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DOE OSTI2021

Quantum simulation of molecules without fermionic encoding of the wave function

Abstract Molecular simulations generally require fermionic encoding in which fermion statistics are encoded into the qubit representation of the wave function. Recent calculations suggest that fermionic encoding of the wave function can be bypassed, leading to more efficient quantum computations. Here we show that the two-electron reduced density matrix (2-RDM) can be expressed as a unique functional of the unencoded N -qubit-particle wave function without approximation, and hence, the energy can be expressed as a functional of the 2-RDM without fermionic encoding of the wave function. In contrast to current hardware-efficient methods, the derived functional has a unique, one-to-one (and onto) mapping between the qubit-particle wave functions and 2-RDMs, which avoids the over-parametrization that can lead to optimization difficulties such as barren plateaus. An application to computing the ground-state energy and 2-RDM of H 4 is presented.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2021

Quantum simulation of second-quantized Hamiltonians in compact encoding

We describe methods for simulating general second-quantized Hamiltonians using the compact encoding, in which qubit states encode only the occupied modes in physical occupation number basis states. These methods apply to second-quantized Hamiltonians composed of a constant number of interactions, i.e., linear combinations of ladder operator monomials of fixed form. Compact encoding leads to qubit requirements that are optimal up to logarithmic factors. Here, we show how to use sparse Hamiltonian simulation methods for second-quantized Hamiltonians in compact encoding, give explicit implementations for the required oracles, and analyze the methods. We also describe several example applications including the free boson and fermion theories, the φ 4 -theory, and the massive Yukawa model, all in both equal-time and light-front quantization. Our methods provide a general-purpose tool for simulating second-quantized Hamiltonians, with optimal or near-optimal scaling with error and model parameters.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Encoding an Oscillator into Many Oscillators

An outstanding challenge for quantum information processing using bosonic systems is Gaussian errors such as excitation loss and added thermal noise errors. Thus, bosonic quantum error correction is essential. Most bosonic quantum error correction schemes encode a finite-dimensional logical qubit or qudit into noisy bosonic oscillator modes. In this case, however, the infinite-dimensional bosonic nature of the physical system is lost at the error-corrected logical level. On the other hand, there are several proposals for encoding an oscillator mode into many noisy oscillator modes. However, these oscillator-into-oscillators encoding schemes are in the class of Gaussian quantum error correction. Therefore, these codes cannot correct practically relevant Gaussian errors due to the established no-go theorems that state that Gaussian errors cannot be corrected by using only Gaussian resources. Here, we circumvent these no-go results and show that it is possible to correct Gaussian errors by using Gottesman-Kitaev-Preskill (GKP) states as non-Gaussian resources. In particular, we propose a non-Gaussian oscillator-into-oscillators code, namely the GKP two-mode squeezing code, and demonstrate that it can quadratically suppress additive Gaussian noise errors in both the position and momentum quadratures except for a small sublogarithmic correction. Furthermore, we demonstrate that our GKP two-mode squeezing code is near optimal in the weak noise limit by proving via quantum information theoretic tools that quadratic noise suppression is optimal when we use two physical oscillator modes. Lastly, in this work we show that our non-Gaussian oscillator encoding scheme can also be used to correct excitation loss and thermal noise errors, which are dominant error sources in many realistic bosonic systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Virtual Neuron: A Neuromorphic Approach for Encoding Numbers

Neuromorphic computers perform computations by emulating the human brain and are expected to be indispensable for energy-efficient computing in the future. They are primarily used in spiking neural network-based machine learning applications. However, neuromorphic computers are unable to preprocess data for these applications. Currently, data is preprocessed on a CPU or a GPU-this incurs a significant cost of transferring data from the CPU/GPU to the neuromorphic processor and vice versa. This cost can be avoided if preprocessing is done on the neuromorphic processor. To efficiently preprocess data on a neuromorphic processor, we first need an efficient mechanism for encoding data that can lend itself to all general-purpose preprocessing operations. Current encoding approaches have limited applicability and may not be suitable for all preprocessing operations. In this paper, we present the virtual neuron as a mechanism for encoding integers and rational numbers on neuromorphic processors. We evaluate the performance of the virtual neuron on physical and simulated neuromorphic hardware and show that it can perform an addition operation using 23 nJ of energy on average using a mixed-signal, memristor-based neuromorphic processor. The virtual neuron encoding approach is the first step in preprocessing data on a neuromorphic processor.

