical and quantum simulations of 1+1-dimensional ${\mathbb{Z}}_{2}$ gauge theory at finite temperature and density

Simulating strongly coupled gauge theories at finite temperature and density is a longstanding challenge in nuclear and high-energy physics with fundamental implications for condensed matter physics. Here, we simulate such systems using minimally entangled typical thermal state (METTS) approaches, which combine classical random sampling with imaginary-time evolution, implementable on either classical or quantum computers, to estimate thermal averages of observables. We study 1+1-dimensional ${\mathbb{Z}}_{2}$ gauge theory coupled to spinless fermionic matter, which maps onto a local quantum spin chain. We benchmark both a classical matrix-product-state implementation of METTS and a recently proposed adaptive variational approach for near-term quantum devices, focusing on the equation of state and measures of fermion confinement. Of particular importance is the choice of basis for METTS sampling, which impacts both the sampling overhead and quantum circuit complexity. Our work sets the stage for future studies of strongly coupled gauge theories using classical and quantum hardware.

Chen, I-Chi [Iowa State Univ., Ames, IA (United St↗

DOE OSTI2024

Single-ancilla ground state preparation via Lindbladians

We design a quantum algorithm for ground state preparation in the early fault tolerant regime. As a Monte Carlo style quantum algorithm, our method features a Lindbladian where the target state is stationary. The construction of this Lindbladian is algorithmic and should not be seen as a specific approximation to some weakly coupled system-bath dynamics in nature. Our algorithm can be implemented using just one ancilla qubit and efficiently simulated on a quantum computer. It can prepare the ground state even when the initial state has zero overlap with the ground state, bypassing the most significant limitation of methods like quantum phase estimation. As a variant, we also propose a discrete-time algorithm, demonstrating even better efficiency and providing a near-optimal simulation cost depending on the desired evolution time and precision. Numerical simulations using Ising and Hubbard models demonstrate the efficacy and applicability of our method. Published by the American Physical Society 2024

Ding, Zhiyan (ORCID:000000018863403X)↗

DOE OSTI2024

Quantum Complexity of the Kronecker Coefficients

Whether or not the Kronecker coefficients of the symmetric group count some set of combinatorial objects is a longstanding open question. In this work we show that a given Kronecker coefficient is proportional to the rank of a projector that can be measured efficiently using a quantum computer. In other words a Kronecker coefficient counts the dimension of the vector space spanned by the accepting witnesses of a QMA verifier, where QMA is the quantum analogue of NP . This implies that approximating the Kronecker coefficients to within a given relative error is not harder than a certain natural class of problems that captures the complexity of estimating thermal properties of quantum many-body systems. A second consequence is that deciding positivity of Kronecker coefficients is contained in QMA , complementing a recent NP -hardness result of Ikenmeyer, Mulmuley, and Walter. We obtain similar results for the related problem of approximating row sums of the character table of the symmetric group. Finally, we discuss an efficient quantum algorithm that approximates normalized Kronecker coefficients to inverse-polynomial additive error. Published by the American Physical Society 2024

Physics↗

DOE OSTI2025

Power and Limitations of Linear Programming Decoder for Quantum LDPC Codes

Decoding quantum error-correcting codes is a key challenge in enabling fault-tolerant quantum computation. In the classical setting, linear programming (LP) decoders offer provable performance guarantees and can leverage fast practical optimization algorithms. Although LP decoders have been proposed for quantum codes, their performance and limitations remain relatively underexplored. In this work, we uncover a key limitation of LP decoding for quantum low-density parity-check (LDPC) codes: certain constant-weight error patterns lead to ambiguous fractional solutions that cannot be resolved through independent rounding. To address this issue, we incorporate a post-processing technique known as ordered statistics decoding (OSD), which significantly enhances LP decoding performance in practice. Our results show that LP decoding, when augmented with OSD, can outperform belief propagation with the same post-processing for intermediate code sizes of up to hundreds of qubits. These findings suggest that LP-based decoders, equipped with effective post-processing, offer a promising approach for decoding near-term quantum LDPC codes.

Gu, Shouzhen [Yale U.]↗

DOE OSTI2025

Power and Limitations of Linear Programming Decoder for Quantum LDPC Codes

Gu, Shouzhen [Yale U.]↗

DOE OSTI2025

Power and Limitations of Linear Programming Decoder for Quantum LDPC Codes

Gu, Shouzhen [Yale U.]↗

DOE OSTI2022

Modeling quantum state transport with SQMS devices

To scale up the Hilbert space of architectures for quantum computation involving microwave cavities, we need to control more and more photons states. A big step forward in this direction would be to connect two different cavities from a quantum mechanics point of view. In this report, we will discuss which experimental approach would be feasible to transfer a quantum state from one cavity to another. To perform this task, we will take advantage of the secondary modes of the cavities, discussing how a variable coupling between the cavity modes could help us in this process. In the end, we will see how we can create entanglement between the cavities from this procedure.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2026

Robust Design Under Uncertainty in Quantum Error Mitigation

Error mitigation techniques are crucial to achieving near-term quantum advantage. Classical postprocessing of quantum computation outcomes is a popular approach for error mitigation, which includes methods, such as zero noise extrapolation, virtual distillation, and learning-based error mitigation. However, these techniques have limitations due to the propagation of uncertainty resulting from the finite shot number of a quantum measurement. In this work, we introduce general and unbiased methods for quantifying the uncertainty and error of error-mitigated observables based on the strategic sampling of error mitigation outcomes. We then extend our approach to demonstrate the optimization of performance and robustness of error mitigation under uncertainty. To illustrate our methods, we apply them to zero noise extrapolation and Clifford date regression in the ground state of the XY model simulated using depolarizing and International Business Machines Corporation (IBM) Toronto noise models, respectively. In particular, we optimize the choice of noise levels and the allocation of shots for zero noise extrapolation and the distribution of the training circuits for Clifford data regression. While our methods are readily applicable to any postprocessing-based error mitigation approach, in practice they must not be prohibitively expensive—even though they perform optimizations of the error mitigation hyperparameters requiring sampling of a statistical distribution of error mitigation outcomes. By leveraging surrogate-based optimization, we show that our methods can efficiently perform optimal design for a zero noise extrapolation implementation. We then further demonstrate the transferability of learned zero noise extrapolation hyperparameters to other similar circuits.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Energy Use in Quantum Data Centers: Scaling the Impact of Computer Architecture, Qubit Performance, Size, and Thermal Parameters

