Alrighty, so today first and foremost, hey Sal, hey, Genevieve, hi, hey Fon, hey Heather, and everybody else watching on YouTube. Thank you for your patience, everybody on the call log. And you know what? You guys are so amazing. I did not lose not one of you even though I didn't sign on on time. Okay, couple really quick things before I get to callers and answering questions. The first thing done, done, done. I actually remembered to bring one of my books to the show today. Here it is. What if a transformational, a transformational guide. This is a book, I love this book. Like I'll still, I'll go through it and I'll ask these questions of myself because you guys, I channel my books so I have seven books that I have channeled and authored and published and all of them are channeled. There's one, one poem in one book I can't even get through. It's my latest book called channel messages from like whispers from above or something like that. Yeah, I know, I should know the titles of my book. It's the last book I published. And there's a poem in there that I cannot get through. Like by the third line, I start crying and I can't read the rest of it. But there's also a poem in there from loved ones above and how they communicate with you. Now you really wanna know the name of it, right? It's my second channeled messages book. Okay, so this book is a guide. Obviously it says so right there. So it must be, it just must be, right? Cause it's in writing, Jesus, Moses and Mary. Okay, so this book was channeled through me to help you see the world and your life and what happens in your life in a different way. So if you open the book, it looks like a big book, it's not. I don't like big books. I don't, I know, I know that makes me sound exactly as I am a person who doesn't like big books. So if you open the book, there's like these questions. See, here's a question. And then there's all these empty pages. It's a book of empty pages. Okay, so the first question that I'm going today is what if who you are or how you are is how you return? That's a fair question. So if you believe in reincarnation, what if who you are now or how you are now is how you return in your next life? And I've heard this so many times where you leave off is where you begin. So the more you progress in this life, the better you come into your next life, whether it's on this plane or another plane. And as a matter of fact, and let me say that again, as a matter of fact, if we progress enough in this life, we can end up on a higher plane in our next life. Let that sink in. So maybe all the work we're doing to just be a person of love is what gets us to that next plane, the higher plane.  There's not a place called hell, but there are lower planes. Don't, don't, don't. I'm joking, cause we all do dirty. We all like, I don't care how good you are. And I believe most people intrinsically are very, very good people. We just get a little lost in sh-tuff, stuffing, the turkey stuffing, we get lost in stuff. So we end up, you know, acting and behaving out of our lostness. Yep, that's my word of the day. My word I made up of the day, lostness, we're all living in a muck of lostness, trying to get out of it. I do not believe, however, that this is a planet that punishes. I do not believe that this is a planet of, if you believe that, that's exactly what you're going to get. I, one million, trillion, billion, the amount of money Biden has given to other countries, by the way, trillion to the Middle East, not just one trillion either. He's committed by 2030 to give many trillion, ooh, 110 billion so far to Ukraine. So I believe a billion trillion. You like the way I just l-otted in, kind of like my date last, I'm kidding, oh my God. I didn't even have a date last night. I was at a total, oh my God. And there was no, no, it was a total joke. Oh, spirit is funny as fudge, aren't they? Oh, if you guys aren't laughing, that wasn't worth it, thank you, Bob. And now that song is in my head, that one that goes gas pedal, gas pedal, but they're going slide, it is in the chat, Jesus. Oh my God, my show is derailed within five minutes of starting. Okay, so you guys, really seriously, I need to say this and I need you to get this really clearly. When I make jokes like that, they're not true. Like 90% of the time, no, that one was not true.  I do believe there are planes and this earth is a plane and I believe this is a plane of creation. We came here to create and how we create is out of love. The more we do out of love and light, the higher we evolve. And when we learn to create, to totally create, spontaneously create, then we've hit it. At that point, we know that we are, we love ourselves and we are worthy and we deserve and we are working with creation to create and that's what this plane is. This is the plane of creating and we can create an unhappy existence. We can create a happy existence and the idea is to get to the point where we know like we know like we know it is not out of our control. It's all in our control. Okay, so again, done done done done, what if? Okay, I did actually in the chat section I put a link to my author page on Amazon. You can get my books on Amazon. And if you so do so choose. And if you get my book, channeled messages, the second one, not the first one, the second one and you can figure out the poem that makes me cry. I will admit it, but I won't tell you what poem it is but you, if you ask me, I'll tell you. And the reason, oh, I do know the name of it. That poem gets me every single time. Like I had so much difficulty channeling that poem and I had even more difficulty like editing it. I didn't wanna put it in there and I had to, I think it's called ever, E-V-E-R, ever. Yeah, it's called ever. And it is, so you don't have to guess, there it is. And it is the, like I cannot get through that poem. Hopefully someday I will. Hopefully someday I'll be able to like get through it without breaking down. Okay, all right, all right, all right. All right, all right. Oh, Kiddoki, there were some things here I wanted to say that I have to say, so I'm gonna say them. This Wednesday, I'm going live on TikTok for the first time and I'm doing it on my live.beauty.reviews page and I'm having like this Metaizba procedure done. It should be entertaining if nothing else but here's the deal. I cannot do Botox, I'm allergic to Botox and I don't care if other people do it, do what, do, there is no judgment except for within ourselves. So whatever makes you happy, that's within your means, do it if that's what makes you happy. And so I found an esthetician that can do some work and it's not like artificial stuff. So I'm going in Wednesday and I'm gonna let y'all see the procedure, I'm gonna let y'all see me without makeup, oh my God, that's the scary part. And then we're going to do this little procedure that should not take horribly long and we're doing it live. So anybody who wants to ask questions and comment on it, you can comment on it. She's gonna have an assistant there that will be able to answer all of your questions and hopefully you won't hear me cry. Nobody will hear me cry, I wouldn't cry much. Okay, anyway, so please do join me for that. I'm gonna go to the very first caller now who is 301. Please tell me what's your name, where are you calling from and if you have me on speakerphone, take the call. 301. Speakerphone, please tell me this is Diamond. I'm calling from Washington DC, can you hear me? I can love, can you hear me? Yes ma'am, I can hear you now. Beautiful, how can I help you love? You can give me a bit of direction. I'm one currently for about six months now and the chemistry is strongly there. I'm sure you've had this question before but his actions are not lining up with what he tells me. So I'm hoping to see if he can tell me what are his true intentions regarding me. How honest do you want me to be and how funny can I be? Like is this a really sensitive subject?  I mean, I need to know how sensitive do you need me to be on this? You can give it to me straight, I don't like sugarcoating at all, his name is Carrie by the way. So you can pick up on his energy. Thank you, I got his energy full force from the beginning. He is a, okay, I'm just gonna say it. And if this offends anybody, this is an 18 and over adult show. So hey, here we go, even though it is on TV so I do have to watch my mouth a little bit. Um, he doesn't, he is, he is an, every time I go to say the words, it won't even come out my mouth, but I'm just gonna do it cause I don't, I don't wanna, I'm trying to be, I'm trying to be gentle and they're trying to be, so we're just gonna be blatant. He is not, he's, he's, he's, he's along for the ride. He is not looking for something.  