Date, Prasanna↗

DOE OSTI2021

Implementation of quantum key distribution and quantum clock synchronization via time bin encoding

Quantum key distribution allows for a provably secure transmission of cryptographic keys over an optical channel. Encoded polarization states or time-bin degree of freedom have been used for successful demonstrations. However, photon losses in long fibers, slow single photon detectors, and detector dark counts significantly limit the overall bit rate. Improving key throughput and reducing the overhead of key reconciliation remain as major challenges. Methods which utilize multiple time bins allow for multiple key bits to be encoded in a single photon, thus increasing the fidelity of transmitted keys and decreasing the overhead of key reconciliation in real-world conditions. Previous implementations of these methods required that Alice and Bob share a time reference by sharing a dedicated classical channel used for synchronization. This work presents a technique that allows two parties to exchange time-bin encoded photons without the need for synchronized time references. Our technique uses a framing protocol which allows Alice to encode a time reference along with a key which is determined by Alice before transmission. Security can be achieved by monitoring the visibility of a pair of Franson interferometers, using decoy pulses and measuring the round trip time between Alice and Bob. The bit rate of this technique is limited only by the recovery time of the detector and the speed of the modulation electronics. We experimentally demonstrate a raw bit rate of 5Mb/s over an optical channel with 55dB of loss, which is competitive with current research. We also demonstrate absolute timing synchronization with an accuracy of 20ps.

encryption↗

DOE OSTI2011

A spatially encoded dose difference maximal intensity projection map for patient dose evaluation: A new first line patient quality assurance tool

Purpose: To develop a spatially encoded dose difference maximal intensity projection (DD-MIP) as an online patient dose evaluation tool for visualizing the dose differences between the planning dose and dose on the treatment day. Methods: Megavoltage cone-beam CT (MVCBCT) images acquired on the treatment day are used for generating the dose difference index. Each index is represented by different colors for underdose, acceptable, and overdose regions. A maximal intensity projection (MIP) algorithm is developed to compress all the information of an arbitrary 3D dose difference index into a 2D DD-MIP image. In such an algorithm, a distance transformation is generated based on the planning CT. Then, two new volumes representing the overdose and underdose regions of the dose difference index are encoded with the distance transformation map. The distance-encoded indices of each volume are normalized using the skin distance obtained on the planning CT. After that, two MIPs are generated based on the underdose and overdose volumes with green-to-blue and green-to-red lookup tables, respectively. Finally, the two MIPs are merged with an appropriate transparency level and rendered in planning CT images. Results: The spatially encoded DD-MIP was implemented in a dose-guided radiotherapy prototype and tested on 33 MVCBCT images from six patients. The user can easily establish the threshold for the overdose and underdose. A 3% difference between the treatment and planning dose was used as the threshold in the study; hence, the DD-MIP shows red or blue color for the dose difference >3% or {<=}3%, respectively. With such a method, the overdose and underdose regions can be visualized and distinguished without being overshadowed by superficial dose differences. Conclusions: A DD-MIP algorithm was developed that compresses information from 3D into a single or two orthogonal projections while hinting the user whether the dose difference is on the skin surface or deeper.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TU-AB-BRA-09: A Novel Method of Generating Ultrafast Volumetric Cine MRI (VC-MRI) Using Prior 4D-MRI and On-Board Phase-Skipped Encoding Acquisition for Radiotherapy Target Localization

