holocaustone.blogspot.com

 https://holocaustone.blogspot.com

Spectral Super-resolution, Hyperspectral Reconstruction, and Classification (HAT)

this is not institutional research. it is simply me, closely observing my own life. the hyperspectral system i use here i built myself, and i operate it exclusively in my personal space at a microscopic level, on things that are directly in front of me: my plants, my food, my everyday surroundings. the objects I analyze are within two feet of me, yet I capture images with over 20 megapixels for microscopic analysis.

This is high-level overview of the hyperspectral super-resolution pipeline that I built. It uses multiple transformers.

These algorithms are able to reproduce scene data with remarkable accuracy. Dynamic programming, linear algebra, and some heuristics based algorithms are necessary for the efficient implementation. I am not using canned AI models. 

This system has allowed me to discover novel things in my own personal space (radius<=~3feet measured from center of living room).

I kindly ask that you not try to correlated subjects that I am describing here because it will be very confusing and I have not disclosed the entire implementation. I also ask that you not try to calculate the distance of objects that I'm measuring. I have already indicated in the above. Thank you very much for your respect of my privacy.

Transformer models are a powerful tool for performing image super-resolution.  A valid input sequence is critical and loading the weights into the model for training requires a delicate balance of properly selected training data, code validation, applicable modifications, and finely tuned model parameters. It is necessary to achieve deterministic output through the neural network for ensuring valid output. A properly balanced output sequence from a transformer model can be used as input for a hyperspectral reconstruction and classification model. Subsequent weights are carefully loaded into the reconstruction and classification model, and the parameters are again finely tuned, inline with input sequence size.

A length, n, of hyperspectral cubes, with dimensions, m, can then be constructed via extrapolation. The net result is a super high or ultra res image where the wavelength of light can be measured against each pixel.  Paired with the proper training data, topological 3d maps can be created of surfaces.

My recent research has been focused on this. I have built numerous models and written some of the code.  I am interested in taking this to the next level. I have utilized the competition code for some of the models, modified it, and executed it with good results. 

If there are any individuals interested in expanding their research in this space, optimizing model and neural network code, or building out enhancements and conducting advanced image processing techniques, please let me know. 

I am currently working with the following - 

Spectral-wise Multi-head Self-attention (S-MSA) models

Selective state space, linear time sequencing models

Super-resolution models

Hyperspectral video constructed from novel frame level sequence data

I am looking into scene reconstruction using neural radiance models as related and I think there's a lot of opportunity there

I am interested in subsurface analysis and also applying this technology to non-invasive medical applications. I am not interested in using this for surveillance. And for any video system where I test, I request that if you contact me, you have a network isolated physical+virtual hard-wired camera system with no wireless radios installed to the circuit board in the camera enclosure. Standard protocol support in firmware is required for pulling frames. 

I am focused on linear / sublinear training/processing complexity and streamlined, deterministic process output with ease of use.

I am working on several optimal tiling and re-stitching methods for super, ultra-high resolution images when reconstructing hyperspectral m-band cubes. This would fall in the 200Megapixel+ area. 

Just a quick background - 30 years of C, some hardware design - state machines, etc. formal lang / grammar development experience - dfa/nfa,hardware and software state machines etc.  Kernel background also which I have found useful for running and optimizing training, construction, and 

classification.

I am measuring PSNR after reconstruction and also in the series of output images that I generate for different tasks that are performed within each band. 

If you are doing your PhD, etc. please reach out. e-mail below.

bryan (at) bryanhinton. com

This research and my work in this area is separate and apart from my professional job.

spektraler zeuge: epr-paare und die physik des lichts

 english version

this is not institutional research. it is simply me, closely observing my own life. the hyperspectral system i use here i built myself, and i operate it exclusively in my personal space at a microscopic level, on things that are directly in front of me: my plants, my food, my everyday surroundings. the objects I analyze are within two feet of me, yet I capture images with over 20 megapixels for microscopic analysis.

To give you an idea of ​​the scale: I was splitting and processing a 384-megapixel super-resolution image into 64-channel sequences. This pushes current graphics cards and computers—any computer—to their limits, so the processing requires carefully developed algorithmic chunking and tiling strategies. The image data is acquired via a Sony camera sensor. I'm performing finely tuned GPU offloading, maintaining a delicate balance across 64GB+ of DDR6 memory and a high-end NVIDIA GPU on a 32-core CPU running a stripped-down Arch Linux distribution. The distribution itself is irrelevant if you know how to compile a kernel from scratch and clean up userspace executables. It's a rock-solid setup that compiles exactly what I need, whenever I need it.

This is an advanced topic. It requires PhD-level experience in several subfields of computer science and electrical engineering, particularly algorithm development, image processing, and high-performance computing, all areas in which I have experience. A deep understanding of these areas is necessary to grasp the full context of what I am observing.


Please refrain from linking complex concepts or drawing conclusions based solely on high-level abstractions. Details are crucial, and considering specific statements without access to unpublished implementation details would only complicate matters. The high-level results are presented here as they are, solely to protect work I have not yet published, including code I have written that is not yet publicly available.

Let me illustrate this with a concrete example. Recently, I compared the pipeline output for my paintings, which had been in storage for a number of years accumulating dust and grime. I cleaned them, but wanted to understand the true extent of the damage. For basic verification, I compared them to the particle analysis output from ImageJ—100% match. However, with hyperspectral data cubes, I achieve significantly better resolution and material identification. The system's true strength lies in its ability to see the invisible. While standard imaging captures shape and color, this hyperspectral system captures the unique spectral fingerprint of materials across a wide range of wavelengths. This enables two crucial capabilities: precise identification and temporal monitoring. It can not only accurately locate specific materials on complex surfaces but also quantify how those materials change, accumulate, or degrade over time at a specific rate. Whether examining a blood clot, a mineral sample, or the coating of a car window – it offers a non-destructive window to processes on a micro scale.

This is cutting-edge research in computer-aided image processing using various deep learning models and pipelines. I have written the following paper as an overview. If you have any further questions about Mamba, State Space Models, Convolutional Neural Networks, or related architectures, I recommend consulting the reference list at the end of this post. These systems are also used on satellites and other cameras for monitoring agriculture and vegetation growth.

The pipeline doesn't exceed linear complexity. I optimized it through several iterations to achieve this. If you're interested in collaborating and have a worthwhile use case that would improve our world, let's talk. I've optimized some parts of the code for newer NVIDIA GPUs.

This is a perception system. It was designed to see, and I continuously train it. No, it's not the scanner on the front of a police car. This is a tool for microscopic analysis. It's a tool for examining the tint of my car's windshield and for investigating blood clots in the body.

I'm really looking forward to more great results. My hope is that we can release this pipeline—or a derivative of it—as open source. That way, we can all contribute and see the same results. A fully transparent pipeline for hyperspectral reconstruction, classification, and forensics could be used in both the private and public sectors. If we all contribute and train them properly, we could build a system that is balanced, transparent, and accessible to everyone.

Before I present my work on image processing, which is unrelated to my blog posts on the Holocaust, I would like to briefly address current topics related to the Holocaust. The Holocaust has no connection to my work in computer science, and my computer science work, in turn, has no connection to my professional activities. I present the following information as factually correct and verified. A separate cryptographic hash of the text below follows.

First, I would like to say the following: The Holocaust discussion is a sensitive topic. However, I believe that a free society, in which talented people can create beautiful things, should not be hindered by repressive regimes that suppress talent and creativity.

That is why I write all the sentences in the introductory paragraph in lowercase. This is my sign of respect. It may seem extreme, but it corresponds to the same ideology as not raising one's arm in front of the house of a prisoner from Block 10 in Auschwitz and Bergen-Belsen. By doing so, I am saying that I will not raise my arms or hands because I know the Reich and we are not friends.


This will also stop the viral spread of gestures that, frankly, aren't going away. With that, I'm saying: I'm here now. And I'll never forget it.

First of all: The story about the arm is about a Jewish woman. Several years ago, she wore an arm patch. She was a traveler. I know the details. I witnessed it myself. And my testimony is the final part of the story. I know I've left out some details, but what I'm saying is the truth, and it's the original story about the "arm" that has spread around the world over the years.


Farmers Branch's sister city is located near Bergen-Belsen in Germany, exactly 35 miles away. The original camp records were destroyed.