As quantum computers increase in size, the total energy used by a quantum data center, including the cooling, will become a greater concern. The cooling requirements of quantum computers, which operate at temperatures near absolute zero, are determined by computing system parameters, including the number and type of physical qubits, the packaging efficiency of the system, and the split between circuits operating at cryogenic temperatures and those operating at room temperature. When combined with thermal system parameters such as cooling efficiency and cryostat heat transfer, the total energy use can be determined using a first-principles energy model. These models show that cooling of quantum computers differs in two fundamental ways from conventional data centers: (1) the energy required for cooling is much greater than the energy required for computation, and (2) the cooling loads are sensitive to the computational architecture. The temperature requirements for different qubit types can change energy requirements by orders of magnitude. Power use and computational power, as quantified by quantum volume, are analytically correlated. Approaches are identified for minimizing energy use in integrated quantum systems relative to computational power. Furthermore, designing a sustainable quantum computer will require both efficient cooling and system design that minimizes cooling requirements.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Design of an ultra-low mode volume piezo-optomechanical quantum transducer

Coherent transduction of quantum states from the microwave to the optical domain can play a key role in quantum networking and distributed quantum computing. We present the design of a piezo-optomechanical device formed in a hybrid lithium niobate on silicon platform, that is suitable for microwave-to-optical quantum transduction. Our design is based on acoustic hybridization of an ultra-low mode volume piezoacoustic cavity with an optomechanical crystal cavity. The strong piezoelectric nature of lithium niobate allows us to mediate transduction via an acoustic mode which only minimally interacts with the lithium niobate, and is predominantly silicon-like, with very low electrical and acoustic loss. We estimate that this transducer can realize an intrinsic conversion efficiency of up to 35% with <0.5 added noise quanta when resonantly coupled to a superconducting transmon qubit and operated in pulsed mode at 10 kHz repetition rate. The performance improvement gained in such hybrid lithium niobate-silicon transducers make them suitable for heralded entanglement of qubits between superconducting quantum processors connected by optical fiber links.

Chiappina, Piero↗

DOE OSTI2021

Quantum Divide and Compute: Exploring the Effect of Different Noise Sources

Abstract Our recent work (Ayral et al. in Proceedings of IEEE computer society annual symposium on VLSI, ISVLSI, pp 138–140, 2020. 10.1109/ISVLSI49217.2020.00034 ) showed the first implementation of the Quantum Divide and Compute (QDC) method, which allows to break quantum circuits into smaller fragments with fewer qubits and shallower depth. This accommodates the limited number of qubits and short coherence times of quantum processors. This article investigates the impact of different noise sources—readout error, gate error and decoherence—on the success probability of the QDC procedure. We perform detailed noise modeling on the Atos Quantum Learning Machine, allowing us to understand tradeoffs and formulate recommendations about which hardware noise sources should be preferentially optimized. We also describe in detail the noise models we used to reproduce experimental runs on IBM’s Johannesburg processor. This article also includes a detailed derivation of the equations used in the QDC procedure to compute the output distribution of the original quantum circuit from the output distribution of its fragments. Finally, we analyze the computational complexity of the QDC method for the circuit under study via tensor-network considerations, and elaborate on the relation the QDC method with tensor-network simulation methods.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Scaling adaptive quantum simulation algorithms via operator pool tiling

Adaptive variational quantum simulation algorithms use information from a quantum computer to dynamically create optimal trial wave functions for a given problem Hamiltonian. A key ingredient in these algorithms is a predefined operator pool from which trial wave functions are constructed. Finding suitable pools is critical for the efficiency of the algorithm as the problem size increases. Here, we present a technique called operator pool tiling that facilitates the construction of problem-tailored pools for arbitrarily large problem instances. By first performing an Adaptive Derivative-Assembled Problem-Tailored Ansatz Variational Quantum Eigensolver (ADAPT-VQE) calculation on a smaller instance of the problem using a large, but computationally inefficient, operator pool, we extract the most relevant operators and use them to design more efficient pools for larger instances. We demonstrate the method here on strongly correlated quantum spin models in one and two dimensions, finding that ADAPT automatically finds a highly effective ansatz for these systems. Given that many problems, such as those arising in condensed matter physics, have a naturally repeating lattice structure, we expect the pool tiling method to be a widely applicable technique apt for such systems. Published by the American Physical Society 2024

Van Dyke, John S. (ORCID:0000000167815480)↗

DOE OSTI2020

A quantum algorithm to efficiently sample from interfering binary trees

Quantum computers provide an opportunity to efficiently sample from probability distributions that include non-trivial interference effects between amplitudes. Using a simple process wherein all possible state histories can be specified by a binary tree, we construct an explicit quantum algorithm that runs in polynomial time to sample from the process once. The corresponding naive Markov Chain algorithm does not produce the correct probability distribution and an explicit classical calculation of the full distribution requires exponentially many operations. Finally, the problem can be reduced to a system of two qubits with repeated measurements, shedding light on a quantum-inspired efficient classical algorithm.

97 MATHEMATICS AND COMPUTING↗