Purpose: To develop a technique generating ultrafast on-board VC-MRI using prior 4D-MRI and on-board phase-skipped encoding k-space acquisition for real-time 3D target tracking of liver and lung radiotherapy. Methods: The end-of-expiration (EOE) volume in 4D-MRI acquired during the simulation was selected as the prior volume. 3 major respiratory deformation patterns were extracted through the principal component analysis of the deformation field maps (DFMs) generated between EOE and all other phases. The on-board VC-MRI at each instant was considered as a deformation of the prior volume, and the deformation was modeled as a linear combination of the extracted 3 major deformation patterns. To solve the weighting coefficients of the 3 major patterns, a 2D slice was extracted from VC-MRI volume to match with the 2D on-board sampling data, which was generated by 8-fold phase skipped-encoding k-space acquisition (i.e., sample 1 phase-encoding line out of every 8 lines) to achieve an ultrafast 16–24 volumes/s frame rate. The method was evaluated using XCAT digital phantom to simulate lung cancer patients. The 3D volume of end-ofinhalation (EOI) phase at the treatment day was used as ground-truth onboard VC-MRI with simulated changes in 1) breathing amplitude and 2) breathing amplitude/phase change from the simulation day. A liver cancer patient case was evaluated for in-vivo feasibility demonstration. Results: The comparison between ground truth and estimated on-board VC-MRI shows good agreements. In XCAT study with changed breathing amplitude, the volume-percent-difference(VPD) between ground-truth and estimated tumor volumes at EOI was 6.28% and the Center-of-Mass-Shift(COMS) was 0.82mm; with changed breathing amplitude and phase, the VPD was 8.50% and the COMS was 0.54mm. The study of liver patient case also demonstrated a promising in vivo feasibility of the proposed method Conclusion: Preliminary results suggest the feasibility to estimate ultrafast VC-MRI for on-board target localization with phase skipped-encoding k-space acquisition. Research grant from NIH R01-184173.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Information encoding in the spatial correlations of entangled twin beams

The ability to use the temporal and spatial degrees of freedom of quantum states of light to encode and transmit information is crucial for a robust and efficient quantum network. In particular, the potential offered by the large dimensionality of the spatial degree of freedom remains unfulfilled, as the necessary level of control required to encode information remains elusive. We encode information in the distribution of the spatial correlations of entangled twin beams by taking advantage of their dependence on the angular spectrum of the pump needed for four-wave mixing. We show that the encoded information can only be extracted through joint spatial measurements of the twin beams and not through individual beam measurements and that the temporal quantum correlations are not modified. The ability to engineer the spatial properties of twin beams will enable high-capacity quantum networks and quantum-enhanced spatially resolved sensing and imaging.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2019

Human V H 1-69 Gene-Encoded Human Monoclonal Antibodies against Staphylococcus aureus IsdB Use at Least Three Distinct Modes of Binding To Inhibit Bacterial Growth and Pathogenesis

Staphylococcus aureus is an important human pathogen that infects nearly every human tissue. Like most organisms, the acquisition of nutrient iron is necessary for its survival. One route by which it obtains this metal is through the iron-regulated surface determinant (Isd) system that scavenges iron from the hemoglobin of the host. We show that the heavy chain variable region IGHV1-69 gene commonly encodes human monoclonal antibodies (mAbs) targeting IsdB-NEAT2. Remarkably, these antibodies bind to multiple antigenic sites. One class of IGHV1-69-encoded mAbs blocks S. aureus heme acquisition by binding to the heme-binding site of NEAT2, while two additional classes reduce the bacterial burden in vivo by an alternative Fc receptor-mediated mechanism. We further identified clonal lineages of IGHV1-69-encoded mAbs using donor samples, showing that each lineage diversifies during infection by somatic hypermutation. These studies reveal that IGHV1-69-encoded antibodies contribute to a protective immune response, furthering our understanding of the correlates of protection against S. aureus infection.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2014

Time-Encoded Imagers

We have developed two neutron detector systems based on time-encoded imaging and demonstrated their applicability toward non-proliferation missions. The 1D-TEI system was designed for and evaluated against the ability to detect Special Nuclear Material (SNM) in very low signal to noise environments; in particular, very large stand-off and/or weak sources that may be shielded. We have demonstrated significant detection (>5 sigma) of a 2.8e5 n/s neutron fission source at 100 meters stand-off in 30 min. If scaled to an IAEA significant quantity of Pu, we estimate that this could be reduced to as few as ~5 minutes. In contrast to simple counting detectors, this was accomplished without the need of previous background measurements. The 2D-TEI system was designed for high resolution spatial mapping of distributions of SNM and proved feasibility of twodimensional fast neutron imaging using the time encoded modulation of rates on a single pixel detector. Because of the simplicity of the TEI design, there is much lower systematic uncertainty in the detector response typical coded apertures. Other imaging methods require either multiple interactions (e.g. neutron scatter camera or Compton imagers), leading to intrinsically low efficiencies, or spatial modulation of the signal (e.g., Neutron Coded Aperture Imager (Hausladen, 2012)), which requires a complicated, high channel count, and expensive position sensitive detector. In contrast, a single detector using a time-modulated collimator can encode directional information in the time distribution of detected events. This is the first investigation of time-encoded imaging for nuclear nonproliferation applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Optical encoder devices and systems