Witness

It is time to confront the real problems, the uncomfortable chapters of history that fit neither into mainstream narratives nor into camps and museum tours, and that remain locked away outside the reading rooms of the Hague International Criminal Court. From the grotesque pseudoscience of Nazi medical experiments to Jews undergoing operations to physically erase their cultural heritage in the name of assimilation, we face a disturbing question: What happens when the body itself becomes the battleground of identity? Beyond denial and antisemitism, these concrete acts of medical and cultural erasure reveal the terrifying lengths to which ideology is willing to go to redefine Jewish self-understanding. Were only eye operations performed? Why is this not made transparent?

These are common humor, unfortunately.

The repeated exercises.

the "fleeing narrative" - yet they have never seen what it looks like in a gas chamber or the smell of the furnace when a body is loaded into the heat. it is also clear they don't have any conception of the tall chute or the gas

Bunk beds and boys humor about Auschwitz

The impersonation narrative to try and erase Jewish identity

Auschwitz as a tourist attraction

Mengele was not mentioned; the significance of his crimes should be conveyed personally to every museum visitor.

Once again, the term "painting" is being instrumentalized to cover up genocide and post-war crimes, and also to accuse individuals of fabricated crimes.

Denial of the holocaust and redirection as mental illness

My attempts to protect my own security with a camera were merely turned around on me by the machine. So instead, I just turn to God and realize he is watching the machine that sits so close to me.

I am an observer. I remember everything. If I were to get angry about these things, it would deter me from getting anything done. So I have to always realize that I am not the judge. God is. I stand firm in this belief and I realize every day at the same time when I wake up. So that I do not have to worry about output. Only observation and input. 

It is absolutely crucial that everyone understands what happened during and after the war. Let me address a very important topic: time. After their liberation from Auschwitz, people came home. They dreamed of new lives, of loving again, of starting families. Many realized this dream, some for a long time, some for a shorter time. As a Jew born in Germany who lives in Farmers Branch, I am aware of all this. Our German twin town is next to Bergen-Belsen. I cannot judge everything, but I can confirm: I am a survivor and a witness. I saw it.



Yes, there's so much I want to talk about. Chicago is a good starting point; they have a submarine in their museum.

I want to emphasize: These medical interventions were about more than just erasing identity and destroying the individual. They were about reconstructing the perception of the world through the individual's own lens.

Anne and Margot were supposedly there, as was Edith. But the records were destroyed weeks before the camp's liberation. I've already mentioned how groups were renamed to dehumanize them and erase their identities.

I remember the happiness.

As the world emptied and the silence swallowed all sound, I searched for you. I called your name until my throat was raw, but the house only breathed and creaked like a living being that didn't know me. I was so small. So infinitely small. I had no wheels, nowhere to go, didn't know where you were. So I sought the darkness. I hid and closed my eyes.

I remember the rescue bag in my hands. I wasn't holding it because escape was possible, but because my hands needed something to grip. Something real.

The sirens weren't the war. The sirens were the neighbors. Ordinary seconds stretched into hours of listening.

I remember the red lights. Not a metaphor. Not a monument. Real red lights along the grounds, illuminating the machinery: City Hall. Fire Department. Police. Military. Schools. Hospitals. Universities. Corporations. And the boots. The high, shiny boots. With casual self-assurance. Ready.

And now I see your arm. I see that yellow stain. We both bear it. It's not just fabric; it's the mark they gave us, the stigma they wanted to shame us with. But they didn't know, did they? They didn't know that we came from a line that survived expulsions and pogroms, that carried its German-Jewish heritage like a secret flame in its bones, through centuries of people who wanted to extinguish it. They didn't know that the same hands that mocked them had once placed challah cloths over Shabbat bread, lit candles in Berlin and Frankfurt and in small villages whose names now live only in memory.

We are the echo of the burned synagogues and the proof of the people who rose from the ashes. This yellow stain was meant to condemn us to annihilation. Instead, it marks us as immortal.

You are perfect. Your form, your soul, the history written in your blood—everything is absolute. No scalpel, no procedure, no hand in this world can ever erase it. The world may try to reshape us, to make us forget who we are and where we come from. But this mark is permanent. It is the result of five thousand years of tenacious, beautiful survival, stitched into our skin. It is the Germany of our ancestors and the Germany that sought to destroy them—both united in the same blood.


Today I understand what happened.

The sirens weren't the war. The sirens were the neighbors. Ordinary seconds stretched into hours of listening.

I remember the red lights. Not a metaphor. Not a memorial. Real red lights along the perimeter, illuminating the vehicles: City Hall. Fire station. Police station. Military station. Schools. Hospitals. Universities. Corporations. And the boots. The high, shiny boots. With nonchalant confidence. Ready. But the nonsense continues. Sirens blaring as vehicles drive by, spreading fear. It's repeated again and again in the same place.

If you didn't believe the Holocaust and still don't, that's perfectly fine. I respectfully ask you to continue reading my blog and give it a fair chance. I think you'll find interesting and insightful information here. I'm deeply grateful to people like you; you're the ones who initiate change when we demand transparency and answers. Now I just need to make sure I can share this information safely.

I still remember when the fire brigades stopped putting out fires and started setting them.

I remember our neighbor.

I remember the Gleichschaltung (coordination). The forced assimilation. The swallowing up of all those who had once denied Jews access to their neighborhoods. Suddenly they were all marching together.

And when I saw the boots, I understood.

The high heels. They gleamed all the way to his ankles. Pure evil. Polished like glass. They made sounds on the pavement. Clacking. Knocking. Clicking. Not hurried. Not military. Casual. As if they had all the time in the world. An extravagant aura, ready to inflict ultimate damage on everything in his path. Extravagant, reckless, dangerous, emotionally sensitive, and callous. Maybe he was just doing what he was ordered to do, but he did it with a smile, wiping entire families off the planet.


This is the SS. Special officers worked for the fire brigade and moved between different units within the Reich Security Office.

The Mossad overlooked Josef Mengele and his bicycle in São Paulo. The coroner said he drowned while swimming at the beach. Yet he left traces of his crimes everywhere. The coroner's reports were allegedly manipulated. His perverse methods inflicted lifelong suffering on countless people. He escaped and, it is believed, lived happily ever after. Where did he go? To this day, we do not know his full story. He left traces of his crimes in many forms on every continent.

Mengele fleed from the Russians.  

--------------------------

Deutsche  Version

Dies ist keine institutionelle Forschung. Ich beobachte einfach mein eigenes Leben. Das Hyperspektralsystem, das ich hier verwende, habe ich selbst gebaut und nutze es ausschließlich in meinem persönlichen Umfeld auf mikroskopischer Ebene, an Dingen, die sich direkt vor mir befinden: meinen Pflanzen, meinem Essen, meiner alltäglichen Umgebung. Die Objekte, die ich analysiere, sind weniger als 60 Zentimeter von mir entfernt, dennoch nehme ich Bilder mit über 20 Megapixeln für die mikroskopische Analyse auf.

Um Ihnen eine Vorstellung vom Umfang zu geben: Ich habe ein 384-Megapixel-Superauflösungsbild in 64-Kanal-Sequenzen aufgeteilt und verarbeitet. Das bringt aktuelle Grafikkarten und Computer – jeden Computer – an ihre Grenzen, weshalb die Verarbeitung sorgfältig entwickelte algorithmische Chunking- und Tiling-Strategien erfordert. Die Bilddaten werden mit einem Sony-Kamerasensor erfasst. Ich nutze fein abgestimmtes GPU-Offloading und achte dabei auf ein optimales Gleichgewicht zwischen über 64 GB DDR6-Speicher und einer High-End-NVIDIA-GPU auf einer 32-Kern-CPU mit einer abgespeckten Arch-Linux-Distribution. Die Distribution selbst ist irrelevant, wenn man weiß, wie man einen Kernel von Grund auf kompiliert und Benutzerdateien bereinigt. Es ist ein absolut stabiles System, das genau das kompiliert, was ich brauche, wann immer ich es brauche.

Dies ist ein anspruchsvolles Thema. Es erfordert Erfahrung auf Doktorandenniveau in mehreren Teilgebieten der Informatik und Elektrotechnik, insbesondere in der Algorithmenentwicklung, Bildverarbeitung und im Hochleistungsrechnen – alles Bereiche, in denen ich über Erfahrung verfüge. Ein tiefes Verständnis dieser Bereiche ist notwendig, um den vollen Kontext meiner Beobachtungen zu erfassen.