Just because somebody likes you or they could even love you or love what you do for them or how you do certain things because you know us girls, we got skills. I'm just saying we do not, not all, just like not all drumsticks are the same, not all these are the same and some of us girls, we, we know what we're doing and we enjoy it.  Like what? Who have you been with? Like, how do you not enjoy that? How do you not like, you know that? Like, I don't, I don't get it, but here's the thing. He is not in it to win it. He is, he, he doesn't want you to be gone, but he doesn't, he's not looking at a long-term committed situation. And it's not only you, he wouldn't be looking for one with any one. I'm going to tell you that words, words are, are very easy for some people but actions will tell you the truth. And I'm going to also tell you that a man who is very committed to you will behave in a way that shows you that he is committed to you. He is as interested in what's going on in your life and in your mind as he is as what's going on in your panties, pantolumes. He is as interested in talking about your future and what your goals are as he is sexy talk. And he's actually more interested in what's going on in your life and your future and what your goals are than he is sexy talk because he knows that's just going to be a given. And he is trying to make plans with you for the future, not like, hey, Saturday night, it's more like a, I have this thing coming up, would you be interested? And it's all done in a very healthy and genuine way. It's done in an extremely healthy and genuine way. Now that doesn't mean the sexy time is not good or on point because believe me, if you're already into the guy and you're bringing full-on sexy time and they're only, they're not thinking about a future, their sexy time isn't even all in, right? And when two people- We haven't had sex. Oh, good. We haven't had any sex. Good. Good. Which is why I'm curious why he's still around after six months. Good. I'm going to tell you for whatever, I'm happy you haven't had sexy time. I'm happy you haven't had sex. I don't know why I keep calling it sexy time. What I'm going to tell you is if, okay, here's the thing. And again, and sometimes when I answer a question, nine times out of 10, when I'm answering a question, it's for you, but it's for a little broader for everybody listening also.  They're talking to you about a future. Their topic of conversation is about where the two of you are going in the future. Now, if his actions are not lining up with that, that's all you need to know. Like either this guy cannot pull through on his actions, in which case you don't want him anyway, because that's not only in relationship, that's every area of his life, or he is not thinking in that direction with you. The everything I'm getting is he's not ready for what, and it doesn't matter why somebody isn't ready for a relationship. Okay, it's just they're not ready. That's just what it is. For whatever reason, he's not ready for this with you. And I think the worst thing somebody can do is waste somebody else's time stringing them along until they are ready or letting them believe something's gonna go on until, or if they are ready. I believe this person has a lot of other things going on in his life or their life. It doesn't mean other people, it could be personal stuff, but it could be other people too. This person just isn't ready for what you want. He isn't ready for what you want with you. It doesn't matter if he would be with somebody else. He is not, as of this moment, he's not going to change his actions. His actions are going to be those that they are. And I hear the word front, F-R-O-N-T, there's a front going on with this person.  So what I'm gonna say to you is, if you wanna friend-zone him, friend-zone him without any expectation of the future, and if he asks, I have a very, very honest, honest conversation about what you want as far as what a relationship should look like to you, but know that just because you tell somebody that they can change momentarily, chances are he's showing you his true patterns and that's what you need to look at who he is now, not who he can be because you said something to him. Does that make sense to you? Okay. So what- Yeah, it does make sense. Yeah, go ahead, love. And what the front or the mask is, I mean, we've both spent a lot of time, he always treats me well, he asks me out, and I kinda get the sense that this is just stalling, stalling, stalling. So the mask, that word has come up to me before. What is the front? Does it matter? Let me ask you this. Well, I guess I want to know. Yeah, I know, I know. Listen, I've been in situations where I'm like, why the heck is this this? In the end, that keeps us hooked. And if we know what the thing is, we think I can work through it or I can fix it. And the bottom line, the truth of the matter is, no. He's showing you who he is. It doesn't matter if he's, and I'm not being psychic right now, I'm just saying things right now. It doesn't matter if it's because he has a possessive mother, it doesn't matter if he's on the down low, it doesn't matter if he's got another woman he's trying to get on mesh from, it doesn't matter if he doesn't have enough money, it doesn't matter if he's afraid of commitment. It doesn't, none of those things matter. Whatever the mask is, it doesn't matter. The fact that he showed up with one is the fact that he will always be able to put one on at any moment and keep wearing it or take it off for a couple minutes and put it back on, it doesn't matter. How a person shows up in your life is how they are. If he has things to work through, you let that boy go. When he becomes a man, he can come back and he can show you that. When he becomes, and when I say boy and man, I mean, right now he's not ready for a full on man commitment. He's kind of dating like a prepubescent teenager or a pubescent teenager, whatever. I don't know when boys go through puberty anymore. He's sleeping around, basically, which is saying, he's sleeping around. I'm not gonna go so far as to say that. I am gonna say he has something else going on and I do feel like whatever it is, he's not ready to let it go. So if he, here's the thing with us women and it's so hard for us to get this. It's so hard because we have hope and we're fixers and nurturers. We kind of feel like if we know what the problem is, we can fix the problem. Just tell me what's going on so I can fix it. The fact that we feel that way allows men, allows partners, and it goes both ways. Some men are like this too, so men please don't think I'm always attacking men because it does go both ways. I'm talking to a woman and her situation, so I'm gonna reference it in this way. The fact that we think we can fix them allows them to do more shady stuff and behave and not show up on their top level. If somebody can't show up fully ready and prepared to move forward with you in a full on relationship, if that's what you're looking for, then they are not the person for you. So either you're fooling yourself saying that you want a full on relationship and this is helping you be in denial about that or you're hoping you can fix this guy and whatever his thing is. And the truth of the matter is if you want a full on relationship with somebody who can show up in every way and be accountable with their actions, this is not the man for you. This is not the person for you. It is not the person for you because this person has already shown you, they cannot show up and act in the way they need to for you, for you to have a healthy, productive, loving relationship with them. Now it doesn't matter what anybody else in the effing world wants. What matters in your world? And I don't care, every woman wants different things in a relationship. What matters in your world is what you personally want in a relationship. And yes, there is somebody out there that is going to full on give that to you. They're going to show up as that person, you're not going to need to fix them as that person or into that person. They are going to have the actions backing up their words. They are going to behave in the way that you would have your expectations. But as people in relationships, we have dropped our expectations so low that we think, well, if I just stick with this, eventually we will get there. And the longer we stick with it and the more hope we have, the more difficult it is to kind of walk away because we feel like we've invested. But if we're investing in junk or penny stock, not that the person is junk or penny, I don't know, haven't met him, just saying, we're hoping for that payoff. But some stocks just completely delete or dilute or they never go up in value. And if you have yourself a penny stock that isn't going up in value because they're not changing who they are on their own. And I'm going to tell you this too, for the first three to six months, their ambassador shows up and that's when they're on their best behavior. After that, their true self shows up. So if it's spent six months, you may not even, this is the best he is because guys show up as the best and women to show up as the best that they are. They show up as the best that they are and they go from there. I'm going to tell you, it is in your best interest, forget, don't try to figure out another person's behavior, good, bad or indifferent because inside their mind, we can never figure out what's going on inside their mind. Okay, we can never know what happened or why. And that might just be none of our business because it just takes us further into the spider web that we can't get out of. And what I'm telling you right here right now, this person isn't showing up as who you need or who you want.   