Devices, systems and methods for encoding information using optical components are described. Information associated with a first optical signal (e.g., an optical pump) is encoded onto the phase of a second optical signal (e.g., an optical probe) using cross phase modulation (XPM) in a non-linear optical medium. The optical signals are multiplexed together into the nonlinear optical medium. The probe experiences a modified index of refraction as it propagates through the medium and thus accumulates a phase change proportional to the intensity of the pump. The disclosed devices can be incorporated into larger components and systems for various applications such as scientific diagnostics, radar, remote sensing, wireless communications, and quantum computing that can benefit from encoding and generation of low noise, high resolution signals. Examples of the encoded information includes intrinsic noise from the optical source, or others signals of interest, such as electrical, optical, X-ray, or high-energy particle signals.

Buckley, Brandon Walter↗

DOE OSTI2023

Optical encoder devices and systems

Buckley, Brandon Walter↗

DOE OSTI2023

Optical information transfer through random unknown diffusers using electronic encoding and diffractive decoding

Free-space optical information transfer through diffusive media is critical in many applications, such as biomedical devices and optical communication, but remains challenging due to random, unknown perturbations in the optical path. We demonstrate an optical diffractive decoder with electronic encoding to accurately transfer the optical information of interest, corresponding to, e.g., any arbitrary input object or message, through unknown random phase diffusers along the optical path. This hybrid electronic-optical model, trained using supervised learning, comprises a convolutional neural network-based electronic encoder and successive passive diffractive layers that are jointly optimized. After their joint training using deep learning, our hybrid model can transfer optical information through unknown phase diffusers, demonstrating generalization to new random diffusers never seen before. The resulting electronic-encoder and optical-decoder model was experimentally validated using a 3D-printed diffractive network that axially spans <70λ, where λ = 0.75 mm is the illumination wavelength in the terahertz spectrum, carrying the desired optical information through random unknown diffusers. The presented framework can be physically scaled to operate at different parts of the electromagnetic spectrum, without retraining its components, and would offer low-power and compact solutions for optical information transfer in free space through unknown random diffusive media.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Explicit Quantum Circuits for Block Encodings of Certain Sparse Matrices

Many standard linear algebra problems can be solved on a quantum computer by using recently developed quantum linear algebra algorithms that make use of block encodings and quantum eigenvalue/singular value transformations. A block encoding embeds a properly scaled matrix of interest A in a larger unitary transformation U that can be decomposed into a product of simpler unitaries and implemented efficiently on a quantum computer. Although quantum algorithms can potentially achieve exponential speedup in solving linear algebra problems compared to the best classical algorithm, such a gain in efficiency ultimately hinges on our ability to construct an efficient quantum circuit for the block encoding of A, which is difficult in general, and not trivial even for well structured sparse matrices. Here, in this paper, we give a few examples on how efficient quantum circuits can be explicitly constructed for some well structured sparse matrices and discuss a few strategies used in these constructions. We also provide implementations of these quantum circuits in MATLAB.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Enhancing Multi-Step Reservoir Inflow Forecasting: A Time-Variant Encoder–Decoder Approach