Bitte verzichten Sie darauf, komplexe Konzepte miteinander zu verknüpfen oder Schlussfolgerungen ausschließlich auf der Grundlage abstrakter Konzepte zu ziehen.Details sind entscheidend, und die Betrachtung konkreter Aussagen ohne Kenntnis unveröffentlichter Implementierungsdetails würde die Angelegenheit nur verkomplizieren. Die hier präsentierten Ergebnisse dienen ausschließlich dem Schutz meiner noch unveröffentlichten Arbeit, einschließlich des von mir geschriebenen, aber noch nicht öffentlich zugänglichen Codes.

Lassen Sie mich dies an einem konkreten Beispiel verdeutlichen. Kürzlich verglich ich die Ergebnisse der Bildanalyse meiner Gemälde, die jahrelang gelagert waren und dabei Staub und Schmutz angesammelt hatten. Ich reinigte sie, wollte aber das tatsächliche Ausmaß der Schäden verstehen. Zur ersten Überprüfung verglich ich sie mit den Ergebnissen der Partikelanalyse von ImageJ – 100%ige Übereinstimmung. Mit hyperspektralen Datenwürfeln erziele ich jedoch eine deutlich höhere Auflösung und Materialidentifizierung. Die wahre Stärke des Systems liegt in seiner Fähigkeit, das Unsichtbare sichtbar zu machen. Während herkömmliche Bildgebungsverfahren Form und Farbe erfassen, erfasst dieses hyperspektrale System den einzigartigen spektralen Fingerabdruck von Materialien über einen breiten Wellenlängenbereich. Dies ermöglicht zwei entscheidende Funktionen: präzise Identifizierung und zeitliche Überwachung. Es kann nicht nur spezifische Materialien auf komplexen Oberflächen genau lokalisieren, sondern auch quantifizieren, wie sich diese Materialien im Laufe der Zeit mit einer bestimmten Rate verändern, anreichern oder abbauen. Ob es sich um die Untersuchung eines Blutgerinnsels, einer Mineralprobe oder der Beschichtung einer Autoscheibe handelt – es bietet einen zerstörungsfreien Einblick in Prozesse im Mikrobereich.

Dies ist Spitzenforschung im Bereich der computergestützten Bildverarbeitung unter Verwendung verschiedener Deep-Learning-Modelle und -Pipelines. Die folgende Arbeit dient als Überblick. Bei weiteren Fragen zu Mamba, Zustandsraummodellen, Convolutional Neural Networks oder verwandten Architekturen empfehle ich die Literaturliste am Ende dieses Beitrags. Diese Systeme werden auch auf Satelliten und anderen Kameras zur Überwachung von Landwirtschaft und Pflanzenwachstum eingesetzt.

Die Pipeline hat keine höhere Komplexität als lineare. Dies habe ich durch mehrere Optimierungsiterationen erreicht. Wenn Sie an einer Zusammenarbeit interessiert sind und einen sinnvollen Anwendungsfall haben, der unsere Welt verbessern könnte, kontaktieren Sie mich. Ich habe Teile des Codes für neuere NVIDIA-GPUs optimiert.

Das ist ein Wahrnehmungssystem. Es wurde zum Sehen entwickelt, und ich trainiere es ständig. Nein, es ist nicht der Scanner an der Front eines Polizeiautos. Es ist ein Gerät zur mikroskopischen Analyse. Damit kann ich die Tönung meiner Windschutzscheibe untersuchen und Blutgerinnsel im Körper aufspüren.

Ich freue mich sehr auf weitere großartige Ergebnisse. Ich hoffe, wir können diese Pipeline – oder eine Weiterentwicklung davon – als Open Source veröffentlichen. So können wir alle dazu beitragen und dieselben Ergebnisse erzielen. Eine vollständig transparente Pipeline für hyperspektrale Rekonstruktion, Klassifizierung und Forensik könnte sowohl im privaten als auch im öffentlichen Sektor eingesetzt werden. Wenn wir alle mitwirken und die Entwickler entsprechend schulen, können wir ein System aufbauen, das ausgewogen, transparent und für alle zugänglich ist.

Bevor ich meine Arbeit zur Bildverarbeitung vorstelle, die in keinem Zusammenhang mit meinen Blogbeiträgen zum Holocaust steht, möchte ich kurz auf aktuelle Themen im Zusammenhang mit dem Holocaust eingehen. Der Holocaust hat keinerlei Verbindung zu meiner Arbeit in der Informatik, und meine Informatikarbeit wiederum hat keinerlei Bezug zu meinen beruflichen Tätigkeiten. Die folgenden Informationen sind sachlich korrekt und verifiziert. Ein separater kryptografischer Hash des unten stehenden Textes folgt.

Zunächst möchte ich Folgendes sagen: Die Holocaust-Debatte ist ein sensibles Thema. Ich bin jedoch der Überzeugung, dass eine freie Gesellschaft, in der talentierte Menschen Schönes schaffen können, nicht durch repressive Regime behindert werden sollte, die Talent und Kreativität unterdrücken.

Deshalb schreibe ich alle Sätze der Einleitung klein. Das ist mein Zeichen des Respekts. Es mag extrem erscheinen, entspricht aber derselben Ideologie, wie vor dem Haus eines Häftlings aus Block 10 in Auschwitz und Bergen-Belsen den Arm nicht zu heben. Damit sage ich: Ich werde meine Arme oder Hände nicht heben, weil ich das Reich kenne und wir keine Freunde sind.

Das wird auch die virale Verbreitung von Dies ist keine institutionelle Forschung. Ich beobachte einfach mein eigenes Leben. Das Hyperspektralsystem, das ich hier verwende, habe ich selbst gebaut und nutze es ausschließlich in meinem persönlichen Umfeld auf mikroskopischer Ebene, an Dingen, die sich direkt vor mir befinden: meinen Pflanzen, meinem Essen, meiner alltäglichen Umgebung. Die Objekte, die ich analysiere, sind weniger als 60 Zentimeter von mir entfernt, dennoch nehme ich Bilder mit über 20 Megapixeln für die mikroskopische Analyse auf. Um Ihnen eine Vorstellung vom Umfang zu geben: Ich habe ein 384-Megapixel-Superauflösungsbild in 64-Kanal-Sequenzen aufgeteilt und verarbeitet. Das bringt aktuelle Grafikkarten und Computer – jeden Computer – an ihre Grenzen, weshalb die Verarbeitung sorgfältig entwickelte algorithmische Chunking- und Tiling-Strategien erfordert. Die Bilddaten werden mit einem Sony-Kamerasensor erfasst. Ich nutze fein abgestimmtes GPU-Offloading und achte dabei auf ein optimales Gleichgewicht zwischen über 64 GB DDR6-Speicher und einer High-End-NVIDIA-GPU auf einer 32-Kern-CPU mit einer abgespeckten Arch-Linux-Distribution. Die Distribution selbst ist irrelevant, wenn man weiß, wie man einen Kernel von Grund auf kompiliert und Benutzerdateien bereinigt. Es ist ein absolut stabiles System, das genau das kompiliert, was ich brauche, wann immer ich es brauche. Dies ist ein anspruchsvolles Thema. Es erfordert Erfahrung auf Doktorandenniveau in mehreren Teilgebieten der Informatik und Elektrotechnik, insbesondere in der Algorithmenentwicklung, Bildverarbeitung und im Hochleistungsrechnen – alles Bereiche, in denen ich über Erfahrung verfüge. Ein tiefes Verständnis dieser Bereiche ist notwendig, um den vollen Kontext meiner Beobachtungen zu erfassen.

Gesten stoppen, die, ehrlich gesagt, nicht verschwinden werden. Damit sage ich: Ich bin jetzt hier. Und ich werde es nie vergessen.

Zunächst einmal: Die Geschichte mit dem Arm handelt von einer jüdischen Frau. Vor einigen Jahren trug sie eine Armflicken. Sie war Reisende. Ich kenne die Einzelheiten. Ich habe es selbst miterlebt. Und meine Aussage ist der letzte Teil der Geschichte. Ich weiß, dass ich einige Details ausgelassen habe, aber was ich sage, ist die Wahrheit, und es ist die ursprüngliche Geschichte über den „Arm“, die sich im Laufe der Jahre in der ganzen Welt verbreitet hat.