But as long as you're trying to fix what you have, you will never get what you want. Never ever will you get what you want if you're trying to make what you have what you want. Because what you have, God created that the way it is and that is not what you, that is not your thing then. You have to let that go to somebody else who thinks that's perfect and you move on and you say, okay, thank you for the test. I passed, cause I said pass on this. If you had all the money in the world and you really wanted up, I'm just gonna up a Bentley. And you wanted a Bentley. You wouldn't go to the car dealership and get a Mustang. Right? No, you wouldn't because you're like, no, I want a Bentley. I have, I'm not paying Bentley money for a mother fridge in Mustang. And there's nothing wrong with Mustang for don't come at me and Mustangs are cute now. Okay. So this is not, that's not where I'm going here.  Like, however I can say that better. I don't know.  Give me my Bentley. I want all the extra everything. Cause I have Bentley money. Yeah. And they roll up in a Mustang.  No, you take that Mustang.  That is not what I asked for. Now, in the world of dating, our energy and our love is our currency. Stop, stop, stop having Bentley love and settling for pentals. And thank you to everybody who participates live, whether it's the call in or on YouTube. I'm so grateful for each and every one of you and love each and every one of you so very, very much until Wednesday have an amazing rest of the day. Thanks. Bye bye.


Hey everyone, welcome back for more XOZeroes content, Happy Holidays and Merry Christmas to everyone. Today we'll be discussing the Quantum Raid Guide but before that if you want to see more XOZeroes content please hit the subscribe button down below. Hey guys, I was not able to play the Quantum Raid event for Halloween but I'm here now for Christmas so let's start this guide. So to play this event slash content you need Levistones for this game so it's actually here and you will need Levistones and this one will generate you Levistones aside from that you can also get Levistones from your airship squadron donation using your wing tokens and also you can use alliance points in your door to creation so these will actually fuel your what do you call this your progress in the game so why we do the Quantum Raid this is just very simple because we are actually after the the awards or the gifts once we finish them so here are a couple of rewards that actually are very good and you need the progress in the game especially this one the faith core recruit ticket and also you will also be able to if you are a free to play player you also be getting rewards for the free pass above and the premium pass below for those who paid for the Quantum Raid pass okay so how do you progress in this game you'll be starting off with actually these heroes they're the only ones with a level one on them at the start of the game as you progress you should be able to level up other heroes so if you can look at my roster I've had actually several several heroes already leveled up so I'll I'll try to suggest so these these are the the heroes that I'm actually bringing in right now for my team I'm no longer using the the what do you call this the the default heroes that were given to me because most of these heroes have better skills especially for the generals because they have a level 20 unique skill so I'm actually trying to prioritize generals for my team and I'll discuss later the different jobs per front mid and back but number one to take note of is get more heroes as quick as you can so for you to get more heroes you have to attain these tones up here so fire frost nature machine darkness and light for you to attain them you have to actually play through the game and let's let's start with one content so that you can see the gameplay at least so I'm already at hard and I'm at stage eight so for you to be able to to get these tones you should be able to clear these stages as you progress to the game as you progress on the harder stages from easy hard and so on rewards are actually getting better so again once you start the game it's it's a bit it would be a bit tedious because you don't have that that much of a heroes or that that that many heroes in your roster so try to grind the game out and aside from the stages or the difficulty like hard stage eight you can actually purchase those tones at the shop later so let's finish this content first then we proceed to the shop also I mentioned before there are there are several hero classifications you have your your mid back and I think front so we'll discuss that once this is done also try to consider bringing various elements to your teams because if you concentrate on just one element I don't think you'll you'll be leveling them up as fast as you can because you'll be sharing your resources with multiple heroes at most have two heroes of the same element so for my team I think I have two dark I have two frost I have two machine and two light and what else sorry I can see only one light two too far and one nature so try to share try to share elements or colors of each element um as few as possible so that they can be level up faster so if you can see here I have here a far element stone I have three two and so on and this one is the raid raid quantum raid coupon that you actually um spend later and this is the experience point as well so for the experience it goes here to this one the quantum raid pass and for the coupon you can spend it here and the shop do not do not spend um um when you are starting this game or you you're starting at probably easy and the stages one to eight do not actually start in getting the wards up down here um always prioritize the ones on top because these will actually hasten or make your progress faster in the game so that is actually my best tip for you guys do not be greedy and and get those items as early as possible because you'll be getting them anyway once you progress faster in the game so let's go back to managing the team so you have front mid and back for front you have night so night is decreases all um increases defense of all allies which I like so I have one um I also have one um paladin for invincibility for 3.5 seconds take note as you level them up the the stats go even higher and I have a gargant so a loom has provoked for five seconds a decrease attack by 20% so those are your front um I recommend at least one of each or a mix of you can actually take um the what do you call this the paladin out and switch it for a night or a gargant preferably a night for your mid you have a warrior who stuns preferably you have another warrior or actually the assassin is is is not really helpful based on the gameplay that I had already so I'm trying to replace um a weak and z on I also had a ranger the work is good and actually Rachel is good so I'm currently using for mid um um I'm taking out a weak and z on and putting in Rachel because I'm using two warriors at this point because they deal much bigger damage and for the back part you have your trickster which is increases all allies attack speed your cleric is basically your healer and your enchanter is decreases attack speed of the enemy so again try to put at least a group of four so that you can mix and match your your heroes so I have another healer here um for Lepin to compliment to compliment Anastasia if I need more healers in this team so because because normally what I do is um usually I mix and match depending if I'm if I'm fighting the boss at stage nine or I'm