arXiv subjects

Kfir Sulimany

Publications and source records attributed to Kfir Sulimany.

18 recordsLinked to original sources

arXiv2026

A Machine-Verified Proof of a Quantum-Optimization Conjecture

We report a machine-verified resolution of a problem open for over a decade in quantum optimization: the Farhi, Goldstone and Gutmann (FGG) conjecture that depth-$p$ Quantum Approximate Optimization Algorithm (QAOA) on the ring of disagrees attains approximation ratio $(2p+1)/(2p+2)$ exactly. We found the proof using a large language model, Claude Fable 5, and verified its correctness end-to-end by the Lean 4 proof assistant. Our methodology includes several ingredients: building on a substantial Lean library of quantum information, we formalized the QAOA components and the known parts of the problem, and reduced the conjecture to a single open mathematical statement. The model was then handed the library and our agentic toolkit, and tasked with closing that gap by constructing a proof in Lean. The resulting process is a feedback loop between the model's natural-language reasoning and Lean's mechanical verification, which converged to a machine-verified proof. Human verification is required only for the structural scaffolding - that the formal statement faithfully encodes the intended claim - while the proof itself is supplied by the model and certified mechanically by Lean. The proof is nevertheless striking - the model uncovered a hidden dynamical symmetry of the problem and exploited it, borrowing tools and machinery from an adjacent field to turn a hard existence problem into an explicit construction. This work paves the way for resolving open conjectures in quantum information science and beyond.

quant-ph↗

arXiv2026

Ax-Prover: A Deep Reasoning Agentic Framework for Theorem Proving in Mathematics and Quantum Physics

We present Ax-Prover, a multi-agent system for automated theorem proving in Lean that can solve problems across diverse scientific domains and operate either autonomously or collaboratively with human experts. To achieve this, Ax-Prover approaches scientific problem solving through formal proof generation, a process that demands both creative reasoning and strict syntactic rigor. Ax-Prover meets this challenge by equipping Large Language Models (LLMs), which provide knowledge and reasoning, with Lean tools via the Model Context Protocol (MCP), which ensure formal correctness. To evaluate its performance as an autonomous prover, we benchmark our approach against frontier LLMs and specialized prover models on two public math benchmarks and on two Lean benchmarks we introduce in the fields of abstract algebra and quantum theory. On public datasets, Ax-Prover is competitive with state-of-the-art provers, while it largely outperforms them on the new benchmarks. This shows that, unlike specialized systems that struggle to generalize, our tool-based agentic theorem prover approach offers a generalizable methodology for formal verification across diverse scientific domains. Furthermore, we demonstrate Ax-Prover's assistant capabilities in a practical use case, showing how it enabled an expert mathematician to formalize the proof of a complex cryptography theorem.

cs.AI↗

arXiv2025

Reduced State Embedding for Error Correction in Quantum Cryptography

Encoding in a high-dimensional Hilbert space improves noise resilience in quantum information processing. This approach, however, may result in cross-mode coupling and detection complexities, thereby reducing quantum cryptography performance. This fundamental trade-off between correctness and secrecy motivates the search for quantum error-correction approaches for cryptography. Here, we introduce state embeddings that use a k-symbol subset within a d-dimensional Hilbert space, tailored to the channel's error structure. In the framework of quantum error-correction, our reduced-state embedding realizes an explicit erasure-type error-correction within the quantum channel. We demonstrate the advantage of our scheme in realistic quantum channels, producing a higher secure key rate. We validate our approach using a d=25 quantum key distribution (QKD) experimental data, derive closed-form expressions for the key rate and threshold, and determine the optimum at k=5. These findings advance high-dimensional QKD and pave the way to error-correction and modulation for quantum cryptography.

quant-ph↗

arXiv2025

Machine Intelligence on Wireless Edge Networks

Machine intelligence on edge devices enables low-latency processing and improved privacy, but is often limited by the energy and delay of moving and converting data. Current systems frequently avoid local model storage by sending queries to a server, incurring uplink cost, network latency, and privacy risk. We present the opposite approach: broadcasting model weights to clients that perform inference locally using in-physics computation inside the radio receive chain. A base station transmits weights as radio frequency (RF) waveforms; the client encodes activations onto the waveform and computes the result using existing mixer and filter stages, RF components already present in billions of edge devices such as cellphones, eliminating repeated signal conversions and extra hardware. Analysis shows that thermal noise and nonlinearity create an optimal energy window for accurate analog inner products. Hardware-tailored training through a differentiable RF chain preserves accuracy within this regime. Circuit-informed simulations, consistent with a companion experiment, demonstrate reduced memory and conversion overhead while maintaining high accuracy in realistic wireless edge scenarios.