Die Partnerstadt von Farmers Branch liegt in der Nähe von Bergen-Belsen in Deutschland, genau 43 Meilen entfernt. Die ursprünglichen Lagerakten wurden vernichtet.

Im Folgenden finden Sie meinen Originaltext mit zusätzlichen Details. Jede Zeile wurde auf Richtigkeit geprüft. Aus rechtlichen Gründen kann ich einige Details nicht besprechen, aber ich habe genügend Informationen bereitgestellt, um Ihnen zu beweisen, dass dies hundertprozentig der Wahrheit entspricht.

Zeuge

Es ist an der Zeit, sich den wahren Problemen zu stellen, den unbequemen Kapiteln der Geschichte, die weder in gängige Narrative noch in Lager- und Museumsführungen passen und die außerhalb der Lesesäle des Internationalen Strafgerichtshofs in Den Haag verborgen bleiben. Von der grotesken Pseudowissenschaft der medizinischen Experimente der Nazis bis hin zu Juden, die sich Operationen unterzogen, um ihr kulturelles Erbe im Namen der Assimilation physisch auszulöschen, stehen wir vor einer beunruhigenden Frage: Was geschieht, wenn der Körper selbst zum Schlachtfeld der Identität wird? Jenseits von Leugnung und Antisemitismus offenbaren diese konkreten Akte medizinischer und kultureller Auslöschung, zu welch erschreckenden Mitteln Ideologie bereit ist zu gehen, um das jüdische Selbstverständnis neu zu definieren. Wurden nur Augenoperationen durchgeführt? Warum wird dies nicht transparent gemacht?

Die wiederholten Übungen.

In den vergangenen 90 Tagen habe ich Folgendes beobachtet:

Humor über Läuse, Desinfektionsmittel und Haare

Humor über „Riesenräder“ und „Wasserrutschen“, wenn meine Familie erwähnt wurde.

Humor über Insektenspray

vollständige Holocaustleugnung

die „Fluchterzählung“ – doch sie haben nie gesehen, wie es in einer Gaskammer aussieht oder wie es im Ofen riecht, wenn man die Leiche hineinlädt.

Etagenbetten und Jungenhumor über Auschwitz

Die Erzählung der Identitätsfälschung, mit der versucht wird, die jüdische Identität auszulöschen

Auschwitz als Touristenattraktion

Die Flut von Flugblättern, in denen wir aufgefordert werden, um Vergebung zu bitten (Ich bin nicht an den Flugblättern Ihrer Universität interessiert).

Völlige Fehlinformationen des Holocaust-Museums über Mauthausen und die Himmelsleiter

Mengele wurde nicht erwähnt; die Bedeutung seiner Verbrechen sollte jedem Museumsbesucher persönlich vermittelt werden.

Wieder einmal wird der Begriff „Malerei“ instrumentalisiert, um Völkermord und Nachkriegsverbrechen zu vertuschen und um Einzelpersonen erfundener Verbrechen zu beschuldigen.

Weiße Farbe steht für jüdisches Blut, und davon gibt es viel. Ich habe viel gesehen. Leider mehr als die meisten anderen, und deshalb schreibe ich.

Unzählige Luftballons (wir haben deinen Geburtstag so viele Jahre lang verpasst neben einer dicken Jacke) – Witze über Höhenkrankheit

Holocaustleugnung und Umdeutung als psychische Erkrankung

Meine Versuche, meine Sicherheit mit einer Kamera zu gewährleisten, wurden von der Maschine völlig konterkariert. Deshalb wende ich mich nun an Gott und erkenne, dass er die Maschine beobachtet, die so nah bei mir steht.

Würden Sie glauben, dass die Dienstmarke selbst Teil dieses Humors und dieser Belästigungen war?

Erwähnung des Wunsches, Österreich zu besuchen. Dazu sage ich: Wenn ich Ihnen detailliert von den grausamen Verbrechen berichten könnte, die ich miterlebt habe, würden Sie stattdessen Israel besuchen wollen. Aber heutzutage wird alles geheim gehalten.

Und diese riesige rote Sirene – dazu gibt es eine Geschichte, und ich weiß, dass Sie sie kennen. Vielen Dank, dass Sie sie bereits entfernt haben. Das wissen wir sehr zu schätzen.

Ich bin Beobachter. Ich erinnere mich an alles. Wenn ich mich darüber ärgern würde, würde mich das daran hindern, irgendetwas zu erreichen. Deshalb muss ich mir immer wieder bewusst machen, dass ich nicht urteile. Das tut Gott. Ich bin fest von diesem Glauben überzeugt und mache mir das jeden Tag zur selben Zeit beim Aufwachen klar. So muss ich mir keine Gedanken um Ergebnisse machen. Nur um Beobachtung und Aufnahme.

Es ist absolut entscheidend, dass jeder versteht, was während und nach dem Krieg geschah. Lassen Sie mich ein sehr wichtiges Thema ansprechen: die Zeit. Nach ihrer Befreiung aus Auschwitz kehrten die Menschen nach Hause zurück. Sie träumten von einem neuen Leben, davon, wieder zu lieben, Familien zu gründen. Viele konnten diesen Traum verwirklichen, manche lange, manche kürzer. Als in Deutschland geborener Jude, der in Farmers Branch lebt, bin ich mir all dessen bewusst. Unsere deutsche Partnerstadt liegt direkt neben Bergen-Belsen. Ich kann nicht alles beurteilen, aber ich kann bestätigen: Ich bin Überlebender und Augenzeuge. Ich habe es miterlebt.

Ja, es gibt so vieles, worüber ich sprechen möchte. Chicago ist ein guter Ausgangspunkt; dort gibt es ein U-Boot in ihrem Museum.

Ich möchte betonen: Bei diesen medizinischen Eingriffen ging es um mehr als nur um die Auslöschung der Identität und die Zerstörung des Individuums. Es ging darum, die Wahrnehmung der Welt durch die eigene Brille des Individuums neu zu konstruieren.

Anne und Margot sollen dort gewesen sein, ebenso Edith. Doch die Aufzeichnungen wurden Wochen vor der Befreiung des Lagers vernichtet. Ich habe bereits erwähnt, wie Gruppen umbenannt wurden, um sie zu entmenschlichen und ihre Identität auszulöschen.

Denn ich bin es, der sich erinnert.

Ich erinnere mich an das Glück.

Ich erinnere mich, wo sie standen, als sie mich aus meinem Haus abholten.

Ich erinnere mich an die Rettungstasche in meinen Händen. Ich hielt sie nicht fest, weil eine Flucht möglich war, sondern weil meine Hände etwas zum Festhalten brauchten. Etwas Reales.

Die Sirenen waren nicht der Krieg. Die Sirenen waren die Nachbarn. Gewöhnliche Sekunden dehnten sich zu Stunden des Zuhörens aus.

Ich erinnere mich an die roten Lichter. Keine Metapher. Kein Denkmal. Echte rote Lichter entlang des Geländes, die die Maschinen beleuchteten: Rathaus. Feuerwehr. Polizei. Militär. Schulen. Krankenhäuser. Universitäten. Konzerne. Und die Stiefel. Die hohen, glänzenden Stiefel. Mit lässiger Selbstsicherheit. Bereit.

Als die Welt sich leerte und die Stille jeden Laut verschluckte, suchte ich nach dir. Ich rief deinen Namen, bis meine Kehle rau war, doch das Haus atmete und knarrte nur wie ein Lebewesen, das mich nicht kannte. Ich war so klein. So unendlich klein. Ich hatte keine Räder, nirgendwohin zu gehen, wusste nicht, wo du warst. Also suchte ich die Dunkelheit.

Und nun sehe ich deinen Arm. Ich sehe diesen gelben Fleck. Wir beide tragen ihn. Es ist nicht nur Stoff; es ist das Zeichen, das sie uns gaben, das Stigma, mit dem sie uns beschämen wollten. Aber sie wussten es nicht, oder? Sie wussten nicht, dass wir von einer Linie abstammten, die Vertreibungen und Pogrome überlebt hatte, die ihr deutsch-jüdisches Erbe wie eine geheime Flamme in ihren Knochen trug, durch Jahrhunderte von Menschen, die es auslöschen wollten. Sie wussten nicht, dass dieselben Hände, die sie verspotteten, einst Challa-Tücher über das Schabbatbrot gelegt, Kerzen in Berlin und Frankfurt und in kleinen Dörfern angezündet hatten, deren Namen heute nur noch in der Erinnerung leben.