clearing um mobs at stages one to eight so um those are the possible heroes that you can actually use in your team um basically right now I'm practically contented with this one with the lineup that that I've chosen um I'm actually just leveling them up because I can't clear yet stage nine once you're starting you actually need to grind out stages one to four um depending on which do you want to prefer but from there once you gain the momentum once you gain heroes more heroes you'll be able to progress through the stage so before you level up anybody here from front mid and back try to um complete your roster first then level them up based on based on the stones that you get because every time you every time you play for example a stage it's usually a random random gift or random prices or random stones that are being given out when choosing heroes it would really depend on what stones you really get or if you want to control the stones that you get you actually get them in the shop so it's also important that you unlock um um all the heroes um skills up to level four before you level them up further so if you have nine heroes already um unlock their their skills up to level four each of them before going further we go before you go further five and up and also take note um it's important that you try to level up um the your your generals to up to level 20 if you can because they have unique skills but based on my progress actually I I don't think I don't think I will if I go past hard I don't think it would be um uh essential that you go past the next that the next stage after hard because I think you'd be able to clear all of the prices even after hard um I'm not sure what the what what the next stage is um but I'm sure that after hard that's the you know the preferred um the preferred stage that you will have to grind out all of the prices for the quantum rate also take note of this one the the what you call this the the hero um affinity and weakness or probably the strength so if you carry if you carry nature um weakness is fire but nature is strong against machine and for dark and dark and light they're they're against each other so they cancel out each other so if you can see again most of uh most of the gems are given to me at random so build your team based on what is being given to you okay I think the next stage for yeah I think it's the the next stage would be ideal to stay in very hard after that um if you want to grind further you can actually go further than very hard to extreme okay so so that's it for me guys um so far I'm actually I'm actually good with the game um the game mode it's not really that exciting anyway um it's I I'm actually just grinding it because of the rewards because of the freebies that I'll be getting and some something new in terms of what to do okay so if you have any more questions um write it down below in the comment section or yeah if you have comments so anyway you all stay safe this is the warden and I'm out


I'm very happy to open this conference and talk to you about some of the recent work that my group and I have been doing now in the area of error correction. Some of the people that actually did this work are here. Peter Johnson is there, Jonathan Romero, Jonny Olson, Judon Kau is in California right now and anyway, so please feel free to ask them questions. I actually wanted to begin in a similar tone as Jay actually, I didn't see his lights before but I think it's very important to think about what to do with a 50 to 100 qubit quantum computer in the context that he mentioned so I'm not gonna elaborate on this idea that we want to think about not only the number of qubits but also how many gates which is roughly a thousand nowadays you can do as depth and that defines what IBM calls a quantum volume. I'm showing you here a picture of the IBM machine because we are at IBM and of course there's machines built by startup companies like Rigeri, there's machines built by Intel, there's machines built by Google, etc.  I mean there's something common in a lot of the algorithms that we're talking about as early applications for this technology and it is because we really don't have a lot of circuit debt that we need to think about this heuristic type of algorithms that might or might not have an advantage but hopefully we'll do something interesting. So Jared McLean which is here somewhere is the architect of this, there he is, the variational quantum eigen solver which became a very popular technology for trying to find ground states. This is a picture just to bury it a little bit, a picture of the Google experiment doing the hydrogen molecule. We just saw earlier the IBM experiment and this paper is actually not this, I apologize, this is a paper for the first quantum optics experiment and I remember we were already talking about this in the 2013 conference here so this is kind of like things are moving pretty quickly. Eddie Farge also present here somewhere introduce a very powerful or heuristic algorithm, this quantum adiabatic optimization algorithm and I think it's powerful in the sense that it's very compact and will potentially show interesting results as these machines become having larger and larger quantum volume as it's called. We recently introduced a technique that we like a lot, Jonathan is here as well, the quantum auto encoder which is a way of using this Chaluse circuit quantum computers to compress quantum states. So so many people have been saying you know there are problems in quantum machine learning when you actually try to feed classical data on quantum computers. This algorithm is designed more for quantum data. If you have quantum data we hope there is some sparsity in terms of its representation. For example it's not optimally represented in the quantum computer and by using this encoding decoding circuit you're able to compress the quantum information and therefore generalize from it by moving around in this so-called latent space. So the talk is not about that but it is true that this inspired us for this error correction scheme I've been telling you about. Even in the paper we were thinking about how can we use these tools for error correction because it has similarities. And finally we used to use another paper that we're very excited about, you don't count it's not here. Also we know Giacomo Gurecci. We call it the quantum neuron. It's a little bit longer term because it requires a lot of measurements and repeated until success. But it is a quantum machine learning algorithm that has this little unit called the neuron that reverts to the classical neuron of classical machine learning. So it has very interesting properties. It can be trained in parallel and you know because it is it can reverts back to the classical one. It has a limiting which is the classical one. You can actually borrow technology from from classical machine learning. So in these early machines probably we'll be able to do a very very simple experiment and of course we don't expect this to be beating Google at classifying images of cats or something like that. So anyway I believe this is kind of like a sampling of some algorithms as many many other algorithms that use this a variational approach to quantum computing and in all of them you train quantum circuits. That's kind of the main goal of these algorithms. You don't know what are the right parameters for any of these systems. This is a neural network. This is optimization etc. So you're moving around the Hamiltonian sorry the gates the gate parameters and trying to for example minimize energy in the case of the variational elegant solver, maximizing the code size in the max code problem, optimizing the compression of a quantum state or minimizing a loss function for a machine learning problem. So all of them have this joint ideas. So on the other hand many people here including us as well and thinking also what was going to happen in the long term right there's going to be this transition into a recorrected algorithms that we all know and love. For example Hamiltonian simulation beautiful paper recently by Andrew Childs and his co-workers on what would be like realistic limits of when we can beat a classical computer. Of course short factoring algorithm Grover search quantum machine learning with classical data you know all these quantum RAM algorithms. Adam Harrow is also here with his algorithm with set Lloyd and Hasidim for solving linear equations and all of these require full-blown quantum error correction and therefore we have to be somewhere in between and I think error mitigation the word that Jay mentioned is an important area. So let's just begin by actually just defining