cs.ET↗

arXiv2025

Decoy state and purification protocols for superior quantum key distribution with imperfect quantum-dot based single photon sources: Theory and Experiment

The original proposal of quantum key distribution (QKD) was based on ideal single photon sources, which 40 years later, are still challenging to develop. Therefore, the development of decoy state protocols using weak coherent states (WCS) from lasers, set the frontier in terms of secure key rates and distances. Here, we propose and experimentally demonstrate two simple-to-implement QKD protocols that allow practical, far from ideal sub-Poissonian photon sources to outperform state-of-the-art WCS. By engineering the photon statistics of a biexciton-exciton cascade in room temperature single photon sources based on giant colloidal quantum dots coupled to nanoantennas, we show that either a truncated decoy state protocol or a heralded purification protocol can be employed to achieve a significantly increased performance in terms of the maximal allowed channel loss for secure key creation, which can exceed even that of ideal WCS by more than 3dB. We then experimentally emulate a BB84 QKD using such a quantum dot source, verifying the superiority of our protocols over the best possible BB84 WCS performance. These protocols can be utilized efficiently on a host of various quantum emitters having controllable photon statistics with a finite photon-number basis, offering a practical approach to QKD without the hindering requirements on the single photon purity of the photon source.

quant-ph↗

arXiv2025

Disaggregated Deep Learning via In-Physics Computing at Radio Frequency

Modern edge devices, such as cameras, drones, and Internet-of-Things nodes, rely on deep learning to enable a wide range of intelligent applications, including object recognition, environment perception, and autonomous navigation. However, deploying deep learning models directly on the often resource-constrained edge devices demands significant memory footprints and computational power for real-time inference using traditional digital computing architectures. In this paper, we present WISE, a novel computing architecture for wireless edge networks designed to overcome energy constraints in deep learning inference. WISE achieves this goal through two key innovations: disaggregated model access via wireless broadcasting and in-physics computation of general complex-valued matrix-vector multiplications directly at radio frequency. Using a software-defined radio platform with wirelessly broadcast model weights over the air, we demonstrate that WISE achieves 95.7% image classification accuracy with ultra-low operation power of 6.0 fJ/MAC per client, corresponding to a computation efficiency of 165.8 TOPS/W. This approach enables energy-efficient deep learning inference on wirelessly connected edge devices, achieving more than two orders of magnitude improvement in efficiency compared to traditional digital computing.

cs.ET↗

arXiv2024

QAMNet: Fast and Efficient Optical QAM Neural Networks

The energy consumption of neural network inference has become a topic of paramount importance with the growing success and adoption of deep neural networks. Analog optical neural networks (ONNs) can reduce the energy of matrix-vector multiplication in neural network inference below that of digital electronics. However, realizing this promise remains challenging due to digital-to-analog conversion: even at low bit precisions $b$, encoding the $2^b$ levels of digital weights and inputs into the analog domain requires specialized and power-hungry electronics. Faced with similar challenges, the field of telecommunications has developed the complex-valued Quadrature-Amplitude Modulation (QAM), the workhorse modulation format for decades. QAM maximally exploits the complex amplitude to provide a quadratic $O(N^2) \to O(N)$ energy saving over intensity-only modulation. Inspired by this advantage, this work introduces QAMNet, an optical neural network hardware and architecture with superior energy consumption to existing ONNs, that fully utilizes the complex nature of the amplitude of light with QAM. When implemented with conventional telecommunications equipment, we show that QAMNet accelerates complex-valued deep neural networks with accuracies indistinguishable from digital hardware, based on physics-based simulations. Compared to standard ONNs, we find that QAMNet ONNs: (1) attain higher accuracy above moderate levels of total bit precision, (2) are more accurate above low energy budgets, and (3) are an optimal choice when hardware bit precision is limited.