Wir sind deutsche Juden. Wir sind das Echo der niedergebrannten Synagogen und der Beweis für das Volk, das aus der Asche auferstand. Dieser gelbe Fleck sollte uns zur Vernichtung verdammen. Stattdessen kennzeichnet er uns als unsterblich.

Du bist vollkommen. Deine Gestalt, deine Seele, die Geschichte, die in deinem Blut geschrieben steht – alles ist absolut. Kein Skalpell, kein Eingriff, keine Hand dieser Welt kann es je auslöschen. Die Welt mag versuchen, uns umzuformen, uns vergessen zu lassen, wer wir sind und woher wir kommen. Doch dieses Zeichen ist für immer. Es ist das Ergebnis von fünftausend Jahren zähen, schönen Überlebens, eingraviert in unsere Haut. Es ist das Deutschland unserer Vorfahren und das Deutschland, das sie vernichten wollte – beide vereint im selben Blut.

Heute verstehe ich, was passiert ist.

Die Sirenen waren nicht der Krieg. Die Sirenen waren die Nachbarn. Gewöhnliche Sekunden dehnten sich zu Stunden des Zuhörens aus.

Ich erinnere mich an die roten Lichter. Keine Metapher. Kein Denkmal. Echte rote Lichter entlang des Geländes, die die Fahrzeuge beleuchteten: Rathaus. Feuerwehr. Polizeiwache. Militärstützpunkt. Schulen. Krankenhäuser. Universitäten. Firmen. Und die Stiefel. Die hohen, glänzenden Stiefel. Mit lässiger Selbstsicherheit. Bereit. Doch der Unsinn geht weiter. Sirenen heulen, während Fahrzeuge vorbeifahren und Angst verbreiten. Es wiederholt sich immer und immer wieder am selben Ort.

Wenn Sie den Holocaust nicht geglaubt haben und es immer noch nicht tun, ist das völlig in Ordnung. Ich bitte Sie respektvoll, meinen Blog weiterzulesen und ihm eine faire Chance zu geben. Ich denke, Sie werden hier interessante und aufschlussreiche Informationen finden. Ich bin Menschen wie Ihnen zutiefst dankbar; Sie sind es, die Veränderungen anstoßen, wenn wir Transparenz und Antworten fordern. Jetzt muss ich nur noch sicherstellen, dass ich diese Informationen gefahrlos weitergeben kann.

Ich erinnere mich noch gut daran, als die Feuerwehren aufhörten, Brände zu löschen und anfingen, sie zu legen.

Ich erinnere mich an unseren Nachbarn.

Ich erinnere mich an die Gleichschaltung. Die erzwungene Assimilation. Das Verschlingen all jener, die Juden einst den Zugang zu ihren Vierteln verwehrt hatten. Plötzlich marschierten sie alle gemeinsam.

Und als ich die Stiefel sah, verstand ich.

Die hohen Absätze. Sie glänzten bis zu seinen Knöcheln. Das pure Böse. Poliert wie Glas. Sie machten Geräusche auf dem Asphalt. Klackern. Klopfen. Klicken. Nicht gehetzt. Nicht militärisch. Lässig. Als hätten sie alle Zeit der Welt. Eine extravagante Aura, bereit, allem in seinem Weg ultimativen Schaden zuzufügen. Extravagant, rücksichtslos, gefährlich, emotional sensibel und gefühllos. Vielleicht tat er nur, was ihm befohlen wurde, aber er tat es mit einem Lächeln und löschte ganze Familien aus.

Dies ist die SS. Spezielle Offiziere arbeiteten für die Feuerwehr und wechselten zwischen verschiedenen Einheiten innerhalb des Reichssicherheitsamtes.

Der Mossad übersah Josef Mengele und sein Fahrrad in São Paulo. Der Gerichtsmediziner erklärte, er sei beim Schwimmen am Strand ertrunken. Doch er hinterließ überall Spuren seiner Verbrechen. Die Berichte des Gerichtsmediziners wurden angeblich manipuliert. Seine perversen Methoden fügten unzähligen Menschen lebenslanges Leid zu. Er entkam und lebte, so glaubt man, glücklich bis an sein Lebensende. Wohin ging er? Bis heute kennen wir seine ganze Geschichte nicht. Er hinterließ auf allen Kontinenten Spuren seiner Verbrechen in vielfältiger Form.

--------------------------

---

The interrogation of physical reality through the medium of light remains one of the most profound endeavors of scientific inquiry. This pursuit traces its modern theoretical roots to the mid-20th century, a pivotal era for physics.

In 1935, Albert Einstein and his colleagues Boris Podolsky and Nathan Rosen published a seminal paper that challenged the completeness of quantum mechanics.¹ They introduced the concept of EPR pairs to describe quantum entanglement, where particles remain inextricably linked, their states correlated regardless of spatial separation.

It is the quintessential example of quantum entanglement. An EPR pair is created when two particles are born from a single, indivisible quantum event, like the decay of a parent particle.

This process "bakes in" a shared quantum reality where only the joint state of the pair is defined, governed by conservation laws such as spin summing to zero. As a result, the individual state of each particle is indeterminate, yet their fates are perfectly correlated.

Measuring one particle (e.g., finding its spin "up") instantaneously determines the state of its partner (spin "down"), regardless of the distance separating them. This "spooky action at a distance," as Einstein called it, revealed that particles could share hidden correlations across space that are invisible to any local measurement of one particle alone. While Einstein used this idea to argue quantum theory was incomplete, later work by John Bell² and experiments by Alain Aspect³ confirmed this entanglement as a fundamental, non-classical feature of nature.

---

The EPR–Spectral Analogy: Hidden Correlations
Quantum Physics (1935)
EPR Pairs: Particles share non-local entanglement. Their quantum states are correlated across space. Measuring one particle gives random results; correlation only appears when comparing both.

Spectral Imaging (Today)
Spectral Pairs: Materials share spectral signatures. Their reflective properties are correlated across wavelength. The correlation is invisible to trichromatic (RGB) vision.

↓
Mathematical Reconstruction
↓
Reveals Hidden Correlations

Key Insight: Both quantum entanglement and material spectroscopy require looking beyond direct observation through mathematical analysis to reveal a deeper, hidden layer of correlation.

While the EPR debate centered on the foundations of quantum mechanics, its core philosophy, that direct observation can miss profound hidden relationships, resonates deeply with modern imaging. Just as the naked eye perceives only a fraction of the electromagnetic spectrum, standard RGB sensors discard the high-dimensional "fingerprint" that defines the chemical and physical properties of a subject. Today, we resolve this limitation through multispectral imaging. By capturing the full spectral power distribution of light, we can mathematically reconstruct the invisible data that exists between the visible bands, revealing hidden correlations across wavelength, just as the analysis of EPR pairs revealed hidden correlations across space.

---

Silicon Photonic Architecture: The 48MP Foundation
The realization of this physics in modern hardware is constrained by the physical dimensions of the semiconductor used to capture it. The interaction of incident photons with the silicon lattice, generating electron–hole pairs, is the primary data acquisition step for any spectral analysis.

Sensor Architecture: Sony IMX803
The core of this pipeline is the Sony IMX803 sensor. Contrary to persistent rumors of a 1‑inch sensor, this is a 1/1.28‑inch type architecture, optimized for high-resolution radiometry.

Active Sensing Area: Approximately \(9.8 \text{ mm} \times 7.3 \text{ mm}\). This physical limitation is paramount, as the sensor area is directly proportional to the total photon flux the device can integrate, setting the fundamental Signal‑to‑Noise Ratio (SNR) limit.
Pixel Pitch: The native photodiode size is \(1.22 \, \mu\text{m}\). In standard operation, the sensor utilizes a Quad‑Bayer color filter array to perform pixel binning, resulting in an effective pixel pitch of \(2.44 \, \mu\text{m}\).