what is quantum error correction and then I will continue talking about the quantum variational error corrector algorithm that we that we propose. So this line represents a quantum register or qubit in this case let's just mine it's a qubit you have a noise channel we're gonna call it n so the qubit is not perfect it's not in a perfect environment so this noise will actually of course denigrate the quality of the quantum state and by these little triangles in the left and the right where the defining is just this average fidelity of the channel right of starting in a quantum state and leaving in you know ending in another quantum state so this is you know what happens to the channel what happens to the to the quantum information after it it's affected by the noise. So the bet in quantum error correction is the fact that you know if I actually add more complexity to the problem in other words I add a set of ancilla qubits that of course presumably undergo a very similar if not the same noise process I want to point out something important to my talk when Jay showed you the picture of his 20 qubit device you notice that every qubit had a different t1 and t2 and different parameters right this is gonna be important to us because you know the traditional error correction thinking is what can I assume an error model and start playing with it whereas your machine will have crappier qubits and others and all machines do that right I mean Alejandro Perdomo has a beautiful paper on characterizing the d-wave machine in the same way like some qubits are better than others so the way our correction works then you have some sort of encoding v circuit and some sort of decoding type of operation that actually will allow you in principle to distribute the quantum information over these qubits and quote-unquote fight the noise and hopefully improve the fidelity of of of your preservation of your quantum state so the bet is that actually adding all this complexity will allow you to actually have a better performance than just a raw qubit and that's kind of the philosophy of our correction a very long very very long-standing idea obviously so what are the prospects for state-of-the-art error correction so that's the first part that we're gonna just review I will say one of the state-of-the-art algorithms perhaps one of the spears you that lot in industry at the moment is a so-called surface code it has many interesting features is realizing a two-dimensional architecture it has local syndrome measurements and people have demonstrated gate operations below threshold so we're on the route in principle to actually building a machine in the surface code and again many of the industrial players are focusing on building machines that realize an error correction scheme it could be another one and the reason this is so attractive is because it's like an instruction manual you know if you if you follow the instructions of how to build a machine that does the surface code you might eventually end on the other side of the of the of the journey with an error corrected machine so so now let's just look at Google's 49 qubit processor as a function of little blue circles in a slide okay so it looks very daunting and very exciting to have a machine of this size so now if you actually think about mapping a logical qubit now a qubit with realistic parameters of the surface code in in a bunch of qubits we're going to just put to scale Google's 49 qubit processor with all the qubits you need to map a single logical qubit and I'm very optimistic as always I believe we're gonna get there and I think this conference is well what are we doing between we build this monster quantum memory the last forever and the machines that we have today so is there a hopeful alternative that's what my group and I were thinking about this is a very old question you know here is loin loin loin Nielsen and Chuang you know in the case of the laboratory what works with a specific apparatus with a particular domain and quantum noise process right and in that p.r.a. paper they also say that the error correcting codes that are kind of idealized do not take advantage of specific knowledge of the particulars of your device and therefore might be suboptimal so this is a question that we're trying to look at so how can you gain specific knowledge of the noise to actually do a better a better performance so this is of course our pictorial way of representing the coherence in a single qubit we have here the density operator and the T2 process phase damping what it does is basically kills the coherences in the device the T1 process amplitude damping is relaxation back to the ground state of the device right so these are kind of the two physical processes one is kind of like jiggling noise the defaces and the other one is just basically relaxation to a ground state that actually kind of define the noise processes that can happen to the quantum state a formal way of writing them is of course discuss operators they are just green here I want to you to remember that they are this coherent mixing of these Pauli operators x plus I y I minus C I minus C this is gonna be important later okay for the purposes of our discussion but basically here we have the noise processes and notice that the T1 and T2 obviously can be just mixed into this gamma and lambda parameters for this for this you know map that the coherence just is very simple model so what is the quality of error correction for this process let's think about a raw qubit with you know typical parameters we see as we as we wait you know and here are the parameters the T2 of 60 microseconds you actually look at the average fidelity coming down for this very simple one qubit experiment and you hope that something like the five qubit code will actually do better at least in certain parameter regimes right so this is a encode wait and then decode type of scheme okay very simple so the five qubit code is gonna have these logical operators here are all this like transfer CCCC and xxxx that actually perform logical computation and the stabilizer operators that actually allow you to detect if there were errors in the qubits you know so this is the very traditional classic scheme that we are comparing against and if you actually look at this five qubit code now here in in orange or light orange you can see that many things first of all this thing is designed for actually you know very very short times looks like you get very very good fidelity after a while after a lot of waiting time then it's better all you're better off by just running your your rock on one computer and not doing this error correction I will dare to say that we are in the parameter regime of quantum devices that we're somewhere around here where it's not obvious that it makes sense even sense to do this error correction right and as we build better and better devices and get better very coherences then in the next three or four to five years this variation algorithms will be mixed with these error correction schemes whatever mitigation schemes that we're talking about so what is the optimal scheme you can go back to early papers by Fletcher short and zine and kosut and lidar where the question is well can I find the optimal the ultimate the optimal map that actually corrects for errors right given a particular noise model okay so the way it works is you want to maximize the average fidelity and then you have decent coding and decoding so you optimize first the the the for example in this particular case the decoding given giving the coding fixed now you optimize the coding given the decoding fixed and then numerically just go ahead and you know try to converge to the best possible encoding and decoding schemes and then you declare victory at a certain point of course therefore the plot that I'm showing you here might not be completely optimal this we did it numerically and we stopped at a certain point but it shows you kind of like a like a good practical upper bound of what you could do if you were able to actually invert this map and look at error correction with that perfect type of encoding decoding type of architecture and you can see that it was very very similar to the five qubit code at short times and then you know it starts outperforming especially longer waiting times which is something that we would like to have in this early quantum devices you know we want to kind of do the least possible error correction on the most algorithm right we don't have too many gates so we argue that this approach is very elegant but it's not practical first of all you need a noise model and you know for getting that noise model you need to do