cs.ET↗

arXiv2024

Quantum-secure multiparty deep learning

Secure multiparty computation enables the joint evaluation of multivariate functions across distributed users while ensuring the privacy of their local inputs. This field has become increasingly urgent due to the exploding demand for computationally intensive deep learning inference. These computations are typically offloaded to cloud computing servers, leading to vulnerabilities that can compromise the security of the clients' data. To solve this problem, we introduce a linear algebra engine that leverages the quantum nature of light for information-theoretically secure multiparty computation using only conventional telecommunication components. We apply this linear algebra engine to deep learning and derive rigorous upper bounds on the information leakage of both the deep neural network weights and the client's data via the Holevo and the Cramér-Rao bounds, respectively. Applied to the MNIST classification task, we obtain test accuracies exceeding $96\%$ while leaking less than $0.1$ bits per weight symbol and $0.01$ bits per data symbol. This weight leakage is an order of magnitude below the minimum bit precision required for accurate deep learning using state-of-the-art quantization techniques. Our work lays the foundation for practical quantum-secure computation and unlocks secure cloud deep learning as a field.

quant-ph↗

arXiv2024

Tutorial: How to build and control an all-fiber wavefront modulator using mechanical perturbations

Multimode optical fibers support the dense, low-loss transmission of many spatial modes, making them attractive for technologies such as communications and imaging. However, information propagating through multimode fibers is scrambled, due to modal dispersion and mode mixing. This is usually rectified using wavefront shaping techniques with devices such as spatial light modulators. Recently, we demonstrated an all-fiber system for controlling light propagation inside multimode fibers using mechanical perturbations, called the fiber piano. In this tutorial we explain the design considerations and experimental methods needed to build a fiber piano, and review applications where fiber pianos have been used.

physics.optics↗

arXiv2024

High-dimensional quantum key distribution using a multi-plane light converter

High-dimensional quantum key distribution (QKD) offers higher information capacity and stronger resilience to noise compared to its binary counterpart. However, these advantages are often hindered by the difficulty of realizing the required high-dimensional measurements and transformations. Here, we implement a large-scale multi-plane light converter (MPLC) and program it as a high-dimensional mode sorter of spatial modes for QKD. Using the MPLC, we demonstrate five-dimensional QKD with six mutually unbiased bases and 25-dimensional QKD with two mutually unbiased bases in the same experimental setup. Furthermore, we propose a construction of pairs of mutually unbiased bases that are robust to experimental errors, with measurement complexity scaling only with the square root of the encoded dimension. This approach paves the way for QKD implementations in higher dimensions.

quant-ph↗

arXiv2024

High-dimensional quantum key distribution using orbital angular momentum of single photons from a colloidal quantum dot at room temperature

High-dimensional quantum key distribution (HDQKD) is a promising avenue to address the inherent limitations of basic QKD protocols. However, experimental realizations of HDQKD to date have relied on indeterministic photon sources that limit the achievable key rate. In this paper, we demonstrate a full emulation of a HDQKD system using a single colloidal giant quantum dot (gQD) as a deterministic, compact and room-temperature single-photon source (SPS). We demonstrate a practical protocol by encoding information in a high-dimensional space ($d = 3$) of the orbital angular momentum of the photons. Our experimental configuration incorporates two spatial light modulators for encoding and decoding the spatial information carried by individual photons. Our experimental demonstration establishes the feasibility of utilizing high radiative quantum yield gQDs as practical SPSs for HDQKD. We also demonstrate experimentally secure qudit transmission exceeding one secure bit per photon, thus already beating the traditional d=2 QKD capacity.

quant-ph↗

arXiv2024

Bandwidth-induced saturation in multimode fiber-based absorbers

Multimode fiber-based saturable absorbers enable mode-locking in lasers, generating ultrafast pulses and providing an exceptional platform for investigating nonlinear phenomena. Previous analyses in the continuous wave (CW) limit showed that saturable absorption can be obtained due to nonlinear interactions between transverse modes. We find experimentally that saturable absorption can be achieved thanks to the interplay of single-mode fiber nonlinearity and the wavelength-dependent linear transmission of the multimode fiber, even with negligible intermodal nonlinearities. We further show that even when intermodal nonlinearities are significant, the CW analysis may not be sufficient for long multimode fibers. Understanding the underlying mechanisms of multimode fiber-based saturable absorbers opens new possibilities for developing programmable devices for ultrafast control.

physics.optics↗

arXiv2023

High-dimensional coherent one-way quantum key distribution

High-dimensional quantum key distribution (QKD) offers secure communication, with secure key rates that surpass those achievable by QKD protocols utilizing two-dimensional encoding. However, existing high-dimensional QKD protocols require additional experimental resources, such as multiport interferometers and multiple detectors, thus raising the cost of practical high-dimensional systems and limiting their use. Here, we present and analyze a novel protocol for arbitrary-dimensional QKD, that requires only the hardware of a standard two-dimensional system. We provide security proofs against individual attacks and coherent attacks, setting an upper and lower bound on the secure key rates. Then, we test the new high-dimensional protocol in a standard two-dimensional QKD system over a 40 km fiber link. The new protocol yields a two-fold enhancement of the secure key rate compared to the standard two-dimensional coherent one-way protocol, without introducing any hardware modifications to the system. This work, therefore, holds great potential to enhance the performance of already deployed time-bin QKD systems through a software update alone. Furthermore, its applications extend across different encoding schemes of QKD qudits.