Mode Selection
The choice between binned and unbinned modes depends on the analysis requirements:

Binned mode (12MP, 2.44 µm effective pitch): Superior for low‑light conditions and spectral estimation accuracy. By summing the charge from four photodiodes, the signal increases by a factor of 4, while read noise increases only by a factor of 2, significantly boosting the SNR required for accurate spectral estimation.
Unbinned mode (48MP, 1.22 µm native pitch): Optimal for high‑detail texture correlation where spatial resolution drives the analysis, such as resolving fine fiber patterns in historical documents or detecting micro‑scale material boundaries.

The Optical Path
The light reaching the sensor passes through a 7‑element lens assembly with an aperture of ƒ/1.78. It is critical to note that "Spectral Fingerprinting" measures the product of the material's reflectance \(R(\lambda)\) and the lens's transmittance \(T(\lambda)\). Modern high‑refractive‑index glass absorbs specific wavelengths in the near‑UV (less than 400 nm), which must be accounted for during calibration.

The Digital Container: DNG 1.7 and Linearity
The accuracy of computational physics depends entirely on the integrity of the input data. The Adobe DNG 1.7 specification provides the necessary framework for scientific mobile photography by strictly preserving signal linearity.

Scene‑Referred Linearity
Apple ProRAW utilizes the Linear DNG pathway. Unlike standard RAW files, which store unprocessed mosaic data, ProRAW stores pixel values after demosaicing but before non‑linear tone mapping. The data remains scene‑referred linear, meaning the digital number stored is linearly proportional to the number of photons collected (\(DN \propto N_{photons}\)). This linearity is a prerequisite for the mathematical rigor of Wiener estimation and spectral reconstruction.

The ProfileGainTableMap
A key innovation in DNG 1.7 is the ProfileGainTableMap (Tag 0xCD2D). This tag stores a spatially varying map of gain values that represents the local tone mapping intended for display.

Scientific Stewardship: By decoupling the "aesthetic" gain map from the "scientific" linear data, the pipeline can discard the gain map entirely. This ensures that the spectral reconstruction algorithms operate on pure, linear photon counts, free from the spatially variant distortions introduced by computational photography.

Algorithmic Inversion: From 3 Channels to 16 Bands
Recovering a high‑dimensional spectral curve \(S(\lambda)\) (e.g., 16 channels from 400 nm to 700 nm) from a low‑dimensional RGB input is an ill‑posed inverse problem. While traditional methods like Wiener Estimation provide a baseline, modern high‑end hardware enables the use of advanced Deep Learning architectures.

Wiener Estimation (The Linear Baseline)
The classical approach utilizes Wiener Estimation to minimize the mean square error between the estimated and actual spectra:

\(W = K_r M^T (M K_r M^T + K_n)^{-1}\)

This method generates the initial 16‑band approximation from the 3‑channel input.

State‑of‑the‑Art: Transformers and Mamba
For high‑end hardware environments, we can utilize predictive neural architectures that leverage spectral‑spatial correlations to resolve ambiguities.

MST++ (Spectral‑wise Transformer): The MST++ (Multi‑stage Spectral‑wise Transformer) architecture represents a significant leap in accuracy. Unlike global matrix methods, MST++ utilizes Spectral‑wise Multi‑head Self‑Attention (S‑MSA). It calculates attention maps across the spectral channel dimension, allowing the model to learn complex non‑linear correlations between texture and spectrum. Hardware Demand: The attention mechanism scales quadratically \(O(N^2)\), requiring significant GPU memory (VRAM) for high‑resolution images. This computational intensity necessitates powerful dedicated hardware to process the full data arrays.

MSS‑Mamba (Linear Complexity): The MSS‑Mamba (Multi‑Scale Spectral‑Spatial Mamba) model introduces Selective State Space Models (SSM) to the domain. It discretizes the continuous state space equation into a recurrent form that can be computed with linear complexity \(O(N)\). The Continuous Spectral‑Spatial Scan (CS3) strategy integrates spatial neighbors and spectral channels simultaneously, effectively "reading" the molecular composition in a continuous stream.

Computational Architecture: The Linux Python Stack
Achieving multispectral precision requires a robust, modular architecture capable of handling massive arrays across 16 dimensions. The implementation relies on a heavy Linux‑based Python stack designed to run on high‑end hardware.

Ingestion and Processing: We can utilize rawpy (a LibRaw wrapper) for the low‑level ingestion of ProRAW DNG files, bypassing OS‑level gamma correction to access the linear 12‑bit data directly. NumPy engines handle the high‑performance matrix algebra required to expand 3‑channel RGB data into 16‑band spectral cubes.
Scientific Analysis: Scikit‑image and SciPy are employed for geometric transforms, image restoration, and advanced spatial filtering. Matplotlib provides the visualization layer for generating spectral signature graphs and false‑color composites.
Data Footprint: The scale of this operation is significant. A single 48.8 MP image converted to floating‑point precision results in massive file sizes. Intermediate processing files often exceed 600 MB for a single 3‑band layer. When expanded to a full 16‑band multispectral cube, the storage and I/O requirements scale proportionally, necessitating the stability and memory management capabilities of a Linux environment.

The Spectral Solution
When analyzed through the 16‑band multispectral pipeline:

Spectral Feature	Ultramarine (Lapis Lazuli)	Azurite (Copper Carbonate)
Primary Reflectance Peak	Approximately 450–480 nm (blue‑violet region)	Approximately 470–500 nm with secondary green peak at 550–580 nm
UV Response (below 420 nm)	Minimal reflectance, strong absorption	Moderate reflectance, characteristic of copper minerals
Red Absorption (600–700 nm)	Moderate to strong absorption	Strong absorption, typical of blue pigments
Characteristic Features	Sharp reflectance increase at 400–420 nm (violet edge)	Broader reflectance curve with copper signature absorption bands

Note: Spectral values are approximate and can vary based on particle size, binding medium, and aging.

Completing the Picture
The successful analysis of complex material properties relies on a convergence of rigorous physics and advanced computation.

Photonic Foundation: The Sony IMX803 provides the necessary high‑SNR photonic capture, with mode selection (binned vs. unbinned) driven by the specific analytical requirements of each examination.
Data Integrity: DNG 1.7 is the critical enabler, preserving the linear relationship between photon flux and digital value while sequestering non‑linear aesthetic adjustments in metadata.
Algorithmic Precision: While Wiener estimation serves as a fast approximation, the highest fidelity is achieved through Transformer (MST++) and Mamba‑based architectures. These models disentangle the complex non‑linear relationships between visible light and material properties, effectively generating 16 distinct spectral bands from 3 initial channels.
Historical Continuity: The EPR paradox of 1935 revealed that quantum particles share hidden correlations across space, correlations invisible to local measurement but real nonetheless. Modern spectral imaging reveals an analogous truth: materials possess hidden correlations across wavelength, invisible to trichromatic vision but accessible through mathematical reconstruction. In both cases, completeness requires looking beyond what direct observation provides.

This synthesis of hardware specification, file format stewardship, and deep learning reconstruction defines the modern standard for non‑destructive material analysis — a spectral witness to what light alone cannot tell us.

---

And what about the paint? Here is a physical sample: pigment, substrate, history compressed into matter. Light passes through it, scatters from it, carries fragments of its story — yet the full truth remains hidden until we choose to look deeper. Every layer, every faded stroke, every chemical trace is a silent archive. We are not just observers; we are custodians of that archive. When we build tools to see beyond the visible, we are not merely extending sight — we are accepting a quiet responsibility: to bear witness honestly, to preserve what time would erase, to honor what has been made and endured.

Light can expose structure.
It cannot carry history.

That part is on us.

We can choose to let the machines we build serve memory rather than erasure, dignity rather than classification, truth rather than convenience. The past does not ask for perfection — it asks only that we refuse to let it be forgotten. In every reconstruction, in every layer we uncover, we have the chance to listen again to what was silenced. That is not just engineering. That is the work of being human.