benchmarking right you need to know a lot about your system will it be nice that you benchmark the system at the same time you're learning about how to do error correction and the algorithm ultimately you want to do everything together so you need to require a noise model and you know the optimization of this in general that map will scale exponentially with a number of qubits to actually encode a general type of encoding decoding scheme so that's another broad block for this algorithm and again the other problem is that you will need to do a compiler to actually try to get that map which anyway we know that parameters for it will scale exponentially so we know the circuit is going to be very crappy and therefore we have to have something in the middle this is going to be a great idea but it's not going to be practical so we introduce Q vector so Q vector is an algorithm that tries to fight all of these things because we have first thing is we don't we try to start with a model free architecture we just say okay there's no noise in the machine let's learn it we want to have an efficient evaluation of the of the of the optimization with therefore we want to have like compact circuits and we make an ansatz like in the variation of the ligand solver make a circuit ansatz for error correction so you might argue about our circuit ansatz I bet you many other people we have better ansatz there but now this is a game everybody can propose what is their favorite circuit architecture for encoding and decoding the error correction and we can all learn from each other what is a good way of encoding the other thing that is not here but it's also important is that this might be very problem specific as well if your problem is encoding in a particular subspace you might be better off you know so there's some other things that could happen here so Q vector so let's just animate like this so you remember the name of it so again it's a very simple encoding that looks similar you encode go through the noise process and decode and our objective again in the in the in the variational type of context is to maximize average fidelity so how does it bypass the roadblocks the first thing is okay very simple observation noise models itself exactly right so if noise is there well you might as well just not use a noise model just look at the noise directly so we optimize on the hardware device directly and the idea is to figure out how to do it so this idea of to design okay that has been around for a while uses basically Clifford gates which is shown to be sufficient to actually estimate the fidelity this is related to a lot of work I was just in the boss hearing to Joe Emerson talk to Adam Harrow they were talking this is based on work from him and others a lot of work in literature about this type of things but you know you basically you basically measure just zero and one with these two design type of sampling scheme and then you basically count the number of zero outcomes and that will give you the average fidelity as you increase the number of sampling okay so that's basically the way we do it so we we basically encode these gates and then we do the two samples encode decode and measure and variationally optimize and maximize that fidelity the other things then we define circuits that more or less look like this they have gates that allow you to encode and decode the quantum information so the way this looks like it's very similar to the variational eigen solver and other algorithms like this or the QAO you have a classical optimizer these parameters vectors p and q are the parameter vectors of these circuits and therefore you basically provide the fidelity change the p and q and the classical optimizer is driving the quantum computer something interesting that I heard from Arturo Mezacapo at the conference recently is that for doing variational eigen solver at IBM just even transferring back and forth information between the classical computer and the quantum computer takes a lot of time so a lot of these different things have been people have been discussing okay let's put a very fast classical computer next to the quantum computer because a lot of these near-term algorithms will require a lot of back and forth so that's pretty exciting this will be the same case here because you need to measure quickly optimize and so on so the entire scheme is summarizing this slide hopefully I've been going slow enough unlike me that I usually don't explain things slow to show you how it works then you sample from the to design initialize apply the map measure optimize the average fidelity that's basically what the quantum computer is doing okay and then and again these encoded circuits are actually predefined and you can assign your favorite so of course for the end of this talk let's how does this look like is this like a cool thing to do or is this just hopeless so just to remind you this is a single qubit error the five qubit code and by convex optimization again kind of like a benchmark to look towards but not practical let's sit down a four here this for waiting time okay just because we want to have the longest waiting time possible to apply this algorithm I'm gonna apply Q vector there and this is what we get makes a lot of sense it's not perfect it's not gonna get as good as say cost of the Nidar's type of general scheme we don't have enough parameters to get there but we do better than both the single qubit and the five qubit code and you can optimize there and then extrapolate you know you see it everywhere else and you get this kind of linear behavior like so but it's not next fully linear Peter Peter Johnson and I were putting a little envelope in our PowerPoint slide to see how linear it was we have to characterize it better but you notice that of course we optimize here is not gonna be optimal over here where currently starting to do experiments to try to understand how we optimize it the different waiting periods how does this look like but I had to confess it's very hard to optimize these things too so you have to know that the classical optimization area for this is actually a big a big big effort and Hanna sheen one of my students here is working with Jonathan in a software package that hopefully we can release and help people see what's the best way of optimizing these parameters so I think we all as a community should learn a lot about optimizers so now why does it outperform the five qubit code that's the last topic I'm gonna mention okay do you remember I kind of emphasized that these noise processes are these coherent combinations of these Pauli operators so this K2 is X plus IY for example and I be an approximation that is used not only to design but also to simulate errors in computers makes a lot of sense and my group and I actually have employed it to simulate for example how quantum chemistry degrades you know in a computer it's just say well you know we're going to a certain probability flip cubits X Y and Z this is called the Pauli tooling approximation easy to simulate easy to analyze mathematically etc but it's not connected in some sense directly to the physical process that you are expecting the relaxation and the facing okay so there is coherence what I'm called in this process is and here you have this incoherent noise process so let's look at how the models fair the exact noise model and the five qubit code will give you 8.9 and in the power to the approximation it will be the same again because it's designed to fit this type of error model of the Pauli tool approximation okay the numerically optimized does better this is the one that constantly that I say optimizing the map and then if we don't allow it to have coherence this if we allow it to kind of just live in the context of the Pauli tool approximation it does worse but you know it still upperforms the five qubit code because it's optimal and finally Q vector in the exact noise model performs a point 912 and in the power to the approximation it makes sense that we're not as optimized as the five qubit code okay but what you want to look at is actually this number here okay because we all perform the regular codes and you know we are somewhere in between them and the numerically optimized so that's kind of like the message so we say we're exploiting the part the public coherence because we are doing better than the the five qubit code so it's a way of explaining why this is better than than then perhaps just using a raw code and I think as we learn how to do things better as a community there will be much many more improvements on this quantum vector by no means of if this is gonna be the last word on the subject so we