quant-ph↗

arXiv2022

Spectral Shaping in a Multimode Fiber by All-fiber Modulation

In the past few years, there is a renewed interest in using multimode fibers for a wide range of technologies such as communication, imaging and spectroscopy. Practical implementations of multimode fiber in such applications, however, are held back, due to the challenges in dealing with modal dispersion, mode coupling and the fiber's sensitivity to mechanical perturbations. Here, we utilize these features of multimode fibers to generate all-fiber reconfigurable spectral filters. By applying computer-controlled mechanical deformations to the fiber, along with an optimization algorithm, we manipulate the light propagation in the fiber and control its output field. Using this approach we demonstrate tunable bandpass filters and dual-band filters, with spectral resolutions as low as 5pm.

physics.optics↗

arXiv2022

Processing entangled photons in high dimensions with a programmable light converter

High-dimensional entanglement offers a variety of advantages for both fundamental and applied applications in quantum information science. A central building block for such applications is a programmable processor of entangled states, which is crucial for the certification, manipulation and distribution of high-dimensional entanglement. The leading technology for processing photons is integrated multiport interferometers. However, such devices are incompatible with structured light, and their scaling is challenging. Here, we unlock these limitations by demonstrating a reconfigurable processor of entangled photons in high-dimensions that is based on multi-plane light conversion (MPLC), a technology that was recently developed for multiplexing hundreds of spatial modes for classical communication. We use our programmable MPLC platform to certify three-dimensional entanglement in two mutually unbiased bases, perform 400 arbitrary random transformations on entangled photons, and convert the mode basis of entangled photons for entanglement distribution.

quant-ph↗

arXiv2022

Soliton-pair dynamical transition in mode-locked lasers

Multi-soliton mode-locked laser waveforms are much sought as a complex light source for research and applications, but are difficult to manipulate effectively because of the elaborate and diverse interactions present. Here we present an experimental, numerical, and theoretical study of the interaction and control of the internal dynamics of a two-soliton waveform in a mode-locked fiber laser. Using the pumping current as a control agent, we demonstrate experimentally a two-orders-of-magnitude reduction in the separation of a bound soliton pair, inducing a dynamical transition between a loosely bound, phase-incoherent pair, and a tightly bound phase-locked pair. We show on the basis of a Haus-model numerical simulation of the recently-proposed noise-mediated interaction theory, that the pulse separation and dynamical transition are governed by the shape of the dispersive-wave pedestals. We explain the dynamical transition by showing analytically, within a simplified theory, that the noise-mediated interaction becomes purely attractive when the pedestals energy drops below a threshold. This work demonstrates the ability to control the waveform through the interaction forces, without external intervention in the light propagation in the laser.

physics.optics↗

arXiv2022

All-Fiber Source and Sorter for Multimode Correlated Photons

Photons occupying multiple spatial modes hold a great promise for implementing high-dimensional quantum communication. We use spontaneous four-wave mixing to generate multimode photon pairs in a few mode fiber. We show the photons are correlated in the fiber mode basis using an all-fiber mode sorter. Our demonstration offers an essential building block for realizing high-dimensional quantum protocols based on standard, commercially available fibers, in an all-fiber configuration.

quant-ph↗

arXiv2018

Bidirectional Soliton Rain Dynamics Induced by Casimir-Like Interactions in a Graphene Mode-Locked Fiber Laser

We study experimentally and theoretically the interactions among ultrashort optical pulses in the soliton rain multiple-pulse dynamics of a fiber laser. The laser is mode-locked by a graphene saturable absorber fabricated using the mechanical transfer technique. Dissipative optical solitons aggregate into pulse bunches that exhibit complex behavior, which includes acceleration and bi-directional motion in the moving reference frame. The drift speed and direction depend on the bunch size and relative location in the cavity, punctuated by abrupt changes under bunch collisions. We model the main effects using the recently proposed noise-mediated pulse interaction mechanism, and obtain a good agreement with experiments. This highlights the major role of long-range Casimir-like interactions over dynamical pattern formations within ultrafast lasers.

physics.optics↗