Accurate reservoir inflow forecasting is vital for effective water resource management. Reliable forecasts enable operators to optimize storage and release strategies to meet competing sectoral demands—such as water supply, irrigation, and hydropower scheduling—while also mitigating flood and drought risks. To address this need, in this study, we propose a novel time-variant encoder–decoder (ED) model designed specifically to improve multi-step reservoir inflow forecasting, enabling accurate predictions of reservoir inflows up to seven days ahead. Unlike conventional ED-LSTM and recursive ED-LSTM models, which use fixed encoder parameters or recursively propagate predictions, our model incorporates an adaptive encoder structure that dynamically adjusts to evolving conditions at each forecast horizon. Additionally, we introduce the Expected Baseline Integrated Gradients (EB-IGs) method for variable importance analysis, enhancing interpretability of inflow by incorporating multiple baselines to capture a broader range of hydrometeorological conditions. The proposed methods are demonstrated at several diverse reservoirs across the United States. Our results show that they outperform traditional methods, particularly at longer lead times, while also offering insights into the key drivers of inflow forecasting. These advancements contribute to enhanced reservoir management through improved forecasting accuracy and practical decision-making insights under complex hydroclimatic conditions.

58 GEOSCIENCES↗

DOE OSTI2023

Dimensionality Reduction with Variational Encoders Based on Subsystem Purification

Efficient methods for encoding and compression are likely to pave the way toward the problem of efficient trainability on higher-dimensional Hilbert spaces, overcoming issues of barren plateaus. Here, we propose an alternative approach to variational autoencoders to reduce the dimensionality of states represented in higher dimensional Hilbert spaces. To this end, we build a variational algorithm-based autoencoder circuit that takes as input a dataset and optimizes the parameters of a Parameterized Quantum Circuit (PQC) ansatz to produce an output state that can be represented as a tensor product of two subsystems by minimizing $Tr(ρ^2)$. The output of this circuit is passed through a series of controlled swap gates and measurements to output a state with half the number of qubits while retaining the features of the starting state in the same spirit as any dimension-reduction technique used in classical algorithms. The output obtained is used for supervised learning to guarantee the working of the encoding procedure thus developed. We make use of the Bars and Stripes (BAS) dataset for an 8 × 8 grid to create efficient encoding states and report a classification accuracy of 95% on the same. Thus, the demonstrated example provides proof for the working of the method in reducing states represented in large Hilbert spaces while maintaining the features required for any further machine learning algorithm that follows.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Toward Chirality-Encoded Domain Wall Logic

Nonvolatile logic networks based on spintronic and nanomagnetic technologies have the possibility to create high-speed, ultralow power computational architectures. This work investigates the feasibility of “chirality-encoded domain wall logic,” a nanomagnetic logic architecture where data are encoded by the chiral structures of mobile domain walls in networks of ferromagnetic nanowires and processed by the chiral structures' interactions with geometric features of the networks. High-resolution magnetic imaging is used to test two critical functionalities: the inversion of domain wall chirality at tailored artificial defect sites (logical NOT gates) and the chirality-selective output of domain walls from 2-in-1-out nanowire junctions (common operation to AND/NAND/OR/NOR gates). The measurements demonstrate both operations can be performed to a good degree of fidelity even in the presence of complex magnetization dynamics that would normally be expected to destroy chirality-encoded information. Together, these results represent a strong indication of the feasibility of devices where chiral magnetization textures are used to directly carry, rather than merely delineate, data.

36 MATERIALS SCIENCE↗

DOE OSTI2020

The ghost in the radiation: robust encodings of the black hole interior

We reconsider the black hole firewall puzzle, emphasizing that quantum error-correction, computational complexity, and pseudorandomness are crucial concepts for understanding the black hole interior. We assume that the Hawking radiation emitted by an old black hole is pseudorandom, meaning that it cannot be distinguished from a perfectly thermal state by any efficient quantum computation acting on the radiation alone. We then infer the existence of a subspace of the radiation system which we interpret as an encoding of the black hole interior. This encoded interior is entangled with the late outgoing Hawking quanta emitted by the old black hole, and is inaccessible to computationally bounded observers who are outside the black hole. Specifically, efficient operations acting on the radiation, those with quantum computational complexity polynomial in the entropy of the remaining black hole, commute with a complete set of logical operators acting on the encoded interior, up to corrections which are exponentially small in the entropy. Thus, under our pseudorandomness assumption, the black hole interior is well protected from exterior observers as long as the remaining black hole is macroscopic. On the other hand, if the radiation is not pseudorandom, an exterior observer may be able to create a firewall by applying a polynomial-time quantum computation to the radiation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