want to now of course this was just kind of preserving quantum information how does this work with gates is our next thing right so how we preserve gate operations we want to try to do a lot of numerical experiments to try to find out what is the best circuit ansatz as compact as possible because we don't want to waste gates and obviously we want to work with any maybe remotely over the internet or with a lot of our partners and friends and the different places to actually perform this on existing hardware I think this can be done today and I think this is why this is a good topic to discuss in this conference the final thing is I'm gonna say that not only quantum hardware companies are spawning out like like mushrooms there's also quantum software companies spinning out like mushrooms and we couldn't resist to create ours okay so ours our goal in our company is to have a platform neutral neutral focus quantum software startup that is neutral we work with everybody we want to learn we want to develop algorithms for the applications that I just showed you about okay and this is kind of like I like to say companies are kind of like the CIA and my group is kind of like the like the embassy okay in this kind of Russian spy novels things kind of you know so so if you want to think about us we're currently expanding and hiring and I know everybody's expanding and hiring so our company's name after a Mexican Revolutionary Colin Miliano Zapata that brings revolution to the masses okay so this is our logo this is meant to be some sort of optimization landscape and again basically Johnny Jonathan and Peter are proud members of Zapata Anders here as well so so talk to us about Zapata and with that that's the email and with that thank you for your time and this is a picture of my group in the excited state before it relaxes to the ground state and with that I think I have some time for questions thank you okay some questions for a lot yes I understood that you were looking at essentially a memory channel and optimizing the average fidelity of that channel have you looked at how your optimizer performs when there's noise on the gates used to perform the algorithm itself yes that's something that we're looking at and we inspired by your work on that it's of course it's a weak point of this algorithm like the gates themselves for example for a for example even for a 2D sign will not be perfect and yes we're looking into that and you know learning from what you have done in the past as well yeah any more questions I see a question there um how would you sorry yeah how would it be possible to build a like if you go to a large and larger system suddenly you need a decoder to interpret the result of what you see for your qubit would it be possible to use this variational method to build something like this or can you repeat your question sorry sorry it would it be possible to use this variational method to build a decoder for a larger a larger quantum error correcting code because once you get to a large and larger system then you can't just I mean you know with a five qubit code I can just take the result and use a lookup table to figure out what I think the errors that occurred are but if I go to a larger system then that's not possible so yeah that's how I hope is that this thing scales up and you know of course the number of parameters in the encoder decoder that we design roast polynomially with the size of the system and yes maybe we'll get to a system large enough that that this is the only thing you can do if I understand your question okay yeah we can talk offline and also Peter the first author is here if I didn't get your question hi Alon so over here how did you run the numerics for the five qubit code you had to pick a decoding algorithm to do that but you didn't you didn't say explicitly what the process was I mean you stated you fixed the T1 and T2 times right but those were coherent errors so how did you pick the decoder for the five qubit code like what were you comparing to well we execute like textbook lab textbook type five qubit code right we just measure the stabilizers and all that stuff right Peter you were just applying Pali error correction there okay that did you did you compare to where you fix the five qubit code but you optimize just the decoder that is it's the optimal decoder using like the SDP okay so the question is when you encode and decode this way can you do logical operations fall tolerantly as well does that put more constraints on the encoding this is exactly what we're trying right now this is I mean we first wrote the paper just like encoding and decoding but we hope that you encode carry out look logical operations and optimize everything together will be probably something that will work but that's what we're doing numerically but we're having a side step because we're rewriting our code to have a much better optimizer before we do a lot of numerics again okay thank you so Jonathan how does the circuits the parameters of the circuit scale is a number of so repeating Jonathan linear scaling actually 40 was quadratic I learned so yeah good any more questions I see so when you compared the Q vector approach to the the previous approach that does offline optimization of the encoding decoding circuit you commented that there's an exponential cost to that offline classical approach in the number of qubits and it seems like there are two exponential costs here one is in simulating the noisy dynamics on n qubits which is a subroutine for the the optimization classically and you eliminate that by just performing it on an n qubit quantum computer with you vector that's correct but there's another slowdown which is in the landscape the space of circuits that you need to optimize over which is very large and quite possibly very very complex so to be provocative what if I were to say that I'm concerned that the that your algorithm even though it drops one of those exponentials is gonna get horribly bogged down in that nasty landscape very good question we're actually where this goes in right with Peter earlier so our numerical experiments today show things like for example using swarm optimizers is like a good strategy you can move in in the space and have several tries of getting to the global minima but we also find several minima that are near optimal like so we might just land in something that is quite good enough and never get to the optimal optimal optimal one but you know we we satisfied with that that's our current understanding of the landscape as we're exploring it in a few qubits like correctly so I mean if you want try to do it numerically with 20 30 qubits and we can do that with a lot of the simulators that are out there it will be interesting to see that and even better when we have a 50 qubit device from IBM or Google or Regetti or whatever to actually try it there yeah that would be the next characterizing that in your landscape but we are aware of that luckily we have found that we land in many near-optima and I mean this is paper that's very controversial by rabbits that says that you can do that in an optimal control and so on of course that's very idealized and it's not I don't necessarily believe that resolved very much but he plots something similar to what we see that there are many minima any more questions well we do have a little time maybe I'll ask a question it's a it's a little bit going maybe to the next step if you end up with these kind of random codes how will you do logic on the we will optimize the they will optimize the circuit the coding the coding for a particular circuit for example so it's like you know and then in principle you can you can vary parameters in that circuit and see how well it does right for example we have stencils for for variation like insolvers that the parameters are very similar you're optimizing you know so that's that's we hope that this is gonna be useful that's similar to the question we had before we see local T1 T2 model right yeah if you did a depolarizing model does your cue back find the same solution as the optimum numeric optimize or do you understand for other noise models when I don't think we I don't think we have run it through it's through more sophisticated noise models but we should yeah like see collective collectively what happens the collective noise and correlated noise and things like that yeah okay let's thank a lot