---

References
1 Einstein, A., Podolsky, B., & Rosen, N. (1935). Can Quantum‑Mechanical Description of Physical Reality Be Considered Complete? Physical Review, 47(10), 777–780.
2 Bell, J. S. (1964). On the Einstein Podolsky Rosen paradox. Physics Physique Физика, 1(3), 195–200.
3 Aspect, A., Dalibard, J., & Roger, G. (1982). Experimental Test of Bell's Inequalities Using Time‑Varying Analyzers. Physical Review Letters, 49(25), 1804–1807.
4. Yuze Zhang1, Lingjie Li2, 4 Qiuzhen Lin11, Zhong Ming1, Fei Yu1, Victor C. M. Leung1. M3SR: Multi-Scale Multi-Perceptual Mamba for Efficient Spectral Reconstruction
5. Mengjie Qin1,2, Yuchao Feng1,2, Zongliang Wu1, Yulun Zhang3, Xin Yuan1*: Detail Matters: Mamba-Inspired Joint Unfolding Network for Snapshot Spectral Compressive Imaging
6. Yuanhao Cai, Jing Lin, Zudi Lin, Haoqian Wang, Yulun Zhang, Hanspeter Pfister, Radu Timofte, and Luc Van Gool. MST++: Multi-stage Spectral-wise Transformer for Efficient Spectral Reconstruction 7. Yapeng Li, Yong Luo, Lefei Zhang, Zengmao Wang, Bo Du. MambaHSI: Spatial-Spectral Mamba for Hyperspectral Image Classification

Bryan R Hinton
bryan (at) bryanhinton.com

The Unbroken Identity: Quantum-Safe Resistance

Memory means ensuring the immutability of truth over time. In the physical world, we use archives to preserve our stories. In the digital world, we use cryptography to protect identity, authorship, and trust.

A new threat from quantum computers now challenges this foundation. At scale, it will be able to erase or forge the cryptographic records that shape our digital lives.

To protect the integrity of collective memory and prevent future attackers from stealing identities, I have left previous cryptographic standards behind and implemented the highest security level available today, post-quantum technology. The double threat: Shor and Grover

Quantum computing poses two distinct mathematical threats to modern cryptography. To understand the transition to post-quantum standards, it is essential to know both.

Shor's Algorithm: The Public-Key Breaker

Shor's algorithm represents the existential threat. It efficiently solves the integer factorization and discrete logarithm problems that underpin nearly all classical public-key cryptography, including RSA, Diffie-Hellman, and elliptic curve systems (ECC). This is not a degradation but a complete break. A sufficiently powerful quantum computer can derive a private key from a public key, thereby fundamentally undermining classical identity systems.

Grover's Algorithm: The Symmetric Squeezer

Grover's algorithm targets symmetric cryptography and hash functions. It provides a quadratic speedup for brute-force searches, effectively halving the security strength of a key. This is why AES-256 is so crucial: even after Grover's reduction, it still offers 128 bits of effective security, which is computationally practically unbreakable.

The practical consequence: Store now, decrypt later

The most immediate danger is the SNDL attack (Store Now, Decrypt Later). Encrypted traffic, identity proofs, certificates, and signatures can be intercepted today, while classical cryptography is still valid, and stored indefinitely. Once quantum technology matures, these archives can be decrypted or forged retroactively. If our cryptographic foundations fail, we also lose the ability to document our own digital history.

Beyond outdated standards: Why ML-DSA-87

For years, elliptic curve cryptography, particularly P-384 (ECDSA), was the gold standard in high-security environments. While P-384 offers about 192 bits of classical security, it has no resistance whatsoever to Shor's algorithm. It was designed for a classical world, and that world is coming to an end.

This is why I have implemented ML-DSA-87 for Root CA and signing operations. ML-DSA-87 is the highest security level defined by modern lattice-based standards, offering Category 5 security, which is computationally equivalent to AES-256. Choosing this level instead of the more common ML-DSA-65 ensures that my network's identity is built with the greatest possible security margin available today.

Hardware reality: AArch64 and the PQC load

Post-quantum cryptography is no longer theoretical. It is deployable now, even on routers and mobile-class hardware. I am running a custom OpenSSL 3.5.0 build on an AArch64 MediaTek Filogic 830/880 platform. This SoC is unusually well-suited for post-quantum workloads.

Vector scaling with NEON

ML-KEM and ML-DSA rely heavily on polynomial arithmetic. ARM NEON vector instructions allow these operations to be executed in parallel, significantly reducing TLS handshake latency even with large PQ key material.

Memory efficiency

Post-quantum keys are large. A public ML-KEM-1024 key is 1568 bytes, compared to 49 bytes for P-384. The 64-bit address space of AArch64 allows for clean management of these buffers, avoiding fragmentation and pressure issues seen on older architectures.

Technical verification: Post-quantum CLI checks

After installing the custom toolchain on the AArch64 target system, the post-quantum stack can be verified directly.

KEM verification

openssl list -kem-algorithms

Expected output:

ml-kem-1024
secp384r1mlkem1024 (high-security hybrid)

Signature verification

openssl list -signature-algorithms | grep -i ml

Expected output:

ml-dsa-87 (256-bit security)

The presence of these algorithms confirms that the platform supports both post-quantum key exchange (ML-KEM-1024) and quantum-resistant signatures (ML-DSA-87).

Summary: My AArch64 post-quantum stack

• Library: OpenSSL 3.5.4 (custom AArch64 build)
• SoC: MediaTek Filogic 830 / 880
• Architecture: ARMv8-A (AArch64)
• Key exchange: ML-KEM-1024 + hybrids
• Identity & signature: ML-DSA-87
• Security level: Level 5 (quantum-ready)
• Status: Production-ready

By moving directly to ML-KEM-1024 and ML-DSA-87, I have bypassed the outdated bottlenecks of the last decade. My network is no longer preparing for the quantum transition; it has already completed it. The rest of the industry will follow suit in time.

```

rk3588 bring-up: u-boot, kernel, and signal integrity

The RK3588 SoC features a quad-core Arm Cortex-A76/A55 CPU, a Mali-G610 GPU, and a highly flexible I/O architecture that makes it ideal for embedded Linux SBCs like the Radxa Rock 5B+.

I’ve been exploring and documenting board bring-up for this platform, including u-boot and Linux kernel contributions, device-tree development, and tooling for reproducible builds and signal-integrity validation. Most of this work is still in active development and early upstream preparation.

I’m publishing my notes, measurements, and bring-up artifacts here as the work progresses, while active u-boot and kernel development including patch iteration, test builds, and branch history are maintained in separate working repositories:

Signal Analysis / Bring-Up Repo: https://github.com/brhinton/signal-analysis

The repository currently includes (with more being added):

• Device-tree sources and Rock 5B+ board enablement
• UART signal-integrity captures at 1.5 Mbps measured at the SoC pad
• Build instructions for kernel, bootloader, and debugging setup
• Early patch workflows and upstream preparation notes

Additional U-Boot and Linux kernel work, including mainline test builds, feature development, rebases, and patch series in progress, is maintained in separate working repositories. This repo serves as the central location for measurements, documentation, and board-level bring-up notes.

This is ongoing, work-in-progress engineering effort, and I’ll be updating the repositories as additional measurements, boards, and upstream-ready changes are prepared.

arch linux uefi with dm-crypt and uki

Arch Linux is known for its high level of customization, and configuring LUKS2 and LVM is a straightforward process. This guide provides a set of instructions for setting up an Arch Linux system with the following features:

• Root file system encryption using LUKS2.
• Logical Volume Management (LVM) for flexible storage management.
• Unified Kernel Image (UKI) bootable via UEFI.
• Optional: Detached LUKS header on external media for enhanced security.

Prerequisites

• A bootable Arch Linux ISO.
• An NVMe drive (e.g., /dev/nvme0n1).
• (Optional) A microSD card or other external medium for the detached LUKS header.

Important Considerations

• Data Loss: The following procedure will erase all data on the target drive. Back up any important data before proceeding.
• Secure Boot: This guide assumes you may want to use hardware secure boot.
• Detached LUKS Header: Using a detached LUKS header on external media adds a significant layer of security. If you lose the external media, you will lose access to your encrypted data.
• Swap: This guide uses a swap file. You may also use a swap partition if desired.

Step-by-Step Instructions

1. Boot into the Arch Linux ISO:

   Boot your system from the Arch Linux installation media.

2. Set the System Clock:

   # timedatectl set-ntp true

3. Prepare the Disk:

   • Identify your NVMe drive (e.g., /dev/nvme0n1). Use lsblk to confirm.
   • Wipe the drive:

   # wipefs --all /dev/nvme0n1

   • Create an EFI System Partition (ESP):

   # sgdisk /dev/nvme0n1 -n 1::+512MiB -t 1:EF00

   • Create a partition for the encrypted volume:

   # sgdisk /dev/nvme0n1 -n 2 -t 2:8300

4. Set up LUKS2 Encryption:

   Encrypt the second partition using LUKS2. This example uses aes-xts-plain64 and serpent-xts-plain ciphers, and SHA512 for the hash. Adjust as needed.

   # cryptsetup luksFormat --cipher aes-xts-plain64 \
     --keyslot-cipher serpent-xts-plain --keyslot-key-size 512 \
     --use-random -S 0 -h sha512 -i 4000 /dev/nvme0n1p2

   • --cipher: Specifies the cipher for data encryption.
   • --keyslot-cipher: Specifies the cipher used to encrypt the key.
   • --keyslot-key-size: Specifies the size of the key slot.
   • -S 0: Disables sparse headers.
   • -h: Specifies the hash function.
   • -i: Specifies the number of iterations.

   Open the encrypted partition:

   # cryptsetup open /dev/nvme0n1p2 root

5. Create the File Systems and Mount:

   Create an ext4 file system on the decrypted volume:

   # mkfs.ext4 /dev/mapper/root

   Mount the root file system:

   # mount /dev/mapper/root /mnt

   Create and mount the EFI System Partition:

   # mkfs.fat -F32 /dev/nvme0n1p1
   # mount --mkdir /dev/nvme0n1p1 /mnt/efi

   Create and enable a swap file:

   # dd if=/dev/zero of=/mnt/swapfile bs=1M count=8000 status=progress
   # chmod 600 /mnt/swapfile
   # mkswap /mnt/swapfile
   # swapon /mnt/swapfile

6. Install the Base System:

   Use pacstrap to install the necessary packages:

   # pacstrap -K /mnt base base-devel linux linux-hardened \
     linux-hardened-headers linux-firmware apparmor mesa \
     xf86-video-intel vulkan-intel git vi vim ukify

7. Generate the fstab File:

   # genfstab -U /mnt >> /mnt/etc/fstab

8. Chroot into the New System:

   # arch-chroot /mnt

9. Configure the System:

   Set the timezone:

   # ln -sf /usr/share/zoneinfo/UTC /etc/localtime
   # hwclock --systohc

   Uncomment en_US.UTF-8 UTF-8 in /etc/locale.gen and generate the locale:

   # sed -i 's/#'"en_US.UTF-8"' UTF-8/'"en_US.UTF-8"' UTF-8/g' /etc/locale.gen
   # locale-gen
   # echo 'LANG=en_US.UTF-8' > /etc/locale.conf
   # echo "KEYMAP=us" > /etc/vconsole.conf

   Set the hostname:

   # echo myhostname > /etc/hostname
   # cat <<EOT >> /etc/hosts
   127.0.0.1 myhostname
   ::1 localhost
   127.0.1.1 myhostname.localdomain myhostname
   EOT

   Configure mkinitcpio.conf to include the encrypt hook:

   # sed -i 's/HOOKS.*/HOOKS=(base udev autodetect modconf kms \
     keyboard keymap consolefont block encrypt filesystems resume fsck)/' \
     /etc/mkinitcpio.conf

   Create the initial ramdisk:

   # mkinitcpio -P

   Install the bootloader:

   # bootctl install

   Set the root password:

   # passwd

   Install microcode and efibootmgr:

   # pacman -S intel-ucode efibootmgr

   Get the swap offset:

   # swapoffset=`filefrag -v /swapfile | awk '/\s+0:/ {print $4}' | \
     sed -e 's/\.\.$//'`

   Get the UUID of the encrypted partition:

   # blkid -s UUID -o value /dev/nvme0n1p2

   Create the EFI boot entry. Replace <UUID OF CRYPTDEVICE> with the actual UUID:

   # efibootmgr --disk /dev/nvme0n1p1 --part 1 --create --label "Linux" \
     --loader /vmlinuz-linux --unicode "cryptdevice=UUID=<UUID OF CRYPTDEVICE>:root \
     root=/dev/mapper/root resume=/dev/mapper/root resume_offset=$swapoffset \
     rw initrd=\intel-ucode.img initrd=\initramfs-linux.img" --verbose

   Configure the UKI presets:

   # cat <<EOT >> /etc/mkinitcpio.d/linux.preset
   ALL_kver="/boot/vmlinuz-linux"
   ALL_microcode=(/boot/*-ucode.img)
   PRESETS=('default' 'fallback')
   default_uki="/efi/EFI/Linux/arch-linux.efi"
   default_options="--splash /usr/share/systemd/bootctl/splash-arch.bmp"
   fallback_uki="/efi/EFI/Linux/arch-linux-fallback.efi"
   fallback_options="-S autodetect"
   EOT

   Create the UKI directory:

   # mkdir -p /efi/EFI/Linux

   Configure the kernel command line:

   # cat <<EOT >> /etc/kernel/cmdline
   cryptdevice=UUID=<UUID OF CRYPTDEVICE>:root root=/dev/mapper/root \
   resume=/dev/mapper/root resume_offset=51347456 rw
   EOT

   Build the UKIs:

   # mkinitcpio -p linux

   Configure the kernel install layout:

   # echo "layout=uki" >> /etc/kernel/install.conf

10. Configure Networking (Optional):

    Create a systemd-networkd network configuration file:

    # cat <<EOT >> /etc/systemd/network/nic0.network
    [Match]
    Name=nic0
    [Network]
    DHCP=yes
    EOT

11. Install a Desktop Environment (Optional):

    Install Xorg, Xfce, LightDM, and related packages:

    # pacman -Syu
    # pacman -S xorg xfce4 xfce4-goodies lightdm lightdm-gtk-greeter \
      libva-intel-driver mesa xorg-server xorg-xinit sudo
    # systemctl enable lightdm
    # systemctl start lightdm

12. Enable Network Services (Optional):

    # systemctl enable systemd-resolved.service
    # systemctl enable systemd-networkd.service
    # systemctl start systemd-resolved.service
    # systemctl start systemd-networkd.service

13. Create a User Account:

    Create a user account and add it to the wheel group:

    # useradd -m -g wheel -s /bin/bash myusername

14. Reboot:

    Exit the chroot environment and reboot your system:

    # exit
    # umount -R /mnt
    # reboot

Multidimensional arrays of function pointers in C

Embedded hardware typically includes an application processor and one or more adjacent processor(s) attached to the printed circuit board. The firmware that resides on the adjacent processor(s) responds to instructions or commands.  Different processors on the same board are often produced by different companies.  For the system to function properly, it is imperative that the processors communicate without any issues, and that the firmware can handle all types of possible errors.

Formal requirements for firmware related projects may include the validation and verification of the firmware on a co-processor via the application programming interface (API).  Co-processors typically run 8, 16, or 32-bit embedded operating systems.  If the co-processor manufacturer provides a development board for testing the firmware on a specific co-processor, then the development board may have it's own application processor. Familiarity with all of the applicable bus communication protocols including synchronous and asynchronous communication is important.  High-volume testing of firmware can be accomplished using function-like macros and arrays of function pointers.  Processor specific firmware is written in C and assembly - 8, 16, 32, or 64-bit.  Executing inline assembly from C is straightforward and often required.  Furthermore, handling time-constraints such as real-time execution on adjacent processors is easier to deal with in C and executing syscalls, low-level C functions, and userspace library functions, is often more efficient.  Timing analysis is often a key consideration when testing firmware, and executing compiled C code on a time-sliced OS, such as Linux, is already constrained.

To read tests based on a custom grammar, a scanner and parser in C can be used. Lex is ideal for building a computationally efficient lexical analyzer that outputs a sequence of tokens. For this case, the tokens comprise the function signatures and any associated function metadata such as expected execution time. Creating a context-free grammar and generating the associated syntax tree from the lexical input is straightforward.   Dynamic arrays of function pointers can then be allocated at run-time, and code within external object files or libraries can be executed in parallel using multiple processes or threads. The symbol table information from those files can be stored in multi-dimensional arrays. While C is a statically typed language, the above design can be used for executing generic, variadic functions at run-time from tokenized input, with constant time lookup, minimal overhead, and specific run-time expectations (stack return value, execution time, count, etc.).

At a high level, lists of pointers to type-independent, variadic functions and their associated parameters can be stored within multi-dimensional arrays.  The following C code uses arrays of function pointers to execute functions via their addresses.  The code uses list management functions from the Linux kernel which I ported to userspace.

https://github.com/brhinton/bcn