This week's IonMPI brought to you by DigiKey is Intel's RealSense. That's right. Check out that cool new Intel logo. So this is the RealSense family. We actually covered RealSense LiDAR cameras like eight, nine months ago, but they came with a new product and I thought it was cool. Now, people who watch this show know that I am a total sucker for sensors and edge machine learning devices because I really like machine learning, but I also think privacy is very important. So this is an identification system, an official identification system that's completely on the edge and very affordable. So this is the module. This is the F450, not to be confused with the truck, and the F455, which is the enclosed version. Same technology, but one of them is the bare PCB and one of them is enclosed. So I played with the enclosed one because it's, of course, easier to use, but for your final product, you'd use the bare PCB. Even the enclosed one, it's got a lot of mounting holes. Look at how nice this is, a full aluminum enclosure that's easy to use. Come for the kit with a little tripod, USB cable, starting pack. So what is this? This is a depth camera. It's not a true LiDAR. It uses, I think, an infrared scatter and two cameras to do depth recognition, to do facial authentication on the edge. So you don't need to be connected to the internet. You don't need to have a cloud computing thing. Everything is stored on the device and it's really easy to use. And what I thought was really cool is they specifically talk about, I mean, some people might say this is like, it's accessibility, but it's still like recognizing faces and they don't like any kind of facial recognition. But that said, it does work on a wide range of people with different hairstyles and facial hair and glasses or prostheses and works for people of like a variety of heights. So if you're going to do a facial recognition system, I think this is the least bad, right? Because there's no cloud and it's tested to work with a wide range of human faces, which is good if you're doing that sort of thing. So this is what's inside of it. So there is a chip, the flash memory, the projector, that's probably the infrared projector, the illuminator, IR illuminator, IR LED.  There's also a secure element. This actually allows you to, you can't communicate with it over USB or you are using encrypted data packets. I won't cover that here, but it's in the SDK and the datasheet. So if you're like, I want to have everything fully encrypted, you can do that. So even if you're sniffing the connection, you wouldn't be able to see what's going on. What's neat, I think, about this is on the board itself, you have two ways of connecting. You can power it from three to five volts. This means it can be powered from USB or from a LiPo battery, a couple of nickel metal hydride batteries that are rechargeable. There's UART and USB connectivity. The USB, of course, gets you full video. But if you just want to control it on a device, like as an embedded device, you can use UART. So you can use it with a microcontroller or a microcomputer. That's what it looks like. There's a full datasheet with all the connectivity. Bottom right is that flex connector, which has like 54 pins. And all of the pins will let you basically reach in and basically get the video or get the infrared data or get like the point map from the infrared. Here you can see the projector and the LED are 850 nanometer IR, the IPEX host connector for, again, embedding it. Or if you want to use it with a computer, like if your system is using a normal desktop computer or a single board computer, just use USB. This was the FPC connector. And then all the pins. So you can look. I'm not going to go through all them. Everything is brought out. So you can integrate this very deeply into your product using a flux connector. So all that hard stuff to take care of. Here is some examples of, it says audio, but it doesn't speak. The audio will be handled separately because it doesn't have a speaker on the module. But you can have it speak. You can have, here's some of the error codes you can get, how to communicate with the user, to enroll people without a computer, and also detect faces without a computer. There's a full SDK. Intel RealSense has a GitHub repo. They have SDK and example code for a variety of use cases and different languages, which I thought was really cool. One of the things that I really liked about this is it's like really embeddable. It's all done for you. And the SDK is simple but effective. It's just all the things you want, and none of the nonsense that you don't want to deal with, so you can really quickly integrate this into your product. This is a software architecture. I think in here, I think it covers some of the encryption stuff and all the stuff that you can touch. Again, I'm not going to talk about the encryption, but you can have it be fully encrypted. And it doesn't store photos of faces. It stores only points, vectors of how it identifies the face. It also does a fuzzy learning. And so if somebody's face ages, or they're wearing glasses, or they're not, or they grew a beard, or they're not, or their hair's up or down, or they're wearing a scarf, or wearing a mask, it can still identify faces. And we'll show that in a little video. You can upload. So download it. If you want to get started quickly, with Windows, there's an application. You download it because this is new. I updated the firmware. There's a console code, so you can actually see the UART data sent back and forth, which could be really good if you are like, I want to debug my UART code and how is the application working, so you can see all the packet data being sent. I enrolled my face. Basically, you just get it nice and centered, tilt to the left, tilt to the right. It did take me a couple tries to get used to how it wants you to scan, but I think a lot of times when you're enrolling people, there's somebody there to get you enrolled, like it's a security system. And so it's not so bad, because once you know how to do it, it's very easy to tell people how to do it. But I definitely think you should enroll with somebody around to start and get used to it when you're starting to enroll your group of people. As it's enrolling, you can see the video output, and you can see it's purple because it's doing infrared and point cloud stuff. And then once you do that, it can authenticate you, so you can just say, like, detect who it is. Boom, lady detected. And as I moved around, it kind of followed me with the green box. So it did a pretty good job of detecting. And detection is very fast. It's under a second. So. Available on DigGate. Right, you can get the module or, again, like I said, the all-in-one starter kit. You're not going to be able to get anything cheaper than this. It's under $90 for a full, ready-to-go, two cameras, plus IR projector.  This one didn't make me feel bad. No IDE was installed. This cloud thing is going to be bad? No, there's no cloud thing. This is good. And what's nice is that because you can get the data over UART, the rest of your system, if it's a security system or a lock or authentication, whatever, it doesn't have to be that complicated because all the really heavy-duty computational stuff is outsourced to this module, you can run this with an Arduino. Like, this could be plugged into an Arduino if you wanted. Ape and microcontroller could communicate with this because it's all over UART. Or if you have a full computer plugged in over USB, mount it, and it's all weather-proofed and nice to go. So you have two options. Did a very good job here. Easy projects with this, too. Like, flip a relay to open up a box or something. So here's a video. Trivial to do. This is their presentation that they did at CES that was only a few months ago. This is the engineer showing, of course, there's the mask demo. It works even when you have a mask working. Nobody has to do a mask demo now. And this is interesting. They actually showed it at slow speeds. You can see at half speed what is going on. It illuminates the area with LED. It shows this guy. I don't know if he grew a beard or he pissed one on, a mustache, and glasses. It still works with headphones. I'm pretty sure that's a fake mustache. You don't think he grew it in like five minutes? No. Oh, man. Different angles, one of the things that they really focused on was even in different light, different angle, it'll still work. One of the cool things about Edge is you don't have to worry about if your internet goes down, can you not get into your apartment. But this worked really well showing that it can't be spoofed with a cell phone image, because that's some old facial recognition systems. You could do that. Pieces of paper or cell phones won't work. It's going to illuminate it. It's going to be like, no, there's a flat object in front of me.  OK, so that's OK. And that is this week's IonMPI. OK. IonMPI.